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Etienne Patin

Bio: Etienne Patin is an academic researcher from Pasteur Institute. The author has contributed to research in topics: Population & Natural selection. The author has an hindex of 44, co-authored 104 publications receiving 5757 citations. Previous affiliations of Etienne Patin include Uganda Revenue Authority & Paris Descartes University.


Papers
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Journal ArticleDOI
TL;DR: The degree of population differentiation is analyzed at 2.8 million Phase II HapMap single-nucleotide polymorphisms to identify a fraction of loci that have contributed, and probably still contribute, to the morphological and disease-related phenotypic diversity of current human populations.
Abstract: The considerable range of observed phenotypic variation in human populations may reflect, in part, distinctive processes of natural selection and adaptation to variable environmental conditions. Although recent genome-wide studies have identified candidate regions under selection1,2,3,4,5, it is not yet clear how natural selection has shaped population differentiation. Here, we have analyzed the degree of population differentiation at 2.8 million Phase II HapMap single-nucleotide polymorphisms6. We find that negative selection has globally reduced population differentiation at amino acid–altering mutations, particularly in disease-related genes. Conversely, positive selection has ensured the regional adaptation of human populations by increasing population differentiation in gene regions, primarily at nonsynonymous and 5′-UTR variants. Our analyses identify a fraction of loci that have contributed, and probably still contribute, to the morphological and disease-related phenotypic diversity of current human populations.

599 citations

Journal ArticleDOI
TL;DR: It is found that the intracellular TLRs—activated by nucleic acids and particularly specialized in viral recognition—have evolved under strong purifying selection, indicating their essential non-redundant role in host survival.
Abstract: Infectious diseases have been paramount among the threats to health and survival throughout human evolutionary history. Natural selection is therefore expected to act strongly on host defense genes, particularly on innate immunity genes whose products mediate the direct interaction between the host and the microbial environment. In insects and mammals, the Toll-like receptors (TLRs) appear to play a major role in initiating innate immune responses against microbes. In humans, however, it has been speculated that the set of TLRs could be redundant for protective immunity. We investigated how natural selection has acted upon human TLRs, as an approach to assess their level of biological redundancy. We sequenced the ten human TLRs in a panel of 158 individuals from various populations worldwide and found that the intracellular TLRs—activated by nucleic acids and particularly specialized in viral recognition—have evolved under strong purifying selection, indicating their essential non-redundant role in host survival. Conversely, the selective constraints on the TLRs expressed on the cell surface—activated by compounds other than nucleic acids—have been much more relaxed, with higher rates of damaging nonsynonymous and stop mutations tolerated, suggesting their higher redundancy. Finally, we tested whether TLRs have experienced spatially-varying selection in human populations and found that the region encompassing TLR10-TLR1-TLR6 has been the target of recent positive selection among non-Africans. Our findings indicate that the different TLRs differ in their immunological redundancy, reflecting their distinct contributions to host defense. The insights gained in this study foster new hypotheses to be tested in clinical and epidemiological genetics of infectious disease.

377 citations

Journal ArticleDOI
20 Oct 2016-Cell
TL;DR: The transcriptional response of primary monocytes from Africans and Europeans to bacterial and viral stimuli is characterized and regulatory variants are enriched in population-specific signals of natural selection and admixture with Neandertals introduced regulatory variants into European genomes, affecting preferentially responses to viral challenges.

355 citations

Journal ArticleDOI
TL;DR: This study identifies highly constrained genes that fulfill essential, non-redundant functions in host survival and reveals others that are more permissive to change-containing variation acquired from archaic hominins or adaptive variants in specific populations-improving the understanding of the relative biological importance of innate immunity pathways in natural conditions.
Abstract: Human genes governing innate immunity provide a valuable tool for the study of the selective pressure imposed by microorganisms on host genomes. A comprehensive, genome-wide study of how selective constraints and adaptations have driven the evolution of innate immunity genes is missing. Using full-genome sequence variation from the 1000 Genomes Project, we first show that innate immunity genes have globally evolved under stronger purifying selection than the remainder of protein-coding genes. We identify a gene set under the strongest selective constraints, mutations in which are likely to predispose individuals to life-threatening disease, as illustrated by STAT1 and TRAF3. We then evaluate the occurrence of local adaptation and detect 57 high-scoring signals of positive selection at innate immunity genes, variation in which has been associated with susceptibility to common infectious or autoimmune diseases. Furthermore, we show that most adaptations targeting coding variation have occurred in the last 6,000–13,000 years, the period at which populations shifted from hunting and gathering to farming. Finally, we show that innate immunity genes present higher Neandertal introgression than the remainder of the coding genome. Notably, among the genes presenting the highest Neandertal ancestry, we find the TLR6-TLR1-TLR10 cluster, which also contains functional adaptive variation in Europeans. This study identifies highly constrained genes that fulfill essential, non-redundant functions in host survival and reveals others that are more permissive to change—containing variation acquired from archaic hominins or adaptive variants in specific populations—improving our understanding of the relative biological importance of innate immunity pathways in natural conditions.

220 citations

Journal ArticleDOI
TL;DR: The gene damage index (GDI) is described, a genome-wide, gene-level metric of the mutational damage that has accumulated in the general population, and it is found that the GDI was correlated with selective evolutionary pressure, protein complexity, coding sequence length, and the number of paralogs.
Abstract: The protein-coding exome of a patient with a monogenic disease contains about 20,000 variants, only one or two of which are disease causing. We found that 58% of rare variants in the protein-coding exome of the general population are located in only 2% of the genes. Prompted by this observation, we aimed to develop a gene-level approach for predicting whether a given human protein-coding gene is likely to harbor disease-causing mutations. To this end, we derived the gene damage index (GDI): a genome-wide, gene-level metric of the mutational damage that has accumulated in the general population. We found that the GDI was correlated with selective evolutionary pressure, protein complexity, coding sequence length, and the number of paralogs. We compared GDI with the leading gene-level approaches, genic intolerance, and de novo excess, and demonstrated that GDI performed best for the detection of false positives (i.e., removing exome variants in genes irrelevant to disease), whereas genic intolerance and de novo excess performed better for the detection of true positives (i.e., assessing de novo mutations in genes likely to be disease causing). The GDI server, data, and software are freely available to noncommercial users from lab.rockefeller.edu/casanova/GDI.

200 citations


Cited by
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Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

10,124 citations

Journal ArticleDOI
Monkol Lek, Konrad J. Karczewski1, Konrad J. Karczewski2, Eric Vallabh Minikel1, Eric Vallabh Minikel2, Kaitlin E. Samocha, Eric Banks2, Timothy Fennell2, Anne H. O’Donnell-Luria1, Anne H. O’Donnell-Luria3, Anne H. O’Donnell-Luria2, James S. Ware, Andrew J. Hill1, Andrew J. Hill2, Andrew J. Hill4, Beryl B. Cummings2, Beryl B. Cummings1, Taru Tukiainen1, Taru Tukiainen2, Daniel P. Birnbaum2, Jack A. Kosmicki, Laramie E. Duncan1, Laramie E. Duncan2, Karol Estrada2, Karol Estrada1, Fengmei Zhao2, Fengmei Zhao1, James Zou2, Emma Pierce-Hoffman2, Emma Pierce-Hoffman1, Joanne Berghout5, David Neil Cooper6, Nicole A. Deflaux7, Mark A. DePristo2, Ron Do, Jason Flannick2, Jason Flannick1, Menachem Fromer, Laura D. Gauthier2, Jackie Goldstein2, Jackie Goldstein1, Namrata Gupta2, Daniel P. Howrigan1, Daniel P. Howrigan2, Adam Kiezun2, Mitja I. Kurki1, Mitja I. Kurki2, Ami Levy Moonshine2, Pradeep Natarajan, Lorena Orozco, Gina M. Peloso2, Gina M. Peloso1, Ryan Poplin2, Manuel A. Rivas2, Valentin Ruano-Rubio2, Samuel A. Rose2, Douglas M. Ruderfer8, Khalid Shakir2, Peter D. Stenson6, Christine Stevens2, Brett Thomas1, Brett Thomas2, Grace Tiao2, María Teresa Tusié-Luna, Ben Weisburd2, Hong-Hee Won9, Dongmei Yu, David Altshuler10, David Altshuler2, Diego Ardissino, Michael Boehnke11, John Danesh12, Stacey Donnelly2, Roberto Elosua, Jose C. Florez1, Jose C. Florez2, Stacey Gabriel2, Gad Getz1, Gad Getz2, Stephen J. Glatt13, Christina M. Hultman14, Sekar Kathiresan, Markku Laakso15, Steven A. McCarroll2, Steven A. McCarroll1, Mark I. McCarthy16, Mark I. McCarthy17, Dermot P.B. McGovern18, Ruth McPherson19, Benjamin M. Neale1, Benjamin M. Neale2, Aarno Palotie, Shaun Purcell8, Danish Saleheen20, Jeremiah M. Scharf, Pamela Sklar, Patrick F. Sullivan14, Patrick F. Sullivan21, Jaakko Tuomilehto22, Ming T. Tsuang23, Hugh Watkins16, Hugh Watkins17, James G. Wilson24, Mark J. Daly1, Mark J. Daly2, Daniel G. MacArthur1, Daniel G. MacArthur2 
18 Aug 2016-Nature
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

8,758 citations

Journal ArticleDOI
28 Oct 2010-Nature
TL;DR: The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype as mentioned in this paper, and the results of the pilot phase of the project, designed to develop and compare different strategies for genomewide sequencing with high-throughput platforms.
Abstract: The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10(-8) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research.

7,538 citations

01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

4,409 citations