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1. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses.

Author

Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, Stein TI, Nudel R, Lieder I, Mazor Y, Kaplan S, Dahary D, Warshawsky D, Guan-Golan Y, Kohn A, Rappaport N, Safran M, and Lancet D

Subjects
High-Throughput Nucleotide Sequencing, Humans, Phenotype, Proteome, Software standards, Data Mining methods, Databases, Genetic, Genomics methods, Sequence Analysis methods
Abstract

GeneCards, the human gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human genes, diseases, variants, proteins, cells, and biological pathways. Our recently launched Version 4 has a revamped infrastructure facilitating faster data updates, better-targeted data queries, and friendlier user experience. It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Improved data unification includes gene-disease links via MalaCards and merged biological pathways via PathCards, as well as drug information and proteome expression. VarElect, another suite member, is a phenotype prioritizer for next-generation sequencing, leveraging the GeneCards and MalaCards knowledgebase. It automatically infers direct and indirect scored associations between hundreds or even thousands of variant-containing genes and disease phenotype terms. VarElect's capabilities, either independently or within TGex, our comprehensive variant analysis pipeline, help prepare for the challenge of clinical projects that involve thousands of exome/genome NGS analyses. © 2016 by John Wiley & Sons, Inc., (Copyright © 2016 John Wiley & Sons, Inc.)

Published
2016
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2. Reduced genomic potential for secreted plant cell-wall-degrading enzymes in the ectomycorrhizal fungus Amanita bisporigera, based on the secretome of Trichoderma reesei

Author

Subashini Nagendran, Nighat Aslam, Janet M. Paper, Jonathan D. Walton, and Heather E. Hallen-Adams

Subjects
Proteome, Amanita, Genomics, Cellulase, Biology, biology.organism_classification, Zea mays, Microbiology, Culture Media, Amanita bisporigera, Fungal Proteins, Coprinopsis cinerea, Biochemistry, Cell Wall, Tandem Mass Spectrometry, Hypocrea, Laccaria bicolor, Genetics, biology.protein, Glycoside hydrolase, Trichoderma reesei, Galerina marginata
Abstract

Based on the analysis of its genome sequence, the ectomycorrhizal (ECM) basidiomycetous fungus Laccaria bicolor was shown to be lacking many of the major classes of secreted enzymes that depolymerize plant cell wall polysaccharides. To test whether this is also a feature of other ECM fungi, we searched a survey genome database of Amanita bisporigera with the proteins found in the secretome of Trichoderma reesei (syn. Hypocrea jecorina), a biochemically well-characterized industrial fungus. Additional proteins were also used as queries to compensate for major groups of cell-wall-degrading enzymes lacking in the secretome of T. reesei and to substantiate conclusions drawn from the T. reesei collection. By MS/MS-based “shotgun” proteomics, 80 proteins were identified in culture filtrates of T. reesei strain RUTC30 grown on corn cell walls and in a commercial “cellulase” preparation, Spezyme CP. The two T. reesei enzyme preparations were qualitatively and quantitatively similar, the most striking difference being the lack of at least five major peptidases from the commercial enzyme mixture. Based on our analysis of A. bisporigera, this ECM fungus is deficient in many major classes of cell-wall-degrading enzymes, including both glycosyl hydrolases and carbohydrate esterases. By comparison, the genomes of the saprophytic basidiomycetes Coprinopsis cinerea and Galerina marginata (using a genome survey sequence approximately equivalent in depth to that of A. bisporigera) have, like T. reesei, a much more complete complement of cell-wall-degrading enzymes.

Published
2009

3. Quantitative genetic parameters for growth and wood properties in Eucalyptus 'urograndis' hybrid using near-infrared phenotyping and genome-wide SNP-based relationships

Author

Orzenil B. Silva-Junior, Bruno Marco de Lima, Shawn D. Mansfield, Carla Garcia, Dario Grattapaglia, Eduardo P. Cappa, BRUNO MARCO DE LIMA, USP, EDUARDO P. CAPPA, INSTITUTO NACIONAL DE TECNOLOGI´A AGROPECUARIA (INTA), ARGENTINA, ORZENIL BONFIM DA SILVA JUNIOR, Cenargen, CARLA GARCIA, INTERNATIONAL PAPER DO BRASIL ROD, SHAWN D. MANSFIELD, UNIVERSITY OF BRITISH COLUMBIA, CANADA, and DARIO GRATTAPAGLIA, Cenargen.

Subjects
0106 biological sciences, 0301 basic medicine, Heredity, Plant Science, 01 natural sciences, Lignin, Trees, Spectrum Analysis Techniques, NEAR-INFRARED PEHNOTYPING, Data Management, education.field_of_study, Eucalyptus, Multidisciplinary, Spectroscopy, Near-Infrared, Organic Compounds, Plant Anatomy, Eukaryota, near-Infrared Spectroscopy, Phylogenetic Analysis, Genomics, Plants, Wood, Phylogenetics, Polimorfismo de un Solo Nucleótido, Chemistry, Phenotypes, Phenotype, Genetic gain, Physical Sciences, Medicine, Brazil, Genome, Plant, Research Article, Genetic Research, Computer and Information Sciences, Genética Cuantitativa, Genotype, Science, Population, Infrared Spectroscopy, Quantitative trait locus, Biology, Research and Analysis Methods, Polymorphism, Single Nucleotide, Quantitative Genetics, 03 medical and health sciences, Quantitative Trait, Heritable, MOLECULAR RELATIONSHIP, Species Specificity, Genetic variation, Genetics, Evolutionary Systematics, PEDIGREE RELATIONSHIP, education, Cellulose, Fenotipos, Hybrid, Taxonomy, Evolutionary Biology, Models, Genetic, Directional selection, Organic Chemistry, Organisms, Chemical Compounds, Biology and Life Sciences, Heritability, purl.org/becyt/ford/4.5 [https], Plant Breeding, 030104 developmental biology, Evolutionary biology, Single Nucleotide Polymorphism, Tree breeding, Hybridization, Genetic, purl.org/becyt/ford/4 [https], 010606 plant biology & botany
Abstract

A thorough understanding of the heritability, genetic correlations and additive and non-additive variance components of tree growth and wood properties is a requisite for effective tree breeding. This knowledge is essential to maximize genetic gain, that is, the amount of increase in trait performance achieved annually through directional selection. Understanding the genetic attributes of traits targeted by breeding is also important to sustain decade-long genetic progress, that is, the progress made by increasing the average genetic value of the offspring as compared to that of the parental generation. In this study, we report quantitative genetic parameters for fifteen growth, wood chemical and physical traits for the world-famous Eucalyptus urograndis hybrid (E. grandis × E. urophylla). These traits directly impact the optimal use of wood for cellulose pulp, paper, and energy production. A population of 1,000 trees sampled in a progeny trial was phenotyped directly or following the development and use of near-infrared spectroscopy calibration models. Trees were genotyped with 33,398 SNPs and 24,001 DArT-seq genome-wide markers and genomic realized relationship matrices (GRM) were used for parameter estimation with an individual-tree additive-dominant mixed model. Wood chemical properties and wood density showed stronger genetic control than growth, cellulose and fiber traits. Additive effects are the main drivers of genetic variation for all traits, but dominance plays an equally or more important role for growth, singularly in this hybrid. GRM´s with >10,000 markers provided stable relationships estimates and more accurate parameters than pedigrees by capturing the full genetic relationships among individuals and disentangling the non-additive from the additive genetic component. Low correlations between growth and wood properties indicate that simultaneous selection for wood traits can be applied with minor effects on genetic gain for growth. Conversely, moderate to strong correlations between wood density and chemical traits exist, likely due to their interdependency on cell wall structure such that responses to selection will be connected for these traits. Our results illustrate the advantage of using genomewide marker data to inform tree breeding in general and have important consequences for operational breeding of eucalypt urograndis hybrids. Fil: de Lima, Bruno Marco. Universidade de Sao Paulo; Brasil. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Silva Junior, Orzenil B.. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil. Universidade Católica de Brasília; Brasil Fil: Garcia, Carla. No especifíca; Fil: Mansfield, Shawn D.. University of British Columbia; Canadá Fil: Grattapaglia, Dario. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil. Universidade Católica de Brasília; Brasil

Published
2019

4. History of CRISPR-Cas from Encounter with a Mysterious Repeated Sequence to Genome Editing Technology

Author

Mart Krupovic, Patrick Forterre, Yoshizumi Ishino, Biologie Moléculaire du Gène chez les Extrêmophiles (BMGE), Institut Pasteur [Paris], Kyushu University [Fukuoka], Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), P.F. is supported by an ERC grant from the European Union's Seventh Framework Program (FP/2007-2013)/Project., This perspective paper stemmed from discussions during Y.I.'s stay in P.F.'s laboratory thanks to the generous support from the program of visiting researchers in Institut Pasteur and the two-country exchange program of the Japan Society for the Promotion of Science (JSPS)., We apologize to the researchers whose work was not cited due to space limitations., Institut Pasteur [Paris] (IP), and Kyushu University

Subjects
0301 basic medicine, MESH: Gene Editing, MESH: CRISPR-Cas Systems, [SDV]Life Sciences [q-bio], 030106 microbiology, Computational biology, Biology, MESH: Genome, Bacterial, Microbiology, Genome, 03 medical and health sciences, Genome editing, repeated sequence, Escherichia coli, CRISPR, genome editing, Humans, Clustered Regularly Interspaced Short Palindromic Repeats, casposon, Repeated sequence, Molecular Biology, Gene, Sequence (medicine), Comparative genomics, Gene Editing, [SDV.GEN]Life Sciences [q-bio]/Genetics, MESH: Humans, Bacteria, MESH: Escherichia coli, MESH: Genomics, Genomics, History, 20th Century, Archaea, MESH: Bacteria, MESH: Archaea, MESH: Clustered Regularly Interspaced Short Palindromic Repeats, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, MESH: History, 20th Century, Minireview, Mobile genetic elements, CRISPR-Cas Systems, Genome, Bacterial
Abstract

Clustered regularly interspaced short palindromic repeat (CRISPR)-Cas systems are well-known acquired immunity systems that are widespread in archaea and bacteria. The RNA-guided nucleases from CRISPR-Cas systems are currently regarded as the most reliable tools for genome editing and engineering. The first hint of their existence came in 1987, when an unusual repetitive DNA sequence, which subsequently was defined as a CRISPR, was discovered in the Escherichia coli genome during an analysis of genes involved in phosphate metabolism. Similar sequence patterns were then reported in a range of other bacteria as well as in halophilic archaea, suggesting an important role for such evolutionarily conserved clusters of repeated sequences. A critical step toward functional characterization of the CRISPR-Cas systems was the recognition of a link between CRISPRs and the associated Cas proteins, which were initially hypothesized to be involved in DNA repair in hyperthermophilic archaea. Comparative genomics, structural biology, and advanced biochemistry could then work hand in hand, not only culminating in the explosion of genome editing tools based on CRISPR-Cas9 and other class II CRISPR-Cas systems but also providing insights into the origin and evolution of this system from mobile genetic elements denoted casposons. To celebrate the 30th anniversary of the discovery of CRISPR, this minireview briefly discusses the fascinating history of CRISPR-Cas systems, from the original observation of an enigmatic sequence in E. coli to genome editing in humans.

Published
2018

5. An integrated encyclopedia of DNA elements in the human genome

Author

Robert Altshuler, Laura Elnitski, Michael Anaya, Alec Victorsen, Deborah Winter, Javier Herrero, Katherine Varley, Andrea Sboner, Oscar Junhong Luo, Marco Mariotti, Cristina Sisu, Mike Kay, Timothy Dreszer, Jane Loveland, Alexandra Bignell, Ewan Birney, Tim @timjph Hubbard, Kuljeet Sandhu, Eric Haugen, Chris Gunter, Alexej Abyzov, Lucas Ward, Georgi Marinov, Michael Pazin, Thomas Gingeras, Alexander Dobin, Kimberly Foss, Xianjun Dong, Benoit Miotto, Piotr Mieczkowski, Cedric Notredame, Andrew Berry, Shawn Gillespie, Axel Visel, Shawn Levy, Richard Sandstrom, Jose M Gonzalez, Melissa Fullwood, Timo Lassmann, Michael Tress, Julien Lagarde, Kevin Yip, Leslie Adams, Sylvain Foissac, Bronwen Aken, Piero Carninci, Suganthi Balasubramanian, Andrea Tanzer, Sarah Djebali, Michael Hoffman, Gloria Despacio-Reyes, Peter Park, Felix Kokocinski, Katherine Fisher-Aylor, Juan M Vaquerizas, Peggy Farnham, Patrick Collins, Amonida Zadissa, Pedro Ferreira, Philippe Batut, Michael Snyder, Electra Tapanari, Adam Frankish, Paul Flicek, AMARTYA SANYAL, Tyler Alioto, Giovanni Bussotti, Laurence Meyer, Jingyi Jessica Li, Matthew Blow, Tristan FRUM, Roger Alexander, Rory Johnson, Charles Steward, Meizhen Zheng, Margus Lukk, Ross Hardison, Claire Davidson, Gary Saunders, Alan Boyle, Luiz Penalva, Rajinder Kaul, Lazaro Centanin, Florencia Pauli Behn, Thomas Derrien, Nathan Sheffield, Toby Hunt, Eric Nguyen, Jeff Vierstra, Konrad Karczewski, Kimberly Bell, Yanbao Yu, Hagen U Tilgner, James Taylor, Balázs Bánfai, Catherine Snow, Benjamin Vernot, Stephan Kirchmaier, Michael Sammeth, Steven Wilder, Angelika Merkel, Joanna Mieczkowska, Guoliang Li, Wei Lin, Jennifer Harrow, Thomas Oliver Auer, Daniel Barrell, Eddie Park, Alvis Brazma, Hazuki Takahashi, Nathan Johnson, Daniel Sobral, Terry Furey, Alexandre Reymond, Jonathan Mudge, Anshul Kundaje, Jose Rodriguez, Akshay Bhinge, James Gilbert, Jakub Karczewski, Venkat Malladi, Troy Whitfield, Orion Buske, Ian Dunham, Jennifer Moran, Joachim Wittbrodt, Charles B. Epstein, Laurens Wilming, Jason Gertz, Joshua Akey, Joel Rozowsky, Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), National Human Genome Research Institute (NHGRI), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Antonarakis, Stylianos, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Altshuler, Robert Charles, Ernst, Jason, Kellis, Manolis, Kheradpour, Pouya, Ward, Lucas D., Eaton, Matthew Lucas, Hendrix, David A., Jungreis, Irwin, Lin, Michael F., Washietl, Stefan, Lists of participants and their affiliations appear at the end of the paper and in the 'Collaboration/Projet' field., The Consortium is funded by grants from the NHGRI as follows: production grants: U54HG004570 (B. E. Bernstein), U01HG004695 (E. Birney), U54HG004563 (G. E. Crawford), U54HG004557 (T. R. Gingeras), U54HG004555 (T. J. Hubbard), U41HG004568 (W. J. Kent), U54HG004576 (R. M. Myers), U54HG004558 (M. Snyder), U54HG004592 (J. A. Stamatoyannopoulos). Pilot grants: R01HG003143 (J. Dekker), RC2HG005591 and R01HG003700 (M. C. Giddings), R01HG004456-03 (Y. Ruan), U01HG004571 (S. A. Tenenbaum), U01HG004561 (Z. Weng), RC2HG005679 (K. P. White). This project was supported in part by American Recovery and Reinvestment Act (ARRA) funds from the NHGRI through grants U54HG004570, U54HG004563, U41HG004568, U54HG004592, R01HG003143, RC2HG005591, R01HG003541,U01HG004561,RC2HG005679andR01HG003988(L. Pennacchio). In addition, work from NHGRI Groups was supported by the Intramural Research Program of the NHGRI (L. Elnitski, ZIAHG200323, E. H. Margulies, ZIAHG200341). Research in the Pennachio laboratory was performed at Lawrence Berkeley National Laboratory and at the United States Department of Energy Joint Genome Institute, Department of Energy Contract DE-AC02-05CH11231, University of California., Dunham I, Kundaje A, Aldred SF, Collins PJ, Davis CA, Doyle F, Epstein CB, Frietze S, Harrow J, Kaul R, Khatun J, Lajoie BR, Landt SG, Lee BK, Pauli F, Rosenbloom KR, Sabo P, Safi A, Sanyal A, Shoresh N, Simon JM, Song L, Trinklein ND, Altshuler RC, Birney E, Brown JB, Cheng C, Djebali S, Dong X, Dunham I, Ernst J, Furey TS, Gerstein M, Giardine B, Greven M, Hardison RC, Harris RS, Herrero J, Hoffman MM, Iyer S, Kellis M, Khatun J, Kheradpour P, Kundaje A, Lassmann T, Li Q, Lin X, Marinov GK, Merkel A, Mortazavi A, Parker SC, Reddy TE, Rozowsky J, Schlesinger F, Thurman RE, Wang J, Ward LD, Whitfield TW, Wilder SP, Wu W, Xi HS, Yip KY, Zhuang J, Pazin MJ, Lowdon RF, Dillon LA, Adams LB, Kelly CJ, Zhang J, Wexler JR, Green ED, Good PJ, Feingold EA, Bernstein BE, Birney E, Crawford GE, Dekker J, Elnitski L, Farnham PJ, Gerstein M, Giddings MC, Gingeras TR, Green ED, Guigó R, Hardison RC, Hubbard TJ, Kellis M, Kent W, Lieb JD, Margulies EH, Myers RM, Snyder M, Stamatoyannopoulos JA, Tenenbaum SA, Weng Z, White KP, Wold B, Khatun J, Yu Y, Wrobel J, Risk BA, Gunawardena HP, Kuiper HC, Maier CW, Xie L, Chen X, Giddings MC, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Kheradpour P, Mikkelsen TS, Gillespie S, Goren A, Ram O, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Eaton ML, Kellis M, Djebali S, Davis CA, Merkel A, Dobin A, Lassmann T, Mortazavi A, Tanzer A, Lagarde J, Lin W, Schlesinger F, Xue C, Marinov GK, Khatun J, Williams BA, Zaleski C, Rozowsky J, Röder M, Kokocinski F, Abdelhamid RF, Alioto T, Antoshechkin I, Baer MT, Batut P, Bell I, Bell K, Chakrabortty S, Chen X, Chrast J, Curado J, Derrien T, Drenkow J, Dumais E, Dumais J, Duttagupta R, Fastuca M, Fejes-Toth K, Ferreira P, Foissac S, Fullwood MJ, Gao H, Gonzalez D, Gordon A, Gunawardena HP, Howald C, Jha S, Johnson R, Kapranov P, King B, Kingswood C, Li G, Luo OJ, Park E, Preall JB, Presaud K, Ribeca P, Risk BA, Robyr D, Ruan X, Sammeth M, Sandhu KS, Schaeffer L, See LH, Shahab A, Skancke J, Suzuki AM, Takahashi H, Tilgner H, Trout D, Walters N, Wang H, Wrobel J, Yu Y, Hayashizaki Y, Harrow J, Gerstein M, Hubbard TJ, Reymond A, Antonarakis SE, Hannon GJ, Giddings MC, Ruan Y, Wold B, Carninci P, Guigó R, Gingeras TR, Rosenbloom KR, Sloan CA, Learned K, Malladi VS, Wong MC, Barber GP, Cline MS, Dreszer TR, Heitner SG, Karolchik D, Kent W, Kirkup VM, Meyer LR, Long JC, Maddren M, Raney BJ, Furey TS, Song L, Grasfeder LL, Giresi PG, Lee BK, Battenhouse A, Sheffield NC, Simon JM, Showers KA, Safi A, London D, Bhinge AA, Shestak C, Schaner MR, Kim SK, Zhang ZZ, Mieczkowski PA, Mieczkowska JO, Liu Z, McDaniell RM, Ni Y, Rashid NU, Kim MJ, Adar S, Zhang Z, Wang T, Winter D, Keefe D, Birney E, Iyer VR, Lieb JD, Crawford GE, Li G, Sandhu KS, Zheng M, Wang P, Luo OJ, Shahab A, Fullwood MJ, Ruan X, Ruan Y, Myers RM, Pauli F, Williams BA, Gertz J, Marinov GK, Reddy TE, Vielmetter J, Partridge E, Trout D, Varley KE, Gasper C, Bansal A, Pepke S, Jain P, Amrhein H, Bowling KM, Anaya M, Cross MK, King B, Muratet MA, Antoshechkin I, Newberry KM, McCue K, Nesmith AS, Fisher-Aylor KI, Pusey B, DeSalvo G, Parker SL, Balasubramanian S, Davis NS, Meadows SK, Eggleston T, Gunter C, Newberry J, Levy SE, Absher DM, Mortazavi A, Wong WH, Wold B, Blow MJ, Visel A, Pennachio LA, Elnitski L, Margulies EH, Parker SC, Petrykowska HM, Abyzov A, Aken B, Barrell D, Barson G, Berry A, Bignell A, Boychenko V, Bussotti G, Chrast J, Davidson C, Derrien T, Despacio-Reyes G, Diekhans M, Ezkurdia I, Frankish A, Gilbert J, Gonzalez JM, Griffiths E, Harte R, Hendrix DA, Howald C, Hunt T, Jungreis I, Kay M, Khurana E, Kokocinski F, Leng J, Lin MF, Loveland J, Lu Z, Manthravadi D, Mariotti M, Mudge J, Mukherjee G, Notredame C, Pei B, Rodriguez JM, Saunders G, Sboner A, Searle S, Sisu C, Snow C, Steward C, Tanzer A, Tapanari E, Tress ML, van Baren MJ, Walters N, Washietl S, Wilming L, Zadissa A, Zhang Z, Brent M, Haussler D, Kellis M, Valencia A, Gerstein M, Reymond A, Guigó R, Harrow J, Hubbard TJ, Landt SG, Frietze S, Abyzov A, Addleman N, Alexander RP, Auerbach RK, Balasubramanian S, Bettinger K, Bhardwaj N, Boyle AP, Cao AR, Cayting P, Charos A, Cheng Y, Cheng C, Eastman C, Euskirchen G, Fleming JD, Grubert F, Habegger L, Hariharan M, Harmanci A, Iyengar S, Jin VX, Karczewski KJ, Kasowski M, Lacroute P, Lam H, Lamarre-Vincent N, Leng J, Lian J, Lindahl-Allen M, Min R, Miotto B, Monahan H, Moqtaderi Z, Mu XJ, O'Geen H, Ouyang Z, Patacsil D, Pei B, Raha D, Ramirez L, Reed B, Rozowsky J, Sboner A, Shi M, Sisu C, Slifer T, Witt H, Wu L, Xu X, Yan KK, Yang X, Yip KY, Zhang Z, Struhl K, Weissman SM, Gerstein M, Farnham PJ, Snyder M, Tenenbaum SA, Penalva LO, Doyle F, Karmakar S, Landt SG, Bhanvadia RR, Choudhury A, Domanus M, Ma L, Moran J, Patacsil D, Slifer T, Victorsen A, Yang X, Snyder M, Auer T, Centanin L, Eichenlaub M, Gruhl F, Heermann S, Hoeckendorf B, Inoue D, Kellner T, Kirchmaier S, Mueller C, Reinhardt R, Schertel L, Schneider S, Sinn R, Wittbrodt B, Wittbrodt J, Weng Z, Whitfield TW, Wang J, Collins PJ, Aldred SF, Trinklein ND, Partridge EC, Myers RM, Dekker J, Jain G, Lajoie BR, Sanyal A, Balasundaram G, Bates DL, Byron R, Canfield TK, Diegel MJ, Dunn D, Ebersol AK, Frum T, Garg K, Gist E, Hansen R, Boatman L, Haugen E, Humbert R, Jain G, Johnson AK, Johnson EM, Kutyavin TV, Lajoie BR, Lee K, Lotakis D, Maurano MT, Neph SJ, Neri FV, Nguyen ED, Qu H, Reynolds AP, Roach V, Rynes E, Sabo P, Sanchez ME, Sandstrom RS, Sanyal A, Shafer AO, Stergachis AB, Thomas S, Thurman RE, Vernot B, Vierstra J, Vong S, Wang H, Weaver MA, Yan Y, Zhang M, Akey JM, Bender M, Dorschner MO, Groudine M, MacCoss MJ, Navas P, Stamatoyannopoulos G, Kaul R, Dekker J, Stamatoyannopoulos JA, Dunham I, Beal K, Brazma A, Flicek P, Herrero J, Johnson N, Keefe D, Lukk M, Luscombe NM, Sobral D, Vaquerizas JM, Wilder SP, Batzoglou S, Sidow A, Hussami N, Kyriazopoulou-Panagiotopoulou S, Libbrecht MW, Schaub MA, Kundaje A, Hardison RC, Miller W, Giardine B, Harris RS, Wu W, Bickel PJ, Banfai B, Boley NP, Brown JB, Huang H, Li Q, Li JJ, Noble WS, Bilmes JA, Buske OJ, Hoffman MM, Sahu AD, Kharchenko PV, Park PJ, Baker D, Taylor J, Weng Z, Iyer S, Dong X, Greven M, Lin X, Wang J, Xi HS, Zhuang J, Gerstein M, Alexander RP, Balasubramanian S, Cheng C, Harmanci A, Lochovsky L, Min R, Mu XJ, Rozowsky J, Yan KK, Yip KY, Birney E., and Miotto, Benoit

Subjects
Encyclopedias as Topic, [SDV]Life Sciences [q-bio], DNA Footprinting, Genoma humà, Binding Sites/genetics, Histones/chemistry/metabolism, 0302 clinical medicine, Exons/genetics, ddc:576.5, 0303 health sciences, Multidisciplinary, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], DNA-Binding Proteins/metabolism, region, Chemistry, Genetic Predisposition to Disease/genetics, Genomics, Polymorphism, Single Nucleotide/genetics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Neoplasms/genetics, Chromatin, Cell biology, in vivo, Genetic Variation/genetics, 030220 oncology & carcinogenesis, Deoxyribonuclease I/metabolism, Proteins/genetics, transcription factor-binding, chromosome conformation capture, DNA Methylation/genetics, Chromosomes, Human/genetics/metabolism, Chromatin Immunoprecipitation, Mammals/genetics, DNA/genetics, determinant, Article, 03 medical and health sciences, map, Animals, Humans, Transcription Factors/metabolism, Alleles, mouse, 030304 developmental biology, Transcription, Genetic/genetics, Chromatin/genetics/metabolism, Sequence Analysis, RNA, human cell, Molecular Sequence Annotation, Regulatory Sequences, Nucleic Acid/genetics, Promoter Regions, Genetic/genetics, DNA binding site, Genòmica, Genome, Human/genetics, chromatin, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Genètica, Genome-Wide Association Study
Abstract

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research. The Consortium is funded by grants from the NHGRI as follows: production grants: U54HG004570 (B. E. Bernstein); U01HG004695 (E. Birney); U54HG004563 (G. E. Crawford); U54HG004557 (T. R. Gingeras); U54HG004555 (T. J. Hubbard); U41HG004568 /n(W. J. Kent); U54HG004576 (R. M. Myers); U54HG004558 (M. Snyder);/nU54HG004592 (J. A. Stamatoyannopoulos). Pilot grants: R01HG003143 (J. Dekker); RC2HG005591 and R01HG003700 (M. C. Giddings); R01HG004456-03 (Y. Ruan); U01HG004571 (S. A. Tenenbaum); U01HG004561 (Z. Weng); RC2HG005679 (K. P. White). This project was supported in part by American Recovery and/nReinvestment Act (ARRA) funds from the NHGRI through grants U54HG004570, U54HG004563, U41HG004568, U54HG004592, R01HG003143, RC2HG005591,R01HG003541, U01HG004561, RC2HG005679andR01HG003988(L. Pennacchio). In addition, work from NHGRI Groups was supported by the Intramural Research/nProgram of the NHGRI (L. Elnitski, ZIAHG200323; E. H. Margulies, ZIAHG200341). Research in the Pennachio laboratory was performed at Lawrence Berkeley National Laboratory and at the United States Department of Energy Joint Genome Institute, Department of Energy Contract DE-AC02-05CH11231, University of California.

Published
2012

6. BMC Genomics

Author

Grace C. Davey, Penelope K. Lindeque, Richard Reinhardt, Christophe Klopp, Pascal Favrel, Dario Moraga, Pierre Boudry, Sylvie Lapegue, Patrick Prunet, Arnaud Huvet, Julien de Lorgeril, Jeanne Moal, Viviane Boulo, Elodie Fleury, Christophe Lelong, Christopher Sauvage, Patrick Wincker, François Moreews, Michel Mathieu, Frédérick Gavory, Arnaud Tanguy, Caroline Fabioux, Charlotte Corporeau, Evelyne Bachère, Jenny P. Shaw, Yannick Gueguen, Laboratoire Environnement Ressources Morbihan Pays de Loire (LERMPL), LITTORAL (LITTORAL), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Physiologie et Ecophysiologie des Mollusques Marins (PE2M), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Ecosystèmes lagunaires : organisation biologique et fonctionnement (ECOLAG), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Centre National de la Recherche Scientifique (CNRS), Adaptation et diversité en milieu marin (ADMM), Institut national des sciences de l'Univers (INSU - CNRS)-Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Brest (UBO), Plymouth Marine Laboratory (PML), Max-Planck-Institut für Molekulare Genetik (MPIMG), Max-Planck-Gesellschaft, Station commune de Recherches en Ichtyophysiologie, Biodiversité et Environnement (SCRIBE), Institut National de la Recherche Agronomique (INRA), Génétique fonctionnelle, agronomie et santé [IFR 140] (GFAS), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), National Diagnostics Centre (NDC), National University of Ireland [Galway] (NUI Galway), Laboratoire de Génétique et Pathologie (LGP), Amélioration génétique, du contrôle des performances et de la santé des mollusques marins (AGSAE), Genoscope - Centre national de séquençage [Evry] (GENOSCOPE), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Biological systems and models, bioinformatics and sequences (SYMBIOSE), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Systèmes d'Elevage, Nutrition Animale et Humaine (SENAH), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Rennes, Système d'Information des GENomes des Animaux d'Elevage (SIGENAE), Unité de Biométrie et Intelligence Artificielle (ancêtre de MIAT) (UBIA), Laboratoire de Physiologie des Invertébrés (LPI), Physiologie Fonctionnelle des Organismes Marins (PFOM), The research presented in this paper was performed within the framework of several research projects funded by: Genoscope (11/AP2006-2007), Marine Genomics Network of Excellence (GOCE-CT-2004-505403), the European project 'Aquafirst' (513692) in the Sixth Framework Program, ANR 'CgPhysiogène' (ANR-06-GANI-0009) and 'Gametogenes' (ANR-08-GENM-041), ANR-06-GANI-0009,CgPhysiogene,Bases moléculaires des fonctions physiologiques de l'huître Crassostrea gigas : interactions hôte/pathogène/milieu(2006), ANR-08-GENM-0041,Gametogenes,Génomiques de la gamétogénèse chez l'huître creuse Crassostrea gigas(2008), Laboratoire Laboratoire Environnement Ressources Morbihan Pays de Loire (LER/MPL), Institut de Recherche pour le Développement (IRD)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Centre National de la Recherche Scientifique (CNRS), Adaptation et Biologie des Invertébrés en Conditions Extrêmes (ABICE), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Plymouth Marine Laboratory, Institut National de la Recherche Agronomique (INRA)-IFR140, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Ecole Nationale Supérieure Agronomique de Rennes-Institut National de la Recherche Agronomique (INRA), Unité de Biométrie et Intelligence Artificielle de Toulouse [Castanet-Tolosan] (UBIA), Institut National de la Recherche Agronomique (INRA)-Plateforme bioinformatique du GIS GENOTOUL - Génopole Toulouse Midi-Pyrénées, Laboratoire de Physiologie des Invertébrés [Plouzané] (LPI), Adaptation et diversité en milieu marin (AD2M), Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Recherche Agronomique (INRA), Station biologique de Roscoff (SBR), and Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Oyster, genome annotation, génomique fonctionnelle, computer.software_genre, Genome, User-Computer Interface, single nucleotide polymorphisms, Databases, Genetic, crassostrea gigas, structure du génome, Expressed Sequence Tags, base de données, 0303 health sciences, Expressed sequence tag, biology, Database, 04 agricultural and veterinary sciences, Genomics, crustacea, Pacific oyster, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], energy-balance, factor-beta superfamily, DNA microarray, expression des gènes, Biotechnology, lcsh:QH426-470, Sequence analysis, lcsh:Biotechnology, kappa-b, Polymorphism, Single Nucleotide, génomique, 03 medical and health sciences, biology.animal, lcsh:TP248.13-248.65, Genetics, summer mortality, Animals, Crassostrea, 030304 developmental biology, Gene Library, Whole genome sequencing, [SDV.GEN]Life Sciences [q-bio]/Genetics, huître, cell-development, génome, Gene Expression Profiling, linkage maps, Sequence Analysis, DNA, biology.organism_classification, lcsh:Genetics, coquillage, 040102 fisheries, 0401 agriculture, forestry, and fisheries, identification, marine genomics, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], computer, Microsatellite Repeats
Abstract

Background Although bivalves are among the most-studied marine organisms because of their ecological role and economic importance, very little information is available on the genome sequences of oyster species. This report documents three large-scale cDNA sequencing projects for the Pacific oyster Crassostrea gigas initiated to provide a large number of expressed sequence tags that were subsequently compiled in a publicly accessible database. This resource allowed for the identification of a large number of transcripts and provides valuable information for ongoing investigations of tissue-specific and stimulus-dependant gene expression patterns. These data are crucial for constructing comprehensive DNA microarrays, identifying single nucleotide polymorphisms and microsatellites in coding regions, and for identifying genes when the entire genome sequence of C. gigas becomes available. Description In the present paper, we report the production of 40,845 high-quality ESTs that identify 29,745 unique transcribed sequences consisting of 7,940 contigs and 21,805 singletons. All of these new sequences, together with existing public sequence data, have been compiled into a publicly-available Website http://public-contigbrowser.sigenae.org:9090/Crassostrea_gigas/index.html. Approximately 43% of the unique ESTs had significant matches against the SwissProt database and 27% were annotated using Gene Ontology terms. In addition, we identified a total of 208 in silico microsatellites from the ESTs, with 173 having sufficient flanking sequence for primer design. We also identified a total of 7,530 putative in silico, single-nucleotide polymorphisms using existing and newly-generated EST resources for the Pacific oyster. Conclusion A publicly-available database has been populated with 29,745 unique sequences for the Pacific oyster Crassostrea gigas. The database provides many tools to search cleaned and assembled ESTs. The user may input and submit several filters, such as protein or nucleotide hits, to select and download relevant elements. This database constitutes one of the most developed genomic resources accessible among Lophotrochozoans, an orphan clade of bilateral animals. These data will accelerate the development of both genomics and genetics in a commercially-important species with the highest annual, commercial production of any aquatic organism.

Published
2009