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author:("Leung, kenri")
1.  The zebrafish reference genome sequence and its relationship to the human genome 
Howe, Kerstin | Clark, Matthew D. | Torroja, Carlos F. | Torrance, James | Berthelot, Camille | Muffato, Matthieu | Collins, John E. | Humphray, Sean | McLaren, Karen | Matthews, Lucy | McLaren, Stuart | Sealy, Ian | Caccamo, Mario | Churcher, Carol | Scott, Carol | Barrett, Jeffrey C. | Koch, Romke | Rauch, Gerd-Jörg | White, Simon | Chow, William | Kilian, Britt | Quintais, Leonor T. | Guerra-Assunção, José A. | Zhou, Yi | Gu, Yong | Yen, Jennifer | Vogel, Jan-Hinnerk | Eyre, Tina | Redmond, Seth | Banerjee, Ruby | Chi, Jianxiang | Fu, Beiyuan | Langley, Elizabeth | Maguire, Sean F. | Laird, Gavin K. | Lloyd, David | Kenyon, Emma | Donaldson, Sarah | Sehra, Harminder | Almeida-King, Jeff | Loveland, Jane | Trevanion, Stephen | Jones, Matt | Quail, Mike | Willey, Dave | Hunt, Adrienne | Burton, John | Sims, Sarah | McLay, Kirsten | Plumb, Bob | Davis, Joy | Clee, Chris | Oliver, Karen | Clark, Richard | Riddle, Clare | Eliott, David | Threadgold, Glen | Harden, Glenn | Ware, Darren | Mortimer, Beverly | Kerry, Giselle | Heath, Paul | Phillimore, Benjamin | Tracey, Alan | Corby, Nicole | Dunn, Matthew | Johnson, Christopher | Wood, Jonathan | Clark, Susan | Pelan, Sarah | Griffiths, Guy | Smith, Michelle | Glithero, Rebecca | Howden, Philip | Barker, Nicholas | Stevens, Christopher | Harley, Joanna | Holt, Karen | Panagiotidis, Georgios | Lovell, Jamieson | Beasley, Helen | Henderson, Carl | Gordon, Daria | Auger, Katherine | Wright, Deborah | Collins, Joanna | Raisen, Claire | Dyer, Lauren | Leung, Kenric | Robertson, Lauren | Ambridge, Kirsty | Leongamornlert, Daniel | McGuire, Sarah | Gilderthorp, Ruth | Griffiths, Coline | Manthravadi, Deepa | Nichol, Sarah | Barker, Gary | Whitehead, Siobhan | Kay, Michael | Brown, Jacqueline | Murnane, Clare | Gray, Emma | Humphries, Matthew | Sycamore, Neil | Barker, Darren | Saunders, David | Wallis, Justene | Babbage, Anne | Hammond, Sian | Mashreghi-Mohammadi, Maryam | Barr, Lucy | Martin, Sancha | Wray, Paul | Ellington, Andrew | Matthews, Nicholas | Ellwood, Matthew | Woodmansey, Rebecca | Clark, Graham | Cooper, James | Tromans, Anthony | Grafham, Darren | Skuce, Carl | Pandian, Richard | Andrews, Robert | Harrison, Elliot | Kimberley, Andrew | Garnett, Jane | Fosker, Nigel | Hall, Rebekah | Garner, Patrick | Kelly, Daniel | Bird, Christine | Palmer, Sophie | Gehring, Ines | Berger, Andrea | Dooley, Christopher M. | Ersan-Ürün, Zübeyde | Eser, Cigdem | Geiger, Horst | Geisler, Maria | Karotki, Lena | Kirn, Anette | Konantz, Judith | Konantz, Martina | Oberländer, Martina | Rudolph-Geiger, Silke | Teucke, Mathias | Osoegawa, Kazutoyo | Zhu, Baoli | Rapp, Amanda | Widaa, Sara | Langford, Cordelia | Yang, Fengtang | Carter, Nigel P. | Harrow, Jennifer | Ning, Zemin | Herrero, Javier | Searle, Steve M. J. | Enright, Anton | Geisler, Robert | Plasterk, Ronald H. A. | Lee, Charles | Westerfield, Monte | de Jong, Pieter J. | Zon, Leonard I. | Postlethwait, John H. | Nüsslein-Volhard, Christiane | Hubbard, Tim J. P. | Crollius, Hugues Roest | Rogers, Jane | Stemple, Derek L.
Nature  2013;496(7446):498-503.
Zebrafish have become a popular organism for the study of vertebrate gene function1,2. The virtually transparent embryos of this species, and the ability to accelerate genetic studies by gene knockdown or overexpression, have led to the widespread use of zebrafish in the detailed investigation of vertebrate gene function and increasingly, the study of human genetic disease3–5. However, for effective modelling of human genetic disease it is important to understand the extent to which zebrafish genes and gene structures are related to orthologous human genes. To examine this, we generated a high-quality sequence assembly of the zebrafish genome, made up of an overlapping set of completely sequenced large-insert clones that were ordered and oriented using a high-resolution high-density meiotic map. Detailed automatic and manual annotation provides evidence of more than 26,000 protein-coding genes6, the largest gene set of any vertebrate so far sequenced. Comparison to the human reference genome shows that approximately 70% of human genes have at least one obvious zebrafish orthologue. In addition, the high quality of this genome assembly provides a clearer understanding of key genomic features such as a unique repeat content, a scarcity of pseudogenes, an enrichment of zebrafish-specific genes on chromosome 4 and chromosomal regions that influence sex determination.
doi:10.1038/nature12111
PMCID: PMC3703927  PMID: 23594743
3.  The Life History of 21 Breast Cancers 
Cell  2012;149(5):994-1007.
SUMMARY
Cancer evolves dynamically as clonal expansions supersede one another driven by shifting selective pressures, mutational processes, and disrupted cancer genes. These processes mark the genome, such that a cancer’s life history is encrypted in the somatic mutations present. We developed algorithms to decipher this narrative and applied them to 21 breast cancers. Mutational processes evolve across a cancer’s lifespan, with many emerging late but contributing extensive genetic variation. Subclonal diversification is prominent, and most mutations are found in just a fraction of tumor cells. Every tumor has a dominant subclonal lineage, representing more than 50% of tumor cells. Minimal expansion of these subclones occurs until many hundreds to thousands of mutations have accumulated, implying the existence of long-lived, quiescent cell lineages capable of substantial proliferation upon acquisition of enabling genomic changes. Expansion of the dominant subclone to an appreciable mass may therefore represent the final rate-limiting step in a breast cancer’s development, triggering diagnosis.
doi:10.1016/j.cell.2012.04.023
PMCID: PMC3428864  PMID: 22608083
4.  Mutational Processes Molding the Genomes of 21 Breast Cancers 
Cell  2012;149(5-10):979-993.
Summary
All cancers carry somatic mutations. The patterns of mutation in cancer genomes reflect the DNA damage and repair processes to which cancer cells and their precursors have been exposed. To explore these mechanisms further, we generated catalogs of somatic mutation from 21 breast cancers and applied mathematical methods to extract mutational signatures of the underlying processes. Multiple distinct single- and double-nucleotide substitution signatures were discernible. Cancers with BRCA1 or BRCA2 mutations exhibited a characteristic combination of substitution mutation signatures and a distinctive profile of deletions. Complex relationships between somatic mutation prevalence and transcription were detected. A remarkable phenomenon of localized hypermutation, termed “kataegis,” was observed. Regions of kataegis differed between cancers but usually colocalized with somatic rearrangements. Base substitutions in these regions were almost exclusively of cytosine at TpC dinucleotides. The mechanisms underlying most of these mutational signatures are unknown. However, a role for the APOBEC family of cytidine deaminases is proposed.
PaperClip
Graphical Abstract
Highlights
► The genomes of 21 breast cancers sequenced ► Multiple somatic mutational processes extracted from mutation catalogs ► Mutational processes of BRCA1/BRCA2 breast cancers are distinctive ► Localized regions of hypermutation, “kataegis,” are frequent in breast cancers
Analyses of breast cancer genomes define distinct mutational signatures that imply the existence of multiple distinct somatic mutational processes throughout the genome and reveal a remarkable phenomenon of localized hypermutation. These highly mutated regions vary in size and chromosomal location and are surprisingly frequent in cancer genomes, often colocalizing with somatic rearrangements.
doi:10.1016/j.cell.2012.04.024
PMCID: PMC3414841  PMID: 22608084
5.  The Life History of 21 Breast Cancers 
Cell  2012;149(5):994-1007.
Summary
Cancer evolves dynamically as clonal expansions supersede one another driven by shifting selective pressures, mutational processes, and disrupted cancer genes. These processes mark the genome, such that a cancer's life history is encrypted in the somatic mutations present. We developed algorithms to decipher this narrative and applied them to 21 breast cancers. Mutational processes evolve across a cancer's lifespan, with many emerging late but contributing extensive genetic variation. Subclonal diversification is prominent, and most mutations are found in just a fraction of tumor cells. Every tumor has a dominant subclonal lineage, representing more than 50% of tumor cells. Minimal expansion of these subclones occurs until many hundreds to thousands of mutations have accumulated, implying the existence of long-lived, quiescent cell lineages capable of substantial proliferation upon acquisition of enabling genomic changes. Expansion of the dominant subclone to an appreciable mass may therefore represent the final rate-limiting step in a breast cancer's development, triggering diagnosis.
PaperClip
Graphical Abstract
Highlights
► Genome-wide analyses of mutations emerging through time in 21 breast cancers ► Minimal expansion of subclones occurs until thousands of mutations have accumulated ► Cancer-specific signatures of point mutations and genomic instability emerge late ► ERBB2 amplification begins early but continues to evolve over long molecular time
Newly developed algorithms allow the reconstruction of the genomic history of different breast cancers, tracing the temporal evolution of each tumor and the emergence of the dominant subclones that will eventually trigger diagnosis.
doi:10.1016/j.cell.2012.04.023
PMCID: PMC3428864  PMID: 22608083
7.  Data mining using the Catalogue of Somatic Mutations in Cancer BioMart 
Catalogue of Somatic Mutations in Cancer (COSMIC) (http://www.sanger.ac.uk/cosmic) is a publicly available resource providing information on somatic mutations implicated in human cancer. Release v51 (January 2011) includes data from just over 19 000 genes, 161 787 coding mutations and 5573 gene fusions, described in more than 577 000 tumour samples. COSMICMart (COSMIC BioMart) provides a flexible way to mine these data and combine somatic mutations with other biological relevant data sets. This article describes the data available in COSMIC along with examples of how to successfully mine and integrate data sets using COSMICMart.
Database URL: http://www.sanger.ac.uk/genetics/CGP/cosmic/biomart/martview/
doi:10.1093/database/bar018
PMCID: PMC3263736  PMID: 21609966
8.  COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer 
Nucleic Acids Research  2010;39(Database issue):D945-D950.
COSMIC (http://www.sanger.ac.uk/cosmic) curates comprehensive information on somatic mutations in human cancer. Release v48 (July 2010) describes over 136 000 coding mutations in almost 542 000 tumour samples; of the 18 490 genes documented, 4803 (26%) have one or more mutations. Full scientific literature curations are available on 83 major cancer genes and 49 fusion gene pairs (19 new cancer genes and 30 new fusion pairs this year) and this number is continually increasing. Key amongst these is TP53, now available through a collaboration with the IARC p53 database. In addition to data from the Cancer Genome Project (CGP) at the Sanger Institute, UK, and The Cancer Genome Atlas project (TCGA), large systematic screens are also now curated. Major website upgrades now make these data much more mineable, with many new selection filters and graphics. A Biomart is now available allowing more automated data mining and integration with other biological databases. Annotation of genomic features has become a significant focus; COSMIC has begun curating full-genome resequencing experiments, developing new web pages, export formats and graphics styles. With all genomic information recently updated to GRCh37, COSMIC integrates many diverse types of mutation information and is making much closer links with Ensembl and other data resources.
doi:10.1093/nar/gkq929
PMCID: PMC3013785  PMID: 20952405

Results 1-8 (8)