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Chen J, Glémin S, Lascoux M. Genetic Diversity and the Efficacy of Purifying Selection across Plant and Animal Species. Mol Biol Evol 2017; 34:1417-1428. [DOI: 10.1093/molbev/msx088] [Citation(s) in RCA: 100] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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102
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Gilbert KJ, Sharp NP, Angert AL, Conte GL, Draghi JA, Guillaume F, Hargreaves AL, Matthey-Doret R, Whitlock MC. Local Adaptation Interacts with Expansion Load during Range Expansion: Maladaptation Reduces Expansion Load. Am Nat 2017; 189:368-380. [PMID: 28350500 DOI: 10.1086/690673] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The biotic and abiotic factors that facilitate or hinder species range expansions are many and complex. We examine the impact of two genetic processes and their interaction on fitness at expanding range edges: local maladaptation resulting from the presence of an environmental gradient and expansion load resulting from increased genetic drift at the range edge. Results from spatially explicit simulations indicate that the presence of an environmental gradient during range expansion reduces expansion load; conversely, increasing expansion load allows only locally adapted populations to persist at the range edge. Increased maladaptation reduces the speed of range expansion, resulting in less genetic drift at the expanding front and more immigration from the range center, therefore reducing expansion load at the range edge. These results may have ramifications for species being forced to shift their ranges because of climate change or other anthropogenic changes. If rapidly changing climate leads to faster expansion as populations track their shifting climatic optima, populations may suffer increased expansion load beyond previous expectations.
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103
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Seoighe C, Scally A. Inference of Candidate Germline Mutator Loci in Humans from Genome-Wide Haplotype Data. PLoS Genet 2017; 13:e1006549. [PMID: 28095480 PMCID: PMC5283766 DOI: 10.1371/journal.pgen.1006549] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Revised: 01/31/2017] [Accepted: 12/20/2016] [Indexed: 12/27/2022] Open
Abstract
The rate of germline mutation varies widely between species but little is known about the extent of variation in the germline mutation rate between individuals of the same species. Here we demonstrate that an allele that increases the rate of germline mutation can result in a distinctive signature in the genomic region linked to the affected locus, characterized by a number of haplotypes with a locally high proportion of derived alleles, against a background of haplotypes carrying a typical proportion of derived alleles. We searched for this signature in human haplotype data from phase 3 of the 1000 Genomes Project and report a number of candidate mutator loci, several of which are located close to or within genes involved in DNA repair or the DNA damage response. To investigate whether mutator alleles remained active at any of these loci, we used de novo mutation counts from human parent-offspring trios in the 1000 Genomes and Genome of the Netherlands cohorts, looking for an elevated number of de novo mutations in the offspring of parents carrying a candidate mutator haplotype at each of these loci. We found some support for two of the candidate loci, including one locus just upstream of the BRSK2 gene, which is expressed in the testis and has been reported to be involved in the response to DNA damage.
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Affiliation(s)
- Cathal Seoighe
- School of Mathematics, Statistics and Applied Mathematics, NUI Galway, Galway, Ireland
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Aylwyn Scally
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
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104
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Genetic surfing in human populations: from genes to genomes. Curr Opin Genet Dev 2016; 41:53-61. [DOI: 10.1016/j.gde.2016.08.003] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Revised: 07/06/2016] [Accepted: 08/02/2016] [Indexed: 12/20/2022]
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105
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The Effect of an Extreme and Prolonged Population Bottleneck on Patterns of Deleterious Variation: Insights from the Greenlandic Inuit. Genetics 2016; 205:787-801. [PMID: 27903613 DOI: 10.1534/genetics.116.193821] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Accepted: 11/11/2016] [Indexed: 11/18/2022] Open
Abstract
The genetic consequences of population bottlenecks on patterns of deleterious genetic variation in human populations are of tremendous interest. Based on exome sequencing of 18 Greenlandic Inuit we show that the Inuit have undergone a severe ∼20,000-year-long bottleneck. This has led to a markedly more extreme distribution of allele frequencies than seen for any other human population tested to date, making the Inuit the perfect population for investigating the effect of a bottleneck on patterns of deleterious variation. When comparing proxies for genetic load that assume an additive effect of deleterious alleles, the Inuit show, at most, a slight increase in load compared to European, East Asian, and African populations. Specifically, we observe <4% increase in the number of derived deleterious alleles in the Inuit. In contrast, proxies for genetic load under a recessive model suggest that the Inuit have a significantly higher load (20% increase or more) compared to other less bottlenecked human populations. Forward simulations under realistic models of demography support our empirical findings, showing up to a 6% increase in the genetic load for the Inuit population across all models of dominance. Further, the Inuit population carries fewer deleterious variants than other human populations, but those that are present tend to be at higher frequency than in other populations. Overall, our results show how recent demographic history has affected patterns of deleterious variants in human populations.
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106
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Juric I, Aeschbacher S, Coop G. The Strength of Selection against Neanderthal Introgression. PLoS Genet 2016; 12:e1006340. [PMID: 27824859 PMCID: PMC5100956 DOI: 10.1371/journal.pgen.1006340] [Citation(s) in RCA: 180] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2015] [Accepted: 09/06/2016] [Indexed: 11/19/2022] Open
Abstract
Hybridization between humans and Neanderthals has resulted in a low level of Neanderthal ancestry scattered across the genomes of many modern-day humans. After hybridization, on average, selection appears to have removed Neanderthal alleles from the human population. Quantifying the strength and causes of this selection against Neanderthal ancestry is key to understanding our relationship to Neanderthals and, more broadly, how populations remain distinct after secondary contact. Here, we develop a novel method for estimating the genome-wide average strength of selection and the density of selected sites using estimates of Neanderthal allele frequency along the genomes of modern-day humans. We confirm that East Asians had somewhat higher initial levels of Neanderthal ancestry than Europeans even after accounting for selection. We find that the bulk of purifying selection against Neanderthal ancestry is best understood as acting on many weakly deleterious alleles. We propose that the majority of these alleles were effectively neutral—and segregating at high frequency—in Neanderthals, but became selected against after entering human populations of much larger effective size. While individually of small effect, these alleles potentially imposed a heavy genetic load on the early-generation human–Neanderthal hybrids. This work suggests that differences in effective population size may play a far more important role in shaping levels of introgression than previously thought. A small percentage of Neanderthal DNA is present in the genomes of many contemporary human populations due to hybridization tens of thousands of years ago. Much of this Neanderthal DNA appears to be deleterious in humans, and natural selection is acting to remove it. One hypothesis is that the underlying alleles were not deleterious in Neanderthals, but rather represent genetic incompatibilities that became deleterious only once they were introduced to the human population. If so, reproductive barriers must have evolved rapidly between Neanderthals and humans after their split. Here, we show that observed patterns of Neanderthal ancestry in modern humans can be explained simply as a consequence of the difference in effective population size between Neanderthals and humans. Specifically, we find that on average, selection against individual Neanderthal alleles is very weak. This is consistent with the idea that Neanderthals over time accumulated many weakly deleterious alleles that in their small population were effectively neutral. However, after introgressing into larger human populations, those alleles became exposed to purifying selection. Thus, rather than being the result of hybrid incompatibilities, differences between human and Neanderthal effective population sizes appear to have played a key role in shaping our present-day shared ancestry.
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Affiliation(s)
- Ivan Juric
- Center for Population Biology, University of California, Davis, California, United States of America
- Department of Evolution and Ecology, University of California, Davis, California, United States of America
- * E-mail:
| | - Simon Aeschbacher
- Center for Population Biology, University of California, Davis, California, United States of America
- Department of Evolution and Ecology, University of California, Davis, California, United States of America
| | - Graham Coop
- Center for Population Biology, University of California, Davis, California, United States of America
- Department of Evolution and Ecology, University of California, Davis, California, United States of America
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107
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Abstract
The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.
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Affiliation(s)
- Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Department of Genomes & Genetics, Institut Pasteur, Paris, 75015, France.
- Centre National de la Recherche Scientifique, URA3012, Paris, 75015, France.
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, 75015, France.
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108
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Freedman AH, Lohmueller KE, Wayne RK. Evolutionary History, Selective Sweeps, and Deleterious Variation in the Dog. ANNUAL REVIEW OF ECOLOGY EVOLUTION AND SYSTEMATICS 2016. [DOI: 10.1146/annurev-ecolsys-121415-032155] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The dog is our oldest domesticate and has experienced a wide variety of demographic histories, including a bottleneck associated with domestication and individual bottlenecks associated with the formation of modern breeds. Admixture with gray wolves, and among dog breeds and populations, has also occurred throughout its history. Likewise, the intensity and focus of selection have varied, from an initial focus on traits enhancing cohabitation with humans, to more directed selection on specific phenotypic characteristics and behaviors. In this review, we summarize and synthesize genetic findings from genome-wide and complete genome studies that document the genomic consequences of demography and selection, including the effects on adaptive and deleterious variation. Consistent with the evolutionary history of the dog, signals of natural and artificial selection are evident in the dog genome. However, conclusions from studies of positive selection are fraught with the problem of false positives given that demographic history is often not taken into account.
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Affiliation(s)
- Adam H. Freedman
- Informatics Group, Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts 02138
| | - Kirk E. Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095
| | - Robert K. Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095
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109
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Mallick S, Li H, Lipson M, Mathieson I, Gymrek M, Racimo F, Zhao M, Chennagiri N, Nordenfelt S, Tandon A, Skoglund P, Lazaridis I, Sankararaman S, Fu Q, Rohland N, Renaud G, Erlich Y, Willems T, Gallo C, Spence JP, Song YS, Poletti G, Balloux F, van Driem G, de Knijff P, Romero IG, Jha AR, Behar DM, Bravi CM, Capelli C, Hervig T, Moreno-Estrada A, Posukh OL, Balanovska E, Balanovsky O, Karachanak-Yankova S, Sahakyan H, Toncheva D, Yepiskoposyan L, Tyler-Smith C, Xue Y, Abdullah MS, Ruiz-Linares A, Beall CM, Di Rienzo A, Jeong C, Starikovskaya EB, Metspalu E, Parik J, Villems R, Henn BM, Hodoglugil U, Mahley R, Sajantila A, Stamatoyannopoulos G, Wee JTS, Khusainova R, Khusnutdinova E, Litvinov S, Ayodo G, Comas D, Hammer MF, Kivisild T, Klitz W, Winkler CA, Labuda D, Bamshad M, Jorde LB, Tishkoff SA, Watkins WS, Metspalu M, Dryomov S, Sukernik R, Singh L, Thangaraj K, Pääbo S, Kelso J, Patterson N, Reich D. The Simons Genome Diversity Project: 300 genomes from 142 diverse populations. Nature 2016; 538:201-206. [PMID: 27654912 PMCID: PMC5161557 DOI: 10.1038/nature18964] [Citation(s) in RCA: 864] [Impact Index Per Article: 96.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Accepted: 06/23/2016] [Indexed: 02/06/2023]
Abstract
Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.
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Affiliation(s)
- Swapan Mallick
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Heng Li
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - Mark Lipson
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Iain Mathieson
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Melissa Gymrek
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
- Whitehead Institute for Biomedical Research, Cambridge, Massachusetts 02142, USA
- Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, Massachusetts 02139, USA
- New York Genome Center, New York, New York 10013, USA
| | - Fernando Racimo
- Department of Integrative Biology, University of California, Berkeley, California 94720-3140, USA
| | - Mengyao Zhao
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Niru Chennagiri
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Susanne Nordenfelt
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Arti Tandon
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - Pontus Skoglund
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - Iosif Lazaridis
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - Sriram Sankararaman
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - Qiaomei Fu
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
- Key Laboratory of Vertebrate Evolution and Human Origins of Chinese Academy of Sciences, IVPP, CAS, Beijing 100044, China
| | - Nadin Rohland
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - Gabriel Renaud
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany
| | - Yaniv Erlich
- New York Genome Center, New York, New York 10013, USA
- Department of Computer Science, Columbia University, New York, New York 10027, USA
- Center for Computational Biology and Bioinformatics, Columbia University, New York, New York 10032, USA
| | - Thomas Willems
- New York Genome Center, New York, New York 10013, USA
- Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Perú
| | - Jeffrey P Spence
- Computational Biology Graduate Group, University of California, Berkeley, California 94720, USA
| | - Yun S Song
- Computer Science Division, University of California, Berkeley, California 94720, USA
- Department of Statistics, University of California, Berkeley, California 94720, USA
- Department of Mathematics and Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Perú
| | - Francois Balloux
- Genetics Institute, University College London, Gower Street, London WC1E 6BT, UK
| | - George van Driem
- Institute of Linguistics, University of Bern, Bern CH-3012, Switzerland
| | - Peter de Knijff
- Department of Human and Clinical Genetics, Postzone S5-P, Leiden University Medical Center, 2333 ZA Leiden, Netherlands
| | - Irene Gallego Romero
- School of Biological Sciences, Nanyang Technological University, 637551 Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, 636921 Singapore
| | - Aashish R Jha
- Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA
| | - Doron M Behar
- Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia
| | - Claudio M Bravi
- Laboratorio de Genética Molecular Poblacional, Instituto Multidisciplinario de Biología Celular (IMBICE), CCT-CONICET La Plata/CIC Buenos Aires/Universidad Nacional de La Plata, La Plata B1906APO, Argentina
| | | | - Tor Hervig
- Department of Clinical Science, University of Bergen, Bergen 5021, Norway
| | - Andres Moreno-Estrada
- National Laboratory of Genomics for Biodiversity (LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36821, Mexico
| | - Olga L Posukh
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
- Novosibirsk State University, Novosibirsk 630090, Russia
| | | | - Oleg Balanovsky
- Research Centre for Medical Genetics, Moscow 115478, Russia
- Vavilov Institute for General Genetics, Moscow 119991, Russia
- Moscow Institute for Physics and Technology, Dolgoprudniy 141700, Russia
| | - Sena Karachanak-Yankova
- Department of Medical Genetics, National Human Genome Center, Medical University Sofia, Sofia 1431, Bulgaria
| | - Hovhannes Sahakyan
- Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia
- Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan 0014, Armenia
| | - Draga Toncheva
- Department of Medical Genetics, National Human Genome Center, Medical University Sofia, Sofia 1431, Bulgaria
| | - Levon Yepiskoposyan
- Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan 0014, Armenia
| | - Chris Tyler-Smith
- The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
| | - Yali Xue
- The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
| | | | - Andres Ruiz-Linares
- Department of Genetics, Evolution and Environment, University College London WC1E 6BT, UK
| | - Cynthia M Beall
- Department of Anthropology, Case Western Reserve University, Cleveland, Ohio 44106-7125, USA
| | - Anna Di Rienzo
- Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA
| | - Choongwon Jeong
- Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA
| | - Elena B Starikovskaya
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Ene Metspalu
- Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia
- Department of Evolutionary Biology, University of Tartu, Tartu 51010, Estonia
| | - Jüri Parik
- Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia
| | - Richard Villems
- Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia
- Department of Evolutionary Biology, University of Tartu, Tartu 51010, Estonia
- Estonian Academy of Sciences, Tallinn 10130, Estonia
| | - Brenna M Henn
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York 11794, USA
| | | | - Robert Mahley
- Gladstone Institutes, San Francisco, California 94158, USA
| | - Antti Sajantila
- Department of Forensic Medicine, University of Helsinki, Helsinki 00014, Finland
| | - George Stamatoyannopoulos
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, Washington 98195, USA
| | | | - Rita Khusainova
- Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia
| | - Sergey Litvinov
- Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia
- Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia
| | - George Ayodo
- Jaramogi Oginga Odinga University of Science and Technology, Bondo 40601, Kenya
| | - David Comas
- Institut de Biologia Evolutiva (CSIC-UPF), Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona 08003, Spain
| | - Michael F Hammer
- ARL Division of Biotechnology, University of Arizona, Tucson, Arizona 85721, USA
| | - Toomas Kivisild
- Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia
- Division of Biological Anthropology, University of Cambridge, Fitzwilliam Street, Cambridge CB2 1QH, UK
| | - William Klitz
- New York Genome Center, New York, New York 10013, USA
| | - Cheryl A Winkler
- Basic Research Laboratory, Center for Cancer Research, NCI, Leidos Biomedical Research, Inc., Frederick National Laboratory, Frederick, Maryland 21702, USA
| | - Damian Labuda
- CHU Sainte-Justine, Pediatrics Departement, Université de Montréal, Québec H3T 1C5, Canada
| | - Michael Bamshad
- Department of Pediatrics, University of Washington, Seattle, Washington 98119, USA
| | - Lynn B Jorde
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah 84112, USA
| | - Sarah A Tishkoff
- Departments of Genetics and Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - W Scott Watkins
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA
| | - Mait Metspalu
- Estonian Biocentre, Evolutionary Biology group, Tartu 51010, Estonia
| | - Stanislav Dryomov
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
- Department of Paleolithic Archaeology, Institute of Archaeology and Ethnography, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Rem Sukernik
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
- Altai State University, Barnaul 656000, Russia
| | - Lalji Singh
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500 007, India
| | | | - Svante Pääbo
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany
| | - Janet Kelso
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany
| | - Nick Patterson
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - David Reich
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts 02115, USA
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110
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Simons YB, Sella G. The impact of recent population history on the deleterious mutation load in humans and close evolutionary relatives. Curr Opin Genet Dev 2016; 41:150-158. [PMID: 27744216 DOI: 10.1016/j.gde.2016.09.006] [Citation(s) in RCA: 69] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Revised: 09/13/2016] [Accepted: 09/18/2016] [Indexed: 01/22/2023]
Abstract
Over the past decade, there has been both great interest and confusion about whether recent demographic events-notably the Out-of-Africa-bottleneck and recent population growth-have led to differences in mutation load among human populations. The confusion can be traced to the use of different summary statistics to measure load, which lead to apparently conflicting results. We argue, however, that when statistics more directly related to load are used, the results of different studies and data sets consistently reveal little or no difference in the load of non-synonymous mutations among human populations. Theory helps to understand why no such differences are seen, as well as to predict in what settings they are to be expected. In particular, as predicted by modeling, there is evidence for changes in the load of recessive loss of function mutations in founder and inbred human populations. Also as predicted, eastern subspecies of gorilla, Neanderthals and Denisovans, who are thought to have undergone reductions in population sizes that exceed the human Out-of-Africa bottleneck in duration and severity, show evidence for increased load of non-synonymous mutations (relative to western subspecies of gorillas and modern humans, respectively). A coherent picture is thus starting to emerge about the effects of demographic history on the mutation load in populations of humans and close evolutionary relatives.
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Affiliation(s)
- Yuval B Simons
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | - Guy Sella
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA.
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111
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Challenges and disparities in the application of personalized genomic medicine to populations with African ancestry. Nat Commun 2016; 7:12521. [PMID: 27725664 PMCID: PMC5062569 DOI: 10.1038/ncomms12521] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2015] [Accepted: 07/12/2016] [Indexed: 12/16/2022] Open
Abstract
To characterize the extent and impact of ancestry-related biases in precision genomic medicine, we use 642 whole-genome sequences from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) project to evaluate typical filters and databases. We find significant correlations between estimated African ancestry proportions and the number of variants per individual in all variant classification sets but one. The source of these correlations is highlighted in more detail by looking at the interaction between filtering criteria and the ClinVar and Human Gene Mutation databases. ClinVar's correlation, representing African ancestry-related bias, has changed over time amidst monthly updates, with the most extreme switch happening between March and April of 2014 (r=0.733 to r=-0.683). We identify 68 SNPs as the major drivers of this change in correlation. As long as ancestry-related bias when using these clinical databases is minimally recognized, the genetics community will face challenges with implementation, interpretation and cost-effectiveness when treating minority populations.
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112
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Mathias RA, Taub MA, Gignoux CR, Fu W, Musharoff S, O'Connor TD, Vergara C, Torgerson DG, Pino-Yanes M, Shringarpure SS, Huang L, Rafaels N, Boorgula MP, Johnston HR, Ortega VE, Levin AM, Song W, Torres R, Padhukasahasram B, Eng C, Mejia-Mejia DA, Ferguson T, Qin ZS, Scott AF, Yazdanbakhsh M, Wilson JG, Marrugo J, Lange LA, Kumar R, Avila PC, Williams LK, Watson H, Ware LB, Olopade C, Olopade O, Oliveira R, Ober C, Nicolae DL, Meyers D, Mayorga A, Knight-Madden J, Hartert T, Hansel NN, Foreman MG, Ford JG, Faruque MU, Dunston GM, Caraballo L, Burchard EG, Bleecker E, Araujo MI, Herrera-Paz EF, Gietzen K, Grus WE, Bamshad M, Bustamante CD, Kenny EE, Hernandez RD, Beaty TH, Ruczinski I, Akey J, Barnes KC. A continuum of admixture in the Western Hemisphere revealed by the African Diaspora genome. Nat Commun 2016; 7:12522. [PMID: 27725671 PMCID: PMC5062574 DOI: 10.1038/ncomms12522] [Citation(s) in RCA: 102] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Accepted: 07/12/2016] [Indexed: 01/20/2023] Open
Abstract
The African Diaspora in the Western Hemisphere represents one of the largest forced migrations in history and had a profound impact on genetic diversity in modern populations. To date, the fine-scale population structure of descendants of the African Diaspora remains largely uncharacterized. Here we present genetic variation from deeply sequenced genomes of 642 individuals from North and South American, Caribbean and West African populations, substantially increasing the lexicon of human genomic variation and suggesting much variation remains to be discovered in African-admixed populations in the Americas. We summarize genetic variation in these populations, quantifying the postcolonial sex-biased European gene flow across multiple regions. Moreover, we refine estimates on the burden of deleterious variants carried across populations and how this varies with African ancestry. Our data are an important resource for empowering disease mapping studies in African-admixed individuals and will facilitate gene discovery for diseases disproportionately affecting individuals of African ancestry.
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Affiliation(s)
- Rasika Ann Mathias
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland 21224, USA
- Department of Epidemiology, Bloomberg School of Public Health, JHU, Baltimore, Maryland 21205, USA
| | - Margaret A. Taub
- Department of Biostatistics, Bloomberg School of Public Health, JHU, Baltimore, Maryland 21205, USA
| | - Christopher R. Gignoux
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Wenqing Fu
- Department of Genomic Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Shaila Musharoff
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Timothy D. O'Connor
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
- Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Candelaria Vergara
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland 21224, USA
| | - Dara G. Torgerson
- Department of Medicine, University of California, San Francisco, San Francisco, California 94143, USA
| | - Maria Pino-Yanes
- Department of Medicine, University of California, San Francisco, San Francisco, California 94143, USA
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid 28029, Spain
| | - Suyash S. Shringarpure
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Lili Huang
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland 21224, USA
| | - Nicholas Rafaels
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland 21224, USA
| | | | - Henry Richard Johnston
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia 30322, USA
| | - Victor E. Ortega
- Center for Human Genomics and Personalized Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157, USA
| | - Albert M. Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, Michigan 48202, USA
| | - Wei Song
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
- Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Raul Torres
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, California 94158, USA
| | - Badri Padhukasahasram
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, Michigan 48202, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, San Francisco, California 94143, USA
| | - Delmy-Aracely Mejia-Mejia
- Centro de Neumologia y Alergias, San Pedro Sula 21102, Honduras
- Faculty of Medicine, Centro Medico de la Familia, San Pedro Sula 21102, Honduras
| | - Trevor Ferguson
- Tropical Medicine Research Institute, The University of the West Indies, St. Michael BB11115, Barbados
| | - Zhaohui S. Qin
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia 30322, USA
| | - Alan F. Scott
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland 21224, USA
| | - Maria Yazdanbakhsh
- Department of Parasitology, Leiden University Medical Center, Leiden 2333ZA, The Netherlands
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi 39216, USA
| | - Javier Marrugo
- Instituto de Investigaciones Immunologicas, Universidad de Cartagena, Cartagena 130000, Colombia
| | - Leslie A. Lange
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Rajesh Kumar
- Department of Pediatrics, Northwestern University, Chicago, Illinois 60637, USA
- The Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois 60637, USA
| | - Pedro C. Avila
- Department of Medicine, Northwestern University, Chicago, Illinois 60637, USA
| | - L. Keoki Williams
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, Michigan 48202, USA
- Department of Internal Medicine, Henry Ford Health System, Detroit, Michigan 48202, USA
| | - Harold Watson
- Faculty of Medical Sciences Cave Hill Campus, The University of the West Indies, Bridgetown BB11000, Barbados
- Queen Elizabeth Hospital, The University of the West Indies, St. Michael BB11115, Barbados
| | - Lorraine B. Ware
- Department of Medicine, Vanderbilt University, Nashville, Tennessee 37232, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University, Nashville, Tennessee 37232, USA
| | - Christopher Olopade
- Department of Medicine and Center for Global Health, University of Chicago, Chicago, Illinois 60637, USA
| | | | - Ricardo Oliveira
- Laboratório de Patologia Experimental, Centro de Pesquisas Gonçalo Moniz, Salvador 40296-710, Brazil
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA
| | - Dan L. Nicolae
- Department of Medicine, University of Chicago, Chicago, Illinois 60637, USA
- Department of Statistics, University of Chicago, Chicago, Illinois 60637, USA
| | - Deborah Meyers
- Center for Human Genomics and Personalized Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157, USA
| | - Alvaro Mayorga
- Centro de Neumologia y Alergias, San Pedro Sula 21102, Honduras
| | - Jennifer Knight-Madden
- Tropical Medicine Research Institute, The University of the West Indies, St. Michael BB11115, Barbados
| | - Tina Hartert
- Department of Medicine, Vanderbilt University, Nashville, Tennessee 37232, USA
| | - Nadia N. Hansel
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland 21224, USA
| | - Marilyn G. Foreman
- Pulmonary and Critical Care Medicine, Morehouse School of Medicine, Atlanta, Georgia 30310, USA
| | - Jean G. Ford
- Department of Epidemiology, Bloomberg School of Public Health, JHU, Baltimore, Maryland 21205, USA
- Department of Medicine, The Brooklyn Hospital Center, Brooklyn, New York 11201, USA
| | - Mezbah U. Faruque
- National Human Genome Center, Howard University College of Medicine, Washington DC 20059, USA
| | - Georgia M. Dunston
- National Human Genome Center, Howard University College of Medicine, Washington DC 20059, USA
- Department of Microbiology, Howard University College of Medicine, Washington DC 20059, USA
| | - Luis Caraballo
- Institute for Immunological Research, Universidad de Cartagena, Cartagena 130000, Colombia
| | - Esteban G. Burchard
- Department of Medicine, University of California, San Francisco, San Francisco, California 94143, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94158, USA
| | - Eugene Bleecker
- Center for Human Genomics and Personalized Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157, USA
| | - Maria Ilma Araujo
- Immunology Service, Universidade Federal da Bahia, Salvador 401110170, Brazil
| | - Edwin Francisco Herrera-Paz
- Centro de Neumologia y Alergias, San Pedro Sula 21102, Honduras
- Faculty of Medicine, Centro Medico de la Familia, San Pedro Sula 21102, Honduras
- Facultad de Medicina, Universidad Catolica de Honduras, San Pedro Sula 21102, Honduras
| | | | | | - Michael Bamshad
- Department of Pediatrics, University of Washington, Seattle, Washington 98195, USA
| | - Carlos D. Bustamante
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Eimear E. Kenny
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Ryan D. Hernandez
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, California 94143, USA
- California Institute for Quantitative Biosciences, University of California, San Francisco, California 94143, USA
| | - Terri H. Beaty
- Department of Epidemiology, Bloomberg School of Public Health, JHU, Baltimore, Maryland 21205, USA
| | - Ingo Ruczinski
- Department of Biostatistics, Bloomberg School of Public Health, JHU, Baltimore, Maryland 21205, USA
| | - Joshua Akey
- Department of Genomic Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Kathleen C. Barnes
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland 21224, USA
- Department of Epidemiology, Bloomberg School of Public Health, JHU, Baltimore, Maryland 21205, USA
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Abstract
Events in primate evolution are often dated by assuming a constant rate of substitution per unit time, but the validity of this assumption remains unclear. Among mammals, it is well known that there exists substantial variation in yearly substitution rates. Such variation is to be expected from differences in life history traits, suggesting it should also be found among primates. Motivated by these considerations, we analyze whole genomes from 10 primate species, including Old World Monkeys (OWMs), New World Monkeys (NWMs), and apes, focusing on putatively neutral autosomal sites and controlling for possible effects of biased gene conversion and methylation at CpG sites. We find that substitution rates are up to 64% higher in lineages leading from the hominoid-NWM ancestor to NWMs than to apes. Within apes, rates are ∼2% higher in chimpanzees and ∼7% higher in the gorilla than in humans. Substitution types subject to biased gene conversion show no more variation among species than those not subject to it. Not all mutation types behave similarly, however; in particular, transitions at CpG sites exhibit a more clocklike behavior than do other types, presumably because of their nonreplicative origin. Thus, not only the total rate, but also the mutational spectrum, varies among primates. This finding suggests that events in primate evolution are most reliably dated using CpG transitions. Taking this approach, we estimate the human and chimpanzee divergence time is 12.1 million years, and the human and gorilla divergence time is 15.1 million years.
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114
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Zhou X, Meng X, Liu Z, Chang J, Wang B, Li M, Wengel POT, Tian S, Wen C, Wang Z, Garber PA, Pan H, Ye X, Xiang Z, Bruford MW, Edwards SV, Cao Y, Yu S, Gao L, Cao Z, Liu G, Ren B, Shi F, Peterfi Z, Li D, Li B, Jiang Z, Li J, Gladyshev VN, Li R, Li M. Population Genomics Reveals Low Genetic Diversity and Adaptation to Hypoxia in Snub-Nosed Monkeys. Mol Biol Evol 2016; 33:2670-81. [PMID: 27555581 DOI: 10.1093/molbev/msw150] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Snub-nosed monkeys (genus Rhinopithecus) are a group of endangered colobines endemic to South Asia. Here, we re-sequenced the whole genomes of 38 snub-nosed monkeys representing four species within this genus. By conducting population genomic analyses, we observed a similar load of deleterious variation in snub-nosed monkeys living in both smaller and larger populations and found that genomic diversity was lower than that reported in other primates. Reconstruction of Rhinopithecus evolutionary history suggested that episodes of climatic variation over the past 2 million years, associated with glacial advances and retreats and population isolation, have shaped snub-nosed monkey demography and evolution. We further identified several hypoxia-related genes under selection in R. bieti (black snub-nosed monkey), a species that exploits habitats higher than any other nonhuman primate. These results provide the first detailed and comprehensive genomic insights into genetic diversity, demography, genetic burden, and adaptation in this radiation of endangered primates.
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Affiliation(s)
- Xuming Zhou
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School
| | - Xuehong Meng
- Novogene Bioinformatics Institute, Beijing, China
| | - Zhijin Liu
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Jiang Chang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Boshi Wang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Mingzhou Li
- College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, China
| | - Pablo Orozco-Ter Wengel
- Biodiversity and Sustainable Places Research Institute, Cardiff School of Biosciences, Cardiff University, Cardiff, United Kingdom
| | - Shilin Tian
- Novogene Bioinformatics Institute, Beijing, China College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, China
| | - Changlong Wen
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agricultural and Forestry Sciences, Beijing, China
| | - Ziming Wang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Paul A Garber
- Department of Anthropology, University of Illinois at Urbana-Champaign Program in Ecology and Evolutionary Biology, University of Illinois at Urbana-Champaign
| | - Huijuan Pan
- College of Nature Conservation, Beijing Forestry University, Beijing, China
| | - Xinping Ye
- School of Life Sciences, Shaanxi Normal University, XiXi'an, China
| | - Zuofu Xiang
- College of Life Science and Technology, Central South University of Forestry and Technology, Changsha, China
| | - Michael W Bruford
- Biodiversity and Sustainable Places Research Institute, Cardiff School of Biosciences, Cardiff University, Cardiff, United Kingdom
| | - Scott V Edwards
- Department of Organismic and Evolutionary Biology, Harvard University
| | - Yinchuan Cao
- Novogene Bioinformatics Institute, Beijing, China
| | - Shuancang Yu
- Beijing Vegetable Research Center (BVRC), Beijing Academy of Agricultural and Forestry Sciences, Beijing, China
| | - Lianju Gao
- Novogene Bioinformatics Institute, Beijing, China
| | - Zhisheng Cao
- Novogene Bioinformatics Institute, Beijing, China
| | - Guangjian Liu
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Baoping Ren
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Fanglei Shi
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Zalan Peterfi
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School
| | - Dayong Li
- College of Life Sciences, China West Normal University, Nanchong, Sichuan, China
| | - Baoguo Li
- College of Life Sciences, Northwest University, Xi'an, China
| | - Zhi Jiang
- Novogene Bioinformatics Institute, Beijing, China
| | - Junsheng Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School
| | - Ruiqiang Li
- Novogene Bioinformatics Institute, Beijing, China
| | - Ming Li
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
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115
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Osada N. Genetic diversity in humans and non-human primates and its evolutionary consequences. Genes Genet Syst 2016; 90:133-45. [PMID: 26510568 DOI: 10.1266/ggs.90.133] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Genetic diversity is a key parameter in population genetics and is important for understanding the process of evolution and for the development of appropriate conservation strategies. Recent advances in sequencing technology have enabled the measurement of genetic diversity of various organisms at the nucleotide level and on a genome-wide scale, yielding more precise estimates than were previously achievable. In this review, I have compiled and summarized the estimates of genetic diversity in humans and non-human primates based on recent genome-wide studies. Although studies on population genetics demonstrated fluctuations in population sizes over time, general patterns have emerged. As shown previously, genetic diversity in humans is one of the lowest among primates; however, certain other primate species exhibit genetic diversity that is comparable to or even lower than that in humans. There exists greater than 10-fold variation in genetic diversity among primate species, and I found weak correlation with species fecundity but not with body or propagule size. I further discuss the potential evolutionary consequences of population size decline on the evolution of primate species. The level of genetic diversity negatively correlates with the ratio of non-synonymous to synonymous polymorphisms in a population, suggesting that proportionally greater numbers of slightly deleterious mutations segregate in small rather than large populations. Although population size decline is likely to promote the fixation of slightly deleterious mutations, there are molecular mechanisms, such as compensatory mutations at various molecular levels, which may prevent fitness decline at the population level. The effects of slightly deleterious mutations from theoretical and empirical studies and their relevance to conservation biology are also discussed in this review.
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Affiliation(s)
- Naoki Osada
- Department of Population Genetics, National Institute of Genetics
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116
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Secondary structure impacts patterns of selection in human lncRNAs. BMC Biol 2016; 14:60. [PMID: 27457204 PMCID: PMC4960838 DOI: 10.1186/s12915-016-0283-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Accepted: 07/04/2016] [Indexed: 02/04/2023] Open
Abstract
Background Metazoans transcribe many long non-coding RNAs (lncRNAs) that are poorly conserved and whose function remains unknown. This has raised the questions of what fraction of the predicted lncRNAs is actually functional, and whether selection can effectively constrain lncRNAs in species with small effective population sizes such as human populations. Results Here we evaluate signatures of selection in human lncRNAs using inter-specific data and intra-specific comparisons from five major populations, as well as by assessing relationships between sequence variation and predictions of secondary structure. In all analyses we included a reference of functionally characterized lncRNAs. Altogether, our results show compelling evidence of recent purifying selection acting on both characterized and predicted lncRNAs. We found that RNA secondary structure constrains sequence variation in lncRNAs, so that polymorphisms are depleted in paired regions with low accessibility and tend to be neutral with respect to structural stability. Conclusions Important implications of our results are that secondary structure plays a role in the functionality of lncRNAs, and that the set of predicted lncRNAs contains a large fraction of functional ones that may play key roles that remain to be discovered. Electronic supplementary material The online version of this article (doi:10.1186/s12915-016-0283-0) contains supplementary material, which is available to authorized users.
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117
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Scott EM, Halees A, Itan Y, Spencer EG, He Y, Azab MA, Gabriel SB, Belkadi A, Boisson B, Abel L, Clark AG, Alkuraya FS, Casanova JL, Gleeson JG. Characterization of Greater Middle Eastern genetic variation for enhanced disease gene discovery. Nat Genet 2016; 48:1071-6. [PMID: 27428751 PMCID: PMC5019950 DOI: 10.1038/ng.3592] [Citation(s) in RCA: 281] [Impact Index Per Article: 31.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Accepted: 05/20/2016] [Indexed: 12/19/2022]
Abstract
The Greater Middle East (GME) has been a central hub of human migration and population admixture. The tradition of consanguinity, variably practiced in the Persian Gulf region, North Africa, and Central Asia, has resulted in an elevated burden of recessive disease. Here we generated a whole-exome GME variome from 1,111 unrelated subjects. We detected substantial diversity and admixture in continental and subregional populations, corresponding to several ancient founder populations with little evidence of bottlenecks. Measured consanguinity rates were an order of magnitude above those in other sampled populations, and the GME population exhibited an increased burden of runs of homozygosity (ROHs) but showed no evidence for reduced burden of deleterious variation due to classically theorized 'genetic purging'. Applying this database to unsolved recessive conditions in the GME population reduced the number of potential disease-causing variants by four- to sevenfold. These results show variegated genetic architecture in GME populations and support future human genetic discoveries in Mendelian and population genetics.
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Affiliation(s)
- Eric M Scott
- Howard Hughes Medical Institute, Rockefeller University, New York, New York, USA.,Rady Children's Institute for Genomic Medicine, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA.,Laboratory for Pediatric Brain Disease, Rockefeller University, New York, New York, USA
| | - Anason Halees
- Department of Biostatistics, Epidemiology and Scientific Computing, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Yuval Itan
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller University, New York, New York, USA
| | - Emily G Spencer
- Howard Hughes Medical Institute, Rockefeller University, New York, New York, USA.,Rady Children's Institute for Genomic Medicine, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA.,Laboratory for Pediatric Brain Disease, Rockefeller University, New York, New York, USA
| | - Yupeng He
- Howard Hughes Medical Institute, Rockefeller University, New York, New York, USA.,Rady Children's Institute for Genomic Medicine, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA.,Laboratory for Pediatric Brain Disease, Rockefeller University, New York, New York, USA
| | - Mostafa Abdellateef Azab
- Howard Hughes Medical Institute, Rockefeller University, New York, New York, USA.,Rady Children's Institute for Genomic Medicine, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA.,Laboratory for Pediatric Brain Disease, Rockefeller University, New York, New York, USA
| | - Stacey B Gabriel
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Aziz Belkadi
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Necker Hospital for Sick Children, INSERM, Paris, France.,Paris Descartes University, Imagine Institute, Paris, France
| | - Bertrand Boisson
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller University, New York, New York, USA.,Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Necker Hospital for Sick Children, INSERM, Paris, France.,Paris Descartes University, Imagine Institute, Paris, France
| | - Laurent Abel
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller University, New York, New York, USA.,Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Necker Hospital for Sick Children, INSERM, Paris, France.,Paris Descartes University, Imagine Institute, Paris, France
| | - Andrew G Clark
- Department of Molecular Biology and Genetics, Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA
| | | | - Fowzan S Alkuraya
- Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.,Department of Anatomy and Cell Biology, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
| | - Jean-Laurent Casanova
- Howard Hughes Medical Institute, Rockefeller University, New York, New York, USA.,St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller University, New York, New York, USA.,Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Necker Hospital for Sick Children, INSERM, Paris, France.,Paris Descartes University, Imagine Institute, Paris, France.,Pediatric Hematology-Immunology Unit, Necker Hospital for Sick Children, Paris, France
| | - Joseph G Gleeson
- Howard Hughes Medical Institute, Rockefeller University, New York, New York, USA.,Rady Children's Institute for Genomic Medicine, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA.,Laboratory for Pediatric Brain Disease, Rockefeller University, New York, New York, USA
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118
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Andersen MK, Pedersen CET, Moltke I, Hansen T, Albrechtsen A, Grarup N. Genetics of Type 2 Diabetes: the Power of Isolated Populations. Curr Diab Rep 2016; 16:65. [PMID: 27189761 DOI: 10.1007/s11892-016-0757-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Type 2 diabetes (T2D) affects millions of people worldwide. Improving the understanding of the underlying mechanisms and ultimately improving the treatment strategies are, thus, of great interest. To achieve this, identification of genetic variation predisposing to T2D is important. A large number of variants have been identified in large outbred populations, mainly from Europe and Asia. However, to elucidate additional variation, isolated populations have a number of advantageous properties, including increased amounts of linkage disequilibrium, and increased probability for presence of high frequency disease-associated variants due to genetic drift. Collectively, this increases the statistical power to detect association signals in isolated populations compared to large outbred populations. In this review, we elaborate on why isolated populations are a powerful resource for the identification of complex disease variants and describe their contributions to the understanding of the genetics of T2D.
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Affiliation(s)
- Mette Korre Andersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark
| | - Casper-Emil Tingskov Pedersen
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Ida Moltke
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark
- Faculty of Health Sciences, University of Southern Denmark, J.B. Winsløws Vej 19, 3, 5000, Odense, Denmark
| | - Anders Albrechtsen
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark.
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Beissinger TM, Wang L, Crosby K, Durvasula A, Hufford MB, Ross-Ibarra J. Recent demography drives changes in linked selection across the maize genome. NATURE PLANTS 2016; 2:16084. [PMID: 27294617 DOI: 10.1038/nplants.2016.84] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Accepted: 05/12/2016] [Indexed: 05/14/2023]
Abstract
Genetic diversity is shaped by the interaction of drift and selection, but the details of this interaction are not well understood. The impact of genetic drift in a population is largely determined by its demographic history, typically summarized by its long-term effective population size (Ne). Rapidly changing population demographics complicate this relationship, however. To better understand how changing demography impacts selection, we used whole-genome sequencing data to investigate patterns of linked selection in domesticated and wild maize (teosinte). We produce the first whole-genome estimate of the demography of maize domestication, showing that maize was reduced to approximately 5% the population size of teosinte before it experienced rapid expansion post-domestication to population sizes much larger than its ancestor. Evaluation of patterns of nucleotide diversity in and near genes shows little evidence of selection on beneficial amino acid substitutions, and that the domestication bottleneck led to a decline in the efficiency of purifying selection in maize. Young alleles, however, show evidence of much stronger purifying selection in maize, reflecting the much larger effective size of present day populations. Our results demonstrate that recent demographic change-a hall-mark of many species including both humans and crops-can have immediate and wide-ranging impacts on diversity that conflict with expectations based on long-term Ne alone.
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Affiliation(s)
- Timothy M Beissinger
- Department of Plant Sciences, University of California, Davis, California 95616, USA
- US Department of Agriculture, Agricultural Research Service, Columbia, Missouri 65211, USA
- Division of Plant Sciences, University of Missouri, Columbia, Missouri 65211, USA
| | - Li Wang
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa 50011, USA
| | - Kate Crosby
- Department of Plant Sciences, University of California, Davis, California 95616, USA
| | - Arun Durvasula
- Department of Plant Sciences, University of California, Davis, California 95616, USA
| | - Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa 50011, USA
| | - Jeffrey Ross-Ibarra
- Department of Plant Sciences, University of California, Davis, California 95616, USA
- Genome Center and Center for Population Biology, University of California, Davis, California 95616, USA
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120
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Uricchio LH, Zaitlen NA, Ye CJ, Witte JS, Hernandez RD. Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants. Genome Res 2016; 26:863-73. [PMID: 27197206 PMCID: PMC4937562 DOI: 10.1101/gr.202440.115] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2015] [Accepted: 05/16/2016] [Indexed: 12/20/2022]
Abstract
The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature.
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Affiliation(s)
- Lawrence H Uricchio
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, USA; Graduate Program in Bioinformatics, University of California, San Francisco, San Francisco, California 94143, USA
| | - Noah A Zaitlen
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, California 94143, USA; Institute for Quantitative Biosciences (QB3), University of California, San Francisco, San Francisco, California 94143, USA
| | - Chun Jimmie Ye
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, California 94143, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California 94143, USA
| | - John S Witte
- Institute for Human Genetics, University of California, San Francisco, San Francisco, California 94143, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California 94143, USA
| | - Ryan D Hernandez
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, California 94143, USA; Institute for Quantitative Biosciences (QB3), University of California, San Francisco, San Francisco, California 94143, USA
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121
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Abstract
Approximately 2-4% of genetic material in human populations outside Africa is derived from Neanderthals who interbred with anatomically modern humans. Recent studies have shown that this Neanderthal DNA is depleted around functional genomic regions; this has been suggested to be a consequence of harmful epistatic interactions between human and Neanderthal alleles. However, using published estimates of Neanderthal inbreeding and the distribution of mutational fitness effects, we infer that Neanderthals had at least 40% lower fitness than humans on average; this increased load predicts the reduction in Neanderthal introgression around genes without the need to invoke epistasis. We also predict a residual Neanderthal mutational load in non-Africans, leading to a fitness reduction of at least 0.5%. This effect of Neanderthal admixture has been left out of previous debate on mutation load differences between Africans and non-Africans. We also show that if many deleterious mutations are recessive, the Neanderthal admixture fraction could increase over time due to the protective effect of Neanderthal haplotypes against deleterious alleles that arose recently in the human population. This might partially explain why so many organisms retain gene flow from other species and appear to derive adaptive benefits from introgression.
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122
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Narasimhan VM, Xue Y, Tyler-Smith C. Human Knockout Carriers: Dead, Diseased, Healthy, or Improved? Trends Mol Med 2016; 22:341-351. [PMID: 26988438 PMCID: PMC4826344 DOI: 10.1016/j.molmed.2016.02.006] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2016] [Revised: 02/18/2016] [Accepted: 02/19/2016] [Indexed: 01/11/2023]
Abstract
Whole-genome and whole-exome sequence data from large numbers of individuals reveal that we all carry many variants predicted to inactivate genes (knockouts). This discovery raises questions about the phenotypic consequences of these knockouts and potentially allows us to study human gene function through the investigation of homozygous loss-of-function carriers. Here, we discuss strategies, recent results, and future prospects for large-scale human knockout studies. We examine their relevance to studying gene function, population genetics, and importantly, the implications for accurate clinical interpretations.
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Affiliation(s)
| | - Yali Xue
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
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123
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Abstract
Deleterious alleles can reach high frequency in small populations because of random fluctuations in allele frequency. This may lead, over time, to reduced average fitness. In this sense, selection is more "effective" in larger populations. Recent studies have considered whether the different demographic histories across human populations have resulted in differences in the number, distribution, and severity of deleterious variants, leading to an animated debate. This article first seeks to clarify some terms of the debate by identifying differences in definitions and assumptions used in recent studies. We argue that variants of Morton, Crow, and Muller's "total mutational damage" provide the soundest and most practical basis for such comparisons. Using simulations, analytical calculations, and 1000 Genomes Project data, we provide an intuitive and quantitative explanation for the observed similarity in genetic load across populations. We show that recent demography has likely modulated the effect of selection and still affects it, but the net result of the accumulated differences is small. Direct observation of differential efficacy of selection for specific allele classes is nevertheless possible with contemporary data sets. By contrast, identifying average genome-wide differences in the efficacy of selection across populations will require many modeling assumptions and is unlikely to provide much biological insight about human populations.
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124
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Imamura H, Downing T, Van den Broeck F, Sanders MJ, Rijal S, Sundar S, Mannaert A, Vanaerschot M, Berg M, De Muylder G, Dumetz F, Cuypers B, Maes I, Domagalska M, Decuypere S, Rai K, Uranw S, Bhattarai NR, Khanal B, Prajapati VK, Sharma S, Stark O, Schönian G, De Koning HP, Settimo L, Vanhollebeke B, Roy S, Ostyn B, Boelaert M, Maes L, Berriman M, Dujardin JC, Cotton JA. Evolutionary genomics of epidemic visceral leishmaniasis in the Indian subcontinent. eLife 2016; 5. [PMID: 27003289 PMCID: PMC4811772 DOI: 10.7554/elife.12613] [Citation(s) in RCA: 109] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2015] [Accepted: 02/15/2016] [Indexed: 12/25/2022] Open
Abstract
Leishmania donovani causes visceral leishmaniasis (VL), the second most deadly vector-borne parasitic disease. A recent epidemic in the Indian subcontinent (ISC) caused up to 80% of global VL and over 30,000 deaths per year. Resistance against antimonial drugs has probably been a contributing factor in the persistence of this epidemic. Here we use whole genome sequences from 204 clinical isolates to track the evolution and epidemiology of L. donovani from the ISC. We identify independent radiations that have emerged since a bottleneck coincident with 1960s DDT spraying campaigns. A genetically distinct population frequently resistant to antimonials has a two base-pair insertion in the aquaglyceroporin gene LdAQP1 that prevents the transport of trivalent antimonials. We find evidence of genetic exchange between ISC populations, and show that the mutation in LdAQP1 has spread by recombination. Our results reveal the complexity of L. donovani evolution in the ISC in response to drug treatment. DOI:http://dx.doi.org/10.7554/eLife.12613.001 The parasite Leishmania donovani causes a disease called visceral leishmaniasis that affects many of the world's poorest people. Around half a million new cases develop every year, but health authorities lack safe and effective drugs to treat them. Up to 80% of these cases occur in the Indian subcontinent, where devastating epidemics have occurred in the last decades. One reason these epidemics continue to occur is that the parasites develop genetic mutations allowing them to adapt to and resist the drugs used to kill them. As there are few existing drugs that can kill L. donovani, it is crucial to understand how drug resistance emerges and spreads among parasite populations. Imamura, Downing, Van den Broeck et al. have now investigated the history of visceral leishmaniasis epidemics by characterising the complete genetic sequence – or genome – of 204 L. donovani parasite samples. This revealed that the majority of parasites in the Indian subcontinent first appeared in the nineteenth century, matching the first historical records of visceral leishmaniasis epidemics. The genomes show that most of the parasites are genetically similar and can be clustered into several closely related groups. These groups first appeared in the 1960s following the end of a regional campaign to eradicate malaria. The most common parasite group is particularly resistant to drugs called antimonials, which were the main treatment for leishmaniasis until recently. These parasites have a small genetic change that scrambles most of a protein known to be involved in the uptake of antimonials. Parasites may also be able to develop resistance to drugs through additional mechanisms that allow them to produce many copies of the same gene. These mechanisms could allow the parasites to rapidly adapt to new drugs or changes in the populations it infects. The work of Imamura et al. looks only at parasites isolated from patients then grown in the laboratory, so further research is now needed to explore how variable the Leishmania genome is in both of the parasite’s hosts: humans and sandflies. Imamura et al.’s study reveals how L. donovani has spread throughout the Indian subcontinent in fine detail. The genome data can be used to create simple molecular tools that could form an "early warning system" to track the success of disease control programs and to determine how well the current drugs are working. DOI:http://dx.doi.org/10.7554/eLife.12613.002
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Affiliation(s)
- Hideo Imamura
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Tim Downing
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom.,School of Maths, Applied Maths and Statistics, National University of Ireland Galway, Galway, Ireland
| | | | | | - Suman Rijal
- BP Koirala Institute of Health Sciences, Dharan, Nepal
| | - Shyam Sundar
- Department of Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - An Mannaert
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Manu Vanaerschot
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Maya Berg
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Géraldine De Muylder
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Franck Dumetz
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Bart Cuypers
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Ilse Maes
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | | | - Saskia Decuypere
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.,Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Keshav Rai
- BP Koirala Institute of Health Sciences, Dharan, Nepal
| | | | | | | | - Vijay Kumar Prajapati
- Department of Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Smriti Sharma
- Department of Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Olivia Stark
- Institut für Mikrobiologie und Hygiene, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Gabriele Schönian
- Institut für Mikrobiologie und Hygiene, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Harry P De Koning
- Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Luca Settimo
- Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.,Department of Chemistry and Chemical Biology, Northeastern University, Boston, United States
| | - Benoit Vanhollebeke
- Laboratory of Molecular Parasitology, Université Libre de Bruxelles, Gosselies, Belgium
| | - Syamal Roy
- Department of Infectious Diseases and Immunology, Council of Scientific and Industrial Research, Indian Institute of Chemical Biology, Kolkata, India
| | - Bart Ostyn
- Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
| | - Marleen Boelaert
- Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
| | - Louis Maes
- Department of Biomedical Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Antwerp, Belgium
| | | | - Jean-Claude Dujardin
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.,Department of Biomedical Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Antwerp, Belgium
| | - James A Cotton
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
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125
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Narasimhan VM, Hunt KA, Mason D, Baker CL, Karczewski KJ, Barnes MR, Barnett AH, Bates C, Bellary S, Bockett NA, Giorda K, Griffiths CJ, Hemingway H, Jia Z, Kelly MA, Khawaja HA, Lek M, McCarthy S, McEachan R, O'Donnell-Luria A, Paigen K, Parisinos CA, Sheridan E, Southgate L, Tee L, Thomas M, Xue Y, Schnall-Levin M, Petkov PM, Tyler-Smith C, Maher ER, Trembath RC, MacArthur DG, Wright J, Durbin R, van Heel DA. Health and population effects of rare gene knockouts in adult humans with related parents. Science 2016; 352:474-7. [PMID: 26940866 DOI: 10.1126/science.aac8624] [Citation(s) in RCA: 214] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Accepted: 02/18/2016] [Indexed: 12/13/2022]
Abstract
Examining complete gene knockouts within a viable organism can inform on gene function. We sequenced the exomes of 3222 British adults of Pakistani heritage with high parental relatedness, discovering 1111 rare-variant homozygous genotypes with predicted loss of function (knockouts) in 781 genes. We observed 13.7% fewer homozygous knockout genotypes than we expected, implying an average load of 1.6 recessive-lethal-equivalent loss-of-function (LOF) variants per adult. When genetic data were linked to the individuals' lifelong health records, we observed no significant relationship between gene knockouts and clinical consultation or prescription rate. In this data set, we identified a healthy PRDM9-knockout mother and performed phased genome sequencing on her, her child, and control individuals. Our results show that meiotic recombination sites are localized away from PRDM9-dependent hotspots. Thus, natural LOF variants inform on essential genetic loci and demonstrate PRDM9 redundancy in humans.
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Affiliation(s)
| | - Karen A Hunt
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Dan Mason
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust, Bradford BD9 6RJ, UK
| | - Christopher L Baker
- Center for Genome Dynamics, The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Konrad J Karczewski
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Michael R Barnes
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Anthony H Barnett
- Diabetes and Endocrine Centre, Heart of England NHS Foundation Trust and University of Birmingham, Birmingham B9 5SS, UK
| | - Chris Bates
- TPP, Mill House, Troy Road, Leeds LS18 5TN, UK
| | - Srikanth Bellary
- Aston Research Centre for Healthy Ageing, Aston University, Birmingham B4 7ET, UK
| | - Nicholas A Bockett
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Kristina Giorda
- 10X Genomics, 7068 Koll Center Parkway, Suite 415, Pleasanton, CA 94566, USA
| | - Christopher J Griffiths
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Harry Hemingway
- Farr Institute of Health Informatics Research, London NW1 2DA, UK. Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Zhilong Jia
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - M Ann Kelly
- School of Clinical and Experimental Medicine, University of Birmingham, Birmingham B15 2TT, UK
| | - Hajrah A Khawaja
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Monkol Lek
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shane McCarthy
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Rosie McEachan
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust, Bradford BD9 6RJ, UK
| | - Anne O'Donnell-Luria
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kenneth Paigen
- Center for Genome Dynamics, The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Constantinos A Parisinos
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Eamonn Sheridan
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust, Bradford BD9 6RJ, UK
| | - Laura Southgate
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Louise Tee
- School of Clinical and Experimental Medicine, University of Birmingham, Birmingham B15 2TT, UK
| | - Mark Thomas
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Yali Xue
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | | | - Petko M Petkov
- Center for Genome Dynamics, The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | | | - Eamonn R Maher
- Department of Medical Genetics, University of Cambridge and National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, Box 238, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK. Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Richard C Trembath
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK. Faculty of Life Sciences and Medicine, King's College London, London SE1 1UL, UK
| | - Daniel G MacArthur
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust, Bradford BD9 6RJ, UK
| | - Richard Durbin
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.
| | - David A van Heel
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK.
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126
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Brandvain Y, Wright SI. The Limits of Natural Selection in a Nonequilibrium World. Trends Genet 2016; 32:201-210. [PMID: 26874998 DOI: 10.1016/j.tig.2016.01.004] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 12/23/2015] [Accepted: 01/19/2016] [Indexed: 11/19/2022]
Abstract
Evolutionary theory predicts that factors such as a small population size or low recombination rate can limit the action of natural selection. The emerging field of comparative population genomics offers an opportunity to evaluate these hypotheses. However, classical theoretical predictions assume that populations are at demographic equilibrium. This assumption is likely to be violated in the very populations researchers use to evaluate selection's limits: populations that have experienced a recent shift in population size and/or effective recombination rates. Here we highlight theory and data analyses concerning limitations on the action of natural selection in nonequilibrial populations and argue that substantial care is needed to appropriately test whether species and populations show meaningful differences in selection efficacy. A move toward model-based inferences that explicitly incorporate nonequilibrium dynamics provides a promising approach to more accurately contrast selection efficacy across populations and interpret its significance.
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Affiliation(s)
- Yaniv Brandvain
- Department of Plant Biology, University of Minnesota, St Paul, MN 55108, USA
| | - Stephen I Wright
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON M5S 3B2, Canada.
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127
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Patterns of deleterious variation between human populations reveal an unbalanced load. Proc Natl Acad Sci U S A 2016; 113:809-11. [PMID: 26787891 DOI: 10.1073/pnas.1524016113] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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128
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Marsden CD, Ortega-Del Vecchyo D, O'Brien DP, Taylor JF, Ramirez O, Vilà C, Marques-Bonet T, Schnabel RD, Wayne RK, Lohmueller KE. Bottlenecks and selective sweeps during domestication have increased deleterious genetic variation in dogs. Proc Natl Acad Sci U S A 2016; 113:152-7. [PMID: 26699508 PMCID: PMC4711855 DOI: 10.1073/pnas.1512501113] [Citation(s) in RCA: 210] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Population bottlenecks, inbreeding, and artificial selection can all, in principle, influence levels of deleterious genetic variation. However, the relative importance of each of these effects on genome-wide patterns of deleterious variation remains controversial. Domestic and wild canids offer a powerful system to address the role of these factors in influencing deleterious variation because their history is dominated by known bottlenecks and intense artificial selection. Here, we assess genome-wide patterns of deleterious variation in 90 whole-genome sequences from breed dogs, village dogs, and gray wolves. We find that the ratio of amino acid changing heterozygosity to silent heterozygosity is higher in dogs than in wolves and, on average, dogs have 2-3% higher genetic load than gray wolves. Multiple lines of evidence indicate this pattern is driven by less efficient natural selection due to bottlenecks associated with domestication and breed formation, rather than recent inbreeding. Further, we find regions of the genome implicated in selective sweeps are enriched for amino acid changing variants and Mendelian disease genes. To our knowledge, these results provide the first quantitative estimates of the increased burden of deleterious variants directly associated with domestication and have important implications for selective breeding programs and the conservation of rare and endangered species. Specifically, they highlight the costs associated with selective breeding and question the practice favoring the breeding of individuals that best fit breed standards. Our results also suggest that maintaining a large population size, rather than just avoiding inbreeding, is a critical factor for preventing the accumulation of deleterious variants.
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Affiliation(s)
- Clare D Marsden
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095
| | | | - Dennis P O'Brien
- Department of Veterinary Medicine and Surgery, University of Missouri, Columbia, MO 65211
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211
| | - Oscar Ramirez
- Institut Catala de Recerca i Estudis Avançats, Institut de Biologia Evolutiva (Centro Superior de Investigaciones Cientificas-Universitat Pompeu Fabra), 08003 Barcelona, Spain
| | - Carles Vilà
- Conservation and Evolutionary Genetics Group, Estación Biológica de Doñana-Consejo Superior de Investigaciones Cientificas, 41092, Seville, Spain
| | - Tomas Marques-Bonet
- Institut Catala de Recerca i Estudis Avançats, Institut de Biologia Evolutiva (Centro Superior de Investigaciones Cientificas-Universitat Pompeu Fabra), 08003 Barcelona, Spain; Centro Nacional Analasis Genomico, 08023, Barcelona, Spain
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211; Informatics Institute, University of Missouri, Columbia, MO 65211
| | - Robert K Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095; Interdepartmental Program in Bioinformatics, University of California, Los Angeles, CA 90095; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
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129
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Subramanian S. Europeans have a higher proportion of high‑frequency deleterious variants than Africans. Hum Genet 2016; 135:1-7. [PMID: 26462918 DOI: 10.1007/s00439-015-1604-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Accepted: 10/01/2015] [Indexed: 12/11/2022]
Abstract
Recent studies have shown that a high proportion of rare variants in European and African populations are deleterious in nature. However, the deleterious fraction of high-frequency variants is unclear. Using more than 6500 exomes we show a much higher fraction (11 %) of relatively high-frequency nonsynonymous (amino acid altering) variants (DAF 0.1–10 %) in European Americans (EA) compared to those from African Americans (AA). In contrast, this difference was only marginal (<2 %) for low-frequency nonsynonymous variants (DAF <0.1 %). Our results also revealed that the proportion of high-frequency deleterious nonsynonymous variants in EA was much higher (24 %) than that in AA and this difference was very small (4 %) for the low-frequency deleterious amino acid altering variants. We also show that EA have significantly more number of high-frequency deleterious nonsynonymous variants per genome than AA. The high proportion of high-frequency deleterious variants in EA could be the result of the well-known bottleneck experienced by European populations in which harmful mutations may have drifted to high frequencies. The estimated ages of deleterious variants support this prediction. Our results suggest that high-frequency variants could be relatively more likely to be associated with diseases in Europeans than in Africans and hence emphasize the need for population-specific strategies in genomic medicine studies.
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Affiliation(s)
- Sankar Subramanian
- Environmental Futures Research Institute, Griffith University, 170 Kessels Road, Nathan, QLD 4111, Australia.
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Distance from sub-Saharan Africa predicts mutational load in diverse human genomes. Proc Natl Acad Sci U S A 2015; 113:E440-9. [PMID: 26712023 DOI: 10.1073/pnas.1510805112] [Citation(s) in RCA: 158] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
The Out-of-Africa (OOA) dispersal ∼ 50,000 y ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from seven geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia, and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.
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131
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Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR. A global reference for human genetic variation. Nature 2015; 526:68-74. [PMID: 26432245 PMCID: PMC4750478 DOI: 10.1038/nature15393] [Citation(s) in RCA: 11275] [Impact Index Per Article: 1127.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Accepted: 08/20/2015] [Indexed: 12/04/2022]
Abstract
The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies. Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics. The 1000 Genomes Project has sought to comprehensively catalogue human genetic variation across populations, providing a valuable public genomic resource. The data obtained so far have found applications ranging from association studies and fine mapping studies to the filtering of likely neutral variants in rare-disease cohorts. The authors now report on the final phase of the project, phase 3, which covers previously uncharacterized areas of human genetic diversity in terms of the populations sampled and categories of characterized variation. The sample now includes more than 2,500 individuals from 26 global populations, with low coverage whole-genome and deep exome sequencing, as well as dense microarray genotyping. They find that while most common variants are shared across populations, rarer variants are often restricted to closely related populations. The authors also demonstrate the use of the phase 3 dataset as a reference panel for imputation to improve the resolution in genetic association studies.
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Edge MD, Rosenberg NA. A General Model of the Relationship between the Apportionment of Human Genetic Diversity and the Apportionment of Human Phenotypic Diversity. Hum Biol 2015; 87:313-337. [PMID: 27737590 PMCID: PMC8504698 DOI: 10.13110/humanbiology.87.4.0313] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Models that examine genetic differences between populations alongside a genotype-phenotype map can provide insight about phenotypic variation among groups. We generalize a simple model of a completely heritable, additive, selectively neutral quantitative trait to examine the relationship between single-locus genetic differentiation and phenotypic differentiation on quantitative traits. In agreement with similar efforts using different models, we show that the expected degree to which two groups differ on a neutral quantitative trait is not strongly affected by the number of genetic loci that influence the trait: neutral trait differences are expected to have a magnitude comparable to the genetic differences at a single neutral locus. We discuss this result with respect to population differences in disease phenotypes, arguing that although neutral genetic differences between populations can contribute to specific differences between populations in health outcomes, systematic patterns of difference that run in the same direction for many genetically independent health conditions are unlikely to be explained by neutral genetic differentiation.
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Affiliation(s)
- Michael D. Edge
- Department of Biology, Stanford University, Stanford, California
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Sudmant PH, Mallick S, Nelson BJ, Hormozdiari F, Krumm N, Huddleston J, Coe BP, Baker C, Nordenfelt S, Bamshad M, Jorde LB, Posukh OL, Sahakyan H, Watkins WS, Yepiskoposyan L, Abdullah MS, Bravi CM, Capelli C, Hervig T, Wee JTS, Tyler-Smith C, van Driem G, Romero IG, Jha AR, Karachanak-Yankova S, Toncheva D, Comas D, Henn B, Kivisild T, Ruiz-Linares A, Sajantila A, Metspalu E, Parik J, Villems R, Starikovskaya EB, Ayodo G, Beall CM, Di Rienzo A, Hammer MF, Khusainova R, Khusnutdinova E, Klitz W, Winkler C, Labuda D, Metspalu M, Tishkoff SA, Dryomov S, Sukernik R, Patterson N, Reich D, Eichler EE. Global diversity, population stratification, and selection of human copy-number variation. Science 2015; 349:aab3761. [PMID: 26249230 PMCID: PMC4568308 DOI: 10.1126/science.aab3761] [Citation(s) in RCA: 236] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2015] [Accepted: 07/29/2015] [Indexed: 12/14/2022]
Abstract
In order to explore the diversity and selective signatures of duplication and deletion human copy-number variants (CNVs), we sequenced 236 individuals from 125 distinct human populations. We observed that duplications exhibit fundamentally different population genetic and selective signatures than deletions and are more likely to be stratified between human populations. Through reconstruction of the ancestral human genome, we identify megabases of DNA lost in different human lineages and pinpoint large duplications that introgressed from the extinct Denisova lineage now found at high frequency exclusively in Oceanic populations. We find that the proportion of CNV base pairs to single-nucleotide-variant base pairs is greater among non-Africans than it is among African populations, but we conclude that this difference is likely due to unique aspects of non-African population history as opposed to differences in CNV load.
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Affiliation(s)
- Peter H Sudmant
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Swapan Mallick
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Bradley J Nelson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | | | - Niklas Krumm
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - John Huddleston
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Bradley P Coe
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Carl Baker
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Susanne Nordenfelt
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Michael Bamshad
- Department of Pediatrics, University of Washington, Seattle, WA 98119, USA
| | - Lynn B Jorde
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Olga L Posukh
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia. Novosibirsk State University, Novosibirsk 630090, Russia
| | - Hovhannes Sahakyan
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia. Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan 0014, Armenia
| | - W Scott Watkins
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
| | - Levon Yepiskoposyan
- Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan 0014, Armenia
| | - M Syafiq Abdullah
- Raja Isteri Pengiran Anak Saleha (RIPAS) Hospital, Bandar Seri Begawan, Brunei Darussalam
| | - Claudio M Bravi
- Laboratorio de Genética Molecular Poblacional, Instituto Multidisciplinario de Biología Celular (IMBICE), Centro Científico y Tecnológico-Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET) and Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CICPBA), La Plata B1906APO, Argentina
| | | | - Tor Hervig
- Department of Clinical Science, University of Bergen, Bergen 5021, Norway
| | | | - Chris Tyler-Smith
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
| | - George van Driem
- Institute of Linguistics, University of Bern, Bern CH-3012, Switzerland
| | | | - Aashish R Jha
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Sena Karachanak-Yankova
- Department of Medical Genetics, National Human Genome Center, Medical University Sofia, Sofia 1431, Bulgaria
| | - Draga Toncheva
- Department of Medical Genetics, National Human Genome Center, Medical University Sofia, Sofia 1431, Bulgaria
| | - David Comas
- Institut de Biologia Evolutiva [Consejo Superior de Investigaciones Científicas-Universitat Pompeu Fabra (CSIC-UPF)], Departament de Ciències Experimentals i de la Salut, UPF, Barcelona 08003, Spain
| | - Brenna Henn
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794, USA
| | - Toomas Kivisild
- Division of Biological Anthropology, University of Cambridge, Fitzwilliam Street, Cambridge CB2 1QH, UK
| | - Andres Ruiz-Linares
- Department of Genetics, Evolution and Environment, University College London, WC1E 6BT, UK
| | - Antti Sajantila
- University of Helsinki, Department of Forensic Medicine, Helsinki 00014, Finland
| | - Ene Metspalu
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia. University of Tartu, Department of Evolutionary Biology, Tartu 5101, Estonia
| | - Jüri Parik
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia
| | - Richard Villems
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia
| | - Elena B Starikovskaya
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - George Ayodo
- Center for Global Health and Child Development, Kisumu 40100, Kenya
| | - Cynthia M Beall
- Department of Anthropology, Case Western Reserve University, Cleveland, OH 44106-7125, USA
| | - Anna Di Rienzo
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Michael F Hammer
- Arizona Research Laboratories Division of Biotechnology, University of Arizona, Tucson, AZ 85721, USA
| | - Rita Khusainova
- Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia. Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia. Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia
| | - William Klitz
- Integrative Biology, University of California, Berkeley, CA 94720-3140, USA
| | - Cheryl Winkler
- Basic Research Laboratory, Center for Cancer Research, National Cancer Institute, Leidos Biomedical Research, Incorporated, Frederick National Laboratory, Frederick, MD 21702, USA
| | - Damian Labuda
- Centre Hospitalier Universitaire (CHU) Sainte-Justine, Département de Pédiatrie, Université de Montréal, QC H3T 1C5, Canada
| | - Mait Metspalu
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia
| | - Sarah A Tishkoff
- Departments of Biology and Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Stanislav Dryomov
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia. Department of Paleolithic Archaeology, Institute of Archaeology and Ethnography, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Rem Sukernik
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia. Altai State University, Barnaul 656000, Russia
| | - Nick Patterson
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - David Reich
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.
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Balick DJ, Do R, Cassa CA, Reich D, Sunyaev SR. Dominance of Deleterious Alleles Controls the Response to a Population Bottleneck. PLoS Genet 2015; 11:e1005436. [PMID: 26317225 PMCID: PMC4552954 DOI: 10.1371/journal.pgen.1005436] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Accepted: 07/09/2015] [Indexed: 11/30/2022] Open
Abstract
Population bottlenecks followed by re-expansions have been common throughout history of many populations. The response of alleles under selection to such demographic perturbations has been a subject of great interest in population genetics. On the basis of theoretical analysis and computer simulations, we suggest that this response qualitatively depends on dominance. The number of dominant or additive deleterious alleles per haploid genome is expected to be slightly increased following the bottleneck and re-expansion. In contrast, the number of completely or partially recessive alleles should be sharply reduced. Changes of population size expose differences between recessive and additive selection, potentially providing insight into the prevalence of dominance in natural populations. Specifically, we use a simple statistic, BR≡∑xipop1/∑xjpop2, where xi represents the derived allele frequency, to compare the number of mutations in different populations, and detail its functional dependence on the strength of selection and the intensity of the population bottleneck. We also provide empirical evidence showing that gene sets associated with autosomal recessive disease in humans may have a BR indicative of recessive selection. Together, these theoretical predictions and empirical observations show that complex demographic history may facilitate rather than impede inference of parameters of natural selection. Dominance has played a central role in classical genetics since its inception. However, the effect of dominance introduces substantial technical complications into theoretical models describing dynamics of alleles in populations. As a result, dominance is often ignored in population genetic models. Statistical tests for selection built on these models do not discriminate between recessive and additive alleles. We show that historical changes in population size can provide a way to differentiate between recessive and additive selection. Our analysis compares two sub-populations with different demographic histories. History of our own species provides plenty of examples of sub-populations that went through population bottlenecks followed by re-expansions. We show that demographic differences, which generally complicate the analysis, can instead aid in the inference of features of natural selection.
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Affiliation(s)
- Daniel J. Balick
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
| | - Ron Do
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Center for Statistical Genetics, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Christopher A. Cassa
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
| | - David Reich
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Shamil R. Sunyaev
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
- * E-mail:
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135
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The role of climate and out-of-Africa migration in the frequencies of risk alleles for 21 human diseases. BMC Genet 2015; 16:81. [PMID: 26170196 PMCID: PMC4501093 DOI: 10.1186/s12863-015-0239-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2015] [Accepted: 06/24/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Demography and environmental adaptation can affect the global distribution of genetic variants and possibly the distribution of disease. Population heterozygosity of single nucleotide polymorphisms has been shown to decrease strongly with distance from Africa and this has been attributed to the effect of serial founding events during the migration of humans out of Africa. Additionally, population allele frequencies have been shown to change due to environmental adaptation. Here, we investigate the relationship of Out-of-Africa migration and climatic variables to the distribution of risk alleles for 21 diseases. RESULTS For each disease, we computed the regression of average heterozygosity and average allele frequency of the risk alleles with distance from Africa and 9 environmental variables. We compared these regressions to a null distribution created by regressing statistics for SNPs not associated with disease on distance from Africa and these environmental variables. Additionally, we used Bayenv 2.0 to assess the signal of environmental adaptation associated with individual risk SNPs. For those SNPs in HGDP and HapMap that are risk alleles for type 2 diabetes, we cannot reject that their distribution is as expected from Out-of-Africa migration. However, the allelic statistics for many other diseases correlate more closely with environmental variables than would be expected from the serial founder effect and show signals of environmental adaptation. We report strong environmental interactions with several autoimmune diseases, and note a particularly strong interaction between asthma and summer humidity. Additionally, we identified several risk genes with strong environmental associations. CONCLUSIONS For most diseases, migration does not explain the distribution of risk alleles and the worldwide pattern of allele frequencies for some diseases may be better explained by environmental associations, which suggests that some selection has acted on these diseases.
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Kehdy FSG, Gouveia MH, Machado M, Magalhães WCS, Horimoto AR, Horta BL, Moreira RG, Leal TP, Scliar MO, Soares-Souza GB, Rodrigues-Soares F, Araújo GS, Zamudio R, Sant Anna HP, Santos HC, Duarte NE, Fiaccone RL, Figueiredo CA, Silva TM, Costa GNO, Beleza S, Berg DE, Cabrera L, Debortoli G, Duarte D, Ghirotto S, Gilman RH, Gonçalves VF, Marrero AR, Muniz YC, Weissensteiner H, Yeager M, Rodrigues LC, Barreto ML, Lima-Costa MF, Pereira AC, Rodrigues MR, Tarazona-Santos E. Origin and dynamics of admixture in Brazilians and its effect on the pattern of deleterious mutations. Proc Natl Acad Sci U S A 2015; 112:8696-701. [PMID: 26124090 PMCID: PMC4507185 DOI: 10.1073/pnas.1504447112] [Citation(s) in RCA: 183] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
While South Americans are underrepresented in human genomic diversity studies, Brazil has been a classical model for population genetics studies on admixture. We present the results of the EPIGEN Brazil Initiative, the most comprehensive up-to-date genomic analysis of any Latin-American population. A population-based genome-wide analysis of 6,487 individuals was performed in the context of worldwide genomic diversity to elucidate how ancestry, kinship, and inbreeding interact in three populations with different histories from the Northeast (African ancestry: 50%), Southeast, and South (both with European ancestry >70%) of Brazil. We showed that ancestry-positive assortative mating permeated Brazilian history. We traced European ancestry in the Southeast/South to a wider European/Middle Eastern region with respect to the Northeast, where ancestry seems restricted to Iberia. By developing an approximate Bayesian computation framework, we infer more recent European immigration to the Southeast/South than to the Northeast. Also, the observed low Native-American ancestry (6-8%) was mostly introduced in different regions of Brazil soon after the European Conquest. We broadened our understanding of the African diaspora, the major destination of which was Brazil, by revealing that Brazilians display two within-Africa ancestry components: one associated with non-Bantu/western Africans (more evident in the Northeast and African Americans) and one associated with Bantu/eastern Africans (more present in the Southeast/South). Furthermore, the whole-genome analysis of 30 individuals (42-fold deep coverage) shows that continental admixture rather than local post-Columbian history is the main and complex determinant of the individual amount of deleterious genotypes.
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Affiliation(s)
- Fernanda S G Kehdy
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Mateus H Gouveia
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Moara Machado
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Wagner C S Magalhães
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Andrea R Horimoto
- Instituto do Coração, Universidade de São Paulo, 05403-900, São Paulo, Sao Paulo, Brazil
| | - Bernardo L Horta
- Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, 464, 96001-970 Pelotas, Rio Grande do Sul, Brazil
| | - Rennan G Moreira
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Thiago P Leal
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Marilia O Scliar
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Giordano B Soares-Souza
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Fernanda Rodrigues-Soares
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Gilderlanio S Araújo
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Roxana Zamudio
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Hanaisa P Sant Anna
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Hadassa C Santos
- Instituto do Coração, Universidade de São Paulo, 05403-900, São Paulo, Sao Paulo, Brazil
| | - Nubia E Duarte
- Instituto do Coração, Universidade de São Paulo, 05403-900, São Paulo, Sao Paulo, Brazil
| | - Rosemeire L Fiaccone
- Departamento de Estatística, Instituto de Matemática, Universidade Federal da Bahia, 40170-110, Salvador, Bahia, Brazil
| | - Camila A Figueiredo
- Departamento de Ciências da Biointeração, Instituto de Ciências da Saúde, Universidade Federal da Bahia, 40110-100, Salvador, Bahia, Brazil
| | - Thiago M Silva
- Instituto de Saúde Coletiva, Universidade Federal da Bahia, 40110-040, Salvador, Bahia, Brazil
| | - Gustavo N O Costa
- Instituto de Saúde Coletiva, Universidade Federal da Bahia, 40110-040, Salvador, Bahia, Brazil
| | - Sandra Beleza
- Department of Genetics, University of Leicester, LE1 7RH, Leicester, United Kingdom
| | - Douglas E Berg
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110; Department of Medicine, University of California, San Diego, CA 92093
| | - Lilia Cabrera
- Biomedical Research Unit, Asociación Benéfica Proyectos en Informática, Salud, Medicina y Agricultura (AB PRISMA), 170070, Lima, Peru
| | - Guilherme Debortoli
- Departamento de Biologia Celular, Embriologia e Genética, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, Santa Catarina, Brazil
| | - Denise Duarte
- Departamento de Estatística, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Silvia Ghirotto
- Dipartimento di Scienze della Vita e Biotecnologie, Università di Ferrara, 44121 Ferrara, Italy
| | - Robert H Gilman
- Bloomberg School of Public Health, International Health, Johns Hopkins University, Baltimore, MD 21205; Laboratorio de Investigación de Enfermedades Infecciosas, Universidade Peruana Cayetano Heredia, 15102, Lima, Peru
| | - Vanessa F Gonçalves
- Department of Psychiatry and Neuroscience Section, Center for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada M5T 1R8
| | - Andrea R Marrero
- Departamento de Biologia Celular, Embriologia e Genética, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, Santa Catarina, Brazil
| | - Yara C Muniz
- Departamento de Biologia Celular, Embriologia e Genética, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, Santa Catarina, Brazil
| | - Hansi Weissensteiner
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, 6020 Innsbruck, Austria
| | - Meredith Yeager
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 20850
| | - Laura C Rodrigues
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom
| | - Mauricio L Barreto
- Instituto de Saúde Coletiva, Universidade Federal da Bahia, 40110-040, Salvador, Bahia, Brazil
| | - M Fernanda Lima-Costa
- Instituto de Pesquisa Rene Rachou, Fundação Oswaldo Cruz, 30190-002, Belo Horizonte, Minas Gerais, Brazil
| | - Alexandre C Pereira
- Instituto do Coração, Universidade de São Paulo, 05403-900, São Paulo, Sao Paulo, Brazil
| | - Maíra R Rodrigues
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil
| | - Eduardo Tarazona-Santos
- Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Minas Gerais, Brazil;
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Gambin T, Jhangiani SN, Below JE, Campbell IM, Wiszniewski W, Muzny DM, Staples J, Morrison AC, Bainbridge MN, Penney S, McGuire AL, Gibbs RA, Lupski JR, Boerwinkle E. Secondary findings and carrier test frequencies in a large multiethnic sample. Genome Med 2015; 7:54. [PMID: 26195989 PMCID: PMC4507324 DOI: 10.1186/s13073-015-0171-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 05/06/2015] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Besides its growing importance in clinical diagnostics and understanding the genetic basis of Mendelian and complex diseases, whole exome sequencing (WES) is a rich source of additional information of potential clinical utility for physicians, patients and their families. We analyzed the frequency and nature of single nucleotide variants (SNVs) considered secondary findings and recessive disease allele carrier status in the exomes of 8554 individuals from a large, randomly sampled cohort study and 2514 patients from a study of presumed Mendelian disease having undergone WES. METHODS We used the same sequencing platform and data processing pipeline to analyze all samples and characterized the distributions of reported pathogenic (ClinVar, Human Gene Mutation Database (HGMD)) and predicted deleterious variants in the pre-specified American College of Medical Genetics and Genomics (ACMG) secondary findings and recessive disease genes in different ethnic groups. RESULTS In the 56 ACMG secondary findings genes, the average number of predicted deleterious variants per individual was 0.74, and the mean number of ClinVar reported pathogenic variants was 0.06. We observed an average of 10 deleterious and 0.78 ClinVar reported pathogenic variants per individual in 1423 autosomal recessive disease genes. By repeatedly sampling pairs of exomes, 0.5 % of the randomly generated couples were at 25 % risk of having an affected offspring for an autosomal recessive disorder based on the ClinVar variants. CONCLUSIONS By investigating reported pathogenic and novel, predicted deleterious variants we estimated the lower and upper limits of the population fraction for which exome sequencing may reveal additional medically relevant information. We suggest that the observed wide range for the lower and upper limits of these frequency numbers will be gradually reduced due to improvement in classification databases and prediction algorithms.
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Affiliation(s)
- Tomasz Gambin
- />Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030 USA
- />Institute of Computer Science, Warsaw University of Technology, Warsaw, 00-665 Poland
| | - Shalini N. Jhangiani
- />The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030 USA
| | - Jennifer E. Below
- />Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Ian M. Campbell
- />Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030 USA
| | - Wojciech Wiszniewski
- />Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030 USA
| | - Donna M. Muzny
- />The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030 USA
| | - Jeffrey Staples
- />Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Alanna C. Morrison
- />Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Matthew N. Bainbridge
- />The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030 USA
| | - Samantha Penney
- />Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030 USA
- />Texas Children’s Hospital, Houston, TX 77030 USA
| | - Amy L. McGuire
- />The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030 USA
- />Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX 77030 USA
| | - Richard A. Gibbs
- />Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030 USA
- />The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030 USA
| | - James R. Lupski
- />Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030 USA
- />Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030 USA
- />Texas Children’s Hospital, Houston, TX 77030 USA
| | - Eric Boerwinkle
- />The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030 USA
- />Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
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138
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Xu L, Tang H, El-Naggar AK, Wei P, Sturgis EM. Genetic variants in DNA double-strand break repair genes and risk of salivary gland carcinoma: a case-control study. PLoS One 2015; 10:e0128753. [PMID: 26035306 PMCID: PMC4452711 DOI: 10.1371/journal.pone.0128753] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Accepted: 05/01/2015] [Indexed: 11/19/2022] Open
Abstract
DNA double strand break (DSB) repair is the primary defense mechanism against ionizing radiation-induced DNA damage. Ionizing radiation is the only established risk factor for salivary gland carcinoma (SGC). We hypothesized that genetic variants in DSB repair genes contribute to individual variation in susceptibility to SGC. To test this hypothesis, we conducted a case-control study in which we analyzed 415 single nucleotide polymorphisms (SNPs) in 45 DSB repair genes in 352 SGC cases and 598 controls. Multivariate logistic regression analysis was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Rs3748522 in RAD52 and rs13180356 in XRCC4 were significantly associated with SGC after Bonferroni adjustment; ORs (95% CIs) for the variant alleles of these SNPs were 1.71 (1.40-2.09, P=1.70 × 10-7) and 0.58 (0.45-0.74, P=2.00 × 10-5) respectively. The genetic effects were modulated by histological subtype. The association of RAD52-rs3748522 with SGC was strongest for mucoepidermoid carcinoma (OR=2.21, 95% CI: 1.55-3.15, P=1.25 × 10-5, n=74), and the association of XRCC4-rs13180356 with SGC was strongest for adenoid cystic carcinoma (OR=0.60, 95% CI: 0.42-0.87, P=6.91 × 10-3, n=123). Gene-level association analysis revealed one gene, PRKDC, with a marginally significant association with SGC risk in non-Hispanic whites. To our knowledge, this study is the first to comprehensively evaluate the genetic effect of DSB repair genes on SGC risk. Our results indicate that genetic variants in the DSB repair pathways contribute to inter-individual differences in susceptibility to SGC and show that the impact of genetic variants differs by histological subtype. Independent studies are warranted to confirm these findings.
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Affiliation(s)
- Li Xu
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Hongwei Tang
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Adel K. El-Naggar
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Peng Wei
- Division of Biostatistics and Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, Texas, United States of America
| | - Erich M. Sturgis
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
- * E-mail:
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139
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Abstract
Next-generation sequencing technology has facilitated the discovery of millions of genetic variants in human genomes. A sizeable fraction of these variants are predicted to be deleterious. Here, we review the pattern of deleterious alleles as ascertained in genome sequencing data sets and ask whether human populations differ in their predicted burden of deleterious alleles - a phenomenon known as mutation load. We discuss three demographic models that are predicted to affect mutation load and relate these models to the evidence (or the lack thereof) for variation in the efficacy of purifying selection in diverse human genomes. We also emphasize why accurate estimation of mutation load depends on assumptions regarding the distribution of dominance and selection coefficients - quantities that remain poorly characterized for current genomic data sets.
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140
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Renaut S, Rieseberg LH. The Accumulation of Deleterious Mutations as a Consequence of Domestication and Improvement in Sunflowers and Other Compositae Crops. Mol Biol Evol 2015; 32:2273-83. [PMID: 25939650 DOI: 10.1093/molbev/msv106] [Citation(s) in RCA: 100] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
For populations to maintain optimal fitness, harmful mutations must be efficiently purged from the genome. Yet, under circumstances that diminish the effectiveness of natural selection, such as the process of plant and animal domestication, deleterious mutations are predicted to accumulate. Here, we compared the load of deleterious mutations in 21 accessions from natural populations and 19 domesticated accessions of the common sunflower using whole-transcriptome single nucleotide polymorphism data. Although we find that genetic diversity has been greatly reduced during domestication, the remaining mutations were disproportionally biased toward nonsynonymous substitutions. Bioinformatically predicted deleterious mutations affecting protein function were especially strongly over-represented. We also identify similar patterns in two other domesticated species of the sunflower family (globe artichoke and cardoon), indicating that this phenomenon is not due to idiosyncrasies of sunflower domestication or the sunflower genome. Finally, we provide unequivocal evidence that deleterious mutations accumulate in low recombining regions of the genome, due to the reduced efficacy of purifying selection. These results represent a conundrum for crop improvement efforts. Although the elimination of harmful mutations should be a long-term goal of plant and animal breeding programs, it will be difficult to weed them out because of limited recombination.
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Affiliation(s)
- Sebastien Renaut
- Biodiversity Research Centre and Department of Botany, University of British Columbia, Vancouver, BC, Canada
| | - Loren H Rieseberg
- Biodiversity Research Centre and Department of Botany, University of British Columbia, Vancouver, BC, Canada Department of Biology, Indiana University - Bloomington
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141
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Peischl S, Excoffier L. Expansion load: recessive mutations and the role of standing genetic variation. Mol Ecol 2015; 24:2084-94. [DOI: 10.1111/mec.13154] [Citation(s) in RCA: 121] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2014] [Revised: 03/11/2015] [Accepted: 03/11/2015] [Indexed: 12/13/2022]
Affiliation(s)
- Stephan Peischl
- Institute of Ecology and Evolution; University of Berne; Berne 3012 Switzerland
- Swiss Institute of Bioinformatics; Lausanne 1015 Switzerland
| | - Laurent Excoffier
- Institute of Ecology and Evolution; University of Berne; Berne 3012 Switzerland
- Swiss Institute of Bioinformatics; Lausanne 1015 Switzerland
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142
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Xu L, Tang H, Chen DW, El-Naggar AK, Wei P, Sturgis EM. Genome-wide association study identifies common genetic variants associated with salivary gland carcinoma and its subtypes. Cancer 2015; 121:2367-74. [PMID: 25823930 DOI: 10.1002/cncr.29381] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Revised: 01/20/2015] [Accepted: 02/09/2015] [Indexed: 01/20/2023]
Abstract
BACKGROUND Salivary gland carcinomas (SGCs) are a rare malignancy with unknown etiology. The objective of the current study was to identify genetic variants modifying the risk of SGC and its major subtypes: adenoid cystic carcinoma and mucoepidermoid carcinoma. METHODS The authors conducted a genome-wide association study in 309 well-defined SGC cases and 535 cancer-free controls. A single-nucleotide polymorphism (SNP)-level discovery study was performed in non-Hispanic white individuals followed by a replication study in Hispanic individuals. A logistic regression analysis was applied to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs). A meta-analysis of the results was conducted. RESULTS A genome-wide significant association with SGC in non-Hispanic white individuals was detected at coding SNPs in CHRNA2 (cholinergic receptor, nicotinic, alpha 2 [neuronal]) (OR, 8.55; 95% CI, 4.53-16.13 [P = 3.6 × 10(-11)]), OR4F15 (olfactory receptor, family 4, subfamily F, member 15) (OR, 5.26; 95% CI, 3.13-8.83 [P = 3.5 × 10(-10)]), ZNF343 (zinc finger protein 343) (OR, 3.28; 95% CI, 2.12-5.07 [P = 9.1 × 10(-8)]), and PARP4 (poly(ADP-ribose) polymerase family, member 4) (OR, 2.00; 95% CI, 1.54-2.59 [P = 1.7 × 10(-7)]). Meta-analysis of the non-Hispanic white and Hispanic cohorts identified another genome-wide significant SNP in ELL2 (meta-OR, 1.86; 95% CI, 1.48-2.34 [P = 1.3 × 10(-7)]). Risk alleles were largely enriched in mucoepidermoid carcinoma, in which the SNPs in CHRNA2, OR4F15, and ZNF343 had ORs of 15.71 (95% CI, 6.59-37.47 [P = 5.2 × 10(-10)]), 15.60 (95% CI, 6.50-37.41 [P = 7.5 × 10(-10)]), and 6.49 (95% CI, 3.36-12.52 [P = 2.5 × 10(-8)]), respectively. None of these SNPs retained a significant association with adenoid cystic carcinoma. CONCLUSIONS To the best of the authors' knowledge, the current study is the first to identify a panel of SNPs associated with the risk of SGC. Confirmation of these findings along with functional analysis of identified SNPs are needed.
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Affiliation(s)
- Li Xu
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Hongwei Tang
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Diane W Chen
- Clincal Research, Quality Improvement, Baylor College of Medicine, Houston, Texas
| | - Adel K El-Naggar
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peng Wei
- Division of Biostatistics and Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, Texas
| | - Erich M Sturgis
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas.,Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
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143
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Osada N, Hettiarachchi N, Adeyemi Babarinde I, Saitou N, Blancher A. Whole-genome sequencing of six Mauritian Cynomolgus macaques (Macaca fascicularis) reveals a genome-wide pattern of polymorphisms under extreme population bottleneck. Genome Biol Evol 2015; 7:821-30. [PMID: 25805843 PMCID: PMC5322541 DOI: 10.1093/gbe/evv033] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Cynomolgus macaques (Macaca fascicularis) were introduced to the island of Mauritius by humans around the 16th century. The unique demographic history of the Mauritian cynomolgus macaques provides the opportunity to not only examine the genetic background of well-established nonhuman primates for biomedical research but also understand the effect of an extreme population bottleneck on the pattern of polymorphisms in genomes. We sequenced the whole genomes of six Mauritian cynomolgus macaques and obtained an average of 20-fold coverage of the genome sequences for each individual. The overall level of nucleotide diversity was 23% smaller than that of the Malaysian cynomolgus macaques, and a reduction of low-frequency polymorphisms was observed. In addition, we also confirmed that the Mauritian cynomolgus macaques were genetically closer to a representative of the Malaysian population than to a representative of the Indochinese population. Excess of nonsynonymous polymorphisms in low frequency, which has been observed in many other species, was not very strong in the Mauritian samples, and the proportion of heterozygous nonsynonymous polymorphisms relative to synonymous polymorphisms is higher within individuals in Mauritian than Malaysian cynomolgus macaques. Those patterns indicate that the extreme population bottleneck made purifying selection overwhelmed by the power of genetic drift in the population. Finally, we estimated the number of founding individuals by using the genome-wide site frequency spectrum of the six samples. Assuming a simple demographic scenario with a single bottleneck followed by exponential growth, the estimated number of founders (∼20 individuals) is largely consistent with previous estimates.
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Affiliation(s)
- Naoki Osada
- Division of Evolutionary Genetics, National Institute of Genetics, Mishima, Japan Department of Genetics, SOKENDAI (The Graduate University for Advanced Studies), Mishima, Japan
| | - Nilmini Hettiarachchi
- Department of Genetics, SOKENDAI (The Graduate University for Advanced Studies), Mishima, Japan Division of Population Genetics, National Institute of Genetics, Mishima, Japan
| | - Isaac Adeyemi Babarinde
- Department of Genetics, SOKENDAI (The Graduate University for Advanced Studies), Mishima, Japan Division of Population Genetics, National Institute of Genetics, Mishima, Japan
| | - Naruya Saitou
- Department of Genetics, SOKENDAI (The Graduate University for Advanced Studies), Mishima, Japan Division of Population Genetics, National Institute of Genetics, Mishima, Japan
| | - Antoine Blancher
- Laboratoire d'Immunogénétique Moléculaire (LIMT, EA3034), Faculté de Médecine Purpan, Université Paul Sabatier, Toulouse III, France
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144
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Fu W, Gittelman RM, Bamshad MJ, Akey JM. Characteristics of neutral and deleterious protein-coding variation among individuals and populations. Am J Hum Genet 2014; 95:421-36. [PMID: 25279984 PMCID: PMC4185119 DOI: 10.1016/j.ajhg.2014.09.006] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2014] [Accepted: 09/11/2014] [Indexed: 01/27/2023] Open
Abstract
Whole-genome and exome data sets continue to be produced at a frenetic pace, resulting in massively large catalogs of human genomic variation. However, a clear picture of the characteristics and patterns of neutral and deleterious variation within and between populations has yet to emerge, given that recent large-scale sequencing studies have often emphasized different aspects of the data and sometimes appear to have conflicting conclusions. Here, we comprehensively studied characteristics of protein-coding variation in high-coverage exome sequence data from 6,515 European American (EA) and African American (AA) individuals. We developed an unbiased approach to identify putatively deleterious variants and investigated patterns of neutral and deleterious single-nucleotide variants and alleles between individuals and populations. We show that there are substantial differences in the composition of genotypes between EA and AA populations and that small but statistically significant differences exist in the average number of deleterious alleles carried by EA and AA individuals. Furthermore, we performed extensive simulations to delineate the temporal dynamics of deleterious alleles for a broad range of demographic models and use these data to inform the interpretation of empirical patterns of deleterious variation. Finally, we illustrate that the effects of demographic perturbations, such as bottlenecks and expansions, often manifest in opposing patterns of neutral and deleterious variation depending on whether the focus is on populations or individuals. Our results clarify seemingly disparate empirical characteristics of protein-coding variation and provide substantial insights into how natural selection and demographic history have patterned neutral and deleterious variation within and between populations.
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Affiliation(s)
- Wenqing Fu
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Rachel M Gittelman
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Michael J Bamshad
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Department of Pediatrics, University of Washington, Seattle, WA 98195, USA
| | - Joshua M Akey
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
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