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1.  Piwi and piRNAs Act Upstream of an Endogenous siRNA Pathway to suppress Tc3 Transposon Mobility in the Caenorhabditis elegans germline 
Molecular cell  2008;31(1):79-90.
The Piwi proteins of the Argonaute superfamily are required for normal germline development in Drosophila, zebrafish and mice, and associate with 24-30 nucleotide RNAs termed piRNAs. We identify a class of 21 nucleotide RNAs, previously named 21U-RNAs, as the piRNAs of C. elegans. Piwi and piRNA expression is restricted to the male and female germline and independent of many proteins in other small RNA pathways, including DCR-1. We show that Piwi is specifically required to silence Tc3, but not other Tc/mariner DNA transposons. Tc3 excision rates in the germline are increased at least 100 fold in piwi mutants as compared to wild type. We find no evidence for a Ping-Pong model for piRNA amplification in C. elegans. Instead, we demonstrate that Piwi acts upstream of an endogenous siRNA pathway in Tc3 silencing. These data might suggest a link between piRNA and siRNA function.
doi:10.1016/j.molcel.2008.06.003
PMCID: PMC3353317  PMID: 18571451
2.  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
3.  A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis 
Nature biotechnology  2008;26(7):779-785.
DNA methylation is an indispensible epigenetic modification of mammalian genomes. Consequently there is great interest in strategies for genome-wide/whole-genome DNA methylation analysis, and immunoprecipitation-based methods have proven to be a powerful option. Such methods are rapidly shifting the bottleneck from data generation to data analysis, necessitating the development of better analytical tools. Until now, a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling has been the inability to estimate absolute methylation levels. Here we report the development of a novel cross-platform algorithm – Bayesian Tool for Methylation Analysis (Batman) – for analyzing Methylated DNA Immunoprecipitation (MeDIP) profiles generated using arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). The latter is an approach we have developed to elucidate the first high-resolution whole-genome DNA methylation profile (DNA methylome) of any mammalian genome. MeDIP-seq/MeDIP-chip combined with Batman represent robust, quantitative, and cost-effective functional genomic strategies for elucidating the function of DNA methylation.
doi:10.1038/nbt1414
PMCID: PMC2644410  PMID: 18612301
4.  The Pfam Protein Families Database 
Nucleic Acids Research  2002;30(1):276-280.
Pfam is a large collection of protein multiple sequence alignments and profile hidden Markov models. Pfam is available on the World Wide Web in the UK at http://www.sanger.ac.uk/Software/Pfam/, in Sweden at http://www.cgb.ki.se/Pfam/, in France at http://pfam.jouy.inra.fr/ and in the US at http://pfam.wustl.edu/. The latest version (6.6) of Pfam contains 3071 families, which match 69% of proteins in SWISS-PROT 39 and TrEMBL 14. Structural data, where available, have been utilised to ensure that Pfam families correspond with structural domains, and to improve domain-based annotation. Predictions of non-domain regions are now also included. In addition to secondary structure, Pfam multiple sequence alignments now contain active site residue mark-up. New search tools, including taxonomy search and domain query, greatly add to the functionality and usability of the Pfam resource.
PMCID: PMC99071  PMID: 11752314
5.  The Pfam Protein Families Database 
Nucleic Acids Research  2000;28(1):263-266.
Pfam is a large collection of protein multiple sequence alignments and profile hidden Markov models. Pfam is available on the WWW in the UK at http://www.sanger.ac.uk/Software/Pfam/ , in Sweden at http://www.cgr.ki.se/Pfam/ and in the US at http://pfam.wustl.edu/ . The latest version (4.3) of Pfam contains 1815 families. These Pfam families match 63% of proteins in SWISS-PROT 37 and TrEMBL 9. For complete genomes Pfam currently matches up to half of the proteins. Genomic DNA can be directly searched against the Pfam library using the Wise2 package.
PMCID: PMC102420  PMID: 10592242
6.  DNA Methylation Profiling of the Human Major Histocompatibility Complex: A Pilot Study for the Human Epigenome Project 
PLoS Biology  2004;2(12):e405.
The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine–guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data.
DNA is frequently modified by methylation, which can affect its function. The Human Epigenome Project aims to identify, catalog, and interpret DNA methylation throughout the genome
doi:10.1371/journal.pbio.0020405
PMCID: PMC529316  PMID: 15550986
7.  Structural analysis of the genome of breast cancer cell line ZR-75-30 identifies twelve expressed fusion genes 
BMC Genomics  2012;13:719.
Background
It has recently emerged that common epithelial cancers such as breast cancers have fusion genes like those in leukaemias. In a representative breast cancer cell line, ZR-75-30, we searched for fusion genes, by analysing genome rearrangements.
Results
We first analysed rearrangements of the ZR-75-30 genome, to around 10kb resolution, by molecular cytogenetic approaches, combining array painting and array CGH. We then compared this map with genomic junctions determined by paired-end sequencing. Most of the breakpoints found by array painting and array CGH were identified in the paired end sequencing—55% of the unamplified breakpoints and 97% of the amplified breakpoints (as these are represented by more sequence reads). From this analysis we identified 9 expressed fusion genes: APPBP2-PHF20L1, BCAS3-HOXB9, COL14A1-SKAP1, TAOK1-PCGF2, TIAM1-NRIP1, TIMM23-ARHGAP32, TRPS1-LASP1, USP32-CCDC49 and ZMYM4-OPRD1. We also determined the genomic junctions of a further three expressed fusion genes that had been described by others, BCAS3-ERBB2, DDX5-DEPDC6/DEPTOR and PLEC1-ENPP2. Of this total of 12 expressed fusion genes, 9 were in the coamplification. Due to the sensitivity of the technologies used, we estimate these 12 fusion genes to be around two-thirds of the true total. Many of the fusions seem likely to be driver mutations. For example, PHF20L1, BCAS3, TAOK1, PCGF2, and TRPS1 are fused in other breast cancers. HOXB9 and PHF20L1 are members of gene families that are fused in other neoplasms. Several of the other genes are relevant to cancer—in addition to ERBB2, SKAP1 is an adaptor for Src, DEPTOR regulates the mTOR pathway and NRIP1 is an estrogen-receptor coregulator.
Conclusions
This is the first structural analysis of a breast cancer genome that combines classical molecular cytogenetic approaches with sequencing. Paired-end sequencing was able to detect almost all breakpoints, where there was adequate read depth. It supports the view that gene breakage and gene fusion are important classes of mutation in breast cancer, with a typical breast cancer expressing many fusion genes.
doi:10.1186/1471-2164-13-719
PMCID: PMC3548764  PMID: 23260012
Breast cancer; Chromosome aberrations; Genomics; Fusion genes

Results 1-7 (7)