1
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Taylor CS, Lawson DJ. Heritability of complex traits in sub-populations experiencing bottlenecks and growth. J Hum Genet 2024; 69:329-335. [PMID: 38589509 PMCID: PMC11199143 DOI: 10.1038/s10038-024-01249-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 03/20/2024] [Accepted: 03/23/2024] [Indexed: 04/10/2024]
Abstract
Populations that have experienced a bottleneck are regularly used in Genome Wide Association Studies (GWAS) to investigate variants associated with complex traits. It is generally understood that these isolated sub-populations may experience high frequency of otherwise rare variants with large effect size, and therefore provide a unique opportunity to study said trait. However, the demographic history of the population under investigation affects all SNPs that determine the complex trait genome-wide, changing its heritability and genetic architecture. We use a simulation based approach to identify the impact of the demographic processes of drift, expansion, and migration on the heritability of complex trait. We show that demography has considerable impact on complex traits. We then investigate the power to resolve heritability of complex traits in GWAS studies subjected to demographic effects. We find that demography is an important component for interpreting inference of complex traits and has a nuanced impact on the power of GWAS. We conclude that demographic histories need to be explicitly modelled to properly quantify the history of selection on a complex trait.
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Affiliation(s)
| | - Daniel J Lawson
- School of Mathematics, University of Bristol, Bristol, UK.
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK.
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2
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Janivara R, Hazra U, Pfennig A, Harlemon M, Kim MS, Eaaswarkhanth M, Chen WC, Ogunbiyi A, Kachambwa P, Petersen LN, Jalloh M, Mensah JE, Adjei AA, Adusei B, Joffe M, Gueye SM, Aisuodionoe-Shadrach OI, Fernandez PW, Rohan TE, Andrews C, Rebbeck TR, Adebiyi AO, Agalliu I, Lachance J. Uncovering the genetic architecture and evolutionary roots of androgenetic alopecia in African men. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.12.575396. [PMID: 38293167 PMCID: PMC10827056 DOI: 10.1101/2024.01.12.575396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Androgenetic alopecia is a highly heritable trait. However, much of our understanding about the genetics of male pattern baldness comes from individuals of European descent. Here, we examined a novel dataset comprising 2,136 men from Ghana, Nigeria, Senegal, and South Africa that were genotyped using a custom array. We first tested how genetic predictions of baldness generalize from Europe to Africa, finding that polygenic scores from European GWAS yielded AUC statistics that ranged from 0.513 to 0.546, indicating that genetic predictions of baldness in African populations performed notably worse than in European populations. Subsequently, we conducted the first African GWAS of androgenetic alopecia, focusing on self-reported baldness patterns at age 45. After correcting for present age, population structure, and study site, we identified 266 moderately significant associations, 51 of which were independent (p-value < 10-5, r2 < 0.2). Most baldness associations were autosomal, and the X chromosomes does not appear to have a large impact on baldness in African men. Finally, we examined the evolutionary causes of continental differences in genetic architecture. Although Neanderthal alleles have previously been associated with skin and hair phenotypes, we did not find evidence that European-ascertained baldness hits were enriched for signatures of ancient introgression. Most loci that are associated with androgenetic alopecia are evolving neutrally. However, multiple baldness-associated SNPs near the EDA2R and AR genes have large allele frequency differences between continents. Collectively, our findings illustrate how evolutionary history contributes to the limited portability of genetic predictions across ancestries.
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Affiliation(s)
- Rohini Janivara
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Ujani Hazra
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Aaron Pfennig
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Maxine Harlemon
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
- Department of Biology, Morgan State University, Baltimore, Maryland, USA
| | - Michelle S Kim
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
- Department of Human Genetics University of Michigan, Ann Arbor, Michigan, USA
| | | | - Wenlong C Chen
- Strengthening Oncology Services Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- National Cancer Registry, National Institute for Communicable Diseases a Division of the National Health Laboratory Service, Johannesburg, South Africa
| | | | - Paidamoyo Kachambwa
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
- Mediclinic Precise Southern Africa, Cape Town, South Africa
| | - Lindsay N Petersen
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
- Mediclinic Precise Southern Africa, Cape Town, South Africa
| | - Mohamed Jalloh
- Université Cheikh Anta Diop de Dakar, Dakar, Senegal
- Université Iba Der Thiam de Thiès, Thiès, Senegal
| | - James E Mensah
- Korle-Bu Teaching Hospital and University of Ghana Medical School, Accra, Ghana
| | - Andrew A Adjei
- Department of Pathology, University of Ghana Medical School, Accra, Ghana
| | | | - Maureen Joffe
- Strengthening Oncology Services Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Oseremen I Aisuodionoe-Shadrach
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Centre, Abuja, Nigeria
| | - Pedro W Fernandez
- Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Thomas E Rohan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | | | - Timothy R Rebbeck
- Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | | | - Ilir Agalliu
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
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3
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McClellan JM, Zoghbi AW, Buxbaum JD, Cappi C, Crowley JJ, Flint J, Grice DE, Gulsuner S, Iyegbe C, Jain S, Kuo PH, Lattig MC, Passos-Bueno MR, Purushottam M, Stein DJ, Sunshine AB, Susser ES, Walsh CA, Wootton O, King MC. An evolutionary perspective on complex neuropsychiatric disease. Neuron 2024; 112:7-24. [PMID: 38016473 PMCID: PMC10842497 DOI: 10.1016/j.neuron.2023.10.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 08/09/2023] [Accepted: 10/26/2023] [Indexed: 11/30/2023]
Abstract
The forces of evolution-mutation, selection, migration, and genetic drift-shape the genetic architecture of human traits, including the genetic architecture of complex neuropsychiatric illnesses. Studying these illnesses in populations that are diverse in genetic ancestry, historical demography, and cultural history can reveal how evolutionary forces have guided adaptation over time and place. A fundamental truth of shared human biology is that an allele responsible for a disease in anyone, anywhere, reveals a gene critical to the normal biology underlying that condition in everyone, everywhere. Understanding the genetic causes of neuropsychiatric disease in the widest possible range of human populations thus yields the greatest possible range of insight into genes critical to human brain development. In this perspective, we explore some of the relationships between genes, adaptation, and history that can be illuminated by an evolutionary perspective on studies of complex neuropsychiatric disease in diverse populations.
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Affiliation(s)
- Jon M McClellan
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA
| | - Anthony W Zoghbi
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - Joseph D Buxbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Carolina Cappi
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - James J Crowley
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jonathan Flint
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Dorothy E Grice
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Suleyman Gulsuner
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Conrad Iyegbe
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sanjeev Jain
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru 560029, India
| | - Po-Hsiu Kuo
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100, Taiwan
| | | | | | - Meera Purushottam
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru 560029, India
| | - Dan J Stein
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Anna B Sunshine
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA; Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Ezra S Susser
- Department of Epidemiology, Mailman School of Public Health, and New York State Psychiatric Institute, Columbia University, New York, NY 10032, USA
| | - Christopher A Walsh
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Genetics and Genomics and Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA; Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Olivia Wootton
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Mary-Claire King
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
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4
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Rougemont Q, Leroy T, Rondeau EB, Koop B, Bernatchez L. Allele surfing causes maladaptation in a Pacific salmon of conservation concern. PLoS Genet 2023; 19:e1010918. [PMID: 37683018 PMCID: PMC10545117 DOI: 10.1371/journal.pgen.1010918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 10/02/2023] [Accepted: 08/11/2023] [Indexed: 09/10/2023] Open
Abstract
How various factors, including demography, recombination or genome duplication, may impact the efficacy of natural selection and the burden of deleterious mutations, is a central question in evolutionary biology and genetics. In this study, we show that key evolutionary processes, including variations in i) effective population size (Ne) ii) recombination rates and iii) chromosome inheritance, have influenced the genetic load and efficacy of selection in Coho salmon (Oncorhynchus kisutch), a widely distributed salmonid species on the west coast of North America. Using whole genome resequencing data from 14 populations at different migratory distances from their southern glacial refugium, we found evidence supporting gene surfing, wherein reduced Ne at the postglacial recolonization front, leads to a decrease in the efficacy of selection and a surf of deleterious alleles in the northernmost populations. Furthermore, our results indicate that recombination rates play a prime role in shaping the load along the genome. Additionally, we identified variation in polyploidy as a contributing factor to within-genome variation of the load. Overall, our results align remarkably well with expectations under the nearly neutral theory of molecular evolution. We discuss the fundamental and applied implications of these findings for evolutionary and conservation genomics.
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Affiliation(s)
- Quentin Rougemont
- Centre d’Ecologie Fonctionnelle et Evolutive, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Thibault Leroy
- GenPhySE, INRAE, INP, ENVT, Université de Toulouse, Auzeville- Tolosane, France
| | - Eric B. Rondeau
- Department of Fisheries and Ocean, Pacific Biological Station, Nanaimo, Canada
| | - Ben Koop
- Department of Biology, University of Victoria, Victoria, Canada
| | - Louis Bernatchez
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Canada
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5
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Robinson J, Kyriazis CC, Yuan SC, Lohmueller KE. Deleterious Variation in Natural Populations and Implications for Conservation Genetics. Annu Rev Anim Biosci 2023; 11:93-114. [PMID: 36332644 PMCID: PMC9933137 DOI: 10.1146/annurev-animal-080522-093311] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Deleterious mutations decrease reproductive fitness and are ubiquitous in genomes. Given that many organisms face ongoing threats of extinction, there is interest in elucidating the impact of deleterious variation on extinction risk and optimizing management strategies accounting for such mutations. Quantifying deleterious variation and understanding the effects of population history on deleterious variation are complex endeavors because we do not know the strength of selection acting on each mutation. Further, the effect of demographic history on deleterious mutations depends on the strength of selection against the mutation and the degree of dominance. Here we clarify how deleterious variation can be quantified and studied in natural populations. We then discuss how different demographic factors, such as small population size, nonequilibrium population size changes, inbreeding, and gene flow, affect deleterious variation. Lastly, we provide guidance on studying deleterious variation in nonmodel populations of conservation concern.
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Affiliation(s)
- Jacqueline Robinson
- Institute for Human Genetics, University of California, San Francisco, California, USA;
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , ,
| | - Stella C Yuan
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , ,
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , , .,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, USA
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6
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Schlichta F, Moinet A, Peischl S, Excoffier L. The Impact of Genetic Surfing on Neutral Genomic Diversity. Mol Biol Evol 2022; 39:msac249. [PMID: 36403964 PMCID: PMC9703594 DOI: 10.1093/molbev/msac249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Range expansions have been common in the history of most species. Serial founder effects and subsequent population growth at expansion fronts typically lead to a loss of genomic diversity along the expansion axis. A frequent consequence is the phenomenon of "gene surfing," where variants located near the expanding front can reach high frequencies or even fix in newly colonized territories. Although gene surfing events have been characterized thoroughly for a specific locus, their effects on linked genomic regions and the overall patterns of genomic diversity have been little investigated. In this study, we simulated the evolution of whole genomes during several types of 1D and 2D range expansions differing by the extent of migration, founder events, and recombination rates. We focused on the characterization of local dips of diversity, or "troughs," taken as a proxy for surfing events. We find that, for a given recombination rate, once we consider the amount of diversity lost since the beginning of the expansion, it is possible to predict the initial evolution of trough density and their average width irrespective of the expansion condition. Furthermore, when recombination rates vary across the genome, we find that troughs are over-represented in regions of low recombination. Therefore, range expansions can leave local and global genomic signatures often interpreted as evidence of past selective events. Given the generality of our results, they could be used as a null model for species having gone through recent expansions, and thus be helpful to correctly interpret many evolutionary biology studies.
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Affiliation(s)
- Flávia Schlichta
- Computational and Molecular Population Genetics lab, Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Antoine Moinet
- Computational and Molecular Population Genetics lab, Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Interfaculty Bioinformatics Unit, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland
| | - Stephan Peischl
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Interfaculty Bioinformatics Unit, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland
| | - Laurent Excoffier
- Computational and Molecular Population Genetics lab, Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
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7
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Burny C, Nolte V, Dolezal M, Schlötterer C. Genome-wide selection signatures reveal widespread synergistic effects of two different stressors in Drosophila melanogaster. Proc Biol Sci 2022; 289:20221857. [PMID: 36259211 PMCID: PMC9579754 DOI: 10.1098/rspb.2022.1857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Experimental evolution combined with whole-genome sequencing (evolve and resequence (E&R)) is a powerful approach to study the adaptive architecture of selected traits. Nevertheless, so far the focus has been on the selective response triggered by a single stressor. Building on the highly parallel selection response of founder populations with reduced variation, we evaluated how the presence of a second stressor affects the genomic selection response. After 20 generations of adaptation to laboratory conditions at either 18°C or 29°C, strong genome-wide selection signatures were observed. Only 38% of the selection signatures can be attributed to laboratory adaptation (no difference between temperature regimes). The remaining selection responses are either caused by temperature-specific effects, or reflect the joint effects of temperature and laboratory adaptation (same direction, but the magnitude differs between temperatures). The allele frequency changes resulting from the combined effects of temperature and laboratory adaptation were more extreme in the hot environment for 83% of the affected genomic regions-indicating widespread synergistic effects of the two stressors. We conclude that E&R with reduced genetic variation is a powerful approach to study genome-wide fitness consequences driven by the combined effects of multiple environmental factors.
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Affiliation(s)
- Claire Burny
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Vienna 1210, Austria.,Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna 1210, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Vienna 1210, Austria
| | - Marlies Dolezal
- Plattform Bioinformatik und Biostatistik, Vetmeduni Vienna, Vienna 1210, Austria
| | - Christian Schlötterer
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Vienna 1210, Austria
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8
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Evidence for continent-wide convergent evolution and stasis throughout 150 y of a biological invasion. Proc Natl Acad Sci U S A 2022; 119:e2107584119. [PMID: 35476511 PMCID: PMC9170017 DOI: 10.1073/pnas.2107584119] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Adaptive evolution can help species to persist and spread in new environments, but it is unclear how the rate and duration of adaptive evolution vary throughout species ranges and on the decadal timescales most relevant to managing biodiversity for the 21st century. Using herbarium records, we reconstruct 150 y of evolution in an invasive plant as it spread across North America. Flowering phenology evolves to adapt to local growing seasons throughout the range but stalls after about a century. This punctuated, convergent evolution recapitulates long-term dynamics in the fossil record, implicating limits to evolutionary rates that are not evident for the first century of spread. The extent to which evolution can rescue a species from extinction, or facilitate range expansion, depends critically on the rate, duration, and geographical extent of the evolutionary response to natural selection. Adaptive evolution can occur quickly, but the duration and geographical extent of contemporary evolution in natural systems remain poorly studied. This is particularly true for species with large geographical ranges and for timescales that lie between “long-term” field experiments and the fossil record. Here, we introduce the Virtual Common Garden (VCG) to investigate phenotypic evolution in natural history collections while controlling for phenotypic plasticity in response to local growing conditions. Reconstructing 150 y of evolution in Lythrum salicaria (purple loosestrife) as it invaded North America, we analyze phenology measurements of 3,429 herbarium records, reconstruct growing conditions from more than 12 million local temperature records, and validate predictions across three common gardens spanning 10° of latitude. We find that phenological clines have evolved repeatedly throughout the range, during the first century of evolution. Thereafter, the rate of microevolution stalls, recapitulating macroevolutionary stasis observed in the fossil record. Our study demonstrates that preserved specimens are a critical resource for investigating limits to evolution in natural populations. Our results show how natural selection and trade-offs measured in field studies predict adaptive divergence observable in herbarium specimens over 15 decades at a continental scale.
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9
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Vecchyo DOD, Lohmueller KE, Novembre J. Haplotype-based inference of the distribution of fitness effects. Genetics 2022; 220:6501446. [PMID: 35100400 PMCID: PMC8982047 DOI: 10.1093/genetics/iyac002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 12/18/2021] [Indexed: 11/13/2022] Open
Abstract
Abstract
Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.
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Affiliation(s)
- Diego Ortega-Del Vecchyo
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, 76230, México
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
| | - Kirk E Lohmueller
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, Illinois, 60637, United States of America
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, 60637, United States of America
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10
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Hayward LK, Sella G. Polygenic adaptation after a sudden change in environment. eLife 2022; 11:66697. [PMID: 36155653 PMCID: PMC9683794 DOI: 10.7554/elife.66697] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 07/18/2022] [Indexed: 11/13/2022] Open
Abstract
Polygenic adaptation is thought to be ubiquitous, yet remains poorly understood. Here, we model this process analytically, in the plausible setting of a highly polygenic, quantitative trait that experiences a sudden shift in the fitness optimum. We show how the mean phenotype changes over time, depending on the effect sizes of loci that contribute to variance in the trait, and characterize the allele dynamics at these loci. Notably, we describe the two phases of the allele dynamics: The first is a rapid phase, in which directional selection introduces small frequency differences between alleles whose effects are aligned with or opposed to the shift, ultimately leading to small differences in their probability of fixation during a second, longer phase, governed by stabilizing selection. As we discuss, key results should hold in more general settings and have important implications for efforts to identify the genetic basis of adaptation in humans and other species.
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Affiliation(s)
- Laura Katharine Hayward
- Department of Mathematics, Columbia UniversityNew YorkUnited States,Institute of Science and TechnologyMaria GuggingAustria
| | - Guy Sella
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States,Program for Mathematical Genomics, Columbia UniversityNew YorkUnited States
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11
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Sohail M, Izarraras-Gomez A, Ortega-Del Vecchyo D. Populations, Traits, and Their Spatial Structure in Humans. Genome Biol Evol 2021; 13:evab272. [PMID: 34894236 PMCID: PMC8715524 DOI: 10.1093/gbe/evab272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/06/2021] [Indexed: 11/16/2022] Open
Abstract
The spatial distribution of genetic variants is jointly determined by geography, past demographic processes, natural selection, and its interplay with environmental variation. A fraction of these genetic variants are "causal alleles" that affect the manifestation of a complex trait. The effect exerted by these causal alleles on complex traits can be independent or dependent on the environment. Understanding the evolutionary processes that shape the spatial structure of causal alleles is key to comprehend the spatial distribution of complex traits. Natural selection, past population size changes, range expansions, consanguinity, assortative mating, archaic introgression, admixture, and the environment can alter the frequencies, effect sizes, and heterozygosities of causal alleles. This provides a genetic axis along which complex traits can vary. However, complex traits also vary along biogeographical and sociocultural axes which are often correlated with genetic axes in complex ways. The purpose of this review is to consider these genetic and environmental axes in concert and examine the ways they can help us decipher the variation in complex traits that is visible in humans today. This initiative necessarily implies a discussion of populations, traits, the ability to infer and interpret "genetic" components of complex traits, and how these have been impacted by adaptive events. In this review, we provide a history-aware discussion on these topics using both the recent and more distant past of our academic discipline and its relevant contexts.
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Affiliation(s)
- Mashaal Sohail
- Department of Human Genetics, University of Chicago, USA
- Centro de Ciencias Genómicas (CCG), Universidad Nacional Autónoma de México (UNAM), Cuernavaca, Morelos, México
| | - Alan Izarraras-Gomez
- Laboratorio Internacional de Investigación sobre el Genoma Humano (LIIGH), Universidad Nacional Autónoma de México (UNAM), Juriquilla, Querétaro, México
| | - Diego Ortega-Del Vecchyo
- Laboratorio Internacional de Investigación sobre el Genoma Humano (LIIGH), Universidad Nacional Autónoma de México (UNAM), Juriquilla, Querétaro, México
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12
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Li SH, Liu Y, Yeh CF, Fu Y, Yeung CKL, Lee CC, Chiu CC, Kuo TH, Chan FT, Chen YC, Ko WY, Yao CT. Not out of the woods yet: Signatures of the prolonged negative genetic consequences of a population bottleneck in a rapidly re-expanding wader, the black-faced spoonbill Platalea minor. Mol Ecol 2021; 31:529-545. [PMID: 34726290 DOI: 10.1111/mec.16260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 09/27/2021] [Accepted: 10/20/2021] [Indexed: 11/30/2022]
Abstract
The long-term persistence of a population which has suffered a bottleneck partly depends on how historical demographic dynamics impacted its genetic diversity and the accumulation of deleterious mutations. Here we provide genomic evidence for the genetic effect of a recent population bottleneck in the endangered black-faced spoonbill (Platalea minor) after its rapid population recovery. Our data suggest that the bird's effective population size, Ne , had been relatively stable (7500-9000) since 22,000 years ago; however, a recent brief yet severe bottleneck (Ne = 20) which we here estimated to occur around the 1940s wiped out >99% of its historical Ne in roughly three generations. Despite a >15-fold population recovery since 1988, we found that black-faced spoonbill population has higher levels of inbreeding (7.4 times more runs of homozygosity) than its sister species, the royal spoonbill (P. regia), which is not thought to have undergone a marked population contraction. Although the two spoonbills have similar levels of genome-wide genetic diversity, our results suggest that selection on more genes was relaxed in the black-faced spoonbill; moreover individual black-faced spoonbills carry more putatively deleterious mutations (Grantham's score > 50), and may therefore express more deleterious phenotypic effects than royal spoonbills. Here we demonstrate the value of using genomic indices to monitor levels of genetic erosion, inbreeding and mutation load in species with conservation concerns. To mitigate the prolonged negative genetic effect of a population bottleneck, we recommend that all possible measures should be employed to maintain population growth of a threatened species.
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Affiliation(s)
- Shou-Hsien Li
- School of Life Science, National Taiwan Normal University, Taipei, Taiwan
| | - Yang Liu
- State Key Laboratory of Biocontrol, School of Ecology, Sun Yat-Sen University, Guangzhou, China
| | - Chia-Fen Yeh
- School of Life Science, National Taiwan Normal University, Taipei, Taiwan
| | - Yuchen Fu
- School of Life Science, National Taiwan Normal University, Taipei, Taiwan
| | | | - Chun-Cheng Lee
- School of Life Science, National Taiwan Normal University, Taipei, Taiwan
| | - Chi-Cheng Chiu
- School of Life Science, National Taiwan Normal University, Taipei, Taiwan
| | | | - Fang-Tse Chan
- Division of Zoology, Taiwan Endemic Species Research Institute, Nantou, Taiwan
| | - Yu-Chia Chen
- Department of Life Sciences, National Yanming Medical University, Taipei, Taiwan
| | - Wen-Ya Ko
- Department of Life Sciences, National Yanming Medical University, Taipei, Taiwan
| | - Cheng-Te Yao
- High Altitude Research Station, Taiwan Endemic Species Research Institute, Nantou, Taiwan
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13
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Chiang CWK. The Opportunities and Challenges of Integrating Population Histories Into Genetic Studies for Diverse Populations: A Motivating Example From Native Hawaiians. Front Genet 2021; 12:643883. [PMID: 34646295 PMCID: PMC8503554 DOI: 10.3389/fgene.2021.643883] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 08/19/2021] [Indexed: 11/25/2022] Open
Abstract
There is a well-recognized need to include diverse populations in genetic studies, but several obstacles continue to be prohibitive, including (but are not limited to) the difficulty of recruiting individuals from diverse populations in large numbers and the lack of representation in available genomic references. These obstacles notwithstanding, studying multiple diverse populations would provide informative, population-specific insights. Using Native Hawaiians as an example of an understudied population with a unique evolutionary history, I will argue that by developing key genomic resources and integrating evolutionary thinking into genetic epidemiology, we will have the opportunity to efficiently advance our knowledge of the genetic risk factors, ameliorate health disparity, and improve healthcare in this underserved population.
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Affiliation(s)
- Charleston W K Chiang
- Department of Population and Public Health Sciences, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.,Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, United States
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14
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Ochoa A, Gibbs HL. Genomic signatures of inbreeding and mutation load in a threatened rattlesnake. Mol Ecol 2021; 30:5454-5469. [PMID: 34448259 DOI: 10.1111/mec.16147] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 08/04/2021] [Accepted: 08/16/2021] [Indexed: 11/28/2022]
Abstract
Theory predicts that threatened species living in small populations will experience high levels of inbreeding that will increase their genetic load, but recent work suggests that the impact of load may be minimized by purging resulting from long-term population bottlenecks. Empirical studies that examine this idea using genome-wide estimates of inbreeding and genetic load in threatened species are limited. Here we use individual genome resequencing data to compare levels of inbreeding, levels of genetic load (estimated as mutation load) and population history in threatened Eastern massasauga rattlesnakes (Sistrurus catenatus), which exist in small isolated populations, and closely related yet outbred Western massasauga rattlesnakes (Sistrurus tergeminus). In terms of inbreeding, S. catenatus genomes had a greater number of runs of homozygosity of varying sizes, indicating sustained inbreeding through repeated bottlenecks when compared to S. tergeminus. At the species level, outbred S. tergeminus had higher genome-wide levels of mutation load in the form of greater numbers of derived deleterious mutations compared to S. catenatus, presumably due to long-term purging of deleterious mutations in S. catenatus. In contrast, mutations that escaped species-level drift effects within S. catenatus populations were in general more frequent and more often found in homozygous genotypes than in S. tergeminus, suggesting a reduced efficiency of purifying selection in smaller S. catenatus populations for most mutations. Our results support an emerging idea that the historical demography of a threatened species has a significant impact on the type of genetic load present, which impacts implementation of conservation actions such as genetic rescue.
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Affiliation(s)
- Alexander Ochoa
- Department of Evolution, Ecology, and Organismal Biology, Ohio Biodiversity Conservation Partnership, Ohio State University, Columbus, Ohio, USA
| | - H Lisle Gibbs
- Department of Evolution, Ecology, and Organismal Biology, Ohio Biodiversity Conservation Partnership, Ohio State University, Columbus, Ohio, USA
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15
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Foote AD, Hooper R, Alexander A, Baird RW, Baker CS, Ballance L, Barlow J, Brownlow A, Collins T, Constantine R, Dalla Rosa L, Davison NJ, Durban JW, Esteban R, Excoffier L, Martin SLF, Forney KA, Gerrodette T, Gilbert MTP, Guinet C, Hanson MB, Li S, Martin MD, Robertson KM, Samarra FIP, de Stephanis R, Tavares SB, Tixier P, Totterdell JA, Wade P, Wolf JBW, Fan G, Zhang Y, Morin PA. Runs of homozygosity in killer whale genomes provide a global record of demographic histories. Mol Ecol 2021; 30:6162-6177. [PMID: 34416064 DOI: 10.1111/mec.16137] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 08/10/2021] [Accepted: 08/18/2021] [Indexed: 02/06/2023]
Abstract
Runs of homozygosity (ROH) occur when offspring inherit haplotypes that are identical by descent from each parent. Length distributions of ROH are informative about population history; specifically, the probability of inbreeding mediated by mating system and/or population demography. Here, we investigated whether variation in killer whale (Orcinus orca) demographic history is reflected in genome-wide heterozygosity and ROH length distributions, using a global data set of 26 genomes representative of geographic and ecotypic variation in this species, and two F1 admixed individuals with Pacific-Atlantic parentage. We first reconstructed demographic history for each population as changes in effective population size through time using the pairwise sequential Markovian coalescent (PSMC) method. We found a subset of populations declined in effective population size during the Late Pleistocene, while others had more stable demography. Genomes inferred to have undergone ancestral declines in effective population size, were autozygous at hundreds of short ROH (<1 Mb), reflecting high background relatedness due to coalescence of haplotypes deep within the pedigree. In contrast, longer and therefore younger ROH (>1.5 Mb) were found in low latitude populations, and populations of known conservation concern. These include a Scottish killer whale, for which 37.8% of the autosomes were comprised of ROH >1.5 Mb in length. The fate of this population, in which only two adult males have been sighted in the past five years, and zero fecundity over the last two decades, may be inextricably linked to its demographic history and consequential inbreeding depression.
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Affiliation(s)
- Andrew D Foote
- Department of Natural History, NTNU University Museum, Norwegian University of Science and Technology (NTNU, Trondheim, Norway.,Molecular Ecology and Fisheries Genetics Laboratory, School of Biological Sciences, Bangor University, Bangor, Gwynedd, UK.,CMPG, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland
| | - Rebecca Hooper
- University of Exeter, Penryn Campus, Penryn, Cornwall, UK
| | - Alana Alexander
- Department of Anatomy, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | | | - Charles Scott Baker
- Marine Mammal Institute, Oregon State University, Newport, Oregon, USA.,School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | - Lisa Ballance
- Marine Mammal Institute, Oregon State University, Newport, Oregon, USA.,Marine Mammal and Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, La Jolla, California, USA
| | - Jay Barlow
- Marine Mammal and Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, La Jolla, California, USA
| | - Andrew Brownlow
- Scottish Marine Animal Stranding Scheme, Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK
| | - Tim Collins
- Ocean Giants Program, Wildlife Conservation Society, New York City, New York
| | | | - Luciano Dalla Rosa
- Laboratório de Ecologia e Conservação da Megafauna Marinha, Instituto de Oceanografia, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Nicholas J Davison
- Scottish Marine Animal Stranding Scheme, Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK
| | - John W Durban
- Marine Mammal Institute, Oregon State University, Newport, Oregon, USA.,Marine Mammal and Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, La Jolla, California, USA
| | - Ruth Esteban
- CIRCE, Conservation, Information and Research on Cetaceans, Algeciras, Spain
| | - Laurent Excoffier
- CMPG, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland
| | - Sarah L Fordyce Martin
- Department of Natural History, NTNU University Museum, Norwegian University of Science and Technology (NTNU, Trondheim, Norway
| | - Karin A Forney
- Marine Mammal and Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Moss Landing, California, USA.,Moss Landing Marine Laboratories, San Jose State University, Moss Landing, California, USA
| | - Tim Gerrodette
- Marine Mammal and Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, La Jolla, California, USA
| | - M Thomas P Gilbert
- Department of Natural History, NTNU University Museum, Norwegian University of Science and Technology (NTNU, Trondheim, Norway.,Section for Evolutionary Genomics, The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Christophe Guinet
- UMR 7372 La Rochelle Université - CNRS, Centre d'Etudes Biologiques de Chizé (CEBC), Villiers-en-Bois, France
| | - M Bradley Hanson
- National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, Seattle, Washington, USA
| | - Songhai Li
- Marine Mammal and Marine Bioacoustics Laboratory, Institute of Deep-Sea Science and Engineering, Chinese Academy of Science, Sanya, China
| | - Michael D Martin
- Department of Natural History, NTNU University Museum, Norwegian University of Science and Technology (NTNU, Trondheim, Norway
| | - Kelly M Robertson
- Marine Mammal and Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, La Jolla, California, USA
| | - Filipa I P Samarra
- University of Iceland's Institute of Research Centres, Vestmannaeyjar, Iceland
| | - Renaud de Stephanis
- CIRCE, Conservation, Information and Research on Cetaceans, Algeciras, Spain
| | - Sara B Tavares
- Scottish Oceans Institute, East Sands, University of St. Andrews, St. Andrews, UK.,Cetacean Research Program, Pacific Biological Station, Fisheries and Oceans Canada, Nanaimo, Canada
| | - Paul Tixier
- UMR 7372 La Rochelle Université - CNRS, Centre d'Etudes Biologiques de Chizé (CEBC), Villiers-en-Bois, France.,MARBEC Université de Montpellier-CNRS-IFREMER-IRD, Sète, France
| | | | - Paul Wade
- National Marine Mammal Laboratory, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Alaska Fisheries Science Center, Seattle, Washington, USA
| | - Jochen B W Wolf
- Section of Evolutionary Biology, Department of Biology II, Ludwig Maximilian University of Munich, Planegg-Martinsried, Germany
| | - Guangyi Fan
- BGI-Qingdao, BGI-Shenzhen, Qingdao, China.,BGI-Shenzhen, Shenzhen, China.,China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Yaolei Zhang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, China.,Translational Immunology group, Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Phillip A Morin
- Marine Mammal and Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, La Jolla, California, USA
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16
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Otte KA, Nolte V, Mallard F, Schlötterer C. The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime. Genome Biol 2021; 22:211. [PMID: 34271951 PMCID: PMC8285869 DOI: 10.1186/s13059-021-02425-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 06/29/2021] [Indexed: 12/28/2022] Open
Abstract
Background Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates. Results Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime. Conclusions These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-021-02425-9.
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Affiliation(s)
- Kathrin A Otte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Present address: Institute for Zoology, University of Cologne, Cologne, Germany
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - François Mallard
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Present address: Institut de Biologie de l'École Normale Supérieure, CNRS UMR 8197, Inserm U1024, PSL Research University, F-75005, Paris, France
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17
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Abstract
Severe neuropsychiatric disorders are so genetically heterogeneous that virtually every unrelated patient harbors different clinically significant alleles. By studying schizophrenia in the Ashkenazi Jewish founder population, Lencz and co-authors identified rare severe alleles each shared by a few patients. Experimental evaluation of an implicated protocadherin allele revealed failure to form homophilic cellular aggregates as a possible mechanism for defective development of neural circuits.
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Affiliation(s)
- Jon M McClellan
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Mary-Claire King
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA, USA.
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18
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Takou M, Hämälä T, Koch EM, Steige KA, Dittberner H, Yant L, Genete M, Sunyaev S, Castric V, Vekemans X, Savolainen O, de Meaux J. Maintenance of Adaptive Dynamics and No Detectable Load in a Range-Edge Outcrossing Plant Population. Mol Biol Evol 2021; 38:1820-1836. [PMID: 33480994 PMCID: PMC8097302 DOI: 10.1093/molbev/msaa322] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
During range expansion, edge populations are expected to face increased genetic drift, which in turn can alter and potentially compromise adaptive dynamics, preventing the removal of deleterious mutations and slowing down adaptation. Here, we contrast populations of the European subspecies Arabidopsis lyrata ssp. petraea, which expanded its Northern range after the last glaciation. We document a sharp decline in effective population size in the range-edge population and observe that nonsynonymous variants segregate at higher frequencies. We detect a 4.9% excess of derived nonsynonymous variants per individual in the range-edge population, suggesting an increase of the genomic burden of deleterious mutations. Inference of the fitness effects of mutations and modeling of allele frequencies under the explicit demographic history of each population predicts a depletion of rare deleterious variants in the range-edge population, but an enrichment for fixed ones, consistent with the bottleneck effect. However, the demographic history of the range-edge population predicts a small net decrease in per-individual fitness. Consistent with this prediction, the range-edge population is not impaired in its growth and survival measured in a common garden experiment. We further observe that the allelic diversity at the self-incompatibility locus, which ensures strict outcrossing and evolves under negative frequency-dependent selection, has remained unchanged. Genomic footprints indicative of selective sweeps are broader in the Northern population but not less frequent. We conclude that the outcrossing species A. lyrata ssp. petraea shows a strong resilience to the effect of range expansion.
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Affiliation(s)
- Margarita Takou
- Institute of Botany, University of Cologne, Cologne, Germany
| | - Tuomas Hämälä
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, MN, USA
| | - Evan M Koch
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Kim A Steige
- Institute of Botany, University of Cologne, Cologne, Germany
| | | | - Levi Yant
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Mathieu Genete
- CNRS, UMR 8198 – Evo-Eco-Paleo, University of Lille, Lille, France
| | - Shamil Sunyaev
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Vincent Castric
- CNRS, UMR 8198 – Evo-Eco-Paleo, University of Lille, Lille, France
| | - Xavier Vekemans
- CNRS, UMR 8198 – Evo-Eco-Paleo, University of Lille, Lille, France
| | - Outi Savolainen
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
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19
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Guirao‐Rico S, González J. Benchmarking the performance of Pool-seq SNP callers using simulated and real sequencing data. Mol Ecol Resour 2021; 21:1216-1229. [PMID: 33534960 PMCID: PMC8251607 DOI: 10.1111/1755-0998.13343] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 12/21/2020] [Accepted: 01/27/2021] [Indexed: 12/13/2022]
Abstract
Population genomics is a fast-developing discipline with promising applications in a growing number of life sciences fields. Advances in sequencing technologies and bioinformatics tools allow population genomics to exploit genome-wide information to identify the molecular variants underlying traits of interest and the evolutionary forces that modulate these variants through space and time. However, the cost of genomic analyses of multiple populations is still too high to address them through individual genome sequencing. Pooling individuals for sequencing can be a more effective strategy in Single Nucleotide Polymorphism (SNP) detection and allele frequency estimation because of a higher total coverage. However, compared to individual sequencing, SNP calling from pools has the additional difficulty of distinguishing rare variants from sequencing errors, which is often avoided by establishing a minimum threshold allele frequency for the analysis. Finding an optimal balance between minimizing information loss and reducing sequencing costs is essential to ensure the success of population genomics studies. Here, we have benchmarked the performance of SNP callers for Pool-seq data, based on different approaches, under different conditions, and using computer simulations and real data. We found that SNP callers performance varied for allele frequencies up to 0.35. We also found that SNP callers based on Bayesian (SNAPE-pooled) or maximum likelihood (MAPGD) approaches outperform the two heuristic callers tested (VarScan and PoolSNP), in terms of the balance between sensitivity and FDR both in simulated and sequencing data. Our results will help inform the selection of the most appropriate SNP caller not only for large-scale population studies but also in cases where the Pool-seq strategy is the only option, such as in metagenomic or polyploid studies.
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Affiliation(s)
- Sara Guirao‐Rico
- Institute of Evolutionary BiologyCSIC‐Universitat Pompeu FabraBarcelonaSpain
| | - Josefa González
- Institute of Evolutionary BiologyCSIC‐Universitat Pompeu FabraBarcelonaSpain
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20
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Durvasula A, Lohmueller KE. Negative selection on complex traits limits phenotype prediction accuracy between populations. Am J Hum Genet 2021; 108:620-631. [PMID: 33691092 DOI: 10.1016/j.ajhg.2021.02.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 02/17/2021] [Indexed: 12/22/2022] Open
Abstract
Phenotype prediction is a key goal for medical genetics. Unfortunately, most genome-wide association studies are done in European populations, which reduces the accuracy of predictions via polygenic scores in non-European populations. Here, we use population genetic models to show that human demographic history and negative selection on complex traits can result in population-specific genetic architectures. For traits where alleles with the largest effect on the trait are under the strongest negative selection, approximately half of the heritability can be accounted for by variants in Europe that are absent from Africa, leading to poor performance in phenotype prediction across these populations. Further, under such a model, individuals in the tails of the genetic risk distribution may not be identified via polygenic scores generated in another population. We empirically test these predictions by building a model to stratify heritability between European-specific and shared variants and applied it to 37 traits and diseases in the UK Biobank. Across these phenotypes, ∼30% of the heritability comes from European-specific variants. We conclude that genetic association studies need to include more diverse populations to enable the utility of phenotype prediction in all populations.
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Affiliation(s)
- Arun Durvasula
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kirk E Lohmueller
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA; Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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21
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Long X, Xue H. Genetic-variant hotspots and hotspot clusters in the human genome facilitating adaptation while increasing instability. Hum Genomics 2021; 15:19. [PMID: 33741065 PMCID: PMC7976700 DOI: 10.1186/s40246-021-00318-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 03/04/2021] [Indexed: 12/25/2022] Open
Abstract
Background Genetic variants, underlining phenotypic diversity, are known to distribute unevenly in the human genome. A comprehensive understanding of the distributions of different genetic variants is important for insights into genetic functions and disorders. Methods Herein, a sliding-window scan of regional densities of eight kinds of germline genetic variants, including single-nucleotide-polymorphisms (SNPs) and four size-classes of copy-number-variations (CNVs) in the human genome has been performed. Results The study has identified 44,379 hotspots with high genetic-variant densities, and 1135 hotspot clusters comprising more than one type of hotspots, accounting for 3.1% and 0.2% of the genome respectively. The hotspots and clusters are found to co-localize with different functional genomic features, as exemplified by the associations of hotspots of middle-size CNVs with histone-modification sites, work with balancing and positive selections to meet the need for diversity in immune proteins, and facilitate the development of sensory-perception and neuroactive ligand-receptor interaction pathways in the function-sparse late-replicating genomic sequences. Genetic variants of different lengths co-localize with retrotransposons of different ages on a “long-with-young” and “short-with-all” basis. Hotspots and clusters are highly associated with tumor suppressor genes and oncogenes (p < 10−10), and enriched with somatic tumor CNVs and the trait- and disease-associated SNPs identified by genome-wise association studies, exceeding tenfold enrichment in clusters comprising SNPs and extra-long CNVs. Conclusions In conclusion, the genetic-variant hotspots and clusters represent two-edged swords that spearhead both positive and negative genomic changes. Their strong associations with complex traits and diseases also open up a potential “Common Disease-Hotspot Variant” approach to the missing heritability problem. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-021-00318-3.
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Affiliation(s)
- Xi Long
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China.,HKUST Shenzhen Research Institute, 9 Yuexing First Road, Nanshan, Shenzhen, China
| | - Hong Xue
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China. .,HKUST Shenzhen Research Institute, 9 Yuexing First Road, Nanshan, Shenzhen, China. .,Centre for Cancer Genomics, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
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22
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Schneider K, White TJ, Mitchell S, Adams CE, Reeve R, Elmer KR. The pitfalls and virtues of population genetic summary statistics: Detecting selective sweeps in recent divergences. J Evol Biol 2020; 34:893-909. [DOI: 10.1111/jeb.13738] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 10/22/2020] [Accepted: 10/24/2020] [Indexed: 12/12/2022]
Affiliation(s)
- Kevin Schneider
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Tom J. White
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Sonia Mitchell
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Colin E. Adams
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
- Scottish Centre for Ecology and the Natural Environment Institute of Biodiversity, Animal Health and Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Richard Reeve
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Kathryn R. Elmer
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
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23
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Arnoux S, Fraïsse C, Sauvage C. Genomic inference of complex domestication histories in three Solanaceae species. J Evol Biol 2020; 34:270-283. [PMID: 33107098 DOI: 10.1111/jeb.13723] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 10/15/2020] [Indexed: 12/30/2022]
Abstract
Domestication is a human-induced selection process that imprints the genomes of domesticated populations over a short evolutionary time scale and that occurs in a given demographic context. Reconstructing historical gene flow, effective population size changes and their timing is therefore of fundamental interest to understand how plant demography and human selection jointly shape genomic divergence during domestication. Yet, the comparison under a single statistical framework of independent domestication histories across different crop species has been little evaluated so far. Thus, it is unclear whether domestication leads to convergent demographic changes that similarly affect crop genomes. To address this question, we used existing and new transcriptome data on three crop species of Solanaceae (eggplant, pepper and tomato), together with their close wild relatives. We fitted twelve demographic models of increasing complexity on the unfolded joint allele frequency spectrum for each wild/crop pair, and we found evidence for both shared and species-specific demographic processes between species. A convergent history of domestication with gene flow was inferred for all three species, along with evidence of strong reduction in the effective population size during the cultivation stage of tomato and pepper. The absence of any reduction in size of the crop in eggplant stands out from the classical view of the domestication process; as does the existence of a "protracted period" of management before cultivation. Our results also suggest divergent management strategies of modern cultivars among species as their current demography substantially differs. Finally, the timing of domestication is species-specific and supported by the few historical records available.
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Affiliation(s)
- Stéphanie Arnoux
- INRA UR1052 GAFL, Centre de Recherche INRA PACA, Avignon Cedex 9, France.,Vilmorin SA, Lédenon, France
| | | | - Christopher Sauvage
- INRA UR1052 GAFL, Centre de Recherche INRA PACA, Avignon Cedex 9, France.,Syngenta SAS France, Saint Sauveur, France
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24
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Ghirotto S, Vizzari MT, Tassi F, Barbujani G, Benazzo A. Distinguishing among complex evolutionary models using unphased whole-genome data through random forest approximate Bayesian computation. Mol Ecol Resour 2020; 21:2614-2628. [PMID: 33000507 DOI: 10.1111/1755-0998.13263] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 08/28/2020] [Accepted: 09/07/2020] [Indexed: 01/25/2023]
Abstract
Inferring past demographic histories is crucial in population genetics, and the amount of complete genomes now available should in principle facilitate this inference. In practice, however, the available inferential methods suffer from severe limitations. Although hundreds complete genomes can be simultaneously analysed, complex demographic processes can easily exceed computational constraints, and the procedures to evaluate the reliability of the estimates contribute to increase the computational effort. Here we present an approximate Bayesian computation framework based on the random forest algorithm (ABC-RF), to infer complex past population processes using complete genomes. To this aim, we propose to summarize the data by the full genomic distribution of the four mutually exclusive categories of segregating sites (FDSS), a statistic fast to compute from unphased genome data and that does not require the ancestral state of alleles to be known. We constructed an efficient ABC pipeline and tested how accurately it allows one to recognize the true model among models of increasing complexity, using simulated data and taking into account different sampling strategies in terms of number of individuals analysed, number and size of the genetic loci considered. We also compared the FDSS with the unfolded and folded site frequency spectrum (SFS), and for these statistics we highlighted the experimental conditions maximizing the inferential power of the ABC-RF procedure. We finally analysed real data sets, testing models on the dispersal of anatomically modern humans out of Africa and exploring the evolutionary relationships of the three species of Orangutan inhabiting Borneo and Sumatra.
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Affiliation(s)
- Silvia Ghirotto
- Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy
| | - Maria Teresa Vizzari
- Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy
| | - Francesca Tassi
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Guido Barbujani
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Andrea Benazzo
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
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25
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Gurdasani D, Carstensen T, Fatumo S, Chen G, Franklin CS, Prado-Martinez J, Bouman H, Abascal F, Haber M, Tachmazidou I, Mathieson I, Ekoru K, DeGorter MK, Nsubuga RN, Finan C, Wheeler E, Chen L, Cooper DN, Schiffels S, Chen Y, Ritchie GRS, Pollard MO, Fortune MD, Mentzer AJ, Garrison E, Bergström A, Hatzikotoulas K, Adeyemo A, Doumatey A, Elding H, Wain LV, Ehret G, Auer PL, Kooperberg CL, Reiner AP, Franceschini N, Maher D, Montgomery SB, Kadie C, Widmer C, Xue Y, Seeley J, Asiki G, Kamali A, Young EH, Pomilla C, Soranzo N, Zeggini E, Pirie F, Morris AP, Heckerman D, Tyler-Smith C, Motala AA, Rotimi C, Kaleebu P, Barroso I, Sandhu MS. Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa. Cell 2020; 179:984-1002.e36. [PMID: 31675503 DOI: 10.1016/j.cell.2019.10.004] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 04/03/2019] [Accepted: 10/02/2019] [Indexed: 12/19/2022]
Abstract
Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.
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Affiliation(s)
- Deepti Gurdasani
- William Harvey Research Institute, Queen Mary's University of London, London, UK
| | | | - Segun Fatumo
- London School of Hygiene and Tropical Medicine, London, UK; Uganda Medical Informatics Centre (UMIC), MRC/UVRI and LSHTM (Uganda Research Unit), Entebbe, Uganda; H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation (CGRI)/National Biotechnology Development Agency CGRI/NABDA, Abuja, Nigeria
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Institute of Health, Bethesda, MD, USA
| | | | | | | | | | - Marc Haber
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Ioanna Tachmazidou
- GSK Medicines Research Centre, Gunnels Wood Road, Stevenage Hertfordshire SG1 2NY, UK
| | - Iain Mathieson
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kenneth Ekoru
- Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene & Tropical Medicine Uganda Research Unit on AIDS, Entebbe, Uganda; Department of Medicine, University of Cambridge, Cambridge, UK
| | - Marianne K DeGorter
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Rebecca N Nsubuga
- Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene & Tropical Medicine Uganda Research Unit on AIDS, Entebbe, Uganda
| | - Chris Finan
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Eleanor Wheeler
- Wellcome Sanger Institute, Hinxton, Cambridge, UK; MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Li Chen
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - Stephan Schiffels
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany
| | - Yuan Chen
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | | | | | | | - Alex J Mentzer
- The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | | | - Konstantinos Hatzikotoulas
- Wellcome Sanger Institute, Hinxton, Cambridge, UK; Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Institute of Health, Bethesda, MD, USA
| | - Ayo Doumatey
- Center for Research on Genomics and Global Health, National Institute of Health, Bethesda, MD, USA
| | | | - Louise V Wain
- Department of Health Sciences, University of Leicester, Leicester, UK; National Institute for Health Research, Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Georg Ehret
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1211 Genève 14, Switzerland
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Charles L Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Dermot Maher
- Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene & Tropical Medicine Uganda Research Unit on AIDS, Entebbe, Uganda
| | - Stephen B Montgomery
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | | | | | - Yali Xue
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Janet Seeley
- London School of Hygiene and Tropical Medicine, London, UK; Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene & Tropical Medicine Uganda Research Unit on AIDS, Entebbe, Uganda
| | - Gershim Asiki
- Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene & Tropical Medicine Uganda Research Unit on AIDS, Entebbe, Uganda
| | - Anatoli Kamali
- Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene & Tropical Medicine Uganda Research Unit on AIDS, Entebbe, Uganda
| | - Elizabeth H Young
- Wellcome Sanger Institute, Hinxton, Cambridge, UK; Department of Medicine, University of Cambridge, Cambridge, UK
| | - Cristina Pomilla
- Wellcome Sanger Institute, Hinxton, Cambridge, UK; Department of Medicine, University of Cambridge, Cambridge, UK
| | - Nicole Soranzo
- Wellcome Sanger Institute, Hinxton, Cambridge, UK; Department of Haematology, University of Cambridge, Cambridge, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Fraser Pirie
- Department of Diabetes and Endocrinology, University of KwaZulu-Natal, Durban, South Africa
| | - Andrew P Morris
- The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK; Department of Biostatistics, University of Liverpool, Liverpool, UK
| | | | | | - Ayesha A Motala
- Department of Diabetes and Endocrinology, University of KwaZulu-Natal, Durban, South Africa.
| | - Charles Rotimi
- Center for Research on Genomics and Global Health, National Institute of Health, Bethesda, MD, USA.
| | - Pontiano Kaleebu
- London School of Hygiene and Tropical Medicine, London, UK; Uganda Medical Informatics Centre (UMIC), MRC/UVRI and LSHTM (Uganda Research Unit), Entebbe, Uganda; Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene & Tropical Medicine Uganda Research Unit on AIDS, Entebbe, Uganda.
| | - Inês Barroso
- Wellcome Sanger Institute, Hinxton, Cambridge, UK; MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
| | - Manj S Sandhu
- Department of Medicine, University of Cambridge, Cambridge, UK.
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26
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Turner-Hissong SD, Mabry ME, Beissinger TM, Ross-Ibarra J, Pires JC. Evolutionary insights into plant breeding. CURRENT OPINION IN PLANT BIOLOGY 2020; 54:93-100. [PMID: 32325397 DOI: 10.1016/j.pbi.2020.03.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 01/20/2020] [Accepted: 03/04/2020] [Indexed: 06/11/2023]
Abstract
Crop domestication is a fascinating area of study, as shown by a multitude of recent reviews. Coupled with the increasing availability of genomic and phenomic resources in numerous crop species, insights from evolutionary biology will enable a deeper understanding of the genetic architecture and short-term evolution of complex traits, which can be used to inform selection strategies. Future advances in crop improvement will rely on the integration of population genetics with plant breeding methodology, and the development of community resources to support research in a variety of crop life histories and reproductive strategies. We highlight recent advances related to the role of selective sweeps and demographic history in shaping genetic architecture, how these breakthroughs can inform selection strategies, and the application of precision gene editing to leverage these connections.
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Affiliation(s)
- Sarah D Turner-Hissong
- Center for Population Biology, University of California, Davis, CA, USA; Department of Evolution and Ecology, University of California, Davis, CA, USA.
| | - Makenzie E Mabry
- Bond Life Science Center and Division of Biological Sciences, University of Missouri, Columbia, MO, USA
| | - Timothy M Beissinger
- Division of Plant Breeding Methodology, Department of Crop Science, Georg-August-Universtät, Göttingen, Germany; Center for Integrated Breeding Research, Georg-August-Universtät, Göttingen, Germany
| | - Jeffrey Ross-Ibarra
- Center for Population Biology, University of California, Davis, CA, USA; Department of Evolution and Ecology, University of California, Davis, CA, USA
| | - J Chris Pires
- Bond Life Science Center and Division of Biological Sciences, University of Missouri, Columbia, MO, USA
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27
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Gil-Varea E, Spataro N, Villar LM, Tejeda-Velarde A, Midaglia L, Matesanz F, Malhotra S, Eixarch H, Patsopoulos N, Fernández Ó, Oliver-Martos B, Saiz A, Llufriu S, Ramió-Torrentà L, Quintana E, Izquierdo G, Alcina A, Bosch E, Navarro A, Montalban X, Comabella M. Targeted resequencing reveals rare variants enrichment in multiple sclerosis susceptibility genes. Hum Mutat 2020; 41:1308-1320. [PMID: 32196808 DOI: 10.1002/humu.24016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 03/05/2020] [Accepted: 03/18/2020] [Indexed: 12/25/2022]
Abstract
Although genome-wide association studies have identified a number of common variants associated with multiple sclerosis (MS) susceptibility, little is known about the relevance of rare variants. Here, we aimed to explore the role of rare variants in 14 MS risk genes (FCRL1, RGS1, TIMMDC1, HHEX, CXCR5, LTBR, TSFM, GALC, TRAF3, STAT3, TNFSF14, IFI30, CD40, and CYP24A1) by targeted resequencing in an Iberian population of 524 MS cases and 546 healthy controls. Four rare variants-enriched regions within CYP24A1, FCRL1, RGS1, and TRAF3 were identified as significantly associated with MS. Functional studies revealed significantly decreased regulator of G protein signaling 1 (RGS1) gene expression levels in peripheral blood mononuclear cells from MS patients with RGS1 rare variants compared to noncarriers, whereas no significant differences in gene expression were observed for CYP24A1, FCRL1, and TRAF3 between rare variants carriers and noncarriers. Immunophenotyping showed significant decrease in RGS1 expression in peripheral blood B lymphocytes from MS patients with RGS1 rare variants relative to noncarriers. Lastly, peripheral blood mononuclear cell from MS patients carrying RGS1 rare variants showed significantly lower induction of RGS1 gene expression by interferon-β compared to MS patients lacking RGS1 variants. The presence of rare variants in RGS1 reinforce the ideas of high genetic heterogeneity and a role of rare variants in MS pathogenesis.
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Affiliation(s)
- Elia Gil-Varea
- Servei de Neurologia-Neuroimmunologia, Center d'Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d'Hebron (VHIR), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Nino Spataro
- Genetics Laboratory, UDIAT-Centre Diagnòstic, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Spain
| | - Luisa María Villar
- Departments of Immunology and Neurology, Multiple Sclerosis Unit, Hospital Ramon y Cajal, (IRYCIS), Madrid, Spain
| | - Amalia Tejeda-Velarde
- Departments of Immunology and Neurology, Multiple Sclerosis Unit, Hospital Ramon y Cajal, (IRYCIS), Madrid, Spain
| | - Luciana Midaglia
- Servei de Neurologia-Neuroimmunologia, Center d'Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d'Hebron (VHIR), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Fuencisla Matesanz
- Department of Cell Biology and Immunology, Instituto de Parasitología y Biomedicina "López Neyra", Consejo Superior de Investigaciones Científicas (IPBLN-CSIC), Granada, Spain
| | - Sunny Malhotra
- Servei de Neurologia-Neuroimmunologia, Center d'Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d'Hebron (VHIR), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Herena Eixarch
- Servei de Neurologia-Neuroimmunologia, Center d'Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d'Hebron (VHIR), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Nikolaos Patsopoulos
- Department of Neurology, Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Óscar Fernández
- Neuroimmunology and Neuroinflammation Group, Instituto de Investigación Biomédica de Málaga-IBIMA. UGC Neurociencias, Hospital Regional Universitario de Málaga, Málaga, Spain
| | - Begoña Oliver-Martos
- Neuroimmunology and Neuroinflammation Group, Instituto de Investigación Biomédica de Málaga-IBIMA. UGC Neurociencias, Hospital Regional Universitario de Málaga, Málaga, Spain
| | - Albert Saiz
- Servicio de Neurología, Hospital Clinic and Institut d'Investigació Biomèdica Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Sara Llufriu
- Servicio de Neurología, Hospital Clinic and Institut d'Investigació Biomèdica Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Lluís Ramió-Torrentà
- Department of Medical Sciences, Faculty of Medicine, Neurodegeneration and Neuroinflammation Group, Girona Biomedical Research Institute (IdIBGi), University of Girona, Girona, Spain
| | - Ester Quintana
- Department of Medical Sciences, Faculty of Medicine, Neurodegeneration and Neuroinflammation Group, Girona Biomedical Research Institute (IdIBGi), University of Girona, Girona, Spain
| | - Guillermo Izquierdo
- Departamento de Neurología, Hospital Universitario Virgen Macarena, Sevilla, Spain
| | - Antonio Alcina
- Department of Cell Biology and Immunology, Instituto de Parasitología y Biomedicina "López Neyra", Consejo Superior de Investigaciones Científicas (IPBLN-CSIC), Granada, Spain
| | - Elena Bosch
- Genetics Laboratory, UDIAT-Centre Diagnòstic, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Reus, Spain
| | - Arcadi Navarro
- Genetics Laboratory, UDIAT-Centre Diagnòstic, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Spain.,Centre de Regulació Genòmica (CRG), Barcelona, España.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Cataluña, Spain
| | - Xavier Montalban
- Servei de Neurologia-Neuroimmunologia, Center d'Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d'Hebron (VHIR), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Manuel Comabella
- Servei de Neurologia-Neuroimmunologia, Center d'Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d'Hebron (VHIR), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
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28
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Uricchio LH. Evolutionary perspectives on polygenic selection, missing heritability, and GWAS. Hum Genet 2020; 139:5-21. [PMID: 31201529 PMCID: PMC8059781 DOI: 10.1007/s00439-019-02040-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 06/06/2019] [Indexed: 12/26/2022]
Abstract
Genome-wide association studies (GWAS) have successfully identified many trait-associated variants, but there is still much we do not know about the genetic basis of complex traits. Here, we review recent theoretical and empirical literature regarding selection on complex traits to argue that "missing heritability" is as much an evolutionary problem as it is a statistical problem. We discuss empirical findings that suggest a role for selection in shaping the effect sizes and allele frequencies of causal variation underlying complex traits, and the limitations of these studies. We then use simulations of selection, realistic genome structure, and complex human demography to illustrate the results of recent theoretical work on polygenic selection, and show that statistical inference of causal loci is sharply affected by evolutionary processes. In particular, when selection acts on causal alleles, it hampers the ability to detect causal loci and constrains the transferability of GWAS results across populations. Last, we discuss the implications of these findings for future association studies, and suggest that future statistical methods to infer causal loci for genetic traits will benefit from explicit modeling of the joint distribution of effect sizes and allele frequencies under plausible evolutionary models.
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Affiliation(s)
- Lawrence H Uricchio
- Department of Biology, Stanford University, Stanford, CA, USA.
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, USA.
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29
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Tong DMH, Hernandez RD. Population genetic simulation study of power in association testing across genetic architectures and study designs. Genet Epidemiol 2020; 44:90-103. [PMID: 31587362 PMCID: PMC6980249 DOI: 10.1002/gepi.22264] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 08/26/2019] [Accepted: 09/16/2019] [Indexed: 12/22/2022]
Abstract
While it is well established that genetics can be a major contributor to population variation of complex traits, the relative contributions of rare and common variants to phenotypic variation remains a matter of considerable debate. Here, we simulate genetic and phenotypic data across different case/control panel sampling strategies, sequencing methods, and genetic architecture models based on evolutionary forces to determine the statistical performance of rare variant association tests (RVATs) widely in use. We find that the highest statistical power of RVATs is achieved by sampling case/control individuals from the extremes of an underlying quantitative trait distribution. We also demonstrate that the use of genotyping arrays, in conjunction with imputation from a whole-genome sequenced (WGS) reference panel, recovers the vast majority (90%) of the power that could be achieved by sequencing the case/control panel using current tools. Finally, we show that for dichotomous traits, the statistical performance of RVATs decreases as rare variants become more important in the trait architecture. Our results extend previous work to show that RVATs are insufficiently powered to make generalizable conclusions about the role of rare variants in dichotomous complex traits.
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Affiliation(s)
- Dominic M. H. Tong
- University of California, Berkeley ‐ University of California, San Francisco Graduate Program in BioengineeringSan FranciscoCalifornia
| | - Ryan D. Hernandez
- Department of Bioengineering and Therapeutic SciencesUniversity of CaliforniaSan FranciscoCalifornia
- Department of Human GeneticsMcGill UniversityMontrealCanada
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30
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Structural variants exhibit widespread allelic heterogeneity and shape variation in complex traits. Nat Commun 2019; 10:4872. [PMID: 31653862 PMCID: PMC6814777 DOI: 10.1038/s41467-019-12884-1] [Citation(s) in RCA: 84] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Accepted: 09/25/2019] [Indexed: 12/11/2022] Open
Abstract
It has been hypothesized that individually-rare hidden structural variants (SVs) could account for a significant fraction of variation in complex traits. Here we identified more than 20,000 euchromatic SVs from 14 Drosophila melanogaster genome assemblies, of which ~40% are invisible to high specificity short-read genotyping approaches. SVs are common, with 31.5% of diploid individuals harboring a SV in genes larger than 5kb, and 24% harboring multiple SVs in genes larger than 10kb. SV minor allele frequencies are rarer than amino acid polymorphisms, suggesting that SVs are more deleterious. We show that a number of functionally important genes harbor previously hidden structural variants likely to affect complex phenotypes. Furthermore, SVs are overrepresented in candidate genes associated with quantitative trait loci mapped using the Drosophila Synthetic Population Resource. We conclude that SVs are ubiquitous, frequently constitute a heterogeneous allelic series, and can act as rare alleles of large effect.
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31
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O'Connor LJ, Schoech AP, Hormozdiari F, Gazal S, Patterson N, Price AL. Extreme Polygenicity of Complex Traits Is Explained by Negative Selection. Am J Hum Genet 2019; 105:456-476. [PMID: 31402091 PMCID: PMC6732528 DOI: 10.1016/j.ajhg.2019.07.003] [Citation(s) in RCA: 119] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 07/03/2019] [Indexed: 12/16/2022] Open
Abstract
Complex traits and common diseases are extremely polygenic, their heritability spread across thousands of loci. One possible explanation is that thousands of genes and loci have similarly important biological effects when mutated. However, we hypothesize that for most complex traits, relatively few genes and loci are critical, and negative selection-purging large-effect mutations in these regions-leaves behind common-variant associations in thousands of less critical regions instead. We refer to this phenomenon as flattening. To quantify its effects, we introduce a mathematical definition of polygenicity, the effective number of independently associated SNPs (Me), which describes how evenly the heritability of a trait is spread across the genome. We developed a method, stratified LD fourth moments regression (S-LD4M), to estimate Me, validating that it produces robust estimates in simulations. Analyzing 33 complex traits (average N = 361k), we determined that heritability is spread ∼4× more evenly among common SNPs than among low-frequency SNPs. This difference, together with evolutionary modeling of new mutations, suggests that complex traits would be orders of magnitude less polygenic if not for the influence of negative selection. We also determined that heritability is spread more evenly within functionally important regions in proportion to their heritability enrichment; functionally important regions do not harbor common SNPs with greatly increased causal effect sizes, due to selective constraint. Our results suggest that for most complex traits, the genes and loci with the most critical biological effects often differ from those with the strongest common-variant associations.
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Affiliation(s)
- Luke J O'Connor
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Bioinformatics and Integrative Genomics, Harvard Graduate School of Arts and Sciences, Boston, MA 02115, USA.
| | - Armin P Schoech
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Farhad Hormozdiari
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Nick Patterson
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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Hernandez RD, Uricchio LH, Hartman K, Ye C, Dahl A, Zaitlen N. Ultrarare variants drive substantial cis heritability of human gene expression. Nat Genet 2019; 51:1349-1355. [PMID: 31477931 PMCID: PMC6730564 DOI: 10.1038/s41588-019-0487-7] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Accepted: 07/08/2019] [Indexed: 11/09/2022]
Abstract
The vast majority of human mutations have minor allele frequencies under 1%, with the plurality observed only once (that is, 'singletons'). While Mendelian diseases are predominantly caused by rare alleles, their cumulative contribution to complex phenotypes is largely unknown. We develop and rigorously validate an approach to jointly estimate the contribution of all alleles, including singletons, to phenotypic variation. We apply our approach to transcriptional regulation, an intermediate between genetic variation and complex disease. Using whole-genome DNA and lymphoblastoid cell line RNA sequencing data from 360 European individuals, we conservatively estimate that singletons contribute approximately 25% of cis heritability across genes (dwarfing the contributions of other frequencies). The majority (approximately 76%) of singleton heritability derives from ultrarare variants absent from thousands of additional samples. We develop an inference procedure to demonstrate that our results are consistent with pervasive purifying selection shaping the regulatory architecture of most human genes.
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Affiliation(s)
- Ryan D Hernandez
- Bioengineering & Therapeutic Sciences, UCSF, San Francisco, CA, USA.
- Institute for Human Genetics, UCSF, San Francisco, CA, USA.
- Institute for Quantitative Biosciences, UCSF, San Francisco, CA, USA.
- Institute for Computational Health Sciences, UCSF, San Francisco, CA, USA.
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada.
- McGill University and the Genome Quebec Innovation Center, Montreal, Quebec, Canada.
| | | | - Kevin Hartman
- Biological and Medical Informatics Graduate Program, UCSF, San Francisco, CA, USA
| | - Chun Ye
- Institute for Human Genetics, UCSF, San Francisco, CA, USA
- Epidemiology & Biostatistics, UCSF, San Francisco, CA, USA
| | - Andrew Dahl
- Institute for Human Genetics, UCSF, San Francisco, CA, USA
- Institute for Quantitative Biosciences, UCSF, San Francisco, CA, USA
| | - Noah Zaitlen
- Institute for Human Genetics, UCSF, San Francisco, CA, USA.
- Institute for Quantitative Biosciences, UCSF, San Francisco, CA, USA.
- Department of Medicine Lung Biology Center, UCSF, San Francisco, CA, USA.
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Sella G, Barton NH. Thinking About the Evolution of Complex Traits in the Era of Genome-Wide Association Studies. Annu Rev Genomics Hum Genet 2019; 20:461-493. [DOI: 10.1146/annurev-genom-083115-022316] [Citation(s) in RCA: 123] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Many traits of interest are highly heritable and genetically complex, meaning that much of the variation they exhibit arises from differences at numerous loci in the genome. Complex traits and their evolution have been studied for more than a century, but only in the last decade have genome-wide association studies (GWASs) in humans begun to reveal their genetic basis. Here, we bring these threads of research together to ask how findings from GWASs can further our understanding of the processes that give rise to heritable variation in complex traits and of the genetic basis of complex trait evolution in response to changing selection pressures (i.e., of polygenic adaptation). Conversely, we ask how evolutionary thinking helps us to interpret findings from GWASs and informs related efforts of practical importance.
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Affiliation(s)
- Guy Sella
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Program for Mathematical Genomics, Columbia University, New York, NY 10032, USA
| | - Nicholas H. Barton
- Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria
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Hou K, Burch KS, Majumdar A, Shi H, Mancuso N, Wu Y, Sankararaman S, Pasaniuc B. Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture. Nat Genet 2019; 51:1244-1251. [PMID: 31358995 PMCID: PMC6686906 DOI: 10.1038/s41588-019-0465-0] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 06/13/2019] [Indexed: 12/14/2022]
Abstract
SNP-heritability is a fundamental quantity in the study of complex traits. Recent studies have shown that existing methods to estimate genome-wide SNP-heritability can yield biases when their assumptions are violated. While various approaches have been proposed to account for frequency- and linkage disequilibrium (LD)-dependent genetic architectures, it remains unclear which estimates reported in the literature are reliable. Here we show that genome-wide SNP-heritability can be accurately estimated from biobank-scale data irrespective of genetic architecture, without specifying a heritability model or partitioning SNPs by allele frequency and/or LD. We show analytically and through extensive simulations starting from real genotypes (UK Biobank, N = 337 K) that, unlike existing methods, our closed-form estimator is robust across a wide range of architectures. We provide estimates of SNP-heritability for 22 complex traits in the UK Biobank and show that, consistent with our results in simulations, existing biobank-scale methods yield estimates up to 30% different from our theoretically-justified approach.
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Affiliation(s)
- Kangcheng Hou
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- College of Computer Science and Technology, Zhejiang University, Hangzhou, China
| | - Kathryn S Burch
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Arunabha Majumdar
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Huwenbo Shi
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Nicholas Mancuso
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Biostatistics Division, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yue Wu
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sriram Sankararaman
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
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35
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Han S, Andrés AM, Marques-Bonet T, Kuhlwilm M. Genetic Variation in Pan Species Is Shaped by Demographic History and Harbors Lineage-Specific Functions. Genome Biol Evol 2019; 11:1178-1191. [PMID: 30847478 PMCID: PMC6482415 DOI: 10.1093/gbe/evz047] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/05/2019] [Indexed: 01/08/2023] Open
Abstract
Chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) are the closest living relatives of humans, but the two species show distinct behavioral and physiological differences, particularly regarding female reproduction. Despite their recent rapid decline, the demographic histories of the two species have been different during the past 1–2 Myr, likely having an impact on their genomic diversity. Here, we analyze the inferred functional consequences of genetic variation across 69 individuals, making use of the most complete data set of genomes in the Pan clade to date. We test to which extent the demographic history influences the efficacy of purifying selection in these species. We find that small historical effective population sizes (Ne) correlate not only with low levels of genetic diversity but also with a larger number of deleterious alleles in homozygosity and an increased proportion of deleterious changes at low frequencies. To investigate the putative genetic basis for phenotypic differences between chimpanzees and bonobos, we exploit the catalog of putatively deleterious protein-coding changes in each lineage. We show that bonobo-specific nonsynonymous changes are enriched in genes related to age at menarche in humans, suggesting that the prominent physiological differences in the female reproductive system between chimpanzees and bonobos might be explained, in part, by putatively adaptive changes on the bonobo lineage.
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Affiliation(s)
- Sojung Han
- Institut de Biologia Evolutiva, Consejo Superior de Investigaciones Científicas-Universitat Pompeu Fabra, Barcelona, Spain
| | - Aida M Andrés
- Department of Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.,Department of Genetics, Evolution and Environment, UCL Genetics Institute, University College London, London, United Kingdom
| | - Tomas Marques-Bonet
- Institut de Biologia Evolutiva, Consejo Superior de Investigaciones Científicas-Universitat Pompeu Fabra, Barcelona, Spain.,Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.,CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, Barcelona, Spain
| | - Martin Kuhlwilm
- Institut de Biologia Evolutiva, Consejo Superior de Investigaciones Científicas-Universitat Pompeu Fabra, Barcelona, Spain
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36
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Prohaska A, Racimo F, Schork AJ, Sikora M, Stern AJ, Ilardo M, Allentoft ME, Folkersen L, Buil A, Moreno-Mayar JV, Korneliussen T, Geschwind D, Ingason A, Werge T, Nielsen R, Willerslev E. Human Disease Variation in the Light of Population Genomics. Cell 2019; 177:115-131. [DOI: 10.1016/j.cell.2019.01.052] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 01/23/2019] [Accepted: 01/29/2019] [Indexed: 01/25/2023]
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37
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Schoech AP, Jordan DM, Loh PR, Gazal S, O'Connor LJ, Balick DJ, Palamara PF, Finucane HK, Sunyaev SR, Price AL. Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection. Nat Commun 2019; 10:790. [PMID: 30770844 PMCID: PMC6377669 DOI: 10.1038/s41467-019-08424-6] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 01/09/2019] [Indexed: 02/06/2023] Open
Abstract
Understanding the role of rare variants is important in elucidating the genetic basis of human disease. Negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1 - p)]α, where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α for 25 UK Biobank diseases and complex traits. All traits produce negative α estimates, with best-fit mean of -0.38 (s.e. 0.02) across traits. Despite larger rare variant effect sizes, rare variants (MAF < 1%) explain less than 10% of total SNP-heritability for most traits analyzed. Using evolutionary modeling and forward simulations, we validate the α model of MAF-dependent trait effects and assess plausible values of relevant evolutionary parameters.
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Affiliation(s)
- Armin P Schoech
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA.
| | - Daniel M Jordan
- Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, 10029, NY, USA
| | - Po-Ru Loh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, 02115, MA, USA
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Luke J O'Connor
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Daniel J Balick
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, 02115, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02115, MA, USA
| | - Pier F Palamara
- Department of Statistics, University of Oxford, Oxford, OX1 3LB, UK
| | - Hilary K Finucane
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Shamil R Sunyaev
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, 02115, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02115, MA, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA.
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38
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Uricchio LH, Kitano HC, Gusev A, Zaitlen NA. An evolutionary compass for detecting signals of polygenic selection and mutational bias. Evol Lett 2019; 3:69-79. [PMID: 30788143 PMCID: PMC6369964 DOI: 10.1002/evl3.97] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 12/03/2018] [Accepted: 12/10/2018] [Indexed: 12/17/2022] Open
Abstract
Selection and mutation shape the genetic variation underlying human traits, but the specific evolutionary mechanisms driving complex trait variation are largely unknown. We developed a statistical method that uses polarized genome-wide association study (GWAS) summary statistics from a single population to detect signals of mutational bias and selection. We found evidence for nonneutral signals on variation underlying several traits (body mass index [BMI], schizophrenia, Crohn's disease, educational attainment, and height). We then used simulations that incorporate simultaneous negative and positive selection to show that these signals are consistent with mutational bias and shifts in the fitness-phenotype relationship, but not stabilizing selection or mutational bias alone. We additionally replicate two of our top three signals (BMI and educational attainment) in an external cohort, and show that population stratification may have confounded GWAS summary statistics for height in the GIANT cohort. Our results provide a flexible and powerful framework for evolutionary analysis of complex phenotypes in humans and other species, and offer insights into the evolutionary mechanisms driving variation in human polygenic traits.
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Affiliation(s)
| | - Hugo C. Kitano
- Department of Computer ScienceStanford UniversityStanfordCA
| | | | - Noah A. Zaitlen
- Department of MedicineUniversity of CaliforniaSan FranciscoCA
- Bioengineering and Therapeutic SciencesUniversity of CaliforniaSan FranciscoCA
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39
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The arms race between man and Mycobacterium tuberculosis: Time to regroup. INFECTION GENETICS AND EVOLUTION 2018; 66:361-375. [DOI: 10.1016/j.meegid.2017.08.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Revised: 08/21/2017] [Accepted: 08/22/2017] [Indexed: 12/12/2022]
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40
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Stetter MG, Thornton K, Ross-Ibarra J. Genetic architecture and selective sweeps after polygenic adaptation to distant trait optima. PLoS Genet 2018; 14:e1007794. [PMID: 30452452 PMCID: PMC6277123 DOI: 10.1371/journal.pgen.1007794] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 12/03/2018] [Accepted: 10/26/2018] [Indexed: 11/22/2022] Open
Abstract
Understanding the genetic basis of phenotypic adaptation to changing environments is an essential goal of population and quantitative genetics. While technological advances now allow interrogation of genome-wide genotyping data in large panels, our understanding of the process of polygenic adaptation is still limited. To address this limitation, we use extensive forward-time simulation to explore the impacts of variation in demography, trait genetics, and selection on the rate and mode of adaptation and the resulting genetic architecture. We simulate a population adapting to an optimum shift, modeling sequence variation for 20 QTL for each of 12 different demographies for 100 different traits varying in the effect size distribution of new mutations, the strength of stabilizing selection, and the contribution of the genomic background. We then use random forest regression approaches to learn the relative importance of input parameters in determining a number of aspects of the process of adaptation, including the speed of adaptation, the relative frequency of hard sweeps and sweeps from standing variation, or the final genetic architecture of the trait. We find that selective sweeps occur even for traits under relatively weak selection and where the genetic background explains most of the variation. Though most sweeps occur from variation segregating in the ancestral population, new mutations can be important for traits under strong stabilizing selection that undergo a large optimum shift. We also show that population bottlenecks and expansion impact overall genetic variation as well as the relative importance of sweeps from standing variation and the speed with which adaptation can occur. We then compare our results to two traits under selection during maize domestication, showing that our simulations qualitatively recapitulate differences between them. Overall, our results underscore the complex population genetics of individual loci in even relatively simple quantitative trait models, but provide a glimpse into the factors that drive this complexity and the potential of these approaches for understanding polygenic adaptation.
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Affiliation(s)
- Markus G. Stetter
- Dept. of Plant Sciences and Center for Population Biology, University of California, Davis, Davis, CA, USA
| | - Kevin Thornton
- Dept. of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, CA, USA
| | - Jeffrey Ross-Ibarra
- Dept. of Plant Sciences and Center for Population Biology, University of California, Davis, Davis, CA, USA
- Genome Center, University of California, Davis, Davis, CA, USA
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41
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Mooney JA, Huber CD, Service S, Sul JH, Marsden CD, Zhang Z, Sabatti C, Ruiz-Linares A, Bedoya G, Freimer N, Lohmueller KE. Understanding the Hidden Complexity of Latin American Population Isolates. Am J Hum Genet 2018; 103:707-726. [PMID: 30401458 PMCID: PMC6218714 DOI: 10.1016/j.ajhg.2018.09.013] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Accepted: 09/26/2018] [Indexed: 12/12/2022] Open
Abstract
Most population isolates examined to date were founded from a single ancestral population. Consequently, there is limited knowledge about the demographic history of admixed population isolates. Here we investigate genomic diversity of recently admixed population isolates from Costa Rica and Colombia and compare their diversity to a benchmark population isolate, the Finnish. These Latin American isolates originated during the 16th century from admixture between a few hundred European males and Amerindian females, with a limited contribution from African founders. We examine whole-genome sequence data from 449 individuals, ascertained as families to build mutigenerational pedigrees, with a mean sequencing depth of coverage of approximately 36×. We find that Latin American isolates have increased genetic diversity relative to the Finnish. However, there is an increase in the amount of identity by descent (IBD) segments in the Latin American isolates relative to the Finnish. The increase in IBD segments is likely a consequence of a very recent and severe population bottleneck during the founding of the admixed population isolates. Furthermore, the proportion of the genome that falls within a long run of homozygosity (ROH) in Costa Rican and Colombian individuals is significantly greater than that in the Finnish, suggesting more recent consanguinity in the Latin American isolates relative to that seen in the Finnish. Lastly, we find that recent consanguinity increased the number of deleterious variants found in the homozygous state, which is relevant if deleterious variants are recessive. Our study suggests that there is no single genetic signature of a population isolate.
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Affiliation(s)
- Jazlyn A Mooney
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Christian D Huber
- Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Susan Service
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Jae Hoon Sul
- Department of Psychiatry and Biobehavioral Sciences, Semel Center for Informatics and Personalized Genomics, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Clare D Marsden
- Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Zhongyang Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Chiara Sabatti
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, Fudan University, Shanghai 200438, China; Aix-Marseille Univ, CNRS, EFS, ADES, Marseille, France
| | - Gabriel Bedoya
- Genética Molecular (GENMOL), Universidad de Antioquia, Medellín, Colombia
| | - Nelson Freimer
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Kirk E Lohmueller
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA 90095, USA.
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42
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Kim BY, Huber CD, Lohmueller KE. Deleterious variation shapes the genomic landscape of introgression. PLoS Genet 2018; 14:e1007741. [PMID: 30346959 PMCID: PMC6233928 DOI: 10.1371/journal.pgen.1007741] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Revised: 11/13/2018] [Accepted: 10/05/2018] [Indexed: 11/19/2022] Open
Abstract
While it is appreciated that population size changes can impact patterns of deleterious variation in natural populations, less attention has been paid to how gene flow affects and is affected by the dynamics of deleterious variation. Here we use population genetic simulations to examine how gene flow impacts deleterious variation under a variety of demographic scenarios, mating systems, dominance coefficients, and recombination rates. Our results show that admixture between populations can temporarily reduce the genetic load of smaller populations and cause increases in the frequency of introgressed ancestry, especially if deleterious mutations are recessive. Additionally, when fitness effects of new mutations are recessive, between-population differences in the sites at which deleterious variants exist creates heterosis in hybrid individuals. Together, these factors lead to an increase in introgressed ancestry, particularly when recombination rates are low. Under certain scenarios, introgressed ancestry can increase from an initial frequency of 5% to 30–75% and fix at many loci, even in the absence of beneficial mutations. Further, deleterious variation and admixture can generate correlations between the frequency of introgressed ancestry and recombination rate or exon density, even in the absence of other types of selection. The direction of these correlations is determined by the specific demography and whether mutations are additive or recessive. Therefore, it is essential that null models of admixture include both demography and deleterious variation before invoking other mechanisms to explain unusual patterns of genetic variation. Individuals from distinct populations sometimes will produce fertile offspring and will exchange genetic material in a process called hybridization. Genomes of hybrid individuals often show non-random patterns of hybrid ancestry across the genome, where some regions have a high frequency of ancestry from the second population and other regions have less. Typically, this pattern has been attributed to adaptive introgression, where beneficial genetic variants are passed from one population to the other, or to genomic incompatibilities between these distinct species. However, other mechanisms could lead to these heterogeneous patterns of ancestry in hybrids. Here we use simulations to investigate whether deleterious mutations affect the patterns of introgressed ancestry across genomes. We show that when ancestry from a larger population is added to a smaller population, the ancestry from the larger population dramatically increases in frequency because it carries fewer deleterious mutations. This occurs even in the absence of beneficial mutations in either population. Additionally, we show that differences in sex chromosome evolution relative to autosomes, or differences in mating system, can affect patterns of introgression in similar ways. Our study argues that deleterious mutations should be included in population genetic models used to identify unusual regions of the genome that appear to be under selection in hybrids.
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Affiliation(s)
- Bernard Y. Kim
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, United States of America
| | - Christian D. Huber
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, United States of America
| | - Kirk E. Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, United States of America
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, California, United States of America
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America
- * E-mail:
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43
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Cornejo OE, Yee MC, Dominguez V, Andrews M, Sockell A, Strandberg E, Livingstone D, Stack C, Romero A, Umaharan P, Royaert S, Tawari NR, Ng P, Gutierrez O, Phillips W, Mockaitis K, Bustamante CD, Motamayor JC. Population genomic analyses of the chocolate tree, Theobroma cacao L., provide insights into its domestication process. Commun Biol 2018; 1:167. [PMID: 30345393 PMCID: PMC6191438 DOI: 10.1038/s42003-018-0168-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 09/14/2018] [Indexed: 01/24/2023] Open
Abstract
Domestication has had a strong impact on the development of modern societies. We sequenced 200 genomes of the chocolate plant Theobroma cacao L. to show for the first time to our knowledge that a single population, the Criollo population, underwent strong domestication ~3600 years ago (95% CI: 2481-13,806 years ago). We also show that during the process of domestication, there was strong selection for genes involved in the metabolism of the colored protectants anthocyanins and the stimulant theobromine, as well as disease resistance genes. Our analyses show that domesticated populations of T. cacao (Criollo) maintain a higher proportion of high-frequency deleterious mutations. We also show for the first time the negative consequences of the increased accumulation of deleterious mutations during domestication on the fitness of individuals (significant reduction in kilograms of beans per hectare per year as Criollo ancestry increases, as estimated from a GLM, P = 0.000425).
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Affiliation(s)
- Omar E Cornejo
- School of Biological Sciences, Washington State University, PO Box 644236, Heald Hall 429B, Pullman, Washington, 99164, USA
- Department of Genetics, School of Medicine, Stanford University, 300 Pasteur Dr. Lane Bldg Room L331, Stanford, CA, 94305, USA
| | - Muh-Ching Yee
- Department of Genetics, School of Medicine, Stanford University, 300 Pasteur Dr. Lane Bldg Room L331, Stanford, CA, 94305, USA
- Stanford Functional Genomics Facility, Stanford, CA, 94305, USA
| | - Victor Dominguez
- Department of Biology, Indiana University, 915 E. Third St, Bloomington, IN, 47405, USA
| | - Mary Andrews
- Department of Biology, Indiana University, 915 E. Third St, Bloomington, IN, 47405, USA
| | - Alexandra Sockell
- Department of Genetics, School of Medicine, Stanford University, 300 Pasteur Dr. Lane Bldg Room L331, Stanford, CA, 94305, USA
| | - Erika Strandberg
- Department of Genetics, School of Medicine, Stanford University, 300 Pasteur Dr. Lane Bldg Room L331, Stanford, CA, 94305, USA
- Biomedical Informatics Training Program, 1265 Welch Road, MSOB, X-215, MC 5479, Stanford, CA, 94305-5479, USA
| | - Donald Livingstone
- Mars, Incorporated, 6885 Elm Street, McLean, VA, 22101, USA
- United States Department of Agriculture-Agriculture Research Service, Subtropical Horticulture Research Station, 13601 Old Cutler Rd, Miami, FL, 33158, USA
| | - Conrad Stack
- Mars, Incorporated, 6885 Elm Street, McLean, VA, 22101, USA
| | - Alberto Romero
- Mars, Incorporated, 6885 Elm Street, McLean, VA, 22101, USA
| | - Pathmanathan Umaharan
- Cocoa Research Centre, The University of the West Indies, St. Augustine, Trinidad and Tobago
| | - Stefan Royaert
- Mars, Incorporated, 6885 Elm Street, McLean, VA, 22101, USA
| | - Nilesh R Tawari
- Computational and Systems Biology, Genome Institute of Singapore, 60 Biopolis Street, Genome, #02-01, Singapore, 138672, Singapore
| | - Pauline Ng
- Computational and Systems Biology, Genome Institute of Singapore, 60 Biopolis Street, Genome, #02-01, Singapore, 138672, Singapore
| | - Osman Gutierrez
- SHRS, USDS-ARS, 13601 Old Cutler Road, Miami, FL, 33158, USA
| | - Wilbert Phillips
- Programa de Mejoramiento de Cacao, CATIE, 7170, Turrialba, Costa Rica
| | - Keithanne Mockaitis
- Department of Biology, Indiana University, 915 E. Third St, Bloomington, IN, 47405, USA
- Pervasive Technology Institute, Indiana University, 2709 E. 10th St., Bloomington, IN, 47408, USA
| | - Carlos D Bustamante
- Department of Genetics, School of Medicine, Stanford University, 300 Pasteur Dr. Lane Bldg Room L331, Stanford, CA, 94305, USA
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44
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Abstract
The population of the Mediterranean island of Sardinia has made important contributions to genome-wide association studies of complex disease traits and, based on ancient DNA (aDNA) studies of mainland Europe, Sardinia is hypothesized to be a unique refuge for early Neolithic ancestry. To provide new insights on the genetic history of this flagship population, we analyzed 3,514 whole-genome sequenced individuals from Sardinia. We find Sardinian samples show elevated levels of shared ancestry with Basque individuals, especially samples from the more historically isolated regions of Sardinia. Our analysis also uniquely illuminates how levels of genetic similarity with mainland aDNA samples varies subtly across the island. Together, our results indicate within-island sub-structure and sex-biased processes have substantially impacted the genetic history of Sardinia. These results give new insight to the demography of ancestral Sardinians and help further the understanding of sharing of disease risk alleles between Sardinia and mainland populations.
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45
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Hlusko LJ. Recent insights into the evolution of quantitative traits in non-human primates. Curr Opin Genet Dev 2018; 53:15-20. [PMID: 29913352 DOI: 10.1016/j.gde.2018.05.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 05/25/2018] [Accepted: 05/31/2018] [Indexed: 10/28/2022]
Abstract
The past few years of genetic research on primate quantitative trait variation have been notable in the diversity of phenotypes explored, ranging from classic skeletal measurements to behavior, through to levels of gene expression, and with observations from both captive and wild populations. These studies demonstrate the importance of captive pedigreed breeding colonies, populations that can be matched to their wild counterparts to enable comparison of genetic architectures. Non-human primate genotype:phenotype maps are essential for placing human variation within an evolutionary framework as well as for gaining insight to human biology. While the demographic history of most primates has been fairly stable since the Late Pleistocene, humans experienced a dramatic population expansion that increased the number of rare, mildly deleterious mutations. These rare genetic variants complicate the genotype:phenotype association because they account for a disproportionate amount of the genetic variance and are harder to detect. The similar physiologies of our closest living relatives may prove to be key for overcoming the hurdles posed by humans' peculiar demographic explosion.
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Affiliation(s)
- Leslea J Hlusko
- Human Evolution Research Center, Department of Integrative Biology, University of California Berkeley, 3040 Valley Life Science Bldg, MC-3140, Berkeley, CA 94720, USA.
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46
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Rougeux C, Bernatchez L, Gagnaire PA. Modeling the Multiple Facets of Speciation-with-Gene-Flow toward Inferring the Divergence History of Lake Whitefish Species Pairs (Coregonus clupeaformis). Genome Biol Evol 2018; 9:2057-2074. [PMID: 28903535 PMCID: PMC5737413 DOI: 10.1093/gbe/evx150] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/01/2017] [Indexed: 02/07/2023] Open
Abstract
Parallel divergence across replicated species pairs occurring in similar environmental contrasts may arise through distinct evolutionary scenarios. Deciphering whether such parallelism actually reflects repeated parallel divergence driven by divergent selection or a single divergence event with subsequent gene flow needs to be ascertained. Reconstructing historical gene flow is therefore of fundamental interest to understand how demography and selection jointly shaped genomic divergence during speciation. Here, we use an extended modeling framework to explore the multiple facets of speciation-with-gene-flow with demo-genetic divergence models that capture both temporal and genomic variation in effective population size and migration rate. We investigate the divergence history of replicate sympatric species pairs of Lake Whitefish (normal benthic and dwarf limnetic) characterized by variable degrees of ecological divergence and reproductive isolation. Genome-wide SNPs were used to document the extent of genetic differentiation in each species pair, and 26 divergence models were fitted and compared with the unfolded joint allele frequency spectrum of each pair. We found evidence that a recent (circa 3,000–4,000 generations) asymmetrical secondary contact between expanding postglacial populations has accompanied Whitefish diversification. Our results suggest that heterogeneous genomic differentiation has emerged through the combined effects of linked selection generating variable rates of lineage sorting across the genome during geographical isolation, and heterogeneous introgression eroding divergence at different rates across the genome upon secondary contact. This study thus provides a new retrospective insight into the historical demographic and selective processes that shaped a continuum of divergence associated with ecological speciation.
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Affiliation(s)
- Clément Rougeux
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Canada
| | - Louis Bernatchez
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Canada
| | - Pierre-Alexandre Gagnaire
- Université de Montpellier, Place Eugène Bataillon, France.,Institut des Sciences de l'Évolution de Montpellier-UMR 5554 UM-CNRS-IRD-EPHE, Place Eugène Bataillon, Montpellier, France
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47
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Martin AR, Karczewski KJ, Kerminen S, Kurki MI, Sarin AP, Artomov M, Eriksson JG, Esko T, Genovese G, Havulinna AS, Kaprio J, Konradi A, Korányi L, Kostareva A, Männikkö M, Metspalu A, Perola M, Prasad RB, Raitakari O, Rotar O, Salomaa V, Groop L, Palotie A, Neale BM, Ripatti S, Pirinen M, Daly MJ. Haplotype Sharing Provides Insights into Fine-Scale Population History and Disease in Finland. Am J Hum Genet 2018; 102:760-775. [PMID: 29706349 DOI: 10.1016/j.ajhg.2018.03.003] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 02/28/2018] [Indexed: 01/23/2023] Open
Abstract
Finland provides unique opportunities to investigate population and medical genomics because of its adoption of unified national electronic health records, detailed historical and birth records, and serial population bottlenecks. We assembled a comprehensive view of recent population history (≤100 generations), the timespan during which most rare-disease-causing alleles arose, by comparing pairwise haplotype sharing from 43,254 Finns to that of 16,060 Swedes, Estonians, Russians, and Hungarians from geographically and linguistically adjacent countries with different population histories. We find much more extensive sharing in Finns, with at least one ≥ 5 cM tract on average between pairs of unrelated individuals. By coupling haplotype sharing with fine-scale birth records from more than 25,000 individuals, we find that although haplotype sharing broadly decays with geographical distance, there are pockets of excess haplotype sharing; individuals from northeast Finland typically share several-fold more of their genome in identity-by-descent segments than individuals from southwest regions. We estimate recent effective population-size changes through time across regions of Finland, and we find that there was more continuous gene flow as Finns migrated from southwest to northeast between the early- and late-settlement regions than was dichotomously described previously. Lastly, we show that haplotype sharing is locally enriched by an order of magnitude among pairs of individuals sharing rare alleles and especially among pairs sharing rare disease-causing variants. Our work provides a general framework for using haplotype sharing to reconstruct an integrative view of recent population history and gain insight into the evolutionary origins of rare variants contributing to disease.
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Affiliation(s)
- Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, 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 Harvard and MIT, Cambridge, MA 02142, USA
| | - Sini Kerminen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland
| | - Mitja I Kurki
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; National Institute for Health and Welfare of Finland, Helsinki 00271, Finland
| | - Mykyta Artomov
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Johan G Eriksson
- National Institute for Health and Welfare of Finland, Helsinki 00271, Finland; Folkhälsan Research Center, Helsinki 00290, Finland; Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki 00014, Finland
| | - Tõnu Esko
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Estonian Genome Center, University of Tartu, Tartu 50090, Estonia
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; National Institute for Health and Welfare of Finland, Helsinki 00271, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland
| | - Alexandra Konradi
- Almazov National Medical Research Centre, Saint Petersburg 197341, Russia; National Research University of Information Technologies, Mechanics, and Optics, Saint Petersburg 197101, Russia
| | - László Korányi
- Heart Center Foundation, Drug Research Centre, Balatonfured H-8230, Hungary
| | - Anna Kostareva
- Almazov National Medical Research Centre, Saint Petersburg 197341, Russia; National Research University of Information Technologies, Mechanics, and Optics, Saint Petersburg 197101, Russia
| | - Minna Männikkö
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu 90014, Finland
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 50090, Estonia
| | - Markus Perola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Estonian Genome Center, University of Tartu, Tartu 50090, Estonia; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku University Hospital, Turku 20520, Finland
| | - Rashmi B Prasad
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University CRC, Skåne University Hospital Malmö, SE-205 02, Malmö, Sweden
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku University Hospital, Turku 20520, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
| | - Oxana Rotar
- Almazov National Medical Research Centre, Saint Petersburg 197341, Russia
| | - Veikko Salomaa
- National Institute for Health and Welfare of Finland, Helsinki 00271, Finland
| | - Leif Groop
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Lund University Diabetes Centre, Department of Clinical Sciences, Lund University CRC, Skåne University Hospital Malmö, SE-205 02, Malmö, Sweden
| | - Aarno Palotie
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland; Helsinki Institute for Information Technology and Department of Mathematics and Statistics, University of Helsinki, 00014 Helsinki, Finland
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki 00014, Finland.
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48
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High-depth whole genome sequencing of an Ashkenazi Jewish reference panel: enhancing sensitivity, accuracy, and imputation. Hum Genet 2018; 137:343-355. [PMID: 29705978 DOI: 10.1007/s00439-018-1886-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Accepted: 04/21/2018] [Indexed: 12/31/2022]
Abstract
While increasingly large reference panels for genome-wide imputation have been recently made available, the degree to which imputation accuracy can be enhanced by population-specific reference panels remains an open question. Here, we sequenced at full-depth (≥ 30×), across two platforms (Illumina X Ten and Complete Genomics, Inc.), a moderately large (n = 738) cohort of samples drawn from the Ashkenazi Jewish population. We developed a series of quality control steps to optimize sensitivity, specificity, and comprehensiveness of variant calls in the reference panel, and then tested the accuracy of imputation against target cohorts drawn from the same population. Quality control (QC) thresholds for the Illumina X Ten platform were identified that permitted highly accurate calling of single nucleotide variants across 94% of the genome. QC procedures also identified numerous regions that are poorly mapped using current reference or alternate assemblies. After stringent QC, the population-specific reference panel produced more accurate and comprehensive imputation results relative to publicly available, large cosmopolitan reference panels, especially in the range of rare variants that may be most critical to further progress in mapping of complex phenotypes. The population-specific reference panel also permitted enhanced filtering of clinically irrelevant variants from personal genomes.
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49
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Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project. Am J Hum Genet 2018; 102:658-675. [PMID: 29551419 DOI: 10.1016/j.ajhg.2018.02.013] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 02/19/2018] [Indexed: 12/11/2022] Open
Abstract
Genomic regions of autozygosity (ROAs) represent segments of individual genomes that are homozygous for haplotypes inherited identical-by-descent (IBD) from a common ancestor. ROAs are nonuniformly distributed across the genome, and increased ROA levels are a reported risk factor for numerous complex diseases. Previously, we hypothesized that long ROAs are enriched for deleterious homozygotes as a result of young haplotypes with recent deleterious mutations-relatively untouched by purifying selection-being paired IBD as a consequence of recent parental relatedness, a pattern supported by ROA and whole-exome sequence data on 27 individuals. Here, we significantly bolster support for our hypothesis and expand upon our original analyses using ROA and whole-genome sequence data on 2,436 individuals from The 1000 Genomes Project. Considering CADD deleteriousness scores, we reaffirm our previous observation that long ROAs are enriched for damaging homozygotes worldwide. We show that strongly damaging homozygotes experience greater enrichment than weaker damaging homozygotes, while overall enrichment varies appreciably among populations. Mendelian disease genes and those encoding FDA-approved drug targets have significantly increased rates of gain in damaging homozygotes with increasing ROA coverage relative to all other genes. In genes implicated in eight complex phenotypes for which ROA levels have been identified as a risk factor, rates of gain in damaging homozygotes vary across phenotypes and populations but frequently differ significantly from non-disease genes. These findings highlight the potential confounding effects of population background in the assessment of associations between ROA levels and complex disease risk, which might underlie reported inconsistencies in ROA-phenotype associations.
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50
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Abstract
This primer provides some background to help non-specialists understand a new theoretical evolutionary genetics study that helps explain why thousands of variants of small effect contribute to complex traits.
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