1
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Temple SD, Waples RK, Browning SR. Modeling recent positive selection using identity-by-descent segments. Am J Hum Genet 2024:S0002-9297(24)00333-1. [PMID: 39362217 DOI: 10.1016/j.ajhg.2024.08.023] [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: 02/20/2024] [Revised: 08/29/2024] [Accepted: 08/30/2024] [Indexed: 10/05/2024] Open
Abstract
Recent positive selection can result in an excess of long identity-by-descent (IBD) haplotype segments overlapping a locus. The statistical methods that we propose here address three major objectives in studying selective sweeps: scanning for regions of interest, identifying possible sweeping alleles, and estimating a selection coefficient s. First, we implement a selection scan to locate regions with excess IBD rates. Second, we estimate the allele frequency and location of an unknown sweeping allele by aggregating over variants that are more abundant in an inferred outgroup with excess IBD rate versus the rest of the sample. Third, we propose an estimator for the selection coefficient and quantify uncertainty using the parametric bootstrap. Comparing against state-of-the-art methods in extensive simulations, we show that our methods are more precise at estimating s when s≥0.015. We also show that our 95% confidence intervals contain s in nearly 95% of our simulations. We apply these methods to study positive selection in European ancestry samples from the Trans-Omics for Precision Medicine project. We analyze eight loci where IBD rates are more than four standard deviations above the genome-wide median, including LCT where the maximum IBD rate is 35 standard deviations above the genome-wide median. Overall, we present robust and accurate approaches to study recent adaptive evolution without knowing the identity of the causal allele or using time series data.
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Affiliation(s)
- Seth D Temple
- Department of Statistics, University of Washington, Seattle, WA, USA.
| | - Ryan K Waples
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA, USA.
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2
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Akbari A, Barton AR, Gazal S, Li Z, Kariminejad M, Perry A, Zeng Y, Mittnik A, Patterson N, Mah M, Zhou X, Price AL, Lander ES, Pinhasi R, Rohland N, Mallick S, Reich D. Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.14.613021. [PMID: 39314480 PMCID: PMC11419161 DOI: 10.1101/2024.09.14.613021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
We present a method for detecting evidence of natural selection in ancient DNA time-series data that leverages an opportunity not utilized in previous scans: testing for a consistent trend in allele frequency change over time. By applying this to 8433 West Eurasians who lived over the past 14000 years and 6510 contemporary people, we find an order of magnitude more genome-wide significant signals than previous studies: 347 independent loci with >99% probability of selection. Previous work showed that classic hard sweeps driving advantageous mutations to fixation have been rare over the broad span of human evolution, but in the last ten millennia, many hundreds of alleles have been affected by strong directional selection. Discoveries include an increase from ~0% to ~20% in 4000 years for the major risk factor for celiac disease at HLA-DQB1; a rise from ~0% to ~8% in 6000 years of blood type B; and fluctuating selection at the TYK2 tuberculosis risk allele rising from ~2% to ~9% from ~5500 to ~3000 years ago before dropping to ~3%. We identify instances of coordinated selection on alleles affecting the same trait, with the polygenic score today predictive of body fat percentage decreasing by around a standard deviation over ten millennia, consistent with the "Thrifty Gene" hypothesis that a genetic predisposition to store energy during food scarcity became disadvantageous after farming. We also identify selection for combinations of alleles that are today associated with lighter skin color, lower risk for schizophrenia and bipolar disease, slower health decline, and increased measures related to cognitive performance (scores on intelligence tests, household income, and years of schooling). These traits are measured in modern industrialized societies, so what phenotypes were adaptive in the past is unclear. We estimate selection coefficients at 9.9 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits.
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Affiliation(s)
- Ali Akbari
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alison R Barton
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Steven Gazal
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Zheng Li
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | | | - Annabel Perry
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yating Zeng
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Alissa Mittnik
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany
| | - Nick Patterson
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matthew Mah
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Alkes L Price
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Ron Pinhasi
- Department of Biology, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Nadin Rohland
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Swapan Mallick
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - David Reich
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
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3
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Wang Y, Allen SL, Reddiex AJ, Chenoweth SF. The impacts of positive selection on genomic variation in Drosophila serrata: Insights from a deep learning approach. Mol Ecol 2024:e17499. [PMID: 39188068 DOI: 10.1111/mec.17499] [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: 03/20/2024] [Revised: 07/22/2024] [Accepted: 08/07/2024] [Indexed: 08/28/2024]
Abstract
This study explores the impact of positive selection on the genetic composition of a Drosophila serrata population in eastern Australia through a comprehensive analysis of 110 whole genome sequences. Utilizing an advanced deep learning algorithm (partialS/HIC) and a range of inferred demographic histories, we identified that approximately 14% of the genome is directly affected by sweeps, with soft sweeps being more prevalent (10.6%) than hard sweeps (2.1%), and partial sweeps being uncommon (1.3%). The algorithm demonstrated robustness to demographic assumptions in classifying complete sweeps but faced challenges in distinguishing neutral regions from partial sweeps and linked regions under demographic misspecification. The findings reveal the indirect influence of sweeps on nearly two-thirds of the genome through linkage, with an over-representation of putatively deleterious variants suggesting that positive selection drags deleterious variants to higher frequency due to hitchhiking with beneficial loci. Gene ontology enrichment analysis further supported our confidence in the accuracy of sweep detection as several traits expected to be under positive selection due to evolutionary arms races (e.g. immunity) were detected in hard sweeps. This study provides valuable insights into the direct and indirect contributions of positive selection in shaping genomic variation in natural populations.
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Affiliation(s)
- Yiguan Wang
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Scott L Allen
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
| | - Adam J Reddiex
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
- Biological Data Science Institute, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Stephen F Chenoweth
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
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4
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Igoshin AV, Romashov GA, Yurchenko AA, Yudin NS, Larkin DM. Scans for Signatures of Selection in Genomes of Wagyu and Buryat Cattle Breeds Reveal Candidate Genes and Genetic Variants for Adaptive Phenotypes and Production Traits. Animals (Basel) 2024; 14:2059. [PMID: 39061521 PMCID: PMC11274160 DOI: 10.3390/ani14142059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 07/10/2024] [Accepted: 07/11/2024] [Indexed: 07/28/2024] Open
Abstract
Past and ongoing selection shapes the genomes of livestock breeds. Identifying such signatures of selection allows for uncovering the genetic bases of affected phenotypes, including economically important traits and environmental adaptations, for the further improvement of breed genetics to respond to climate and economic challenges. Turano-Mongolian cattle are a group of taurine breeds known for their adaptation to extreme environmental conditions and outstanding production performance. Buryat Turano-Mongolian cattle are among the few breeds adapted to cold climates and poor forage. Wagyu, on the other hand, is famous for high productivity and unique top-quality marbled meat. We used hapFLK, the de-correlated composite of multiple signals (DCMS), PBS, and FST methods to search for signatures of selection in their genomes. The scans revealed signals in genes related to cold adaptation (e.g., STAT3, DOCK5, GSTM3, and CXCL8) and food digestibility (SI) in the Buryat breed, and growth and development traits (e.g., RBFOX2 and SHOX2) and marbling (e.g., DGAT1, IQGAP2, RSRC1, and DIP2B) in Wagyu. Several putatively selected genes associated with reproduction, immunity, and resistance to pathogens were found in both breed genomes. The results of our work could be used for creating new productive adapted breeds or improving the extant breeds.
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Affiliation(s)
- Alexander V. Igoshin
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), Novosibirsk 630090, Russia; (A.V.I.)
| | - Grigorii A. Romashov
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), Novosibirsk 630090, Russia; (A.V.I.)
| | - Andrey A. Yurchenko
- INSERM U981, Gustave Roussy Cancer Campus, Université Paris Saclay, 94800 Villejuif, France
| | - Nikolay S. Yudin
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), Novosibirsk 630090, Russia; (A.V.I.)
| | - Denis M. Larkin
- Royal Veterinary College, University of London, London NW1 0TU, UK
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5
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Song H, Chu J, Li W, Li X, Fang L, Han J, Zhao S, Ma Y. A Novel Approach Utilizing Domain Adversarial Neural Networks for the Detection and Classification of Selective Sweeps. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2304842. [PMID: 38308186 PMCID: PMC11005742 DOI: 10.1002/advs.202304842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 01/10/2024] [Indexed: 02/04/2024]
Abstract
The identification and classification of selective sweeps are of great significance for improving the understanding of biological evolution and exploring opportunities for precision medicine and genetic improvement. Here, a domain adaptation sweep detection and classification (DASDC) method is presented to balance the alignment of two domains and the classification performance through a domain-adversarial neural network and its adversarial learning modules. DASDC effectively addresses the issue of mismatch between training data and real genomic data in deep learning models, leading to a significant improvement in its generalization capability, prediction robustness, and accuracy. The DASDC method demonstrates improved identification performance compared to existing methods and excels in classification performance, particularly in scenarios where there is a mismatch between application data and training data. The successful implementation of DASDC in real data of three distinct species highlights its potential as a useful tool for identifying crucial functional genes and investigating adaptive evolutionary mechanisms, particularly with the increasing availability of genomic data.
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Affiliation(s)
- Hui Song
- Key Laboratory of Agricultural Animal GeneticsBreeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhan430070China
| | - Jinyu Chu
- Key Laboratory of Agricultural Animal GeneticsBreeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhan430070China
| | - Wangjiao Li
- Key Laboratory of Agricultural Animal GeneticsBreeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhan430070China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal GeneticsBreeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhan430070China
- Hubei Hongshan LaboratoryWuhan430070China
| | - Lingzhao Fang
- Center for Quantitative Genetics and GenomicsAarhus UniversityAarhus8000Denmark
| | - Jianlin Han
- Key Laboratory of Agricultural Animal GeneticsBreeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhan430070China
- CAAS‐ILRI Joint Laboratory on Livestock and Forage Genetic ResourcesInstitute of Animal ScienceChinese Academy of Agricultural Sciences (CAAS)Beijing100193China
- Livestock Genetics ProgramInternational Livestock Research Institute (ILRI)Nairobi00100Kenya
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal GeneticsBreeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhan430070China
- Hubei Hongshan LaboratoryWuhan430070China
- Lingnan Modern Agricultural Science and Technology Guangdong LaboratoryGuangzhou510642China
| | - Yunlong Ma
- Key Laboratory of Agricultural Animal GeneticsBreeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of AgricultureHuazhong Agricultural UniversityWuhan430070China
- Hubei Hongshan LaboratoryWuhan430070China
- Lingnan Modern Agricultural Science and Technology Guangdong LaboratoryGuangzhou510642China
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6
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Liu S, Luo H, Zhang P, Li Y, Hao D, Zhang S, Song T, Xu T, He S. Adaptive Selection of Cis-regulatory Elements in the Han Chinese. Mol Biol Evol 2024; 41:msae034. [PMID: 38377343 PMCID: PMC10917166 DOI: 10.1093/molbev/msae034] [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: 10/02/2023] [Revised: 01/18/2024] [Accepted: 02/05/2024] [Indexed: 02/22/2024] Open
Abstract
Cis-regulatory elements have an important role in human adaptation to the living environment. However, the lag in population genomic cohort studies and epigenomic studies, hinders the research in the adaptive analysis of cis-regulatory elements in human populations. In this study, we collected 4,013 unrelated individuals and performed a comprehensive analysis of adaptive selection of genome-wide cis-regulatory elements in the Han Chinese. In total, 12.34% of genomic regions are under the influence of adaptive selection, where 1.00% of enhancers and 2.06% of promoters are under positive selection, and 0.06% of enhancers and 0.02% of promoters are under balancing selection. Gene ontology enrichment analysis of these cis-regulatory elements under adaptive selection reveals that many positive selections in the Han Chinese occur in pathways involved in cell-cell adhesion processes, and many balancing selections are related to immune processes. Two classes of adaptive cis-regulatory elements related to cell adhesion were in-depth analyzed, one is the adaptive enhancers derived from neanderthal introgression, leads to lower hyaluronidase level in skin, and brings better performance on UV-radiation resistance to the Han Chinese. Another one is the cis-regulatory elements regulating wound healing, and the results suggest the positive selection inhibits coagulation and promotes angiogenesis and wound healing in the Han Chinese. Finally, we found that many pathogenic alleles, such as risky alleles of type 2 diabetes or schizophrenia, remain in the population due to the hitchhiking effect of positive selections. Our findings will help deepen our understanding of the adaptive evolution of genome regulation in the Han Chinese.
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Affiliation(s)
- Shuai Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huaxia Luo
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Peng Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanyan Li
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Di Hao
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Sijia Zhang
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tingrui Song
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Xu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250117, Shandong, China
| | - Shunmin He
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
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7
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Lawrence ES, Gu W, Bohlender RJ, Anza-Ramirez C, Cole AM, Yu JJ, Hu H, Heinrich EC, O’Brien KA, Vasquez CA, Cowan QT, Bruck PT, Mercader K, Alotaibi M, Long T, Hall JE, Moya EA, Bauk MA, Reeves JJ, Kong MC, Salem RM, Vizcardo-Galindo G, Macarlupu JL, Figueroa-Mujíca R, Bermudez D, Corante N, Gaio E, Fox KP, Salomaa V, Havulinna AS, Murray AJ, Malhotra A, Powel FL, Jain M, Komor AC, Cavalleri GL, Huff CD, Villafuerte FC, Simonson TS. Functional EPAS1/ HIF2A missense variant is associated with hematocrit in Andean highlanders. SCIENCE ADVANCES 2024; 10:eadj5661. [PMID: 38335297 PMCID: PMC10857371 DOI: 10.1126/sciadv.adj5661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 01/10/2024] [Indexed: 02/12/2024]
Abstract
Hypoxia-inducible factor pathway genes are linked to adaptation in both human and nonhuman highland species. EPAS1, a notable target of hypoxia adaptation, is associated with relatively lower hemoglobin concentration in Tibetans. We provide evidence for an association between an adaptive EPAS1 variant (rs570553380) and the same phenotype of relatively low hematocrit in Andean highlanders. This Andean-specific missense variant is present at a modest frequency in Andeans and absent in other human populations and vertebrate species except the coelacanth. CRISPR-base-edited human cells with this variant exhibit shifts in hypoxia-regulated gene expression, while metabolomic analyses reveal both genotype and phenotype associations and validation in a lowland population. Although this genocopy of relatively lower hematocrit in Andean highlanders parallels well-replicated findings in Tibetans, it likely involves distinct pathway responses based on a protein-coding versus noncoding variants, respectively. These findings illuminate how unique variants at EPAS1 contribute to the same phenotype in Tibetans and a subset of Andean highlanders despite distinct evolutionary trajectories.
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Affiliation(s)
- Elijah S. Lawrence
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Wanjun Gu
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Ryan J. Bohlender
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cecilia Anza-Ramirez
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Amy M. Cole
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - James J. Yu
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Hao Hu
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Erica C. Heinrich
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Division of Biomedical Sciences, School of Medicine, University of California, Riverside, Riverside, CA, USA
| | - Katie A. O’Brien
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, UK
| | - Carlos A. Vasquez
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA
| | - Quinn T. Cowan
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA
| | - Patrick T. Bruck
- Department of Anthropology and Global Health, University of California, San Diego, La Jolla, CA, USA
| | - Kysha Mercader
- Department of Medicine and Pharmacology, University of California, San Diego, La Jolla, CA, USA
| | - Mona Alotaibi
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Medicine and Pharmacology, University of California, San Diego, La Jolla, CA, USA
| | - Tao Long
- Department of Medicine and Pharmacology, University of California, San Diego, La Jolla, CA, USA
- Sapient Bioanalytics, LLC, San Diego, CA, USA
| | - James E. Hall
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Esteban A. Moya
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Marco A. Bauk
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jennifer J. Reeves
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Mitchell C. Kong
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Rany M. Salem
- Herbert Wertheim School of Public Health and Longevity Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Gustavo Vizcardo-Galindo
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Jose-Luis Macarlupu
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Rómulo Figueroa-Mujíca
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Daniela Bermudez
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Noemi Corante
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Eduardo Gaio
- Laboratório de Fisiologia Respiratória, Faculdade de Medicina, Universidade de Brasília, Brasília, Brazil
| | - Keolu P. Fox
- Department of Anthropology and Global Health, University of California, San Diego, La Jolla, CA, USA
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Aki S. Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM-HiLIFE), Helsinki, Finland
| | - Andrew J. Murray
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, UK
| | - Atul Malhotra
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Frank L. Powel
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Mohit Jain
- Department of Medicine and Pharmacology, University of California, San Diego, La Jolla, CA, USA
- Sapient Bioanalytics, LLC, San Diego, CA, USA
| | - Alexis C. Komor
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA
| | - Gianpiero L. Cavalleri
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Chad D. Huff
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Francisco C. Villafuerte
- Laboratorio de Fisiología Comparada/Fisiología de del Transporte de Oxígeno-LID, Departamento de Ciencias Biológicas y Fisiológicas, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Tatum S. Simonson
- Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
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Yin ZT, Li XQ, Sun YX, Smith J, Hincke M, Yang N, Hou ZC. Selection on the promoter regions plays an important role in complex traits during duck domestication. BMC Biol 2023; 21:303. [PMID: 38129834 PMCID: PMC10740227 DOI: 10.1186/s12915-023-01801-0] [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: 02/01/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Identifying the key factors that underlie complex traits during domestication is a great challenge for evolutionary and biological studies. In addition to the protein-coding region differences caused by variants, a large number of variants are located in the noncoding regions containing multiple types of regulatory elements. However, the roles of accumulated variants in gene regulatory elements during duck domestication and economic trait improvement are poorly understood. RESULTS We constructed a genomics, transcriptomics, and epigenomics map of the duck genome and assessed the evolutionary forces that have been in play across the whole genome during domestication. In total, 304 (42.94%) gene promoters have been specifically selected in Pekin duck among all selected genes. Joint multi-omics analysis reveals that 218 genes (72.01%) with selected promoters are located in open and active chromatin, and 267 genes (87.83%) with selected promoters were highly and differentially expressed in domestic trait-related tissues. One important candidate gene ELOVL3, with a strong signature of differentiation on the core promoter region, is known to regulate fatty acid elongation. Functional experiments showed that the nearly fixed variants in the top selected ELOVL3 promoter in Pekin duck decreased binding ability with HLF and increased gene expression, with the overexpression of ELOVL3 able to increase lipid deposition and unsaturated fatty acid enrichment. CONCLUSIONS This study presents genome resequencing, RNA-Seq, Hi-C, and ATAC-Seq data of mallard and Pekin duck, showing that selection of the gene promoter region plays an important role in gene expression and phenotypic changes during domestication and highlights that the variants of the ELOVL3 promoter may have multiple effects on fat and long-chain fatty acid content in ducks.
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Affiliation(s)
- Zhong-Tao Yin
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, MARA, China Agricultural University, No. 2 Yuanmingyuan West Rd, Beijing, 100193, China
| | - Xiao-Qin Li
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, MARA, China Agricultural University, No. 2 Yuanmingyuan West Rd, Beijing, 100193, China
| | - Yun-Xiao Sun
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, MARA, China Agricultural University, No. 2 Yuanmingyuan West Rd, Beijing, 100193, China
| | - Jacqueline Smith
- The Roslin Institute & R(D)SVS, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK
| | - Maxwell Hincke
- Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa, ON, K1H 8M5, Canada
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, MARA, China Agricultural University, No. 2 Yuanmingyuan West Rd, Beijing, 100193, China.
| | - Zhuo-Cheng Hou
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, MARA, China Agricultural University, No. 2 Yuanmingyuan West Rd, Beijing, 100193, China.
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9
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Schrider DR. Allelic gene conversion softens selective sweeps. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.05.570141. [PMID: 38106127 PMCID: PMC10723294 DOI: 10.1101/2023.12.05.570141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The prominence of positive selection, in which beneficial mutations are favored by natural selection and rapidly increase in frequency, is a subject of intense debate. Positive selection can result in selective sweeps, in which the haplotype(s) bearing the adaptive allele "sweep" through the population, thereby removing much of the genetic diversity from the region surrounding the target of selection. Two models of selective sweeps have been proposed: classical sweeps, or "hard sweeps", in which a single copy of the adaptive allele sweeps to fixation, and "soft sweeps", in which multiple distinct copies of the adaptive allele leave descendants after the sweep. Soft sweeps can be the outcome of recurrent mutation to the adaptive allele, or the presence of standing genetic variation consisting of multiple copies of the adaptive allele prior to the onset of selection. Importantly, soft sweeps will be common when populations can rapidly adapt to novel selective pressures, either because of a high mutation rate or because adaptive alleles are already present. The prevalence of soft sweeps is especially controversial, and it has been noted that selection on standing variation or recurrent mutations may not always produce soft sweeps. Here, we show that the inverse is true: selection on single-origin de novo mutations may often result in an outcome that is indistinguishable from a soft sweep. This is made possible by allelic gene conversion, which "softens" hard sweeps by copying the adaptive allele onto multiple genetic backgrounds, a process we refer to as a "pseudo-soft" sweep. We carried out a simulation study examining the impact of gene conversion on sweeps from a single de novo variant in models of human, Drosophila, and Arabidopsis populations. The fraction of simulations in which gene conversion had produced multiple haplotypes with the adaptive allele upon fixation was appreciable. Indeed, under realistic demographic histories and gene conversion rates, even if selection always acts on a single-origin mutation, sweeps involving multiple haplotypes are more likely than hard sweeps in large populations, especially when selection is not extremely strong. Thus, even when the mutation rate is low or there is no standing variation, hard sweeps are expected to be the exception rather than the rule in large populations. These results also imply that the presence of signatures of soft sweeps does not necessarily mean that adaptation has been especially rapid or is not mutation limited.
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Affiliation(s)
- Daniel R Schrider
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599
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10
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Roca-Umbert A, Garcia-Calleja J, Vogel-González M, Fierro-Villegas A, Ill-Raga G, Herrera-Fernández V, Bosnjak A, Muntané G, Gutiérrez E, Campelo F, Vicente R, Bosch E. Human genetic adaptation related to cellular zinc homeostasis. PLoS Genet 2023; 19:e1010950. [PMID: 37747921 PMCID: PMC10553801 DOI: 10.1371/journal.pgen.1010950] [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: 02/28/2023] [Revised: 10/05/2023] [Accepted: 08/31/2023] [Indexed: 09/27/2023] Open
Abstract
SLC30A9 encodes a ubiquitously zinc transporter (ZnT9) and has been consistently suggested as a candidate for positive selection in humans. However, no direct adaptive molecular phenotype has been demonstrated. Our results provide evidence for directional selection operating in two major complementary haplotypes in Africa and East Asia. These haplotypes are associated with differential gene expression but also differ in the Met50Val substitution (rs1047626) in ZnT9, which we show is found in homozygosis in the Denisovan genome and displays accompanying signatures suggestive of archaic introgression. Although we found no significant differences in systemic zinc content between individuals with different rs1047626 genotypes, we demonstrate that the expression of the derived isoform (ZnT9 50Val) in HEK293 cells shows a gain of function when compared with the ancestral (ZnT9 50Met) variant. Notably, the ZnT9 50Val variant was found associated with differences in zinc handling by the mitochondria and endoplasmic reticulum, with an impact on mitochondrial metabolism. Given the essential role of the mitochondria in skeletal muscle and since the derived allele at rs1047626 is known to be associated with greater susceptibility to several neuropsychiatric traits, we propose that adaptation to cold may have driven this selection event, while also impacting predisposition to neuropsychiatric disorders in modern humans.
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Affiliation(s)
- Ana Roca-Umbert
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - Jorge Garcia-Calleja
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - Marina Vogel-González
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Alejandro Fierro-Villegas
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Gerard Ill-Raga
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Víctor Herrera-Fernández
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Anja Bosnjak
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Gerard Muntané
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira i Virgili, Reus, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Esteban Gutiérrez
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Felix Campelo
- ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Rubén Vicente
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
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11
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Meadows JRS, Kidd JM, Wang GD, Parker HG, Schall PZ, Bianchi M, Christmas MJ, Bougiouri K, Buckley RM, Hitte C, Nguyen AK, Wang C, Jagannathan V, Niskanen JE, Frantz LAF, Arumilli M, Hundi S, Lindblad-Toh K, Ginja C, Agustina KK, André C, Boyko AR, Davis BW, Drögemüller M, Feng XY, Gkagkavouzis K, Iliopoulos G, Harris AC, Hytönen MK, Kalthoff DC, Liu YH, Lymberakis P, Poulakakis N, Pires AE, Racimo F, Ramos-Almodovar F, Savolainen P, Venetsani S, Tammen I, Triantafyllidis A, vonHoldt B, Wayne RK, Larson G, Nicholas FW, Lohi H, Leeb T, Zhang YP, Ostrander EA. Genome sequencing of 2000 canids by the Dog10K consortium advances the understanding of demography, genome function and architecture. Genome Biol 2023; 24:187. [PMID: 37582787 PMCID: PMC10426128 DOI: 10.1186/s13059-023-03023-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 07/25/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND The international Dog10K project aims to sequence and analyze several thousand canine genomes. Incorporating 20 × data from 1987 individuals, including 1611 dogs (321 breeds), 309 village dogs, 63 wolves, and four coyotes, we identify genomic variation across the canid family, setting the stage for detailed studies of domestication, behavior, morphology, disease susceptibility, and genome architecture and function. RESULTS We report the analysis of > 48 M single-nucleotide, indel, and structural variants spanning the autosomes, X chromosome, and mitochondria. We discover more than 75% of variation for 239 sampled breeds. Allele sharing analysis indicates that 94.9% of breeds form monophyletic clusters and 25 major clades. German Shepherd Dogs and related breeds show the highest allele sharing with independent breeds from multiple clades. On average, each breed dog differs from the UU_Cfam_GSD_1.0 reference at 26,960 deletions and 14,034 insertions greater than 50 bp, with wolves having 14% more variants. Discovered variants include retrogene insertions from 926 parent genes. To aid functional prioritization, single-nucleotide variants were annotated with SnpEff and Zoonomia phyloP constraint scores. Constrained positions were negatively correlated with allele frequency. Finally, the utility of the Dog10K data as an imputation reference panel is assessed, generating high-confidence calls across varied genotyping platform densities including for breeds not included in the Dog10K collection. CONCLUSIONS We have developed a dense dataset of 1987 sequenced canids that reveals patterns of allele sharing, identifies likely functional variants, informs breed structure, and enables accurate imputation. Dog10K data are publicly available.
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Affiliation(s)
- Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden.
| | - Jeffrey M Kidd
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA.
| | - Guo-Dong Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Heidi G Parker
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Peter Z Schall
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA
| | - Matteo Bianchi
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Matthew J Christmas
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Katia Bougiouri
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Øster Voldgade 5-7, 1350, Copenhagen, Denmark
| | - Reuben M Buckley
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Christophe Hitte
- University of Rennes, CNRS, Institute Genetics and Development Rennes - UMR6290, 35000, Rennes, France
| | - Anthony K Nguyen
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA
| | - Chao Wang
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Vidhya Jagannathan
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Julia E Niskanen
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Laurent A F Frantz
- School of Biological and Behavioural Sciences, Queen Mary University of London, London E14NS, UK and Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, D-80539, Munich, Germany
| | - Meharji Arumilli
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Sruthi Hundi
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Catarina Ginja
- BIOPOLIS-CIBIO-InBIO-Centro de Investigação Em Biodiversidade E Recursos Genéticos - ArchGen Group, Universidade Do Porto, 4485-661, Vairão, Portugal
| | | | - Catherine André
- University of Rennes, CNRS, Institute Genetics and Development Rennes - UMR6290, 35000, Rennes, France
| | - Adam R Boyko
- Department of Biomedical Sciences, Cornell University, 930 Campus Road, Ithaca, NY, 14853, USA
| | - Brian W Davis
- Department of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA
| | - Michaela Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Xin-Yao Feng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Konstantinos Gkagkavouzis
- Department of Genetics, School of Biology, ), Aristotle University of Thessaloniki, Thessaloniki, Macedonia 54124, Greece and Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation (CIRI-AUTH, Balkan Center, Thessaloniki, Greece
| | - Giorgos Iliopoulos
- NGO "Callisto", Wildlife and Nature Conservation Society, 54621, Thessaloniki, Greece
| | - Alexander C Harris
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Marjo K Hytönen
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Daniela C Kalthoff
- NGO "Callisto", Wildlife and Nature Conservation Society, 54621, Thessaloniki, Greece
| | - Yan-Hu Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Petros Lymberakis
- Natural History Museum of Crete & Department of Biology, University of Crete, 71202, Irakleio, Greece
- Biology Department, School of Sciences and Engineering, University of Crete, Heraklion, Greece
- Palaeogenomics and Evolutionary Genetics Lab, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology - Hellas (FORTH), Heraklion, Greece
| | - Nikolaos Poulakakis
- Natural History Museum of Crete & Department of Biology, University of Crete, 71202, Irakleio, Greece
- Biology Department, School of Sciences and Engineering, University of Crete, Heraklion, Greece
- Palaeogenomics and Evolutionary Genetics Lab, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology - Hellas (FORTH), Heraklion, Greece
| | - Ana Elisabete Pires
- BIOPOLIS-CIBIO-InBIO-Centro de Investigação Em Biodiversidade E Recursos Genéticos - ArchGen Group, Universidade Do Porto, 4485-661, Vairão, Portugal
| | - Fernando Racimo
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Øster Voldgade 5-7, 1350, Copenhagen, Denmark
| | | | - Peter Savolainen
- Department of Gene Technology, Science for Life Laboratory, KTH - Royal Institute of Technology, 17121, Solna, Sweden
| | - Semina Venetsani
- Department of Genetics, School of Biology, Aristotle University of Thessaloniki, 54124, Thessaloniki, Macedonia, Greece
| | - Imke Tammen
- Sydney School of Veterinary Science, The University of Sydney, Sydney, NSW, 2570, Australia
| | - Alexandros Triantafyllidis
- Department of Genetics, School of Biology, ), Aristotle University of Thessaloniki, Thessaloniki, Macedonia 54124, Greece and Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation (CIRI-AUTH, Balkan Center, Thessaloniki, Greece
| | - Bridgett vonHoldt
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, 08544, USA
| | - Robert K Wayne
- Department of Ecology and Evolutionary Biology, Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095-7246, USA
| | - Greger Larson
- Palaeogenomics and Bio-Archaeology Research Network, School of Archaeology, University of Oxford, Oxford, OX1 3TG, UK
| | - Frank W Nicholas
- Sydney School of Veterinary Science, The University of Sydney, Sydney, NSW, 2570, Australia
| | - Hannes Lohi
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Tosso Leeb
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Elaine A Ostrander
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA.
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12
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Tobler R, Souilmi Y, Huber CD, Bean N, Turney CSM, Grey ST, Cooper A. The role of genetic selection and climatic factors in the dispersal of anatomically modern humans out of Africa. Proc Natl Acad Sci U S A 2023; 120:e2213061120. [PMID: 37220274 PMCID: PMC10235988 DOI: 10.1073/pnas.2213061120] [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: 07/29/2022] [Accepted: 03/14/2023] [Indexed: 05/25/2023] Open
Abstract
The evolutionarily recent dispersal of anatomically modern humans (AMH) out of Africa (OoA) and across Eurasia provides a unique opportunity to examine the impacts of genetic selection as humans adapted to multiple new environments. Analysis of ancient Eurasian genomic datasets (~1,000 to 45,000 y old) reveals signatures of strong selection, including at least 57 hard sweeps after the initial AMH movement OoA, which have been obscured in modern populations by extensive admixture during the Holocene. The spatiotemporal patterns of these hard sweeps provide a means to reconstruct early AMH population dispersals OoA. We identify a previously unsuspected extended period of genetic adaptation lasting ~30,000 y, potentially in the Arabian Peninsula area, prior to a major Neandertal genetic introgression and subsequent rapid dispersal across Eurasia as far as Australia. Consistent functional targets of selection initiated during this period, which we term the Arabian Standstill, include loci involved in the regulation of fat storage, neural development, skin physiology, and cilia function. Similar adaptive signatures are also evident in introgressed archaic hominin loci and modern Arctic human groups, and we suggest that this signal represents selection for cold adaptation. Surprisingly, many of the candidate selected loci across these groups appear to directly interact and coordinately regulate biological processes, with a number associated with major modern diseases including the ciliopathies, metabolic syndrome, and neurodegenerative disorders. This expands the potential for ancestral human adaptation to directly impact modern diseases, providing a platform for evolutionary medicine.
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Affiliation(s)
- Raymond Tobler
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
| | - Yassine Souilmi
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
- Environment Institute, The University of Adelaide, Adelaide, SA5005, Australia
| | - Christian D. Huber
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
| | - Nigel Bean
- Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, SA5005, Australia
- School of Mathematical Sciences, The University of Adelaide, Adelaide, SA5005, Australia
| | - Chris S. M. Turney
- Division of Research, University of Technology Sydney, Ultimo, NSW2007, Australia
| | - Shane T. Grey
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, NSW2052, Australia
- Transplantation Immunology Group, Translation Science Pillar, Garvan Institute of Medical Research, Darlinghurst, NSW2010, Australia
| | - Alan Cooper
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
- Blue Sky Genetics, Ashton, SA5137, Australia
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13
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Pandey D, Harris M, Garud NR, Narasimhan VM. Understanding natural selection in Holocene Europe using multi-locus genotype identity scans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.24.538113. [PMID: 37163039 PMCID: PMC10168228 DOI: 10.1101/2023.04.24.538113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Ancient DNA (aDNA) has been a revolutionary technology in understanding human history but has not been used extensively to study natural selection as large sample sizes to study allele frequency changes over time have thus far not been available. Here, we examined a time transect of 708 published samples over the past 7,000 years of European history using multi-locus genotype-based selection scans. As aDNA data is affected by high missingness, ascertainment bias, DNA damage, random allele calling, and is unphased, we first validated our selection scan, G 12 a n c i e n t , on simulated data resembling aDNA under a demographic model that captures broad features of the allele frequency spectrum of European genomes as well as positive controls that have been previously identified and functionally validated in modern European datasets on data from ancient individuals from time periods very close to the present time. We then applied our statistic to the aDNA time transect to detect and resolve the timing of natural selection occurring genome wide and found several candidates of selection across the different time periods that had not been picked up by selection scans using single SNP allele frequency approaches. In addition, enrichment analysis discovered multiple categories of complex traits that might be under adaptation across these periods. Our results demonstrate the utility of applying different types of selection scans to aDNA to uncover putative selection signals at loci in the ancient past that might have been masked in modern samples.
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Affiliation(s)
- Devansh Pandey
- Department of Integrative Biology, The University of Texas at Austin
| | - Mariana Harris
- Department of Computational Medicine, University of California, Los Angeles
| | - Nandita R Garud
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles
- Department of Human Genetics, University of California, Los Angeles
| | - Vagheesh M Narasimhan
- Department of Integrative Biology, The University of Texas at Austin
- Department of Statistics and Data Science, The University of Texas at Austin
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14
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Lorenzini PA, Gusareva ES, Ghosh AG, Ramli NAB, Preiser PR, Kim HL. Population-specific positive selection on low CR1 expression in malaria-endemic regions. PLoS One 2023; 18:e0280282. [PMID: 36626386 PMCID: PMC9831336 DOI: 10.1371/journal.pone.0280282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 12/25/2022] [Indexed: 01/11/2023] Open
Abstract
Complement Receptor Type 1 (CR1) is a malaria-associated gene that encodes a transmembrane receptor of erythrocytes and is crucial for malaria parasite invasion. The expression of CR1 contributes to the rosetting of erythrocytes in the brain bloodstream, causing cerebral malaria, the most severe form of the disease. Here, we study the history of adaptation against malaria by analyzing selection signals in the CR1 gene. We used whole-genome sequencing datasets of 907 healthy individuals from malaria-endemic and non-endemic populations. We detected robust positive selection in populations from the hyperendemic regions of East India and Papua New Guinea. Importantly, we identified a new adaptive variant, rs12034598, which is associated with a slower rate of erythrocyte sedimentation and is linked with a variant associated with low levels of CR1 expression. The combination of the variants likely drives natural selection. In addition, we identified a variant rs3886100 under positive selection in West Africans, which is also related to a low level of CR1 expression in the brain. Our study shows the fine-resolution history of positive selection in the CR1 gene and suggests a population-specific history of CR1 adaptation to malaria. Notably, our novel approach using population genomic analyses allows the identification of protective variants that reduce the risk of malaria infection without the need for patient samples or malaria individual medical records. Our findings contribute to understanding of human adaptation against cerebral malaria.
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Affiliation(s)
- Paolo Alberto Lorenzini
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
| | - Elena S. Gusareva
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Amit Gourav Ghosh
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
| | - Nurul Adilah Binte Ramli
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
| | - Peter Rainer Preiser
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Hie Lim Kim
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- The GenomeAsia 100K Consortium, Singapore, Singapore
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- * E-mail:
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15
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Prioritizing autoimmunity risk variants for functional analyses by fine-mapping mutations under natural selection. Nat Commun 2022; 13:7069. [PMID: 36400766 PMCID: PMC9674589 DOI: 10.1038/s41467-022-34461-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 10/25/2022] [Indexed: 11/19/2022] Open
Abstract
Pathogen-driven selection shaped adaptive mutations in immunity genes, including those contributing to inflammatory disorders. Functional characterization of such adaptive variants can shed light on disease biology and past adaptations. This popular idea, however, was difficult to test due to challenges in pinpointing adaptive mutations in selection footprints. In this study, using a local-tree-based approach, we show that 28% of risk loci (153/535) in 21 inflammatory disorders bear footprints of moderate and weak selection, and part of them are population specific. Weak selection footprints allow partial fine-mapping, and we show that in 19% (29/153) of the risk loci under selection, candidate disease variants are hitchhikers, and only in 39% of cases they are likely selection targets. We predict function for a subset of these selected SNPs and highlight examples of antagonistic pleiotropy. We conclude by offering disease variants under selection that can be tested functionally using infectious agents and other stressors to decipher the poorly understood link between environmental stressors and genetic risk in inflammatory conditions.
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16
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Lee J, Lee J, Jeon S, Lee J, Jang I, Yang JO, Park S, Lee B, Choi J, Choi BO, Gee HY, Oh J, Jang IJ, Lee S, Baek D, Koh Y, Yoon SS, Kim YJ, Chae JH, Park WY, Bhak JH, Choi M. A database of 5305 healthy Korean individuals reveals genetic and clinical implications for an East Asian population. Exp Mol Med 2022; 54:1862-1871. [PMID: 36323850 PMCID: PMC9628380 DOI: 10.1038/s12276-022-00871-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/21/2022] [Accepted: 08/08/2022] [Indexed: 11/29/2022] Open
Abstract
Despite substantial advances in disease genetics, studies to date have largely focused on individuals of European descent. This limits further discoveries of novel functional genetic variants in other ethnic groups. To alleviate the paucity of East Asian population genome resources, we established the Korean Variant Archive 2 (KOVA 2), which is composed of 1896 whole-genome sequences and 3409 whole-exome sequences from healthy individuals of Korean ethnicity. This is the largest genome database from the ethnic Korean population to date, surpassing the 1909 Korean individuals deposited in gnomAD. The variants in KOVA 2 displayed all the known genetic features of those from previous genome databases, and we compiled data from Korean-specific runs of homozygosity, positively selected intervals, and structural variants. In doing so, we found loci, such as the loci of ADH1A/1B and UHRF1BP1, that are strongly selected in the Korean population relative to other East Asian populations. Our analysis of allele ages revealed a correlation between variant functionality and evolutionary age. The data can be browsed and downloaded from a public website ( https://www.kobic.re.kr/kova/ ). We anticipate that KOVA 2 will serve as a valuable resource for genetic studies involving East Asian populations.
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Affiliation(s)
- Jeongeun Lee
- grid.31501.360000 0004 0470 5905Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul, 03080 Republic of Korea
| | - Jean Lee
- grid.31501.360000 0004 0470 5905Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
| | - Sungwon Jeon
- grid.42687.3f0000 0004 0381 814XDepartment of Biomedical Engineering, College of Information and Biotechnology, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Jeongha Lee
- grid.31501.360000 0004 0470 5905Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
| | - Insu Jang
- grid.249967.70000 0004 0636 3099Korea BioInformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141 Republic of Korea
| | - Jin Ok Yang
- grid.249967.70000 0004 0636 3099Korea BioInformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141 Republic of Korea ,grid.37172.300000 0001 2292 0500Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141 Republic of Korea
| | - Soojin Park
- grid.31501.360000 0004 0470 5905Department of Pediatrics, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
| | - Byungwook Lee
- grid.249967.70000 0004 0636 3099Korea BioInformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141 Republic of Korea
| | - Jinwook Choi
- grid.31501.360000 0004 0470 5905Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul, 03080 Republic of Korea ,grid.31501.360000 0004 0470 5905Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
| | - Byung-Ok Choi
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351 Republic of Korea
| | - Heon Yung Gee
- grid.15444.300000 0004 0470 5454Department of Pharmacology, Brain Korea 21 PLUS Project for Medical Sciences, Yonsei University College of Medicine, Seoul, 03722 Republic of Korea
| | - Jaeseong Oh
- grid.31501.360000 0004 0470 5905Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080 Republic of Korea
| | - In-Jin Jang
- grid.31501.360000 0004 0470 5905Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080 Republic of Korea
| | - Sanghyuk Lee
- grid.255649.90000 0001 2171 7754Department of Bio-Information Science, Ewha Womans University, Seoul, 03760 Republic of Korea
| | - Daehyun Baek
- grid.31501.360000 0004 0470 5905School of Biological Sciences, Seoul National University, Seoul, 08826 Republic of Korea
| | - Youngil Koh
- grid.412484.f0000 0001 0302 820XDepartment of Internal Medicine, Seoul National University Hospital, Seoul, 03080 Republic of Korea
| | - Sung-Soo Yoon
- grid.412484.f0000 0001 0302 820XDepartment of Internal Medicine, Seoul National University Hospital, Seoul, 03080 Republic of Korea
| | - Young-Joon Kim
- grid.15444.300000 0004 0470 5454Department of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul, 03722 Republic of Korea
| | - Jong-Hee Chae
- grid.31501.360000 0004 0470 5905Department of Pediatrics, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea ,grid.412484.f0000 0001 0302 820XDepartment of Genomic Medicine, Seoul National University Hospital, Seoul, 03080 Republic of Korea
| | - Woong-Yang Park
- grid.414964.a0000 0001 0640 5613Samsung Genome Institute, Samsung Medical Center, Seoul, 06351 Republic of Korea
| | - Jong Hwa Bhak
- grid.42687.3f0000 0004 0381 814XDepartment of Biomedical Engineering, College of Information and Biotechnology, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Murim Choi
- grid.31501.360000 0004 0470 5905Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
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17
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Naji MM, Jiang Y, Utsunomiya YT, Rosen BD, Sölkner J, Wang C, Jiang L, Zhang Q, Zhang Y, Ding X, Mészáros G. Favored single nucleotide variants identified using whole genome Re-sequencing of Austrian and Chinese cattle breeds. Front Genet 2022; 13:974787. [PMID: 36238155 PMCID: PMC9552183 DOI: 10.3389/fgene.2022.974787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 08/29/2022] [Indexed: 11/25/2022] Open
Abstract
Cattle have been essential for the development of human civilization since their first domestication few thousand years ago. Since then, they have spread across vast geographic areas following human activities. Throughout generations, the cattle genome has been shaped with detectable signals induced by various evolutionary processes, such as natural and human selection processes and demographic events. Identifying such signals, called selection signatures, is one of the primary goals of population genetics. Previous studies used various selection signature methods and normalized the outputs score using specific windows, in kbp or based on the number of SNPs, to identify the candidate regions. The recent method of iSAFE claimed for high accuracy in pinpointing the candidate SNPs. In this study, we analyzed whole-genome resequencing (WGS) data of ten individuals from Austrian Fleckvieh (Bos taurus) and fifty individuals from 14 Chinese indigenous breeds (Bos taurus, Bos taurus indicus, and admixed). Individual WGS reads were aligned to the cattle reference genome of ARS. UCD1.2 and subsequently undergone single nucleotide variants (SNVs) calling pipeline using GATK. Using these SNVs, we examined the population structure using principal component and admixture analysis. Then we refined selection signature candidates using the iSAFE program and compared it with the classical iHS approach. Additionally, we run Fst population differentiation from these two cattle groups. We found gradual changes of taurine in north China to admixed and indicine to the south. Based on the population structure and the number of individuals, we grouped samples to Fleckvieh, three Chinese taurines (Kazakh, Mongolian, Yanbian), admixed individuals (CHBI_Med), indicine individuals (CHBI_Low), and a combination of admixed and indicine (CHBI) for performing iSAFE and iHS tests. There were more significant SNVs identified using iSAFE than the iHS for the candidate of positive selection and more detectable signals in taurine than in indicine individuals. However, combining admixed and indicine individuals decreased the iSAFE signals. From both within-population tests, significant SNVs are linked to the olfactory receptors, production, reproduction, and temperament traits in taurine cattle, while heat and parasites tolerance in the admixed individuals. Fst test suggests similar patterns of population differentiation between Fleckvieh and three Chinese taurine breeds against CHBI. Nevertheless, there are genes shared only among the Chinese taurine, such as PAX5, affecting coat color, which might drive the differences between these yellowish coated breeds, and those in the greater Far East region.
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Affiliation(s)
- Maulana M. Naji
- University of Natural Resources and Life Sciences, Vienna, Austria
| | - Yifan Jiang
- China Agricultural University, Beijing, China
| | - Yuri T. Utsunomiya
- Department of Production and Animal Health, School of Veterinary Medicine, São Paulo State University (Unesp), Araçatuba, Brazil
| | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, USDA‐ARS, Beltsville, MD, United States
| | - Johann Sölkner
- University of Natural Resources and Life Sciences, Vienna, Austria
| | | | - Li Jiang
- China Agricultural University, Beijing, China
| | - Qin Zhang
- China Agricultural University, Beijing, China
| | - Yi Zhang
- China Agricultural University, Beijing, China
| | - Xiangdong Ding
- China Agricultural University, Beijing, China
- *Correspondence: Xiangdong Ding, ; Gábor Mészáros,
| | - Gábor Mészáros
- University of Natural Resources and Life Sciences, Vienna, Austria
- *Correspondence: Xiangdong Ding, ; Gábor Mészáros,
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18
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Tang J, Huang M, He S, Zeng J, Zhu H. Uncovering the extensive trade-off between adaptive evolution and disease susceptibility. Cell Rep 2022; 40:111351. [PMID: 36103812 DOI: 10.1016/j.celrep.2022.111351] [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: 03/31/2022] [Revised: 06/13/2022] [Accepted: 08/23/2022] [Indexed: 11/03/2022] Open
Abstract
Favored mutations in the human genome may make the carriers adapt to changing environments and lifestyles but also susceptible to specific diseases. The scale and details of the trade-off between adaptive evolution and disease susceptibility are unclear because most favored mutations in different populations remain unidentified. As no statistical test can discriminate favored mutations from nearby hitchhiking neutral ones, we report a deep-learning network (DeepFavored) to integrate multiple statistical tests and divide identifying favored mutations into two subtasks. We identify favored mutations in three human populations and analyzed the correlation between favored/hitchhiking mutations and genome-wide association study (GWAS) sites. Both favored and hitchhiking neutral mutations are enriched in GWAS sites with population-specific features, and the enrichment and population specificity are prominent in genes in specific Gene Ontology (GO) terms. These provide evidence for extensive and population-specific trade-offs between adaptive evolution and disease susceptibility. The unveiled scale helps understand and investigate differences and diseases of humans.
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Affiliation(s)
- Ji Tang
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Maosheng Huang
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; School of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Sha He
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Junxiang Zeng
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Hao Zhu
- Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China.
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19
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Hernandez-Beeftink T, Marcelino-Rodríguez I, Guillen-Guio B, Rodríguez-Pérez H, Lorenzo-Salazar JM, Corrales A, Díaz-de Usera A, González-Montelongo R, Domínguez D, Espinosa E, Villar J, Flores C. Admixture Mapping of Sepsis in European Individuals With African Ancestries. Front Med (Lausanne) 2022; 9:754440. [PMID: 35345767 PMCID: PMC8957104 DOI: 10.3389/fmed.2022.754440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 01/24/2022] [Indexed: 11/30/2022] Open
Abstract
Sepsis is a severe systemic inflammatory response to infections that is accompanied by organ dysfunction. Although the ancestral genetic background is a relevant factor for sepsis susceptibility, there is a lack of studies using the genetic singularities of a recently admixed population to identify loci involved in sepsis susceptibility. Here we aimed to discover new sepsis loci by completing the first admixture mapping study of sepsis in Canary Islanders, leveraging their distinctive genetic makeup as a mixture of Europeans and African ancestries. We used a case-control approach and inferred local ancestry blocks from genome-wide data from 113,414 polymorphisms genotyped in 343 patients with sepsis and 410 unrelated controls, all ascertained for grandparental origin in the Canary Islands (Spain). Deviations in local ancestries between cases and controls were tested using logistic regressions, followed by fine-mapping analyses based on imputed genotypes, in silico functional assessments, and gene expression analysis centered on the region of interest. The admixture mapping analysis detected that local European ancestry in a locus spanning 1.2 megabases of chromosome 8p23.1 was associated with sepsis (lowest p = 1.37 × 10−4; Odds Ratio [OR] = 0.51; 95%CI = 0.40–0.66). Fine-mapping studies prioritized the variant rs13249564 within intron 1 of MFHAS1 gene associated with sepsis (p = 9.94 × 10−4; OR = 0.65; 95%CI = 0.50–0.84). Functional and gene expression analyses focused on 8p23.1 allowed us to identify alternative genes with possible biological plausibility such as defensins, which are well-known effector molecules of innate immunity. By completing the first admixture mapping study of sepsis, our results revealed a new genetic locus (8p23.1) harboring a number of genes with plausible implications in sepsis susceptibility.
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Affiliation(s)
- Tamara Hernandez-Beeftink
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,Research Unit, Hospital Universitario de Gran Canaria Dr. Negrín, Las Palmas de Gran Canaria, Spain
| | - Itahisa Marcelino-Rodríguez
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Beatriz Guillen-Guio
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Héctor Rodríguez-Pérez
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Jose M Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Almudena Corrales
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Ana Díaz-de Usera
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | | | - David Domínguez
- Department of Anesthesiology, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Elena Espinosa
- Department of Anesthesiology, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Jesús Villar
- Research Unit, Hospital Universitario de Gran Canaria Dr. Negrín, Las Palmas de Gran Canaria, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Carlos Flores
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
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20
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Schaschl H, Göllner T, Morris DL. Positive selection acts on regulatory genetic variants in populations of European ancestry that affect ALDH2 gene expression. Sci Rep 2022; 12:4563. [PMID: 35296751 PMCID: PMC8927298 DOI: 10.1038/s41598-022-08588-0] [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] [Received: 10/21/2021] [Accepted: 03/09/2022] [Indexed: 11/09/2022] Open
Abstract
ALDH2 is a key enzyme in alcohol metabolism that protects cells from acetaldehyde toxicity. Using iHS, iSAFE and FST statistics, we identified regulatory acting variants affecting ALDH2 gene expression under positive selection in populations of European ancestry. Several SNPs (rs3184504, rs4766578, rs10774625, rs597808, rs653178, rs847892, rs2013002) that function as eQTLs for ALDH2 in various tissues showed evidence of strong positive selection. Very large pairwise FST values indicated high genetic differentiation at these loci between populations of European ancestry and populations of other global ancestries. Estimating the timing of positive selection on the beneficial alleles suggests that these variants were recently adapted approximately 3000-3700 years ago. The derived beneficial alleles are in complete linkage disequilibrium with the derived ALDH2 promoter variant rs886205, which is associated with higher transcriptional activity. The SNPs rs4766578 and rs847892 are located in binding sequences for the transcription factor HNF4A, which is an important regulatory element of ALDH2 gene expression. In contrast to the missense variant ALDH2 rs671 (ALDH2*2), which is common only in East Asian populations and is associated with greatly reduced enzyme activity and alcohol intolerance, the beneficial alleles of the regulatory variants identified in this study are associated with increased expression of ALDH2. This suggests adaptation of Europeans to higher alcohol consumption.
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Affiliation(s)
- Helmut Schaschl
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria.
| | - Tobias Göllner
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Djerassiplatz 1, 1030, Vienna, Austria
| | - David L Morris
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King's College London, Great Maze Pond, London, SE1 9RT, UK
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21
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Colomer-Vilaplana A, Murga-Moreno J, Canalda-Baltrons A, Inserte C, Soto D, Coronado-Zamora M, Barbadilla A, Casillas S. PopHumanVar: an interactive application for the functional characterization and prioritization of adaptive genomic variants in humans. Nucleic Acids Res 2022; 50:D1069-D1076. [PMID: 34664660 PMCID: PMC8728255 DOI: 10.1093/nar/gkab925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/17/2021] [Accepted: 09/28/2021] [Indexed: 12/22/2022] Open
Abstract
Adaptive challenges that humans faced as they expanded across the globe left specific molecular footprints that can be decoded in our today's genomes. Different sets of metrics are used to identify genomic regions that have undergone selection. However, there are fewer methods capable of pinpointing the allele ultimately responsible for this selection. Here, we present PopHumanVar, an interactive online application that is designed to facilitate the exploration and thorough analysis of candidate genomic regions by integrating both functional and population genomics data currently available. PopHumanVar generates useful summary reports of prioritized variants that are putatively causal of recent selective sweeps. It compiles data and graphically represents different layers of information, including natural selection statistics, as well as functional annotations and genealogical estimations of variant age, for biallelic single nucleotide variants (SNVs) of the 1000 Genomes Project phase 3. Specifically, PopHumanVar amasses SNV-based information from GEVA, SnpEFF, GWAS Catalog, ClinVar, RegulomeDB and DisGeNET databases, as well as accurate estimations of iHS, nSL and iSAFE statistics. Notably, PopHumanVar can successfully identify known causal variants of frequently reported candidate selection regions, including EDAR in East-Asians, ACKR1 (DARC) in Africans and LCT/MCM6 in Europeans. PopHumanVar is open and freely available at https://pophumanvar.uab.cat.
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Affiliation(s)
- Aina Colomer-Vilaplana
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Jesús Murga-Moreno
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Aleix Canalda-Baltrons
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Clara Inserte
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Daniel Soto
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Marta Coronado-Zamora
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Antonio Barbadilla
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Sònia Casillas
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
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22
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Liu YH, Wang L, Zhang Z, Otecko NO, Khederzadeh S, Dai Y, Liang B, Wang GD, Zhang YP. Whole-Genome Sequencing Reveals Lactase Persistence Adaptation in European Dogs. Mol Biol Evol 2021; 38:4884-4890. [PMID: 34289055 PMCID: PMC8557436 DOI: 10.1093/molbev/msab214] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Coexistence and cooperation between dogs and humans over thousands of years have supported convergent evolutionary processes in the two species. Previous studies found that Eurasian dogs evolved into a distinct geographic cluster. In this study, we used the genomes of 242 European dogs, 38 Southeast Asian indigenous (SEAI) dogs, and 41 gray wolves to identify adaptation of European dogs . We report 86 unique positively selected genes in European dogs, among which is LCT (lactase). LCT encodes lactase, which is fundamental for the digestion of lactose. We found that an A-to-G mutation (chr19:38,609,592) is almost fixed in Middle Eastern and European dogs. The results of two-dimensional site frequency spectrum (2D SFS) support that the mutation is under soft sweep . We inferred that the onset of positive selection of the mutation is shorter than 6,535 years and behind the well-developed dairy economy in central Europe. It increases the expression of LCT by reducing its binding with ZEB1, which would enhance dog's ability to digest milk-based diets. Our study uncovers the genetic basis of convergent evolution between humans and dogs with respect to diet, emphasizing the import of the dog as a biomedical model for studying mechanisms of the digestive system.
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Affiliation(s)
- Yan-Hu Liu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Lu Wang
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, and School of Life Sciences, Yunnan University, Kunming, Yunnan, China
| | - Zhiguo Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Newton O Otecko
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Saber Khederzadeh
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yongqin Dai
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, and School of Life Sciences, Yunnan University, Kunming, Yunnan, China
| | - Bin Liang
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, and School of Life Sciences, Yunnan University, Kunming, Yunnan, China
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Center for Excellence in Animal Evolution and Genetics, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Guo-Dong Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Center for Excellence in Animal Evolution and Genetics, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, and School of Life Sciences, Yunnan University, Kunming, Yunnan, China
- Center for Excellence in Animal Evolution and Genetics, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
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23
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Lo YH, Cheng HC, Hsiung CN, Yang SL, Wang HY, Peng CW, Chen CY, Lin KP, Kang ML, Chen CH, Chu HW, Lin CF, Lee MH, Liu Q, Satta Y, Lin CJ, Lin M, Chaw SM, Loo JH, Shen CY, Ko WY. Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People. Mol Biol Evol 2021; 38:4149-4165. [PMID: 33170928 PMCID: PMC8476137 DOI: 10.1093/molbev/msaa276] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.
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Affiliation(s)
- Yun-Hua Lo
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Hsueh-Chien Cheng
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chia-Ni Hsiung
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Show-Ling Yang
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Han-Yu Wang
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chia-Wei Peng
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chun-Yu Chen
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Kung-Ping Lin
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Mei-Ling Kang
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Hou-Wei Chu
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | | | - Mei-Hsuan Lee
- Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Quintin Liu
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan
| | - Yoko Satta
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan
| | - Cheng-Jui Lin
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Marie Lin
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Shu-Miaw Chaw
- Biodiversity Research Center, Academia Sinica, Taipei City, Taiwan
| | - Jun-Hun Loo
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Chen-Yang Shen
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Wen-Ya Ko
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
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24
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Souilmi Y, Lauterbur ME, Tobler R, Huber CD, Johar AS, Moradi SV, Johnston WA, Krogan NJ, Alexandrov K, Enard D. An ancient viral epidemic involving host coronavirus interacting genes more than 20,000 years ago in East Asia. Curr Biol 2021; 31:3504-3514.e9. [PMID: 34171302 PMCID: PMC8223470 DOI: 10.1016/j.cub.2021.05.067] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/22/2021] [Accepted: 05/28/2021] [Indexed: 11/30/2022]
Abstract
The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the vulnerability of human populations to novel viral pressures, despite the vast array of epidemiological and biomedical tools now available. Notably, modern human genomes contain evolutionary information tracing back tens of thousands of years, which may help identify the viruses that have impacted our ancestors-pointing to which viruses have future pandemic potential. Here, we apply evolutionary analyses to human genomic datasets to recover selection events involving tens of human genes that interact with coronaviruses, including SARS-CoV-2, that likely started more than 20,000 years ago. These adaptive events were limited to the population ancestral to East Asian populations. Multiple lines of functional evidence support an ancient viral selective pressure, and East Asia is the geographical origin of several modern coronavirus epidemics. An arms race with an ancient coronavirus, or with a different virus that happened to use similar interactions as coronaviruses with human hosts, may thus have taken place in ancestral East Asian populations. By learning more about our ancient viral foes, our study highlights the promise of evolutionary information to better predict the pandemics of the future. Importantly, adaptation to ancient viral epidemics in specific human populations does not necessarily imply any difference in genetic susceptibility between different human populations, and the current evidence points toward an overwhelming impact of socioeconomic factors in the case of coronavirus disease 2019 (COVID-19).
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Affiliation(s)
- Yassine Souilmi
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA 5005, Australia; National Centre for Indigenous Genomics, Australian National University, Canberra, ACT 0200, Australia
| | - M Elise Lauterbur
- University of Arizona Department of Ecology and Evolutionary Biology, Tucson, AZ, USA
| | - Ray Tobler
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA 5005, Australia
| | - Christian D Huber
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA 5005, Australia
| | - Angad S Johar
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA 5005, Australia
| | - Shayli Varasteh Moradi
- CSIRO-QUT Synthetic Biology Alliance, Centre for Tropical Crops and Biocommodities, Queensland University of Technology, Brisbane, QLD 4001, Australia
| | - Wayne A Johnston
- CSIRO-QUT Synthetic Biology Alliance, Centre for Tropical Crops and Biocommodities, Queensland University of Technology, Brisbane, QLD 4001, Australia
| | - Nevan J Krogan
- QBI COVID-19 Research Group (QCRG), San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA, USA; J. David Gladstone Institutes, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kirill Alexandrov
- CSIRO-QUT Synthetic Biology Alliance, Centre for Tropical Crops and Biocommodities, Queensland University of Technology, Brisbane, QLD 4001, Australia.
| | - David Enard
- University of Arizona Department of Ecology and Evolutionary Biology, Tucson, AZ, USA.
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25
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Oberstaller J, Zoungrana L, Bannerman CD, Jahangiri S, Dwivedi A, Silva JC, Adams JH, Takala-Harrison S. Integration of population and functional genomics to understand mechanisms of artemisinin resistance in Plasmodium falciparum. Int J Parasitol Drugs Drug Resist 2021; 16:119-128. [PMID: 34102588 PMCID: PMC8187163 DOI: 10.1016/j.ijpddr.2021.05.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 05/05/2021] [Accepted: 05/21/2021] [Indexed: 11/05/2022]
Abstract
Resistance to antimalarial drugs, and in particular to the artemisinin derivatives and their partner drugs, threatens recent progress toward regional malaria elimination and eventual global malaria eradication. Population-level studies utilizing whole-genome sequencing approaches have facilitated the identification of regions of the parasite genome associated with both clinical and in vitro drug-resistance phenotypes. However, the biological relevance of genes identified in these analyses and the establishment of a causal relationship between genotype and phenotype requires functional characterization. Here we examined data from population genomic and transcriptomic studies in the context of data generated from recent functional studies, using a new population genetic approach designed to identify potential favored mutations within the region of a selective sweep (iSAFE). We identified several genes functioning in pathways now known to be associated with artemisinin resistance that were supported in early population genomic studies, as well as potential new drug targets/pathways for further validation and consideration for treatment of artemisinin-resistant Plasmodium falciparum. In addition, we establish the utility of iSAFE in identifying positively-selected mutations in population genomic studies, potentially accelerating the time to functional validation of candidate genes.
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Affiliation(s)
- Jenna Oberstaller
- Center for Global Health and Infectious Disease Research and USF Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA.
| | - Linda Zoungrana
- Center for Global Health and Infectious Disease Research and USF Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA.
| | - Carl D Bannerman
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Samira Jahangiri
- Center for Global Health and Infectious Disease Research and USF Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA.
| | - Ankit Dwivedi
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Joana C Silva
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - John H Adams
- Center for Global Health and Infectious Disease Research and USF Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA.
| | - Shannon Takala-Harrison
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA.
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26
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Rendón-Anaya M, Wilson J, Sveinsson S, Fedorkov A, Cottrell J, Bailey MES, Ruņģis D, Lexer C, Jansson S, Robinson KM, Street NR, Ingvarsson PK. Adaptive introgression facilitate adaptation to high latitudes in European aspen (Populus tremula L.). Mol Biol Evol 2021; 38:5034-5050. [PMID: 34329481 PMCID: PMC8557470 DOI: 10.1093/molbev/msab229] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Understanding local adaptation has become a key research area given the ongoing climate challenge and the concomitant requirement to conserve genetic resources. Perennial plants, such as forest trees, are good models to study local adaptation given their wide geographic distribution, largely outcrossing mating systems, and demographic histories. We evaluated signatures of local adaptation in European aspen (Populus tremula) across Europe by means of whole-genome resequencing of a collection of 411 individual trees. We dissected admixture patterns between aspen lineages and observed a strong genomic mosaicism in Scandinavian trees, evidencing different colonization trajectories into the peninsula from Russia, Central and Western Europe. As a consequence of the secondary contacts between populations after the last glacial maximum, we detected an adaptive introgression event in a genome region of ∼500 kb in chromosome 10, harboring a large-effect locus that has previously been shown to contribute to adaptation to the short growing seasons characteristic of Northern Scandinavia. Demographic simulations and ancestry inference suggest an Eastern origin—probably Russian—of the adaptive Nordic allele which nowadays is present in a homozygous state at the north of Scandinavia. The strength of introgression and positive selection signatures in this region is a unique feature in the genome. Furthermore, we detected signals of balancing selection, shared across regional populations, that highlight the importance of standing variation as a primary source of alleles that facilitate local adaptation. Our results, therefore, emphasize the importance of migration–selection balance underlying the genetic architecture of key adaptive quantitative traits.
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Affiliation(s)
- Martha Rendón-Anaya
- Linnean Centre for Plant Biology, Department of Plant Biology, Uppsala BioCenter, Swedish University of Agricultural Science, Uppsala, Sweden
| | - Jonathan Wilson
- Linnean Centre for Plant Biology, Department of Plant Biology, Uppsala BioCenter, Swedish University of Agricultural Science, Uppsala, Sweden
| | | | - Aleksey Fedorkov
- Institute of Biology, Komi Science Center, Russian Academy of Sciences, Syktyvkar, Russia
| | - Joan Cottrell
- Forest Research, Northern Research Station, Roslin, UK
| | - Mark E S Bailey
- School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Dainis Ruņģis
- Genetic Resource Centre, Latvian State Forest Research Institute "Silava", LV2169 Salaspils, Latvia
| | - Christian Lexer
- Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria
| | - Stefan Jansson
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden
| | - Kathryn M Robinson
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden
| | - Nathaniel R Street
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden
| | - Pär K Ingvarsson
- Linnean Centre for Plant Biology, Department of Plant Biology, Uppsala BioCenter, Swedish University of Agricultural Science, Uppsala, Sweden
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27
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Casares-Marfil D, Guillen-Guio B, Lorenzo-Salazar JM, Rodríguez-Pérez H, Kerick M, Jaimes-Campos MA, Díaz ML, Estupiñán E, Echeverría LE, González CI, Martin J, Flores C, Acosta-Herrera M. Admixture mapping analysis reveals differential genetic ancestry associated with Chagas disease susceptibility in the Colombian population. Hum Mol Genet 2021; 30:2503-2512. [PMID: 34302177 PMCID: PMC8643504 DOI: 10.1093/hmg/ddab213] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 01/02/2023] Open
Abstract
Chagas disease is an infection caused by the parasite Trypanosoma cruzi, endemic in Latino America. Leveraging the three-way admixture between Native American (AMR), European (EUR) and African (AFR) populations in Latin Americans, we aimed to better understand the genetic basis of Chagas disease by performing an admixture mapping study in a Colombian population. A two-stage study was conducted, and subjects were classified as seropositive and seronegative for T. cruzi. In stage 1, global and local ancestries were estimated using reference data from the 1000 Genomes Project (1KGP) and local ancestry associations were performed by logistic regression models. The AMR ancestry showed a protective association with Chagas disease within the Major Histocompatibility Complex region (OR = 0.74, 95%CI = 0.66-0.83, lowest p-value = 4.53x10-8). The fine mapping assessment on imputed genotypes combining data from stage 1 and 2 from an independent Colombian cohort, revealed nominally associated variants in high linkage disequilibrium with the top signal (rs2032134, OR = 0.93, 95%CI = 0.90-0.97, p-value = 3.54x10-4) in the previously associated locus. To assess ancestry-specific adaptive signals, a selective sweep scan in an AMR reference population from 1KGP together with an in silico functional analysis highlighted the Tripartite Motif family and the Human Leukocyte Antigen (HLA) genes, with crucial role in the immune response against pathogens. Furthermore, these analyses emphasized the macrophages, neutrophils, and eosinophils, as key players in the defense against T. cruzi. This first admixture mapping study in Chagas disease provided novel insights underlying the host immune response in the pathogenesis of this neglected disease.
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Affiliation(s)
| | - Beatriz Guillen-Guio
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Jose M Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Héctor Rodríguez-Pérez
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Martin Kerick
- Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain
| | - Mayra A Jaimes-Campos
- Grupo de Inmunología y Epidemiología Molecular, Escuela de Microbiología, Universidad Industrial de Santander, Bucaramanga, Colombia
| | - Martha L Díaz
- Grupo de Inmunología y Epidemiología Molecular, Escuela de Microbiología, Universidad Industrial de Santander, Bucaramanga, Colombia
| | - Elkyn Estupiñán
- Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain.,Grupo de Inmunología y Epidemiología Molecular, Escuela de Microbiología, Universidad Industrial de Santander, Bucaramanga, Colombia
| | - Luis E Echeverría
- Heart Failure and Heart Transplant Clinic, Fundación Cardiovascular de Colombia, Floridablanca, Colombia
| | - Clara I González
- Grupo de Inmunología y Epidemiología Molecular, Escuela de Microbiología, Universidad Industrial de Santander, Bucaramanga, Colombia
| | - Javier Martin
- Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain
| | - Carlos Flores
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain.,Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
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28
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Mathyer ME, Brettmann EA, Schmidt AD, Goodwin ZA, Oh IY, Quiggle AM, Tycksen E, Ramakrishnan N, Matkovich SJ, Guttman-Yassky E, Edwards JR, de Guzman Strong C. Selective sweep for an enhancer involucrin allele identifies skin barrier adaptation out of Africa. Nat Commun 2021; 12:2557. [PMID: 33963188 PMCID: PMC8105351 DOI: 10.1038/s41467-021-22821-w] [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: 10/10/2019] [Accepted: 03/30/2021] [Indexed: 02/03/2023] Open
Abstract
The genetic modules that contribute to human evolution are poorly understood. Here we investigate positive selection in the Epidermal Differentiation Complex locus for skin barrier adaptation in diverse HapMap human populations (CEU, JPT/CHB, and YRI). Using Composite of Multiple Signals and iSAFE, we identify selective sweeps for LCE1A-SMCP and involucrin (IVL) haplotypes associated with human migration out-of-Africa, reaching near fixation in European populations. CEU-IVL is associated with increased IVL expression and a known epidermis-specific enhancer. CRISPR/Cas9 deletion of the orthologous mouse enhancer in vivo reveals a functional requirement for the enhancer to regulate Ivl expression in cis. Reporter assays confirm increased regulatory and additive enhancer effects of CEU-specific polymorphisms identified at predicted IRF1 and NFIC binding sites in the IVL enhancer (rs4845327) and its promoter (rs1854779). Together, our results identify a selective sweep for a cis regulatory module for CEU-IVL, highlighting human skin barrier evolution for increased IVL expression out-of-Africa.
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Affiliation(s)
- Mary Elizabeth Mathyer
- grid.4367.60000 0001 2355 7002Division of Dermatology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for the Study of Itch & Sensory Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Erin A. Brettmann
- grid.4367.60000 0001 2355 7002Division of Dermatology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for the Study of Itch & Sensory Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Alina D. Schmidt
- grid.4367.60000 0001 2355 7002Division of Dermatology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for the Study of Itch & Sensory Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Zane A. Goodwin
- grid.4367.60000 0001 2355 7002Division of Dermatology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for the Study of Itch & Sensory Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Inez Y. Oh
- grid.4367.60000 0001 2355 7002Division of Dermatology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for the Study of Itch & Sensory Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Ashley M. Quiggle
- grid.4367.60000 0001 2355 7002Division of Dermatology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for the Study of Itch & Sensory Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Eric Tycksen
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Natasha Ramakrishnan
- grid.4367.60000 0001 2355 7002Division of Dermatology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for the Study of Itch & Sensory Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Scot J. Matkovich
- grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Emma Guttman-Yassky
- grid.59734.3c0000 0001 0670 2351Department of Dermatology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029 USA
| | - John R. Edwards
- grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
| | - Cristina de Guzman Strong
- grid.4367.60000 0001 2355 7002Division of Dermatology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for Pharmacogenomics, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Center for the Study of Itch & Sensory Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO 63110 USA
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29
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Xue AT, Schrider DR, Kern AD. Discovery of Ongoing Selective Sweeps within Anopheles Mosquito Populations Using Deep Learning. Mol Biol Evol 2021; 38:1168-1183. [PMID: 33022051 PMCID: PMC7947845 DOI: 10.1093/molbev/msaa259] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Identification of partial sweeps, which include both hard and soft sweeps that have not currently reached fixation, provides crucial information about ongoing evolutionary responses. To this end, we introduce partialS/HIC, a deep learning method to discover selective sweeps from population genomic data. partialS/HIC uses a convolutional neural network for image processing, which is trained with a large suite of summary statistics derived from coalescent simulations incorporating population-specific history, to distinguish between completed versus partial sweeps, hard versus soft sweeps, and regions directly affected by selection versus those merely linked to nearby selective sweeps. We perform several simulation experiments under various demographic scenarios to demonstrate partialS/HIC's performance, which exhibits excellent resolution for detecting partial sweeps. We also apply our classifier to whole genomes from eight mosquito populations sampled across sub-Saharan Africa by the Anopheles gambiae 1000 Genomes Consortium, elucidating both continent-wide patterns as well as sweeps unique to specific geographic regions. These populations have experienced intense insecticide exposure over the past two decades, and we observe a strong overrepresentation of sweeps at insecticide resistance loci. Our analysis thus provides a list of candidate adaptive loci that may be relevant to mosquito control efforts. More broadly, our supervised machine learning approach introduces a method to distinguish between completed and partial sweeps, as well as between hard and soft sweeps, under a variety of demographic scenarios. As whole-genome data rapidly accumulate for a greater diversity of organisms, partialS/HIC addresses an increasing demand for useful selection scan tools that can track in-progress evolutionary dynamics.
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Affiliation(s)
- Alexander T Xue
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
| | - Daniel R Schrider
- Department of Genetics, University of North Carolina, Chapel Hill, NC
| | - Andrew D Kern
- Institute of Ecology and Evolution, 5289 University of Oregon, Eugene, OR
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30
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Naji MM, Utsunomiya YT, Sölkner J, Rosen BD, Mészáros G. Investigation of ancestral alleles in the Bovinae subfamily. BMC Genomics 2021; 22:108. [PMID: 33557747 PMCID: PMC7871596 DOI: 10.1186/s12864-021-07412-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 01/27/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND In evolutionary theory, divergence and speciation can arise from long periods of reproductive isolation, genetic mutation, selection and environmental adaptation. After divergence, alleles can either persist in their initial state (ancestral allele - AA), co-exist or be replaced by a mutated state (derived alleles -DA). In this study, we aligned whole genome sequences of individuals from the Bovinae subfamily to the cattle reference genome (ARS.UCD-1.2) for defining ancestral alleles necessary for selection signatures study. RESULTS Accommodating independent divergent of each lineage from the initial ancestral state, AA were defined based on fixed alleles on at least two groups of yak, bison and gayal-gaur-banteng resulting in ~ 32.4 million variants. Using non-overlapping scanning windows of 10 Kb, we counted the AA observed within taurine and zebu cattle. We focused on the extreme points, regions with top 0. 1% (high count) and regions without any occurrence of AA (null count). High count regions preserved gene functions from ancestral states that are still beneficial in the current condition, while null counts regions were linked to mutated ones. For both cattle, high count regions were associated with basal lipid metabolism, essential for survival of various environmental pressures. Mutated regions were associated to productive traits in taurine, i.e. higher metabolism, cell development and behaviors and in immune response domain for zebu. CONCLUSIONS Our findings suggest that retaining and losing AA in some regions are varied and made it species-specific with possibility of overlapping as it depends on the selective pressure they had to experience.
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Affiliation(s)
- Maulana M. Naji
- University of Natural Resources and Life Sciences (BOKU), Vienna, Austria
| | - Yuri T. Utsunomiya
- São Paulo State University (Unesp), School of Veterinary Medicine, Department of Production and Animal Health, Araçatuba, São Paulo Brazil
- International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, São Paulo Brazil
- AgroPartners Consulting. R. Floriano Peixoto, 120-Sala 43A-Centro, Araçatuba, SP 16010-220 Brazil
- Personal-PEC. R. Sebastiao Lima, 1336-Centro, Campo Grande, MS 79004-600 Brazil
| | - Johann Sölkner
- University of Natural Resources and Life Sciences (BOKU), Vienna, Austria
| | | | - Gábor Mészáros
- University of Natural Resources and Life Sciences (BOKU), Vienna, Austria
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31
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Enard D, Petrov DA. Ancient RNA virus epidemics through the lens of recent adaptation in human genomes. Philos Trans R Soc Lond B Biol Sci 2020; 375:20190575. [PMID: 33012231 PMCID: PMC7702803 DOI: 10.1098/rstb.2019.0575] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Over the course of the last several million years of evolution, humans probably have been plagued by hundreds or perhaps thousands of epidemics. Little is known about such ancient epidemics and a deep evolutionary perspective on current pathogenic threats is lacking. The study of past epidemics has typically been limited in temporal scope to recorded history, and in physical scope to pathogens that left sufficient DNA behind, such as Yersinia pestis during the Great Plague. Host genomes, however, offer an indirect way to detect ancient epidemics beyond the current temporal and physical limits. Arms races with pathogens have shaped the genomes of the hosts by driving a large number of adaptations at many genes, and these signals can be used to detect and further characterize ancient epidemics. Here, we detect the genomic footprints left by ancient viral epidemics that took place in the past approximately 50 000 years in the 26 human populations represented in the 1000 Genomes Project. By using the enrichment in signals of adaptation at approximately 4500 host loci that interact with specific types of viruses, we provide evidence that RNA viruses have driven a particularly large number of adaptive events across diverse human populations. These results suggest that different types of viruses may have exerted different selective pressures during human evolution. Knowledge of these past selective pressures will provide a deeper evolutionary perspective on current pathogenic threats. This article is part of the theme issue ‘Insights into health and disease from ancient biomolecules’.
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Affiliation(s)
- David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA
| | - Dmitri A Petrov
- Department of Biology, Stanford University, Stanford, CA, USA
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32
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Werren EA, Garcia O, Bigham AW. Identifying adaptive alleles in the human genome: from selection mapping to functional validation. Hum Genet 2020; 140:241-276. [PMID: 32728809 DOI: 10.1007/s00439-020-02206-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 07/07/2020] [Indexed: 12/19/2022]
Abstract
The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.
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Affiliation(s)
- Elizabeth A Werren
- Department of Human Genetics, The University of Michigan, Ann Arbor, MI, USA
- Department of Anthropology, The University of Michigan, Ann Arbor, MI, USA
| | - Obed Garcia
- Department of Anthropology, The University of Michigan, Ann Arbor, MI, USA
| | - Abigail W Bigham
- Department of Anthropology, University of California Los Angeles, 341 Haines Hall, Los Angeles, CA, 90095, USA.
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33
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A positively selected FBN1 missense variant reduces height in Peruvian individuals. Nature 2020; 582:234-239. [PMID: 32499652 PMCID: PMC7410362 DOI: 10.1038/s41586-020-2302-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 03/10/2020] [Indexed: 01/21/2023]
Abstract
On average, Peruvian individuals are among the shortest in the world1. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.
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34
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Harris AM, DeGiorgio M. Identifying and Classifying Shared Selective Sweeps from Multilocus Data. Genetics 2020; 215:143-171. [PMID: 32152048 PMCID: PMC7198270 DOI: 10.1534/genetics.120.303137] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 02/29/2020] [Indexed: 11/18/2022] Open
Abstract
Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term [Formula: see text] and [Formula: see text] to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.
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Affiliation(s)
- Alexandre M Harris
- Department of Biology, Pennsylvania State University, University Park, Pennsylvania 16802
- Molecular, Cellular, and Integrative Biosciences at the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida 33431
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35
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Scossa F, Fernie AR. The evolution of metabolism: How to test evolutionary hypotheses at the genomic level. Comput Struct Biotechnol J 2020; 18:482-500. [PMID: 32180906 PMCID: PMC7063335 DOI: 10.1016/j.csbj.2020.02.009] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Revised: 02/12/2020] [Accepted: 02/13/2020] [Indexed: 01/21/2023] Open
Abstract
The origin of primordial metabolism and its expansion to form the metabolic networks extant today represent excellent systems to study the impact of natural selection and the potential adaptive role of novel compounds. Here we present the current hypotheses made on the origin of life and ancestral metabolism and present the theories and mechanisms by which the large chemical diversity of plants might have emerged along evolution. In particular, we provide a survey of statistical methods that can be used to detect signatures of selection at the gene and population level, and discuss potential and limits of these methods for investigating patterns of molecular adaptation in plant metabolism.
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Affiliation(s)
- Federico Scossa
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany
- Council for Agricultural Research and Economics (CREA), Research Centre for Genomics and Bioinformatics (CREA-GB), Via Ardeatina 546, 00178 Rome, Italy
| | - Alisdair R. Fernie
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany
- Center of Plant Systems Biology and Biotechnology (CPSBB), Plovdiv, Bulgaria
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36
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Mierzwa BE. Communicating scientific concepts through art. J Vis Commun Med 2019; 43:85-90. [PMID: 31858847 DOI: 10.1080/17453054.2019.1700783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Beata E Mierzwa
- Ludwig Institute for Cancer Research, San Diego; Department of Cellular and Molecular Medicine, University of California, San Diego, USA
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37
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Refoyo-Martínez A, da Fonseca RR, Halldórsdóttir K, Árnason E, Mailund T, Racimo F. Identifying loci under positive selection in complex population histories. Genome Res 2019; 29:1506-1520. [PMID: 31362936 PMCID: PMC6724678 DOI: 10.1101/gr.246777.118] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 07/23/2019] [Indexed: 12/24/2022]
Abstract
Detailed modeling of a species' history is of prime importance for understanding how natural selection operates over time. Most methods designed to detect positive selection along sequenced genomes, however, use simplified representations of past histories as null models of genetic drift. Here, we present the first method that can detect signatures of strong local adaptation across the genome using arbitrarily complex admixture graphs, which are typically used to describe the history of past divergence and admixture events among any number of populations. The method-called graph-aware retrieval of selective sweeps (GRoSS)-has good power to detect loci in the genome with strong evidence for past selective sweeps and can also identify which branch of the graph was most affected by the sweep. As evidence of its utility, we apply the method to bovine, codfish, and human population genomic data containing panels of multiple populations related in complex ways. We find new candidate genes for important adaptive functions, including immunity and metabolism in understudied human populations, as well as muscle mass, milk production, and tameness in specific bovine breeds. We are also able to pinpoint the emergence of large regions of differentiation owing to inversions in the history of Atlantic codfish.
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Affiliation(s)
- Alba Refoyo-Martínez
- Lundbeck GeoGenetics Centre, The Globe Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 1350, Denmark
| | - Rute R da Fonseca
- Centre for Macroecology, Evolution and Climate, The Globe Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copehnagen 2100, Denmark
| | - Katrín Halldórsdóttir
- Faculty of Life and Environmental Sciences, University of Iceland, Reykjavík 107, Iceland
| | - Einar Árnason
- Faculty of Life and Environmental Sciences, University of Iceland, Reykjavík 107, Iceland
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Thomas Mailund
- Bioinformatics Research Centre, Aarhus University, Aarhus 8000, Denmark
| | - Fernando Racimo
- Lundbeck GeoGenetics Centre, The Globe Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 1350, Denmark
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38
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Lona-Durazo F, Hernandez-Pacheco N, Fan S, Zhang T, Choi J, Kovacs MA, Loftus SK, Le P, Edwards M, Fortes-Lima CA, Eng C, Huntsman S, Hu D, Gómez-Cabezas EJ, Marín-Padrón LC, Grauholm J, Mors O, Burchard EG, Norton HL, Pavan WJ, Brown KM, Tishkoff S, Pino-Yanes M, Beleza S, Marcheco-Teruel B, Parra EJ. Meta-analysis of GWA studies provides new insights on the genetic architecture of skin pigmentation in recently admixed populations. BMC Genet 2019; 20:59. [PMID: 31315583 PMCID: PMC6637524 DOI: 10.1186/s12863-019-0765-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 07/08/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Association studies in recently admixed populations are extremely useful to identify the genetic architecture of pigmentation, due to their high genotypic and phenotypic variation. However, to date only four Genome-Wide Association Studies (GWAS) have been carried out in these populations. RESULTS We present a GWAS of skin pigmentation in an admixed sample from Cuba (N = 762). Additionally, we conducted a meta-analysis including the Cuban sample, and admixed samples from Cape Verde, Puerto Rico and African-Americans from San Francisco. This meta-analysis is one of the largest efforts so far to characterize the genetic basis of skin pigmentation in admixed populations (N = 2,104). We identified five genome-wide significant regions in the meta-analysis, and explored if the markers observed in these regions are associated with the expression of relevant pigmentary genes in human melanocyte cultures. In three of the regions identified in the meta-analysis (SLC24A5, SLC45A2, and GRM5/TYR), the association seems to be driven by non-synonymous variants (rs1426654, rs16891982, and rs1042602, respectively). The rs16891982 polymorphism is strongly associated with the expression of the SLC45A2 gene. In the GRM5/TYR region, in addition to the rs1042602 non-synonymous SNP located on the TYR gene, variants located in the nearby GRM5 gene have an independent effect on pigmentation, possibly through regulation of gene expression of the TYR gene. We also replicated an association recently described near the MFSD12 gene on chromosome 19 (lead variant rs112332856). Additionally, our analyses support the presence of multiple signals in the OCA2/HERC2/APBA2 region on chromosome 15. A clear causal candidate is the HERC2 intronic variant rs12913832, which has a profound influence on OCA2 expression. This variant has pleiotropic effects on eye, hair, and skin pigmentation. However, conditional and haplotype-based analyses indicate the presence of other variants with independent effects on melanin levels in OCA2 and APBA2. Finally, a follow-up of genome-wide signals identified in a recent GWAS for tanning response indicates that there is a substantial overlap in the genetic factors influencing skin pigmentation and tanning response. CONCLUSIONS Our meta-analysis of skin pigmentation GWAS in recently admixed populations provides new insights about the genetic architecture of this complex trait.
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Affiliation(s)
- Frida Lona-Durazo
- Department of Anthropology, University of Toronto at Mississauga, Health Sciences Complex, room 352, Mississauga, Ontario L5L 1C6 Canada
| | - Natalia Hernandez-Pacheco
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, La Laguna, Tenerife, Spain
| | - Shaohua Fan
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Tongwu Zhang
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Jiyeon Choi
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Michael A. Kovacs
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Stacie K. Loftus
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, USA
| | - Phuong Le
- Department of Anthropology, University of Toronto at Mississauga, Health Sciences Complex, room 352, Mississauga, Ontario L5L 1C6 Canada
| | - Melissa Edwards
- Department of Anthropology, University of Toronto at Mississauga, Health Sciences Complex, room 352, Mississauga, Ontario L5L 1C6 Canada
| | - Cesar A. Fortes-Lima
- Evolutionary Anthropology Team, Laboratory Eco-Anthropology and Ethno-Biology UMR7206, CNRS-MNHN-University Paris Diderot, Musée de l’Homme, Paris, France
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Celeste Eng
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | - Scott Huntsman
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | - Donglei Hu
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | | | | | - Jonas Grauholm
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Ole Mors
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus University, Aarhus, Denmark
- Psychiatric Department, Aarhus University Hospital, Aarhus, Denmark
| | - Esteban G. Burchard
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | - Heather L. Norton
- Department of Anthropology, University of Cincinnati, Cincinnati, USA
| | - William J. Pavan
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, USA
| | - Kevin M. Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - Sarah Tishkoff
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA USA
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, La Laguna, Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Sandra Beleza
- Department of Genetics and Genome Biology, College of Life Sciences, University of Leicester, Leicester, UK
| | | | - Esteban J. Parra
- Department of Anthropology, University of Toronto at Mississauga, Health Sciences Complex, room 352, Mississauga, Ontario L5L 1C6 Canada
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Liang Z, Duan S, Sheng J, Zhu S, Ni X, Shao J, Liu C, Nick P, Du F, Fan P, Mao R, Zhu Y, Deng W, Yang M, Huang H, Liu Y, Ding Y, Liu X, Jiang J, Zhu Y, Li S, He X, Chen W, Dong Y. Whole-genome resequencing of 472 Vitis accessions for grapevine diversity and demographic history analyses. Nat Commun 2019; 10:1190. [PMID: 30867414 PMCID: PMC6416300 DOI: 10.1038/s41467-019-09135-8] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Accepted: 02/21/2019] [Indexed: 01/27/2023] Open
Abstract
Understanding the Vitis species at the genomic level is important for cultivar improvement of grapevine. Here we report whole-genome genetic variation at single-base resolution of 472 Vitis accessions, which cover 48 out of 60 extant Vitis species from a wide geographic distribution. The variation helps to identify a recent dramatic expansion and contraction of effective population size in the domesticated grapevines and that cultivars from the pan-Black Sea region have a unique demographic history in comparison to the other domesticated cultivars. We also find selective sweeps for berry edibility and stress resistance improvement. Furthermore, we find associations between candidate genes and important agronomic traits, such as berry shape and aromatic compounds. These results demonstrate resource value of the resequencing data for illuminating the evolutionary biology of Vitis species and providing targets for grapevine genetic improvement. Despite the importance of grapevine cultivation in human history and the economic values of cultivar improvement, large-scale genomic variation data are lacking. Here the authors resequence 472 Vitis accessions and use the identified genetic variations for domestication history, demography, and GWAS analyses.
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Affiliation(s)
- Zhenchang Liang
- Beijing Key Laboratory of Grape Sciences and Enology, Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Wuhan, 430074, China
| | - Shengchang Duan
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China.,Nowbio Biotechnology Company, Kunming, 650201, China
| | - Jun Sheng
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China.,Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, 650201, China.,Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Shusheng Zhu
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China.,Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Xuemei Ni
- BGI, BGI-Shenzhen, Shenzhen, 518120, China.,BGI Institute of Applied Agriculture, BGI-Shenzhen, Shenzhen, 518120, China
| | - Jianhui Shao
- Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Chonghuai Liu
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, 450009, China
| | - Peter Nick
- Botanical Institute, Karlsruhe Institute of Technology, Karlsruhe, 76128, Germany
| | - Fei Du
- Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Peige Fan
- Beijing Key Laboratory of Grape Sciences and Enology, Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Ruzhi Mao
- Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Yifan Zhu
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China.,Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Weiping Deng
- Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Min Yang
- Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Huichuan Huang
- Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Yixiang Liu
- Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Yiqing Ding
- Beijing Key Laboratory of Grape Sciences and Enology, Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xianju Liu
- Beijing Key Laboratory of Grape Sciences and Enology, Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jianfu Jiang
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, 450009, China
| | - Youyong Zhu
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China.,Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, 650201, China.,Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China
| | - Shaohua Li
- Beijing Key Laboratory of Grape Sciences and Enology, Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Xiahong He
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China. .,Key Laboratory for Agro-biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, 650201, China.
| | - Wei Chen
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China. .,Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, 650201, China.
| | - Yang Dong
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China. .,Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, 650201, China.
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40
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Abstract
For almost 20 years, many inference methods have been developed to detect selective sweeps and localize the targets of directional selection in the genome. These methods are based on population genetic models that describe the effect of a beneficial allele (e.g., a new mutation) on linked neutral variation (driven by directional selection from a single copy to fixation). Here, I discuss these models, ranging from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and emphasize the important role of demography and population structure in data analysis. In the past 10 years, soft sweeps that may arise after an environmental change from directional selection on standing variation have become a focus of population genetic research. In contrast to selective sweeps, they are caused by beneficial alleles that were neutrally segregating in a population before the environmental change or were present at a mutation-selection balance in appreciable frequency.
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41
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Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity. Genetics 2018; 210:1429-1452. [PMID: 30315068 DOI: 10.1534/genetics.118.301502] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2018] [Accepted: 10/08/2018] [Indexed: 11/18/2022] Open
Abstract
Positive natural selection can lead to a decrease in genomic diversity at the selected site and at linked sites, producing a characteristic signature of elevated expected haplotype homozygosity. These selective sweeps can be hard or soft. In the case of a hard selective sweep, a single adaptive haplotype rises to high population frequency, whereas multiple adaptive haplotypes sweep through the population simultaneously in a soft sweep, producing distinct patterns of genetic variation in the vicinity of the selected site. Measures of expected haplotype homozygosity have previously been used to detect sweeps in multiple study systems. However, these methods are formulated for phased haplotype data, typically unavailable for nonmodel organisms, and some may have reduced power to detect soft sweeps due to their increased genetic diversity relative to hard sweeps. To address these limitations, we applied the H12 and H2/H1 statistics proposed in 2015 by Garud et al., which have power to detect both hard and soft sweeps, to unphased multilocus genotypes, denoting them as G12 and G2/G1. G12 (and the more direct expected homozygosity analog to H12, denoted G123) has comparable power to H12 for detecting both hard and soft sweeps. G2/G1 can be used to classify hard and soft sweeps analogously to H2/H1, conditional on a genomic region having high G12 or G123 values. The reason for this power is that, under random mating, the most frequent haplotypes will yield the most frequent multilocus genotypes. Simulations based on parameters compatible with our recent understanding of human demographic history suggest that expected homozygosity methods are best suited for detecting recent sweeps, and increase in power under recent population expansions. Finally, we find candidates for selective sweeps within the 1000 Genomes CEU, YRI, GIH, and CHB populations, which corroborate and complement existing studies.
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Expression patterns and mutation analysis of p53 in fish Rita rita from polluted riverine environment. MUTATION RESEARCH-GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS 2018; 832-833:41-51. [PMID: 30057020 DOI: 10.1016/j.mrgentox.2018.05.022] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 04/12/2018] [Accepted: 05/29/2018] [Indexed: 12/14/2022]
Abstract
The present study was undertaken to investigate the alterations in gene expression patterns and for mutation analysis of p53 in the riverine catfish Rita rita collected from polluted riverine habitat. The partial p53 gene sequence of Rita rita generated showed a high degree of similarities with the DNA binding domains of fishes, mice and human. Transcriptomic analysis, carried out by quantitative real-time Polymerase Chain Reaction (RT-qPCR), showed significant down-regulation of p53 in fishes collected from most of the polluted stretches. Similar trend in protein abundance was observed by western blot analysis. Down-regulation of p53 was more pronounced in gill than liver. Expression patterns of p53 suggest that exposure to a multitude of contaminants in the natural riverine ecosystem could suppress the expression of p53. Genomic DNA showed a low stained smear pattern upon electrophoresis, with no evidence of DNA fragmentation. For mutation analysis PCR-SSCP followed by sequence analysis was carried out, which identified eight mutations; two at codon level and six missense mutations in the DNA binding domain IV and V. Secondary structure prediction showed that these mutations could lead to impairment of protein structure. Thus, the present study indicated that aquatic pollution has impacted these lower vertebrates which are reflected by the down-regulation of tumor suppressor protein (p53) in majority of the stretches studied.
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Pierron D, Heiske M, Razafindrazaka H, Pereda-Loth V, Sanchez J, Alva O, Arachiche A, Boland A, Olaso R, Deleuze JF, Ricaut FX, Rakotoarisoa JA, Radimilahy C, Stoneking M, Letellier T. Strong selection during the last millennium for African ancestry in the admixed population of Madagascar. Nat Commun 2018; 9:932. [PMID: 29500350 PMCID: PMC5834599 DOI: 10.1038/s41467-018-03342-5] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 02/06/2018] [Indexed: 01/24/2023] Open
Abstract
While admixed populations offer a unique opportunity to detect selection, the admixture in most of the studied populations occurred too recently to produce conclusive signals. By contrast, Malagasy populations originate from admixture between Asian and African populations that occurred ~27 generations ago, providing power to detect selection. We analyze local ancestry across the genomes of 700 Malagasy and identify a strong signal of recent positive selection, with an estimated selection coefficient >0.2. The selection is for African ancestry and affects 25% of chromosome 1, including the Duffy blood group gene. The null allele at this gene provides resistance to Plasmodium vivax malaria, and previous studies have suggested positive selection for this allele in the Malagasy population. This selection event also influences numerous other genes implicated in immunity, cardiovascular diseases, and asthma and decreases the Asian ancestry genome-wide by 10%, illustrating the role played by selection in recent human history.
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Affiliation(s)
- Denis Pierron
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France.
| | - Margit Heiske
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France
| | - Harilanto Razafindrazaka
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France
- Aix Marseille Univ., CNRS, EFS, ADES, Marseille, France
| | - Veronica Pereda-Loth
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France
| | - Jazmin Sanchez
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France
| | - Omar Alva
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France
| | - Amal Arachiche
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France
| | - Anne Boland
- Commissariat à l'Energie Atomique, Institut Génomique, Centre National de Génotypage, 91000, Evry, France
| | - Robert Olaso
- Commissariat à l'Energie Atomique, Institut Génomique, Centre National de Génotypage, 91000, Evry, France
| | - Jean-Francois Deleuze
- Commissariat à l'Energie Atomique, Institut Génomique, Centre National de Génotypage, 91000, Evry, France
| | - Francois-Xavier Ricaut
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France
| | - Jean-Aimé Rakotoarisoa
- Institut de Civilisations/Musée d'Art et d'Archéologie, Université d'Antananarivo, 101, Antananarivo, Madagascar
| | - Chantal Radimilahy
- Institut de Civilisations/Musée d'Art et d'Archéologie, Université d'Antananarivo, 101, Antananarivo, Madagascar
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103, Leipzig, Germany
| | - Thierry Letellier
- Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288 CNRS, Université de Toulouse, 31073, Toulouse, France
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Sugden LA, Atkinson EG, Fischer AP, Rong S, Henn BM, Ramachandran S. Localization of adaptive variants in human genomes using averaged one-dependence estimation. Nat Commun 2018; 9:703. [PMID: 29459739 PMCID: PMC5818606 DOI: 10.1038/s41467-018-03100-7] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 01/19/2018] [Indexed: 12/19/2022] Open
Abstract
Statistical methods for identifying adaptive mutations from population genetic data face several obstacles: assessing the significance of genomic outliers, integrating correlated measures of selection into one analytic framework, and distinguishing adaptive variants from hitchhiking neutral variants. Here, we introduce SWIF(r), a probabilistic method that detects selective sweeps by learning the distributions of multiple selection statistics under different evolutionary scenarios and calculating the posterior probability of a sweep at each genomic site. SWIF(r) is trained using simulations from a user-specified demographic model and explicitly models the joint distributions of selection statistics, thereby increasing its power to both identify regions undergoing sweeps and localize adaptive mutations. Using array and exome data from 45 ‡Khomani San hunter-gatherers of southern Africa, we identify an enrichment of adaptive signals in genes associated with metabolism and obesity. SWIF(r) provides a transparent probabilistic framework for localizing beneficial mutations that is extensible to a variety of evolutionary scenarios.
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Affiliation(s)
- Lauren Alpert Sugden
- Center for Computational Molecular Biology, Brown University, Providence, RI, 02912, USA.
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, 02912, USA.
| | - Elizabeth G Atkinson
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Annie P Fischer
- Division of Applied Mathematics, Brown University, Providence, RI, 02912, USA
| | - Stephen Rong
- Center for Computational Molecular Biology, Brown University, Providence, RI, 02912, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI, 02912, USA
| | - Brenna M Henn
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Sohini Ramachandran
- Center for Computational Molecular Biology, Brown University, Providence, RI, 02912, USA.
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, 02912, USA.
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