PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-25 (2189432)

Clipboard (0)
None

Related Articles

1.  Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015) 
Shay, Jerry W. | Homma, Noriko | Zhou, Ruyun | Naseer, Muhammad Imran | Chaudhary, Adeel G. | Al-Qahtani, Mohammed | Hirokawa, Nobutaka | Goudarzi, Maryam | Fornace, Albert J. | Baeesa, Saleh | Hussain, Deema | Bangash, Mohammed | Alghamdi, Fahad | Schulten, Hans-Juergen | Carracedo, Angel | Khan, Ishaq | Qashqari, Hanadi | Madkhali, Nawal | Saka, Mohamad | Saini, Kulvinder S. | Jamal, Awatif | Al-Maghrabi, Jaudah | Abuzenadah, Adel | Chaudhary, Adeel | Al Qahtani, Mohammed | Damanhouri, Ghazi | Alkhatabi, Heba | Goodeve, Anne | Crookes, Laura | Niksic, Nikolas | Beauchamp, Nicholas | Abuzenadah, Adel M. | Vaught, Jim | Budowle, Bruce | Assidi, Mourad | Buhmeida, Abdelbaset | Al-Maghrabi, Jaudah | Buhmeida, Abdelbaset | Assidi, Mourad | Merdad, Leena | Kumar, Sudhir | Miura, Sayaka | Gomez, Karen | Carracedo, Angel | Rasool, Mahmood | Rebai, Ahmed | Karim, Sajjad | Eldin, Hend F. Nour | Abusamra, Heba | Alhathli, Elham M. | Salem, Nada | Al-Qahtani, Mohammed H. | Kumar, Sudhir | Faheem, Hossam | Agarwa, Ashok | Nieschlag, Eberhard | Wistuba, Joachim | Damm, Oliver S. | Beg, Mohd A. | Abdel-Meguid, Taha A. | Mosli, Hisham A. | Bajouh, Osama S. | Abuzenadah, Adel M. | Al-Qahtani, Mohammed H. | Coskun, Serdar | Abu-Elmagd, Muhammad | Buhmeida, Abdelbaset | Dallol, Ashraf | Al-Maghrabi, Jaudah | Hakamy, Sahar | Al-Qahtani, Wejdan | Al-Harbi, Asia | Hussain, Shireen | Assidi, Mourad | Al-Qahtani, Mohammed | Abuzenadah, Adel | Ozkosem, Burak | DuBois, Rick | Messaoudi, Safia S. | Dandana, Maryam T. | Mahjoub, Touhami | Almawi, Wassim Y. | Abdalla, S. | Al-Aama, M. Nabil | Elzawahry, Asmaa | Takahashi, Tsuyoshi | Mimaki, Sachiyo | Furukawa, Eisaku | Nakatsuka, Rie | Kurosaka, Isao | Nishigaki, Takahiko | Nakamura, Hiromi | Serada, Satoshi | Naka, Tetsuji | Hirota, Seiichi | Shibata, Tatsuhiro | Tsuchihara, Katsuya | Nishida, Toshirou | Kato, Mamoru | Mehmood, Sajid | Ashraf, Naeem Mahmood | Asif, Awais | Bilal, Muhammad | Mehmood, Malik Siddique | Hussain, Aadil | Jamal, Qazi Mohammad Sajid | Siddiqui, Mughees Uddin | Alzohairy, Mohammad A. | Al Karaawi, Mohammad A. | Nedjadi, Taoufik | Al-Maghrabi, Jaudah | Assidi, Mourad | Al-Khattabi, Heba | Al-Ammari, Adel | Al-Sayyad, Ahmed | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Zitouni, Hédia | Raguema, Nozha | Ali, Marwa Ben | Malah, Wided | Lfalah, Raja | Almawi, Wassim | Mahjoub, Touhami | Elanbari, Mohammed | Ptitsyn, Andrey | Mahjoub, Sana | El Ghali, Rabeb | Achour, Bechir | Amor, Nidhal Ben | Assidi, Mourad | N’siri, Brahim | Morjani, Hamid | Nedjadi, Taoufik | Al-Ammari, Adel | Al-Sayyad, Ahmed | Salem, Nada | Azhar, Esam | Al-Maghrabi, Jaudah | Chayeb, Vera | Dendena, Maryam | Zitouni, Hedia | Zouari-Limayem, Khedija | Mahjoub, Touhami | Refaat, Bassem | Ashshi, Ahmed M. | Batwa, Sarah A. | Ramadan, Hazem | Awad, Amal | Ateya, Ahmed | El-Shemi, Adel Galal Ahmed | Ashshi, Ahmad | Basalamah, Mohammed | Na, Youjin | Yun, Chae-Ok | El-Shemi, Adel Galal Ahmed | Ashshi, Ahmad | Basalamah, Mohammed | Na, Youjin | Yun, Chae-Ok | El-Shemi, Adel Galal | Refaat, Bassem | Kensara, Osama | Abdelfattah, Amr | Dheeb, Batol Imran | Al-Halbosiy, Mohammed M. F. | Al lihabi, Rghad Kadhim | Khashman, Basim Mohammed | Laiche, Djouhri | Adeel, Chaudhary | Taoufik, Nedjadi | Al-Afghani, Hani | Łastowska, Maria | Al-Balool, Haya H. | Sheth, Harsh | Mercer, Emma | Coxhead, Jonathan M. | Redfern, Chris P. F. | Peters, Heiko | Burt, Alastair D. | Santibanez-Koref, Mauro | Bacon, Chris M. | Chesler, Louis | Rust, Alistair G. | Adams, David J. | Williamson, Daniel | Clifford, Steven C. | Jackson, Michael S. | Singh, Mala | Mansuri, Mohmmad Shoab | Jadeja, Shahnawaz D. | Patel, Hima | Marfatia, Yogesh S. | Begum, Rasheedunnisa | Mohamed, Amal M. | Kamel, Alaa K. | Helmy, Nivin A. | Hammad, Sayda A. | Kayed, Hesham F. | Shehab, Marwa I. | El Gerzawy, Assad | Ead, Maha M. | Ead, Ola M. | Mekkawy, Mona | Mazen, Innas | El-Ruby, Mona | Shahid, S. M. A. | Jamal, Qazi Mohammad Sajid | Arif, J. M. | Lohani, Mohtashim | Imen, Moumni | Leila, Chaouch | Houyem, Ouragini | Kais, Douzi | Fethi, Chaouachi Dorra Mellouli | Mohamed, Bejaoui | Salem, Abbes | Faggad, Areeg | Gebreslasie, Amanuel T. | Zaki, Hani Y. | Abdalla, Badreldin E. | AlShammari, Maha S. | Al-Ali, Rhaya | Al-Balawi, Nader | Al-Enazi, Mansour | Al-Muraikhi, Ali | Busaleh, Fadi | Al-Sahwan, Ali | Borgio, Francis | Sayyed, Abdulazeez | Al-Ali, Amein | Acharya, Sadananda | Zaki, Maha S. | El-Bassyouni, Hala T. | Shehab, Marwa I. | Elshal, Mohammed F. | M., Kaleemuddin | Aldahlawi, Alia M. | Saadah, Omar | McCoy, J. Philip | El-Tarras, Adel E. | Awad, Nabil S. | Alharthi, Abdulla A. | Ibrahim, Mohamed M. M. | Alsehli, Haneen S. | Dallol, Ashraf | Gari, Abdullah M. | Abbas, Mohammed M. | Kadam, Roaa A. | Gari, Mazen M. | Alkaff, Mohmmed H. | Abuzenadah, Adel M. | Gari, Mamdooh A. | Abusamra, Heba | Karim, Sajjad | eldin, Hend F. Nour | Alhathli, Elham M. | Salem, Nada | Kumar, Sudhir | Al-Qahtani, Mohammed H. | Moradi, Fatima A. | Rashidi, Omran M. | Awan, Zuhier A. | Kaya, Ibrahim Hamza | Al-Harazi, Olfat | Colak, Dilek | Alkousi, Nabila A. | Athanasopoulos, Takis | Bahmaid, Afnan O. | Alhwait, Etimad A. | Gari, Mamdooh A. | Alsehli, Haneen S. | Abbas, Mohammed M. | Alkaf, Mohammed H. | Kadam, Roaa | Dallol, Ashraf | Kalamegam, Gauthaman | Eldin, Hend F. Nour | Karim, Sajjad | Abusamra, Heba | Alhathli, Elham | Salem, Nada | Al-Qahtani, Mohammed H. | Kumar, Sudhir | Alsayed, Salma N. | Aljohani, Fawziah H. | Habeeb, Samaher M. | Almashali, Rawan A. | Basit, Sulman | Ahmed, Samia M. | Sharma, Rakesh | Agarwal, Ashok | Durairajanayagam, Damayanthi | Samanta, Luna | Abu-Elmagd, Muhammad | Abuzenadah, Adel M. | Sabanegh, Edmund S. | Assidi, Mourad | Al-Qahtani, Mohammed | Agarwal, Ashok | Sharma, Rakesh | Samanta, Luna | Durairajanayagam, Damayanthi | Assidi, Mourad | Abu-Elmagd, Muhammad | Al-Qahtani, Mohammed | Abuzenadah, Adel M. | Sabanegh, Edmund S. | Samanta, Luna | Agarwal, Ashok | Sharma, Rakesh | Cui, Zhihong | Assidi, Mourad | Abuzenadah, Adel M. | Abu-Elmagd, Muhammad | Al-Qahtani, Mohammed | Alboogmi, Alaa A. | Alansari, Nuha A. | Al-Quaiti, Maha M. | Ashgan, Fai T. | Bandah, Afnan | Jamal, Hasan S. | Rozi, Abdullraheem | Mirza, Zeenat | Abuzenadah, Adel M. | Karim, Sajjad | Al-Qahtani, Mohammed H. | Karim, Sajjad | Schulten, Hans-Juergen | Al Sayyad, Ahmad J. | Farsi, Hasan M. A. | Al-Maghrabi, Jaudah A. | Mirza, Zeenat | Alotibi, Reem | Al-Ahmadi, Alaa | Alansari, Nuha A. | Albogmi, Alaa A. | Al-Quaiti, Maha M. | Ashgan, Fai T. | Bandah, Afnan | Al-Qahtani, Mohammed H. | Ebiya, Rasha A. | Darwish, Samia M. | Montaser, Metwally M. | Abusamra, Heba | Bajic, Vladimir B. | Al-Maghrabi, Jaudah | Gomaa, Wafaey | Hanbazazh, Mehenaz | Al-Ahwal, Mahmoud | Al-Harbi, Asia | Al-Qahtani, Wejdan | Hakamy, Saher | Baba, Ghali | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Al-Maghrabi, Jaudah | Al-Harbi, Abdullah | Al-Ahwal, Mahmoud | Al-Harbi, Asia | Al-Qahtani, Wejdan | Hakamy, Sahar | Baba, Ghalia | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Alhathli, Elham M. | Karim, Sajjad | Salem, Nada | Eldin, Hend Nour | Abusamra, Heba | Kumar, Sudhir | Al-Qahtani, Mohammed H. | Alyamani, Aisha A. | Kalamegam, Gauthaman | Alhwait, Etimad A. | Gari, Mamdooh A. | Abbas, Mohammed M. | Alkaf, Mohammed H. | Alsehli, Haneen S. | Kadam, Roaa A. | Al-Qahtani, Mohammed | Gadi, Rawan | Buhmeida, Abdelbaset | Assidi, Mourad | Chaudhary, Adeel | Merdad, Leena | Alfakeeh, Saadiah M. | Alhwait, Etimad A. | Gari, Mamdooh A. | Abbas, Mohammed M. | Alkaf, Mohammed H. | Alsehli, Haneen S. | Kadam, Roaa | Kalamegam, Gauthaman | Ghazala, Rubi | Mathew, Shilu | Hamed, M. Haroon | Assidi, Mourad | Al-Qahtani, Mohammed | Qadri, Ishtiaq | Mathew, Shilu | Mira, Lobna | Shaabad, Manal | Hussain, Shireen | Assidi, Mourad | Abu-Elmagd, Muhammad | Al-Qahtani, Mohammed | Mathew, Shilu | Shaabad, Manal | Mira, Lobna | Hussain, Shireen | Assidi, Mourad | Abu-Elmagd, Muhammad | Al-Qahtani, Mohammed | Rebai, Ahmed | Assidi, Mourad | Buhmeida, Abdelbaset | Abu-Elmagd, Muhammad | Dallol, Ashraf | Shay, Jerry W. | Almutairi, Mikhlid H. | Ambers, Angie | Churchill, Jennifer | King, Jonathan | Stoljarova, Monika | Gill-King, Harrell | Assidi, Mourad | Abu-Elmagd, Muhammad | Buhmeida, Abdelbaset | Al-Qatani, Muhammad | Budowle, Bruce | Abu-Elmagd, Muhammad | Ahmed, Farid | Dallol, Ashraf | Assidi, Mourad | Almagd, Taha Abo | Hakamy, Sahar | Agarwal, Ashok | Al-Qahtani, Muhammad | Abuzenadah, Adel | Karim, Sajjad | Schulten, Hans-Juergen | Al Sayyad, Ahmad J. | Farsi, Hasan M. A. | Al-Maghrabi, Jaudah A. | Buhmaida, Abdelbaset | Mirza, Zeenat | Alotibi, Reem | Al-Ahmadi, Alaa | Alansari, Nuha A. | Albogmi, Alaa A. | Al-Quaiti, Maha M. | Ashgan, Fai T. | Bandah, Afnan | Al-Qahtani, Mohammed H. | Satar, Rukhsana | Rasool, Mahmood | Ahmad, Waseem | Nazam, Nazia | Lone, Mohamad I. | Naseer, Muhammad I. | Jamal, Mohammad S. | Zaidi, Syed K. | Pushparaj, Peter N. | Jafri, Mohammad A. | Ansari, Shakeel A. | Alqahtani, Mohammed H. | Bashier, Hanan | Al Qahtani, Abrar | Mathew, Shilu | Nour, Amal M. | Alkhatabi, Heba | Zenadah, Adel M. Abu | Buhmeida, Abdelbaset | Assidi, Mourad | Al Qahtani, Muhammed | Faheem, Muhammad | Mathew, Shilu | Mathew, Shiny | Pushparaj, Peter Natesan | Al-Qahtani, Mohammad H. | Alhadrami, Hani A. | Dallol, Ashraf | Abuzenadah, Adel | Hussein, Ibtessam R. | Chaudhary, Adeel G. | Bader, Rima S. | Bassiouni, Randa | Alquaiti, Maha | Ashgan, Fai | Schulten, Hans | Alama, Mohamed Nabil | Al Qahtani, Mohammad H. | Lone, Mohammad I. | Nizam, Nazia | Ahmad, Waseem | Jafri, Mohammad A. | Rasool, Mahmood | Ansari, Shakeel A. | Al-Qahtani, Muhammed H. | Alshihri, Eradah | Abu-Elmagd, Muhammad | Alharbi, Lina | Assidi, Mourad | Al-Qahtani, Mohammed | Mathew, Shilu | Natesan, Peter Pushparaj | Al Qahtani, Muhammed | Kalamegam, Gauthaman | Pushparaj, Peter Natesan | Khan, Fazal | Kadam, Roaa | Ahmed, Farid | Assidi, Mourad | Sait, Khalid Hussain Wali | Anfinan, Nisreen | Al Qahtani, Mohammed | Naseer, Muhammad I. | Chaudhary, Adeel G. | Jamal, Mohammad S. | Mathew, Shilu | Mira, Lobna S. | Pushparaj, Peter N. | Ansari, Shakeel A. | Rasool, Mahmood | AlQahtani, Mohammed H. | Naseer, Muhammad I. | Chaudhary, Adeel G. | Mathew, Shilu | Mira, Lobna S. | Jamal, Mohammad S. | Sogaty, Sameera | Bassiouni, Randa I. | Rasool, Mahmood | AlQahtani, Mohammed H. | Rasool, Mahmood | Ansari, Shakeel A. | Jamal, Mohammad S. | Pushparaj, Peter N. | Sibiani, Abdulrahman M. S. | Ahmad, Waseem | Buhmeida, Abdelbaset | Jafri, Mohammad A. | Warsi, Mohiuddin K. | Naseer, Muhammad I. | Al-Qahtani, Mohammed H. | Rubi | Kumar, Kundan | Naqvi, Ahmad A. T. | Ahmad, Faizan | Hassan, Md I. | Jamal, Mohammad S. | Rasool, Mahmood | AlQahtani, Mohammed H. | Ali, Ashraf | Jarullah, Jummanah | Rasool, Mahmood | Buhmeida, Abdelbasit | Khan, Shahida | Abdussami, Ghufrana | Mahfooz, Maryam | Kamal, Mohammad A. | Damanhouri, Ghazi A. | Jamal, Mohammad S. | Jarullah, Bushra | Jarullah, Jummanah | Jarullah, Mohammad S. S. | Ali, Ashraf | Rasool, Mahmood | Jamal, Mohammad S. | Assidi, Mourad | Abu-Elmagd, Muhammad | Bajouh, Osama | Pushparaj, Peter Natesan | Al-Qahtani, Mohammed | Abuzenadah, Adel | Jamal, Mohammad S. | Jarullah, Jummanah | Mathkoor, Abdulah E. A. | Alsalmi, Hashim M. A. | Oun, Anas M. M. | Damanhauri, Ghazi A. | Rasool, Mahmood | AlQahtani, Mohammed H. | Naseer, Muhammad I. | Rasool, Mahmood | Sogaty, Sameera | Chudhary, Adeel G. | Abutalib, Yousif A. | Merico, Daniele | Walker, Susan | Marshall, Christian R. | Zarrei, Mehdi | Scherer, Stephen W. | Al-Qahtani, Mohammad H. | Naseer, Muhammad I. | Faheem, Muhammad | Chaudhary, Adeel G. | Rasool, Mahmood | Kalamegam, Gauthaman | Ashgan, Fai Talal | Assidi, Mourad | Ahmed, Farid | Zaidi, Syed Kashif | Jan, Mohammed M. | Al-Qahtani, Mohammad H. | Al-Zahrani, Maryam | Lary, Sahira | Hakamy, Sahar | Dallol, Ashraf | Al-Ahwal, Mahmoud | Al-Maghrabi, Jaudah | Dermitzakis, Emmanuel | Abuzenadah, Adel | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Al-refai, Abeer A. | Saleh, Mona | Yassien, Rehab I. | Kamel, Mahmmoud | Habeb, Rabab M. | Filimban, Najlaa | Dallol, Ashraf | Ghannam, Nadia | Al-Qahtani, Mohammed | Abuzenadah, Adel Mohammed | Bibi, Fehmida | Akhtar, Sana | Azhar, Esam I. | Yasir, Muhammad | Nasser, Muhammad I. | Jiman-Fatani, Asif A. | Sawan, Ali | Lahzah, Ruaa A. | Ali, Asho | Hassan, Syed A. | Hasnain, Seyed E. | Tayubi, Iftikhar A. | Abujabal, Hamza A. | Magrabi, Alaa O. | Khan, Fazal | Kalamegam, Gauthaman | Pushparaj, Peter Natesan | Abuzenada, Adel | Kumosani, Taha Abduallah | Barbour, Elie | Al-Qahtani, Mohammed | Shabaad, Manal | Mathew, Shilu | Dallol, Ashraf | Merdad, Adnan | Buhmeida, Abdelbaset | Al-Qahtani, Mohammed | Assidi, Mourad | Abu-Elmagd, Muhammad | Gauthaman, Kalamegam | Gari, Mamdooh | Chaudhary, Adeel | Abuzenadah, Adel | Pushparaj, Peter Natesan | Al-Qahtani, Mohammed | Hassan, Syed A. | Tayubi, Iftikhar A. | Aljahdali, Hani M. A. | Al Nono, Reham | Gari, Mamdooh | Alsehli, Haneen | Ahmed, Farid | Abbas, Mohammed | Kalamegam, Gauthaman | Al-Qahtani, Mohammed | Mathew, Shilu | Khan, Fazal | Rasool, Mahmood | Jamal, Mohammed Sarwar | Naseer, Muhammad Imran | Mirza, Zeenat | Karim, Sajjad | Ansari, Shakeel | Assidi, Mourad | Kalamegam, Gauthaman | Gari, Mamdooh | Chaudhary, Adeel | Abuzenadah, Adel | Pushparaj, Peter Natesan | Al-Qahtani, Mohammed | Abu-Elmagd, Muhammad | Kalamegam, Gauthaman | Kadam, Roaa | Alghamdi, Mansour A. | Shamy, Magdy | Costa, Max | Khoder, Mamdouh I. | Assidi, Mourad | Pushparaj, Peter Natesan | Gari, Mamdooh | Al-Qahtani, Mohammed | Kharrat, Najla | Belmabrouk, Sabrine | Abdelhedi, Rania | Benmarzoug, Riadh | Assidi, Mourad | Al Qahtani, Mohammed H. | Rebai, Ahmed | Dhamanhouri, Ghazi | Pushparaj, Peter Natesan | Noorwali, Abdelwahab | Alwasiyah, Mohammad Khalid | Bahamaid, Afnan | Alfakeeh, Saadiah | Alyamani, Aisha | Alsehli, Haneen | Abbas, Mohammed | Gari, Mamdooh | Mobasheri, Ali | Kalamegam, Gauthaman | Al-Qahtani, Mohammed | Faheem, Muhammad | Mathew, Shilu | Pushparaj, Peter Natesan | Al-Qahtani, Mohammad H. | Mathew, Shilu | Faheem, Muhammad | Mathew, Shiny | Pushparaj, Peter Natesan | Al-Qahtani, Mohammad H. | Jamal, Mohammad Sarwar | Zaidi, Syed Kashif | Khan, Raziuddin | Bhatia, Kanchan | Al-Qahtani, Mohammed H. | Ahmad, Saif | AslamTayubi, Iftikhar | Tripathi, Manish | Hassan, Syed Asif | Shrivastava, Rahul | Tayubi, Iftikhar A. | Hassan, Syed | Abujabal, Hamza A. S. | Shah, Ishani | Jarullah, Bushra | Jamal, Mohammad S. | Jarullah, Jummanah | Sheikh, Ishfaq A. | Ahmad, Ejaz | Jamal, Mohammad S. | Rehan, Mohd | Abu-Elmagd, Muhammad | Tayubi, Iftikhar A. | AlBasri, Samera F. | Bajouh, Osama S. | Turki, Rola F. | Abuzenadah, Adel M. | Damanhouri, Ghazi A. | Beg, Mohd A. | Al-Qahtani, Mohammed | Hammoudah, Sahar A. F. | AlHarbi, Khalid M. | El-Attar, Lama M. | Darwish, Ahmed M. Z. | Ibrahim, Sara M. | Dallol, Ashraf | Choudhry, Hani | Abuzenadah, Adel | Awlia, Jalaludden | Chaudhary, Adeel | Ahmed, Farid | Al-Qahtani, Mohammed | Jafri, Mohammad A. | Abu-Elmagd, Muhammad | Assidi, Mourad | Al-Qahtani, Mohammed | khan, Imran | Yasir, Muhammad | Azhar, Esam I. | Al-basri, Sameera | Barbour, Elie | Kumosani, Taha | Khan, Fazal | Kalamegam, Gauthaman | Pushparaj, Peter Natesan | Abuzenada, Adel | Kumosani, Taha Abduallah | Barbour, Elie | EL Sayed, Heba M. | Hafez, Eman A. | Schulten, Hans-Juergen | Elaimi, Aisha Hassan | Hussein, Ibtessam R. | Bassiouni, Randa Ibrahim | Alwasiyah, Mohammad Khalid | Wintle, Richard F. | Chaudhary, Adeel | Scherer, Stephen W. | Al-Qahtani, Mohammed | Mirza, Zeenat | Pillai, Vikram Gopalakrishna | Karim, Sajjad | Sharma, Sujata | Kaur, Punit | Srinivasan, Alagiri | Singh, Tej P. | Al-Qahtani, Mohammed | Alotibi, Reem | Al-Ahmadi, Alaa | Al-Adwani, Fatima | Hussein, Deema | Karim, Sajjad | Al-Sharif, Mona | Jamal, Awatif | Al-Ghamdi, Fahad | Al-Maghrabi, Jaudah | Baeesa, Saleh S. | Bangash, Mohammed | Chaudhary, Adeel | Schulten, Hans-Juergen | Al-Qahtani, Mohammed | Faheem, Muhammad | Pushparaj, Peter Natesan | Mathew, Shilu | Kumosani, Taha Abdullah | Kalamegam, Gauthaman | Al-Qahtani, Mohammed | Al-Allaf, Faisal A. | Abduljaleel, Zainularifeen | Alashwal, Abdullah | Taher, Mohiuddin M. | Bouazzaoui, Abdellatif | Abalkhail, Halah | Ba-Hammam, Faisal A. | Athar, Mohammad | Kalamegam, Gauthaman | Pushparaj, Peter Natesan | Abu-Elmagd, Muhammad | Ahmed, Farid | Sait, Khalid HussainWali | Anfinan, Nisreen | Gari, Mamdooh | Chaudhary, Adeel | Abuzenadah, Adel | Assidi, Mourad | Al-Qahtani, Mohammed | Mami, Naira Ben | Haffani, Yosr Z. | Medhioub, Mouna | Hamzaoui, Lamine | Cherif, Ameur | Azouz, Msadok | Kalamegam, Gauthaman | Khan, Fazal | Mathew, Shilu | Nasser, Mohammed Imran | Rasool, Mahmood | Ahmed, Farid | Pushparaj, Peter Natesan | Al-Qahtani, Mohammed | Turkistany, Shereen A. | Al-harbi, Lina M. | Dallol, Ashraf | Sabir, Jamal | Chaudhary, Adeel | Abuzenadah, Adel | Al-Madoudi, Basmah | Al-Aslani, Bayan | Al-Harbi, Khulud | Al-Jahdali, Rwan | Qudaih, Hanadi | Al Hamzy, Emad | Assidi, Mourad | Al Qahtani, Mohammed | Ilyas, Asad M. | Ahmed, Youssri | Gari, Mamdooh | Ahmed, Farid | Alqahtani, Mohammed | Salem, Nada | Karim, Sajjad | Alhathli, Elham M. | Abusamra, Heba | Eldin, Hend F. Nour | Al-Qahtani, Mohammed H. | Kumar, Sudhir | Al-Adwani, Fatima | Hussein, Deema | Al-Sharif, Mona | Jamal, Awatif | Al-Ghamdi, Fahad | Al-Maghrabi, Jaudah | Baeesa, Saleh S. | Bangash, Mohammed | Chaudhary, Adeel | Al-Qahtani, Mohammed | Schulten, Hans-Juergen | Alamandi, Alaa | Alotibi, Reem | Hussein, Deema | Karim, Sajjad | Al-Maghrabi, Jaudah | Al-Ghamdi, Fahad | Jamal, Awatif | Baeesa, Saleh S. | Bangash, Mohammed | Chaudhary, Adeel | Schulten, Hans-Juergen | Al-Qahtani, Mohammed | Subhi, Ohoud | Bagatian, Nadia | Karim, Sajjad | Al-Johari, Adel | Al-Hamour, Osman Abdel | Al-Aradati, Hosam | Al-Mutawa, Abdulmonem | Al-Mashat, Faisal | Al-Maghrabi, Jaudah | Schulten, Hans-Juergen | Al-Qahtani, Mohammad | Bagatian, Nadia | Subhi, Ohoud | Karim, Sajjad | Al-Johari, Adel | Al-Hamour, Osman Abdel | Al-Mutawa, Abdulmonem | Al-Aradati, Hosam | Al-Mashat, Faisal | Al-Qahtani, Mohammad | Schulten, Hans-Juergen | Al-Maghrabi, Jaudah | shah, Muhammad W. | Yasir, Muhammad | Azhar, Esam I | Al-Masoodi, Saad | Haffani, Yosr Z. | Azouz, Msadok | Khamla, Emna | Jlassi, Chaima | Masmoudi, Ahmed S. | Cherif, Ameur | Belbahri, Lassaad | Al-Khayyat, Shadi | Attas, Roba | Abu-Sanad, Atlal | Abuzinadah, Mohammed | Merdad, Adnan | Dallol, Ashraf | Chaudhary, Adeel | Al-Qahtani, Mohammed | Abuzenadah, Adel | Bouazzi, Habib | Trujillo, Carlos | Alwasiyah, Mohammad Khalid | Al-Qahtani, Mohammed | Alotaibi, Maha | Nassir, Rami | Sheikh, Ishfaq A. | Kamal, Mohammad A. | Jiffri, Essam H. | Ashraf, Ghulam M. | Beg, Mohd A. | Aziz, Mohammad A. | Ali, Rizwan | Rasool, Mahmood | Jamal, Mohammad S. | Samman, Nusaibah | Abdussami, Ghufrana | Periyasamy, Sathish | Warsi, Mohiuddin K. | Aldress, Mohammed | Al Otaibi, Majed | Al Yousef, Zeyad | Boudjelal, Mohamed | Buhmeida, Abdelbasit | Al-Qahtani, Mohammed H. | AlAbdulkarim, Ibrahim | Ghazala, Rubi | Mathew, Shilu | Hamed, M. Haroon | Assidi, Mourad | Al-Qahtani, Mohammed | Qadri, Ishtiaq | Sheikh, Ishfaq A. | Abu-Elmagd, Muhammad | Turki, Rola F. | Damanhouri, Ghazi A. | Beg, Mohd A. | Suhail, Mohd | Qureshi, Abid | Jamal, Adil | Pushparaj, Peter Natesan | Al-Qahtani, Mohammad | Qadri, Ishtiaq | El-Readi, Mahmoud Z. | Eid, Safaa Y. | Wink, Michael | Isa, Ahmed M. | Alnuaim, Lulu | Almutawa, Johara | Abu-Rafae, Basim | Alasiri, Saleh | Binsaleh, Saleh | Nazam, Nazia | Lone, Mohamad I. | Ahmad, Waseem | Ansari, Shakeel A. | Alqahtani, Mohamed H.
BMC Genomics  2016;17(Suppl 6):487.
Table of contents
O1 Regulation of genes by telomere length over long distances
Jerry W. Shay
O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy
Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa
O3 Integration of metagenomics and metabolomics in gut microbiome research
Maryam Goudarzi, Albert J. Fornace Jr.
O4 A unique integrated system to discern pathogenesis of central nervous system tumors
Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri
O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis
Heba Alkhatabi
O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service
Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp
O7 Targeted sequencing panels and their utilization in personalized medicine
Adel M. Abuzenadah
O8 International biobanking in the era of precision medicine
Jim Vaught
O9 Biobank and biodata for clinical and forensic applications
Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida
O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors
Jaudah Al-Maghrabi
O11 The CEGMR biobanking unit: achievements, challenges and future plans
Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad
O12 Phylomedicine of tumors
Sudhir Kumar, Sayaka Miura, Karen Gomez
O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment
Angel Carracedo, Mahmood Rasool
O14 From association to causality: translation of GWAS findings for genomic medicine
Ahmed Rebai
O15 E-GRASP: an interactive database and web application for efficient analysis of disease-associated genetic information
Sajjad Karim, Hend F Nour Eldin, Heba Abusamra, Elham M Alhathli, Nada Salem, Mohammed H Al-Qahtani, Sudhir Kumar
O16 The supercomputer facility “AZIZ” at KAU: utility and future prospects
Hossam Faheem
O17 New research into the causes of male infertility
Ashok Agarwa
O18 The Klinefelter syndrome: recent progress in pathophysiology and management
Eberhard Nieschlag, Joachim Wistuba, Oliver S. Damm, Mohd A. Beg, Taha A. Abdel-Meguid, Hisham A. Mosli, Osama S. Bajouh, Adel M. Abuzenadah, Mohammed H. Al-Qahtani
O19 A new look to reproductive medicine in the era of genomics
Serdar Coskun
P1 Wnt signalling receptors expression in Saudi breast cancer patients
Muhammad Abu-Elmagd, Abdelbaset Buhmeida, Ashraf Dallol, Jaudah Al-Maghrabi, Sahar Hakamy, Wejdan Al-Qahtani, Asia Al-Harbi, Shireen Hussain, Mourad Assidi, Mohammed Al-Qahtani, Adel Abuzenadah
P2 Analysis of oxidative stress interactome during spermatogenesis: a systems biology approach to reproduction
Burak Ozkosem, Rick DuBois
P3 Interleukin-18 gene variants are strongly associated with idiopathic recurrent pregnancy loss.
Safia S Messaoudi, Maryam T Dandana, Touhami Mahjoub, Wassim Y Almawi
P4 Effect of environmental factors on gene-gene and gene-environment reactions: model and theoretical study applied to environmental interventions using genotype
S. Abdalla, M. Nabil Al-Aama
P5 Genomics and transcriptomic analysis of imatinib resistance in gastrointestinal stromal tumor
Asmaa Elzawahry, Tsuyoshi Takahashi, Sachiyo Mimaki, Eisaku Furukawa, Rie Nakatsuka, Isao Kurosaka, Takahiko Nishigaki, Hiromi Nakamura, Satoshi Serada, Tetsuji Naka, Seiichi Hirota, Tatsuhiro Shibata, Katsuya Tsuchihara, Toshirou Nishida, Mamoru Kato
P6 In-Silico analysis of putative HCV epitopes against Pakistani human leukocyte antigen background: an approach towards development of future vaccines for Pakistani population
Sajid Mehmood, Naeem Mahmood Ashraf, Awais Asif, Muhammad Bilal, Malik Siddique Mehmood, Aadil Hussain
P7 Inhibition of AChE and BuChE with the natural compounds of Bacopa monerri for the treatment of Alzheimer’s disease: a bioinformatics approach
Qazi Mohammad Sajid Jamal, Mughees Uddin Siddiqui, Mohammad A. Alzohairy, Mohammad A. Al Karaawi
P8 Her2 expression in urothelial cell carcinoma of the bladder in Saudi Arabia
Taoufik Nedjadi, Jaudah Al-Maghrabi, Mourad Assidi, Heba Al-Khattabi, Adel Al-Ammari, Ahmed Al-Sayyad, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P9 Association of angiotensinogen single nucleotide polymorphisms with Preeclampsia in patients from North Africa
Hédia Zitouni, Nozha Raguema, Marwa Ben Ali, Wided Malah, Raja Lfalah, Wassim Almawi, Touhami Mahjoub
P10 Systems biology analysis reveals relations between normal skin, benign nevi and malignant melanoma
Mohammed Elanbari, Andrey Ptitsyn
P11 The apoptotic effect of thymoquinone in Jurkat cells
Sana Mahjoub, Rabeb El Ghali, Bechir Achour, Nidhal Ben Amor, Mourad Assidi, Brahim N'siri, Hamid Morjani
P12 Sonic hedgehog contributes in bladder cancer invasion in Saudi Arabia
Taoufik Nedjadi, Adel Al-Ammari, Ahmed Al-Sayyad, Nada Salem, Esam Azhar, Jaudah Al-Maghrabi
P13 Association of Interleukin 18 gene promoter polymorphisms - 607A/C and -137 G/C with colorectal cancer onset in a sample of Tunisian population
Vera Chayeb, Maryam Dendena, Hedia Zitouni, Khedija Zouari-Limayem, Touhami Mahjoub
P14 Pathological expression of interleukin-6, -11, leukemia inhibitory factor and their receptors in tubal gestation with and without tubal cytomegalovirus infection
Bassem Refaat, Ahmed M Ashshi, Sarah A Batwa
P15 Phenotypic and genetic profiling of avian pathogenic and human diarrhegenic Escherichia coli in Egypt
Hazem Ramadan, Amal Awad, Ahmed Ateya
P16 Cancer-targeting dual gene virotherapy as a promising therapeutic strategy for treatment of hepatocellular carcinoma
Adel Galal Ahmed El-Shemi, Ahmad Ashshi, Mohammed Basalamah, Youjin Na, Chae-Ok YUN
P17 Cancer dual gene therapy with oncolytic adenoviruses expressing TRAIL and IL-12 transgenes markedly eradicated human hepatocellular carcinoma both in vitro and in vivo
Adel Galal Ahmed El-Shemi, Ahmad Ashshi, Mohammed Basalamah, Youjin Na, Chae-Ok Yun
P18 Therapy with paricalcitol attenuates tumor growth and augments tumoricidal and anti-oncogenic effects of 5-fluorouracil on animal model of colon cancer
Adel Galal El-Shemi, Bassem Refaat, Osama Kensara, Amr Abdelfattah
P19 The effects of Rubus idaeus extract on normal human lymphocytes and cancer cell line
Batol Imran Dheeb, Mohammed M. F. Al-Halbosiy, Rghad Kadhim Al lihabi, Basim Mohammed Khashman
P20 Etanercept, a TNF-alpha inhibitor, alleviates mechanical hypersensitivity and spontaneous pain in a rat model of chemotherapy-induced neuropathic pain
Djouhri, Laiche, Chaudhary Adeel, Nedjadi, Taoufik
P21 Sleeping beauty mutagenesis system identified genes and neuronal transcription factor network involved in pediatric solid tumour (medulloblastoma)
Hani Al-Afghani, Maria Łastowska, Haya H Al-Balool, Harsh Sheth, Emma Mercer, Jonathan M Coxhead, Chris PF Redfern, Heiko Peters, Alastair D Burt, Mauro Santibanez-Koref, Chris M Bacon, Louis Chesler, Alistair G Rust, David J Adams, Daniel Williamson, Steven C Clifford, Michael S Jackson
P22 Involvement of interleukin-1 in vitiligo pathogenesis
Mala Singh, Mohmmad Shoab Mansuri, Shahnawaz D. Jadeja, Hima Patel, Yogesh S. Marfatia, Rasheedunnisa Begum
P23 Cytogenetics abnormalities in 12,884 referred population for chromosomal analysis and the role of FISH in refining the diagnosis (cytogenetic experience 2004-2013)
Amal M Mohamed, Alaa K Kamel, Nivin A Helmy, Sayda A Hammad, Hesham F Kayed, Marwa I Shehab, Assad El Gerzawy, Maha M. Ead, Ola M Ead, Mona Mekkawy, Innas Mazen, Mona El-Ruby
P24 Analysis of binding properties of angiotensin-converting enzyme 2 through in silico method
S. M. A. Shahid, Qazi Mohammad Sajid Jamal, J. M. Arif, Mohtashim Lohani
P25 Relationship of genetics markers cis and trans to the β-S globin gene with fetal hemoglobin expression in Tunisian sickle cell patients
Moumni Imen, Chaouch Leila, Ouragini Houyem, Douzi Kais, Chaouachi Dorra Mellouli Fethi, Bejaoui Mohamed, Abbes Salem
P26 Analysis of estrogen receptor alpha gene polymorphisms in breast cancer: link to genetic predisposition in Sudanese women
Areeg Faggad, Amanuel T Gebreslasie, Hani Y Zaki, Badreldin E Abdalla
P27 KCNQI gene polymorphism and its association with CVD and T2DM in the Saudi population
Maha S AlShammari, Rhaya Al-Ali, Nader Al-Balawi , Mansour Al-Enazi, Ali Al-Muraikhi, Fadi Busaleh, Ali Al-Sahwan, Francis Borgio, Abdulazeez Sayyed, Amein Al-Ali, Sadananda Acharya
P28 Clinical, neuroimaging and cytogenetic study of a patient with microcephaly capillary malformation syndrome
Maha S. Zaki, Hala T. El-Bassyouni, Marwa I. Shehab
P29 Altered expression of CD200R1 on dendritic cells of patients with inflammatory bowel diseases: in silico investigations and clinical evaluations
Mohammed F. Elshal, Kaleemuddin M., Alia M. Aldahlawi, Omar Saadah,
J. Philip McCoy
P30 Development of real time PCR diagnostic protocol specific for the Saudi Arabian H1N1 viral strains
Adel E El-Tarras, Nabil S Awad, Abdulla A Alharthi, Mohamed M M Ibrahim
P31 Identification of novel genetic variations affecting Osteoarthritis patients
Haneen S Alsehli, Ashraf Dallol, Abdullah M Gari, Mohammed M Abbas, Roaa A Kadam, Mazen M. Gari, Mohmmed H Alkaff, Adel M Abuzenadah, Mamdooh A Gari
P32 An integrated database of GWAS SNVs and their evolutionary properties
Heba Abusamra, Sajjad Karim, Hend F Nour eldin, Elham M Alhathli, Nada Salem, Sudhir Kumar, Mohammed H Al-Qahtani
P33 Familial hypercholesterolemia in Saudi Arabia: prime time for a national registry and genetic analysis
Fatima A. Moradi, Omran M. Rashidi, Zuhier A. Awan
P34 Comparative genomics and network-based analyses of early hepatocellular carcinoma
Ibrahim Hamza Kaya, Olfat Al-Harazi, Dilek Colak
P35 A TALEN-based oncolytic viral vector approach to knock out ABCB1 gene mediated chemoresistance in cancer stem cells
Nabila A Alkousi, Takis Athanasopoulos
P36 Cartilage differentiation and gene expression of synovial fluid mesenchymal stem cells derived from osteoarthritis patients
Afnan O Bahmaid, Etimad A Alhwait, Mamdooh A Gari, Haneen S Alsehli, Mohammed M Abbas, Mohammed H Alkaf, Roaa Kadam, Ashraf Dallol, Gauthaman Kalamegam
P37 E-GRASP: Adding an evolutionary component to the genome-wide repository of associations (GRASP) resource
Hend F Nour Eldin, Sajjad Karim, Heba Abusamra, Elham Alhathli, Nada Salem, Mohammed H Al-Qahtani, Sudhir Kumar
P38 Screening of AGL gene mutation in Saudi family with glycogen storage disease Type III
Salma N Alsayed, Fawziah H Aljohani, Samaher M Habeeb, Rawan A Almashali, Sulman Basit, Samia M Ahmed
P39 High throughput proteomic data suggest modulation of cAMP dependent protein kinase A and mitochondrial function in infertile patients with varicocele
Rakesh Sharma, Ashok Agarwal, Damayanthi Durairajanayagam, Luna Samanta, Muhammad Abu-Elmagd, Adel M. Abuzenadah, Edmund S. Sabanegh, Mourad Assidi, Mohammed Al-Qahtani
P40 Significant protein profile alterations in men with primary and secondary infertility
Ashok Agarwal, Rakesh Sharma, Luna Samanta, Damayanthi Durairajanayagam, Mourad Assidi, Muhammad Abu-Elmagd, Mohammed Al-Qahtani, Adel M. Abuzenadah, Edmund S. Sabanegh
P41 Spermatozoa maturation in infertile patients involves compromised expression of heat shock proteins
Luna Samanta, Ashok Agarwal, Rakesh Sharma, Zhihong Cui, Mourad Assidi, Adel M. Abuzenadah, Muhammad Abu-Elmagd, Mohammed Al-Qahtani
P42 Array comparative genomic hybridization approach to search genomic answers for spontaneous recurrent abortion in Saudi Arabia
Alaa A Alboogmi, Nuha A Alansari, Maha M Al-Quaiti, Fai T Ashgan, Afnan Bandah, Hasan S Jamal, Abdullraheem Rozi, Zeenat Mirza, Adel M Abuzenadah, Sajjad Karim, Mohammed H Al-Qahtani
P43 Global gene expression profiling of Saudi kidney cancer patients
Sajjad Karim, Hans-Juergen Schulten, Ahmad J Al Sayyad, Hasan MA Farsi, Jaudah A Al-Maghrabi, Zeenat Mirza, Reem Alotibi, Alaa Al-Ahmadi, Nuha A Alansari, Alaa A Albogmi, Maha M Al-Quaiti, Fai T Ashgan, Afnan Bandah, Mohammed H Al-Qahtani
P44 Downregulated StAR gene and male reproductive dysfunction caused by nifedipine and ethosuximide
Rasha A Ebiya, Samia M Darwish, Metwally M. Montaser
P45 Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes
Heba Abusamra, Vladimir B. Bajic
P46 Prognostic significance of Osteopontin expression profile in colorectal carcinoma
Jaudah Al-Maghrabi, Wafaey Gomaa, Mehenaz Hanbazazh, Mahmoud Al-Ahwal, Asia Al-Harbi, Wejdan Al-Qahtani, Saher Hakamy, Ghali Baba, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P47 High Glypican-3 expression pattern predicts longer disease-specific survival in colorectal carcinoma
Jaudah Al-Maghrabi, Abdullah Al-Harbi, Mahmoud Al-Ahwal, Asia Al-Harbi, Wejdan Al-Qahtani, Sahar Hakamy, Ghalia Baba, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P48 An evolutionary re-assessment of GWAS single nucleotide variants implicated in the Cholesterol traits
Elham M Alhathli, Sajjad Karim, Nada Salem, Hend Nour Eldin, Heba Abusamra, Sudhir Kumar, Mohammed H Al-Qahtani
P49 Derivation and characterization of human Wharton’s jelly stem cells (hWJSCs) in vitro for future therapeutic applications
Aisha A Alyamani, Gauthaman Kalamegam, Etimad A Alhwait, Mamdooh A Gari, Mohammed M Abbas, Mohammed H Alkaf, Haneen S Alsehli, Roaa A Kadam, Mohammed Al-Qahtani
P50 Attitudes of healthcare students toward biomedical research in the post-genomic era
Rawan Gadi, Abdelbaset Buhmeida, Mourad Assidi , Adeel Chaudhary, Leena Merdad
P51 Evaluation of the immunomodulatory effects of thymoquinone on human bone marrow mesenchymal stem cells (BM-MSCs) from osteoarthritic patients
Saadiah M Alfakeeh, Etimad A Alhwait, Mamdooh A Gari, Mohammed M Abbas, Mohammed H Alkaf, Haneen S Alsehli, Roaa Kadam, Gauthaman Kalamegam
P52 Implication of IL-10 and IL-28 polymorphism with successful anti-HCV therapy and viral clearance
Rubi Ghazala, Shilu Mathew, M.Haroon Hamed, Mourad Assidi, Mohammed Al-Qahtani, Ishtiaq Qadri
P53 Selection of flavonoids against obesity protein (FTO) using in silico and in vitro approaches
Shilu Mathew, Lobna Mira, Manal Shaabad, Shireen Hussain, Mourad Assidi, Muhammad Abu-Elmagd, Mohammed Al-Qahtani
P54 Computational selection and in vitro validation of flavonoids as new antidepressant agents
Shilu Mathew, Manal Shaabad, Lobna Mira, Shireen Hussain, Mourad Assidi, Muhammad Abu-Elmagd, Mohammed Al-Qahtani
P55 In Silico prediction and prioritization of aging candidate genes associated with
progressive telomere shortening
Ahmed Rebai, Mourad Assidi, Abdelbaset Buhmeida, Muhammad Abu-Elmagd, Ashraf Dallol, Jerry W Shay
P56 Identification of new cancer testis antigen genes in diverse types of malignant human tumour cells
Mikhlid H Almutairi
P57 More comprehensive forensic genetic marker analyses for accurate human remains identification using massively parallel sequencing (MPS)
Angie Ambers, Jennifer Churchill, Jonathan King, Monika Stoljarova, Harrell Gill-King, Mourad Assidi, Muhammad Abu-Elmagd, Abdelbaset Buhmeida, Muhammad Al-Qatani, Bruce Budowle
P58 Flow cytometry approach towards treatment men infertility in Saudi Arabia
Muhammad Abu-Elmagd, Farid Ahmed, Ashraf Dallol, Mourad Assidi, Taha Abo Almagd, Sahar Hakamy, Ashok Agarwal, Muhammad Al-Qahtani, Adel Abuzenadah
P59 Tissue microarray based validation of CyclinD1 expression in renal cell carcinoma of Saudi kidney patients
Sajjad Karim, Hans-Juergen Schulten, Ahmad J Al Sayyad, Hasan MA Farsi, Jaudah A Al-Maghrabi, Abdelbaset Buhmaida, Zeenat Mirza, Reem Alotibi, Alaa Al-Ahmadi, Nuha A Alansari, Alaa A Albogmi, Maha M Al-Quaiti, Fai T Ashgan, Afnan Bandah, Mohammed H Al-Qahtani
P60 Assessment of gold nanoparticles in molecular diagnostics and DNA damage studies
Rukhsana Satar, Mahmood Rasool, Waseem Ahmad, Nazia Nazam, Mohamad I Lone, Muhammad I Naseer, Mohammad S Jamal, Syed K Zaidi, Peter N Pushparaj, Mohammad A Jafri, Shakeel A Ansari, Mohammed H Alqahtani
P61 Surfing the biospecimen management and processing workflow at CEGMR Biobank
Hanan Bashier, Abrar Al Qahtani, Shilu Mathew, Amal M. Nour, Heba Alkhatabi, Adel M. Abu Zenadah, Abdelbaset Buhmeida, Mourad Assidi, Muhammed Al Qahtani
P62 Autism Spectrum Disorder: knowledge, attitude and awareness in Jeddah, Kingdom of Saudi Arabia
Muhammad Faheem, Shilu Mathew, Shiny Mathew, Peter Natesan Pushparaj, Mohammad H. Al-Qahtani
P63 Simultaneous genetic screening of the coagulation pathway genes using the Thromboscan targeted sequencing panel
Hani A. Alhadrami, Ashraf Dallol, Adel Abuzenadah
P64 Genome wide array comparative genomic hybridization analysis in patients with syndromic congenital heart defects
Ibtessam R. Hussein, Adeel G. Chaudhary, Rima S Bader, Randa Bassiouni, Maha Alquaiti, Fai Ashgan, Hans Schulten, Mohamed Nabil Alama, Mohammad H. Al Qahtani
P65 Toxocogenetic evaluation of 1, 2-Dichloroethane in bone marrow, blood and cells of immune system using conventional, molecular and flowcytometric approaches
Mohammad I Lone, Nazia Nizam, Waseem Ahmad, Mohammad A Jafri, Mahmood Rasool, Shakeel A Ansari, Muhammed H Al-Qahtani
P66 Molecular cytogenetic diagnosis of sexual development disorders in newborn: A case of ambiguous genitalia
Eradah Alshihri, Muhammad Abu-Elmagd, Lina Alharbi, Mourad Assidi, Mohammed Al-Qahtani
P67 Identification of disease specific gene expression clusters and pathways in hepatocellular carcinoma using In Silico methodologies
Shilu Mathew, Peter Pushparaj Natesan, Muhammed Al Qahtani
P68 Human Wharton’s Jelly stem cell conditioned medium inhibits primary ovarian cancer cells in vitro: Identification of probable targets and mechanisms using systems biology
Gauthaman Kalamegam, Peter Natesan Pushparaj, Fazal Khan, Roaa Kadam, Farid Ahmed, Mourad Assidi, Khalid Hussain Wali Sait, Nisreen Anfinan, Mohammed Al Qahtani
P69 Mutation spectrum of ASPM (Abnormal Spindle-like, Microcephaly-associated) gene in Saudi Arabian population
Muhammad I Naseer, Adeel G Chaudhary, Mohammad S Jamal, Shilu Mathew, Lobna S Mira, Peter N Pushparaj, Shakeel A Ansari, Mahmood Rasool, Mohammed H AlQahtani
P70 Identification and characterization of novel genes and mutations of primary microcephaly in Saudi Arabian population
Muhammad I Naseer, Adeel G Chaudhary, Shilu Mathew, Lobna S Mira, Mohammad S Jamal, Sameera Sogaty, Randa I Bassiouni, Mahmood Rasool, Mohammed H AlQahtani
P71 Molecular genetic analysis of hereditary nonpolyposis colorectal cancer (Lynch Syndrome) in Saudi Arabian population
Mahmood Rasool, Shakeel A Ansari, Mohammad S Jamal, Peter N Pushparaj, Abdulrahman MS Sibiani, Waseem Ahmad, Abdelbaset Buhmeida, Mohammad A Jafri, Mohiuddin K Warsi, Muhammad I Naseer, Mohammed H Al-Qahtani
P72 Function predication of hypothetical proteins from genome database of chlamydia trachomatis
Rubi, Kundan Kumar, Ahmad AT Naqvi, Faizan Ahmad, Md I Hassan, Mohammad S Jamal, Mahmood Rasool, Mohammed H AlQahtani
P73 Transcription factors as novel molecular targets for skin cancer
Ashraf Ali, Jummanah Jarullah, Mahmood Rasool, Abdelbasit Buhmeida, Shahida Khan, Ghufrana Abdussami, Maryam Mahfooz, Mohammad A Kamal, Ghazi A Damanhouri, Mohammad S Jamal
P74 An In Silico analysis of Plumbagin binding to apoptosis executioner: Caspase-3 and Caspase-7
Bushra Jarullah, Jummanah Jarullah, Mohammad SS Jarullah, Ashraf Ali, Mahmood Rasool, Mohammad S Jamal
P75 Single cell genomics applications for preimplantation genetic screening optimization: Comparative analysis of whole genome amplification technologies
Mourad Assidi, Muhammad Abu-Elmagd, Osama Bajouh, Peter Natesan Pushparaj, Mohammed Al-Qahtani, Adel Abuzenadah
P76 ZFP36 regulates miRs-34a in anti-IgM triggered immature B cells
Mohammad S Jamal, Jummanah Jarullah, Abdulah EA Mathkoor, Hashim MA Alsalmi, Anas MM Oun, Ghazi A Damanhauri, Mahmood Rasool, Mohammed H AlQahtani
P77 Identification of a novel mutation in the STAMBP gene in a family with microcephaly-capillary malformation syndrome
Muhammad I. Naseer, Mahmood Rasool, Sameera Sogaty, Adeel G. Chudhary, Yousif A. Abutalib, Daniele Merico, Susan Walker, Christian R. Marshall, Mehdi Zarrei, Stephen W. Scherer, Mohammad H. Al-Qahtani
P78 Copy number variations in Saudi patients with intellectual disability and epilepsy
Muhammad I. Naseer, Muhammad Faheem, Adeel G. Chaudhary, Mahmood Rasool, Gauthaman Kalamegam, Fai Talal Ashgan, Mourad Assidi, Farid Ahmed, Syed Kashif Zaidi, Mohammed M. Jan, Mohammad H. Al-Qahtani
P79 Prognostic significance of CD44 expression profile in colorectal carcinoma
Maryam Al-Zahrani, Sahira Lary, Sahar Hakamy, Ashraf Dallol, Mahmoud Al-Ahwal, Jaudah Al-Maghrabi, Emmanuel Dermitzakis, Adel Abuzenadah, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P80 Association of the endothelial nitric oxide synthase (eNOS) gene G894T polymorphism with hypertension risk and complications
Abeer A Al-refai, Mona Saleh, Rehab I Yassien, Mahmmoud Kamel, Rabab M Habeb
P81 SNPs array to screen genetic variation among diabetic patients
Najlaa Filimban, Ashraf Dallol, Nadia Ghannam, Mohammed Al-Qahtani, Adel Mohammed Abuzenadah
P82 Detection and genotyping of Helicobacter pylori among gastric cancer patients from Saudi Arabian population
Fehmida Bibi, Sana Akhtar, Esam I. Azhar, Muhammad Yasir, Muhammad I. Nasser, Asif A. Jiman-Fatani, Ali Sawan
P83 Antimicrobial drug resistance and molecular detection of susceptibility to Fluoroquinolones among clinical isolates of Salmonella species from Jeddah-Saudi Arabia
Ruaa A Lahzah, Asho Ali
P84 Identification of the toxic and virulence nature of MAP1138c protein of Mycobacterium avium subsp. paratuberculosis
Syed A Hassan, Seyed E Hasnain, Iftikhar A Tayubi, Hamza A Abujabal, Alaa O Magrabi
P85 In vitro and in silico evaluation of miR137 in human breast cancer
Fazal Khan, Gauthaman Kalamegam, Peter Natesan Pushparaj, Adel Abuzenada, Taha Abduallah Kumosani, Elie Barbour, Mohammed Al-Qahtani
P86 Auruka gene is over-expressed in Saudi breast cancer
Manal Shabaad, Shilu Mathew, Ashraf Dallol, Adnan Merdad, Abdelbaset Buhmeida, Mohammed Al-Qahtani
P87 The potential of immunogenomics in personalized healthcare
Mourad Assidi, Muhammad Abu-Elmagd, Kalamegam Gauthaman, Mamdooh Gari, Adeel Chaudhary, Adel Abuzenadah, Peter Natesan Pushparaj, Mohammed Al-Qahtani
P88 In Silico physiochemical and structural characterization of a putative ORF MAP0591 and its implication in the pathogenesis of Mycobacterium paratuberculosis in ruminants and humans
Syed A Hassan, Iftikhar A Tayubi, Hani MA Aljahdali
P89 Effects of heat shock on human bone marrow mesenchymal stem cells (BM-MSCs): Implications in regenerative medicine
Reham Al Nono, Mamdooh Gari, Haneen Alsehli, Farid Ahmed, Mohammed Abbas, Gauthaman Kalamegam, Mohammed Al-Qahtani
P90 In Silico analyses of the molecular targets of Resveratrol unravels its importance in mast cell mediated allergic responses
Shilu Mathew, Fazal Khan, Mahmood Rasool, Mohammed Sarwar Jamal, Muhammad Imran Naseer, Zeenat Mirza, Sajjad Karim, Shakeel Ansari, Mourad Assidi, Gauthaman Kalamegam, Mamdooh Gari, Adeel Chaudhary, Adel Abuzenadah, Peter Natesan Pushparaj, Mohammed Al-Qahtani
P91 Effects of environmental particulate matter on bone-marrow mesenchymal stem cells
Muhammad Abu-Elmagd, Gauthaman Kalamegam, Roaa Kadam, Mansour A Alghamdi, Magdy Shamy, Max Costa, Mamdouh I Khoder, Mourad Assidi, Peter Natesan Pushparaj, Mamdooh Gari, Mohammed Al-Qahtani
P92 Distinctive charge clusters in human virus proteomes
Najla Kharrat, Sabrine Belmabrouk, Rania Abdelhedi, Riadh Benmarzoug, Mourad Assidi, Mohammed H. Al Qahtani, Ahmed Rebai
P93 In vitro experimental model and approach in identification of new biomarkers of inflammatory forms of arthritis
Ghazi Dhamanhouri, Peter Natesan Pushparaj, Abdelwahab Noorwali, Mohammad Khalid Alwasiyah, Afnan Bahamaid, Saadiah Alfakeeh, Aisha Alyamani, Haneen Alsehli, Mohammed Abbas, Mamdooh Gari, Ali Mobasheri, Gauthaman Kalamegam, Mohammed Al-Qahtani
P94 Molecular docking of GABAA receptor subunit γ-2 with novel anti-epileptic compounds
Muhammad Faheem, Shilu Mathew, Peter Natesan Pushparaj, Mohammad H. Al-Qahtani
P95 Breast cancer knowledge, awareness, and practices among Saudi females residing in Jeddah
Shilu Mathew, Muhammad Faheem, Shiny Mathew, Peter Natesan Pushparaj, Mohammad H. Al-Qahtani
P96 Anti-inflammatory role of Sesamin by Attenuation of Iba1/TNF-α/ICAM-1/iNOS signaling in Diabetic Retinopathy
Mohammad Sarwar Jamal, Syed Kashif Zaidi, Raziuddin Khan, Kanchan Bhatia, Mohammed H. Al-Qahtani, Saif Ahmad
P97 Identification of drug lead molecule against vp35 protein of Ebola virus: An In-Silico approach
Iftikhar AslamTayubi, Manish Tripathi, Syed Asif Hassan, Rahul Shrivastava
P98 An approach to personalized medicine from SNP-calling through disease analysis using whole exome-sequencing of three sub-continental populations
Iftikhar A Tayubi, Syed Hassan, Hamza A.S Abujabal
P99 Low versus high frequency of Glucose –6 – Phosphate Dehydrogenase (G6PD) deficiency in urban against tribal population of Gujarat – A signal to natural selection
Ishani Shah, Bushra Jarullah, Mohammad S Jamal, Jummanah Jarullah
P100 Spontaneous preterm birth and single nucleotide gene polymorphisms: a recent update
Ishfaq A Sheikh, Ejaz Ahmad, Mohammad S Jamal, Mohd Rehan, Muhammad Abu-Elmagd, Iftikhar A Tayubi, Samera F AlBasri, Osama S Bajouh, Rola F Turki, Adel M Abuzenadah, Ghazi A Damanhouri, Mohd A Beg, Mohammed Al-Qahtani
P101 Prevalence of congenital heart diseases among Down syndrome cases in Saudi Arabia: role of molecular genetics in the pathogenesis
Sahar AF Hammoudah, Khalid M AlHarbi, Lama M El-Attar, Ahmed MZ Darwish
P102 Combinatorial efficacy of specific pathway inhibitors in breast cancer cells
Sara M Ibrahim, Ashraf Dallol, Hani Choudhry, Adel Abuzenadah, Jalaludden Awlia, Adeel Chaudhary, Farid Ahmed, Mohammed Al-Qahtani
P103 MiR-143 and miR-145 cluster as potential replacement medicine for the treatment of cancer
Mohammad A Jafri, Muhammad Abu-Elmagd, Mourad Assidi, Mohammed Al-Qahtani
P104 Metagenomic profile of gut microbiota during pregnancy in Saudi population
Imran khan, Muhammad Yasir, Esam I. Azhar, Sameera Al-basri, Elie Barbour, Taha Kumosani
P105 Exploration of anticancer targets of selected metabolites of Phoenix dactylifera L. using systems biological approaches
Fazal Khan, Gauthaman Kalamegam, Peter Natesan Pushparaj, Adel Abuzenada, Taha Abduallah Kumosani, Elie Barbour
P106 CD226 and CD40 gene polymorphism in susceptibility to Juvenile rheumatoid arthritis in Egyptian patients
Heba M. EL Sayed, Eman A. Hafez
P107 Paediatric exome sequencing in autism spectrum disorder ascertained in Saudi families
Hans-Juergen Schulten, Aisha Hassan Elaimi, Ibtessam R Hussein, Randa Ibrahim Bassiouni, Mohammad Khalid Alwasiyah, Richard F Wintle, Adeel Chaudhary, Stephen W Scherer, Mohammed Al-Qahtani
P108 Crystal structure of the complex formed between Phospholipase A2 and the central core hydrophobic fragment of Alzheimer’s β- amyloid peptide: a reductionist approach
Zeenat Mirza, Vikram Gopalakrishna Pillai, Sajjad Karim, Sujata Sharma, Punit Kaur, Alagiri Srinivasan, Tej P Singh, Mohammed Al-Qahtani
P109 Differential expression profiling between meningiomas from female and male patients
Reem Alotibi, Alaa Al-Ahmadi, Fatima Al-Adwani, Deema Hussein, Sajjad Karim, Mona Al-Sharif, Awatif Jamal, Fahad Al-Ghamdi, Jaudah Al-Maghrabi, Saleh S Baeesa, Mohammed Bangash, Adeel Chaudhary, Hans-Juergen Schulten, Mohammed Al-Qahtani
P110 Neurospheres as models of early brain development and therapeutics
Muhammad Faheem, Peter Natesan Pushparaj, Shilu Mathew, Taha Abdullah Kumosani, Gauthaman Kalamegam, Mohammed Al-Qahtani
P111 Identification of a recurrent causative missense mutation p.(W577C) at the LDLR exon 12 in familial hypercholesterolemia affected Saudi families
Faisal A Al-Allaf, Zainularifeen Abduljaleel, Abdullah Alashwal, Mohiuddin M. Taher, Abdellatif Bouazzaoui, Halah Abalkhail, Faisal A. Ba-Hammam, Mohammad Athar
P112 Epithelial ovarian carcinoma (EOC): Systems oncological approach to identify diagnostic, prognostic and therapeutic biomarkers
Gauthaman Kalamegam, Peter Natesan Pushparaj, Muhammad Abu-Elmagd, Farid Ahmed Khalid HussainWali Sait, Nisreen Anfinan, Mamdooh Gari, Adeel Chaudhary, Adel Abuzenadah, Mourad Assidi, Mohammed Al-Qahtani
P113 Crohn’s disease phenotype in northern Tunisian population
Naira Ben Mami, Yosr Z Haffani, Mouna Medhioub, Lamine Hamzaoui, Ameur Cherif, Msadok Azouz
P114 Establishment of In Silico approaches to decipher the potential toxicity and mechanism of action of drug candidates and environmental agents
Gauthaman Kalamegam, Fazal Khan, Shilu Mathew, Mohammed Imran Nasser, Mahmood Rasool, Farid Ahmed, Peter Natesan Pushparaj, Mohammed Al-Qahtani
P115 1q Gain predicts poor prognosis marker for young breast cancer patients
Shereen A Turkistany, Lina M Al-harbi, Ashraf Dallol, Jamal Sabir, Adeel Chaudhary, Adel Abuzenadah
P116 Disorders of sex chromosomes in a diagnostic genomic medicine unit in Saudi Arabia: Prevalence, diagnosis and future guidelines
Basmah Al-Madoudi, Bayan Al-Aslani, Khulud Al-Harbi, Rwan Al-Jahdali, Hanadi Qudaih, Emad Al Hamzy, Mourad Assidi, Mohammed Al Qahtani
P117 Combination of WYE354 and Sunitinib demonstrate synergistic inhibition of acute myeloid leukemia in vitro
Asad M Ilyas, Youssri Ahmed, Mamdooh Gari, Farid Ahmed, Mohammed Alqahtani
P118 Integrated use of evolutionary information in GWAS reveals important SNPs in Asthma
Nada Salem, Sajjad Karim, Elham M Alhathli, Heba Abusamra, Hend F Nour Eldin, Mohammed H Al-Qahtani, Sudhir Kumar
P119 Assessment of BRAF, IDH1, IDH2, and EGFR mutations in a series of primary brain tumors
Fatima Al-Adwani, Deema Hussein, Mona Al-Sharif, Awatif Jamal, Fahad Al-Ghamdi, Jaudah Al-Maghrabi, Saleh S Baeesa, Mohammed Bangash, Adeel Chaudhary, Mohammed Al-Qahtani, Hans-Juergen Schulten
P120 Expression profiles distinguish oligodendrogliomas from glioblastoma multiformes with or without oligodendroglioma component
Alaa Alamandi, Reem Alotibi, Deema Hussein, Sajjad Karim, Jaudah Al-Maghrabi, Fahad Al-Ghamdi, Awatif Jamal, Saleh S Baeesa, Mohammed Bangash, Adeel Chaudhary, Hans-Juergen Schulten, Mohammed Al-Qahtani
P121 Hierarchical clustering in thyroid goiters and hyperplastic lesions
Ohoud Subhi, Nadia Bagatian, Sajjad Karim, Adel Al-Johari, Osman Abdel Al-Hamour, Hosam Al-Aradati, Abdulmonem Al-Mutawa, Faisal Al-Mashat, Jaudah Al-Maghrabi, Hans-Juergen Schulten, Mohammad Al-Qahtani
P122 Differential expression analysis in thyroiditis and papillary thyroid carcinomas with or without coexisting thyroiditis
Nadia Bagatian, Ohoud Subhi, Sajjad Karim, Adel Al-Johari, Osman Abdel Al-Hamour, Abdulmonem Al-Mutawa, Hosam Al-Aradati, Faisal Al-Mashat, Mohammad Al-Qahtani, Hans-Juergen Schulten, Jaudah Al-Maghrabi
P123 Metagenomic analysis of waste water microbiome in Sausdi Arabia
Muhammad W shah, Muhammad Yasir, Esam I Azhar, Saad Al-Masoodi
P124 Molecular characterization of Helicobacter pylori from faecal samples of Tunisian patients with gastric cancer
Yosr Z Haffani, Msadok Azouz, Emna Khamla, Chaima Jlassi, Ahmed S. Masmoudi, Ameur Cherif, Lassaad Belbahri
P125 Diagnostic application of the oncoscan© panel for the identification of hereditary cancer syndrome
Shadi Al-Khayyat, Roba Attas, Atlal Abu-Sanad, Mohammed Abuzinadah, Adnan MerdadAshraf Dallol, Adeel Chaudhary, Mohammed Al-Qahtani, Adel Abuzenadah
P126 Characterization of clinical and neurocognitive features in a family with a novel OGT gene missense mutation c. 1193G > A/ (p. Ala319Thr)
Habib Bouazzi, Carlos Trujillo, Mohammad Khalid Alwasiyah, Mohammed Al-Qahtani
P127 Case report: a rare homozygous deletion mutation of TMEM70 gene associated with 3-Methylglutaconic Aciduria and cataract in a Saudi patient
Maha Alotaibi, Rami Nassir
P128 Isolation and purification of antimicrobial milk proteins
Ishfaq A Sheikh, Mohammad A Kamal, Essam H Jiffri, Ghulam M Ashraf, Mohd A Beg
P129 Integrated analysis reveals association of ATP8B1 gene with colorectal cancer
Mohammad A Aziz, Rizwan Ali, Mahmood Rasool, Mohammad S Jamal, Nusaibah samman, Ghufrana Abdussami, Sathish Periyasamy, Mohiuddin K Warsi, Mohammed Aldress, Majed Al Otaibi, Zeyad Al Yousef, Mohamed Boudjelal, Abdelbasit Buhmeida, Mohammed H Al-Qahtani, Ibrahim AlAbdulkarim
P130 Implication of IL-10 and IL-28 polymorphism with successful anti-HCV therapy and viral clearance
Rubi Ghazala, Shilu Mathew, M. Haroon Hamed, Mourad Assidi, Mohammed Al-Qahtani, Ishtiaq Qadri
P131 Interactions of endocrine disruptor di-(2-ethylhexyl) phthalate (DEHP) and its metabolite mono-2-ethylhexyl phthalate (MEHP) with progesterone receptor
Ishfaq A Sheikh, Muhammad Abu-Elmagd, Rola F Turki, Ghazi A Damanhouri, Mohd A. Beg
P132 Association of HCV nucleotide polymorphism in the development of hepatocellular carcinoma
Mohd Suhail, Abid Qureshi, Adil Jamal, Peter Natesan Pushparaj, Mohammad Al-Qahtani, Ishtiaq Qadri
P133 Gene expression profiling by DNA microarrays in colon cancer treated with chelidonine alkaloid
Mahmoud Z El-Readi, Safaa Y Eid, Michael Wink
P134 Successful in vitro fertilization after eight failed trials
Ahmed M. Isa, Lulu Alnuaim, Johara Almutawa, Basim Abu-Rafae, Saleh Alasiri, Saleh Binsaleh
P135 Genetic sensitivity analysis using SCGE, cell cycle and mitochondrial membrane potential in OPs stressed leukocytes in Rattus norvegicus through flow cytometric input
Nazia Nazam, Mohamad I Lone, Waseem Ahmad, Shakeel A Ansari, Mohamed H Alqahtani
doi:10.1186/s12864-016-2858-0
PMCID: PMC4959372  PMID: 27454254
2.  Fine-Scale Variation and Genetic Determinants of Alternative Splicing across Individuals 
PLoS Genetics  2009;5(12):e1000766.
Recently, thanks to the increasing throughput of new technologies, we have begun to explore the full extent of alternative pre–mRNA splicing (AS) in the human transcriptome. This is unveiling a vast layer of complexity in isoform-level expression differences between individuals. We used previously published splicing sensitive microarray data from lymphoblastoid cell lines to conduct an in-depth analysis on splicing efficiency of known and predicted exons. By combining publicly available AS annotation with a novel algorithm designed to search for AS, we show that many real AS events can be detected within the usually unexploited, speculative majority of the array and at significance levels much below standard multiple-testing thresholds, demonstrating that the extent of cis-regulated differential splicing between individuals is potentially far greater than previously reported. Specifically, many genes show subtle but significant genetically controlled differences in splice-site usage. PCR validation shows that 42 out of 58 (72%) candidate gene regions undergo detectable AS, amounting to the largest scale validation of isoform eQTLs to date. Targeted sequencing revealed a likely causative SNP in most validated cases. In all 17 incidences where a SNP affected a splice-site region, in silico splice-site strength modeling correctly predicted the direction of the micro-array and PCR results. In 13 other cases, we identified likely causative SNPs disrupting predicted splicing enhancers. Using Fst and REHH analysis, we uncovered significant evidence that 2 putative causative SNPs have undergone recent positive selection. We verified the effect of five SNPs using in vivo minigene assays. This study shows that splicing differences between individuals, including quantitative differences in isoform ratios, are frequent in human populations and that causative SNPs can be identified using in silico predictions. Several cases affected disease-relevant genes and it is likely some of these differences are involved in phenotypic diversity and susceptibility to complex diseases.
Author Summary
Alternative splicing (AS), through the alternative use of exons, can produce many different mRNA transcripts from the same genomic locus, thus possibly resulting in the production of many different proteins. We know that splicing differences between individuals exist and that these changes are often associated with genetic variants. Thus far, very few of these associations have led to the precise localization of the causative polymorphisms. In this work, using in-depth analysis of previously published splicing sensitive micro-array data from human cell lines, we identified and validated a large number of splicing changes which are highly correlated with nearby genetic variations. We then sequenced the genomic DNA around candidate exons and used in silico modeling tools to identify causative SNPs for most of our candidates. Using a plasmid reporter construct, we further demonstrated that five selected SNPs reproduce the expected effect in vivo. Our results indicate that genetically controlled splicing differences between individuals may be more common than previously suggested and can be very subtle; and most are caused by SNPs affecting either the splice-site region or exonic splicing enhancers (ESEs) sequences.
doi:10.1371/journal.pgen.1000766
PMCID: PMC2780703  PMID: 20011102
3.  Genome-Wide Associations of Gene Expression Variation in Humans 
PLoS Genetics  2005;1(6):e78.
The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12–13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.
Synopsis
With the finished reference sequence of the human genome now available, focus has shifted towards trying to identify all of the functional elements within the sequence. Although quite a lot of progress has been made towards identifying some classes of genomic elements, in particular protein-coding sequences, the characterization of regulatory elements remains a challenge. The authors describe the genetic mapping of regions of the genome that have functional effects on quantitative levels of gene expression. Gene expression of 630 genes was measured in cell lines derived from 60 unrelated human individuals, the same Utah residents of Northern and Western European ancestry that have been genetically well-characterized by The International HapMap Project. This paper reports significant variation among individuals with respect to levels of gene expression, and demonstrates that this quantitative trait has a genetic basis. For some genes, the genetic signal was localized to specific locations in the human genome sequence; in most cases the genomic region associated with expression variation was physically close to the gene whose expression it regulated. The authors demonstrate the feasibility of performing whole-genome association scans to map quantitative traits, and highlight statistical issues that are increasingly important for whole-genome disease mapping studies.
doi:10.1371/journal.pgen.0010078
PMCID: PMC1315281  PMID: 16362079
4.  In Silico Detection of Sequence Variations Modifying Transcriptional Regulation 
Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation.
Author Summary
DNA sequence variations (polymorphisms) that affect the expression levels of genes play important roles in the pathogenesis of many complex diseases. Compared with genetic variations that alter the amino acid sequences of encoded proteins, which are relatively easy to identify, sequence variants that affect the regulation of genes are difficult to pinpoint among the large amount of nonfunctional polymorphisms located in the vicinity of genes. Computational methods to distinguish functional from neutral variations could therefore prove useful to direct limited laboratory resources to sites most likely to exhibit a phenotypic effect. In this paper we present a Web-based tool for the identification of genetic variation in potential transcription factor binding sites. This tool can be used by any scientist interested in the characterization of regulatory polymorphisms. Using experimentally verified regulatory polymorphisms and background data collected from the literature, we evaluate the method's capacity to identify regulatory genetic variation, and we discuss the limitations of its application.
doi:10.1371/journal.pcbi.0040005
PMCID: PMC2211530  PMID: 18208319
5.  DNA sequence polymorphisms in a panel of eight candidate bovine imprinted genes and their association with performance traits in Irish Holstein-Friesian cattle 
BMC Genetics  2010;11:93.
Background
Studies in mice and humans have shown that imprinted genes, whereby expression from one of the two parentally inherited alleles is attenuated or completely silenced, have a major effect on mammalian growth, metabolism and physiology. More recently, investigations in livestock species indicate that genes subject to this type of epigenetic regulation contribute to, or are associated with, several performance traits, most notably muscle mass and fat deposition. In the present study, a candidate gene approach was adopted to assess 17 validated single nucleotide polymorphisms (SNPs) and their association with a range of performance traits in 848 progeny-tested Irish Holstein-Friesian artificial insemination sires. These SNPs are located proximal to, or within, the bovine orthologs of eight genes (CALCR, GRB10, PEG3, PHLDA2, RASGRF1, TSPAN32, ZIM2 and ZNF215) that have been shown to be imprinted in cattle or in at least one other mammalian species (i.e. human/mouse/pig/sheep).
Results
Heterozygosities for all SNPs analysed ranged from 0.09 to 0.46 and significant deviations from Hardy-Weinberg proportions (P ≤ 0.01) were observed at four loci. Phenotypic associations (P ≤ 0.05) were observed between nine SNPs proximal to, or within, six of the eight analysed genes and a number of performance traits evaluated, including milk protein percentage, somatic cell count, culled cow and progeny carcass weight, angularity, body conditioning score, progeny carcass conformation, body depth, rump angle, rump width, animal stature, calving difficulty, gestation length and calf perinatal mortality. Notably, SNPs within the imprinted paternally expressed gene 3 (PEG3) gene cluster were associated (P ≤ 0.05) with calving, calf performance and fertility traits, while a single SNP in the zinc finger protein 215 gene (ZNF215) was associated with milk protein percentage (P ≤ 0.05), progeny carcass weight (P ≤ 0.05), culled cow carcass weight (P ≤ 0.01), angularity (P ≤ 0.01), body depth (P ≤ 0.01), rump width (P ≤ 0.01) and animal stature (P ≤ 0.01).
Conclusions
Of the eight candidate bovine imprinted genes assessed, DNA sequence polymorphisms in six of these genes (CALCR, GRB10, PEG3, RASGRF1, ZIM2 and ZNF215) displayed associations with several of the phenotypes included for analyses. The genotype-phenotype associations detected here are further supported by the biological function of these six genes, each of which plays important roles in mammalian growth, development and physiology. The associations between SNPs within the imprinted PEG3 gene cluster and traits related to calving, calf performance and gestation length suggest that this domain on chromosome 18 may play a role regulating pre-natal growth and development and fertility. SNPs within the bovine ZNF215 gene were associated with bovine growth and body conformation traits and studies in humans have revealed that the human ZNF215 ortholog belongs to the imprinted gene cluster associated with Beckwith-Wiedemann syndrome--a genetic disorder characterised by growth abnormalities. Similarly, the data presented here suggest that the ZNF215 gene may have an important role in regulating bovine growth. Collectively, our results support previous work showing that (candidate) imprinted genes/loci contribute to heritable variation in bovine performance traits and suggest that DNA sequence polymorphisms within these genes/loci represents an important reservoir of genomic markers for future genetic improvement of dairy and beef cattle populations.
doi:10.1186/1471-2156-11-93
PMCID: PMC2965127  PMID: 20942903
6.  Human genome meeting 2016 
Srivastava, A. K. | Wang, Y. | Huang, R. | Skinner, C. | Thompson, T. | Pollard, L. | Wood, T. | Luo, F. | Stevenson, R. | Polimanti, R. | Gelernter, J. | Lin, X. | Lim, I. Y. | Wu, Y. | Teh, A. L. | Chen, L. | Aris, I. M. | Soh, S. E. | Tint, M. T. | MacIsaac, J. L. | Yap, F. | Kwek, K. | Saw, S. M. | Kobor, M. S. | Meaney, M. J. | Godfrey, K. M. | Chong, Y. S. | Holbrook, J. D. | Lee, Y. S. | Gluckman, P. D. | Karnani, N. | Kapoor, A. | Lee, D. | Chakravarti, A. | Maercker, C. | Graf, F. | Boutros, M. | Stamoulis, G. | Santoni, F. | Makrythanasis, P. | Letourneau, A. | Guipponi, M. | Panousis, N. | Garieri, M. | Ribaux, P. | Falconnet, E. | Borel, C. | Antonarakis, S. E. | Kumar, S. | Curran, J. | Blangero, J. | Chatterjee, S. | Kapoor, A. | Akiyama, J. | Auer, D. | Berrios, C. | Pennacchio, L. | Chakravarti, A. | Donti, T. R. | Cappuccio, G. | Miller, M. | Atwal, P. | Kennedy, A. | Cardon, A. | Bacino, C. | Emrick, L. | Hertecant, J. | Baumer, F. | Porter, B. | Bainbridge, M. | Bonnen, P. | Graham, B. | Sutton, R. | Sun, Q. | Elsea, S. | Hu, Z. | Wang, P. | Zhu, Y. | Zhao, J. | Xiong, M. | Bennett, David A. | Hidalgo-Miranda, A. | Romero-Cordoba, S. | Rodriguez-Cuevas, S. | Rebollar-Vega, R. | Tagliabue, E. | Iorio, M. | D’Ippolito, E. | Baroni, S. | Kaczkowski, B. | Tanaka, Y. | Kawaji, H. | Sandelin, A. | Andersson, R. | Itoh, M. | Lassmann, T. | Hayashizaki, Y. | Carninci, P. | Forrest, A. R. R. | Semple, C. A. | Rosenthal, E. A. | Shirts, B. | Amendola, L. | Gallego, C. | Horike-Pyne, M. | Burt, A. | Robertson, P. | Beyers, P. | Nefcy, C. | Veenstra, D. | Hisama, F. | Bennett, R. | Dorschner, M. | Nickerson, D. | Smith, J. | Patterson, K. | Crosslin, D. | Nassir, R. | Zubair, N. | Harrison, T. | Peters, U. | Jarvik, G. | Menghi, F. | Inaki, K. | Woo, X. | Kumar, P. | Grzeda, K. | Malhotra, A. | Kim, H. | Ucar, D. | Shreckengast, P. | Karuturi, K. | Keck, J. | Chuang, J. | Liu, E. T. | Ji, B. | Tyler, A. | Ananda, G. | Carter, G. | Nikbakht, H. | Montagne, M. | Zeinieh, M. | Harutyunyan, A. | Mcconechy, M. | Jabado, N. | Lavigne, P. | Majewski, J. | Goldstein, J. B. | Overman, M. | Varadhachary, G. | Shroff, R. | Wolff, R. | Javle, M. | Futreal, A. | Fogelman, D. | Bravo, L. | Fajardo, W. | Gomez, H. | Castaneda, C. | Rolfo, C. | Pinto, J. A. | Akdemir, K. C. | Chin, L. | Futreal, A. | Patterson, S. | Statz, C. | Mockus, S. | Nikolaev, S. N. | Bonilla, X. I. | Parmentier, L. | King, B. | Bezrukov, F. | Kaya, G. | Zoete, V. | Seplyarskiy, V. | Sharpe, H. | McKee, T. | Letourneau, A. | Ribaux, P. | Popadin, K. | Basset-Seguin, N. | Chaabene, R. Ben | Santoni, F. | Andrianova, M. | Guipponi, M. | Garieri, M. | Verdan, C. | Grosdemange, K. | Sumara, O. | Eilers, M. | Aifantis, I. | Michielin, O. | de Sauvage, F. | Antonarakis, S. | Likhitrattanapisal, S. | Lincoln, S. | Kurian, A. | Desmond, A. | Yang, S. | Kobayashi, Y. | Ford, J. | Ellisen, L. | Peters, T. L. | Alvarez, K. R. | Hollingsworth, E. F. | Lopez-Terrada, D. H. | Hastie, A. | Dzakula, Z. | Pang, A. W. | Lam, E. T. | Anantharaman, T. | Saghbini, M. | Cao, H. | Gonzaga-Jauregui, C. | Ma, L. | King, A. | Rosenzweig, E. Berman | Krishnan, U. | Reid, J. G. | Overton, J. D. | Dewey, F. | Chung, W. K. | Small, K. | DeLuca, A. | Cremers, F. | Lewis, R. A. | Puech, V. | Bakall, B. | Silva-Garcia, R. | Rohrschneider, K. | Leys, M. | Shaya, F. S. | Stone, E. | Sobreira, N. L. | Schiettecatte, F. | Ling, H. | Pugh, E. | Witmer, D. | Hetrick, K. | Zhang, P. | Doheny, K. | Valle, D. | Hamosh, A. | Jhangiani, S. N. | Akdemir, Z. Coban | Bainbridge, M. N. | Charng, W. | Wiszniewski, W. | Gambin, T. | Karaca, E. | Bayram, Y. | Eldomery, M. K. | Posey, J. | Doddapaneni, H. | Hu, J. | Sutton, V. R. | Muzny, D. M. | Boerwinkle, E. A. | Valle, D. | Lupski, J. R. | Gibbs, R. A. | Shekar, S. | Salerno, W. | English, A. | Mangubat, A. | Bruestle, J. | Thorogood, A. | Knoppers, B. M. | Takahashi, H. | Nitta, K. R. | Kozhuharova, A. | Suzuki, A. M. | Sharma, H. | Cotella, D. | Santoro, C. | Zucchelli, S. | Gustincich, S. | Carninci, P. | Mulvihill, J. J. | Baynam, G. | Gahl, W. | Groft, S. C. | Kosaki, K. | Lasko, P. | Melegh, B. | Taruscio, D. | Ghosh, R. | Plon, S. | Scherer, S. | Qin, X. | Sanghvi, R. | Walker, K. | Chiang, T. | Muzny, D. | Wang, L. | Black, J. | Boerwinkle, E. | Weinshilboum, R. | Gibbs, R. | Karpinets, T. | Calderone, T. | Wani, K. | Yu, X. | Creasy, C. | Haymaker, C. | Forget, M. | Nanda, V. | Roszik, J. | Wargo, J. | Haydu, L. | Song, X. | Lazar, A. | Gershenwald, J. | Davies, M. | Bernatchez, C. | Zhang, J. | Futreal, A. | Woodman, S. | Chesler, E. J. | Reynolds, T. | Bubier, J. A. | Phillips, C. | Langston, M. A. | Baker, E. J. | Xiong, M. | Ma, L. | Lin, N. | Amos, C. | Lin, N. | Wang, P. | Zhu, Y. | Zhao, J. | Calhoun, V. | Xiong, M. | Dobretsberger, O. | Egger, M. | Leimgruber, F. | Sadedin, S. | Oshlack, A. | Antonio, V. A. A. | Ono, N. | Ahmed, Z. | Bolisetty, M. | Zeeshan, S. | Anguiano, E. | Ucar, D. | Sarkar, A. | Nandineni, M. R. | Zeng, C. | Shao, J. | Cao, H. | Hastie, A. | Pang, A. W. | Lam, E. T. | Liang, T. | Pham, K. | Saghbini, M. | Dzakula, Z. | Chee-Wei, Y. | Dongsheng, L. | Lai-Ping, W. | Lian, D. | Hee, R. O. Twee | Yunus, Y. | Aghakhanian, F. | Mokhtar, S. S. | Lok-Yung, C. V. | Bhak, J. | Phipps, M. | Shuhua, X. | Yik-Ying, T. | Kumar, V. | Boon-Peng, H. | Campbell, I. | Young, M. -A. | James, P. | Rain, M. | Mohammad, G. | Kukreti, R. | Pasha, Q. | Akilzhanova, A. R. | Guelly, C. | Abilova, Z. | Rakhimova, S. | Akhmetova, A. | Kairov, U. | Trajanoski, S. | Zhumadilov, Z. | Bekbossynova, M. | Schumacher, C. | Sandhu, S. | Harkins, T. | Makarov, V. | Doddapaneni, H. | Glenn, R. | Momin, Z. | Dilrukshi, B. | Chao, H. | Meng, Q. | Gudenkauf, B. | Kshitij, R. | Jayaseelan, J. | Nessner, C. | Lee, S. | Blankenberg, K. | Lewis, L. | Hu, J. | Han, Y. | Dinh, H. | Jireh, S. | Walker, K. | Boerwinkle, E. | Muzny, D. | Gibbs, R. | Hu, J. | Walker, K. | Buhay, C. | Liu, X. | Wang, Q. | Sanghvi, R. | Doddapaneni, H. | Ding, Y. | Veeraraghavan, N. | Yang, Y. | Boerwinkle, E. | Beaudet, A. L. | Eng, C. M. | Muzny, D. M. | Gibbs, R. A. | Worley, K. C. C. | Liu, Y. | Hughes, D. S. T. | Murali, S. C. | Harris, R. A. | English, A. C. | Qin, X. | Hampton, O. A. | Larsen, P. | Beck, C. | Han, Y. | Wang, M. | Doddapaneni, H. | Kovar, C. L. | Salerno, W. J. | Yoder, A. | Richards, S. | Rogers, J. | Lupski, J. R. | Muzny, D. M. | Gibbs, R. A. | Meng, Q. | Bainbridge, M. | Wang, M. | Doddapaneni, H. | Han, Y. | Muzny, D. | Gibbs, R. | Harris, R. A. | Raveenedran, M. | Xue, C. | Dahdouli, M. | Cox, L. | Fan, G. | Ferguson, B. | Hovarth, J. | Johnson, Z. | Kanthaswamy, S. | Kubisch, M. | Platt, M. | Smith, D. | Vallender, E. | Wiseman, R. | Liu, X. | Below, J. | Muzny, D. | Gibbs, R. | Yu, F. | Rogers, J. | Lin, J. | Zhang, Y. | Ouyang, Z. | Moore, A. | Wang, Z. | Hofmann, J. | Purdue, M. | Stolzenberg-Solomon, R. | Weinstein, S. | Albanes, D. | Liu, C. S. | Cheng, W. L. | Lin, T. T. | Lan, Q. | Rothman, N. | Berndt, S. | Chen, E. S. | Bahrami, H. | Khoshzaban, A. | Keshal, S. Heidari | Bahrami, H. | Khoshzaban, A. | Keshal, S. Heidari | Alharbi, K. K. R. | Zhalbinova, M. | Akilzhanova, A. | Rakhimova, S. | Bekbosynova, M. | Myrzakhmetova, S. | Matar, M. | Mili, N. | Molinari, R. | Ma, Y. | Guerrier, S. | Elhawary, N. | Tayeb, M. | Bogari, N. | Qotb, N. | McClymont, S. A. | Hook, P. W. | Goff, L. A. | McCallion, A. | Kong, Y. | Charette, J. R. | Hicks, W. L. | Naggert, J. K. | Zhao, L. | Nishina, P. M. | Edrees, B. M. | Athar, M. | Al-Allaf, F. A. | Taher, M. M. | Khan, W. | Bouazzaoui, A. | Harbi, N. A. | Safar, R. | Al-Edressi, H. | Anazi, A. | Altayeb, N. | Ahmed, M. A. | Alansary, K. | Abduljaleel, Z. | Kratz, A. | Beguin, P. | Poulain, S. | Kaneko, M. | Takahiko, C. | Matsunaga, A. | Kato, S. | Suzuki, A. M. | Bertin, N. | Lassmann, T. | Vigot, R. | Carninci, P. | Plessy, C. | Launey, T. | Graur, D. | Lee, D. | Kapoor, A. | Chakravarti, A. | Friis-Nielsen, J. | Izarzugaza, J. M. | Brunak, S. | Chakraborty, A. | Basak, J. | Mukhopadhyay, A. | Soibam, B. S. | Das, D. | Biswas, N. | Das, S. | Sarkar, S. | Maitra, A. | Panda, C. | Majumder, P. | Morsy, H. | Gaballah, A. | Samir, M. | Shamseya, M. | Mahrous, H. | Ghazal, A. | Arafat, W. | Hashish, M. | Gruber, J. J. | Jaeger, N. | Snyder, M. | Patel, K. | Bowman, S. | Davis, T. | Kraushaar, D. | Emerman, A. | Russello, S. | Henig, N. | Hendrickson, C. | Zhang, K. | Rodriguez-Dorantes, M. | Cruz-Hernandez, C. D. | Garcia-Tobilla, C. D. P. | Solorzano-Rosales, S. | Jäger, N. | Chen, J. | Haile, R. | Hitchins, M. | Brooks, J. D. | Snyder, M. | Jiménez-Morales, S. | Ramírez, M. | Nuñez, J. | Bekker, V. | Leal, Y. | Jiménez, E. | Medina, A. | Hidalgo, A. | Mejía, J. | Halytskiy, V. | Naggert, J. | Collin, G. B. | DeMauro, K. | Hanusek, R. | Nishina, P. M. | Belhassa, K. | Belhassan, K. | Bouguenouch, L. | Samri, I. | Sayel, H. | moufid, FZ. | El Bouchikhi, I. | Trhanint, S. | Hamdaoui, H. | Elotmani, I. | Khtiri, I. | Kettani, O. | Quibibo, L. | Ahagoud, M. | Abbassi, M. | Ouldim, K. | Marusin, A. V. | Kornetov, A. N. | Swarovskaya, M. | Vagaiceva, K. | Stepanov, V. | De La Paz, E. M. Cutiongco | Sy, R. | Nevado, J. | Reganit, P. | Santos, L. | Magno, J. D. | Punzalan, F. E. | Ona, D. | Llanes, E. | Santos-Cortes, R. L. | Tiongco, R. | Aherrera, J. | Abrahan, L. | Pagauitan-Alan, P. | Morelli, K. H. | Domire, J. S. | Pyne, N. | Harper, S. | Burgess, R. | Zhalbinova, M. | Akilzhanova, A. | Rakhimova, S. | Bekbosynova, M. | Myrzakhmetova, S. | Gari, M. A. | Dallol, A. | Alsehli, H. | Gari, A. | Gari, M. | Abuzenadah, A. | Thomas, M. | Sukhai, M. | Garg, S. | Misyura, M. | Zhang, T. | Schuh, A. | Stockley, T. | Kamel-Reid, S. | Sherry, S. | Xiao, C. | Slotta, D. | Rodarmer, K. | Feolo, M. | Kimelman, M. | Godynskiy, G. | O’Sullivan, C. | Yaschenko, E. | Xiao, C. | Yaschenko, E. | Sherry, S. | Rangel-Escareño, C. | Rueda-Zarate, H. | Tayubi, I. A. | Mohammed, R. | Ahmed, I. | Ahmed, T. | Seth, S. | Amin, S. | Song, X. | Mao, X. | Sun, H. | Verhaak, R. G. | Futreal, A. | Zhang, J. | Whiite, S. J. | Chiang, T. | English, A. | Farek, J. | Kahn, Z. | Salerno, W. | Veeraraghavan, N. | Boerwinkle, E. | Gibbs, R. | Kasukawa, T. | Lizio, M. | Harshbarger, J. | Hisashi, S. | Severin, J. | Imad, A. | Sahin, S. | Freeman, T. C. | Baillie, K. | Sandelin, A. | Carninci, P. | Forrest, A. R. R. | Kawaji, H. | Salerno, W. | English, A. | Shekar, S. N. | Mangubat, A. | Bruestle, J. | Boerwinkle, E. | Gibbs, R. A. | Salem, A. H. | Ali, M. | Ibrahim, A. | Ibrahim, M. | Barrera, H. A. | Garza, L. | Torres, J. A. | Barajas, V. | Ulloa-Aguirre, A. | Kershenobich, D. | Mortaji, Shahroj | Guizar, Pedro | Loera, Eliezer | Moreno, Karen | De León, Adriana | Monsiváis, Daniela | Gómez, Jackeline | Cardiel, Raquel | Fernandez-Lopez, J. C. | Bonifaz-Peña, V. | Rangel-Escareño, C. | Hidalgo-Miranda, A. | Contreras, A. V. | Polfus, L. | Wang, X. | Philip, V. | Carter, G. | Abuzenadah, A. A. | Gari, M. | Turki, R. | Dallol, A. | Uyar, A. | Kaygun, A. | Zaman, S. | Marquez, E. | George, J. | Ucar, D. | Hendrickson, C. L. | Emerman, A. | Kraushaar, D. | Bowman, S. | Henig, N. | Davis, T. | Russello, S. | Patel, K. | Starr, D. B. | Baird, M. | Kirkpatrick, B. | Sheets, K. | Nitsche, R. | Prieto-Lafuente, L. | Landrum, M. | Lee, J. | Rubinstein, W. | Maglott, D. | Thavanati, P. K. R. | de Dios, A. Escoto | Hernandez, R. E. Navarro | Aldrate, M. E. Aguilar | Mejia, M. R. Ruiz | Kanala, K. R. R. | Abduljaleel, Z. | Khan, W. | Al-Allaf, F. A. | Athar, M. | Taher, M. M. | Shahzad, N. | Bouazzaoui, A. | Huber, E. | Dan, A. | Al-Allaf, F. A. | Herr, W. | Sprotte, G. | Köstler, J. | Hiergeist, A. | Gessner, A. | Andreesen, R. | Holler, E. | Al-Allaf, F. | Alashwal, A. | Abduljaleel, Z. | Taher, M. | Bouazzaoui, A. | Abalkhail, H. | Al-Allaf, A. | Bamardadh, R. | Athar, M. | Filiptsova, O. | Kobets, M. | Kobets, Y. | Burlaka, I. | Timoshyna, I. | Filiptsova, O. | Kobets, M. N. | Kobets, Y. | Burlaka, I. | Timoshyna, I. | Filiptsova, O. | Kobets, M. N. | Kobets, Y. | Burlaka, I. | Timoshyna, I. | Al-allaf, F. A. | Mohiuddin, M. T. | Zainularifeen, A. | Mohammed, A. | Abalkhail, H. | Owaidah, T. | Bouazzaoui, A.
Human Genomics  2016;10(Suppl 1):12.
Table of contents
O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder
A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson
O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents
R. Polimanti, J. Gelernter
O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort
X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group
O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus
A. Kapoor, D. Lee, A. Chakravarti
O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells
C. Maercker, F. Graf, M. Boutros
O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies
G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis
O7 Role of microRNA in LCL to IPSC reprogramming
S. Kumar, J. Curran, J. Blangero
O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease
S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti
O9 Metabolomic profiling for the diagnosis of neurometabolic disorders
T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea
O10 A novel causal methylation network approach to Alzheimer’s disease
Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett
O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway
A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni
O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types
B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest
O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types
C. A. Semple
O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer
E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project
O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer
F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu
O16 Modeling genetic interactions associated with molecular subtypes of breast cancer
B. Ji, A. Tyler, G. Ananda, G. Carter
O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors
H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski
O18 Predictive biomarkers to metastatic pancreatic cancer treatment
J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman
O19 DDIT4 gene expression as a prognostic marker in several malignant tumors
L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto
O20 Spatial organization of the genome and genomic alterations in human cancers
K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group
O21 Landscape of targeted therapies in solid tumors
S. Patterson, C. Statz, S. Mockus
O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma
S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis
O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis
S. Likhitrattanapisal
O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study
S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen
O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array
T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada
O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation
A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics
O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4
C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung
O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13
K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone
O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data
N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh
O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review
S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs
O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio
S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle
O32 Legal interoperability: a sine qua non for international data sharing
A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group
O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target
H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci
O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs
J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio
O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes
R. Ghosh, S. Plon
O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing
S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs
O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma
T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman
O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver
E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker
O40 A general statistic framework for genome-based disease risk prediction
M. Xiong, L. Ma, N. Lin, C. Amos
O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies
N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong
O42 Big data and NGS data analysis: the cloud to the rescue
O. Dobretsberger, M. Egger, F. Leimgruber
O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing
S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance
O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data
V. A. A. Antonio, N. Ono, Clark Kendrick C. Go
O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data
Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar
O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans
C. Zeng, J. Shao
O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations
H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula
O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing
Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng
O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes?
I. Campbell, M.-A. Young, P. James, Lifepool
O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS
C. Schumacher, S. Sandhu, T. Harkins, V. Makarov
O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform
H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs
O55 Rapid capture methods for clinical sequencing
J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs
O56 A diploid personal human genome model for better genomes from diverse sequence data
K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs
O57 Development of PacBio long range capture for detection of pathogenic structural variants
Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs
O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans
R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers
O59 Assessing RNA structure disruption induced by single-nucleotide variation
J. Lin, Y. Zhang, Z. Ouyang
P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number
A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt
P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility
E. S. Chen
P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients
H. Bahrami, A. Khoshzaban, S. Heidari Keshal
P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population
K. K. R. Alharbi
P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding
M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova
P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population
M. Matar
P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization
N. Mili, R. Molinari, Y. Ma, S. Guerrier
P9 Vulnerability of genetic variants to the risk of autism among Saudi children
N. Elhawary, M. Tayeb, N. Bogari, N. Qotb
P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction
S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion
P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3rd7 mice
Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina
P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients
B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel
P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments
A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey
P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome
D. Graur
P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients
J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak
P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns
B. S. Soibam
P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer
D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder
P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes
J. J. Gruber, N. Jaeger, M. Snyder
P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors
K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson
P23 RNA sequencing identifies gene mutations for neuroblastoma
K. Zhang
P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines
M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales
P25 Targeted Methylation Sequencing of Prostate Cancer
N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder
P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico
S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía
P28 Genetic modifiers of Alström syndrome
J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina
P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos
E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group
P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D
K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess
P34 Molecular regulation of chondrogenic human induced pluripotent stem cells
M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah
P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting
M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid
P36 Accessing genomic evidence for clinical variants at NCBI
S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko
P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA
C. Xiao, E. Yaschenko, S. Sherry
P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling
C. Rangel-Escareño, H. Rueda-Zarate
P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr
S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang
P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data
S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs
P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells
T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium
P43 Rapid and scalable typing of structural variants for disease cohorts
W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs
P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population
A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim
P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations
J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras
P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits
L. Polfus, CHARGE and NHLBI Exome Sequence Project Working Groups
P48 Association of adipoq gene with type 2 diabetes and related phenotypes in african american men and women: The jackson heart study
S. Davis, R. Xu, S. Gebeab, P Riestra, A Gaye, R. Khan, J. Wilson, A. Bidulescu
P49 Common variants in casr gene are associated with serum calcium levels in koreans
S. H. Jung, N. Vinayagamoorthy, S. H. Yim, Y. J. Chung
P50 Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions
Y. Zhou, S. Xu
P51 A Bayesian framework for generalized linear mixed models in genome-wide association studies
X. Wang, V. Philip, G. Carter
P52 Targeted sequencing approach for the identification of the genetic causes of hereditary hearing impairment
A. A. Abuzenadah, M. Gari, R. Turki, A. Dallol
P53 Identification of enhancer sequences by ATAC-seq open chromatin profiling
A. Uyar, A. Kaygun, S. Zaman, E. Marquez, J. George, D. Ucar
P54 Direct enrichment for the rapid preparation of targeted NGS libraries
C. L. Hendrickson, A. Emerman, D. Kraushaar, S. Bowman, N. Henig, T. Davis, S. Russello, K. Patel
P56 Performance of the Agilent D5000 and High Sensitivity D5000 ScreenTape assays for the Agilent 4200 Tapestation System
R. Nitsche, L. Prieto-Lafuente
P57 ClinVar: a multi-source archive for variant interpretation
M. Landrum, J. Lee, W. Rubinstein, D. Maglott
P59 Association of functional variants and protein physical interactions of human MUTY homolog linked with familial adenomatous polyposis and colorectal cancer syndrome
Z. Abduljaleel, W. Khan, F. A. Al-Allaf, M. Athar , M. M. Taher, N. Shahzad
P60 Modification of the microbiom constitution in the gut using chicken IgY antibodies resulted in a reduction of acute graft-versus-host disease after experimental bone marrow transplantation
A. Bouazzaoui, E. Huber, A. Dan, F. A. Al-Allaf, W. Herr, G. Sprotte, J. Köstler, A. Hiergeist, A. Gessner, R. Andreesen, E. Holler
P61 Compound heterozygous mutation in the LDLR gene in Saudi patients suffering severe hypercholesterolemia
F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Athar
doi:10.1186/s40246-016-0063-5
PMCID: PMC4896275  PMID: 27294413
7.  Rare and Common Regulatory Variation in Population-Scale Sequenced Human Genomes 
PLoS Genetics  2011;7(7):e1002144.
Population-scale genome sequencing allows the characterization of functional effects of a broad spectrum of genetic variants underlying human phenotypic variation. Here, we investigate the influence of rare and common genetic variants on gene expression patterns, using variants identified from sequencing data from the 1000 genomes project in an African and European population sample and gene expression data from lymphoblastoid cell lines. We detect comparable numbers of expression quantitative trait loci (eQTLs) when compared to genotypes obtained from HapMap 3, but as many as 80% of the top expression quantitative trait variants (eQTVs) discovered from 1000 genomes data are novel. The properties of the newly discovered variants suggest that mapping common causal regulatory variants is challenging even with full resequencing data; however, we observe significant enrichment of regulatory effects in splice-site and nonsense variants. Using RNA sequencing data, we show that 46.2% of nonsynonymous variants are differentially expressed in at least one individual in our sample, creating widespread potential for interactions between functional protein-coding and regulatory variants. We also use allele-specific expression to identify putative rare causal regulatory variants. Furthermore, we demonstrate that outlier expression values can be due to rare variant effects, and we approximate the number of such effects harboured in an individual by effect size. Our results demonstrate that integration of genomic and RNA sequencing analyses allows for the joint assessment of genome sequence and genome function.
Author Summary
The recent availability of almost fully sequenced human genomes by the 1000 genomes project allows the direct study of genetic variants that influence levels of gene expression in the cell. In this study, we explore the effect of rare and common variants on levels of gene expression. We show that the availability of a more comprehensive list of variants brings us closer to the likely causal variants, and we discuss their genomic and evolutionary properties. We also demonstrate the effects of variants that change splicing patterns or length of the protein product, the putative joint impacts of variants that affect gene expression, and those that affect protein structure. Finally, we show the impact of rare regulatory variants that cannot be detected by the conventional methodologies of association and require the interrogation of full genome sequencing and full transcriptome sequencing. These approaches bring us closer to the implementation of these data and methodologies to a direct clinical application.
doi:10.1371/journal.pgen.1002144
PMCID: PMC3141000  PMID: 21811411
8.  Genome-wide survey of allele-specific splicing in humans 
BMC Genomics  2008;9:265.
Background
Accurate mRNA splicing depends on multiple regulatory signals encoded in the transcribed RNA sequence. Many examples of mutations within human splice regulatory regions that alter splicing qualitatively or quantitatively have been reported and allelic differences in mRNA splicing are likely to be a common and important source of phenotypic diversity at the molecular level, in addition to their contribution to genetic disease susceptibility. However, because the effect of a mutation on the efficiency of mRNA splicing is often difficult to predict, many mutations that cause disease through an effect on splicing are likely to remain undiscovered.
Results
We have combined a genome-wide scan for sequence polymorphisms likely to affect mRNA splicing with analysis of publicly available Expressed Sequence Tag (EST) and exon array data. The genome-wide scan uses published tools and identified 30,977 SNPs located within donor and acceptor splice sites, branch points and exonic splicing enhancer elements. For 1,185 candidate splicing polymorphisms the difference in splicing between alternative alleles was corroborated by publicly available exon array data from 166 lymphoblastoid cell lines. We developed a novel probabilistic method to infer allele-specific splicing from EST data. The method uses SNPs and alternative mRNA isoforms mapped to EST sequences and models both regulated alternative splicing as well as allele-specific splicing. We have also estimated heritability of splicing and report that a greater proportion of genes show evidence of splicing heritability than show heritability of overall gene expression level. Our results provide an extensive resource that can be used to assess the possible effect on splicing of human polymorphisms in putative splice-regulatory sites.
Conclusion
We report a set of genes showing evidence of allele-specific splicing from an integrated analysis of genomic polymorphisms, EST data and exon array data, including several examples for which there is experimental evidence of polymorphisms affecting splicing in the literature. We also present a set of novel allele-specific splicing candidates and discuss the strengths and weaknesses of alternative technologies for inferring the effect of sequence variants on mRNA splicing.
doi:10.1186/1471-2164-9-265
PMCID: PMC2427040  PMID: 18518984
9.  Convergence of Mutation and Epigenetic Alterations Identifies Common Genes in Cancer That Predict for Poor Prognosis  
PLoS Medicine  2008;5(5):e114.
Background
The identification and characterization of tumor suppressor genes has enhanced our understanding of the biology of cancer and enabled the development of new diagnostic and therapeutic modalities. Whereas in past decades, a handful of tumor suppressors have been slowly identified using techniques such as linkage analysis, large-scale sequencing of the cancer genome has enabled the rapid identification of a large number of genes that are mutated in cancer. However, determining which of these many genes play key roles in cancer development has proven challenging. Specifically, recent sequencing of human breast and colon cancers has revealed a large number of somatic gene mutations, but virtually all are heterozygous, occur at low frequency, and are tumor-type specific. We hypothesize that key tumor suppressor genes in cancer may be subject to mutation or hypermethylation.
Methods and Findings
Here, we show that combined genetic and epigenetic analysis of these genes reveals many with a higher putative tumor suppressor status than would otherwise be appreciated. At least 36 of the 189 genes newly recognized to be mutated are targets of promoter CpG island hypermethylation, often in both colon and breast cancer cell lines. Analyses of primary tumors show that 18 of these genes are hypermethylated strictly in primary cancers and often with an incidence that is much higher than for the mutations and which is not restricted to a single tumor-type. In the identical breast cancer cell lines in which the mutations were identified, hypermethylation is usually, but not always, mutually exclusive from genetic changes for a given tumor, and there is a high incidence of concomitant loss of expression. Sixteen out of 18 (89%) of these genes map to loci deleted in human cancers. Lastly, and most importantly, the reduced expression of a subset of these genes strongly correlates with poor clinical outcome.
Conclusions
Using an unbiased genome-wide approach, our analysis has enabled the discovery of a number of clinically significant genes targeted by multiple modes of inactivation in breast and colon cancer. Importantly, we demonstrate that a subset of these genes predict strongly for poor clinical outcome. Our data define a set of genes that are targeted by both genetic and epigenetic events, predict for clinical prognosis, and are likely fundamentally important for cancer initiation or progression.
Stephen Baylin and colleagues show that a combined genetic and epigenetic analysis of breast and colon cancers identifies a number of clinically significant genes targeted by multiple modes of inactivation.
Editors' Summary
Background.
Cancer is one of the developed world's biggest killers—over half a million Americans die of cancer each year, for instance. As a result, there is great interest in understanding the genetic and environmental causes of cancer in order to improve cancer prevention, diagnosis, and treatment.
Cancer begins when cells begin to multiply out of control. DNA is the sequence of coded instructions—genes—for how to build and maintain the body. Certain “tumor suppressor” genes, for instance, help to prevent cancer by preventing tumors from developing, but changes that alter the DNA code sequence—mutations—can profoundly affect how a gene works. Modern techniques of genetic analysis have identified genes such as tumor suppressors that, when mutated, are linked to the development of certain cancers.
Why Was This Study Done?
However, in recent years, it has become increasingly apparent that mutations are neither necessary nor sufficient to explain every case of cancer. This has led researchers to look at so-called epigenetic factors, which also alter how a gene works without altering its DNA sequence. An example of this is “methylation,” which prevents a gene from being expressed—deactivates it—by a chemical tag. Methylation of genes is part of the normal functioning of DNA, but abnormal methylation has been linked with cancer, aging, and some rare birth abnormalities.
Previous analysis of DNA from breast and colon cancer cells had revealed 189 “candidate cancer genes”—mutated genes that were linked to the development of breast and colon cancer. However, it was not clear how those mutations gave rise to cancer, and individual mutations were present in only 5% to 15% of specific tumors. The authors of this study wanted to know whether epigenetic factors such as methylation contributed to causing the cancers.
What Did the Researchers Do and Find?
The researchers first identified 56 of the 189 candidate cancer genes as likely tumor suppressors and then determined that 36 of these genes were methylated and deactivated, often in both breast and colon (laboratory-grown) cancer cells. In nearly all cases, the methylated genes were not active but could be reactivated by being demethylated. They further showed that, in normal colon and breast tissue samples, 18 of the 36 genes were unmethylated and functioned normally, but in cells taken from breast and colon cancer tumors they were methylated.
In contrast to the genetic mutations, the 18 genes were frequently methylated across a range of tumor types, and eight genes were methylated in both the breast and colon cancers. The authors found by reviewing the genetics and epigenetics of those 18 genes in breast and colon cancer that they were either mutated, methylated, or both. A literature review showed that at least six of the 18 genes were known to have tumor suppressor properties, and the authors determined that 16 were located in parts of DNA known to be missing from cells taken from a range of cancer tumors.
Finally, the researchers analyzed data on cancer cases to show that methylation of these 18 genes was correlated with reduced function of these genes in tumors and with a greater likelihood that a cancer will be terminal or spread to other parts of the body.
What Do These Findings Mean?
The researchers considered only the 189 candidate cancer genes found in one previous study and not other genes identified elsewhere. They also did not consider the biological effects of the individual mutations found in those genes. Despite this, they have demonstrated that methylation of specific genes is likely to play a role in the development of breast and/or colon cancer cells either together with mutations or independently, most likely by turning off their tumor suppression function.
More broadly, however, the study adds to the evidence that future analysis of the role of genes in cancer should include epigenetic as well as genetic factors. In addition, the authors have also shown that a number of these genes may be useful for predicting clinical outcomes for a range of tumor types.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050114.
A December 2006 PLoS Medicine Perspective article reviews the value of examining methylation as a factor in common cancers and its use for early detection
The Web site of the American Cancer Society has a wealth of information and resources on a variety of cancers, including breast and colon cancer
Breastcancer.org is a nonprofit organization providing information about breast cancer on the Web, including research news
Cancer Research UK provides information on cancer research
The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins publishes background information on the authors' research on methylation, setting out its potential for earlier diagnosis and better treatment of cancer
doi:10.1371/journal.pmed.0050114
PMCID: PMC2429944  PMID: 18507500
10.  Contrasting signals of positive selection in genes involved in human skin-color variation from tests based on SNP scans and resequencing 
Background
Numerous genome-wide scans conducted by genotyping previously ascertained single-nucleotide polymorphisms (SNPs) have provided candidate signatures for positive selection in various regions of the human genome, including in genes involved in pigmentation traits. However, it is unclear how well the signatures discovered by such haplotype-based test statistics can be reproduced in tests based on full resequencing data. Four genes (oculocutaneous albinism II (OCA2), tyrosinase-related protein 1 (TYRP1), dopachrome tautomerase (DCT), and KIT ligand (KITLG)) implicated in human skin-color variation, have shown evidence for positive selection in Europeans and East Asians in previous SNP-scan data. In the current study, we resequenced 4.7 to 6.7 kb of DNA from each of these genes in Africans, Europeans, East Asians, and South Asians.
Results
Applying all commonly used neutrality-test statistics for allele frequency distribution to the newly generated sequence data provided conflicting results regarding evidence for positive selection. Previous haplotype-based findings could not be clearly confirmed. Although some tests were marginally significant for some populations and genes, none of them were significant after multiple-testing correction. Combined P values for each gene-population pair did not improve these results. Application of Approximate Bayesian Computation Markov chain Monte Carlo based to these sequence data using a simple forward simulator revealed broad posterior distributions of the selective parameters for all four genes, providing no support for positive selection. However, when we applied this approach to published sequence data on SLC45A2, another human pigmentation candidate gene, we could readily confirm evidence for positive selection, as previously detected with sequence-based and some haplotype-based tests.
Conclusions
Overall, our data indicate that even genes that are strong biological candidates for positive selection and show reproducible signatures of positive selection in SNP scans do not always show the same replicability of selection signals in other tests, which should be considered in future studies on detecting positive selection in genetic data.
doi:10.1186/2041-2223-2-24
PMCID: PMC3287149  PMID: 22133426
11.  Genetic Modifiers of Neurofibromatosis Type 1-Associated Café-au-Lait Macule Count Identified Using Multi-platform Analysis 
PLoS Genetics  2014;10(10):e1004575.
Neurofibromatosis type 1 (NF1) is an autosomal dominant, monogenic disorder of dysregulated neurocutaneous tissue growth. Pleiotropy, variable expressivity and few NF1 genotype-phenotype correlates limit clinical prognostication in NF1. Phenotype complexity in NF1 is hypothesized to derive in part from genetic modifiers unlinked to the NF1 locus. In this study, we hypothesized that normal variation in germline gene expression confers risk for certain phenotypes in NF1. In a set of 79 individuals with NF1, we examined the association between gene expression in lymphoblastoid cell lines with NF1-associated phenotypes and sequenced select genes with significant phenotype/expression correlations. In a discovery cohort of 89 self-reported European-Americans with NF1 we examined the association between germline sequence variants of these genes with café-au-lait macule (CALM) count, a tractable, tumor-like phenotype in NF1. Two correlated, common SNPs (rs4660761 and rs7161) between DPH2 and ATP6V0B were significantly associated with the CALM count. Analysis with tiled regression also identified SNP rs4660761 as significantly associated with CALM count. SNP rs1800934 and 12 rare variants in the mismatch repair gene MSH6 were also associated with CALM count. Both SNPs rs7161 and rs4660761 (DPH2 and ATP6V0B) were highly significant in a mega-analysis in a combined cohort of 180 self-reported European-Americans; SNP rs1800934 (MSH6) was near-significant in a meta-analysis assuming dominant effect of the minor allele. SNP rs4660761 is predicted to regulate ATP6V0B, a gene associated with melanosome biology. Individuals with homozygous mutations in MSH6 can develop an NF1-like phenotype, including multiple CALMs. Through a multi-platform approach, we identified variants that influence NF1 CALM count.
Author Summary
Neurofibromatosis type 1 (NF1) is a relatively common genetic disease that increases the chance to develop a variety of benign and malignant tumors. People with NF1 also typically feature a large number of birthmarks called café-au-lait macules. It is difficult to predict severity or specific problems in NF1. We sought to identify genes (other than NF1, the gene that causes the disease) that influence severity in NF1. We determined the number of café-au-lait macules in two groups of people with NF1. We measured the gene expression of about 10,000 genes in the cultured white blood cells from one group of people. We then sequenced a group of genes whose expression level was increased in people with higher numbers of café-au-lait macules. In the first group, we found common variants in genes MSH6 and near DPH2 and ATP6V0B that were significantly associated with the number of café-au-lait macules. Some of these variants were close to significant in the second group of people. The two variants near DPH2 and ATP6V0B were very significant when analysed in both groups combined. Our work is among the first to identify genetic variants that influence the severity of NF1.
doi:10.1371/journal.pgen.1004575
PMCID: PMC4199479  PMID: 25329635
12.  Genetic interactions affecting human gene expression identified by variance association mapping 
eLife  2014;3:e01381.
Non-additive interaction between genetic variants, or epistasis, is a possible explanation for the gap between heritability of complex traits and the variation explained by identified genetic loci. Interactions give rise to genotype dependent variance, and therefore the identification of variance quantitative trait loci can be an intermediate step to discover both epistasis and gene by environment effects (GxE). Using RNA-sequence data from lymphoblastoid cell lines (LCLs) from the TwinsUK cohort, we identify a candidate set of 508 variance associated SNPs. Exploiting the twin design we show that GxE plays a role in ∼70% of these associations. Further investigation of these loci reveals 57 epistatic interactions that replicated in a smaller dataset, explaining on average 4.3% of phenotypic variance. In 24 cases, more variance is explained by the interaction than their additive contributions. Using molecular phenotypes in this way may provide a route to uncovering genetic interactions underlying more complex traits.
DOI: http://dx.doi.org/10.7554/eLife.01381.001
eLife digest
Every person has two copies of each gene: one is inherited from their mother and the other from their father. These two copies are often not identical because there can be many different variants of the same gene in the human population. Traits (such as height, body mass and risk of disease) vary from one person to the next—and for many traits this variation depends in part on the different gene variants that each person has inherited. Studies seeking to find the differences in DNA that can predict this variation have often assumed that the changes in DNA act on traits independently of the effect of environment and of other genetic variants.
In contrast, studies with animals have shown that some genetic variants can interact to produce a bigger (or smaller) effect than would be expected from simply ‘adding together’ their individual effects—a phenomenon called epistasis. But how much does epistasis contribute to variation in human traits, if at all? This question has been much disputed, and is difficult to test, not least because of the sheer number of interactions to assess: tens of millions of changes in DNA have been observed in the human genome, and so there are many more than billions of possible combinations of these changes to investigate.
Here, Brown et al. have examined the sequences of all the genes that were expressed in cells taken from a cohort of twins and searched for genetic variants that show these epistatic interactions. By studying gene expression, which can be greatly affected by small changes in the DNA code, Brown et al. were able to identify 508 variants that had a bigger than expected effect on the level of gene expression. This may be a sign that these variants act in combinations: if within one genome a variant increased expression and in another it decreased expression, then this would cause greater variation in gene expression. Further investigation of these 508 variants led to the discovery of 256 examples of epistasis, and 57 of these were replicated in samples from another cohort. Brown et al. calculated that these epistatic interactions explained up to 16% of the variation in gene expression. Furthermore, as well as being involved in epistatic interactions, about 70% of the genetic variants that had an effect on the variation in gene expression were also involved in interactions between genes and the environment.
In addition to showing that epistasis contributes to variation in human traits, the work of Brown et al. could help to uncover interactions behind complex traits—beyond the expression level of a gene—that could not previously be investigated.
DOI: http://dx.doi.org/10.7554/eLife.01381.002
doi:10.7554/eLife.01381
PMCID: PMC4017648  PMID: 24771767
gene expression; epistasis; gene-environment interactions; human
13.  RHOA Is a Modulator of the Cholesterol-Lowering Effects of Statin 
PLoS Genetics  2012;8(11):e1003058.
Although statin drugs are generally efficacious for lowering plasma LDL-cholesterol levels, there is considerable variability in response. To identify candidate genes that may contribute to this variation, we used an unbiased genome-wide filter approach that was applied to 10,149 genes expressed in immortalized lymphoblastoid cell lines (LCLs) derived from 480 participants of the Cholesterol and Pharmacogenomics (CAP) clinical trial of simvastatin. The criteria for identification of candidates included genes whose statin-induced changes in expression were correlated with change in expression of HMGCR, a key regulator of cellular cholesterol metabolism and the target of statin inhibition. This analysis yielded 45 genes, from which RHOA was selected for follow-up because it has been found to participate in mediating the pleiotropic but not the lipid-lowering effects of statin treatment. RHOA knock-down in hepatoma cell lines reduced HMGCR, LDLR, and SREBF2 mRNA expression and increased intracellular cholesterol ester content as well as apolipoprotein B (APOB) concentrations in the conditioned media. Furthermore, inter-individual variation in statin-induced RHOA mRNA expression measured in vitro in CAP LCLs was correlated with the changes in plasma total cholesterol, LDL-cholesterol, and APOB induced by simvastatin treatment (40 mg/d for 6 wk) of the individuals from whom these cell lines were derived. Moreover, the minor allele of rs11716445, a SNP located in a novel cryptic RHOA exon, dramatically increased inclusion of the exon in RHOA transcripts during splicing and was associated with a smaller LDL-cholesterol reduction in response to statin treatment in 1,886 participants from the CAP and Pravastatin Inflamation and CRP Evaluation (PRINCE; pravastatin 40 mg/d) statin clinical trials. Thus, an unbiased filter approach based on transcriptome-wide profiling identified RHOA as a gene contributing to variation in LDL-cholesterol response to statin, illustrating the power of this approach for identifying candidate genes involved in drug response phenotypes.
Author Summary
Statins, or HMG CoA reductase inhibitors, are widely used to lower plasma LDL-cholesterol levels as a means of reducing risk for cardiovascular disease. We performed an unbiased genome-wide survey to identify novel candidate genes that may be involved in statin response using genome-wide mRNA expression analysis in a sequential filtering strategy to identify those most likely to be relevant to cholesterol metabolism based on their gene expression characteristics. Among these, RHOA was selected for further functional study. A role for this gene in the maintenance of intracellular cholesterol homeostasis was confirmed by knock-down in hepatoma cell lines. In addition, statin-induced RHOA transcript levels measured in a panel of lymphoblastoid cell lines was correlated with statin-induced change in plasma LDL-cholesterol measured in individuals from whom the cell lines were derived. Lastly, a cis-acting splicing QTL associated with expression of a rare cryptic RHOA exon was also associated with statin-induced changes in plasma LDLC levels. This result exemplifies the power of applying biological information of well understood molecular pathways with genome-wide expression data for the identification of candidate genes that influence drug response.
doi:10.1371/journal.pgen.1003058
PMCID: PMC3499361  PMID: 23166513
14.  A towards-multidimensional screening approach to predict candidate genes of rheumatoid arthritis based on SNP, structural and functional annotations 
BMC Medical Genomics  2010;3:38.
Background
According to the Genetic Analysis Workshops (GAW), hundreds of thousands of SNPs have been tested for association with rheumatoid arthritis. Traditional genome-wide association studies (GWAS) have been developed to identify susceptibility genes using a "most significant SNPs/genes" model. However, many minor- or modest-risk genes are likely to be missed after adjustment of multiple testing. This screening process uses a strict selection of statistical thresholds that aim to identify susceptibility genes based only on statistical model, without considering multi-dimensional biological similarities in sequence arrangement, crystal structure, or functional categories/biological pathways between candidate and known disease genes.
Methods
Multidimensional screening approaches combined with traditional statistical genetics methods can consider multiple biological backgrounds of genetic mutation, structural, and functional annotations. Here we introduce a newly developed multidimensional screening approach for rheumatoid arthritis candidate genes that considers all SNPs with nominal evidence of Bayesian association (BFLn > 0), and structural and functional similarities of corresponding genes or proteins.
Results
Our multidimensional screening approach extracted all risk genes (BFLn > 0) by odd ratios of hypothesis H1 to H0, and determined whether a particular group of genes shared underlying biological similarities with known disease genes. Using this method, we found 6614 risk SNPs in our Bayesian screen result set. Finally, we identified 146 likely causal genes for rheumatoid arthritis, including CD4, FGFR1, and KDR, which have been reported as high risk factors by recent studies. We must denote that 790 (96.1%) of genes identified by GWAS could not easily be classified into related functional categories or biological processes associated with the disease, while our candidate genes shared underlying biological similarities (e.g. were in the same pathway or GO term) and contributed to disease etiology, but where common variations in each of these genes make modest contributions to disease risk. We also found 6141 risk SNPs that were too minor to be detected by conventional approaches, and associations between 58 candidate genes and rheumatoid arthritis were verified by literature retrieved from the NCBI PubMed module.
Conclusions
Our proposed approach to the analysis of GAW16 data for rheumatoid arthritis was based on an underlying biological similarities-based method applied to candidate and known disease genes. Application of our method could identify likely causal candidate disease genes of rheumatoid arthritis, and could yield biological insights that not detected when focusing only on genes that give the strongest evidence by multiple testing. We hope that our proposed method complements the "most significant SNPs/genes" model, and provides additional insights into the pathogenesis of rheumatoid arthritis and other diseases, when searching datasets for hundreds of genetic variances.
doi:10.1186/1755-8794-3-38
PMCID: PMC2939610  PMID: 20727150
15.  Transcriptome Sequencing from Diverse Human Populations Reveals Differentiated Regulatory Architecture 
PLoS Genetics  2014;10(8):e1004549.
Large-scale sequencing efforts have documented extensive genetic variation within the human genome. However, our understanding of the origins, global distribution, and functional consequences of this variation is far from complete. While regulatory variation influencing gene expression has been studied within a handful of populations, the breadth of transcriptome differences across diverse human populations has not been systematically analyzed. To better understand the spectrum of gene expression variation, alternative splicing, and the population genetics of regulatory variation in humans, we have sequenced the genomes, exomes, and transcriptomes of EBV transformed lymphoblastoid cell lines derived from 45 individuals in the Human Genome Diversity Panel (HGDP). The populations sampled span the geographic breadth of human migration history and include Namibian San, Mbuti Pygmies of the Democratic Republic of Congo, Algerian Mozabites, Pathan of Pakistan, Cambodians of East Asia, Yakut of Siberia, and Mayans of Mexico. We discover that approximately 25.0% of the variation in gene expression found amongst individuals can be attributed to population differences. However, we find few genes that are systematically differentially expressed among populations. Of this population-specific variation, 75.5% is due to expression rather than splicing variability, and we find few genes with strong evidence for differential splicing across populations. Allelic expression analyses indicate that previously mapped common regulatory variants identified in eight populations from the International Haplotype Map Phase 3 project have similar effects in our seven sampled HGDP populations, suggesting that the cellular effects of common variants are shared across diverse populations. Together, these results provide a resource for studies analyzing functional differences across populations by estimating the degree of shared gene expression, alternative splicing, and regulatory genetics across populations from the broadest points of human migration history yet sampled.
Author Summary
Previous gene expression studies have identified factors influencing population-level variation in gene regulation. However, these efforts have been limited to a small set of well-studied populations. By leveraging the high resolution of RNA sequencing and broad population sampling, we survey the landscape of transcriptome variation across a globally distributed set of seven populations that span a breadth of human genetic variation and major dispersal events. We assess differences in gene expression, transcript structure, and regulatory variation. We find only 44 transcripts that show significant differences in expression, likely as a result of the small sample size, but we find that 25% of the variance in gene expression is due to population differences. This is a larger fraction than previously observed, and it is likely due to the greater breadth of human diversity assayed in this study. We also find that population-specific variance is mostly due to transcription variability rather than the configuration of expressed gene products. Additionally, known common regulatory variants have similar effects across populations including those we study here. These data and results serve as a resource cataloging the wide array of gene expression regulation affecting population variation among diverse groups, improving our understanding of transcriptional diversity.
doi:10.1371/journal.pgen.1004549
PMCID: PMC4133153  PMID: 25121757
16.  Gemcitabine and Arabinosylcytosin Pharmacogenomics: Genome-Wide Association and Drug Response Biomarkers 
PLoS ONE  2009;4(11):e7765.
Cancer patients show large individual variation in their response to chemotherapeutic agents. Gemcitabine (dFdC) and AraC, two cytidine analogues, have shown significant activity against a variety of tumors. We previously used expression data from a lymphoblastoid cell line-based model system to identify genes that might be important for the two drug cytotoxicity. In the present study, we used that same model system to perform a genome-wide association (GWA) study to test the hypothesis that common genetic variation might influence both gene expression and response to the two drugs. Specifically, genome-wide single nucleotide polymorphisms (SNPs) and mRNA expression data were obtained using the Illumina 550K® HumanHap550 SNP Chip and Affymetrix U133 Plus 2.0 GeneChip, respectively, for 174 ethnically-defined “Human Variation Panel” lymphoblastoid cell lines. Gemcitabine and AraC cytotoxicity assays were performed to obtain IC50 values for the cell lines. We then performed GWA studies with SNPs, gene expression and IC50 of these two drugs. This approach identified SNPs that were associated with gemcitabine or AraC IC50 values and with the expression regulation for 29 genes or 30 genes, respectively. One SNP in IQGAP2 (rs3797418) was significantly associated with variation in both the expression of multiple genes and gemcitabine and AraC IC50. A second SNP in TGM3 (rs6082527) was also significantly associated with multiple gene expression and gemcitabine IC50. To confirm the association results, we performed siRNA knock down of selected genes with expression that was associated with rs3797418 and rs6082527 in tumor cell and the knock down altered gemcitabine or AraC sensitivity, confirming our association study results. These results suggest that the application of GWA approaches using cell-based model systems, when combined with complementary functional validation, can provide insights into mechanisms responsible for variation in cytidine analogue response.
doi:10.1371/journal.pone.0007765
PMCID: PMC2770319  PMID: 19898621
17.  Allele-Specific Down-Regulation of RPTOR Expression Induced by Retinoids Contributes to Climate Adaptations 
PLoS Genetics  2010;6(10):e1001178.
The mechanistic target of rapamycin (MTOR) pathway regulates cell growth, energy homeostasis, apoptosis, and immune response. The regulatory associated protein of MTOR encoded by the RPTOR gene is a key component of this pathway. A previous survey of candidate genes found that RPTOR contains multiple SNPs with strong correlations between allele frequencies and climate variables, consistent with the action of selective pressures that vary across environments. Using data from a recent genome scan for selection signals, we honed in on a SNP (rs11868112) 26 kb upstream to the transcription start site of RPTOR that exhibits the strongest association with temperature variables. Transcription factor motif scanning and mining of recently mapped transcription factor binding sites identified a binding site for POU class 2 homeobox 1 (POU2F1) spanning the SNP and an adjacent retinoid acid receptor (RAR) binding site. Using expression quantification, chromatin immunoprecipitation (ChIP), and reporter gene assays, we demonstrate that POU2F1 and RARA do bind upstream of the RPTOR gene to regulate its expression in response to retinoids; this regulation is affected by the allele status at rs11868112 with the derived allele resulting in lower expression levels. We propose a model in which the derived allele influences thermogenesis or immune response by altering MTOR pathway activity and thereby increasing fitness in colder climates. Our results show that signatures of genetic adaptations can identify variants with functional effects, consistent with the idea that selection signals may be used for SNP annotation.
Author Summary
Climate has exerted strong selective pressures in human populations during their dispersal, and signatures of these adaptations are still detectable in the geographic distribution of polymorphisms. RPTOR is a key component of the mechanistic target of rapamycin pathway, which regulates cell growth, metabolism, and immune response; and its deregulation is associated with human diseases, including cancer and diabetes. Previous studies showed that variation in RPTOR carry strong signatures of adaptations to different climates. Here, we used evolutionary genetics approaches coupled with transcription factor motif data mining to refine the location of the selection target. We then used functional assays to show that the selected polymorphism resides in a sequence element that regulates gene expression levels in response to retinoids. The derived allele at this SNP, which results in lower expression levels, increases in frequency with decreasing temperatures, consistent with the notion that it confers a selective advantage in colder climates possibly through its effects on energy metabolism or immune response. These results suggest a novel regulatory role for retinoids in MTOR signaling. Moreover, they support the proposal that evolutionary approaches can be informative for SNP functional annotation.
doi:10.1371/journal.pgen.1001178
PMCID: PMC2965758  PMID: 21060808
18.  Identification, Replication, and Functional Fine-Mapping of Expression Quantitative Trait Loci in Primary Human Liver Tissue 
PLoS Genetics  2011;7(5):e1002078.
The discovery of expression quantitative trait loci (“eQTLs”) can help to unravel genetic contributions to complex traits. We identified genetic determinants of human liver gene expression variation using two independent collections of primary tissue profiled with Agilent (n = 206) and Illumina (n = 60) expression arrays and Illumina SNP genotyping (550K), and we also incorporated data from a published study (n = 266). We found that ∼30% of SNP-expression correlations in one study failed to replicate in either of the others, even at thresholds yielding high reproducibility in simulations, and we quantified numerous factors affecting reproducibility. Our data suggest that drug exposure, clinical descriptors, and unknown factors associated with tissue ascertainment and analysis have substantial effects on gene expression and that controlling for hidden confounding variables significantly increases replication rate. Furthermore, we found that reproducible eQTL SNPs were heavily enriched near gene starts and ends, and subsequently resequenced the promoters and 3′UTRs for 14 genes and tested the identified haplotypes using luciferase assays. For three genes, significant haplotype-specific in vitro functional differences correlated directly with expression levels, suggesting that many bona fide eQTLs result from functional variants that can be mechanistically isolated in a high-throughput fashion. Finally, given our study design, we were able to discover and validate hundreds of liver eQTLs. Many of these relate directly to complex traits for which liver-specific analyses are likely to be relevant, and we identified dozens of potential connections with disease-associated loci. These included previously characterized eQTL contributors to diabetes, drug response, and lipid levels, and they suggest novel candidates such as a role for NOD2 expression in leprosy risk and C2orf43 in prostate cancer. In general, the work presented here will be valuable for future efforts to precisely identify and functionally characterize genetic contributions to a variety of complex traits.
Author Summary
Many disease-associated genetic variants do not alter protein sequences and are difficult to precisely identify. Discovery of expression quantitative trait loci (eQTL), or correlations between genetic variants and gene expression levels, offers one means of addressing this challenge. However, eQTL studies in primary cells have several shortcomings. In particular, their reproducibility is largely unknown, the variables that generate unreliable associations are uncharacterized, and the resolution of their findings is constrained by linkage disequilibrium. We performed a three-way replication study of eQTLs in primary human livers. We demonstrated that ∼67% of cis-eQTL associations are replicated in an independent study and that known polymorphisms overlapping expression probes, SNP-to-gene distance, and unmeasured confounding variables all influence the replication rate. We fine-mapped 14 eQTLs and identified causative polymorphisms in the promoter or 3′UTR for 3 genes, suggesting that a considerable fraction of eQTLs are driven by proximal variants that are amenable to functional isolation. Finally, we found hundreds of overlaps between SNPs associated with complex traits and replicated eQTL SNPs. Our data provide both cautionary (i.e. non-reproducibility of many strong eQTLs) and optimistic (i.e. precise identification of functional non-coding variants) forecasts for future eQTL analyses and the complex traits that they influence.
doi:10.1371/journal.pgen.1002078
PMCID: PMC3102751  PMID: 21637794
19.  Comprehensive Analysis of Transcriptome Variation Uncovers Known and Novel Driver Events in T-Cell Acute Lymphoblastic Leukemia 
PLoS Genetics  2013;9(12):e1003997.
RNA-seq is a promising technology to re-sequence protein coding genes for the identification of single nucleotide variants (SNV), while simultaneously obtaining information on structural variations and gene expression perturbations. We asked whether RNA-seq is suitable for the detection of driver mutations in T-cell acute lymphoblastic leukemia (T-ALL). These leukemias are caused by a combination of gene fusions, over-expression of transcription factors and cooperative point mutations in oncogenes and tumor suppressor genes. We analyzed 31 T-ALL patient samples and 18 T-ALL cell lines by high-coverage paired-end RNA-seq. First, we optimized the detection of SNVs in RNA-seq data by comparing the results with exome re-sequencing data. We identified known driver genes with recurrent protein altering variations, as well as several new candidates including H3F3A, PTK2B, and STAT5B. Next, we determined accurate gene expression levels from the RNA-seq data through normalizations and batch effect removal, and used these to classify patients into T-ALL subtypes. Finally, we detected gene fusions, of which several can explain the over-expression of key driver genes such as TLX1, PLAG1, LMO1, or NKX2-1; and others result in novel fusion transcripts encoding activated kinases (SSBP2-FER and TPM3-JAK2) or involving MLLT10. In conclusion, we present novel analysis pipelines for variant calling, variant filtering, and expression normalization on RNA-seq data, and successfully applied these for the detection of translocations, point mutations, INDELs, exon-skipping events, and expression perturbations in T-ALL.
Author Summary
The quest for somatic mutations underlying oncogenic processes is a central theme in today's cancer research. High-throughput genomics approaches including amplicon re-sequencing, exome re-sequencing, full genome re-sequencing, and SNP arrays have contributed to cataloguing driver genes across cancer types. Thus far transcriptome sequencing by RNA-seq has been mainly used for the detection of fusion genes, while few studies have assessed its value for the combined detection of SNPs, INDELs, fusions, gene expression changes, and alternative transcript events. Here we apply RNA-seq to 49 T-ALL samples and perform a critical assessment of the bioinformatics pipelines and filters to identify each type of aberration. By comparing to exome re-sequencing, and by exploiting the catalogues of known cancer drivers, we identified many known and several novel driver genes in T-ALL. We also determined an optimal normalization strategy to obtain accurate gene expression levels and used these to identify over-expressed transcription factors that characterize different T-ALL subtypes. Finally, by PCR, cloning, and in vitro cellular assays we uncover new fusion genes that have consequences at the level of gene expression, oncogenic chimaeras, and tumor suppressor inactivation. In conclusion, we present the first RNA-seq data set across T-ALL patients and identify new driver events.
doi:10.1371/journal.pgen.1003997
PMCID: PMC3868543  PMID: 24367274
20.  Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line 
We provide a large-scale dataset on absolute protein and matching mRNA concentrations from the human medulloblastoma cell line Daoy. The correlation between mRNA and protein concentrations is significant and positive (Rs=0.46, R2=0.29, P-value<2e16), although non-linear.Out of ∼200 tested sequence features, sequence length, frequency and properties of amino acids, as well as translation initiation-related features are the strongest individual correlates of protein abundance when accounting for variation in mRNA concentration.When integrating mRNA expression data and all sequence features into a non-parametric regression model (Multivariate Adaptive Regression Splines), we were able to explain up to 67% of the variation in protein concentrations. Half of the contributions were attributed to mRNA concentrations, the other half to sequence features relating to regulation of translation and protein degradation. The sequence features are primarily linked to the coding and 3′ untranslated region. To our knowledge, this is the most comprehensive predictive model of human protein concentrations achieved so far.
mRNA decay, translation regulation and protein degradation are essential parts of eukaryotic gene expression regulation (Hieronymus and Silver, 2004; Mata et al, 2005), which enable the dynamics of cellular systems and their responses to external and internal stimuli without having to rely exclusively on transcription regulation. The importance of these processes is emphasized by the generally low correlation between mRNA and protein concentrations. For many prokaryotic and eukaryotic organisms, <50% of variation in protein abundance variation is explained by variation in mRNA concentrations (de Sousa Abreu et al, 2009).
Given the plethora of regulatory mechanisms involved, most studies have focused so far on individual regulators and specific targets. Particularly in human, we currently lack system-wide, quantitative analyses that evaluate the relative contribution of regulatory elements encoded in the mRNA and protein sequence. Existing studies have been carried out only in bacteria and yeast (Nie et al, 2006; Brockmann et al, 2007; Tuller et al, 2007; Wu et al, 2008). Here, we present the first comprehensive analysis on the impact of translation and protein degradation on protein abundance variation in a human cell line. For this purpose, we experimentally measured absolute protein and mRNA concentrations in the Daoy medulloblastoma cell line, using shotgun proteomics and microarrays, respectively (Figure 1). These data comprise one of the largest such sets available today for human. We focused on sequence features that likely impact protein translation and protein degradation, including length, nucleotide composition, structure of the untranslated regions (UTRs), coding sequence, composition of the translation initiation site, presence of upstream open reading frames putative target sites of miRNAs, codon usage, amino-acid composition and protein degradation signals.
Three types of tests have been conducted: (a) we examined partial Spearman's rank correlation of numerical features (e.g. length) with protein concentration, accounting for variation in mRNA concentrations; (b) for numerical and categorical features (e.g. function), we compared two extreme populations with Welch's t-test and (c) using a Multivariate Adaptive Regression Splines model, we analyzed the combined contributions of mRNA expression and sequence features to protein abundance variation (Figure 1). To account for the non-linearity of many relationships, we use non-parametric approaches throughout the analysis.
We observed a significant positive correlation between mRNA and protein concentrations, larger than many previous measurements (de Sousa Abreu et al, 2009). We also show that the contribution of translation and protein degradation is at least as important as the contribution of mRNA transcription and stability to the abundance variation of the final protein products. Although variation in mRNA expression explains ∼25–30% of the variation in protein abundance, another 30–40% can be accounted for by characteristics of the sequences, which we identified in a comparative assessment of global correlates. Among these characteristics, sequence length, amino-acid frequencies and also nucleotide frequencies in the coding region are of strong influence (Figure 3A). Characteristics of the 3′UTR and of the 5′UTR, that is length, nucleotide composition and secondary structures, describe another part of the variation, leaving 33% expression variation unexplained. The unexplained fraction may be accounted for by mechanisms not considered in this analysis (e.g. regulation by RNA-binding proteins or gene-specific structural motifs), as well as expression and measurement noise.
Our combined model including mRNA concentration and sequence features can explain 67% of the variation of protein abundance in this system—and thus has the highest predictive power for human protein abundance achieved so far (Figure 3B).
Transcription, mRNA decay, translation and protein degradation are essential processes during eukaryotic gene expression, but their relative global contributions to steady-state protein concentrations in multi-cellular eukaryotes are largely unknown. Using measurements of absolute protein and mRNA abundances in cellular lysate from the human Daoy medulloblastoma cell line, we quantitatively evaluate the impact of mRNA concentration and sequence features implicated in translation and protein degradation on protein expression. Sequence features related to translation and protein degradation have an impact similar to that of mRNA abundance, and their combined contribution explains two-thirds of protein abundance variation. mRNA sequence lengths, amino-acid properties, upstream open reading frames and secondary structures in the 5′ untranslated region (UTR) were the strongest individual correlates of protein concentrations. In a combined model, characteristics of the coding region and the 3′UTR explained a larger proportion of protein abundance variation than characteristics of the 5′UTR. The absolute protein and mRNA concentration measurements for >1000 human genes described here represent one of the largest datasets currently available, and reveal both general trends and specific examples of post-transcriptional regulation.
doi:10.1038/msb.2010.59
PMCID: PMC2947365  PMID: 20739923
gene expression regulation; protein degradation; protein stability; translation
21.  Identification of candidate genes for drought tolerance by whole-genome resequencing in maize 
BMC Plant Biology  2014;14:83.
Background
Drought stress is one of the major limiting factors for maize production. With the availability of maize B73 reference genome and whole-genome resequencing of 15 maize inbreds, common variants (CV) and clustering analyses were applied to identify non-synonymous SNPs (nsSNPs) and corresponding candidate genes for drought tolerance.
Results
A total of 524 nsSNPs that were associated with 271 candidate genes involved in plant hormone regulation, carbohydrate and sugar metabolism, signaling molecules regulation, redox reaction and acclimation of photosynthesis to environment were detected by CV and cluster analyses. Most of the nsSNPs identified were clustered in bin 1.07 region that harbored six previously reported QTL with relatively high phenotypic variation explained for drought tolerance. Genes Ontology (GO) analysis of candidate genes revealed that there were 35 GO terms related to biotic stimulus and membrane-bounded organelle, showing significant differences between the candidate genes and the reference B73 background. Changes of expression level in these candidate genes for drought tolerance were detected using RNA sequencing for fertilized ovary, basal leaf meristem tissue and roots collected under drought stressed and well-watered conditions. The results indicated that 70% of candidate genes showed significantly expression changes under two water treatments and our strategies for mining candidate genes are feasible and relatively efficient.
Conclusions
Our results successfully revealed candidate nsSNPs and associated genes for drought tolerance by comparative sequence analysis of 16 maize inbred lines. Both methods we applied were proved to be efficient for identifying candidate genes for complex traits through the next-generation sequencing technologies (NGS). These selected genes will not only facilitate understanding of genetic basis of drought stress response, but also accelerate genetic improvement through marker-assisted selection in maize.
doi:10.1186/1471-2229-14-83
PMCID: PMC4021222  PMID: 24684805
22.  Identification of Common Genetic Variation That Modulates Alternative Splicing 
PLoS Genetics  2007;3(6):e99.
Alternative splicing of genes is an efficient means of generating variation in protein function. Several disease states have been associated with rare genetic variants that affect splicing patterns. Conversely, splicing efficiency of some genes is known to vary between individuals without apparent ill effects. What is not clear is whether commonly observed phenotypic variation in splicing patterns, and hence potential variation in protein function, is to a significant extent determined by naturally occurring DNA sequence variation and in particular by single nucleotide polymorphisms (SNPs). In this study, we surveyed the splicing patterns of 250 exons in 22 individuals who had been previously genotyped by the International HapMap Project. We identified 70 simple cassette exon alternative splicing events in our experimental system; for six of these, we detected consistent differences in splicing pattern between individuals, with a highly significant association between splice phenotype and neighbouring SNPs. Remarkably, for five out of six of these events, the strongest correlation was found with the SNP closest to the intron–exon boundary, although the distance between these SNPs and the intron–exon boundary ranged from 2 bp to greater than 1,000 bp. Two of these SNPs were further investigated using a minigene splicing system, and in each case the SNPs were found to exert cis-acting effects on exon splicing efficiency in vitro. The functional consequences of these SNPs could not be predicted using bioinformatic algorithms. Our findings suggest that phenotypic variation in splicing patterns is determined by the presence of SNPs within flanking introns or exons. Effects on splicing may represent an important mechanism by which SNPs influence gene function.
Author Summary
Genetic variation, through its effects on gene expression, influences many aspects of the human phenotype. Understanding the impact of genetic variation on human disease risk has become a major goal for biomedical research and has the potential of revealing both novel disease mechanisms and novel functional elements controlling gene expression. Recent large-scale studies have suggested that a relatively high proportion of human genes show allele-specific variation in expression. Effects of common DNA polymorphisms on mRNA splicing are less well studied. Variation in splicing patterns is known to be tissue specific, and for a small number of genes has been shown to vary among individuals. What is not known is whether allele-specific splicing events are an important mechanism by which common genetic variation affects gene expression. In this study we show that allele-specific alternative splicing was observed in six out of 70 exon-skipping events. Sequence analysis of the relevant splice sites and of the regions surrounding single nucleotide polymorphisms correlated with the splicing events failed to identify any predictive bioinformatic signals. A genome-wide study of allele-specific splicing, using an experimental rather than a bioinformatic approach, is now required.
doi:10.1371/journal.pgen.0030099
PMCID: PMC1904363  PMID: 17571926
23.  DNA polymorphisms and haplotype patterns of transcription factors involved in barley endosperm development are associated with key agronomic traits 
BMC Plant Biology  2010;10:5.
Background
Association mapping is receiving considerable attention in plant genetics for its potential to fine map quantitative trait loci (QTL), validate candidate genes, and identify alleles of interest. In the present study association mapping in barley (Hordeum vulgare L.) is investigated by associating DNA polymorphisms with variation in grain quality traits, plant height, and flowering time to gain further understanding of gene functions involved in the control of these traits. We focused on the four loci BLZ1, BLZ2, BPBF and HvGAMYB that play a role in the regulation of B-hordein expression, the major fraction of the barley storage protein. The association was tested in a collection of 224 spring barley accessions using a two-stage mixed model approach.
Results
Within the sequenced fragments of four candidate genes we observed different levels of nucleotide diversity. The effect of selection on the candidate genes was tested by Tajima's D which revealed significant values for BLZ1, BLZ2, and BPBF in the subset of two-rowed barleys. Pair-wise LD estimates between the detected SNPs within each candidate gene revealed different intra-genic linkage patterns. On the basis of a more extensive examination of genomic regions surrounding the four candidate genes we found a sharp decrease of LD (r2<0.2 within 1 cM) in all but one flanking regions.
Significant marker-trait associations between SNP sites within BLZ1 and flowering time, BPBF and crude protein content and BPBF and starch content were detected. Most haplotypes occurred at frequencies <0.05 and therefore were rejected from the association analysis. Based on haplotype information, BPBF was associated to crude protein content and starch content, BLZ2 showed association to thousand-grain weight and BLZ1 was found to be associated with flowering time and plant height.
Conclusions
Differences in nucleotide diversity and LD pattern within the candidate genes BLZ1, BLZ2, BPBF, and HvGAMYB reflect the impact of selection on the nucleotide sequence of the four candidate loci.
Despite significant associations, the analysed candidate genes only explained a minor part of the total genetic variation although they are known to be important factors influencing the expression of seed quality traits. Therefore, we assume that grain quality as well as plant height and flowering time are influenced by many factors each contributing a small part to the expression of the phenotype. A genome-wide association analysis could provide a more comprehensive picture of loci involved in the regulation of grain quality, thousand grain weight and the other agronomic traits that were analyzed in this study. However, despite available high-throughput genotyping arrays the marker density along the barely genome is still insufficient to cover all associations in a whole genome scan. Therefore, the candidate gene-based approach will further play an important role in barley association studies.
doi:10.1186/1471-2229-10-5
PMCID: PMC2822787  PMID: 20064201
24.  High-Resolution Mapping of Expression-QTLs Yields Insight into Human Gene Regulation 
PLoS Genetics  2008;4(10):e1000214.
Recent studies of the HapMap lymphoblastoid cell lines have identified large numbers of quantitative trait loci for gene expression (eQTLs). Reanalyzing these data using a novel Bayesian hierarchical model, we were able to create a surprisingly high-resolution map of the typical locations of sites that affect mRNA levels in cis. Strikingly, we found a strong enrichment of eQTLs in the 250 bp just upstream of the transcription end site (TES), in addition to an enrichment around the transcription start site (TSS). Most eQTLs lie either within genes or close to genes; for example, we estimate that only 5% of eQTLs lie more than 20 kb upstream of the TSS. After controlling for position effects, SNPs in exons are ∼2-fold more likely than SNPs in introns to be eQTLs. Our results suggest an important role for mRNA stability in determining steady-state mRNA levels, and highlight the potential of eQTL mapping as a high-resolution tool for studying the determinants of gene regulation.
Author Summary
Individual phenotypes within natural populations generally exhibit a large diversity resulting from a complex interplay of genes and environmental factors. Since the advent of molecular markers in the 1980s, quantitative genetics has made a significant step toward unraveling the genetic bases of such complex traits, in particular by developing sophisticated tools to map the genomic locations of genes that affect complex traits. These regions are known as quantitative trait loci (QTLs). More recently, these tools have been extended to the study of gene expression phenotypes on a massive scale. In this paper, we used a previously published dataset consisting of expression measurements of 11,446 genes in human cell lines derived from 210 unrelated human individuals that have been genetically characterized by the International HapMap Project. Our article develops and applies a framework for determining the genetic factors that impact gene regulation. We show that these factors cluster strongly near to the gene start and gene end and are enriched within the transcribed region. Our approach suggests a general framework for studying the genetic factors that affect variation in gene expression.
doi:10.1371/journal.pgen.1000214
PMCID: PMC2556086  PMID: 18846210
25.  Cis-regulatory sequence variation and association with Mycoplasma load in natural populations of the house finch (Carpodacus mexicanus) 
Ecology and Evolution  2013;3(3):655-666.
Characterization of the genetic basis of fitness traits in natural populations is important for understanding how organisms adapt to the changing environment and to novel events, such as epizootics. However, candidate fitness-influencing loci, such as regulatory regions, are usually unavailable in nonmodel species. Here, we analyze sequence data from targeted resequencing of the cis-regulatory regions of three candidate genes for disease resistance (CD74, HSP90α, and LCP1) in populations of the house finch (Carpodacus mexicanus) historically exposed (Alabama) and naïve (Arizona) to Mycoplasma gallisepticum. Our study, the first to quantify variation in regulatory regions in wild birds, reveals that the upstream regions of CD74 and HSP90α are GC-rich, with the former exhibiting unusually low sequence variation for this species. We identified two SNPs, located in a GC-rich region immediately upstream of an inferred promoter site in the gene HSP90α, that were significantly associated with Mycoplasma pathogen load in the two populations. The SNPs are closely linked and situated in potential regulatory sequences: one in a binding site for the transcription factor nuclear NFYα and the other in a dinucleotide microsatellite ((GC)6). The genotype associated with pathogen load in the putative NFYα binding site was significantly overrepresented in the Alabama birds. However, we did not see strong effects of selection at this SNP, perhaps because selection has acted on standing genetic variation over an extremely short time in a highly recombining region. Our study is a useful starting point to explore functional relationships between sequence polymorphisms, gene expression, and phenotypic traits, such as pathogen resistance that affect fitness in the wild.
doi:10.1002/ece3.484
PMCID: PMC3605853  PMID: 23532859
Association mapping; cis-regulatory element; expression; house finch; Mycoplasma gallisepticum

Results 1-25 (2189432)