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author:("Zhu, xianfeng")
1.  Loci influencing blood pressure identified using a cardiovascular gene-centric array 
Ganesh, Santhi K. | Tragante, Vinicius | Guo, Wei | Guo, Yiran | Lanktree, Matthew B. | Smith, Erin N. | Johnson, Toby | Castillo, Berta Almoguera | Barnard, John | Baumert, Jens | Chang, Yen-Pei Christy | Elbers, Clara C. | Farrall, Martin | Fischer, Mary E. | Franceschini, Nora | Gaunt, Tom R. | Gho, Johannes M.I.H. | Gieger, Christian | Gong, Yan | Isaacs, Aaron | Kleber, Marcus E. | Leach, Irene Mateo | McDonough, Caitrin W. | Meijs, Matthijs F.L. | Mellander, Olle | Molony, Cliona M. | Nolte, Ilja M. | Padmanabhan, Sandosh | Price, Tom S. | Rajagopalan, Ramakrishnan | Shaffer, Jonathan | Shah, Sonia | Shen, Haiqing | Soranzo, Nicole | van der Most, Peter J. | Van Iperen, Erik P.A. | Van Setten, Jessica | Vonk, Judith M. | Zhang, Li | Beitelshees, Amber L. | Berenson, Gerald S. | Bhatt, Deepak L. | Boer, Jolanda M.A. | Boerwinkle, Eric | Burkley, Ben | Burt, Amber | Chakravarti, Aravinda | Chen, Wei | Cooper-DeHoff, Rhonda M. | Curtis, Sean P. | Dreisbach, Albert | Duggan, David | Ehret, Georg B. | Fabsitz, Richard R. | Fornage, Myriam | Fox, Ervin | Furlong, Clement E. | Gansevoort, Ron T. | Hofker, Marten H. | Hovingh, G. Kees | Kirkland, Susan A. | Kottke-Marchant, Kandice | Kutlar, Abdullah | LaCroix, Andrea Z. | Langaee, Taimour Y. | Li, Yun R. | Lin, Honghuang | Liu, Kiang | Maiwald, Steffi | Malik, Rainer | Murugesan, Gurunathan | Newton-Cheh, Christopher | O'Connell, Jeffery R. | Onland-Moret, N. Charlotte | Ouwehand, Willem H. | Palmas, Walter | Penninx, Brenda W. | Pepine, Carl J. | Pettinger, Mary | Polak, Joseph F. | Ramachandran, Vasan S. | Ranchalis, Jane | Redline, Susan | Ridker, Paul M. | Rose, Lynda M. | Scharnag, Hubert | Schork, Nicholas J. | Shimbo, Daichi | Shuldiner, Alan R. | Srinivasan, Sathanur R. | Stolk, Ronald P. | Taylor, Herman A. | Thorand, Barbara | Trip, Mieke D. | van Duijn, Cornelia M. | Verschuren, W. Monique | Wijmenga, Cisca | Winkelmann, Bernhard R. | Wyatt, Sharon | Young, J. Hunter | Boehm, Bernhard O. | Caulfield, Mark J. | Chasman, Daniel I. | Davidson, Karina W. | Doevendans, Pieter A. | FitzGerald, Garret A. | Gums, John G. | Hakonarson, Hakon | Hillege, Hans L. | Illig, Thomas | Jarvik, Gail P. | Johnson, Julie A. | Kastelein, John J.P. | Koenig, Wolfgang | März, Winfried | Mitchell, Braxton D. | Murray, Sarah S. | Oldehinkel, Albertine J. | Rader, Daniel J. | Reilly, Muredach P. | Reiner, Alex P. | Schadt, Eric E. | Silverstein, Roy L. | Snieder, Harold | Stanton, Alice V. | Uitterlinden, André G. | van der Harst, Pim | van der Schouw, Yvonne T. | Samani, Nilesh J. | Johnson, Andrew D. | Munroe, Patricia B. | de Bakker, Paul I.W. | Zhu, Xiaofeng | Levy, Daniel | Keating, Brendan J. | Asselbergs, Folkert W.
Human Molecular Genetics  2013;22(16):3394-3395.
doi:10.1093/hmg/ddt177
PMCID: PMC3888295
2.  Loci influencing blood pressure identified using a cardiovascular gene-centric array 
Ganesh, Santhi K. | Tragante, Vinicius | Guo, Wei | Guo, Yiran | Lanktree, Matthew B. | Smith, Erin N. | Johnson, Toby | Castillo, Berta Almoguera | Barnard, John | Baumert, Jens | Chang, Yen-Pei Christy | Elbers, Clara C. | Farrall, Martin | Fischer, Mary E. | Franceschini, Nora | Gaunt, Tom R. | Gho, Johannes M.I.H. | Gieger, Christian | Gong, Yan | Isaacs, Aaron | Kleber, Marcus E. | Leach, Irene Mateo | McDonough, Caitrin W. | Meijs, Matthijs F.L. | Mellander, Olle | Molony, Cliona M. | Nolte, Ilja M. | Padmanabhan, Sandosh | Price, Tom S. | Rajagopalan, Ramakrishnan | Shaffer, Jonathan | Shah, Sonia | Shen, Haiqing | Soranzo, Nicole | van der Most, Peter J. | Van Iperen, Erik P.A. | Van Setten, Jessic A. | Vonk, Judith M. | Zhang, Li | Beitelshees, Amber L. | Berenson, Gerald S. | Bhatt, Deepak L. | Boer, Jolanda M.A. | Boerwinkle, Eric | Burkley, Ben | Burt, Amber | Chakravarti, Aravinda | Chen, Wei | Cooper-DeHoff, Rhonda M. | Curtis, Sean P. | Dreisbach, Albert | Duggan, David | Ehret, Georg B. | Fabsitz, Richard R. | Fornage, Myriam | Fox, Ervin | Furlong, Clement E. | Gansevoort, Ron T. | Hofker, Marten H. | Hovingh, G. Kees | Kirkland, Susan A. | Kottke-Marchant, Kandice | Kutlar, Abdullah | LaCroix, Andrea Z. | Langaee, Taimour Y. | Li, Yun R. | Lin, Honghuang | Liu, Kiang | Maiwald, Steffi | Malik, Rainer | Murugesan, Gurunathan | Newton-Cheh, Christopher | O'Connell, Jeffery R. | Onland-Moret, N. Charlotte | Ouwehand, Willem H. | Palmas, Walter | Penninx, Brenda W. | Pepine, Carl J. | Pettinger, Mary | Polak, Joseph F. | Ramachandran, Vasan S. | Ranchalis, Jane | Redline, Susan | Ridker, Paul M. | Rose, Lynda M. | Scharnag, Hubert | Schork, Nicholas J. | Shimbo, Daichi | Shuldiner, Alan R. | Srinivasan, Sathanur R. | Stolk, Ronald P. | Taylor, Herman A. | Thorand, Barbara | Trip, Mieke D. | van Duijn, Cornelia M. | Verschuren, W. Monique | Wijmenga, Cisca | Winkelmann, Bernhard R. | Wyatt, Sharon | Young, J. Hunter | Boehm, Bernhard O. | Caulfield, Mark J. | Chasman, Daniel I. | Davidson, Karina W. | Doevendans, Pieter A. | FitzGerald, Garret A. | Gums, John G. | Hakonarson, Hakon | Hillege, Hans L. | Illig, Thomas | Jarvik, Gail P. | Johnson, Julie A. | Kastelein, John J.P. | Koenig, Wolfgang | März, Winfried | Mitchell, Braxton D. | Murray, Sarah S. | Oldehinkel, Albertine J. | Rader, Daniel J. | Reilly, Muredach P. | Reiner, Alex P. | Schadt, Eric E. | Silverstein, Roy L. | Snieder, Harold | Stanton, Alice V. | Uitterlinden, André G. | van der Harst, Pim | van der Schouw, Yvonne T. | Samani, Nilesh J. | Johnson, Andrew D. | Munroe, Patricia B. | de Bakker, Paul I.W. | Zhu, Xiaofeng | Levy, Daniel | Keating, Brendan J. | Asselbergs, Folkert W.
Human Molecular Genetics  2013;22(8):1663-1678.
Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10−6). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.
doi:10.1093/hmg/dds555
PMCID: PMC3657476  PMID: 23303523
3.  Effects of cordycepin on HepG2 and EA.hy926 cells: Potential antiproliferative, antimetastatic and anti-angiogenic effects on hepatocellular carcinoma 
Oncology Letters  2014;7(5):1556-1562.
Hepatocellular carcinoma (HCC) is a hypervascular tumor and accumulating evidence suggests that angiogenesis plays an important role in HCC development. Cordycepin, also known as 3′-deoxyadenosine, is a derivative of adenosine, and numerous cellular enzymes cannot differentiate the two. The aim of the present study was to determine whether cordycepin regulates proliferation, migration and angiogenesis in a human umbilical vein endothelial cell line (EA.hy926) and in a hepatocellular carcinoma cell line (HepG2). MTT was used to assess cell proliferation. Apoptosis was analyzed by flow cytometry (propidium iodide staining). Transwell and wound healing assays were used to analyze the migration and invasion of HepG2 and EA.hy926 cells. Angiogenesis in EA.hy926 cells was assessed using a tube formation assay. Cordycepin strongly suppressed HepG2 and EA.hy926 cell proliferation in a dose- and time-dependent manner. Cordycepin induced EA.hy926 cell apoptosis in a dose-dependent manner (2,000 μg/ml: 50.20±1.55% vs. 0 μg/ml: 2.62±0.19%; P<0.01). Cordycepin inhibited EA.hy926 cell migration (percentage of wound healing area, 2,000 μg/ml: 3.45±0.29% vs. 0 μg/ml: 85.48±0.84%; P<0.05), as well as tube formation (total length of tubular structure, 1,000 μg/ml: 107±39 μm vs. 0 μg/ml: 936±56 μm; P<0.05). Cordycepin also efficiently inhibited HepG2 cell invasion and migration. High-performance liquid chromatography analysis of the cytosol from EA.hy926 cells showed that cordycepin was stable for 3 h. In conclusion, cordycepin not only inhibited human HepG2 cell proliferation and invasion, but also induced apoptosis and inhibited migration and angiogenesis in vascular endothelial cells, suggesting that cordycepin may be used as a novel anti-angiogenic therapy in HCC.
doi:10.3892/ol.2014.1965
PMCID: PMC3997733  PMID: 24765175
cordycepin; angiogenesis; invasion; hepatocellular carcinoma; apoptosis; vascular endothelial cells
4.  Interleukin-10 Inhibits Bone Resorption: A Potential Therapeutic Strategy in Periodontitis and Other Bone Loss Diseases 
BioMed Research International  2014;2014:284836.
Periodontitis and other bone loss diseases, decreasing bone volume and strength, have a significant impact on millions of people with the risk of tooth loss and bone fracture. The integrity and strength of bone are maintained through the balance between bone resorption and bone formation by osteoclasts and osteoblasts, respectively, so the loss of bone results from the disruption of such balance due to increased resorption or/and decreased formation of bone. The goal of therapies for diseases of bone loss is to reduce bone loss, improve bone formation, and then keep healthy bone density. Current therapies have mostly relied on long-term medication, exercise, anti-inflammatory therapies, and changing of the life style. However there are some limitations for some patients in the effective treatments for bone loss diseases because of the complexity of bone loss. Interleukin-10 (IL-10) is a potent anti-inflammatory cytokine, and recent studies have indicated that IL-10 can contribute to the maintenance of bone mass through inhibition of osteoclastic bone resorption and regulation of osteoblastic bone formation. This paper will provide a brief overview of the role of IL-10 in bone loss diseases and discuss the possibility of IL-10 adoption in therapy of bone loss diseases therapy.
doi:10.1155/2014/284836
PMCID: PMC3947664  PMID: 24696846
5.  A Meta-Analysis Identifies New Loci Associated with Body Mass index in Individuals of African Ancestry 
Monda, Keri L. | Chen, Gary K. | Taylor, Kira C. | Palmer, Cameron | Edwards, Todd L. | Lange, Leslie A. | Ng, Maggie C.Y. | Adeyemo, Adebowale A. | Allison, Matthew A. | Bielak, Lawrence F. | Chen, Guanji | Graff, Mariaelisa | Irvin, Marguerite R. | Rhie, Suhn K. | Li, Guo | Liu, Yongmei | Liu, Youfang | Lu, Yingchang | Nalls, Michael A. | Sun, Yan V. | Wojczynski, Mary K. | Yanek, Lisa R. | Aldrich, Melinda C. | Ademola, Adeyinka | Amos, Christopher I. | Bandera, Elisa V. | Bock, Cathryn H. | Britton, Angela | Broeckel, Ulrich | Cai, Quiyin | Caporaso, Neil E. | Carlson, Chris | Carpten, John | Casey, Graham | Chen, Wei-Min | Chen, Fang | Chen, Yii-Der I. | Chiang, Charleston W.K. | Coetzee, Gerhard A. | Demerath, Ellen | Deming-Halverson, Sandra L. | Driver, Ryan W. | Dubbert, Patricia | Feitosa, Mary F. | Freedman, Barry I. | Gillanders, Elizabeth M. | Gottesman, Omri | Guo, Xiuqing | Haritunians, Talin | Harris, Tamara | Harris, Curtis C. | Hennis, Anselm JM | Hernandez, Dena G. | McNeill, Lorna H. | Howard, Timothy D. | Howard, Barbara V. | Howard, Virginia J. | Johnson, Karen C. | Kang, Sun J. | Keating, Brendan J. | Kolb, Suzanne | Kuller, Lewis H. | Kutlar, Abdullah | Langefeld, Carl D. | Lettre, Guillaume | Lohman, Kurt | Lotay, Vaneet | Lyon, Helen | Manson, JoAnn E. | Maixner, William | Meng, Yan A. | Monroe, Kristine R. | Morhason-Bello, Imran | Murphy, Adam B. | Mychaleckyj, Josyf C. | Nadukuru, Rajiv | Nathanson, Katherine L. | Nayak, Uma | N’Diaye, Amidou | Nemesure, Barbara | Wu, Suh-Yuh | Leske, M. Cristina | Neslund-Dudas, Christine | Neuhouser, Marian | Nyante, Sarah | Ochs-Balcom, Heather | Ogunniyi, Adesola | Ogundiran, Temidayo O. | Ojengbede, Oladosu | Olopade, Olufunmilayo I. | Palmer, Julie R. | Ruiz-Narvaez, Edward A. | Palmer, Nicholette D. | Press, Michael F. | Rampersaud, Evandine | Rasmussen-Torvik, Laura J. | Rodriguez-Gil, Jorge L. | Salako, Babatunde | Schadt, Eric E. | Schwartz, Ann G. | Shriner, Daniel A. | Siscovick, David | Smith, Shad B. | Wassertheil-Smoller, Sylvia | Speliotes, Elizabeth K. | Spitz, Margaret R. | Sucheston, Lara | Taylor, Herman | Tayo, Bamidele O. | Tucker, Margaret A. | Van Den Berg, David J. | Velez Edwards, Digna R. | Wang, Zhaoming | Wiencke, John K. | Winkler, Thomas W. | Witte, John S. | Wrensch, Margaret | Wu, Xifeng | Yang, James J. | Levin, Albert M. | Young, Taylor R. | Zakai, Neil A. | Cushman, Mary | Zanetti, Krista A. | Zhao, Jing Hua | Zhao, Wei | Zheng, Yonglan | Zhou, Jie | Ziegler, Regina G. | Zmuda, Joseph M. | Fernandes, Jyotika K. | Gilkeson, Gary S. | Kamen, Diane L. | Hunt, Kelly J. | Spruill, Ida J. | Ambrosone, Christine B. | Ambs, Stefan | Arnett, Donna K. | Atwood, Larry | Becker, Diane M. | Berndt, Sonja I. | Bernstein, Leslie | Blot, William J. | Borecki, Ingrid B. | Bottinger, Erwin P. | Bowden, Donald W. | Burke, Gregory | Chanock, Stephen J. | Cooper, Richard S. | Ding, Jingzhong | Duggan, David | Evans, Michele K. | Fox, Caroline | Garvey, W. Timothy | Bradfield, Jonathan P. | Hakonarson, Hakon | Grant, Struan F.A. | Hsing, Ann | Chu, Lisa | Hu, Jennifer J. | Huo, Dezheng | Ingles, Sue A. | John, Esther M. | Jordan, Joanne M. | Kabagambe, Edmond K. | Kardia, Sharon L.R. | Kittles, Rick A. | Goodman, Phyllis J. | Klein, Eric A. | Kolonel, Laurence N. | Le Marchand, Loic | Liu, Simin | McKnight, Barbara | Millikan, Robert C. | Mosley, Thomas H. | Padhukasahasram, Badri | Williams, L. Keoki | Patel, Sanjay R. | Peters, Ulrike | Pettaway, Curtis A. | Peyser, Patricia A. | Psaty, Bruce M. | Redline, Susan | Rotimi, Charles N. | Rybicki, Benjamin A. | Sale, Michèle M. | Schreiner, Pamela J. | Signorello, Lisa B. | Singleton, Andrew B. | Stanford, Janet L. | Strom, Sara S. | Thun, Michael J. | Vitolins, Mara | Zheng, Wei | Moore, Jason H. | Williams, Scott M. | Zhu, Xiaofeng | Zonderman, Alan B. | Kooperberg, Charles | Papanicolaou, George | Henderson, Brian E. | Reiner, Alex P. | Hirschhorn, Joel N. | Loos, Ruth JF | North, Kari E. | Haiman, Christopher A.
Nature genetics  2013;45(6):690-696.
Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry, and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one novel locus at 5q33 (GALNT10, rs7708584, p=3.4×10−11) and another at 7p15 when combined with data from the Giant consortium (MIR148A/NFE2L3, rs10261878, p=1.2×10−10). We also found suggestive evidence of an association at a third locus at 6q16 in the African ancestry sample (KLHL32, rs974417, p=6.9×10−8). Thirty-two of the 36 previously established BMI variants displayed directionally consistent effect estimates in our GWAS (binomial p=9.7×10−7), of which five reached genome-wide significance. These findings provide strong support for shared BMI loci across populations as well as for the utility of studying ancestrally diverse populations.
doi:10.1038/ng.2608
PMCID: PMC3694490  PMID: 23583978
6.  Variants in CXADR and F2RL1 are associated with blood pressure and obesity in African-Americans in regions identified through admixture mapping 
Journal of hypertension  2012;30(10):1970-1976.
Objective
Genetic variants in 296 genes in regions identified through admixture mapping of hypertension, BMI, and lipids were assessed for association with hypertension, blood pressure, BMI, and HDL-C.
Methods
This study identified coding SNPs identified from HapMap2 data that were located in genes on chromosomes 5, 6, 8, and 21, where ancestry association evidence for hypertension, BMI or HDL-C was identified in previous admixture mapping studies. Genotyping was performed in 1,733 unrelated African-Americans from the National Heart, Lung and Blood Institute’s (NHLBI) Family Blood Pressure Project, and gene-based association analyses were conducted for hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), BMI, and HDL-C. A gene score based on the number of minor alleles of each SNP in a gene was created and used for gene-based regression analyses, adjusting for age, age2, sex, local marker ancestry, and BMI, as applicable. An individual’s African ancestry estimated from 2,507 ancestry-informative markers was also adjusted for to eliminate any confounding due to population stratification.
Results
CXADR (rs437470) on chromosome 21 was associated with SBP and DBP with or without adjusting for local ancestry (p < 0.0006). F2RL1 (rs631465) on chromosome 5 was associated with BMI (p = 0.0005). Local ancestry in these regions was associated with the respective traits as well.
Conclusions
This study suggests that CXADR and F2RL1 likely play important roles in blood pressure and obesity variation, respectively; and these findings are consistent with other studies, so replication and functional analyses are necessary.
doi:10.1097/HJH.0b013e3283578c80
PMCID: PMC3575678  PMID: 22914544
Blood pressure; Obesity; African Americans; Genetic Association Studies
7.  Power Comparison of Admixture Mapping and Direct Association Analysis in Genome-Wide Association Studies 
Genetic epidemiology  2012;36(3):235-243.
When dense markers are available, one can interrogate almost every common variant across the genome via imputation and single nucleotide polymorphism (SNP) test, which has become a routine in current genome-wide association studies (GWASs). As a complement, admixture mapping exploits the long-range linkage disequilibrium (LD) generated by admixture between genetically distinct ancestral populations. It is then questionable whether admixture mapping analysis is still necessary in detecting the disease associated variants in admixed populations. We argue that admixture mapping is able to reduce the burden of massive comparisons in GWASs; it therefore can be a powerful tool to locate the disease variants with substantial allele frequency differences between ancestral populations. In this report we studied a two-stage approach, where candidate regions are defined by conducting admixture mapping at stage 1, and single SNP association tests are followed at stage 2 within the candidate regions defined at stage 1. We first established the genome-wide significance levels corresponding to the criteria to define the candidate regions at stage 1 by simulations. We next compared the power of the two-stage approach with direct association analysis. Our simulations suggest that the two-stage approach can be more powerful than the standard genome-wide association analysis when the allele frequency difference of a causal variant in ancestral populations, is larger than 0.4. Our conclusion is consistent with a theoretical prediction by Risch and Tang ([2006] Am J Hum Genet 79:S254). Surprisingly, our study also suggests that power can be improved when we use less strict criteria to define the candidate regions at stage 1.
doi:10.1002/gepi.21616
PMCID: PMC3589174  PMID: 22460597
genome-wide association studies; admixture mapping; permutation based significance thresholds; two-stage approach
8.  Machine Perfusion versus Cold Storage of Kidneys Derived from Donation after Cardiac Death: A Meta-Analysis 
PLoS ONE  2013;8(3):e56368.
Background
In response to the increased organ shortage, organs derived from donation after cardiac death (DCD) donors are becoming an acceptable option once again for clinical use in transplantation. However, transplant outcomes in cases where DCD organs are used are not as favorable as those from donation after brain death or living donors. Different methods of organ preservation are a key factor that may influence the outcomes of DCD kidney transplantation.
Methods
We compared the transplant outcomes in patients receiving DCD kidneys preserved by machine perfusion (MP) or by static cold storage (CS) preservation by conducting a meta-analysis. The MEDLINE, EMBASE and Cochrane Library databases were searched. All studies reporting outcomes for MP versus CS preserved DCD kidneys were further considered for inclusion in this meta-analysis. Odds ratios and 95% confidence intervals (CI) were calculated to compare the pooled data between groups that were transplanted with kidneys that were preserved by MP or CS.
Results
Four prospective, randomized, controlled trials, involving 175 MP and 176 CS preserved DCD kidney transplant recipients, were included. MP preserved DCD kidney transplant recipients had a decreased incidence of delayed graft function (DGF) with an odd ration of 0.56 (95% CI = 0.36–0.86, P = 0.008) compared to CS. However, no significant differences were seen between the two technologies in incidence of primary non-function, one year graft survival, or one year patient survival.
Conclusions
MP preservation of DCD kidneys is superior to CS in terms of reducing DGF rate post-transplant. However, primary non-function, one year graft survival, and one year patient survival were not affected by the use of MP or CS for preservation.
doi:10.1371/journal.pone.0056368
PMCID: PMC3594243  PMID: 23536758
9.  Allowing for Population Stratification in Association Analysis 
In genetic association studies, it is necessary to correct for population structure to avoid inference bias. During the past decade, prevailing corrections often only involved adjustments of global ancestry differences between sampled individuals. Nevertheless, population structure may vary across local genomic regions due to the variability of local ancestries associated with natural selection, migration, or random genetic drift. Adjusting for global ancestry alone may be inadequate when local population structure is an important confounding factor. In contrast, adjusting for local ancestry can more effectively prevent false-positives due to local population structure. To more accurately locate disease genes, we recommend adjusting for local ancestries by interrogating local structure. In practice, locus-specific ancestries are usually unknown and cannot be accurately inferred when ancestral population information is not available. For such scenarios, we propose employing local principal components (PC) to represent local ancestries and adjusting for local PCs when testing for genotype–phenotype association. With an acceptable computation burden, the proposed algorithm successfully eliminates the known spurious association between SNPs in the LCT gene and height due to the population structure in European Americans.
doi:10.1007/978-1-61779-555-8_21
PMCID: PMC3589145  PMID: 22307710
Genome-wide association studies; Local ancestries; Local principal components; Migration; Random genetic drift; Natural selection; Genomic inflation factor; Genomic control; Local ancestry principal components correction; Fine mapping
10.  A variance component based multi-marker association test using family and unrelated data 
BMC Genetics  2013;14:17.
Background
Incorporating family data in genetic association studies has become increasingly appreciated, especially for its potential value in testing rare variants. We introduce here a variance-component based association test that can test multiple common or rare variants jointly using both family and unrelated samples.
Results
The proposed approach implemented in our R package aggregates or collapses the information across a region based on genetic similarity instead of genotype scores, which avoids the power loss when the effects are in different directions or have different association strengths. The method is also able to effectively leverage the LD information in a region and it can produce a test statistic with an adaptively estimated number of degrees of freedom. Our method can readily allow for the adjustment of non-genetic contributions to the familial similarity, as well as multiple covariates.
Conclusions
We demonstrate through simulations that the proposed method achieves good performance in terms of Type I error control and statistical power. The method is implemented in the R package “fassoc”, which provides a useful tool for data analysis and exploration.
doi:10.1186/1471-2156-14-17
PMCID: PMC3614458  PMID: 23497289
Association studies; Family data; Score test; Multi-marker test
11.  Two-marker association tests yield new disease associations for coronary artery disease and hypertension 
Human genetics  2011;130(6):725-733.
It has been postulated that multiple-marker methods may have added ability, over single-marker methods, to detect genetic variants associated with disease. The Wellcome Trust Case Control Consortium (WTCCC) provided the first successful large genome-wide association studies (GWAS) which included single-marker association analyses for seven common complex diseases. Of those signals detected, only one was associated with coronary artery disease (CAD), and none were identified for hypertension (HTN). Our objective was to find additional genetic associations and pathways for cardiovascular disease by examining the WTCCC data for variants associated with CAD and HTN using two-marker testing methods. We applied two-marker association testing to the WTCCC dataset, which includes ~2,000 affected individuals with each disorder, and a shared pool of ~3,000 controls, all genotyped using Affymetrix GeneChip 500 K arrays. For CAD, we detected single nucleotide polymorphisms (SNP) pairs in three genes showing genome-wide significance: HFE2, STK32B, and DIPC2. The most notable SNP pairs in a non-protein-coding region were at 9p21, a known major CAD-associated region. For HTN, we detected SNP pairs in five genes: GPR39, XRCC4, MYO6, ZFAT, and MACROD2. Four further associated SNP pair regions were at least 70 kb from any known gene. We have shown that novel, multiple-marker, statistical methods can be of use in finding variants in GWAS. We describe many new, associated variants for both CAD and HTN and describe their known genetic mechanisms.
doi:10.1007/s00439-011-1009-6
PMCID: PMC3576836  PMID: 21626137
12.  The Analysis of Ethnic Mixtures 
Populations of ethnic mixtures can be useful in genetic studies. Admixture mapping, or mapping by admixture linkage disequilibrium (MALD), is specially developed for admixed populations and can supplement traditional genome-wide association analyses in the search for genetic variants underlying complex traits. Admixture mapping tests the association between a trait and locus-specific ancestries. The locus-specific ancestries are in linkage disequilibrium (LD) which is generated by the admixture process between genetically distinct ancestral populations. Because of highly correlated locus-specific ancestries, admixture mapping performs many fewer independent tests across the genome than current genome-wide association analysis. Therefore, admixture mapping can be more powerful because of the smaller penalty due to multiple tests. In this chapter, I introduce the theory behind admixture mapping and how we conduct the analysis in practice.
doi:10.1007/978-1-61779-555-8_25
PMCID: PMC3576839  PMID: 22307714
Admixture mapping; Population admixture; Ancestry information marker; Hidden Markov model
13.  Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data 
BMC Systems Biology  2012;6(Suppl 3):S15.
Background
Interactions among genomic loci (also known as epistasis) have been suggested as one of the potential sources of missing heritability in single locus analysis of genome-wide association studies (GWAS). The computational burden of searching for interactions is compounded by the extremely low threshold for identifying significant p-values due to multiple hypothesis testing corrections. Utilizing prior biological knowledge to restrict the set of candidate SNP pairs to be tested can alleviate this problem, but systematic studies that investigate the relative merits of integrating different biological frameworks and GWAS data have not been conducted.
Results
We developed four biologically based frameworks to identify pairwise interactions among candidate SNP pairs as follows: (1) for each human protein-coding gene, a set of SNPs associated with that gene was constructed providing a gene-based interaction model, (2) for each known biological pathway, a set of SNPs associated with the genes in the pathway was constructed providing a pathway-based interaction model, (3) a set of SNPs associated with genes in a disease-related subnetwork provides a network-based interaction model, and (4) a framework is based on the function of SNPs. The last approach uses expression SNPs (eSNPs or eQTLs), which are SNPs or loci that have defined effects on the abundance of transcripts of other genes. We constructed pairs of eSNPs and SNPs located in the target genes whose expression is regulated by eSNPs. For all four frameworks the SNP sets were exhaustively tested for pairwise interactions within the sets using a traditional logistic regression model after excluding genes that were previously identified to associate with the trait. Using previously published GWAS data for type 2 diabetes (T2D) and the biologically based pair-wise interaction modeling, we identify twelve genes not seen in the previous single locus analysis.
Conclusion
We present four approaches to detect interactions associated with complex diseases. The results show our approaches outperform the traditional single locus approaches in detecting genes that previously did not reach significance; the results also provide novel drug targets and biomarkers relevant to the underlying mechanisms of disease.
doi:10.1186/1752-0509-6-S3-S15
PMCID: PMC3524014  PMID: 23281810
14.  Association of Genetic Loci with Sleep Apnea in European Americans and African-Americans: The Candidate Gene Association Resource (CARe) 
PLoS ONE  2012;7(11):e48836.
Although obstructive sleep apnea (OSA) is known to have a strong familial basis, no genetic polymorphisms influencing apnea risk have been identified in cross-cohort analyses. We utilized the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe) to identify sleep apnea susceptibility loci. Using a panel of 46,449 polymorphisms from roughly 2,100 candidate genes on a customized Illumina iSelect chip, we tested for association with the apnea hypopnea index (AHI) as well as moderate to severe OSA (AHI≥15) in 3,551 participants of the Cleveland Family Study and two cohorts participating in the Sleep Heart Health Study.
Among 647 African-Americans, rs11126184 in the pleckstrin (PLEK) gene was associated with OSA while rs7030789 in the lysophosphatidic acid receptor 1 (LPAR1) gene was associated with AHI using a chip-wide significance threshold of p-value<2×10−6. Among 2,904 individuals of European ancestry, rs1409986 in the prostaglandin E2 receptor (PTGER3) gene was significantly associated with OSA. Consistency of effects between rs7030789 and rs1409986 in LPAR1 and PTGER3 and apnea phenotypes were observed in independent clinic-based cohorts.
Novel genetic loci for apnea phenotypes were identified through the use of customized gene chips and meta-analyses of cohort data with replication in clinic-based samples. The identified SNPs all lie in genes associated with inflammation suggesting inflammation may play a role in OSA pathogenesis.
doi:10.1371/journal.pone.0048836
PMCID: PMC3498243  PMID: 23155414
15.  The efficacy of detecting variants with small effects on the Affymetrix 6.0 platform using pooled DNA 
Human genetics  2011;130(5):607-621.
Genome-wide genotyping of a cohort using pools rather than individual samples has long been proposed as a cost-saving alternative for performing genome-wide association (GWA) studies. However, successful disease gene mapping using pooled genotyping has thus far been limited to detecting common variants with large effect sizes, which tend not to exist for many complex common diseases or traits. Therefore, for DNA pooling to be a viable strategy for conducting GWA studies, it is important to determine whether commonly used genome-wide SNP array platforms such as the Affymetrix 6.0 array can reliably detect common variants of small effect sizes using pooled DNA. Taking obesity and age at menarche as examples of human complex traits, we assessed the feasibility of genome-wide genotyping of pooled DNA as a single-stage design for phenotype association. By individually genotyping the top associations identified by pooling, we obtained a 14- to 16-fold enrichment of SNPs nominally associated with the phenotype, but we likely missed the top true associations. In addition, we assessed whether genotyping pooled DNA can serve as an inexpensive screen as the second stage of a multi-stage design with a large number of samples by comparing the most cost-effective 3-stage designs with 80% power to detect common variants with genotypic relative risk of 1.1, with and without pooling. Given the current state of the specific technology we employed and the associated genotyping costs, we showed through simulation that a design involving pooling would be 1.07 times more expensive than a design without pooling. Thus, while a significant amount of information exists within the data from pooled DNA, our analysis does not support genotyping pooled DNA as a means to efficiently identify common variants contributing small effects to phenotypes of interest. While our conclusions were based on the specific technology and study design we employed, the approach presented here will be useful for evaluating the utility of other or future genome-wide genotyping platforms in pooled DNA studies.
doi:10.1007/s00439-011-0974-0
PMCID: PMC3474315  PMID: 21424828
16.  PATHWAY-BASED ANALYSIS FOR GENOME-WIDE ASSOCIATION STUDIES USING SUPERVISED PRINCIPAL COMPONENTS 
Genetic epidemiology  2010;34(7):716-724.
Many complex diseases are influenced by genetic variations in multiple genes, each with only a small marginal effect on disease susceptibility. Pathway analysis, which identifies biological pathways associated with disease outcome, has become increasingly popular for genome-wide association studies (GWAS). In addition to combining weak signals from a number of SNPs in the same pathway, results from pathway analysis also shed light on the biological processes underlying disease. We propose a new pathway-based analysis method for GWAS, the supervised principal component analysis (SPCA) model. In the proposed SPCA model, a selected subset of SNPs most associated with disease outcome is used to estimate the latent variable for a pathway. The estimated latent variable for each pathway is an optimal linear combination of a selected subset of SNPs; therefore, the proposed SPCA model provides the ability to borrow strength across the SNPs in a pathway. In addition to identifying pathways associated with disease outcome, SPCA also carries out additional within-category selection to identify the most important SNPs within each gene set. The proposed model operates in a well-established statistical framework and can handle design information such as covariate adjustment and matching information in GWAS. We compare the proposed method with currently available methods using data with realistic linkage disequilibrium structures and we illustrate the SPCA method using the Wellcome Trust Case-Control Consortium Crohn Disease (CD) dataset.
doi:10.1002/gepi.20532
PMCID: PMC3480088  PMID: 20842628
SNPs; genome-wide association; pathway analysis; principal component analysis
17.  Cross-talk between phospho-STAT3 and PLCγ1 plays a critical role in colorectal tumorigenesis 
Molecular cancer research : MCR  2011;9(10):1418-1428.
Hyper-phosphorylation at the Y705 residue of signal transducer and activator of transcription 3 (STAT3) is implicated in tumorigenesis of leukemia and some solid tumors. However, its role in the development of colorectal cancer (CRC) is not well defined. To rigorously test the impact of this phosphorylation on colorectal tumorigenesis, we engineered a STAT3 Y705F knock-in to interrupt STAT3 activity in HCT116 and RKO CRC cells. These STAT3 Y705F mutant cells fail to respond to cytokine stimulation and grow slower than parental cells. These mutant cells are also greatly diminished in their abilities to form colonies in culture, to exhibit anchorage-independent growth in soft agar, and to grow as xenografts in nude mice. These observations strongly support the premise that STAT3 Y705 phosphorylation is crucial in colorectal tumorigenesis. Although it is generally believed that STAT3 functions as a transcription factor, recent studies indicate that transcription-independent functions of STAT3 also play an important role in tumorigenesis. We show here that wild-type STAT3, but not STAT3 Y705F mutant protein, associates with PLCγ1. PLCγ1 is a central signal transducer of growth factor and cytokine signaling pathways that are involved in tumorigenesis. In STAT3 Y705F mutant CRC cells, PLCγ1 activity is reduced. Moreover, over-expression of a constitutively active form of PLC γ1 rescues the transformation defect of STAT3 Y705F mutant cells. In aggregate, our study identifies previously unknown cross-talk between STAT3 and the PLCγ signaling pathways that may play a critical role in colorectal tumorigenesis.
doi:10.1158/1541-7786.MCR-11-0147
PMCID: PMC3196678  PMID: 21840932
STAT3; PLC; colorectal cancer; phosphorylation; PTPRT
18.  Detecting Rare and common Variants for complex traits: sibpair and odds ratio weighted sum statistics (SPWSS, ORWSS) 
Genetic epidemiology  2011;35(5):398-409.
It is generally known that risk variants segregate together with a disease within families but this information has not been used in the existing statistical methods for detecting rare variants. Here we introduce two weighted sum statistics that can apply to either genome-wide association data or resequencing data for identifying rare disease variants: weights calculated based on sibpairs and odd ratios, respectively. We evaluated the two methods via extensive simulations under different disease models. We compared the proposed methods with the weighted sum statistic (WSS) proposed by Madsen and Browning, keeping the same genotyping or resequencing cost. Our methods clearly demonstrate more statistical power than the WSS. In addition, we found using sibpair information can increase power over using only unrelated samples by more than 40%. We applied our methods to the Framingham Heart Study (FHS) and Wellcome Trust Case Control Consortium (WTCCC) hypertension datasets. Although we did not identify any genes as reaching a genome-wide significance level, we found variants in the candidate gene angiotensinogen (AGT) significantly associated with hypertension at P=6.9×10-4, whereas the most significant single SNP association evidence is P=0.063. We further applied the odds ratio weighted method to the IFIH1 gene for type 1 diabetes in the WTCCC data. Our method yielded a P value of 4.82×10-4, much more significant than that obtained by haplotype-based methods. We demonstrated that family data are extremely informative in searching for rare variants underlying complex traits, and the odds ratio weighted sum statistic is more efficient than currently existing methods.
doi:10.1002/gepi.20588
PMCID: PMC3114642  PMID: 21594893
19.  Combined admixture mapping and association analysis identifies a novel blood pressure genetic locus on 5p13: contributions from the CARe consortium 
Human Molecular Genetics  2011;20(11):2285-2295.
Admixture mapping based on recently admixed populations is a powerful method to detect disease variants with substantial allele frequency differences in ancestral populations. We performed admixture mapping analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP), followed by trait-marker association analysis, in 6303 unrelated African-American participants of the Candidate Gene Association Resource (CARe) consortium. We identified five genomic regions (P< 0.001) harboring genetic variants contributing to inter-individual BP variation. In follow-up association analyses, correcting for all tests performed in this study, three loci were significantly associated with SBP and one significantly associated with DBP (P< 10−5). Further analyses suggested that six independent single-nucleotide polymorphisms (SNPs) contributed to the phenotypic variation observed in the admixture mapping analysis. These six SNPs were examined for replication in multiple, large, independent studies of African-Americans [Women's Health Initiative (WHI), Maywood, Genetic Epidemiology Network of Arteriopathy (GENOA) and Howard University Family Study (HUFS)] as well as one native African sample (Nigerian study), with a total replication sample size of 11 882. Meta-analysis of the replication set identified a novel variant (rs7726475) on chromosome 5 between the SUB1 and NPR3 genes, as being associated with SBP and DBP (P< 0.0015 for both); in meta-analyses combining the CARe samples with the replication data, we observed P-values of 4.45 × 10−7 for SBP and 7.52 × 10−7 for DBP for rs7726475 that were significant after accounting for all the tests performed. Our study highlights that admixture mapping analysis can help identify genetic variants missed by genome-wide association studies because of drastically reduced number of tests in the whole genome.
doi:10.1093/hmg/ddr113
PMCID: PMC3090198  PMID: 21422096
20.  A model for 3-methyladenine recognition by 3-methyladenine DNA glycosylase I (TAG) from Staphylococcus aureus  
The structure of 3-methyladenine DNA glycosylase I in complex with 3-methyladenine is reported.
The removal of chemically damaged DNA bases such as 3-methyladenine (3-­MeA) is an essential process in all living organisms and is catalyzed by the enzyme 3-MeA DNA glycosylase I. A key question is how the enzyme selectively recognizes the alkylated 3-MeA over the much more abundant adenine. The crystal structures of native and Y16F-mutant 3-MeA DNA glycosylase I from Staphylococcus aureus in complex with 3-MeA are reported to 1.8 and 2.2 Å resolution, respectively. Isothermal titration calorimetry shows that protonation of 3-MeA decreases its binding affinity, confirming previous fluorescence studies that show that charge–charge recognition is not critical for the selection of 3-MeA over adenine. It is hypothesized that the hydrogen-bonding pattern of Glu38 and Tyr16 of 3-MeA DNA glycosylase I with a particular tautomer unique to 3-MeA contributes to recognition and selection.
doi:10.1107/S1744309112016363
PMCID: PMC3370894  PMID: 22684054
3-methyladenine DNA glycosylase I; fluorescence measurements; ITC; DNA repair; recognition
21.  The mechanism of the enzymatic fluorination in Streptomyces cattleya 
Journal of the American Chemical Society  2007;129(47):14597-14604.
Recently a fluorination enzyme was identified and isolated from Streptomyces cattleya, as the first committed step on the metabolic pathway to the fluorinated metabolites, fluoroacetate and 4-fluorothreonine. This enzyme, 5′-fluoro-5′-deoxy adenosine synthetase (FDAS), has been shown to catalyze C-F bond formation by nucleophilic attack of fluoride ion to S-adenosyl-L-methionine (SAM) with the concomitant displacement of L-methionine to generate 5′-fluoro-5′-deoxy adenosine (5′-FDA). Although the structures of FDAS bound to both SAM and products have been solved, the molecular mechanism remained to be elucidated. We now report site directed mutagenesis studies, structural analyses and isothermal calorimetry (ITC) experiments. The data establish the key residues required for catalysis and the order of substrate binding. Fluoride ion is not readily distinguished from water by protein X-ray crystallography, however using chloride ion (also a substrate) with mutants of low activity has enabled the halide ion to be located in non-productive co-complexes with SAH and SAM. The kinetic data suggest the positively charged sulfur of SAM is a key requirement in stabilizing the transition state. We propose a molecular mechanism for FDAS in which fluoride weakly associates with the enzyme exchanging two water molecules for protein ligation. The binding of SAM expels remaining water associated with fluoride ion and traps the ion in a pocket positioned to react with SAM, generating L-methionine and 5′-FDA. L-SAM then dissociates from the enzyme followed by 5′-FDA.
doi:10.1021/ja0731569
PMCID: PMC3326528  PMID: 17985882
23.  Down-Regulation of microRNA-26a Promotes Mouse Hepatocyte Proliferation during Liver Regeneration 
PLoS ONE  2012;7(4):e33577.
Background
Inadequate liver regeneration (LR) is still an unsolved problem in major liver resection and small-for-size syndrome post-living donor liver transplantation. A number of microRNAs have been shown to play important roles in cell proliferation. Herein, we investigated the role of miR-26a as a pivotal regulator of hepatocyte proliferation in LR.
Methodology/Principal Findings
Adult male C57BL/6J mice, undergoing 70% partial hepatectomy (PH), were treated with Ad5-anti-miR-26a-LUC or Ad5-miR-26a-LUC or Ad5-LUC vector via portal vein. The animals were subjected to in vivo bioluminescence imaging. Serum and liver samples were collected to test liver function, calculate liver-to-body weight ratio (LBWR), document hepatocyte proliferation (Ki-67 staining), and investigate potential targeted gene expression of miR-26a by quantitative real-time PCR and Western blot. The miR-26a level declined during LR after 70% PH. Down-regulation of miR-26a by anti-miR-26a expression led to enhanced proliferation of hepatocytes, and both LBWR and hepatocyte proliferation (Ki-67+ cells %) showed an increased tendency, while liver damage, indicated by aspartate aminotransferase (AST), alanine aminotransferase (ALT) and total bilirubin (T-Bil), was reduced. Furthermore, CCND2 and CCNE2, as possible targeted genes of miR-26a, were up-regulated. In addition, miR-26a over-expression showed converse results.
Conclusions/Significance
MiR-26a plays crucial role in regulating the proliferative phase of LR, probably by repressing expressions of cell cycle proteins CCND2 and CCNE2. The current study reveals a novel miRNA-mediated regulation pattern during the proliferative phase of LR.
doi:10.1371/journal.pone.0033577
PMCID: PMC3319545  PMID: 22496754
24.  Adjustment for local ancestry in genetic association analysis of admixed populations 
Bioinformatics  2010;27(5):670-677.
Motivation: Admixed populations offer a unique opportunity for mapping diseases that have large disease allele frequency differences between ancestral populations. However, association analysis in such populations is challenging because population stratification may lead to association with loci unlinked to the disease locus.
Methods and results: We show that local ancestry at a test single nucleotide polymorphism (SNP) may confound with the association signal and ignoring it can lead to spurious association. We demonstrate theoretically that adjustment for local ancestry at the test SNP is sufficient to remove the spurious association regardless of the mechanism of population stratification, whether due to local or global ancestry differences among study subjects; however, global ancestry adjustment procedures may not be effective. We further develop two novel association tests that adjust for local ancestry. Our first test is based on a conditional likelihood framework which models the distribution of the test SNP given disease status and flanking marker genotypes. A key advantage of this test lies in its ability to incorporate different directions of association in the ancestral populations. Our second test, which is computationally simpler, is based on logistic regression, with adjustment for local ancestry proportion. We conducted extensive simulations and found that the Type I error rates of our tests are under control; however, the global adjustment procedures yielded inflated Type I error rates when stratification is due to local ancestry difference.
Contact: mingyao@upenn.edu; chun.li@vanderbilt.edu.
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btq709
PMCID: PMC3042179  PMID: 21169375
25.  The landscape of recombination in African Americans 
Hinch, Anjali G. | Tandon, Arti | Patterson, Nick | Song, Yunli | Rohland, Nadin | Palmer, Cameron D. | Chen, Gary K. | Wang, Kai | Buxbaum, Sarah G. | Akylbekova, Meggie | Aldrich, Melinda C. | Ambrosone, Christine B. | Amos, Christopher | Bandera, Elisa V. | Berndt, Sonja I. | Bernstein, Leslie | Blot, William J. | Bock, Cathryn H. | Boerwinkle, Eric | Cai, Qiuyin | Caporaso, Neil | Casey, Graham | Cupples, L. Adrienne | Deming, Sandra L. | Diver, W. Ryan | Divers, Jasmin | Fornage, Myriam | Gillanders, Elizabeth M. | Glessner, Joseph | Harris, Curtis C. | Hu, Jennifer J. | Ingles, Sue A. | Isaacs, Williams | John, Esther M. | Kao, W. H. Linda | Keating, Brendan | Kittles, Rick A. | Kolonel, Laurence N. | Larkin, Emma | Le Marchand, Loic | McNeill, Lorna H. | Millikan, Robert C. | Murphy, Adam | Musani, Solomon | Neslund-Dudas, Christine | Nyante, Sarah | Papanicolaou, George J. | Press, Michael F. | Psaty, Bruce M. | Reiner, Alex P. | Rich, Stephen S. | Rodriguez-Gil, Jorge L. | Rotter, Jerome I. | Rybicki, Benjamin A. | Schwartz, Ann G. | Signorello, Lisa B. | Spitz, Margaret | Strom, Sara S. | Thun, Michael J. | Tucker, Margaret A. | Wang, Zhaoming | Wiencke, John K. | Witte, John S. | Wrensch, Margaret | Wu, Xifeng | Yamamura, Yuko | Zanetti, Krista A. | Zheng, Wei | Ziegler, Regina G. | Zhu, Xiaofeng | Redline, Susan | Hirschhorn, Joel N. | Henderson, Brian E. | Taylor, Herman A. | Price, Alkes L. | Hakonarson, Hakon | Chanock, Stephen J. | Haiman, Christopher A. | Wilson, James G. | Reich, David | Myers, Simon R.
Nature  2011;476(7359):170-175.
Recombination, together with mutation, is the ultimate source of genetic variation in populations. We leverage the recent mixture of people of African and European ancestry in the Americas to build a genetic map measuring the probability of crossing-over at each position in the genome, based on about 2.1 million crossovers in 30,000 unrelated African Americans. At intervals of more than three megabases it is nearly identical to a map built in Europeans. At finer scales it differs significantly, and we identify about 2,500 recombination hotspots that are active in people of West African ancestry but nearly inactive in Europeans. The probability of a crossover at these hotspots is almost fully controlled by the alleles an individual carries at PRDM9 (P<10−245). We identify a 17 base pair DNA sequence motif that is enriched in these hotspots, and is an excellent match to the predicted binding target of African-enriched alleles of PRDM9.
doi:10.1038/nature10336
PMCID: PMC3154982  PMID: 21775986

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