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Chenghai Xue

Bio: Chenghai Xue is an academic researcher from Cold Spring Harbor Laboratory. The author has contributed to research in topics: Comparative genomics & Genome. The author has an hindex of 4, co-authored 4 publications receiving 7311 citations.

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Journal ArticleDOI
Sarah Djebali, Carrie A. Davis1, Angelika Merkel, Alexander Dobin1, Timo Lassmann, Ali Mortazavi2, Ali Mortazavi3, Andrea Tanzer, Julien Lagarde, Wei Lin1, Felix Schlesinger1, Chenghai Xue1, Georgi K. Marinov3, Jainab Khatun4, Brian A. Williams3, Chris Zaleski1, Joel Rozowsky5, Marion S. Röder, Felix Kokocinski6, Rehab F. Abdelhamid, Tyler Alioto, Igor Antoshechkin3, Michael T. Baer1, Nadav Bar7, Philippe Batut1, Kimberly Bell1, Ian Bell8, Sudipto K. Chakrabortty1, Xian Chen9, Jacqueline Chrast10, Joao Curado, Thomas Derrien, Jorg Drenkow1, Erica Dumais8, Jacqueline Dumais8, Radha Duttagupta8, Emilie Falconnet11, Meagan Fastuca1, Kata Fejes-Toth1, Pedro G. Ferreira, Sylvain Foissac8, Melissa J. Fullwood12, Hui Gao8, David Gonzalez, Assaf Gordon1, Harsha P. Gunawardena9, Cédric Howald10, Sonali Jha1, Rory Johnson, Philipp Kapranov8, Brandon King3, Colin Kingswood, Oscar Junhong Luo12, Eddie Park2, Kimberly Persaud1, Jonathan B. Preall1, Paolo Ribeca, Brian A. Risk4, Daniel Robyr11, Michael Sammeth, Lorian Schaffer3, Lei-Hoon See1, Atif Shahab12, Jørgen Skancke7, Ana Maria Suzuki, Hazuki Takahashi, Hagen Tilgner13, Diane Trout3, Nathalie Walters10, Huaien Wang1, John A. Wrobel4, Yanbao Yu9, Xiaoan Ruan12, Yoshihide Hayashizaki, Jennifer Harrow6, Mark Gerstein5, Tim Hubbard6, Alexandre Reymond10, Stylianos E. Antonarakis11, Gregory J. Hannon1, Morgan C. Giddings9, Morgan C. Giddings4, Yijun Ruan12, Barbara J. Wold3, Piero Carninci, Roderic Guigó14, Thomas R. Gingeras8, Thomas R. Gingeras1 
06 Sep 2012-Nature
TL;DR: Evidence that three-quarters of the human genome is capable of being transcribed is reported, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs that prompt a redefinition of the concept of a gene.
Abstract: Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.

4,450 citations

01 Sep 2012
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.

2,767 citations

Journal ArticleDOI
John A. Stamatoyannopoulos1, Michael Snyder2, Ross C. Hardison3, Bing Ren4, Thomas R. Gingeras5, David M. Gilbert6, Mark Groudine7, M. A. Bender7, Rajinder Kaul1, Theresa K. Canfield1, Erica Giste1, Audra K. Johnson1, Mia Zhang7, Gayathri Balasundaram7, Rachel Byron7, Vaughan Roach1, Peter J. Sabo1, Richard Sandstrom1, A Sandra Stehling1, Robert E. Thurman1, Sherman M. Weissman8, Philip Cayting8, Manoj Hariharan2, Jin Lian8, Yong Cheng2, Stephen G. Landt2, Zhihai Ma2, Barbara J. Wold9, Job Dekker10, Gregory E. Crawford11, Cheryl A. Keller3, Weisheng Wu3, Christopher T. Morrissey3, Swathi Ashok Kumar3, Tejaswini Mishra3, Deepti Jain3, Marta Byrska-Bishop3, Daniel Blankenberg3, Bryan R. Lajoie2, Gaurav Jain10, Amartya Sanyal10, Kaun-Bei Chen11, Olgert Denas11, James Taylor12, Gerd A. Blobel13, Mitchell J. Weiss13, Max Pimkin13, Wulan Deng13, Georgi K. Marinov9, Brian A. Williams9, Katherine I. Fisher-Aylor9, Gilberto DeSalvo9, Anthony Kiralusha9, Diane Trout9, Henry Amrhein9, Ali Mortazavi14, Lee Edsall4, David McCleary4, Samantha Kuan4, Yin Shen4, Feng Yue4, Zhen Ye4, Carrie A. Davis5, Chris Zaleski5, Sonali Jha5, Chenghai Xue5, Alexander Dobin5, Wei Lin5, Meagan Fastuca5, Huaien Wang5, Roderic Guigó, Sarah Djebali, Julien Lagarde, Tyrone Ryba6, Takayo Sasaki6, Venkat S. Malladi15, Melissa S. Cline15, Vanessa M. Kirkup15, Katrina Learned15, Kate R. Rosenbloom15, W. James Kent15, Elise A. Feingold16, Peter J. Good16, Michael J. Pazin16, Rebecca F. Lowdon16, Leslie B Adams16 
TL;DR: The Mouse E NCODE Consortium is applying the same experimental pipelines developed for human ENCODE to annotate the mouse genome to enable a broad range of mouse genomics efforts.
Abstract: To complement the human Encyclopedia of DNA Elements (ENCODE) project and to enable a broad range of mouse genomics efforts, the Mouse ENCODE Consortium is applying the same experimental pipelines developed for human ENCODE to annotate the mouse genome

445 citations

Journal ArticleDOI
Mark Gerstein1, Joel Rozowsky1, Koon-Kiu Yan1, Daifeng Wang1, Chao Cheng2, James B. Brown3, James B. Brown4, Carrie A. Davis5, LaDeana W. Hillier6, Cristina Sisu1, Jingyi Jessica Li7, Jingyi Jessica Li3, Baikang Pei1, Arif Harmanci1, Michael O. Duff8, Sarah Djebali9, Roger P. Alexander1, Burak H. Alver10, Raymond K. Auerbach1, Kimberly Bell5, Peter J. Bickel3, Max E. Boeck6, Nathan Boley3, Nathan Boley4, Benjamin W. Booth4, Lucy Cherbas11, Peter Cherbas11, Chao Di12, Alexander Dobin5, Jorg Drenkow5, Brent Ewing6, Gang Fang1, Megan Fastuca5, Elise A. Feingold13, Adam Frankish14, Guanjun Gao12, Peter J. Good13, Roderic Guigó9, Ann S. Hammonds4, Jen Harrow14, Roger A. Hoskins4, Cédric Howald15, Cédric Howald16, Long Hu12, Haiyan Huang3, Tim Hubbard14, Tim Hubbard17, Chau Huynh6, Sonali Jha5, Dionna M. Kasper1, Masaomi Kato1, Thomas C. Kaufman11, Robert R. Kitchen1, Erik Ladewig18, Julien Lagarde9, Eric C. Lai18, Jing Leng1, Zhi Lu12, Michael J. MacCoss6, Gemma E. May8, Gemma E. May19, Rebecca McWhirter20, Gennifer E. Merrihew6, David M. Miller20, Ali Mortazavi21, Rabi Murad21, Brian Oliver13, Sara Olson8, Peter J. Park10, Michael J. Pazin13, Norbert Perrimon10, Norbert Perrimon22, Dmitri D. Pervouchine9, Valerie Reinke1, Alexandre Reymond15, Garrett Robinson3, Anastasia Samsonova22, Anastasia Samsonova10, Gary Saunders23, Gary Saunders14, Felix Schlesinger5, Anurag Sethi1, Frank J. Slack1, William C. Spencer20, Marcus H. Stoiber4, Marcus H. Stoiber3, Pnina Strasbourger6, Andrea Tanzer9, Andrea Tanzer24, Owen Thompson6, Kenneth H. Wan4, Guilin Wang1, Huaien Wang5, Kathie L. Watkins20, Jiayu Wen18, Kejia Wen12, Chenghai Xue5, Li Yang8, Li Yang25, Kevin Y. Yip26, Chris Zaleski5, Yan Zhang1, Henry Zheng1, Steven E. Brenner3, Brenton R. Graveley8, Susan E. Celniker4, Thomas R. Gingeras5, Robert H. Waterston6 
28 Aug 2014-Nature
TL;DR: It is found in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a ‘universal model’ based on a single set of organism-independent parameters.
Abstract: The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a 'universal model' based on a single set of organism-independent parameters.

284 citations


Cited by
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Journal ArticleDOI
TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
Abstract: Motivation Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

30,684 citations

Journal ArticleDOI
06 Sep 2012-Nature
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.
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.

13,548 citations

Journal ArticleDOI
23 Jan 2015-Science
TL;DR: In this paper, a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level.
Abstract: Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

9,745 citations

Journal Article
01 Jan 2012-Nature
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.
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.

8,106 citations

Journal ArticleDOI
TL;DR: The Gene Expression Omnibus is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community and supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable.
Abstract: The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.

6,683 citations