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Lei C, Liu J, Zhang R, Pan Y, Lu Y, Gao Y, Ma X, Yang Y, Guan Y, Mamatyusupu D, Xu S. Ancestral Origins and Admixture History of Kazakhs. Mol Biol Evol 2024; 41:msae144. [PMID: 38995236 PMCID: PMC11272102 DOI: 10.1093/molbev/msae144] [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: 12/15/2023] [Revised: 04/29/2024] [Accepted: 07/02/2024] [Indexed: 07/13/2024] Open
Abstract
Kazakh people, like many other populations that settled in Central Asia, demonstrate an array of mixed anthropological features of East Eurasian (EEA) and West Eurasian (WEA) populations, indicating a possible scenario of biological admixture between already differentiated EEA and WEA populations. However, their complex biological origin, genomic makeup, and genetic interaction with surrounding populations are not well understood. To decipher their genetic structure and population history, we conducted, to our knowledge, the first whole-genome sequencing study of Kazakhs residing in Xinjiang (KZK). We demonstrated that KZK derived their ancestries from 4 ancestral source populations: East Asian (∼39.7%), West Asian (∼28.6%), Siberian (∼23.6%), and South Asian (∼8.1%). The recognizable interactions of EEA and WEA ancestries in Kazakhs were dated back to the 15th century BCE. Kazakhs were genetically distinctive from the Uyghurs in terms of their overall genomic makeup, although the 2 populations were closely related in genetics, and both showed a substantial admixture of western and eastern peoples. Notably, we identified a considerable sex-biased admixture, with an excess of western males and eastern females contributing to the KZK gene pool. We further identified a set of genes that showed remarkable differentiation in KZK from the surrounding populations, including those associated with skin color (SLC24A5, OCA2), essential hypertension (HLA-DQB1), hypertension (MTHFR, SLC35F3), and neuron development (CNTNAP2). These results advance our understanding of the complex history of contacts between Western and Eastern Eurasians, especially those living or along the old Silk Road.
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Affiliation(s)
- Chang Lei
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jiaojiao Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Rui Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Lu
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xixian Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yaqun Guan
- Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University, Urumqi 830011, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi 830046, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
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2
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Stoneman HR, Price A, Trout NS, Lamont R, Tifour S, Pozdeyev N, Crooks K, Lin M, Rafaels N, Gignoux CR, Marker KM, Hendricks AE. Characterizing substructure via mixture modeling in large-scale genetic summary statistics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.29.577805. [PMID: 38766180 PMCID: PMC11100604 DOI: 10.1101/2024.01.29.577805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Genetic summary data are broadly accessible and highly useful including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into groups masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted substructure limits summary data usability, especially for understudied or admixed populations. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to estimate and adjust for substructure in genetic summary data. In extensive simulations and application to public data, Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and identifies potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse publicly available summary data resulting in improved and more equitable research.
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Affiliation(s)
- Hayley R Stoneman
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Adelle Price
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikole Scribner Trout
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Riley Lamont
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Souha Tifour
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikita Pozdeyev
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Kristy Crooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Meng Lin
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Christopher R Gignoux
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Katie M Marker
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Audrey E Hendricks
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
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3
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Goli RC, Chishi KG, Ganguly I, Singh S, Dixit S, Rathi P, Diwakar V, Sree C C, Limbalkar OM, Sukhija N, Kanaka K. Global and Local Ancestry and its Importance: A Review. Curr Genomics 2024; 25:237-260. [PMID: 39156729 PMCID: PMC11327809 DOI: 10.2174/0113892029298909240426094055] [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: 01/13/2024] [Revised: 03/02/2024] [Accepted: 03/11/2024] [Indexed: 08/20/2024] Open
Abstract
The fastest way to significantly change the composition of a population is through admixture, an evolutionary mechanism. In animal breeding history, genetic admixture has provided both short-term and long-term advantages by utilizing the phenomenon of complementarity and heterosis in several traits and genetic diversity, respectively. The traditional method of admixture analysis by pedigree records has now been replaced greatly by genome-wide marker data that enables more precise estimations. Among these markers, SNPs have been the popular choice since they are cost-effective, not so laborious, and automation of genotyping is easy. Certain markers can suggest the possibility of a population's origin from a sample of DNA where the source individual is unknown or unwilling to disclose their lineage, which are called Ancestry-Informative Markers (AIMs). Revealing admixture level at the locus-specific level is termed as local ancestry and can be exploited to identify signs of recent selective response and can account for genetic drift. Considering the importance of genetic admixture and local ancestry, in this mini-review, both concepts are illustrated, encompassing basics, their estimation/identification methods, tools/software used and their applications.
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Affiliation(s)
| | - Kiyevi G. Chishi
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
| | - Indrajit Ganguly
- ICAR-National Bureau of Animal Genetic Resources, Karnal, 132001, Haryana, India
| | - Sanjeev Singh
- ICAR-National Bureau of Animal Genetic Resources, Karnal, 132001, Haryana, India
| | - S.P. Dixit
- ICAR-National Bureau of Animal Genetic Resources, Karnal, 132001, Haryana, India
| | - Pallavi Rathi
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
| | - Vikas Diwakar
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
| | - Chandana Sree C
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
| | | | - Nidhi Sukhija
- ICAR-National Dairy Research Institute, Karnal, 132001, Haryana, India
- Central Tasar Research and Training Institute, Ranchi, 835303, Jharkhand, India
| | - K.K Kanaka
- ICAR- Indian Institute of Agricultural Biotechnology, Ranchi, 834010, Jharkhand, India
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4
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Ayala NM, Genetti M, Corbett-Detig R. Inferring multi-locus selection in admixed populations. PLoS Genet 2023; 19:e1011062. [PMID: 38015992 PMCID: PMC10707604 DOI: 10.1371/journal.pgen.1011062] [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: 05/23/2023] [Revised: 12/08/2023] [Accepted: 11/13/2023] [Indexed: 11/30/2023] Open
Abstract
Admixture, the exchange of genetic information between distinct source populations, is thought to be a major source of adaptive genetic variation. Unlike mutation events, which periodically generate single alleles, admixture can introduce many selected alleles simultaneously. As such, the effects of linkage between selected alleles may be especially pronounced in admixed populations. However, existing tools for identifying selected mutations within admixed populations only account for selection at a single site, overlooking phenomena such as linkage among proximal selected alleles. Here, we develop and extensively validate a method for identifying and quantifying the individual effects of multiple linked selected sites on a chromosome in admixed populations. Our approach numerically calculates the expected local ancestry landscape in an admixed population for a given multi-locus selection model, and then maximizes the likelihood of the model. After applying this method to admixed populations of Drosophila melanogaster and Passer italiae, we found that the impacts between linked sites may be an important contributor to natural selection in admixed populations. Furthermore, for the situations we considered, the selection coefficients and number of selected sites are overestimated in analyses that do not consider the effects of linkage among selected sites. Our results imply that linkage among selected sites may be an important evolutionary force in admixed populations. This tool provides a powerful generalized method to investigate these crucial phenomena in diverse populations.
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Affiliation(s)
- Nicolas M. Ayala
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, California, United States of America
- Department of Biomolecular Engineering, University of California, Santa Cruz; Santa Cruz, California, United States of America
| | - Maximilian Genetti
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, California, United States of America
- Department of Biomolecular Engineering, University of California, Santa Cruz; Santa Cruz, California, United States of America
| | - Russell Corbett-Detig
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, California, United States of America
- Department of Biomolecular Engineering, University of California, Santa Cruz; Santa Cruz, California, United States of America
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5
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Harney É, Micheletti S, Bruwelheide KS, Freyman WA, Bryc K, Akbari A, Jewett E, Comer E, Louis Gates H, Heywood L, Thornton J, Curry R, Ancona Esselmann S, Barca KG, Sedig J, Sirak K, Olalde I, Adamski N, Bernardos R, Broomandkhoshbacht N, Ferry M, Qiu L, Stewardson K, Workman JN, Zalzala F, Mallick S, Micco A, Mah M, Zhang Z, Rohland N, Mountain JL, Owsley DW, Reich D. The genetic legacy of African Americans from Catoctin Furnace. Science 2023; 381:eade4995. [PMID: 37535739 PMCID: PMC10958645 DOI: 10.1126/science.ade4995] [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: 08/22/2022] [Accepted: 06/20/2023] [Indexed: 08/05/2023]
Abstract
Few African Americans have been able to trace family lineages back to ancestors who died before the 1870 United States Census, the first in which all Black people were listed by name. We analyzed 27 individuals from Maryland's Catoctin Furnace African American Cemetery (1774-1850), identifying 41,799 genetic relatives among consenting research participants in 23andMe, Inc.'s genetic database. One of the highest concentrations of close relatives is in Maryland, suggesting that descendants of the Catoctin individuals remain in the area. We find that many of the Catoctin individuals derived African ancestry from the Wolof or Kongo groups and European ancestry from Great Britain and Ireland. This study demonstrates the power of joint analysis of historical DNA and large datasets generated through direct-to-consumer ancestry testing.
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Affiliation(s)
- Éadaoin Harney
- 23andMe, Inc.; Sunnyvale, CA 94043, USA
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA, 02138, USA
| | | | - Karin S. Bruwelheide
- Department of Anthropology, National Museum of Natural History, Smithsonian Institution; Washington DC 20560, USA
| | | | | | - Ali Akbari
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA, 02138, USA
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
| | | | - Elizabeth Comer
- Catoctin Furnace Historical Society; Thurmont, MD, 21788, USA
| | - Henry Louis Gates
- Hutchins Center for African and African American Research, Harvard University; Cambridge, MA 02138, USA
| | - Linda Heywood
- Department of History/African American Studies, Boston University; Brookline, MA 02446, USA
| | - John Thornton
- Department of History/African American Studies, Boston University; Brookline, MA 02446, USA
| | - Roslyn Curry
- 23andMe, Inc.; Sunnyvale, CA 94043, USA
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA, 02138, USA
| | | | - Kathryn G. Barca
- Department of Anthropology, National Museum of Natural History, Smithsonian Institution; Washington DC 20560, USA
| | - Jakob Sedig
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA, 02138, USA
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
| | - Kendra Sirak
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA, 02138, USA
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
| | - Iñigo Olalde
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA, 02138, USA
- BIOMICs Research Group, Department of Zoology and Animal Cell Biology, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
- Ikerbasque—Basque Foundation of Science, Bilbao, Spain
| | - Nicole Adamski
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
| | - Rebecca Bernardos
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
| | - Nasreen Broomandkhoshbacht
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
| | - Matthew Ferry
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
| | - Lijun Qiu
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
| | - Kristin Stewardson
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
| | - J. Noah Workman
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
| | - Fatma Zalzala
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
| | - Shop Mallick
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
- Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Adam Micco
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Matthew Mah
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
- Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
| | - Zhao Zhang
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
| | | | - Nadin Rohland
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
| | | | - Douglas W. Owsley
- Department of Anthropology, National Museum of Natural History, Smithsonian Institution; Washington DC 20560, USA
| | - David Reich
- Department of Human Evolutionary Biology, Harvard University; Cambridge, MA, 02138, USA
- Department of Genetics, Harvard Medical School; Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School; Boston, MA, 02115, USA
- Broad Institute of MIT and Harvard; Cambridge, MA, 02142, USA
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6
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Hamid I, Korunes KL, Schrider DR, Goldberg A. Localizing Post-Admixture Adaptive Variants with Object Detection on Ancestry-Painted Chromosomes. Mol Biol Evol 2023; 40:msad074. [PMID: 36947126 PMCID: PMC10116606 DOI: 10.1093/molbev/msad074] [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: 09/04/2022] [Revised: 03/14/2023] [Accepted: 03/20/2023] [Indexed: 03/23/2023] Open
Abstract
Gene flow between previously differentiated populations during the founding of an admixed or hybrid population has the potential to introduce adaptive alleles into the new population. If the adaptive allele is common in one source population, but not the other, then as the adaptive allele rises in frequency in the admixed population, genetic ancestry from the source containing the adaptive allele will increase nearby as well. Patterns of genetic ancestry have therefore been used to identify post-admixture positive selection in humans and other animals, including examples in immunity, metabolism, and animal coloration. A common method identifies regions of the genome that have local ancestry "outliers" compared with the distribution across the rest of the genome, considering each locus independently. However, we lack theoretical models for expected distributions of ancestry under various demographic scenarios, resulting in potential false positives and false negatives. Further, ancestry patterns between distant sites are often not independent. As a result, current methods tend to infer wide genomic regions containing many genes as under selection, limiting biological interpretation. Instead, we develop a deep learning object detection method applied to images generated from local ancestry-painted genomes. This approach preserves information from the surrounding genomic context and avoids potential pitfalls of user-defined summary statistics. We find the method is robust to a variety of demographic misspecifications using simulated data. Applied to human genotype data from Cabo Verde, we localize a known adaptive locus to a single narrow region compared with multiple or long windows obtained using two other ancestry-based methods.
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Affiliation(s)
- Iman Hamid
- Department of Evolutionary Anthropology, Duke University, Durham, NC
| | | | - Daniel R Schrider
- Department of Genetics, University of North Carolina, Chapel Hill, NC
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke University, Durham, NC
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7
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Gopalan S, Smith SP, Korunes K, Hamid I, Ramachandran S, Goldberg A. Human genetic admixture through the lens of population genomics. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200410. [PMID: 35430881 PMCID: PMC9014191 DOI: 10.1098/rstb.2020.0410] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 03/24/2022] [Indexed: 12/13/2022] Open
Abstract
Over the past 50 years, geneticists have made great strides in understanding how our species' evolutionary history gave rise to current patterns of human genetic diversity classically summarized by Lewontin in his 1972 paper, 'The Apportionment of Human Diversity'. One evolutionary process that requires special attention in both population genetics and statistical genetics is admixture: gene flow between two or more previously separated source populations to form a new admixed population. The admixture process introduces ancestry-based structure into patterns of genetic variation within and between populations, which in turn influences the inference of demographic histories, identification of genetic targets of selection and prediction of complex traits. In this review, we outline some challenges for admixture population genetics, including limitations of applying methods designed for populations without recent admixture to the study of admixed populations. We highlight recent studies and methodological advances that aim to overcome such challenges, leveraging genomic signatures of admixture that occurred in the past tens of generations to gain insights into human history, natural selection and complex trait architecture. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.
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Affiliation(s)
- Shyamalika Gopalan
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
| | - Samuel Pattillo Smith
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
- Department of Ecology, Evolution and Organismal Biology, Brown University, Providence, RI 02912, USA
| | - Katharine Korunes
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
| | - Iman Hamid
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
| | - Sohini Ramachandran
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
- Department of Ecology, Evolution and Organismal Biology, Brown University, Providence, RI 02912, USA
- Data Science Initiative, Brown University, Providence, RI 02912, USA
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
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8
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Cuadros-Espinoza S, Laval G, Quintana-Murci L, Patin E. The genomic signatures of natural selection in admixed human populations. Am J Hum Genet 2022; 109:710-726. [PMID: 35259336 DOI: 10.1016/j.ajhg.2022.02.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 02/14/2022] [Indexed: 12/15/2022] Open
Abstract
Admixture has been a pervasive phenomenon in human history, extensively shaping the patterns of population genetic diversity. There is increasing evidence to suggest that admixture can also facilitate genetic adaptation to local environments, i.e., admixed populations acquire beneficial mutations from source populations, a process that we refer to as "adaptive admixture." However, the role of adaptive admixture in human evolution and the power to detect it remain poorly characterized. Here, we use extensive computer simulations to evaluate the power of several neutrality statistics to detect natural selection in the admixed population, assuming multiple admixture scenarios. We show that statistics based on admixture proportions, Fadm and LAD, show high power to detect mutations that are beneficial in the admixed population, whereas other statistics, including iHS and FST, falsely detect neutral mutations that have been selected in the source populations only. By combining Fadm and LAD into a single, powerful statistic, we scanned the genomes of 15 worldwide, admixed populations for signatures of adaptive admixture. We confirm that lactase persistence and resistance to malaria have been under adaptive admixture in West Africans and in Malagasy, North Africans, and South Asians, respectively. Our approach also uncovers other cases of adaptive admixture, including APOL1 in Fulani nomads and PKN2 in East Indonesians, involved in resistance to infection and metabolism, respectively. Collectively, our study provides evidence that adaptive admixture has occurred in human populations whose genetic history is characterized by periods of isolation and spatial expansions resulting in increased gene flow.
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9
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Pan Y, Zhang C, Lu Y, Ning Z, Lu D, Gao Y, Zhao X, Yang Y, Guan Y, Mamatyusupu D, Xu S. Genomic diversity and post-admixture adaptation in the Uyghurs. Natl Sci Rev 2022; 9:nwab124. [PMID: 35350227 PMCID: PMC8953455 DOI: 10.1093/nsr/nwab124] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 05/30/2021] [Accepted: 06/07/2021] [Indexed: 11/17/2022] Open
Abstract
Population admixture results in genome-wide combinations of genetic variants derived from different ancestral populations of distinct ancestry, thus providing a unique opportunity for understanding the genetic determinants of phenotypic variation in humans. Here, we used whole-genome sequencing of 92 individuals with high coverage (30–60×) to systematically investigate genomic diversity in the Uyghurs living in Xinjiang, China (XJU), an admixed population of both European-like and East-Asian-like ancestry. The XJU population shows greater genetic diversity, especially a higher proportion of rare variants, compared with their ancestral source populations, corresponding to greater phenotypic diversity of XJU. Admixture-induced functional variants in EDAR were associated with the diversity of facial morphology in XJU. Interestingly, the interaction of functional variants between SLC24A5 and OCA2 likely influences the diversity of skin pigmentation. Notably, selection has seemingly been relaxed or canceled in several genes with significantly biased ancestry, such as HERC2–OCA2. Moreover, signatures of post-admixture adaptation in XJU were identified, including genes related to metabolism (e.g. CYP2D6), digestion (e.g. COL11A1), olfactory perception (e.g. ANO2) and immunity (e.g. HLA). Our results demonstrated population admixture as a driving force, locally or globally, in shaping human genetic and phenotypic diversity as well as in adaptive evolution.
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Affiliation(s)
- Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Chao Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
| | - Zhilin Ning
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Dongsheng Lu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Yang Gao
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University , Shanghai 201210, China
| | - Xiaohan Zhao
- Human Phenome Institute, Fudan University , Shanghai 201203, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
| | - Yaqun Guan
- Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University , Urumqi 830011, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University , Urumqi 830046, China
| | - Shuhua Xu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
- School of Life Science and Technology, ShanghaiTech University , Shanghai 201210, China
- Human Phenome Institute, Fudan University , Shanghai 201203, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences , Kunming 650223, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University , Zhengzhou 450052, China
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10
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Wu Y, Palmer JR, Rosenberg L, Ruiz-Narváez EA. Admixture mapping of anthropometric traits in the Black Women's Health Study: evidence of a shared African ancestry component with birth weight and type 2 diabetes. J Hum Genet 2022; 67:331-338. [PMID: 35017682 DOI: 10.1038/s10038-022-01010-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 12/27/2021] [Accepted: 12/29/2021] [Indexed: 11/09/2022]
Abstract
Prevalence of obesity, type 2 diabetes (T2D), and being born with low birth weight are much higher in African American women compared to U.S. white women. Genetic factors may contribute to the excess risk of these conditions. We conducted admixture mapping of body mass index (BMI) at age 18, adult BMI, and adult waist circumference and waist-to-hip ratio adjusted for BMI using 2918 ancestral informative markers in 2596 participants of the Black Women's Health Study. We also searched for evidence of shared African genetic ancestry components among the four examined anthropometric traits and among birth weight and T2D. We found that global percent African ancestry was associated with higher adult BMI. We also found that African ancestry at 9q34 was associated with lower BMI at age 18. Our shared ancestry analysis identified ten genomic regions with local African ancestry associated with multiple traits. Seven out of these ten genomic loci were related to T2D risk. Of special interest is the 12q14-21 region where local African ancestry was associated with low birth weight, low BMI, high BMI-adjusted waist-to-hip ratio, and high T2D risk. Findings in the 12q14-21 genomic locus are consistent with the fetal insulin hypothesis that postulates that low birth weight and T2D have a common genetic basis, and they support the hypothesis of a shared African genetic ancestry component linking low birth weight and T2D in African Americans. Future studies should identify the actual genetic variants responsible for the clustering of these conditions in African Americans.
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Affiliation(s)
- Yue Wu
- Department of Bioinformatics and Biostatistics, School of Life Science and Technology, Shanghai Jiao Tong University, Shanghai, China.,Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Julie R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA, USA
| | - Lynn Rosenberg
- Slone Epidemiology Center at Boston University, Boston, MA, USA
| | - Edward A Ruiz-Narváez
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA.
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11
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Laval G, Patin E, Boutillier P, Quintana-Murci L. Sporadic occurrence of recent selective sweeps from standing variation in humans as revealed by an approximate Bayesian computation approach. Genetics 2021; 219:6377789. [PMID: 34849862 DOI: 10.1093/genetics/iyab161] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 09/01/2021] [Indexed: 12/14/2022] Open
Abstract
During their dispersals over the last 100,000 years, modern humans have been exposed to a large variety of environments, resulting in genetic adaptation. While genome-wide scans for the footprints of positive Darwinian selection have increased knowledge of genes and functions potentially involved in human local adaptation, they have globally produced evidence of a limited contribution of selective sweeps in humans. Conversely, studies based on machine learning algorithms suggest that recent sweeps from standing variation are widespread in humans, an observation that has been recently questioned. Here, we sought to formally quantify the number of recent selective sweeps in humans, by leveraging approximate Bayesian computation and whole-genome sequence data. Our computer simulations revealed suitable ABC estimations, regardless of the frequency of the selected alleles at the onset of selection and the completion of sweeps. Under a model of recent selection from standing variation, we inferred that an average of 68 (from 56 to 79) and 140 (from 94 to 198) sweeps occurred over the last 100,000 years of human history, in African and Eurasian populations, respectively. The former estimation is compatible with human adaptation rates estimated since divergence with chimps, and reveals numbers of sweeps per generation per site in the range of values estimated in Drosophila. Our results confirm the rarity of selective sweeps in humans and show a low contribution of sweeps from standing variation to recent human adaptation.
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Affiliation(s)
- Guillaume Laval
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France
| | - Etienne Patin
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France
| | - Pierre Boutillier
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France.,Human Genomics and Evolution, Collège de France, 75005 Paris, France
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12
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Warne RT. Between-Group Mean Differences in Intelligence in the United States Are >0% Genetically Caused: Five Converging Lines of Evidence. AMERICAN JOURNAL OF PSYCHOLOGY 2021. [DOI: 10.5406/amerjpsyc.134.4.0479] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Abstract
The past 30 years of research in intelligence has produced a wealth of knowledge about the causes and consequences of differences in intelligence between individuals, and today mainstream opinion is that individual differences in intelligence are caused by both genetic and environmental influences. Much more contentious is the discussion over the cause of mean intelligence differences between racial or ethnic groups. In contrast to the general consensus that interindividual differences are both genetic and environmental in origin, some claim that mean intelligence differences between racial groups are completely environmental in origin, whereas others postulate a mix of genetic and environmental causes. In this article I discuss 5 lines of research that provide evidence that mean differences in intelligence between racial and ethnic groups are partially genetic. These lines of evidence are findings in support of Spearman’s hypothesis, consistent results from tests of measurement invariance across American racial groups, the mathematical relationship that exists for between-group and within-group sources of heritability, genomic data derived from genome-wide association studies of intelligence and polygenic scores applied to diverse samples, and admixture studies. I also discuss future potential lines of evidence regarding the causes of average group differences across racial groups. However, the data are not fully conclusive, and the exact degree to which genes influence intergroup mean differences in intelligence is not known. This discussion applies only to native English speakers born in the United States and not necessarily to any other human populations.
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13
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Fu R, Qin P, Zou X, Hu Z, Hong N, Wang Y, Jin W. A Comprehensive Characterization of Monoallelic Expression During Hematopoiesis and Leukemogenesis via Single-Cell RNA-Sequencing. Front Cell Dev Biol 2021; 9:702897. [PMID: 34722498 PMCID: PMC8548578 DOI: 10.3389/fcell.2021.702897] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 09/13/2021] [Indexed: 12/30/2022] Open
Abstract
Single-cell RNA-sequencing (scRNA-seq) is becoming a powerful tool to investigate monoallelic expression (MAE) in various developmental and pathological processes. However, our knowledge of MAE during hematopoiesis and leukemogenesis is limited. In this study, we conducted a systematic interrogation of MAEs in bone marrow mononuclear cells (BMMCs) at single-cell resolution to construct a MAE atlas of BMMCs. We identified 1,020 constitutive MAEs in BMMCs, which included imprinted genes such as MEG8, NAP1L5, and IRAIN. We classified the BMMCs into six cell types and identified 74 cell type specific MAEs including MTSS1, MOB1A, and TCF12. We further identified 114 random MAEs (rMAEs) at single-cell level, with 78.1% single-allele rMAE and 21.9% biallelic mosaic rMAE. Many MAEs identified in BMMCs have not been reported and are potentially hematopoietic specific, supporting MAEs are functional relevance. Comparison of BMMC samples from a leukemia patient with multiple clinical stages showed the fractions of constitutive MAE were correlated with fractions of leukemia cells in BMMCs. Further separation of the BMMCs into leukemia cells and normal cells showed that leukemia cells have much higher constitutive MAE and rMAEs than normal cells. We identified the leukemia cell-specific MAEs and relapsed leukemia cell-specific MAEs, which were enriched in immune-related functions. These results indicate MAE is prevalent and is an important gene regulation mechanism during hematopoiesis and leukemogenesis. As the first systematical interrogation of constitutive MAEs, cell type specific MAEs, and rMAEs during hematopoiesis and leukemogenesis, the study significantly increased our knowledge about the features and functions of MAEs.
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Affiliation(s)
- Ruiqing Fu
- Shenzhen Key Laboratory of Microbiology and Gene Engineering, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China.,Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Optoelectronic Engineering, Shenzhen University, Shenzhen, China.,School of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, China
| | - Pengfei Qin
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Xianghui Zou
- School of Food Engineering and Biotechnology, Hanshan Normal University, Chaozhou, China
| | - Zhangli Hu
- Shenzhen Key Laboratory of Microbiology and Gene Engineering, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China.,Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Optoelectronic Engineering, Shenzhen University, Shenzhen, China
| | - Ni Hong
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Yun Wang
- Shenzhen Key Laboratory of Microbiology and Gene Engineering, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
| | - Wenfei Jin
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
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14
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Yougbaré B, Ouédraogo D, Tapsoba ASR, Soudré A, Zoma BL, Orozco-terWengel P, Moumouni S, Ouédraogo-Koné S, Wurzinger M, Tamboura HH, Traoré A, Mwai OA, Sölkner J, Khayatzadeh N, Mészáros G, Burger PA. Local Ancestry to Identify Selection in Response to Trypanosome Infection in Baoulé x Zebu Crossbred Cattle in Burkina Faso. Front Genet 2021; 12:670390. [PMID: 34646296 PMCID: PMC8504455 DOI: 10.3389/fgene.2021.670390] [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: 02/21/2021] [Accepted: 08/09/2021] [Indexed: 11/15/2022] Open
Abstract
The genomes of crossbred (admixed) individuals are a mosaic of ancestral haplotypes formed by recombination in each generation. The proportion of these ancestral haplotypes in certain genomic regions can be responsible for either susceptibility or tolerance against pathogens, and for performances in production traits. Using a medium-density genomic marker panel from the Illumina Bovine SNP50 BeadChip, we estimated individual admixture proportions for Baoulé x Zebu crossbred cattle in Burkina Faso, which were tested for trypanosome infection by direct ELISA from blood samples. Furthermore, we calculated local ancestry deviation from average for each SNP across 29 autosomes to identify potential regions under selection in the trypanotolerant Baoulé cattle and their crossbreds. We identified significant deviation from the local average ancestry (above 5 and 10% genome-wide thresholds) on chromosomes 8 and 19 in the positive animals, while the negative ones showed higher deviation on chromosomes 6, 19, 21, and 22. Some candidate genes on chromosome 6 (PDGFRA) and chromosome 19 (CDC6) have been found associated to trypanotolerance in West African taurines. Screening for FST outliers in trypanosome positive/negative animals we detected seven variants putatively under selection. Finally, we identified a minimum set of highly ancestry informative markers for routine admixture testing. The results of this study contribute to a better understanding of the genetic basis of trypanotolerance in Baoulé cattle and their crossbreeds. Furthermore, we provide a small informative marker set to monitor admixture in this valuable indigenous breed. As such, our results are important for conserving the genetic uniqueness and trypanotolerance of Baoulé cattle, as well as for the improvement of Baoulé and Zebu crossbreds in specific community-based breeding programs.
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Affiliation(s)
- Bernadette Yougbaré
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria.,Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | - Dominique Ouédraogo
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria.,Institut du Développement Rural, Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | - Arnaud S R Tapsoba
- Institut du Développement Rural, Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | - Albert Soudré
- Unité de Formation et de Recherche en Sciences et Technologies, Université Norbert Zongo, Koudougou, Burkina Faso
| | - Bienvenue L Zoma
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria.,Institut du Développement Rural, Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | | | - Sanou Moumouni
- Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | | | - Maria Wurzinger
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria
| | - Hamidou H Tamboura
- Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | - Amadou Traoré
- Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | - Okeyo Ally Mwai
- International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Johann Sölkner
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria
| | - Negar Khayatzadeh
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria.,SUISAG, Sempach, Switzerland
| | - Gábor Mészáros
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria
| | - Pamela A Burger
- Research Institute of Wildlife Ecology, Vetmeduni Vienna, Savoyenstraße 1, Vienna, Austria
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15
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Yang XY, Rakha A, Chen W, Hou J, Qi XB, Shen QK, Dai SS, Sulaiman X, Abdulloevich NT, Afanasevna ME, Ibrohimovich KB, Chen X, Yang WK, Adnan A, Zhao RH, Yao YG, Su B, Peng MS, Zhang YP. Tracing the Genetic Legacy of the Tibetan Empire in the Balti. Mol Biol Evol 2021; 38:1529-1536. [PMID: 33283852 PMCID: PMC8042757 DOI: 10.1093/molbev/msaa313] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
The rise and expansion of Tibetan Empire in the 7th to 9th centuries AD affected the course of history across East Eurasia, but the genetic impact of Tibetans on surrounding populations remains undefined. We sequenced 60 genomes for four populations from Pakistan and Tajikistan to explore their demographic history. We showed that the genomes of Balti people from Baltistan comprised 22.6–26% Tibetan ancestry. We inferred a single admixture event and dated it to about 39–21 generations ago, a period that postdated the conquest of Baltistan by the ancient Tibetan Empire. The analyses of mitochondrial DNA, Y, and X chromosome data indicated that both ancient Tibetan males and females were involved in the male-biased dispersal. Given the fact that the Balti people adopted Tibetan language and culture in history, our study suggested the impact of Tibetan Empire on Baltistan involved dominant cultural and minor demic diffusion.
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Affiliation(s)
- Xing-Yan Yang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming, China
| | - Allah Rakha
- Department of Forensic Sciences, University of Health Sciences, Lahore, Pakistan.,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
| | - Wei Chen
- College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, China.,State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, China
| | - Juzhi Hou
- Key Laboratory of Alpine Ecology (LAE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| | - Xue-Bin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Quan-Kuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Shan-Shan Dai
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Xierzhatijiang Sulaiman
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | | | - Manilova Elena Afanasevna
- E.N. Pavlovsky Institute of Zoology and Parasitology, Academy of Sciences of Republic of Tajikistan, Dushanbe, Tajikistan
| | | | - Xi Chen
- Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, China.,Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China
| | - Wei-Kang Yang
- Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, China.,Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China
| | - Atif Adnan
- Department of Human Anatomy, School of Basic Medicine, China Medical University, Shenyang, China
| | - Ruo-Han Zhao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yong-Gang Yao
- 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.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Min-Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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16
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Ongaro L, Mondal M, Flores R, Marnetto D, Molinaro L, Alarcón-Riquelme ME, Moreno-Estrada A, Mabunda N, Ventura M, Tambets K, Hellenthal G, Capelli C, Kivisild T, Metspalu M, Pagani L, Montinaro F. Continental-scale genomic analysis suggests shared post-admixture adaptation in the Americas. Hum Mol Genet 2021; 30:2123-2134. [PMID: 34196708 PMCID: PMC8561420 DOI: 10.1093/hmg/ddab177] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 06/21/2021] [Accepted: 06/23/2021] [Indexed: 01/05/2023] Open
Abstract
American populations are one of the most interesting examples of recently admixed groups, where ancestral components from three major continental human groups (Africans, Eurasians and Native Americans) have admixed within the last 15 generations. Recently, several genetic surveys focusing on thousands of individuals shed light on the geography, chronology and relevance of these events. However, even though gene flow could drive adaptive evolution, it is unclear whether and how natural selection acted on the resulting genetic variation in the Americas. In this study, we analysed the patterns of local ancestry of genomic fragments in genome-wide data for ~ 6000 admixed individuals from 10 American countries. In doing so, we identified regions characterized by a divergent ancestry profile (DAP), in which a significant over or under ancestral representation is evident. Our results highlighted a series of genomic regions with DAPs associated with immune system response and relevant medical traits, with the longest DAP region encompassing the human leukocyte antigen locus. Furthermore, we found that DAP regions are enriched in genes linked to cancer-related traits and autoimmune diseases. Then, analysing the biological impact of these regions, we showed that natural selection could have acted preferentially towards variants located in coding and non-coding transcripts and characterized by a high deleteriousness score. Taken together, our analyses suggest that shared patterns of post admixture adaptation occurred at a continental scale in the Americas, affecting more often functional and impactful genomic variants.
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Affiliation(s)
- Linda Ongaro
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia
| | - Mayukh Mondal
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia
| | - Rodrigo Flores
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia
| | - Davide Marnetto
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia
| | - Ludovica Molinaro
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia
| | - Marta E Alarcón-Riquelme
- Department of Medical Genomics, GENYO. Centro Pfizer - Universidad de Granada - Junta de Andalucía de Genómica e Investigación Oncológica, Av de la Ilustración 114, Parque Tecnológico de la Salud (PTS), 18016, Granada, Spain
| | - Andrés Moreno-Estrada
- National Laboratory of Genomics for biodiversity (LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36821, Mexico
| | - Nedio Mabunda
- Instituto Nacional de Saúde, Distrito de Marracuene, Estrada Nacional N°1, Província de Maputo, Maputo, 1120, Mozambique
| | - Mario Ventura
- Department of Biology-Genetics, University of Bari, Bari, 70126, Italy
| | - Kristiina Tambets
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia
| | - Garrett Hellenthal
- Department of Genetics, Evolution and Environment and UCL Genetics Institute, University College London, London WC1E 6BT, UK
| | - Cristian Capelli
- Department of Zoology, University of Oxford, Oxford, UK.,Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy
| | - Toomas Kivisild
- Department of Human Genetics, KU Leuven, Herestraat 49 - box 602, B-3000, Leuven, Belgium
| | - Mait Metspalu
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia
| | - Luca Pagani
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia.,Department of Biology, University of Padua, Padua, Italy
| | - Francesco Montinaro
- Estonian Biocentre, Institute of Genomics, Tartu, Riia 23b, 51010, Estonia.,Department of Biology-Genetics, University of Bari, Bari, 70126, Italy
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17
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Abstract
Throughout human history, large-scale migrations have facilitated the formation of populations with ancestry from multiple previously separated populations. This process leads to subsequent shuffling of genetic ancestry through recombination, producing variation in ancestry between populations, among individuals in a population, and along the genome within an individual. Recent methodological and empirical developments have elucidated the genomic signatures of this admixture process, bringing previously understudied admixed populations to the forefront of population and medical genetics. Under this theme, we present a collection of recent PLOS Genetics publications that exemplify recent progress in human genetic admixture studies, and we discuss potential areas for future work.
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Affiliation(s)
- Katharine L. Korunes
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina, United States of America
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina, United States of America
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18
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Atkinson EG, Maihofer AX, Kanai M, Martin AR, Karczewski KJ, Santoro ML, Ulirsch JC, Kamatani Y, Okada Y, Finucane HK, Koenen KC, Nievergelt CM, Daly MJ, Neale BM. Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power. Nat Genet 2021; 53:195-204. [PMID: 33462486 PMCID: PMC7867648 DOI: 10.1038/s41588-020-00766-y] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 12/15/2020] [Indexed: 12/26/2022]
Abstract
Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African-European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants.
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Affiliation(s)
- Elizabeth G Atkinson
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Adam X Maihofer
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Konrad J Karczewski
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Marcos L Santoro
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
- Departamento de Morfologia e Genética, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Jacob C Ulirsch
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Graduate School of Medicine, Osaka University, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
| | - Hilary K Finucane
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Karestan C Koenen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Mark J Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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19
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Hamid I, Korunes KL, Beleza S, Goldberg A. Rapid adaptation to malaria facilitated by admixture in the human population of Cabo Verde. eLife 2021; 10:e63177. [PMID: 33393457 PMCID: PMC7815310 DOI: 10.7554/elife.63177] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 01/04/2021] [Indexed: 12/20/2022] Open
Abstract
Humans have undergone large migrations over the past hundreds to thousands of years, exposing ourselves to new environments and selective pressures. Yet, evidence of ongoing or recent selection in humans is difficult to detect. Many of these migrations also resulted in gene flow between previously separated populations. These recently admixed populations provide unique opportunities to study rapid evolution in humans. Developing methods based on distributions of local ancestry, we demonstrate that this sort of genetic exchange has facilitated detectable adaptation to a malaria parasite in the admixed population of Cabo Verde within the last ~20 generations. We estimate that the selection coefficient is approximately 0.08, one of the highest inferred in humans. Notably, we show that this strong selection at a single locus has likely affected patterns of ancestry genome-wide, potentially biasing demographic inference. Our study provides evidence of adaptation in a human population on historical timescales.
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Affiliation(s)
- Iman Hamid
- Department of Evolutionary Anthropology, Duke UniversityDurhamUnited States
| | | | - Sandra Beleza
- Department of Genetics and Genome Biology, University of LeicesterLeicesterUnited Kingdom
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke UniversityDurhamUnited States
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20
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Affiliation(s)
- Russell T. Warne
- Utah Valley University, 800 West University Parkway MC 115, Orem, UT 84604, E-mail:
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21
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Walsh S, Pagani L, Xue Y, Laayouni H, Tyler-Smith C, Bertranpetit J. Positive selection in admixed populations from Ethiopia. BMC Genet 2020; 21:108. [PMID: 33092534 PMCID: PMC7580818 DOI: 10.1186/s12863-020-00908-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 08/27/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND In the process of adaptation of humans to their environment, positive or adaptive selection has played a main role. Positive selection has, however, been under-studied in African populations, despite their diversity and importance for understanding human history. RESULTS Here, we have used 119 available whole-genome sequences from five Ethiopian populations (Amhara, Oromo, Somali, Wolayta and Gumuz) to investigate the modes and targets of positive selection in this part of the world. The site frequency spectrum-based test SFselect was applied to idfentify a wide range of events of selection (old and recent), and the haplotype-based statistic integrated haplotype score to detect more recent events, in each case with evaluation of the significance of candidate signals by extensive simulations. Additional insights were provided by considering admixture proportions and functional categories of genes. We identified both individual loci that are likely targets of classic sweeps and groups of genes that may have experienced polygenic adaptation. We found population-specific as well as shared signals of selection, with folate metabolism and the related ultraviolet response and skin pigmentation standing out as a shared pathway, perhaps as a response to the high levels of ultraviolet irradiation, and in addition strong signals in genes such as IFNA, MRC1, immunoglobulins and T-cell receptors which contribute to defend against pathogens. CONCLUSIONS Signals of positive selection were detected in Ethiopian populations revealing novel adaptations in East Africa, and abundant targets for functional follow-up.
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Affiliation(s)
- Sandra Walsh
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88 08003, Barcelona, Catalonia, Spain
| | - Luca Pagani
- Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
- Department of Biology, University of Padova, 35131, Padova, Italy
| | - Yali Xue
- The Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK
| | - Hafid Laayouni
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88 08003, Barcelona, Catalonia, Spain
- Bioinformatics Studies, ESCI-UPF, Barcelona, Catalonia, Spain
| | - Chris Tyler-Smith
- The Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK.
| | - Jaume Bertranpetit
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88 08003, Barcelona, Catalonia, Spain.
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22
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Geza E, Mugo J, Mulder NJ, Wonkam A, Chimusa ER, Mazandu GK. A comprehensive survey of models for dissecting local ancestry deconvolution in human genome. Brief Bioinform 2020; 20:1709-1724. [PMID: 30010715 DOI: 10.1093/bib/bby044] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Revised: 04/16/2018] [Indexed: 11/14/2022] Open
Abstract
Over the past decade, studies of admixed populations have increasingly gained interest in both medical and population genetics. These studies have so far shed light on the patterns of genetic variation throughout modern human evolution and have improved our understanding of the demographics and adaptive processes of human populations. To date, there exist about 20 methods or tools to deconvolve local ancestry. These methods have merits and drawbacks in estimating local ancestry in multiway admixed populations. In this article, we survey existing ancestry deconvolution methods, with special emphasis on multiway admixture, and compare these methods based on simulation results reported by different studies, computational approaches used, including mathematical and statistical models, and biological challenges related to each method. This should orient users on the choice of an appropriate method or tool for given population admixture characteristics and update researchers on current advances, challenges and opportunities behind existing ancestry deconvolution methods.
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Affiliation(s)
- Ephifania Geza
- African Institute for Mathematical Sciences, Muizenberg, Cape Town 7945, South Africa.,Computational Biology Division, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, IDM, University of Cape Town, Cape Town 7925, South Africa
| | - Jacquiline Mugo
- African Institute for Mathematical Sciences, Muizenberg, Cape Town 7945, South Africa
| | - Nicola J Mulder
- Computational Biology Division, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, IDM, University of Cape Town, Cape Town 7925, South Africa
| | - Ambroise Wonkam
- Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town 7925, South Africa
| | - Emile R Chimusa
- Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town 7925, South Africa
| | - Gaston K Mazandu
- African Institute for Mathematical Sciences, Muizenberg, Cape Town 7945, South Africa.,Computational Biology Division, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, IDM, University of Cape Town, Cape Town 7925, South Africa.,Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town 7925, South Africa
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23
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Norris ET, Rishishwar L, Chande AT, Conley AB, Ye K, Valderrama-Aguirre A, Jordan IK. Admixture-enabled selection for rapid adaptive evolution in the Americas. Genome Biol 2020; 21:29. [PMID: 32028992 PMCID: PMC7006128 DOI: 10.1186/s13059-020-1946-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 01/24/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Admixture occurs when previously isolated populations come together and exchange genetic material. We hypothesize that admixture can enable rapid adaptive evolution in human populations by introducing novel genetic variants (haplotypes) at intermediate frequencies, and we test this hypothesis through the analysis of whole genome sequences sampled from admixed Latin American populations in Colombia, Mexico, Peru, and Puerto Rico. RESULTS Our screen for admixture-enabled selection relies on the identification of loci that contain more or less ancestry from a given source population than would be expected given the genome-wide ancestry frequencies. We employ a combined evidence approach to evaluate levels of ancestry enrichment at single loci across multiple populations and multiple loci that function together to encode polygenic traits. We find cross-population signals of African ancestry enrichment at the major histocompatibility locus on chromosome 6, consistent with admixture-enabled selection for enhanced adaptive immune response. Several of the human leukocyte antigen genes at this locus, such as HLA-A, HLA-DRB51, and HLA-DRB5, show independent evidence of positive selection prior to admixture, based on extended haplotype homozygosity in African populations. A number of traits related to inflammation, blood metabolites, and both the innate and adaptive immune system show evidence of admixture-enabled polygenic selection in Latin American populations. CONCLUSIONS The results reported here, considered together with the ubiquity of admixture in human evolution, suggest that admixture serves as a fundamental mechanism that drives rapid adaptive evolution in human populations.
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Affiliation(s)
- Emily T. Norris
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332 USA
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
| | - Lavanya Rishishwar
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332 USA
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
| | - Aroon T. Chande
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332 USA
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
| | - Andrew B. Conley
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
| | - Kaixiong Ye
- Department of Genetics, University of Georgia, Athens, GA USA
- Institute of Bioinformatics, University of Georgia, Athens, GA USA
| | - Augusto Valderrama-Aguirre
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
- Biomedical Research Institute (COL0082529), Cali, Colombia
- Universidad Santiago de Cali, Cali, Colombia
| | - I. King Jordan
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332 USA
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
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24
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Yelmen B, Mondal M, Marnetto D, Pathak AK, Montinaro F, Gallego Romero I, Kivisild T, Metspalu M, Pagani L. Ancestry-Specific Analyses Reveal Differential Demographic Histories and Opposite Selective Pressures in Modern South Asian Populations. Mol Biol Evol 2020; 36:1628-1642. [PMID: 30952160 PMCID: PMC6657728 DOI: 10.1093/molbev/msz037] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Genetic variation in contemporary South Asian populations follows a northwest to southeast decreasing cline of shared West Eurasian ancestry. A growing body of ancient DNA evidence is being used to build increasingly more realistic models of demographic changes in the last few thousand years. Through high-quality modern genomes, these models can be tested for gene and genome level deviations. Using local ancestry deconvolution and masking, we reconstructed population-specific surrogates of the two main ancestral components for more than 500 samples from 25 South Asian populations and showed our approach to be robust via coalescent simulations. Our f3 and f4 statistics–based estimates reveal that the reconstructed haplotypes are good proxies for the source populations that admixed in the area and point to complex interpopulation relationships within the West Eurasian component, compatible with multiple waves of arrival, as opposed to a simpler one wave scenario. Our approach also provides reliable local haplotypes for future downstream analyses. As one such example, the local ancestry deconvolution in South Asians reveals opposite selective pressures on two pigmentation genes (SLC45A2 and SLC24A5) that are common or fixed in West Eurasians, suggesting post-admixture purifying and positive selection signals, respectively.
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Affiliation(s)
- Burak Yelmen
- Institute of Genomics, University of Tartu, Tartu, Estonia.,Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Mayukh Mondal
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Ajai K Pathak
- Institute of Genomics, University of Tartu, Tartu, Estonia.,Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Francesco Montinaro
- Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Irene Gallego Romero
- Melbourne Integrative Genomics and School of BioSciences, University of Melbourne, Parkville, Australia
| | - Toomas Kivisild
- Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Mait Metspalu
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Luca Pagani
- Institute of Genomics, University of Tartu, Tartu, Estonia.,APE Lab, Department of Biology, University of Padova, Padova, Italy
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25
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Francis-Lyon PA, Malik F, Cheng X, Ghezavati A, Xin F, Cai R. TRPV6 as a Putative Genomic Susceptibility Locus Influencing Racial Disparities in Cancer. Cancer Prev Res (Phila) 2020; 13:423-428. [PMID: 31996368 DOI: 10.1158/1940-6207.capr-19-0351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 11/15/2019] [Accepted: 01/22/2020] [Indexed: 11/16/2022]
Abstract
It is well established that African Americans exhibit higher incidence, higher mortality, and more aggressive forms of some cancers, including those of breast, prostate, colon, stomach, and cervix. Here we examine the ancestral haplotype of the TRPV6 calcium channel as a putative genomic factor in this racial divide. The minor (ancestral) allele frequency is 60% in people of African ancestry, but between 1% and 11% in all other populations. Research on TRPV6 structure/function, its association with specific cancers, and the evolutionary-ecological conditions that impacted selection of its haplotypes are synthesized to provide evidence for TRPV6 as a germline susceptibility locus in cancer. Recently elucidated mechanisms of TRPV6 channel deactivation are discussed in relation to the location of the allele favored in selection, suggesting a reduced capacity to inactivate the channel in those who have the ancestral haplotype. This could result in an excessively high cellular Ca2+, which has been implicated in cancer, for those in settings where calcium intake is far higher than in their ancestral environment. A recent report associating increasing calcium intake with a pattern of increase in aggressive prostate cancer in African-American but not European-American men may be related. If TRPV6 is found to be associated with cancer, further research would be warranted to improve risk assessment and examine interventions with the aim of improving cancer outcomes for people of African ancestry.
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Affiliation(s)
| | - Fahreen Malik
- University of San Francisco, Health Informatics Program, San Francisco, California
| | - Xiaoyun Cheng
- University of San Francisco, Health Informatics Program, San Francisco, California
| | - Alireza Ghezavati
- University of San Francisco, Health Informatics Program, San Francisco, California
| | - Feihan Xin
- University of San Francisco, Health Informatics Program, San Francisco, California
| | - Rafiki Cai
- Friends of the Congo, Chief Technology Officer, Washington, District of Columbia
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26
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Abstract
Local ancestry, defined as the genetic ancestry at a genomic location of an admixed individual, is widely used as a genetic marker in genetic association and evolutionary genetics studies. Many methods have been developed to infer the local ancestries in a set of unrelated individuals, a few of them have been extended to small nuclear families, but none can be applied to large (e.g. three-generation) pedigrees. In this study, we developed a method, FamANC, that can improve the accuracy of local ancestry inference in large pedigrees by: (1) using an existing algorithm to infer local ancestries for all individuals in a family, assuming (contrary to fact) they are unrelated, and (2) improving its accuracy by correcting inference errors using pedigree structure. Applied on African-American pedigrees from the Cleveland Family Study, FamANC was able to correct all identified Mendelian errors and most of double crossovers.
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27
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Wharton W, Kollhoff AL, Gangishetti U, Verble DD, Upadhya S, Zetterberg H, Kumar V, Watts KD, Kippels AJ, Gearing M, Howell JC, Parker MW, Hu WT. Interleukin 9 alterations linked to alzheimer disease in african americans. Ann Neurol 2019; 86:407-418. [PMID: 31271450 PMCID: PMC6800153 DOI: 10.1002/ana.25543] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 07/01/2019] [Accepted: 07/01/2019] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Compared to older Caucasians, older African Americans have higher risks of developing Alzheimer disease (AD) and lower cerebrospinal fluid (CSF) tau biomarker levels. It is not known whether tau-related differences begin earlier in life or whether race modifies other AD-related biomarkers such as inflammatory proteins. METHODS We performed multiplex cytokine analysis in a healthy middle-aged cohort with family history of AD (n = 68) and an older cohort (n = 125) with normal cognition (NC), mild cognitive impairment, or AD dementia. After determining baseline interleukin (IL)-9 level and AD-associated IL-9 change to differ according to race, we performed immunohistochemical analysis for proteins mechanistically linked to IL-9 in brains of African Americans and Caucasians (n = 38), and analyzed postmortem IL-9-related gene expression profiles in the publicly available Mount Sinai cohort (26 African Americans and 180 Caucasians). RESULTS Compared to Caucasians with NC, African Americans with NC had lower CSF tau, p-Tau181 , and IL-9 levels in both living cohorts. Conversely, AD was only correlated with increased CSF IL-9 levels in African Americans but not Caucasians. Immunohistochemical analysis revealed perivascular, neuronal, and glial cells immunoreactive to IL-9, and quantitative analysis in independent US cohorts showed AD to correlate with molecular changes (upstream differentiation marker and downstream effector cell marker) of IL-9 upregulation only in African Americans but not Caucasians. INTERPRETATION Baseline and AD-associated IL-9 differences between African Americans and Caucasians point to distinct molecular phenotypes for AD according to ancestry. Genetic and nongenetic factors need to be considered in future AD research involving unique populations. ANN NEUROL 2019;86:407-418.
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Affiliation(s)
- Whitney Wharton
- Department of Neurology, Emory University, Atlanta, GA
- Alzheimer's Disease Research Center, Emory University, Atlanta, GA
| | | | | | | | | | - Henrik Zetterberg
- UK Dementia Research Institute at University College London, London, United Kingdom
| | - Veena Kumar
- Department of Neurology, Emory University, Atlanta, GA
| | - Kelly D Watts
- Department of Neurology, Emory University, Atlanta, GA
| | - Andrea J Kippels
- Department of Neurology, Emory University, Atlanta, GA
- Alzheimer's Disease Research Center, Emory University, Atlanta, GA
| | - Marla Gearing
- Alzheimer's Disease Research Center, Emory University, Atlanta, GA
| | - J Christina Howell
- Department of Neurology, Emory University, Atlanta, GA
- Alzheimer's Disease Research Center, Emory University, Atlanta, GA
| | - Monica W Parker
- Department of Neurology, Emory University, Atlanta, GA
- Alzheimer's Disease Research Center, Emory University, Atlanta, GA
| | - William T Hu
- Department of Neurology, Emory University, Atlanta, GA
- Alzheimer's Disease Research Center, Emory University, Atlanta, GA
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28
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Cheruiyot EK, Bett RC, Amimo JO, Zhang Y, Mrode R, Mujibi FDN. Signatures of Selection in Admixed Dairy Cattle in Tanzania. Front Genet 2018; 9:607. [PMID: 30619449 PMCID: PMC6305962 DOI: 10.3389/fgene.2018.00607] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 11/19/2018] [Indexed: 01/07/2023] Open
Abstract
Multiple studies have investigated selection signatures in domestic cattle and other species. However, there is a dearth of information about the response to selection in genomes of highly admixed crossbred cattle in relation to production and adaptation to tropical environments. In this study, we evaluated 839 admixed crossbred cows sampled from two major dairy regions in Tanzania namely Rungwe and Lushoto districts, in order to understand their genetic architecture and detect genomic regions showing preferential selection. Animals were genotyped at 150,000 SNP loci using the Geneseek Genomic Profiler (GGP) High Density (HD) SNP array. Population structure analysis showed a large within-population genetic diversity in the study animals with a high degree of variation in admixture ranging between 7 and 100% taurine genes (dairyness) of mostly Holstein and Friesian ancestry. We explored evidence of selection signatures using three statistical methods (iHS, XP-EHH, and pcadapt). Selection signature analysis identified 108 candidate selection regions in the study population. Annotation of these regions yielded interesting genes potentially under strong positive selection including ABCG2, ABCC2, XKR4, LYN, TGS1, TOX, HERC6, KIT, PLAG1, CHCHD7, NCAPG, and LCORL that are involved in multiple biological pathways underlying production and adaptation processes. Several candidate selection regions showed an excess of African taurine ancestral allele dosage. Our results provide further useful insight into potential selective sweeps in the genome of admixed cattle with possible adaptive and productive importance. Further investigations will be necessary to better characterize these candidate regions with respect to their functional significance to tropical adaptations for dairy cattle.
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Affiliation(s)
- Evans Kiptoo Cheruiyot
- Department of Animal Production, College of Agriculture and Veterinary Sciences, University of Nairobi, Nairobi, Kenya.,USOMI Limited, Nairobi, Kenya
| | - Rawlynce Cheruiyot Bett
- Department of Animal Production, College of Agriculture and Veterinary Sciences, University of Nairobi, Nairobi, Kenya
| | - Joshua Oluoch Amimo
- Department of Animal Production, College of Agriculture and Veterinary Sciences, University of Nairobi, Nairobi, Kenya
| | - Yi Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Raphael Mrode
- International Livestock Research Institute, Nairobi, Kenya.,Scotland's Rural College, Edinburgh, United Kingdom
| | - Fidalis D N Mujibi
- USOMI Limited, Nairobi, Kenya.,Nelson Mandela African Institute of Science and Technology, Arusha, Tanzania
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29
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Norris ET, Wang L, Conley AB, Rishishwar L, Mariño-Ramírez L, Valderrama-Aguirre A, Jordan IK. Genetic ancestry, admixture and health determinants in Latin America. BMC Genomics 2018; 19:861. [PMID: 30537949 PMCID: PMC6288849 DOI: 10.1186/s12864-018-5195-7] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Modern Latin American populations were formed via genetic admixture among ancestral source populations from Africa, the Americas and Europe. We are interested in studying how combinations of genetic ancestry in admixed Latin American populations may impact genomic determinants of health and disease. For this study, we characterized the impact of ancestry and admixture on genetic variants that underlie health- and disease-related phenotypes in population genomic samples from Colombia, Mexico, Peru, and Puerto Rico. RESULTS We analyzed a total of 347 admixed Latin American genomes along with 1102 putative ancestral source genomes from Africans, Europeans, and Native Americans. We characterized the genetic ancestry, relatedness, and admixture patterns for each of the admixed Latin American genomes, finding a spectrum of ancestry proportions within and between populations. We then identified single nucleotide polymorphisms (SNPs) with anomalous ancestry-enrichment patterns, i.e. SNPs that exist in any given Latin American population at a higher frequency than expected based on the population's genetic ancestry profile. For this set of ancestry-enriched SNPs, we inspected their phenotypic impact on disease, metabolism, and the immune system. All four of the Latin American populations show ancestry-enrichment for a number of shared pathways, yielding evidence of similar selection pressures on these populations during their evolution. For example, all four populations show ancestry-enriched SNPs in multiple genes from immune system pathways, such as the cytokine receptor interaction, T cell receptor signaling, and antigen presentation pathways. We also found SNPs with excess African or European ancestry that are associated with ancestry-specific gene expression patterns and play crucial roles in the immune system and infectious disease responses. Genes from both the innate and adaptive immune system were found to be regulated by ancestry-enriched SNPs with population-specific regulatory effects. CONCLUSIONS Ancestry-enriched SNPs in Latin American populations have a substantial effect on health- and disease-related phenotypes. The concordant impact observed for same phenotypes across populations points to a process of adaptive introgression, whereby ancestry-enriched SNPs with specific functional utility appear to have been retained in modern populations by virtue of their effects on health and fitness.
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Affiliation(s)
- Emily T Norris
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.,PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia.,IHRC-Georgia Tech Applied Bioinformatics Laboratory (ABiL), Atlanta, GA, USA
| | - Lu Wang
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Andrew B Conley
- IHRC-Georgia Tech Applied Bioinformatics Laboratory (ABiL), Atlanta, GA, USA
| | - Lavanya Rishishwar
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.,PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia.,IHRC-Georgia Tech Applied Bioinformatics Laboratory (ABiL), Atlanta, GA, USA
| | - Leonardo Mariño-Ramírez
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia.,National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Augusto Valderrama-Aguirre
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia.,Biomedical Research Institute, Faculty of Health, Universidad Libre-Seccional Cali, Cali, Valle del Cauca, Colombia
| | - I King Jordan
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA. .,PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia. .,IHRC-Georgia Tech Applied Bioinformatics Laboratory (ABiL), Atlanta, GA, USA.
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30
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Chimusa ER, Defo J, Thami PK, Awany D, Mulisa DD, Allali I, Ghazal H, Moussa A, Mazandu GK. Dating admixture events is unsolved problem in multi-way admixed populations. Brief Bioinform 2018; 21:144-155. [PMID: 30462157 DOI: 10.1093/bib/bby112] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 10/12/2018] [Accepted: 10/15/2018] [Indexed: 12/12/2022] Open
Abstract
Advances in human sequencing technologies, coupled with statistical and computational tools, have fostered the development of methods for dating admixture events. These methods have merits and drawbacks in estimating admixture events in multi-way admixed populations. Here, we first provide a comprehensive review and comparison of current methods pertinent to dating admixture events. Second, we assess various admixture dating tools. We do so by performing various simulations. Third, we apply the top two assessed methods to real data of a uniquely admixed population from South Africa. Results reveal that current dating admixture models are not sufficiently equipped to estimate ancient admixtures events and to identify multi-faceted admixture events in complex multi-way admixed populations. We conclude with a discussion of research areas where further work on dating admixture-based methods is needed.
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Affiliation(s)
- Emile R Chimusa
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa
| | - Joel Defo
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa
| | - Prisca K Thami
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa.,Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.,Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Denis Awany
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa
| | - Delesa D Mulisa
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa
| | - Imane Allali
- Division of Computational Biology, Department of Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa
| | | | - Ahmed Moussa
- Abdelmalek Essaadi University ENSA, Tangier, Morocco
| | - Gaston K Mazandu
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa.,Division of Computational Biology, Department of Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine,Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa.,African Institute for Mathematical Sciences (AIMS),Muizenberg, Cape Town, South Africa
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31
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Goodswen SJ, Kennedy PJ, Ellis JT. A Gene-Based Positive Selection Detection Approach to Identify Vaccine Candidates Using Toxoplasma gondii as a Test Case Protozoan Pathogen. Front Genet 2018; 9:332. [PMID: 30177953 PMCID: PMC6109633 DOI: 10.3389/fgene.2018.00332] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 08/02/2018] [Indexed: 11/22/2022] Open
Abstract
Over the last two decades, various in silico approaches have been developed and refined that attempt to identify protein and/or peptide vaccines candidates from informative signals encoded in protein sequences of a target pathogen. As to date, no signal has been identified that clearly indicates a protein will effectively contribute to a protective immune response in a host. The premise for this study is that proteins under positive selection from the immune system are more likely suitable vaccine candidates than proteins exposed to other selection pressures. Furthermore, our expectation is that protein sequence regions encoding major histocompatibility complexes (MHC) binding peptides will contain consecutive positive selection sites. Using freely available data and bioinformatic tools, we present a high-throughput approach through a pipeline that predicts positive selection sites, protein subcellular locations, and sequence locations of medium to high T-Cell MHC class I binding peptides. Positive selection sites are estimated from a sequence alignment by comparing rates of synonymous (dS) and non-synonymous (dN) substitutions among protein coding sequences of orthologous genes in a phylogeny. The main pipeline output is a list of protein vaccine candidates predicted to be naturally exposed to the immune system and containing sites under positive selection. Candidates are ranked with respect to the number of consecutive sites located on protein sequence regions encoding MHCI-binding peptides. Results are constrained by the reliability of prediction programs and quality of input data. Protein sequences from Toxoplasma gondii ME49 strain (TGME49) were used as a case study. Surface antigen (SAG), dense granules (GRA), microneme (MIC), and rhoptry (ROP) proteins are considered worthy T. gondii candidates. Given 8263 TGME49 protein sequences processed anonymously, the top 10 predicted candidates were all worthy candidates. In particular, the top ten included ROP5 and ROP18, which are T. gondii virulence determinants. The chance of randomly selecting a ROP protein was 0.2% given 8263 sequences. We conclude that the approach described is a valuable addition to other in silico approaches to identify vaccines candidates worthy of laboratory validation and could be adapted for other apicomplexan parasite species (with appropriate data).
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Affiliation(s)
- Stephen J Goodswen
- School of Life Sciences, University of Technology Sydney, Ultimo, NSW, Australia
| | - Paul J Kennedy
- School of Software, Faculty of Engineering and Information Technology, Centre for Artificial Intelligence, University of Technology Sydney, Ultimo, NSW, Australia
| | - John T Ellis
- School of Life Sciences, University of Technology Sydney, Ultimo, NSW, Australia
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32
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Bahbahani H, Afana A, Wragg D. Genomic signatures of adaptive introgression and environmental adaptation in the Sheko cattle of southwest Ethiopia. PLoS One 2018; 13:e0202479. [PMID: 30114214 PMCID: PMC6095569 DOI: 10.1371/journal.pone.0202479] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2018] [Accepted: 08/04/2018] [Indexed: 11/23/2022] Open
Abstract
Although classified as an African taurine breed, the genomes of Sheko cattle are an admixture of Asian zebu and African taurine ancestries. They populate the humid Bench Maji zone in Sheko and Bench districts in the south-western part of Ethiopia and are considered as a trypanotolerant breed with high potential for dairy production. Here, we investigate the genome of Sheko cattle for candidate signatures of adaptive introgression and positive selection using medium density genome-wide SNP data. Following locus-ancestry deviation analysis, 15 and 72 genome regions show substantial excess and deficiency in Asian zebu ancestry, respectively. Nine and 23 regions show candidate signatures of positive selection following extended haplotype homozygosity (EHH)-based analyses (iHS and Rsb), respectively. The results support natural selection before admixture for one iHS, one Rsb and three zebu ancestry-deficient regions. Genes and/or QTL associated with bovine immunity, fertility, heat tolerance, trypanotolerance and lactation are present within candidate selected regions. The identification of candidate regions under selection in Sheko cattle warrants further investigation of a larger sample size using full genome sequence data to better characterise the underlying haplotypes. The results can then support informative genomic breeding programmes to sustainably enhance livestock productivity in East African trypanosomosis infested areas.
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Affiliation(s)
- Hussain Bahbahani
- Department of Biological Sciences, Faculty of Science, Kuwait University, Kuwait City, Kuwait
- * E-mail: ,
| | - Arwa Afana
- Department of Biological Sciences, Faculty of Science, Kuwait University, Kuwait City, Kuwait
| | - David Wragg
- Centre for Tropical Livestock Genetics and Health, The Roslin Institute, Edinburgh, United Kingdom
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33
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Lachance J, Berens AJ, Hansen MEB, Teng AK, Tishkoff SA, Rebbeck TR. Genetic Hitchhiking and Population Bottlenecks Contribute to Prostate Cancer Disparities in Men of African Descent. Cancer Res 2018; 78:2432-2443. [PMID: 29438991 PMCID: PMC5932264 DOI: 10.1158/0008-5472.can-17-1550] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Revised: 11/02/2017] [Accepted: 02/05/2018] [Indexed: 12/24/2022]
Abstract
Prostate cancer incidence and mortality rates in African and African American men are greatly elevated compared with other ethnicities. This disparity is likely explained by a combination of social, environmental, and genetic factors. A large number of susceptibility loci have been reported by genome-wide association studies (GWAS), but the contribution of these loci to prostate cancer disparities is unclear. Here, we investigated the population structure of 68 previously reported GWAS loci and calculated genetic disparity contribution statistics to identify SNPs that contribute the most to differences in prostate cancer risk across populations. By integrating GWAS results with allele frequency data, we generated genetic risk scores for 45 African and 19 non-African populations. Tests of natural selection were used to assess why some SNPs have large allele frequency differences across populations. We report that genetic predictions of prostate cancer risks are highest for West African men and lowest for East Asian men. These differences may be explained by the out-of-Africa bottleneck and natural selection. A small number of loci appear to drive elevated prostate cancer risks in men of African descent, including rs9623117, rs6983267, rs10896449, rs10993994, and rs817826. Although most prostate cancer-associated loci are evolving neutrally, there are multiple instances where alleles have hitchhiked to high frequencies with linked adaptive alleles. For example, a protective allele at 2q37 appears to have risen to high frequency in Europe due to selection acting on pigmentation. Our results suggest that evolutionary history contributes to the high rates of prostate cancer in African and African American men.Significance: A small number of genetic variants cause an elevated risk of prostate cancer in men of West African descent. Cancer Res; 78(9); 2432-43. ©2018 AACR.
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Affiliation(s)
- Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia.
| | - Ali J Berens
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
| | - Matthew E B Hansen
- Department of Biology and Genetics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Andrew K Teng
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
| | - Sarah A Tishkoff
- Department of Biology and Genetics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Timothy R Rebbeck
- Dana-Farber Cancer Institute and Harvard T. H. Chan School of Public Health, Boston, Massachusetts
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34
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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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35
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Gross JM. Tests of fit of historically-informed models of African American Admixture. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2018; 165:211-222. [PMID: 29131310 DOI: 10.1002/ajpa.23343] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Revised: 08/20/2017] [Accepted: 10/07/2017] [Indexed: 07/13/2024]
Abstract
OBJECTIVES African American populations in the U.S. formed primarily by mating between Africans and Europeans over the last 500 years. To date, studies of admixture have focused on either a one-time admixture event or continuous input into the African American population from Europeans only. Our goal is to gain a better understanding of the admixture process by examining models that take into account (a) assortative mating by ancestry in the African American population, (b) continuous input from both Europeans and Africans, and (c) historically informed variation in the rate of African migration over time. MATERIALS AND METHODS We used a model-based clustering method to generate distributions of African ancestry in three samples comprised of 147 African Americans from two published sources. We used a log-likelihood method to examine the fit of four models to these distributions and used a log-likelihood ratio test to compare the relative fit of each model. RESULTS The mean ancestry estimates for our datasets of 77% African/23% European to 83% African/17% European ancestry are consistent with previous studies. We find admixture models that incorporate continuous gene flow from Europeans fit significantly better than one-time event models, and that a model involving continuous gene flow from Africans and Europeans fits better than one with continuous gene flow from Europeans only for two samples. Importantly, models that involve continuous input from Africans necessitate a higher level of gene flow from Europeans than previously reported. DISCUSSION We demonstrate that models that take into account information about the rate of African migration over the past 500 years fit observed patterns of African ancestry better than alternative models. Our approach will enrich our understanding of the admixture process in extant and past populations.
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Affiliation(s)
- Jessica M Gross
- Department of Anthropology MSC01-1040, Anthropology 1, University of New Mexico, Albuquerque, New Mexico
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36
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Patin E, Lopez M, Grollemund R, Verdu P, Harmant C, Quach H, Laval G, Perry GH, Barreiro LB, Froment A, Heyer E, Massougbodji A, Fortes-Lima C, Migot-Nabias F, Bellis G, Dugoujon JM, Pereira JB, Fernandes V, Pereira L, Van der Veen L, Mouguiama-Daouda P, Bustamante CD, Hombert JM, Quintana-Murci L. Dispersals and genetic adaptation of Bantu-speaking populations in Africa and North America. Science 2018; 356:543-546. [PMID: 28473590 DOI: 10.1126/science.aal1988] [Citation(s) in RCA: 131] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 04/11/2017] [Indexed: 12/12/2022]
Abstract
Bantu languages are spoken by about 310 million Africans, yet the genetic history of Bantu-speaking populations remains largely unexplored. We generated genomic data for 1318 individuals from 35 populations in western central Africa, where Bantu languages originated. We found that early Bantu speakers first moved southward, through the equatorial rainforest, before spreading toward eastern and southern Africa. We also found that genetic adaptation of Bantu speakers was facilitated by admixture with local populations, particularly for the HLA and LCT loci. Finally, we identified a major contribution of western central African Bantu speakers to the ancestry of African Americans, whose genomes present no strong signals of natural selection. Together, these results highlight the contribution of Bantu-speaking peoples to the complex genetic history of Africans and African Americans.
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Affiliation(s)
- Etienne Patin
- Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France. .,Centre National de la Recherche Scientifique URA3012, 75015 Paris, France.,Center of Bioinformatics, Biostatistics, and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Marie Lopez
- Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France.,Centre National de la Recherche Scientifique URA3012, 75015 Paris, France.,Center of Bioinformatics, Biostatistics, and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Rebecca Grollemund
- Evolutionary Biology Group, School of Biological Sciences, University of Reading, Reading RG6 6BX, England.,Departments of English and Anthropology, University of Missouri, Columbia, Missouri, MO 65211, USA
| | - Paul Verdu
- Centre National de la Recherche Scientifique UMR7206, Muséum National d'Histoire Naturelle, Université Paris Diderot, Sorbonne Paris Cité, 75016 Paris, France
| | - Christine Harmant
- Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France.,Centre National de la Recherche Scientifique URA3012, 75015 Paris, France.,Center of Bioinformatics, Biostatistics, and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Hélène Quach
- Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France.,Centre National de la Recherche Scientifique URA3012, 75015 Paris, France.,Center of Bioinformatics, Biostatistics, and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Guillaume Laval
- Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France.,Centre National de la Recherche Scientifique URA3012, 75015 Paris, France.,Center of Bioinformatics, Biostatistics, and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - George H Perry
- Departments of Anthropology and Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Luis B Barreiro
- Université de Montréal, Centre de Recherche CHU Sainte-Justine, Montréal, Québec H3T 1C5, Canada
| | - Alain Froment
- Institut de Recherche pour le Développement, UMR 208, Muséum National d'Histoire Naturelle, 75005 Paris, France
| | - Evelyne Heyer
- Centre National de la Recherche Scientifique UMR7206, Muséum National d'Histoire Naturelle, Université Paris Diderot, Sorbonne Paris Cité, 75016 Paris, France
| | - Achille Massougbodji
- Centre d'Etude et de Recherche sur le Paludisme Associé à la Grossesse et l'Enfance (CERPAGE), Cotonou, Bénin.,Institut de Recherche Clinique du Bénin (IRCB), 01 BP 188 Cotonou, Bénin
| | - Cesar Fortes-Lima
- Centre National de la Recherche Scientifique UMR7206, Muséum National d'Histoire Naturelle, Université Paris Diderot, Sorbonne Paris Cité, 75016 Paris, France.,Anthropologie Moléculaire et Imagerie de Synthèse, Centre National de la Recherche Scientifique UMR 5288/Université Paul Sabatier Toulouse 3, 31073 Toulouse Cedex 3, France
| | - Florence Migot-Nabias
- Institut de Recherche pour le Développement, UMR 216, 75006 Paris, France.,Communautés d'Universités et Etablissements (COMUE) Sorbonne Paris Cité, Faculté de Pharmacie, Université Paris Descartes, 75006 Paris, France
| | - Gil Bellis
- Institut National d'Etudes Démographiques, 75020 Paris, France
| | - Jean-Michel Dugoujon
- Anthropologie Moléculaire et Imagerie de Synthèse, Centre National de la Recherche Scientifique UMR 5288/Université Paul Sabatier Toulouse 3, 31073 Toulouse Cedex 3, France
| | - Joana B Pereira
- Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto, Porto 4200-135, Portugal.,Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto 4200-465, Portugal
| | - Verónica Fernandes
- Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto, Porto 4200-135, Portugal.,Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto 4200-465, Portugal
| | - Luisa Pereira
- Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto, Porto 4200-135, Portugal.,Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto 4200-465, Portugal.,Faculdade de Medicina da Universidade do Porto, Porto 4200-319, Portugal
| | - Lolke Van der Veen
- Centre National de la Recherche Scientifique UMR 5596, Dynamique du Langage, Université Lumière-Lyon 2, 69007 Lyon, France
| | - Patrick Mouguiama-Daouda
- Centre National de la Recherche Scientifique UMR 5596, Dynamique du Langage, Université Lumière-Lyon 2, 69007 Lyon, France.,Laboratoire Langue, Culture et Cognition (LCC), Université Omar Bongo, 13131 Libreville, Gabon
| | - Carlos D Bustamante
- Department of Genetics, Stanford University, Stanford, CA 94305, USA.,Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Jean-Marie Hombert
- Centre National de la Recherche Scientifique UMR 5596, Dynamique du Langage, Université Lumière-Lyon 2, 69007 Lyon, France
| | - Lluís Quintana-Murci
- Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France. .,Centre National de la Recherche Scientifique URA3012, 75015 Paris, France.,Center of Bioinformatics, Biostatistics, and Integrative Biology, Institut Pasteur, 75015 Paris, France
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37
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Smith CJ, Minas TZ, Ambs S. Analysis of Tumor Biology to Advance Cancer Health Disparity Research. THE AMERICAN JOURNAL OF PATHOLOGY 2017; 188:304-316. [PMID: 29137948 DOI: 10.1016/j.ajpath.2017.06.019] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 06/24/2017] [Accepted: 06/29/2017] [Indexed: 12/20/2022]
Abstract
Cancer mortality rates in the United States continue to decline. Reductions in tobacco use, uptake of preventive measures, adoption of early detection methods, and better treatments have resulted in improved cancer outcomes for men and women. Despite this progress, some population groups continue to experience an excessive cancer burden when compared with other population groups. One of the most prominent cancer health disparities exists in prostate cancer. Prostate cancer mortality rates are highest among men of African ancestry when compared with other men, both in the United States and globally. This disparity and other cancer health disparities are largely explained by differences in access to health care, diet, lifestyle, cultural barriers, and disparate exposures to carcinogens and pathogens. Dietary and lifestyle factors, pathogens, and ancestry-related factors can modify tumor biology and induce a more aggressive disease. There are numerous examples of how environmental exposures, like tobacco, chronic stress, or dietary factors, induce an adverse tumor biology, leading to a more aggressive disease and decreased patient survival. Because of population differences in the exposure to these risk factors, they can be the cause of cancer disparities. In this review, we will summarize recent advances in our understanding of prostate and breast cancer disparities in the United States and discuss how the analysis of tumor biology can advance health disparity research.
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Affiliation(s)
- Cheryl J Smith
- Laboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Tsion Z Minas
- Laboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
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38
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Wang H, Choi Y, Tayo B, Wang X, Morris N, Zhang X, Broeckel U, Hanis C, Kardia S, Redline S, Cooper RS, Tang H, Zhu X. Genome-wide survey in African Americans demonstrates potential epistasis of fitness in the human genome. Genet Epidemiol 2017; 41:122-135. [PMID: 27917522 PMCID: PMC5226866 DOI: 10.1002/gepi.22026] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 09/30/2016] [Accepted: 10/03/2016] [Indexed: 11/07/2022]
Abstract
The role played by epistasis between alleles at unlinked loci in shaping population fitness has been debated for many years and the existing evidence has been mainly accumulated from model organisms. In model organisms, fitness epistasis can be systematically inferred by detecting nonindependence of genotypic values between loci in a population and confirmed through examining the number of offspring produced in two-locus genotype groups. No systematic study has been conducted to detect epistasis of fitness in humans owing to experimental constraints. In this study, we developed a novel method to detect fitness epistasis by testing the correlation between local ancestries on different chromosomes in an admixed population. We inferred local ancestry across the genome in 16,252 unrelated African Americans and systematically examined the pairwise correlations between the genomic regions on different chromosomes. Our analysis revealed a pair of genomic regions on chromosomes 4 and 6 that show significant local ancestry correlation (P-value = 4.01 × 10-8 ) that can be potentially attributed to fitness epistasis. However, we also observed substantial local ancestry correlation that cannot be explained by systemic ancestry inference bias. To our knowledge, this study is the first to systematically examine evidence of fitness epistasis across the human genome.
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Affiliation(s)
- Heming Wang
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Yoonha Choi
- Department of Genetics, Stanford University, Stanford, California, United States of America
| | - Bamidele Tayo
- Department of Public Health Science, Loyola University Medical Center, Maywood, Illinois, United States of America
| | - Xuefeng Wang
- Departments of Preventive Medicine, Biomedical Informatics, and Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, United States of America
| | - Nathan Morris
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Xiang Zhang
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Uli Broeckel
- Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America
| | - Craig Hanis
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Sharon Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Susan Redline
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Richard S Cooper
- Department of Public Health Science, Loyola University Medical Center, Maywood, Illinois, United States of America
| | - Hua Tang
- Department of Genetics, Stanford University, Stanford, California, United States of America
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
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Joukhadar R, Daetwyler HD, Bansal UK, Gendall AR, Hayden MJ. Genetic Diversity, Population Structure and Ancestral Origin of Australian Wheat. FRONTIERS IN PLANT SCIENCE 2017; 8:2115. [PMID: 29312381 PMCID: PMC5733070 DOI: 10.3389/fpls.2017.02115] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2017] [Accepted: 11/28/2017] [Indexed: 05/22/2023]
Abstract
Since the introduction of wheat into Australia by the First Fleet settlers, germplasm from different geographical origins has been used to adapt wheat to the Australian climate through selection and breeding. In this paper, we used 482 cultivars, representing the breeding history of bread wheat in Australia since 1840, to characterize their diversity and population structure and to define the geographical ancestral background of Australian wheat germplasm. This was achieved by comparing them to a global wheat collection using in-silico chromosome painting based on SNP genotyping. The global collection involved 2,335 wheat accessions which was divided into 23 different geographical subpopulations. However, the whole set was reduced to 1,544 accessions to increase the differentiation and decrease the admixture among different global subpopulations to increase the power of the painting analysis. Our analysis revealed that the structure of Australian wheat germplasm and its geographic ancestors have changed significantly through time, especially after the Green Revolution. Before 1920, breeders used cultivars from around the world, but mainly Europe and Africa, to select potential cultivars that could tolerate Australian growing conditions. Between 1921 and 1970, a dependence on African wheat germplasm became more prevalent. Since 1970, a heavy reliance on International Maize and Wheat Improvement Center (CIMMYT) germplasm has persisted. Combining the results from linkage disequilibrium, population structure and in-silico painting revealed that the dependence on CIMMYT materials has varied among different Australian States, has shrunken the germplasm effective population size and produced larger linkage disequilibrium blocks. This study documents the evolutionary history of wheat breeding in Australia and provides an understanding for how the wheat genome has been adapted to local growing conditions. This information provides a guide for industry to assist with maintaining genetic diversity for long-term selection gains and to plan future breeding programs.
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Affiliation(s)
- Reem Joukhadar
- Department of Animal, Plant and Soil Sciences, La Trobe University, Bundoora, VIC, Australia
- Agriculture Victoria Research, AgriBio, Centre for Agribioscience, Bundoora, VIC, Australia
- *Correspondence: Reem Joukhadar
| | - Hans D. Daetwyler
- Agriculture Victoria Research, AgriBio, Centre for Agribioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
| | - Urmil K. Bansal
- School of Life and Environmental Sciences, The University of Sydney Plant Breeding Institute, Cobbitty, NSW, Australia
| | - Anthony R. Gendall
- Department of Animal, Plant and Soil Sciences, La Trobe University, Bundoora, VIC, Australia
| | - Matthew J. Hayden
- Agriculture Victoria Research, AgriBio, Centre for Agribioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
- Matthew J. Hayden
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Abstract
The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.
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Affiliation(s)
- Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Department of Genomes & Genetics, Institut Pasteur, Paris, 75015, France.
- Centre National de la Recherche Scientifique, URA3012, Paris, 75015, France.
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, 75015, France.
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41
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Vatsiou AI, Bazin E, Gaggiotti OE. Changes in selective pressures associated with human population expansion may explain metabolic and immune related pathways enriched for signatures of positive selection. BMC Genomics 2016; 17:504. [PMID: 27444955 PMCID: PMC4955149 DOI: 10.1186/s12864-016-2783-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Accepted: 05/26/2016] [Indexed: 12/14/2022] Open
Abstract
Background The study of local adaptation processes is a very important research topic in the field of population genomics. There is a particular interest in the study of human populations because they underwent a process of rapid spatial expansion and faced important environmental changes that translated into changes in selective pressures. New mutations may have been selected for in the new environment and previously existing genetic variants may have become detrimental. Immune related genes may have been released from the selective pressure exerted by pathogens in the ancestral environment and new variants may have been positively selected due to pathogens present in the newly colonized habitat. Also, variants that had a selective advantage in past environments may have become deleterious in the modern world due to external stimuli including climatic, dietary and behavioral changes, which could explain the high prevalence of some polygenic diseases such as diabetes and obesity. Results We performed an enrichment analysis to identify gene sets enriched for signals of positive selection in humans. We used two genome scan methods, XPCLR and iHS to detect selection using a dense coverage of SNP markers combined with two gene set enrichment approaches. We identified immune related gene sets that could be involved in the protection against pathogens especially in the African population. We also identified the glycolysis & gluconeogenesis gene set, related to metabolism, which supports the thrifty genotype hypothesis invoked to explain the current high prevalence of diseases such as diabetes and obesity. Extending our analysis to the gene level, we found signals for 23 candidate genes linked to metabolic syndrome, 13 of which are new candidates for positive selection. Conclusions Our study provides a list of genes and gene sets associated with immunity and metabolic syndrome that are enriched for signals of positive selection in three human populations (Europeans, Africans and Asians). Our results highlight differences in the relative importance of pathogens as drivers of local adaptation in different continents and provide new insights into the evolution and high incidence of metabolic syndrome in modern human populations. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2783-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Alexandra I Vatsiou
- Laboratoire d'Écologie Alpine (LECA), Univesrity Joseph Fourier, 2233 Rue de la Piscine, 38041, Grenoble, Cedex 9, France. .,Scottish Oceans Institute, East Sands, University of St Andrews, St Andrews, KY16 8LB, Scotland, UK. .,Oh no sequences! Research group, Era7Bioinformatics, Plaza de Campo Verde, 3, 18001, Granada, Spain.
| | - Eric Bazin
- Laboratoire d'Écologie Alpine (LECA), Univesrity Joseph Fourier, 2233 Rue de la Piscine, 38041, Grenoble, Cedex 9, France
| | - Oscar E Gaggiotti
- Laboratoire d'Écologie Alpine (LECA), Univesrity Joseph Fourier, 2233 Rue de la Piscine, 38041, Grenoble, Cedex 9, France.,Scottish Oceans Institute, East Sands, University of St Andrews, St Andrews, KY16 8LB, Scotland, UK
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42
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Khayatzadeh N, Mészáros G, Utsunomiya YT, Garcia JF, Schnyder U, Gredler B, Curik I, Sölkner J. Locus-specific ancestry to detect recent response to selection in admixed Swiss Fleckvieh cattle. Anim Genet 2016; 47:637-646. [PMID: 27435758 DOI: 10.1111/age.12470] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/30/2016] [Indexed: 01/08/2023]
Abstract
Identification of selection signatures is one of the current endeavors of evolutionary genetics. Admixed populations may be used to infer post-admixture selection. We calculated local ancestry for Swiss Fleckvieh, a composite of Simmental (SI) and Red Holstein Friesian (RHF), to infer such signals. Illumina Bovine SNP50 BeadChip data for 300 admixed, 88 SI and 97 RHF bulls were used. The average RHF ancestry across the whole genome was 0.70. To identify regions with high deviation from average, we considered two significance thresholds, based on a permutation test and extreme deviation from normal distribution. Regions on chromosomes 13 (46.3-47.3 Mb) and 18 (18.7-25.9 Mb) passed both thresholds in the direction of increased SI. Extended haplotype homozygosity within (iHS) and between (Rsb) populations was calculated to explore additional patterns of pre- and post-admixture selection signals. The Rsb score of admixed and SI was significant in a wide region of chromosome 18 (6.6-24.6 Mb) overlapped with one area of strong local ancestry deviation. FTO, with pleiotropic effect on milk and fertility, NOD2 on dairy and NKD1 and SALL1 on fertility traits are located there. Genetic differentiation of RHF and SI (Fst ), an alternative indicator of pre-admixture selection in pure populations, was calculated. No considerable overlap of peaks of local ancestry deviations and Fst was observed. We found two regions with significant signatures of post-admixture selection in this very young composite, applying comparatively stringent significance thresholds. The signals cover relatively large genomic areas and did not allow pinpointing of the gene(s) responsible for the apparent shift in ancestry proportions.
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Affiliation(s)
- N Khayatzadeh
- Division of Livestock Science, Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences, Vienna, Gregor-Mendel-Straße 33, A-1180, Vienna, Austria
| | - G Mészáros
- Division of Livestock Science, Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences, Vienna, Gregor-Mendel-Straße 33, A-1180, Vienna, Austria.
| | - Y T Utsunomiya
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, Brazil
| | - J F Garcia
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, Brazil.,Departamento de Apoio, Saúde e Produção Animal, Faculdade de Medicina Veterinária de Araçatuba, UNESP - Univ Estadual Paulista, Araçatuba, São Paulo, Brazil
| | - U Schnyder
- Qualitas AG, Chamerstrasse 56, CH-6300, Zug, Switzerland
| | - B Gredler
- Qualitas AG, Chamerstrasse 56, CH-6300, Zug, Switzerland
| | - I Curik
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Svetošimunska cesta 25, 10000, Zagreb, Croatia
| | - J Sölkner
- Division of Livestock Science, Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences, Vienna, Gregor-Mendel-Straße 33, A-1180, Vienna, Austria
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Detecting Heterogeneity in Population Structure Across the Genome in Admixed Populations. Genetics 2016; 204:43-56. [PMID: 27440868 DOI: 10.1534/genetics.115.184184] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Accepted: 06/11/2016] [Indexed: 11/18/2022] Open
Abstract
The genetic structure of human populations is often characterized by aggregating measures of ancestry across the autosomal chromosomes. While it may be reasonable to assume that population structure patterns are similar genome-wide in relatively homogeneous populations, this assumption may not be appropriate for admixed populations, such as Hispanics and African-Americans, with recent ancestry from two or more continents. Recent studies have suggested that systematic ancestry differences can arise at genomic locations in admixed populations as a result of selection and nonrandom mating. Here, we propose a method, which we refer to as the chromosomal ancestry differences (CAnD) test, for detecting heterogeneity in population structure across the genome. CAnD can incorporate either local or chromosome-wide ancestry inferred from SNP genotype data to identify chromosomes harboring genomic regions with ancestry contributions that are significantly different than expected. In simulation studies with real genotype data from phase III of the HapMap Project, we demonstrate the validity and power of CAnD. We apply CAnD to the HapMap Mexican-American (MXL) and African-American (ASW) population samples; in this analysis the software RFMix is used to infer local ancestry at genomic regions, assuming admixing from Europeans, West Africans, and Native Americans. The CAnD test provides strong evidence of heterogeneity in population structure across the genome in the MXL sample ([Formula: see text]), which is largely driven by elevated Native American ancestry and deficit of European ancestry on the X chromosomes. Among the ASW, all chromosomes are largely African derived and no heterogeneity in population structure is detected in this sample.
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Jordan IK. The Columbian Exchange as a source of adaptive introgression in human populations. Biol Direct 2016; 11:17. [PMID: 27038633 PMCID: PMC4818900 DOI: 10.1186/s13062-016-0121-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Accepted: 03/29/2016] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The term "Columbian Exchange" refers to the massive transfer of life between the Afro-Eurasian and American hemispheres that was precipitated by Columbus' voyage to the New World. The Columbian Exchange is widely appreciated by historians, social scientists and economists as a major turning point that had profound and lasting effects on the trajectory of human history and development. PRESENTATION OF THE HYPOTHESIS I propose that the Columbian Exchange should also be appreciated by biologists for its role in the creation of novel human genomes that have been shaped by rapid adaptive evolution. Specifically, I hypothesize that the process of human genome evolution stimulated by the Columbian Exchange was based in part on selective sweeps of introgressed haplotypes from ancestral populations, many of which possessed pre-evolved adaptive utility based on regional-specific fitness and health effects. TESTING THE HYPOTHESIS Testing of this hypothesis will require comparative analysis of genome sequences from putative ancestral source populations, with genomes from modern admixed populations, in order to identify ancestry-specific introgressed haplotypes that exist at higher frequencies in admixed populations than can be expected by chance alone. Investigation of such ancestry-enriched genomic regions can be used to provide clues as to the functional roles of the genes therein and the selective forces that have acted to increase their frequency in the population. IMPLICATIONS OF THE HYPOTHESIS Critical interrogation of this hypothesis could serve to underscore the important role of introgression as a source of adaptive alleles and as a driver of evolutionary change, and it would highlight the role of admixture in facilitating rapid human evolution.
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Affiliation(s)
- I King Jordan
- School of Biology, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA, 30332, USA.
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia.
- BIOS Centro de Bioinformática y Biología Computacional, Manizales, Caldas, Colombia.
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45
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Ancestry variation and footprints of natural selection along the genome in Latin American populations. Sci Rep 2016; 6:21766. [PMID: 26887503 PMCID: PMC4757894 DOI: 10.1038/srep21766] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 01/25/2016] [Indexed: 02/08/2023] Open
Abstract
Latin American populations stem from the admixture of Europeans, Africans and Native Americans, which started over 400 years ago and had lasted for several centuries. Extreme deviation over the genome-wide average in ancestry estimations at certain genomic locations could reflect recent natural selection. We evaluated the distribution of ancestry estimations using 678 genome-wide microsatellite markers in 249 individuals from 13 admixed populations across Latin America. We found significant deviations in ancestry estimations including three locations with more than 3.5 times standard deviations from the genome-wide average: an excess of European ancestry at 1p36 and 14q32, and an excess of African ancestry at 6p22. Using simulations, we could show that at least the deviation at 6p22 was unlikely to result from genetic drift alone. By applying different linguistic groups as well as the most likely ancestral Native American populations as the ancestry, we showed that the choice of Native American ancestry could affect the local ancestry estimation. However, the signal at 6p22 consistently appeared in most of the analyses using various ancestral groups. This study provided important insights for recent natural selection in the context of the unique history of the New World and implications for disease mapping.
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46
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Rishishwar L, Conley AB, Wigington CH, Wang L, Valderrama-Aguirre A, Jordan IK. Ancestry, admixture and fitness in Colombian genomes. Sci Rep 2015. [PMID: 26197429 PMCID: PMC4508918 DOI: 10.1038/srep12376] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The human dimension of the Columbian Exchange entailed substantial genetic admixture between ancestral source populations from Africa, the Americas and Europe, which had evolved separately for many thousands of years. We sought to address the implications of the creation of admixed American genomes, containing novel allelic combinations, for human health and fitness via analysis of an admixed Colombian population from Medellin. Colombian genomes from Medellin show a wide range of three-way admixture contributions from ancestral source populations. The primary ancestry component for the population is European (average = 74.6%, range = 45.0%–96.7%), followed by Native American (average = 18.1%, range = 2.1%–33.3%) and African (average = 7.3%, range = 0.2%–38.6%). Locus-specific patterns of ancestry were evaluated to search for genomic regions that are enriched across the population for particular ancestry contributions. Adaptive and innate immune system related genes and pathways are particularly over-represented among ancestry-enriched segments, including genes (HLA-B and MAPK10) that are involved in defense against endemic pathogens such as malaria. Genes that encode functions related to skin pigmentation (SCL4A5) and cutaneous glands (EDAR) are also found in regions with anomalous ancestry patterns. These results suggest the possibility that ancestry-specific loci were differentially retained in the modern admixed Colombian population based on their utility in the New World environment.
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Affiliation(s)
- Lavanya Rishishwar
- 1] School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA [2] PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia [3] BIOS Centro de Bioinformática y Biología Computacional, Manizales, Caldas, Colombia
| | - Andrew B Conley
- School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | | | - Lu Wang
- School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Augusto Valderrama-Aguirre
- 1] PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia [2] Biomedical Research Institute, Universidad Libre, Cali, Valle del Cauca, Colombia [3] Regenerar - Center of Excellence for Regenerative and Personalized Medicine, Cali, Valle del Cauca, Colombia
| | - I King Jordan
- 1] School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA [2] PanAmerican Bioinformatics Institute, Cali, Valle del Cauca, Colombia [3] BIOS Centro de Bioinformática y Biología Computacional, Manizales, Caldas, Colombia
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47
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Hodgson JA, Pickrell JK, Pearson LN, Quillen EE, Prista A, Rocha J, Soodyall H, Shriver MD, Perry GH. Natural selection for the Duffy-null allele in the recently admixed people of Madagascar. Proc Biol Sci 2015; 281:20140930. [PMID: 24990677 DOI: 10.1098/rspb.2014.0930] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
While gene flow between distantly related populations is increasingly recognized as a potentially important source of adaptive genetic variation for humans, fully characterized examples are rare. In addition, the role that natural selection for resistance to vivax malaria may have played in the extreme distribution of the protective Duffy-null allele, which is nearly completely fixed in mainland sub-Saharan Africa and absent elsewhere, is controversial. We address both these issues by investigating the evolution of the Duffy-null allele in the Malagasy, a recently admixed population with major ancestry components from both East Asia and mainland sub-Saharan Africa. We used genome-wide genetic data and extensive computer simulations to show that the high frequency of the Duffy-null allele in Madagascar can only be explained in the absence of positive natural selection under extreme demographic scenarios involving high genetic drift. However, the observed genomic single nucleotide polymorphism diversity in the Malagasy is incompatible with such extreme demographic scenarios, indicating that positive selection for the Duffy-null allele best explains the high frequency of the allele in Madagascar. We estimate the selection coefficient to be 0.066. Because vivax malaria is endemic to Madagascar, this result supports the hypothesis that malaria resistance drove fixation of the Duffy-null allele in mainland sub-Saharan Africa.
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Affiliation(s)
- Jason A Hodgson
- Department of Anthropology, The Pennsylvania State University, University Park, PA 16802, USA Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, Berkshire SL5 7PY, UK
| | - Joseph K Pickrell
- New York Genome Center, New York, NY 10013, USA Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | - Laurel N Pearson
- Department of Anthropology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Ellen E Quillen
- Department of Anthropology, The Pennsylvania State University, University Park, PA 16802, USA Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78245, USA
| | - António Prista
- Faculdade de Educação Física e Desporto, Universidade Pedagógica, Maputo, Moçambique
| | - Jorge Rocha
- Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto (CIBIO), Vairão, Portugal Departamento de Biologia, Faculdade de Ciências da Universidade do Porto, Porto, Portugal
| | - Himla Soodyall
- Human Genomic Diversity and Disease Research Unit, Division of Human Genetics, School of Pathology, Faculty of Health Sciences, University of Witwatersrand and the National Health Laboratory Service, Johannesburg 2000, South Africa
| | - Mark D Shriver
- Department of Anthropology, The Pennsylvania State University, University Park, PA 16802, USA
| | - George H Perry
- Department of Anthropology, The Pennsylvania State University, University Park, PA 16802, USA Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
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48
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Chimusa ER, Meintjies A, Tchanga M, Mulder N, Seoighe C, Soodyall H, Ramesar R. A genomic portrait of haplotype diversity and signatures of selection in indigenous southern African populations. PLoS Genet 2015; 11:e1005052. [PMID: 25811879 PMCID: PMC4374865 DOI: 10.1371/journal.pgen.1005052] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Accepted: 02/02/2015] [Indexed: 11/21/2022] Open
Abstract
We report a study of genome-wide, dense SNP (∼900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region. Genome-wide analysis of human populations is useful in shedding light on the evolutionary history of the human genome, with a wide range of applications from reconstructing past associations between different population histories to disease mapping. In this manuscript we report on the application of genome-wide data to southern African populations and the identification of genome-wide signatures of selection pre- and post-admixture. Several signals of selection, before and after admixture, were identified, some of which involved loci associated with human diseases, including malaria, influenza, tuberculosis and HIV/AIDS. These results may reflect adaptations of southern African populations to infectious diseases. Consistent with previous studies, this study highlights the significance of the San in the genetics of human populations, as they are distinct from the other populations in many respects i.e. haplotype structure, locations of recombination hotspots, copy number and population structure. Furthermore, our study demonstrates the admixture of the San, Bantu-speaking populations and populations of Eurasian ancestry in some of the southern and eastern African populations. It illustrates the value in correcting for this stratification in future genome-wide association studies, and suggests that a future admixture mapping in these populations would likely be warranted and successful.
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Affiliation(s)
- Emile R. Chimusa
- Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | - Ayton Meintjies
- Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Milaine Tchanga
- Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Nicola Mulder
- Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Cathal Seoighe
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, Galway, Ireland
| | - Himla Soodyall
- Division of Human Genetics, School of Pathology, Faculty of Health Sciences, University of Witwatersrand and the National Health Laboratory Service, Johannesburg, South Africa
| | - Rajkumar Ramesar
- MRC Human Genetics Research Unit, Division of Human Genetics, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
- * E-mail:
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49
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Human knockout research: new horizons and opportunities. Trends Genet 2014; 31:108-15. [PMID: 25497971 DOI: 10.1016/j.tig.2014.11.003] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Revised: 11/15/2014] [Accepted: 11/17/2014] [Indexed: 12/12/2022]
Abstract
Although numerous approaches have been pursued to understand the function of human genes, Mendelian genetics has by far provided the most compelling and medically actionable dataset. Biallelic loss-of-function (LOF) mutations are observed in the majority of autosomal recessive Mendelian disorders, representing natural human knockouts and offering a unique opportunity to study the physiological and developmental context of these genes. The restriction of such context to 'disease' states is artificial, however, and the recent ability to survey entire human genomes for biallelic LOF mutations has revealed a surprising landscape of knockout events in 'healthy' individuals, sparking interest in their role in phenotypic diversity beyond disease causation. As I discuss in this review, the potentially wide implications of human knockout research warrant increased investment and multidisciplinary collaborations to overcome existing challenges and reap its benefits.
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50
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Narang A, Jha P, Kumar D, Kutum R, Mondal AK, Dash D, Mukerji M. Extensive copy number variations in admixed Indian population of African ancestry: potential involvement in adaptation. Genome Biol Evol 2014; 6:3171-81. [PMID: 25398783 PMCID: PMC4986450 DOI: 10.1093/gbe/evu250] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Admixture mapping has been enormously resourceful in identifying genetic variations linked to phenotypes, adaptation, and diseases. In this study through analysis of copy number variable regions (CNVRs), we report extensive restructuring in the genomes of the recently admixed African-Indian population (OG-W-IP) that inhabits a highly saline environment in Western India. The study included subjects from OG-W-IP (OG), five different Indian and three HapMap populations that were genotyped using Affymetrix version 6.0 arrays. Copy number variations (CNVs) detected using Birdsuite were used to define CNVRs. Population structure with respect to CNVRs was delineated using random forest approach. OG genomes have a surprising excess of CNVs in comparison to other studied populations. Individual ancestry proportions computed using STRUCTURE also reveals a unique genetic component in OGs. Population structure analysis with CNV genotypes indicates OG to be distant from both the African and Indian ancestral populations. Interestingly, it shows genetic proximity with respect to CNVs to only one Indian population IE-W-LP4, which also happens to reside in the same geographical region. We also observe a significant enrichment of molecular processes related to ion binding and receptor activity in genes encompassing OG-specific CNVRs. Our results suggest that retention of CNVRs from ancestral natives and de novo acquisition of CNVRs could accelerate the process of adaptation especially in an extreme environment. Additionally, this population would be enormously useful for dissecting genes and delineating the involvement of CNVs in salt adaptation.
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Affiliation(s)
- Ankita Narang
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Pankaj Jha
- Genomics and Molecular Medicine, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Dhirendra Kumar
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Rintu Kutum
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Anupam Kumar Mondal
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | | | - Debasis Dash
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Mitali Mukerji
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India Genomics and Molecular Medicine, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
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