Author
Sylvain Foissac
Other affiliations: Pompeu Fabra University, Affymetrix, Institut national de la recherche agronomique
Bio: Sylvain Foissac is an academic researcher from University of Toulouse. The author has contributed to research in topics: Genome & Gene. The author has an hindex of 20, co-authored 32 publications receiving 14347 citations. Previous affiliations of Sylvain Foissac include Pompeu Fabra University & Affymetrix.
Topics: Genome, Gene, Human genome, Gene expression profiling, Genomics
Papers
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Ewan Birney, John A. Stamatoyannopoulos1, Anindya Dutta2, Roderic Guigó3 +317 more•Institutions (44)
TL;DR: Functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project are reported, providing convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts.
Abstract: We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
5,091 citations
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Cold Spring Harbor Laboratory1, California Institute of Technology2, University of California, Irvine3, Florida State University College of Arts and Sciences4, Yale University5, Wellcome Trust Sanger Institute6, Norwegian University of Science and Technology7, Affymetrix8, University of North Carolina at Chapel Hill9, University of Lausanne10, University of Geneva11, Genome Institute of Singapore12, Stanford University13, Pompeu Fabra University14
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
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TL;DR: It is shown that processing of mature mRNAs through an as yet unknown mechanism may generate complex populations of both long and short RNAs whose apparently capped 5′ ends coincide.
Abstract: The transcriptomes of eukaryotic cells are incredibly complex. Individual non-coding RNAs dwarf the number of protein-coding genes, and include classes that are well understood as well as classes for which the nature, extent and functional roles are obscure. Deep sequencing of small RNAs (<200 nucleotides) from human HeLa and HepG2 cells revealed a remarkable breadth of species. These arose both from within annotated genes and from unannotated intergenic regions. Overall, small RNAs tended to align with CAGE (cap-analysis of gene expression) tags, which mark the 5' ends of capped, long RNA transcripts. Many small RNAs, including the previously described promoter-associated small RNAs, appeared to possess cap structures. Members of an extensive class of both small RNAs and CAGE tags were distributed across internal exons of annotated protein coding and non-coding genes, sometimes crossing exon-exon junctions. Here we show that processing of mature mRNAs through an as yet unknown mechanism may generate complex populations of both long and short RNAs whose apparently capped 5' ends coincide. Supplying synthetic promoter-associated small RNAs corresponding to the c-MYC transcriptional start site reduced MYC messenger RNA abundance. The studies presented here expand the catalogue of cellular small RNAs and demonstrate a biological impact for at least one class of non-canonical small RNAs.
423 citations
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TL;DR: The correlation level between sense and antisense transcripts to depend on gene expression levels, supporting the view that overlapping transcription from opposite strands may play a regulatory role and the data provide a comprehensive view of the polyadenylation state and overlapping transcription.
393 citations
Cited by
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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
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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
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TL;DR: Tests showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method, and requires only 4.3 gigabytes of memory.
Abstract: HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
13,192 citations
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TL;DR: This article showed that OCT4, SOX2, NANOG, and LIN28 factors are sufficient to reprogram human somatic cells to pluripotent stem cells that exhibit the essential characteristics of embryonic stem (ES) cells.
Abstract: Somatic cell nuclear transfer allows trans-acting factors present in the mammalian oocyte to reprogram somatic cell nuclei to an undifferentiated state. We show that four factors (OCT4, SOX2, NANOG, and LIN28) are sufficient to reprogram human somatic cells to pluripotent stem cells that exhibit the essential characteristics of embryonic stem (ES) cells. These induced pluripotent human stem cells have normal karyotypes, express telomerase activity, express cell surface markers and genes that characterize human ES cells, and maintain the developmental potential to differentiate into advanced derivatives of all three primary germ layers. Such induced pluripotent human cell lines should be useful in the production of new disease models and in drug development, as well as for applications in transplantation medicine, once technical limitations (for example, mutation through viral integration) are eliminated.
9,836 citations
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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