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1.  Rapid Whole-Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units 
Science translational medicine  2012;4(154):154ra135.
Monogenic diseases are frequent causes of neonatal morbidity and mortality, and disease presentations are often undifferentiated at birth. More than 3500 monogenic diseases have been characterized, but clinical testing is available for only some of them and many feature clinical and genetic heterogeneity. Hence, an immense unmet need exists for improved molecular diagnosis in infants. Because disease progression is extremely rapid, albeit heterogeneous, in newborns, molecular diagnoses must occur quickly to be relevant for clinical decision-making. We describe 50-hour differential diagnosis of genetic disorders by whole-genome sequencing (WGS) that features automated bioinformatic analysis and is intended to be a prototype for use in neonatal intensive care units. Retrospective 50-hour WGS identified known molecular diagnoses in two children. Prospective WGS disclosed potential molecular diagnosis of a severe GJB2-related skin disease in one neonate; BRAT1-related lethal neonatal rigidity and multifocal seizure syndrome in another infant; identified BCL9L as a novel, recessive visceral heterotaxy gene (HTX6) in a pedigree; and ruled out known candidate genes in one infant. Sequencing of parents or affected siblings expedited the identification of disease genes in prospective cases. Thus, rapid WGS can potentially broaden and foreshorten differential diagnosis, resulting in fewer empirical treatments and faster progression to genetic and prognostic counseling.
doi:10.1126/scitranslmed.3004041
PMCID: PMC4283791  PMID: 23035047
2.  APOBEC3B upregulation and genomic mutation patterns in serous ovarian carcinoma 
Cancer research  2013;73(24):10.1158/0008-5472.CAN-13-1753.
Ovarian cancer is a clinically and molecularly heterogeneous disease. The driving forces behind this variability are unknown. Here we report wide variation in expression of the DNA cytosine deaminase APOBEC3B, with elevated expression in a majority of ovarian cancer cell lines (3 standard deviations above the mean of normal ovarian surface epithelial cells) and high grade primary ovarian cancers. APOBEC3B is active in the nucleus of several ovarian cancer cell lines and elicits a biochemical preference for deamination of cytosines in 5′TC dinucleotides. Importantly, examination of whole-genome sequence from 16 ovarian cancers reveals that APOBEC3B expression correlates with total mutation load as well as elevated levels of transversion mutations. In particular, high APOBEC3B expression correlates with C-to-A and C-to-G transversion mutations within 5′TC dinucleotide motifs in early-stage high grade serous ovarian cancer genomes, suggesting that APOBEC3B-catalyzed genomic uracil lesions are further processed by downstream DNA ‘repair’ enzymes including error-prone translesion polymerases. These data identify a potential role for APOBEC3B in serous ovarian cancer genomic instability.
doi:10.1158/0008-5472.CAN-13-1753
PMCID: PMC3867573  PMID: 24154874
APOBEC3B; DNA cytosine deamination; genomic uracil; ovarian cancer; transversion mutations
3.  Genome Sequencing and Analysis of the Tasmanian Devil and Its Transmissible Cancer 
Cell  2012;148(4):780-791.
Summary
The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genetically diverged during its spread across Tasmania. The devil cancer genome contains more than 17,000 somatic base substitution mutations and bears the imprint of a distinct mutational process. Genotyping of somatic mutations in 104 geographically and temporally distributed Tasmanian devil tumors reveals the pattern of evolution and spread of this parasitic clonal lineage, with evidence of a selective sweep in one geographical area and persistence of parallel lineages in other populations.
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Graphical Abstract
Highlights
► Whole-genome sequences of the Tasmanian devil and two distant cancer subclones ► The Tasmanian devil cancer lineage originated recently in a female devil ► The devil cancer genome is relatively stable despite ongoing evolution ► Clonal divergence and geographic spread elucidated through patterns of mutation
Whole-genome sequences of the Tasmanian devil and two devil cancer subclones suggest that the cancer first arose from a female devil and that the clone has subsequently genetically diverged during its spread across Tasmania.
doi:10.1016/j.cell.2011.11.065
PMCID: PMC3281993  PMID: 22341448
4.  A comprehensive catalogue of somatic mutations from a human cancer genome 
Nature  2009;463(7278):191-196.
All cancers carry somatic mutations. A subset of these somatic alterations, termed driver mutations, confer selective growth advantage and are implicated in cancer development, whereas the remainder are passengers. Here we have sequenced the genomes of a malignant melanoma and a lymphoblastoid cell line from the same person, providing the first comprehensive catalogue of somatic mutations from an individual cancer. The catalogue provides remarkable insights into the forces that have shaped this cancer genome. The dominant mutational signature reflects DNA damage due to ultraviolet light exposure, a known risk factor for malignant melanoma, whereas the uneven distribution of mutations across the genome, with a lower prevalence in gene footprints, indicates that DNA repair has been preferentially deployed towards transcribed regions. The results illustrate the power of a cancer genome sequence to reveal traces of the DNA damage, repair, mutation and selection processes that were operative years before the cancer became symptomatic.
doi:10.1038/nature08658
PMCID: PMC3145108  PMID: 20016485
5.  The DNA sequence of the human X chromosome 
Ross, Mark T. | Grafham, Darren V. | Coffey, Alison J. | Scherer, Steven | McLay, Kirsten | Muzny, Donna | Platzer, Matthias | Howell, Gareth R. | Burrows, Christine | Bird, Christine P. | Frankish, Adam | Lovell, Frances L. | Howe, Kevin L. | Ashurst, Jennifer L. | Fulton, Robert S. | Sudbrak, Ralf | Wen, Gaiping | Jones, Matthew C. | Hurles, Matthew E. | Andrews, T. Daniel | Scott, Carol E. | Searle, Stephen | Ramser, Juliane | Whittaker, Adam | Deadman, Rebecca | Carter, Nigel P. | Hunt, Sarah E. | Chen, Rui | Cree, Andrew | Gunaratne, Preethi | Havlak, Paul | Hodgson, Anne | Metzker, Michael L. | Richards, Stephen | Scott, Graham | Steffen, David | Sodergren, Erica | Wheeler, David A. | Worley, Kim C. | Ainscough, Rachael | Ambrose, Kerrie D. | Ansari-Lari, M. Ali | Aradhya, Swaroop | Ashwell, Robert I. S. | Babbage, Anne K. | Bagguley, Claire L. | Ballabio, Andrea | Banerjee, Ruby | Barker, Gary E. | Barlow, Karen F. | Barrett, Ian P. | Bates, Karen N. | Beare, David M. | Beasley, Helen | Beasley, Oliver | Beck, Alfred | Bethel, Graeme | Blechschmidt, Karin | Brady, Nicola | Bray-Allen, Sarah | Bridgeman, Anne M. | Brown, Andrew J. | Brown, Mary J. | Bonnin, David | Bruford, Elspeth A. | Buhay, Christian | Burch, Paula | Burford, Deborah | Burgess, Joanne | Burrill, Wayne | Burton, John | Bye, Jackie M. | Carder, Carol | Carrel, Laura | Chako, Joseph | Chapman, Joanne C. | Chavez, Dean | Chen, Ellson | Chen, Guan | Chen, Yuan | Chen, Zhijian | Chinault, Craig | Ciccodicola, Alfredo | Clark, Sue Y. | Clarke, Graham | Clee, Chris M. | Clegg, Sheila | Clerc-Blankenburg, Kerstin | Clifford, Karen | Cobley, Vicky | Cole, Charlotte G. | Conquer, Jen S. | Corby, Nicole | Connor, Richard E. | David, Robert | Davies, Joy | Davis, Clay | Davis, John | Delgado, Oliver | DeShazo, Denise | Dhami, Pawandeep | Ding, Yan | Dinh, Huyen | Dodsworth, Steve | Draper, Heather | Dugan-Rocha, Shannon | Dunham, Andrew | Dunn, Matthew | Durbin, K. James | Dutta, Ireena | Eades, Tamsin | Ellwood, Matthew | Emery-Cohen, Alexandra | Errington, Helen | Evans, Kathryn L. | Faulkner, Louisa | Francis, Fiona | Frankland, John | Fraser, Audrey E. | Galgoczy, Petra | Gilbert, James | Gill, Rachel | Glöckner, Gernot | Gregory, Simon G. | Gribble, Susan | Griffiths, Coline | Grocock, Russell | Gu, Yanghong | Gwilliam, Rhian | Hamilton, Cerissa | Hart, Elizabeth A. | Hawes, Alicia | Heath, Paul D. | Heitmann, Katja | Hennig, Steffen | Hernandez, Judith | Hinzmann, Bernd | Ho, Sarah | Hoffs, Michael | Howden, Phillip J. | Huckle, Elizabeth J. | Hume, Jennifer | Hunt, Paul J. | Hunt, Adrienne R. | Isherwood, Judith | Jacob, Leni | Johnson, David | Jones, Sally | de Jong, Pieter J. | Joseph, Shirin S. | Keenan, Stephen | Kelly, Susan | Kershaw, Joanne K. | Khan, Ziad | Kioschis, Petra | Klages, Sven | Knights, Andrew J. | Kosiura, Anna | Kovar-Smith, Christie | Laird, Gavin K. | Langford, Cordelia | Lawlor, Stephanie | Leversha, Margaret | Lewis, Lora | Liu, Wen | Lloyd, Christine | Lloyd, David M. | Loulseged, Hermela | Loveland, Jane E. | Lovell, Jamieson D. | Lozado, Ryan | Lu, Jing | Lyne, Rachael | Ma, Jie | Maheshwari, Manjula | Matthews, Lucy H. | McDowall, Jennifer | McLaren, Stuart | McMurray, Amanda | Meidl, Patrick | Meitinger, Thomas | Milne, Sarah | Miner, George | Mistry, Shailesh L. | Morgan, Margaret | Morris, Sidney | Müller, Ines | Mullikin, James C. | Nguyen, Ngoc | Nordsiek, Gabriele | Nyakatura, Gerald | O’Dell, Christopher N. | Okwuonu, Geoffery | Palmer, Sophie | Pandian, Richard | Parker, David | Parrish, Julia | Pasternak, Shiran | Patel, Dina | Pearce, Alex V. | Pearson, Danita M. | Pelan, Sarah E. | Perez, Lesette | Porter, Keith M. | Ramsey, Yvonne | Reichwald, Kathrin | Rhodes, Susan | Ridler, Kerry A. | Schlessinger, David | Schueler, Mary G. | Sehra, Harminder K. | Shaw-Smith, Charles | Shen, Hua | Sheridan, Elizabeth M. | Shownkeen, Ratna | Skuce, Carl D. | Smith, Michelle L. | Sotheran, Elizabeth C. | Steingruber, Helen E. | Steward, Charles A. | Storey, Roy | Swann, R. Mark | Swarbreck, David | Tabor, Paul E. | Taudien, Stefan | Taylor, Tineace | Teague, Brian | Thomas, Karen | Thorpe, Andrea | Timms, Kirsten | Tracey, Alan | Trevanion, Steve | Tromans, Anthony C. | d’Urso, Michele | Verduzco, Daniel | Villasana, Donna | Waldron, Lenee | Wall, Melanie | Wang, Qiaoyan | Warren, James | Warry, Georgina L. | Wei, Xuehong | West, Anthony | Whitehead, Siobhan L. | Whiteley, Mathew N. | Wilkinson, Jane E. | Willey, David L. | Williams, Gabrielle | Williams, Leanne | Williamson, Angela | Williamson, Helen | Wilming, Laurens | Woodmansey, Rebecca L. | Wray, Paul W. | Yen, Jennifer | Zhang, Jingkun | Zhou, Jianling | Zoghbi, Huda | Zorilla, Sara | Buck, David | Reinhardt, Richard | Poustka, Annemarie | Rosenthal, André | Lehrach, Hans | Meindl, Alfons | Minx, Patrick J. | Hillier, LaDeana W. | Willard, Huntington F. | Wilson, Richard K. | Waterston, Robert H. | Rice, Catherine M. | Vaudin, Mark | Coulson, Alan | Nelson, David L. | Weinstock, George | Sulston, John E. | Durbin, Richard | Hubbard, Tim | Gibbs, Richard A. | Beck, Stephan | Rogers, Jane | Bentley, David R.
Nature  2005;434(7031):325-337.
The human X chromosome has a unique biology that was shaped by its evolution as the sex chromosome shared by males and females. We have determined 99.3% of the euchromatic sequence of the X chromosome. Our analysis illustrates the autosomal origin of the mammalian sex chromosomes, the stepwise process that led to the progressive loss of recombination between X and Y, and the extent of subsequent degradation of the Y chromosome. LINE1 repeat elements cover one-third of the X chromosome, with a distribution that is consistent with their proposed role as way stations in the process of X-chromosome inactivation. We found 1,098 genes in the sequence, of which 99 encode proteins expressed in testis and in various tumour types. A disproportionately high number of mendelian diseases are documented for the X chromosome. Of this number, 168 have been explained by mutations in 113 X-linked genes, which in many cases were characterized with the aid of the DNA sequence.
doi:10.1038/nature03440
PMCID: PMC2665286  PMID: 15772651
6.  Requirement of bic/microRNA-155 for Normal Immune Function 
Science (New York, N.Y.)  2007;316(5824):608-611.
MicroRNAs are a class of small RNAs that are increasingly being recognized as important regulators of gene expression. Although hundreds of microRNAs are present in the mammalian genome, genetic studies addressing their physiological roles are at an early stage. We have shown that mice deficient for bic/microRNA-155 are immunodeficient and display increased lung airway remodeling. We demonstrate a requirement of bic/microRNA-155 for the function of B and T lymphocytes and dendritic cells. Transcriptome analysis of bic/microRNA-155–deficient CD4+ T cells identified a wide spectrum of microRNA-155–regulated genes, including cytokines, chemokines, and transcription factors. Our work suggests that bic/microRNA-155 plays a key role in the homeostasis and function of the immune system.
doi:10.1126/science.1139253
PMCID: PMC2610435  PMID: 17463290
7.  DNA sequence of human chromosome 17 and analysis of rearrangement in the human lineage 
Zody, Michael C. | Garber, Manuel | Adams, David J. | Sharpe, Ted | Harrow, Jennifer | Lupski, James R. | Nicholson, Christine | Searle, Steven M. | Wilming, Laurens | Young, Sarah K. | Abouelleil, Amr | Allen, Nicole R. | Bi, Weimin | Bloom, Toby | Borowsky, Mark L. | Bugalter, Boris E. | Butler, Jonathan | Chang, Jean L. | Chen, Chao-Kung | Cook, April | Corum, Benjamin | Cuomo, Christina A. | de Jong, Pieter J. | DeCaprio, David | Dewar, Ken | FitzGerald, Michael | Gilbert, James | Gibson, Richard | Gnerre, Sante | Goldstein, Steven | Grafham, Darren V. | Grocock, Russell | Hafez, Nabil | Hagopian, Daniel S. | Hart, Elizabeth | Norman, Catherine Hosage | Humphray, Sean | Jaffe, David B. | Jones, Matt | Kamal, Michael | Khodiyar, Varsha K. | LaButti, Kurt | Laird, Gavin | Lehoczky, Jessica | Liu, Xiaohong | Lokyitsang, Tashi | Loveland, Jane | Lui, Annie | Macdonald, Pendexter | Major, John E. | Matthews, Lucy | Mauceli, Evan | McCarroll, Steven A. | Mihalev, Atanas H. | Mudge, Jonathan | Nguyen, Cindy | Nicol, Robert | O'Leary, Sinéad B. | Osoegawa, Kazutoyo | Schwartz, David C. | Shaw-Smith, Charles | Stankiewicz, Pawel | Steward, Charles | Swarbreck, David | Venkataraman, Vijay | Whittaker, Charles A. | Yang, Xiaoping | Zimmer, Andrew R. | Bradley, Allan | Hubbard, Tim | Birren, Bruce W. | Rogers, Jane | Lander, Eric S. | Nusbaum, Chad
Nature  2006;440(7087):1045-1049.
Chromosome 17 is unusual among the human chromosomes in many respects. It is the largest human autosome with orthology to only a single mouse chromosome1, mapping entirely to the distal half of mouse chromosome 11. Chromosome 17 is rich in protein-coding genes, having the second highest gene density in the genome2,3. It is also enriched in segmental duplications, ranking third in density among the autosomes4. Here we report a finished sequence for human chromosome 17, as well as a structural comparison with the finished sequence for mouse chromosome 11, the first finished mouse chromosome. Comparison of the orthologous regions reveals striking differences. In contrast to the typical pattern seen in mammalian evolution5,6, the human sequence has undergone extensive intrachromosomal rearrangement, whereas the mouse sequence has been remarkably stable. Moreover, although the human sequence has a high density of segmental duplication, the mouse sequence has a very low density. Notably, these segmental duplications correspond closely to the sites of structural rearrangement, demonstrating a link between duplication and rearrangement. Examination of the main classes of duplicated segments provides insight into the dynamics underlying expansion of chromosome-specific, low-copy repeats in the human genome.
doi:10.1038/nature04689
PMCID: PMC2610434  PMID: 16625196
8.  Construction, Visualisation, and Clustering of Transcription Networks from Microarray Expression Data 
PLoS Computational Biology  2007;3(10):e206.
Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express3D.
Author Summary
This paper describes a novel approach for analysis of gene expression data. In this approach, normalized gene expression data is transformed into a graph where nodes in the graph represent transcripts connected to each other by virtue of their coexpression across multiple tissues or samples. The graph paradigm has many advantages for such analyses. Graph clustering of the derived network performs extremely well in comparison to traditional pairwise schemes. We show that this approach is robust and able to accommodate large datasets such as the Genomics Institute of the Novartis Research Foundation mouse tissue atlas. The entire approach and algorithms are combined into a single open-source JAVA application that allows users to perform this analysis and further mining on their own data and to visualize the results interactively in 3-D. The approach is not limited to gene expression data but would also be useful for other complex biological datasets. We use the method to investigate the relationship between the phylogenetic age of transcripts and their tissue specificity.
doi:10.1371/journal.pcbi.0030206
PMCID: PMC2041979  PMID: 17967053
9.  RNA editing of human microRNAs 
Genome Biology  2006;7(4):R27.
A survey of RNA editing of miRNAs from ten human tissues indicates that RNA editing increases the diversity of miRNAs and their targets.
Background
MicroRNAs (miRNAs) are short RNAs of around 22 nucleotides that regulate gene expression. The primary transcripts of miRNAs contain double-stranded RNA and are therefore potential substrates for adenosine to inosine (A-to-I) RNA editing.
Results
We have conducted a survey of RNA editing of miRNAs from ten human tissues by sequence comparison of PCR products derived from matched genomic DNA and total cDNA from the same individual. Six out of 99 (6%) miRNA transcripts from which data were obtained were subject to A-to-I editing in at least one tissue. Four out of seven edited adenosines were in the mature miRNA and were predicted to change the target sites in 3' untranslated regions. For a further six miRNAs, we identified A-to-I editing of transcripts derived from the opposite strand of the genome to the annotated miRNA. These miRNAs may have been annotated to the wrong genomic strand.
Conclusion
Our results indicate that RNA editing increases the diversity of miRNAs and their targets, and hence may modulate miRNA function.
doi:10.1186/gb-2006-7-4-r27
PMCID: PMC1557993  PMID: 16594986
10.  miRBase: microRNA sequences, targets and gene nomenclature 
Nucleic Acids Research  2005;34(Database issue):D140-D144.
The miRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. miRBase takes over functionality from the microRNA Registry and fulfils three main roles: the miRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. miRBase Sequences is the primary online repository for miRNA sequence data and annotation. miRBase Targets is a comprehensive new database of predicted miRNA target genes. miRBase is available at .
doi:10.1093/nar/gkj112
PMCID: PMC1347474  PMID: 16381832
11.  Variation in the strength of selected codon usage bias among bacteria 
Nucleic Acids Research  2005;33(4):1141-1153.
Among bacteria, many species have synonymous codon usage patterns that have been influenced by natural selection for those codons that are translated more accurately and/or efficiently. However, in other species selection appears to have been ineffective. Here, we introduce a population genetics-based model for quantifying the extent to which selection has been effective. The approach is applied to 80 phylogenetically diverse bacterial species for which whole genome sequences are available. The strength of selected codon usage bias, S, is found to vary substantially among species; in 30% of the genomes examined, there was no significant evidence that selection had been effective. Values of S are highly positively correlated with both the number of rRNA operons and the number of tRNA genes. These results are consistent with the hypothesis that species exposed to selection for rapid growth have more rRNA operons, more tRNA genes and more strongly selected codon usage bias. For example, Clostridium perfringens, the species with the highest value of S, can have a generation time as short as 7 min.
doi:10.1093/nar/gki242
PMCID: PMC549432  PMID: 15728743

Results 1-11 (11)