1
|
Tiwari M, Gujar G, Shashank CG, Ponsuksili S. Selection signatures for high altitude adaptation in livestock: A review. Gene 2024; 927:148757. [PMID: 38986751 DOI: 10.1016/j.gene.2024.148757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 07/01/2024] [Accepted: 07/05/2024] [Indexed: 07/12/2024]
Abstract
High altitude adapted livestock species (cattle, yak, goat, sheep, and horse) has critical role in the human socioeconomic sphere and acts as good source of animal source products including milk, meat, and leather, among other things. These species sustain production and reproduction even in harsh environments on account of adaptation resulting from continued evolution of beneficial traits. Selection pressure leads to various adaptive strategies in livestock whose footprints are evident at the different genomic sites as the "Selection Signature". Scrutiny of these signatures provides us crucial insight into the evolutionary process and domestication of livestock adapted to diverse climatic conditions. These signatures have the potential to change the sphere of animal breeding and further usher the selection programmes in right direction. Technological revolution and recent strides made in genomic studies has opened the routes for the identification of selection signatures. Numerous statistical approaches and bioinformatics tools have been developed to detect the selection signature. Consequently, studies across years have identified candidate genes under selection region found associated with numerous traits which have a say in adaptation to high-altitude environment. This makes it pertinent to have a better understanding about the selection signature, the ways to identify and how to utilize them for betterment of livestock populations as well as farmers. This review takes a closer look into the general concept, various methodologies, and bioinformatics tools commonly employed in selection signature studies and summarize the results of recent selection signature studies related to high-altitude adaptation in various livestock species. This review will serve as an informative and useful insight for researchers and students in the field of animal breeding and evolutionary biology.
Collapse
Affiliation(s)
- Manish Tiwari
- ICAR-National Dairy Research Institute, Karnal, India; U.P. Pt. Deen Dayal Upadhyaya Veterinary Science University and Cattle Research Institute, Mathura, India.
| | | | - C G Shashank
- ICAR-National Dairy Research Institute, Karnal, India
| | | |
Collapse
|
2
|
Götsch H, Bürger R. Polygenic dynamics underlying the response of quantitative traits to directional selection. Theor Popul Biol 2024; 158:21-59. [PMID: 38677378 DOI: 10.1016/j.tpb.2024.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/14/2024] [Accepted: 04/19/2024] [Indexed: 04/29/2024]
Abstract
We study the response of a quantitative trait to exponential directional selection in a finite haploid population, both at the genetic and the phenotypic level. We assume an infinite sites model, in which the number of new mutations per generation in the population follows a Poisson distribution (with mean Θ) and each mutation occurs at a new, previously monomorphic site. Mutation effects are beneficial and drawn from a distribution. Sites are unlinked and contribute additively to the trait. Assuming that selection is stronger than random genetic drift, we model the initial phase of the dynamics by a supercritical Galton-Watson process. This enables us to obtain time-dependent results. We show that the copy-number distribution of the mutant in generation n, conditioned on non-extinction until n, is described accurately by the deterministic increase from an initial distribution with mean 1. This distribution is related to the absolutely continuous part W+ of the random variable, typically denoted W, that characterizes the stochasticity accumulating during the mutant's sweep. A suitable transformation yields the approximate dynamics of the mutant frequency distribution in a Wright-Fisher population of size N. Our expression provides a very accurate approximation except when mutant frequencies are close to 1. On this basis, we derive explicitly the (approximate) time dependence of the expected mean and variance of the trait and of the expected number of segregating sites. Unexpectedly, we obtain highly accurate approximations for all times, even for the quasi-stationary phase when the expected per-generation response and the trait variance have equilibrated. The latter refine classical results. In addition, we find that Θ is the main determinant of the pattern of adaptation at the genetic level, i.e., whether the initial allele-frequency dynamics are best described by sweep-like patterns at few loci or small allele-frequency shifts at many. The number of segregating sites is an appropriate indicator for these patterns. The selection strength determines primarily the rate of adaptation. The accuracy of our results is tested by comprehensive simulations in a Wright-Fisher framework. We argue that our results apply to more complex forms of directional selection.
Collapse
Affiliation(s)
- Hannah Götsch
- Faculty of Mathematics, University of Vienna, 1090 Vienna, Austria; Vienna Graduate School of Population Genetics, Austria.
| | - Reinhard Bürger
- Faculty of Mathematics, University of Vienna, 1090 Vienna, Austria
| |
Collapse
|
3
|
Unneberg P, Larsson M, Olsson A, Wallerman O, Petri A, Bunikis I, Vinnere Pettersson O, Papetti C, Gislason A, Glenner H, Cartes JE, Blanco-Bercial L, Eriksen E, Meyer B, Wallberg A. Ecological genomics in the Northern krill uncovers loci for local adaptation across ocean basins. Nat Commun 2024; 15:6297. [PMID: 39090106 PMCID: PMC11294593 DOI: 10.1038/s41467-024-50239-7] [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: 12/06/2023] [Accepted: 05/15/2024] [Indexed: 08/04/2024] Open
Abstract
Krill are vital as food for many marine animals but also impacted by global warming. To learn how they and other zooplankton may adapt to a warmer world we studied local adaptation in the widespread Northern krill (Meganyctiphanes norvegica). We assemble and characterize its large genome and compare genome-scale variation among 74 specimens from the colder Atlantic Ocean and warmer Mediterranean Sea. The 19 Gb genome likely evolved through proliferation of retrotransposons, now targeted for inactivation by extensive DNA methylation, and contains many duplicated genes associated with molting and vision. Analysis of 760 million SNPs indicates extensive homogenizing gene-flow among populations. Nevertheless, we detect signatures of adaptive divergence across hundreds of genes, implicated in photoreception, circadian regulation, reproduction and thermal tolerance, indicating polygenic adaptation to light and temperature. The top gene candidate for ecological adaptation was nrf-6, a lipid transporter with a Mediterranean variant that may contribute to early spring reproduction. Such variation could become increasingly important for fitness in Atlantic stocks. Our study underscores the widespread but uneven distribution of adaptive variation, necessitating characterization of genetic variation among natural zooplankton populations to understand their adaptive potential, predict risks and support ocean conservation in the face of climate change.
Collapse
Affiliation(s)
- Per Unneberg
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Mårten Larsson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Anna Olsson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden
| | - Anna Petri
- Uppsala Genome Center, Department of Immunology, Genetics and Pathology, Uppsala University, National Genomics Infrastructure hosted by SciLifeLab, Uppsala, Sweden
| | - Ignas Bunikis
- Uppsala Genome Center, Department of Immunology, Genetics and Pathology, Uppsala University, National Genomics Infrastructure hosted by SciLifeLab, Uppsala, Sweden
| | - Olga Vinnere Pettersson
- Uppsala Genome Center, Department of Immunology, Genetics and Pathology, Uppsala University, National Genomics Infrastructure hosted by SciLifeLab, Uppsala, Sweden
| | | | - Astthor Gislason
- Marine and Freshwater Research Institute, Pelagic Division, Reykjavik, Iceland
| | - Henrik Glenner
- Department of Biological Sciences, University of Bergen, Bergen, Norway
- Center for Macroecology, Evolution and Climate Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Joan E Cartes
- Instituto de Ciencias del Mar (ICM-CSIC), Barcelona, Spain
| | | | | | - Bettina Meyer
- Section Polar Biological Oceanography, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
- Institute for Chemistry and Biology of the Marine Environment, Carlvon Ossietzky University of Oldenburg, Oldenburg, Germany
- Helmholtz Institute for Functional Marine Biodiversity (HIFMB), University of Oldenburg, Oldenburg, Germany
| | - Andreas Wallberg
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden.
| |
Collapse
|
4
|
Chotai M, Wei X, Messer PW. Signatures of selective sweeps in continuous-space populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.26.605365. [PMID: 39091822 PMCID: PMC11291165 DOI: 10.1101/2024.07.26.605365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Selective sweeps describe the process by which an adaptive mutation arises and rapidly fixes in the population, thereby removing genetic variation in its genomic vicinity. The expected signatures of selective sweeps are relatively well understood in panmictic population models, yet natural populations often extend across larger geographic ranges where individuals are more likely to mate with those born nearby. To investigate how such spatial population structure can affect sweep dynamics and signatures, we simulated selective sweeps in populations inhabiting a two-dimensional continuous landscape. The maximum dispersal distance of offspring from their parents can be varied in our simulations from an essentially panmictic population to scenarios with increasingly limited dispersal. We find that in low-dispersal populations, adaptive mutations spread more slowly than in panmictic ones, while recombination becomes less effective at breaking up genetic linkage around the sweep locus. Together, these factors result in a trough of reduced genetic diversity around the sweep locus that looks very similar across dispersal rates. We also find that the site frequency spectrum around hard sweeps in low-dispersal populations becomes enriched for intermediate-frequency variants, making these sweeps appear softer than they are. Furthermore, haplotype heterozygosity at the sweep locus tends to be elevated in low-dispersal scenarios as compared to panmixia, contrary to what we observe in neutral scenarios without sweeps. The haplotype patterns generated by these hard sweeps in low-dispersal populations can resemble soft sweeps from standing genetic variation that arose from substantially older alleles. Our results highlight the need for better accounting for spatial population structure when making inferences about selective sweeps.
Collapse
|
5
|
Ostridge HJ, Fontsere C, Lizano E, Soto DC, Schmidt JM, Saxena V, Alvarez-Estape M, Barratt CD, Gratton P, Bocksberger G, Lester JD, Dieguez P, Agbor A, Angedakin S, Assumang AK, Bailey E, Barubiyo D, Bessone M, Brazzola G, Chancellor R, Cohen H, Coupland C, Danquah E, Deschner T, Dotras L, Dupain J, Egbe VE, Granjon AC, Head J, Hedwig D, Hermans V, Hernandez-Aguilar RA, Jeffery KJ, Jones S, Junker J, Kadam P, Kaiser M, Kalan AK, Kambere M, Kienast I, Kujirakwinja D, Langergraber KE, Lapuente J, Larson B, Laudisoit A, Lee KC, Llana M, Maretti G, Martín R, Meier A, Morgan D, Neil E, Nicholl S, Nixon S, Normand E, Orbell C, Ormsby LJ, Orume R, Pacheco L, Preece J, Regnaut S, Robbins MM, Rundus A, Sanz C, Sciaky L, Sommer V, Stewart FA, Tagg N, Tédonzong LR, van Schijndel J, Vendras E, Wessling EG, Willie J, Wittig RM, Yuh YG, Yurkiw K, Vigilant L, Piel A, Boesch C, Kühl HS, Dennis MY, Marques-Bonet T, Arandjelovic M, Andrés AM. Local genetic adaptation to habitat in wild chimpanzees. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.09.601734. [PMID: 39026872 PMCID: PMC11257515 DOI: 10.1101/2024.07.09.601734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
How populations adapt to their environment is a fundamental question in biology. Yet we know surprisingly little about this process, especially for endangered species such as non-human great apes. Chimpanzees, our closest living relatives, are particularly interesting because they inhabit diverse habitats, from rainforest to woodland-savannah. Whether genetic adaptation facilitates such habitat diversity remains unknown, despite having wide implications for evolutionary biology and conservation. Using 828 newly generated exomes from wild chimpanzees, we find evidence of fine-scale genetic adaptation to habitat. Notably, adaptation to malaria in forest chimpanzees is mediated by the same genes underlying adaptation to malaria in humans. This work demonstrates the power of non-invasive samples to reveal genetic adaptations in endangered populations and highlights the importance of adaptive genetic diversity for chimpanzees.
Collapse
Affiliation(s)
- Harrison J Ostridge
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Claudia Fontsere
- Center for Evolutionary Hologenomics, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Esther Lizano
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Daniela C Soto
- University of California, Davis, Genome Center, MIND Institute, Department of Biochemistry & Molecular Medicine, One Shields Drive, Davis, CA, 95616, USA
| | - Joshua M Schmidt
- Flinders Health and Medical Research Institute (FHMRI), Department of Ophthalmology, Flinders University Sturt Rd, Bedford Park South Australia 5042 Australia
| | - Vrishti Saxena
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Marina Alvarez-Estape
- University of California, Davis, Genome Center, MIND Institute, Department of Biochemistry & Molecular Medicine, One Shields Drive, Davis, CA, 95616, USA
| | - Christopher D Barratt
- Naturalis Biodiversity Center, Darwinweg 2, 2333 CR Leiden, the Netherlands
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Leipzig-Jena, Puschstrasse 4, 04103 Leipzig, Germany
| | - Paolo Gratton
- University of Rome "Tor Vergata" Department of Biology Via Cracovia, 1, Roma, Italia
| | - Gaëlle Bocksberger
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Senckenberganlage, 60325 Frankfurt am Main, Germany
| | - Jack D Lester
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Paula Dieguez
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Leipzig-Jena, Puschstrasse 4, 04103 Leipzig, Germany
| | - Anthony Agbor
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Samuel Angedakin
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Alfred Kwabena Assumang
- Department of Wildlife and Range Management, Faculty of Renewable Natural Resources, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Emma Bailey
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Donatienne Barubiyo
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Mattia Bessone
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- University of Konstanz, Centre for the Advanced Study of Collective Behaviour, Universitätsstraße 10, 78464, Konstanz, Germany
| | - Gregory Brazzola
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Rebecca Chancellor
- West Chester University, Depts of Anthropology & Sociology and Psychology, West Chester, PA, 19382 USA
| | - Heather Cohen
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Leipzig-Jena, Puschstrasse 4, 04103 Leipzig, Germany
| | - Charlotte Coupland
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Emmanuel Danquah
- Department of Wildlife and Range Management, Faculty of Renewable Natural Resources, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Tobias Deschner
- Institute of Cognitive Science, University of Osnabrück, Artilleriestrasse 34, 49076 Osnabrück, Germany
| | - Laia Dotras
- Jane Goodall Institute Spain and Senegal, Dindefelo Biological Station, Dindefelo, Kedougou, Senegal
- Department of Social Psychology and Quantitative Psychology, Serra Hunter Programme, University of Barcelona, Barcelona, Spain
| | - Jef Dupain
- Antwerp Zoo Foundation, RZSA, Kon.Astridplein 26, 2018 Antwerp, Belgium
| | - Villard Ebot Egbe
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Anne-Céline Granjon
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Josephine Head
- The Biodiversity Consultancy, 3E Kings Parade, Cambridge, CB2 1SJ, UK
| | - Daniela Hedwig
- Elephant Listening Project, K. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, NY 14850, USA
| | - Veerle Hermans
- KMDA, Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 20-26, B-2018 Antwerp, Belgium
| | - R Adriana Hernandez-Aguilar
- Jane Goodall Institute Spain and Senegal, Dindefelo Biological Station, Dindefelo, Kedougou, Senegal
- Department of Social Psychology and Quantitative Psychology, Serra Hunter Programme, University of Barcelona, Barcelona, Spain
| | - Kathryn J Jeffery
- School of Natural Sciences, University of Stirling, UK
- Agence National des Parcs Nationaux (ANPN) Batterie 4, BP20379, Libreville, Gabon
| | - Sorrel Jones
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Jessica Junker
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Leipzig-Jena, Puschstrasse 4, 04103 Leipzig, Germany
| | - Parag Kadam
- Greater Mahale Ecosystem Research and Conservation Project
| | - Michael Kaiser
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Ammie K Kalan
- Department of Anthropology, University of Victoria, 3800 Finnerty Rd, Victoria, BC V8P 5C2, Canada
| | - Mbangi Kambere
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Ivonne Kienast
- Department of Natural Resources and the Environment, Cornell University, Ithaca, NY 14850, USA
- K. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY 14850, USA
| | - Deo Kujirakwinja
- Wildlife Conservation Society (WCS), 2300 Southern Boulevard. Bronx, New York 10460, USA
| | - Kevin E Langergraber
- School of Human Evolution and Social Change, Institute of Human Origins, Arizona State University, 777 East University Drive, Tempe, AZ 85287 Arizona State University, PO Box 872402, Tempe, AZ 85287-2402 USA
- Institute of Human Origins, Arizona State University, 900 Cady Mall, Tempe, AZ 85287 Arizona State University, PO Box 872402, Tempe, AZ 85287-2402 USA
| | - Juan Lapuente
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | | | | | - Kevin C Lee
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- K. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY 14850, USA
| | - Manuel Llana
- Jane Goodall Institute Spain and Senegal, Dindefelo Biological Station, Dindefelo, Kedougou, Senegal
| | - Giovanna Maretti
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Rumen Martín
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Amelia Meier
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- Hawai'i Insititute of Marine Biology, University of Hawai'i at Manoa, 46-007 Lilipuna Place, Kaneohe, HI, 96744, USA
| | - David Morgan
- Lester E. Fisher Center for the Study and Conservation of Apes, Lincoln Park Zoo, 2001 North Clark Street, Chicago, Illinois 60614 USA
| | - Emily Neil
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Sonia Nicholl
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Stuart Nixon
- North of England Zoological Society, Chester Zoo, Upton by Chester, CH2 1LH, United Kingdom
| | | | - Christopher Orbell
- Panthera, 8 W 40TH ST, New York, NY 10018, USA
- School of Natural Sciences, University of Stirling, UK
| | - Lucy Jayne Ormsby
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Robinson Orume
- Korup Rainforest Conservation Society, c/o Korup National Park, P.O. Box 36 Mundemba, South West Region, Cameroon
| | - Liliana Pacheco
- Save the Dogs and Other Animals, DJ 223 Km 3, 905200 Cernavoda CT, Romania
| | - Jodie Preece
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | | | - Martha M Robbins
- Max Planck Institute for Evolutionary Anthropology, Department of Primate Behavior and Evolution, Deutscher Platz 6, 04103 Leipzig
| | - Aaron Rundus
- West Chester University, Depts of Anthropology & Sociology and Psychology, West Chester, PA, 19382 USA
| | - Crickette Sanz
- Washington University in Saint Louis, Department of Anthropology, One Brookings Drive, St. Louis, MO 63130, USA
- Congo Program, Wildlife Conservation Society, 151 Avenue Charles de Gaulle, Brazzaville, Republic of Congo
| | - Lilah Sciaky
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Volker Sommer
- University College London, Department of Anthropology, 14 Taviton Street, London WC1H 0BW, UK
| | - Fiona A Stewart
- University College London, Department of Anthropology, 14 Taviton Street, London WC1H 0BW, UK
- Department of Human Origins, Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Nikki Tagg
- KMDA, Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 20-26, B-2018 Antwerp, Belgium
- Born Free Foundation, Floor 2 Frazer House, 14 Carfax, Horsham, RH12 1ER, UK
| | - Luc Roscelin Tédonzong
- KMDA, Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 20-26, B-2018 Antwerp, Belgium
| | - Joost van Schijndel
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Elleni Vendras
- Frankfurt Zoological Society, Bernhard-Grzimek-Allee 1, 60316 Frankfurt, Germany
| | - Erin G Wessling
- Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, Georg-August-University Göttingen,Göttingen, Germany
- German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany
| | - Jacob Willie
- KMDA, Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 20-26, B-2018 Antwerp, Belgium
- Terrestrial Ecology Unit (TEREC), Department of Biology, Ghent University (UGent), K.L. Ledeganckstraat 35, 9000 Ghent, Belgium
| | - Roman M Wittig
- Ape Social Mind Lab, Institute for Cognitive Sciences Marc Jeannerod, CNRS UMR 5229 CNRS, 67 bd Pinel, 69675 Bron CEDEX, France
- Taï Chimpanzee Project, Centre Suisse de Recherches Scientifiques, BP 1301, Abidjan 01, CI
| | - Yisa Ginath Yuh
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Kyle Yurkiw
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Linda Vigilant
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Alex Piel
- University College London, Department of Anthropology, 14 Taviton Street, London WC1H 0BW, UK
| | | | - Hjalmar S Kühl
- Senckenberg Museum for Natural History Görlitz, Senckenberg - Member of the Leibniz Association Am Museum 1, 02826 Görlitz, Germany
- International Institute Zittau, Technische Universität Dresden, Markt 23, 02763 Zittau, Germany
| | - Megan Y Dennis
- University of California, Davis, Genome Center, MIND Institute, Department of Biochemistry & Molecular Medicine, One Shields Drive, Davis, CA, 95616, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010, Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Mimi Arandjelovic
- Max Planck Institute for Evolutionary Anthropology, Department of Primate Behavior and Evolution, Deutscher Platz 6, 04103 Leipzig
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstrasse 4, 04103
| | - Aida M Andrés
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| |
Collapse
|
6
|
Giel AS, Bigge J, Schumacher J, Maj C, Dasmeh P. Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity Across Polygenic Phenotypes. Mol Biol Evol 2024; 41:msae115. [PMID: 38865495 PMCID: PMC11247350 DOI: 10.1093/molbev/msae115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 03/22/2024] [Accepted: 05/03/2024] [Indexed: 06/14/2024] Open
Abstract
Understanding the expression level and evolutionary rate of associated genes with human polygenic diseases provides crucial insights into their disease-contributing roles. In this work, we leveraged genome-wide association studies (GWASs) to investigate the relationship between the genetic association and both the evolutionary rate (dN/dS) and expression level of human genes associated with the two polygenic diseases of schizophrenia and coronary artery disease. Our findings highlight a distinct variation in these relationships between the two diseases. Genes associated with both diseases exhibit a significantly greater variance in evolutionary rate compared to those implicated in monogenic diseases. Expanding our analyses to 4,756 complex traits in the GWAS atlas database, we unraveled distinct trait categories with a unique interplay among the evolutionary rate, expression level, and genetic association of human genes. In most polygenic traits, highly expressed genes were more associated with the polygenic phenotypes compared to lowly expressed genes. About 69% of polygenic traits displayed a negative correlation between genetic association and evolutionary rate, while approximately 30% of these traits showed a positive correlation between genetic association and evolutionary rate. Our results demonstrate the presence of a spectrum among complex traits, shaped by natural selection. Notably, at opposite ends of this spectrum, we find metabolic traits being more likely influenced by purifying selection, and immunological traits that are more likely shaped by positive selection. We further established the polygenic evolution portal (evopolygen.de) as a resource for investigating relationships and generating hypotheses in the field of human polygenic trait evolution.
Collapse
Affiliation(s)
- Ann-Sophie Giel
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | - Jessica Bigge
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | | | - Carlo Maj
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | - Pouria Dasmeh
- Centre for Human Genetics, Marburg University, Marburg, Germany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Institute for Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| |
Collapse
|
7
|
Hartfield M, Glémin S. Polygenic selection to a changing optimum under self-fertilisation. PLoS Genet 2024; 20:e1011312. [PMID: 39018328 DOI: 10.1371/journal.pgen.1011312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 07/29/2024] [Accepted: 05/21/2024] [Indexed: 07/19/2024] Open
Abstract
Many traits are polygenic, affected by multiple genetic variants throughout the genome. Selection acting on these traits involves co-ordinated allele-frequency changes at these underlying variants, and this process has been extensively studied in random-mating populations. Yet many species self-fertilise to some degree, which incurs changes to genetic diversity, recombination and genome segregation. These factors cumulatively influence how polygenic selection is realised in nature. Here, we use analytical modelling and stochastic simulations to investigate to what extent self-fertilisation affects polygenic adaptation to a new environment. Our analytical solutions show that while selfing can increase adaptation to an optimum, it incurs linkage disequilibrium that can slow down the initial spread of favoured mutations due to selection interference, and favours the fixation of alleles with opposing trait effects. Simulations show that while selection interference is present, high levels of selfing (at least 90%) aids adaptation to a new optimum, showing a higher long-term fitness. If mutations are pleiotropic then only a few major-effect variants fix along with many neutral hitchhikers, with a transient increase in linkage disequilibrium. These results show potential advantages to self-fertilisation when adapting to a new environment, and how the mating system affects the genetic composition of polygenic selection.
Collapse
Affiliation(s)
- Matthew Hartfield
- Institute of Ecology and Evolution, The University of Edinburgh, Edinburgh, United Kingdom
| | - Sylvain Glémin
- Université de Rennes, Centre National de la Recherche Scientifique (CNRS), ECOBIO (Ecosystèmes, Biodiversité, Evolution) - Unité Mixte de Recherche (UMR) 6553, Rennes, France
- Department of Ecology and Evolution, Evolutionary Biology Center, Uppsala University, Uppsala, Sweden
| |
Collapse
|
8
|
Venu V, Harjunmaa E, Dreau A, Brady S, Absher D, Kingsley DM, Jones FC. Fine-scale contemporary recombination variation and its fitness consequences in adaptively diverging stickleback fish. Nat Ecol Evol 2024; 8:1337-1352. [PMID: 38839849 PMCID: PMC11239493 DOI: 10.1038/s41559-024-02434-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 05/02/2024] [Indexed: 06/07/2024]
Abstract
Despite deep evolutionary conservation, recombination rates vary greatly across the genome and among individuals, sexes and populations. Yet the impact of this variation on adaptively diverging populations is not well understood. Here we characterized fine-scale recombination landscapes in an adaptively divergent pair of marine and freshwater populations of threespine stickleback from River Tyne, Scotland. Through whole-genome sequencing of large nuclear families, we identified the genomic locations of almost 50,000 crossovers and built recombination maps for marine, freshwater and hybrid individuals at a resolution of 3.8 kb. We used these maps to quantify the factors driving variation in recombination rates. We found strong heterochiasmy between sexes but also differences in recombination rates among ecotypes. Hybrids showed evidence of significant recombination suppression in overall map length and in individual loci. Recombination rates were lower not only within individual marine-freshwater-adaptive loci, but also between loci on the same chromosome, suggesting selection on linked gene 'cassettes'. Through temporal sampling along a natural hybrid zone, we found that recombinants showed traits associated with reduced fitness. Our results support predictions that divergence in cis-acting recombination modifiers, whose functions are disrupted in hybrids, may play an important role in maintaining differences among adaptively diverging populations.
Collapse
Affiliation(s)
- Vrinda Venu
- Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany.
- Los Alamos National Laboratory, New Mexico, NM, USA.
| | - Enni Harjunmaa
- Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany
- CeGAT GmbH, Tübingen, Germany
| | - Andreea Dreau
- Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany
- Evotec SE 'Campus Curie', Toulouse, France
| | - Shannon Brady
- Deptartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - David M Kingsley
- Deptartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Felicity C Jones
- Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany.
- Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Groningen, the Netherlands.
| |
Collapse
|
9
|
Blanc J, Berg JJ. Testing for differences in polygenic scores in the presence of confounding. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.12.532301. [PMID: 36993707 PMCID: PMC10055004 DOI: 10.1101/2023.03.12.532301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Polygenic scores have become an important tool in human genetics, enabling the prediction of individuals' phenotypes from their genotypes. Understanding how the pattern of differences in polygenic score predictions across individuals intersects with variation in ancestry can provide insights into the evolutionary forces acting on the trait in question, and is important for understanding health disparities. However, because most polygenic scores are computed using effect estimates from population samples, they are susceptible to confounding by both genetic and environmental effects that are correlated with ancestry. The extent to which this confounding drives patterns in the distribution of polygenic scores depends on patterns of population structure in both the original estimation panel and in the prediction/test panel. Here, we use theory from population and statistical genetics, together with simulations, to study the procedure of testing for an association between polygenic scores and axes of ancestry variation in the presence of confounding. We use a general model of genetic relatedness to describe how confounding in the estimation panel biases the distribution of polygenic scores in a way that depends on the degree of overlap in population structure between panels. We then show how this confounding can bias tests for associations between polygenic scores and important axes of ancestry variation in the test panel. Specifically, for any given test, there exists a single axis of population structure in the GWAS panel that needs to be controlled for in order to protect the test. Based on this result, we propose a new approach for directly estimating this axis of population structure in the GWAS panel. We then use simulations to compare the performance of this approach to the standard approach in which the principal components of the GWAS panel genotypes are used to control for stratification.
Collapse
Affiliation(s)
- Jennifer Blanc
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Jeremy J. Berg
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| |
Collapse
|
10
|
Ribeiro TDS, Lollar MJ, Sprengelmeyer QD, Huang Y, Benson DM, Orr MS, Johnson ZC, Corbett-Detig RB, Pool JE. Recombinant inbred line panels inform the genetic architecture and interactions of adaptive traits in Drosophila melanogaster. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.14.594228. [PMID: 38798433 PMCID: PMC11118405 DOI: 10.1101/2024.05.14.594228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The distribution of allelic effects on traits, along with their gene-by-gene and gene-by-environment interactions, contributes to the phenotypes available for selection and the trajectories of adaptive variants. Nonetheless, uncertainty persists regarding the effect sizes underlying adaptations and the importance of genetic interactions. Herein, we aimed to investigate the genetic architecture and the epistatic and environmental interactions involving loci that contribute to multiple adaptive traits using two new panels of Drosophila melanogaster recombinant inbred lines (RILs). To better fit our data, we re-implemented functions from R/qtl (Broman et al. 2003) using additive genetic models. We found 14 quantitative trait loci (QTL) underlying melanism, wing size, song pattern, and ethanol resistance. By combining our mapping results with population genetic statistics, we identified potential new genes related to these traits. None of the detected QTLs showed clear evidence of epistasis, and our power analysis indicated that we should have seen at least one significant interaction if sign epistasis or strong positive epistasis played a pervasive role in trait evolution. In contrast, we did find roles for gene-by-environment interactions involving pigmentation traits. Overall, our data suggest that the genetic architecture of adaptive traits often involves alleles of detectable effect, that strong epistasis does not always play a role in adaptation, and that environmental interactions can modulate the effect size of adaptive alleles.
Collapse
Affiliation(s)
- Tiago da Silva Ribeiro
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Matthew J. Lollar
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | | | - Yuheng Huang
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Derek M. Benson
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Megan S. Orr
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Zachary C. Johnson
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Russell B. Corbett-Detig
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA, 95064, USA
| | - John E. Pool
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| |
Collapse
|
11
|
Eldon B, Stephan W. Sweepstakes reproduction facilitates rapid adaptation in highly fecund populations. Mol Ecol 2024; 33:e16903. [PMID: 36896794 DOI: 10.1111/mec.16903] [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: 05/23/2022] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 03/11/2023]
Abstract
Adaptation enables natural populations to survive in a changing environment. Understanding the mechanics of adaptation is therefore crucial for learning about the evolution and ecology of natural populations. We focus on the impact of random sweepstakes on selection in highly fecund haploid and diploid populations partitioned into two genetic types, with one type conferring selective advantage. For the diploid populations, we incorporate various dominance mechanisms. We assume that the populations may experience recurrent bottlenecks. In random sweepstakes, the distribution of individual recruitment success is highly skewed, resulting in a huge variance in the number of offspring contributed by the individuals present in any given generation. Using computer simulations, we investigate the joint effects of random sweepstakes, recurrent bottlenecks and dominance mechanisms on selection. In our framework, bottlenecks allow random sweepstakes to have an effect on the time to fixation, and in diploid populations, the effect of random sweepstakes depends on the dominance mechanism. We describe selective sweepstakes that are approximated by recurrent sweeps of strongly beneficial allelic types arising by mutation. We demonstrate that both types of sweepstakes reproduction may facilitate rapid adaptation (as defined based on the average time to fixation of a type conferring selective advantage conditioned on fixation of the type). However, whether random sweepstakes cause rapid adaptation depends also on their interactions with bottlenecks and dominance mechanisms. Finally, we review a case study in which a model of recurrent sweeps is shown to essentially explain population genomic data from Atlantic cod.
Collapse
Affiliation(s)
- Bjarki Eldon
- Institute of Evolution and Biodiversity Science, Natural History Museum Berlin, Berlin, Germany
| | | |
Collapse
|
12
|
Lai WY, Nolte V, Jakšić AM, Schlötterer C. Evolution of Phenotypic Variance Provides Insights into the Genetic Basis of Adaptation. Genome Biol Evol 2024; 16:evae077. [PMID: 38620076 PMCID: PMC11057206 DOI: 10.1093/gbe/evae077] [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: 05/11/2023] [Revised: 03/27/2024] [Accepted: 04/02/2024] [Indexed: 04/17/2024] Open
Abstract
Most traits are polygenic, and the contributing loci can be identified by genome-wide association studies. The genetic basis of adaptation (adaptive architecture) is, however, difficult to characterize. Here, we propose to study the adaptive architecture of traits by monitoring the evolution of their phenotypic variance during adaptation to a new environment in well-defined laboratory conditions. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting can distinguish between oligogenic and polygenic adaptive architectures. We compared gene expression variance in male Drosophila simulans before and after 100 generations of adaptation to a novel hot environment. The variance change in gene expression was indistinguishable for genes with and without a significant change in mean expression after 100 generations of evolution. We suggest that the majority of adaptive gene expression evolution can be explained by a polygenic architecture. We propose that tracking the evolution of phenotypic variance across generations can provide an approach to characterize the adaptive architecture.
Collapse
Affiliation(s)
- Wei-Yun Lai
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - Ana Marija Jakšić
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna, Austria
- Present address: École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | | |
Collapse
|
13
|
Fenton S, Jacobs A, Bean CW, Adams CE, Elmer KR. Genomic underpinnings of head and body shape in Arctic charr ecomorph pairs. Mol Ecol 2024; 33:e17305. [PMID: 38421099 DOI: 10.1111/mec.17305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 01/31/2024] [Accepted: 02/05/2024] [Indexed: 03/02/2024]
Abstract
Across its Holarctic range, Arctic charr (Salvelinus alpinus) populations have diverged into distinct trophic specialists across independent replicate lakes. The major aspect of divergence between ecomorphs is in head shape and body shape, which are ecomorphological traits reflecting niche use. However, whether the genomic underpinnings of these parallel divergences are consistent across replicates was unknown but key for resolving the substrate of parallel evolution. We investigated the genomic basis of head shape and body shape morphology across four benthivore-planktivore ecomorph pairs of Arctic charr in Scotland. Through genome-wide association analyses, we found genomic regions associated with head shape (89 SNPs) or body shape (180 SNPs) separately and 50 of these SNPs were strongly associated with both body and head shape morphology. For each trait separately, only a small number of SNPs were shared across all ecomorph pairs (3 SNPs for head shape and 10 SNPs for body shape). Signs of selection on the associated genomic regions varied across pairs, consistent with evolutionary demography differing considerably across lakes. Using a comprehensive database of salmonid QTLs newly augmented and mapped to a charr genome, we found several of the head- and body-shape-associated SNPs were within or near morphology QTLs from other salmonid species, reflecting a shared genetic basis for these phenotypes across species. Overall, our results demonstrate how parallel ecotype divergences can have both population-specific and deeply shared genomic underpinnings across replicates, influenced by differences in their environments and demographic histories.
Collapse
Affiliation(s)
- Sam Fenton
- School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow, Glasgow, UK
| | - Arne Jacobs
- School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow, Glasgow, UK
| | - Colin W Bean
- School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow, Glasgow, UK
- NatureScot, Clydebank, UK
| | - Colin E Adams
- School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow, Glasgow, UK
- Scottish Centre for Ecology and the Natural Environment, University of Glasgow, Glasgow, UK
| | - Kathryn R Elmer
- School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow, Glasgow, UK
| |
Collapse
|
14
|
Kyu KL, Taylor CM, Douglas CA, Malik AI, Colmer TD, Siddique KHM, Erskine W. Genetic diversity and candidate genes for transient waterlogging tolerance in mungbean at the germination and seedling stages. FRONTIERS IN PLANT SCIENCE 2024; 15:1297096. [PMID: 38584945 PMCID: PMC10996369 DOI: 10.3389/fpls.2024.1297096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/26/2024] [Indexed: 04/09/2024]
Abstract
Mungbean [Vigna radiata var. radiata (L.) Wilczek] production in Asia is detrimentally affected by transient soil waterlogging caused by unseasonal and increasingly frequent extreme precipitation events. While mungbean exhibits sensitivity to waterlogging, there has been insufficient exploration of germplasm for waterlogging tolerance, as well as limited investigation into the genetic basis for tolerance to identify valuable loci. This research investigated the diversity of transient waterlogging tolerance in a mini-core germplasm collection of mungbean and identified candidate genes for adaptive traits of interest using genome-wide association studies (GWAS) at two critical stages of growth: germination and seedling stage (i.e., once the first trifoliate leaf had fully-expanded). In a temperature-controlled glasshouse, 292 genotypes were screened for tolerance after (i) 4 days of waterlogging followed by 7 days of recovery at the germination stage and (ii) 8 days of waterlogging followed by 7 days of recovery at the seedling stage. Tolerance was measured against drained controls. GWAS was conducted using 3,522 high-quality DArTseq-derived SNPs, revealing five significant associations with five phenotypic traits indicating improved tolerance. Waterlogging tolerance was positively correlated with the formation of adventitious roots and higher dry masses. FGGY carbohydrate kinase domain-containing protein was identified as a candidate gene for adventitious rooting and mRNA-uncharacterized LOC111241851, Caffeoyl-CoA O-methyltransferase At4g26220 and MORC family CW-type zinc finger protein 3 and zinc finger protein 2B genes for shoot, root, and total dry matter production. Moderate to high broad-sense heritability was exhibited for all phenotypic traits, including seed emergence (81%), adventitious rooting (56%), shoot dry mass (81%), root dry mass (79%) and SPAD chlorophyll content (70%). The heritability estimates, marker-trait associations, and identification of sources of waterlogging tolerant germplasm from this study demonstrate high potential for marker-assisted selection of tolerance traits to accelerate breeding of climate-resilient mungbean varieties.
Collapse
Affiliation(s)
- Khin Lay Kyu
- Centre for Plant Genetics and Breeding (PGB), UWA School of Agriculture and Environment, The University of Western Australia, Perth, WA, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
| | | | - Colin Andrew Douglas
- Department of Agriculture and Fisheries, Gatton Research Facility, Gatton, QLD, Australia
| | - Al Imran Malik
- Centre for Plant Genetics and Breeding (PGB), UWA School of Agriculture and Environment, The University of Western Australia, Perth, WA, Australia
- International Center for Tropical Agriculture (CIAT-Asia), Lao PDR Office, Vientiane, Lao People’s Democratic Republic
| | - Timothy David Colmer
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
| | - Kadambot H. M. Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
| | - William Erskine
- Centre for Plant Genetics and Breeding (PGB), UWA School of Agriculture and Environment, The University of Western Australia, Perth, WA, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
| |
Collapse
|
15
|
She H, Hao Y, Song G, Luo X, Lei F, Zhai W, Qu Y. Gene expression plasticity followed by genetic change during colonization in a high-elevation environment. eLife 2024; 12:RP86687. [PMID: 38470231 DOI: 10.7554/elife.86687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024] Open
Abstract
Phenotypic plasticity facilitates organismal invasion of novel environments, and the resultant phenotypic change may later be modified by genetic change, so called 'plasticity first.' Herein, we quantify gene expression plasticity and regulatory adaptation in a wild bird (Eurasian Tree Sparrow) from its original lowland (ancestral stage), experimentally implemented hypoxia acclimation (plastic stage), and colonized highland (colonized stage). Using a group of co-expressed genes from the cardiac and flight muscles, respectively, we demonstrate that gene expression plasticity to hypoxia tolerance is more often reversed than reinforced at the colonized stage. By correlating gene expression change with muscle phenotypes, we show that colonized tree sparrows reduce maladaptive plasticity that largely associated with decreased hypoxia tolerance. Conversely, adaptive plasticity that is congruent with increased hypoxia tolerance is often reinforced in the colonized tree sparrows. Genes displaying large levels of reinforcement or reversion plasticity (i.e. 200% of original level) show greater genetic divergence between ancestral and colonized populations. Overall, our work demonstrates that gene expression plasticity at the initial stage of high-elevation colonization can be reversed or reinforced through selection-driven adaptive modification.
Collapse
Affiliation(s)
- Huishang She
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Yan Hao
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Gang Song
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Xu Luo
- Faculty of Biodiversity and Conservation, Southwest Forestry University, Kunming, China
| | - Fumin Lei
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Weiwei Zhai
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Yanhua Qu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
16
|
Przeworski M. 2023 ASHG Scientific Achievement Award. Am J Hum Genet 2024; 111:425-427. [PMID: 38458164 PMCID: PMC10995464 DOI: 10.1016/j.ajhg.2023.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 12/12/2023] [Indexed: 03/10/2024] Open
Abstract
This article is based on the address given by the author at the 2023 meeting of The American Society of Human Genetics (ASHG) in Washington, D.C. A video of the original address can be found at the ASHG website.
Collapse
Affiliation(s)
- Molly Przeworski
- Departments of Biological Sciences and Systems Biology, Columbia University, New York, NY, USA.
| |
Collapse
|
17
|
Gao Y, Barton JP. A binary trait model reveals the fitness effects of HIV-1 escape from T cell responses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.03.583183. [PMID: 38464239 PMCID: PMC10925374 DOI: 10.1101/2024.03.03.583183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Natural selection often acts on multiple traits simultaneously. For example, the virus HIV-1 faces pressure to evade host immunity while also preserving replicative fitness. While past work has studied selection during HIV-1 evolution, it is challenging to quantitatively separate different contributions to fitness. This task is made more difficult because a single mutation can affect both immune escape and replication. Here, we develop an evolutionary model that disentangles the effects of escaping CD8+ T cell-mediated immunity, which we model as a binary trait, from other contributions to fitness. After validation in simulations, we applied this model to study within-host HIV-1 evolution in a clinical data set. We observed strong selection for immune escape, sometimes greatly exceeding past estimates, especially early in infection. Conservative estimates suggest that roughly half of HIV-1 fitness gains during the first months to years of infection can be attributed to T cell escape. Our approach is not limited to HIV-1 or viruses, and could be adapted to study the evolution of quantitative traits in other contexts.
Collapse
Affiliation(s)
- Yirui Gao
- Department of Physics and Astronomy, University of California, Riverside, USA
| | - John P. Barton
- Department of Physics and Astronomy, University of California, Riverside, USA
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, USA
- Department of Physics and Astronomy, University of Pittsburgh, USA
| |
Collapse
|
18
|
Leonard WR. Pearl Memorial Lecture. Humans at the extremes: Exploring human adaptation to ecological and social stressors. Am J Hum Biol 2024; 36:e24010. [PMID: 37974340 DOI: 10.1002/ajhb.24010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/22/2023] [Accepted: 10/25/2023] [Indexed: 11/19/2023] Open
Abstract
The field of human biology has long explored how human populations have adapted to extreme environmental circumstances. Yet, it has become increasingly clear that conditions of social stress, poverty, and lifestyle change play equally important roles in shaping human biological variation and health. In this paper, I provide a brief background on the foundational human adaptability research of the International Biological Programme (IBP) from the 1960s, highlighting how its successes and critiques have shaped current research directions in the field. I then discuss and reflect on my own field research that has examined the influence of both environmental and social stresses on human populations living in different ecosystems: the Peruvian Andes, the Siberian arctic, and the Bolivian rainforest. Finally, I consider how the papers in this special issue advance our understanding of human adaptability to extreme conditions and offer directions for future research. Drawing on our field's distinctive evolutionary and biocultural perspectives, human biologists are uniquely positioned to examine how the interplay between social and ecological domains influences the human condition.
Collapse
Affiliation(s)
- William R Leonard
- Department of Anthropology & Program in Global Health Studies, Northwestern University, Evanston, Illinois, USA
| |
Collapse
|
19
|
Terasaki Hart DE, Wang IJ. Genomic architecture controls multivariate adaptation to climate change. GLOBAL CHANGE BIOLOGY 2024; 30:e17179. [PMID: 38403891 DOI: 10.1111/gcb.17179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 12/11/2023] [Accepted: 01/12/2024] [Indexed: 02/27/2024]
Abstract
As climate change advances, environmental gradients may decouple, generating novel multivariate environments that stress wild populations. A commonly invoked mechanism of evolutionary rescue is adaptive gene flow tracking climate shifts, but gene flow from populations inhabiting similar conditions on one environmental axis could cause maladaptive introgression when populations are adapted to different environmental variables that do not shift together. Genomic architecture can play an important role in determining the effectiveness and relative magnitudes of adaptive gene flow and in situ adaptation. This may have direct consequences for how species respond to climate change but is often overlooked. Here, we simulated microevolutionary responses to environmental change under scenarios defined by variation in the polygenicity, linkage, and genetic redundancy of two independent traits, one of which is adapted to a gradient that shifts under climate change. We used these simulations to examine how genomic architecture influences evolutionary outcomes under climate change. We found that climate-tracking (up-gradient) gene flow, though present in all scenarios, was strongly constrained under scenarios of lower linkage and higher polygenicity and redundancy, suggesting in situ adaptation as the predominant mechanism of evolutionary rescue under these conditions. We also found that high polygenicity caused increased maladaptation and demographic decline, a concerning result given that many climate-adapted traits may be polygenic. Finally, in scenarios with high redundancy, we observed increased adaptive capacity. This finding adds to the growing recognition of the importance of redundancy in mediating in situ adaptive capacity and suggests opportunities for better understanding the climatic vulnerability of real populations.
Collapse
Affiliation(s)
- Drew E Terasaki Hart
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California, USA
- The Nature Conservancy, Arlington, Virginia, USA
- CSIRO Environment, Brisbane, Queensland, Australia
| | - Ian J Wang
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California, USA
| |
Collapse
|
20
|
Russo CAM, Eyre-Walker A, Katz LA, Gaut BS. Forty Years of Inferential Methods in the Journals of the Society for Molecular Biology and Evolution. Mol Biol Evol 2024; 41:msad264. [PMID: 38197288 PMCID: PMC10763999 DOI: 10.1093/molbev/msad264] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 11/27/2023] [Indexed: 01/11/2024] Open
Abstract
We are launching a series to celebrate the 40th anniversary of the first issue of Molecular Biology and Evolution. In 2024, we will publish virtual issues containing selected papers published in the Society for Molecular Biology and Evolution journals, Molecular Biology and Evolution and Genome Biology and Evolution. Each virtual issue will be accompanied by a perspective that highlights the historic and contemporary contributions of our journals to a specific topic in molecular evolution. This perspective, the first in the series, presents an account of the broad array of methods that have been published in the Society for Molecular Biology and Evolution journals, including methods to infer phylogenies, to test hypotheses in a phylogenetic framework, and to infer population genetic processes. We also mention many of the software implementations that make methods tractable for empiricists. In short, the Society for Molecular Biology and Evolution community has much to celebrate after four decades of publishing high-quality science including numerous important inferential methods.
Collapse
Affiliation(s)
- Claudia A M Russo
- Departamento de Genética, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Laura A Katz
- Department of Biological Sciences, Smith College, Northampton, MA, USA
| | - Brandon S Gaut
- School of Biological Sciences, University of California, Irvine, CA, USA
| |
Collapse
|
21
|
Gao Z. Unveiling recent and ongoing adaptive selection in human populations. PLoS Biol 2024; 22:e3002469. [PMID: 38236800 PMCID: PMC10796035 DOI: 10.1371/journal.pbio.3002469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024] Open
Abstract
Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.
Collapse
Affiliation(s)
- Ziyue Gao
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| |
Collapse
|
22
|
Miller JT, Clark BW, Reid NM, Karchner SI, Roach JL, Hahn ME, Nacci D, Whitehead A. Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect. Evol Appl 2024; 17:e13648. [PMID: 38293268 PMCID: PMC10824703 DOI: 10.1111/eva.13648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 01/02/2024] [Accepted: 01/09/2024] [Indexed: 02/01/2024] Open
Abstract
The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts that adaptation is due to a few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and using RAD-seq genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that one to two large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling. One QTL locus was shared across all populations and another was shared across three populations. One QTL locus showed strong signatures of recent natural selection in the corresponding wild population but another QTL locus did not. Some candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.
Collapse
Affiliation(s)
- Jeffrey T. Miller
- Department of Environmental Toxicology, Center for Population Biology, Coastal and Marine Sciences InstituteUniversity of California, DavisDavisCaliforniaUSA
- Present address:
Molecular, Cellular, and Biomedical SciencesUniversity of New HampshireDurhamNew HampshireUSA
| | - Bryan W. Clark
- Office of Research and Development, Center for Environmental Measurement and Modeling, Atlantic Coastal Environmental Sciences DivisionUS Environmental Protection AgencyNarragansettRhode IslandUSA
| | - Noah M. Reid
- Department of Molecular & Cell BiologyUniversity of ConnecticutStorrsConnecticutUSA
| | - Sibel I. Karchner
- Biology DepartmentWoods Hole Oceanographic InstitutionWoods HoleMassachusettsUSA
| | - Jennifer L. Roach
- Department of Environmental Toxicology, Center for Population Biology, Coastal and Marine Sciences InstituteUniversity of California, DavisDavisCaliforniaUSA
| | - Mark E. Hahn
- Biology DepartmentWoods Hole Oceanographic InstitutionWoods HoleMassachusettsUSA
| | - Diane Nacci
- Office of Research and Development, Center for Environmental Measurement and Modeling, Atlantic Coastal Environmental Sciences DivisionUS Environmental Protection AgencyNarragansettRhode IslandUSA
| | - Andrew Whitehead
- Department of Environmental Toxicology, Center for Population Biology, Coastal and Marine Sciences InstituteUniversity of California, DavisDavisCaliforniaUSA
| |
Collapse
|
23
|
Bell AV. Selection and adaptation in human migration. Evol Anthropol 2023; 32:308-324. [PMID: 37589279 DOI: 10.1002/evan.22003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 06/18/2023] [Accepted: 08/07/2023] [Indexed: 08/18/2023]
Abstract
This article reviews the ways migration shapes human biology. This includes the physiological and genetic, but also socio-cultural aspects such as organization, behavior, and culture. Across disciplines I highlight the multiple levels of cultural and genetic selection whereby individuals and groups adapt to pressures along a migration timeline: the origin, transit, and destination. Generally, the evidence suggests that selective pressures and adaptations occur at the individual, family, and community levels. Consequently, across levels there are negotiations, interactions, and feedbacks that shape migration outcomes and the trajectory of evolutionary change. The rise and persistence of migration-relevant adaptations emerges as a central question, including the maintenance of cumulative culture adaptations, the persistence of "cultures of migration," as well as the individual-level physiological and cognitive adaptations applied to successful transit and settlement in novel environments.
Collapse
Affiliation(s)
- Adrian Viliami Bell
- Department of Anthropology, University of Utah, Salt Lake City, Utah, USA
- Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| |
Collapse
|
24
|
Lamkey CM, Lorenz AJ. A genomic analysis of the University of Nebraska Replicated Recurrent Selection program. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:243. [PMID: 37950832 DOI: 10.1007/s00122-023-04475-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 09/27/2023] [Indexed: 11/13/2023]
Abstract
The inbred-hybrid system of maize breeding closely resembles a reciprocal full-sib (RFS) selection program. Studying changes in genetic variation as a result of RFS selection can help illuminate long-standing questions regarding the relative roles of selection and genetic drift and help understand the nature of adaptation occurring in selection programs. The University of Nebraska-Lincoln Replicated Recurrent Selection (UNL-RpRS) program underwent eight cycles of replicated RFS and S1-progeny selection, making it a powerful system to study genomic changes accompanying selection for inter-population performance. The objectives of this study were to identify regions of the genome under selection after eight cycles of selection and evaluate the effect eight cycles of selection for inter-population full-sib performance had in expanding genome-wide and localized population structure. We address these questions with a large set of individuals sampled from the UNL-RpRS program with dense genotyping-by-sequence data. We found evidence of parallel selection signatures in the UNL-RpRS program, with a region on chromosome 7 being implicated in three of the four selection systems studied. Regions that displayed selection signatures across independently run selection programs represent regions likely to be capitalizing on standing genetic variation and support a soft sweep model of adaptation. We did not find selection to be a strong force in diverging populations undergoing RFS. This could be due to the nature of adaptation occurring in these populations, underlying gene action, or a result of unstable genetic topographies.
Collapse
Affiliation(s)
- Collin M Lamkey
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE, 68583, USA
- Corteva Agriscience, 19456 Hwy 22, Mankato, MN, 56001, USA
| | - Aaron J Lorenz
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE, 68583, USA.
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
| |
Collapse
|
25
|
de Jong M, van Rensburg AJ, Whiteford S, Yung CJ, Beaumont M, Jiggins C, Bridle J. Rapid evolution of novel biotic interactions in the UK Brown Argus butterfly uses genomic variation from across its geographical range. Mol Ecol 2023; 32:5742-5756. [PMID: 37800849 DOI: 10.1111/mec.17138] [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: 05/16/2022] [Revised: 08/28/2023] [Accepted: 09/07/2023] [Indexed: 10/07/2023]
Abstract
Understanding the rate and extent to which populations can adapt to novel environments at their ecological margins is fundamental to predicting the persistence of biological communities during ongoing and rapid global change. Recent range expansion in response to climate change in the UK butterfly Aricia agestis is associated with the evolution of novel interactions with a larval food plant, and the loss of its ability to use an ancestral host species. Using ddRAD analysis of 61,210 variable SNPs from 261 females from throughout the UK range of this species, we identify genomic regions at multiple chromosomes that are associated with evolutionary responses, and their association with demographic history and ecological variation. Gene flow appears widespread throughout the range, despite the apparently fragmented nature of the habitats used by this species. Patterns of haplotype variation between selected and neutral genomic regions suggest that evolution associated with climate adaptation is polygenic, resulting from the independent spread of alleles throughout the established range of this species, rather than the colonization of pre-adapted genotypes from coastal populations. These data suggest that rapid responses to climate change do not depend on the availability of pre-adapted genotypes. Instead, the evolution of novel forms of biotic interaction in A. agestis has occurred during range expansion, through the assembly of novel genotypes from alleles from multiple localities.
Collapse
Affiliation(s)
- Maaike de Jong
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Alexandra Jansen van Rensburg
- School of Biological Sciences, University of Bristol, Bristol, UK
- Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Samuel Whiteford
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
| | - Carl J Yung
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
| | - Mark Beaumont
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Chris Jiggins
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Jon Bridle
- School of Biological Sciences, University of Bristol, Bristol, UK
- Department of Genetics, Evolution and Environment, University College London, London, UK
| |
Collapse
|
26
|
Salazar-Tortosa DF, Huang YF, Enard D. Assessing the Presence of Recent Adaptation in the Human Genome With Mixture Density Regression. Genome Biol Evol 2023; 15:evad170. [PMID: 37713622 PMCID: PMC10563788 DOI: 10.1093/gbe/evad170] [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: 03/18/2023] [Revised: 08/30/2023] [Accepted: 09/04/2023] [Indexed: 09/17/2023] Open
Abstract
How much genome differences between species reflect neutral or adaptive evolution is a central question in evolutionary genomics. In humans and other mammals, the presence of adaptive versus neutral genomic evolution has proven particularly difficult to quantify. The difficulty notably stems from the highly heterogeneous organization of mammalian genomes at multiple levels (functional sequence density, recombination, etc.) which complicates the interpretation and distinction of adaptive versus neutral evolution signals. In this study, we introduce mixture density regressions (MDRs) for the study of the determinants of recent adaptation in the human genome. MDRs provide a flexible regression model based on multiple Gaussian distributions. We use MDRs to model the association between recent selection signals and multiple genomic factors likely to affect the occurrence/detection of positive selection, if the latter was present in the first place to generate these associations. We find that an MDR model with two Gaussian distributions provides an excellent fit to the genome-wide distribution of a common sweep summary statistic (integrated haplotype score), with one of the two distributions likely enriched in positive selection. We further find several factors associated with signals of recent adaptation, including the recombination rate, the density of regulatory elements in immune cells, GC content, gene expression in immune cells, the density of mammal-wide conserved elements, and the distance to the nearest virus-interacting gene. These results support the presence of strong positive selection in recent human evolution and highlight MDRs as a powerful tool to make sense of signals of recent genomic adaptation.
Collapse
Affiliation(s)
- Diego F Salazar-Tortosa
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, USA
- Department of Ecology, University of Granada, Granada, Spain
| | - Yi-Fei Huang
- Department of Biology, Pennsylvania State University, University Park, State College, Pennsylvania, PA 16801, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, State College, Pennsylvania, PA 16801, USA
| | - David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, USA
| |
Collapse
|
27
|
Höllinger I, Wölfl B, Hermisson J. A theory of oligogenic adaptation of a quantitative trait. Genetics 2023; 225:iyad139. [PMID: 37550847 PMCID: PMC10550320 DOI: 10.1093/genetics/iyad139] [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: 04/20/2023] [Revised: 04/20/2023] [Accepted: 07/13/2023] [Indexed: 08/09/2023] Open
Abstract
Rapid phenotypic adaptation is widespread in nature, but the underlying genetic dynamics remain controversial. Whereas population genetics envisages sequential beneficial substitutions, quantitative genetics assumes a collective response through subtle shifts in allele frequencies. This dichotomy of a monogenic and a highly polygenic view of adaptation raises the question of a middle ground, as well as the factors controlling the transition. Here, we consider an additive quantitative trait with equal locus effects under Gaussian stabilizing selection that adapts to a new trait optimum after an environmental change. We present an analytical framework based on Yule branching processes to describe how phenotypic adaptation is achieved by collective changes in allele frequencies at the underlying loci. In particular, we derive an approximation for the joint allele-frequency distribution conditioned on the trait mean as a comprehensive descriptor of the adaptive architecture. Depending on the model parameters, this architecture reproduces the well-known patterns of sequential, monogenic sweeps, or of subtle, polygenic frequency shifts. Between these endpoints, we observe oligogenic architecture types that exhibit characteristic patterns of partial sweeps. We find that a single compound parameter, the population-scaled background mutation rate Θbg, is the most important predictor of the type of adaptation, while selection strength, the number of loci in the genetic basis, and linkage only play a minor role.
Collapse
Affiliation(s)
- Ilse Höllinger
- Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
| | - Benjamin Wölfl
- Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
- Vienna Graduate School of Population Genetics, University of Vienna and Veterinary Medical University of Vienna, Vienna, Austria
- Vienna Doctoral School of Ecology and Evolution, University of Vienna, Vienna, Austria
| | - Joachim Hermisson
- Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
| |
Collapse
|
28
|
Amin MR, Hasan M, Arnab SP, DeGiorgio M. Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data. Mol Biol Evol 2023; 40:msad216. [PMID: 37772983 PMCID: PMC10581699 DOI: 10.1093/molbev/msad216] [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: 03/02/2023] [Revised: 08/10/2023] [Accepted: 09/14/2023] [Indexed: 09/30/2023] Open
Abstract
Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under nonconvex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data although preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx, which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.
Collapse
Affiliation(s)
- Md Ruhul Amin
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Mahmudul Hasan
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Sandipan Paul Arnab
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Michael DeGiorgio
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| |
Collapse
|
29
|
Lin Y, Darolti I, van der Bijl W, Morris J, Mank JE. Extensive variation in germline de novo mutations in Poecilia reticulata. Genome Res 2023; 33:1317-1324. [PMID: 37442578 PMCID: PMC10547258 DOI: 10.1101/gr.277936.123] [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: 03/30/2023] [Accepted: 07/07/2023] [Indexed: 07/15/2023]
Abstract
The rate of germline mutation is fundamental to evolutionary processes, as it generates the variation upon which selection acts. The guppy, Poecilia reticulata, is a model of rapid adaptation, however the relative contribution of standing genetic variation versus de novo mutation (DNM) to evolution in this species remains unclear. Here, we use pedigree-based approaches to quantify and characterize germline DNMs in three large guppy families. Our results suggest germline mutation rate in the guppy varies substantially across individuals and families. Most DNMs are shared across multiple siblings, suggesting they arose during early embryonic development. DNMs are randomly distributed throughout the genome, and male-biased mutation rate is low, as would be expected from the short guppy generation time. Overall, our study shows remarkable variation in germline mutation rate and provides insights into rapid evolution of guppies.
Collapse
Affiliation(s)
- Yuying Lin
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada;
| | - Iulia Darolti
- Department of Ecology and Evolution, University of Lausanne, CH-1015 Lausanne, Switzerland
| | - Wouter van der Bijl
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Jake Morris
- School of Biological Science, University of Bristol, Bristol BS8 1TQ, United Kingdom
| | - Judith E Mank
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| |
Collapse
|
30
|
Tobler R, Souilmi Y, Huber CD, Bean N, Turney CSM, Grey ST, Cooper A. The role of genetic selection and climatic factors in the dispersal of anatomically modern humans out of Africa. Proc Natl Acad Sci U S A 2023; 120:e2213061120. [PMID: 37220274 PMCID: PMC10235988 DOI: 10.1073/pnas.2213061120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 03/14/2023] [Indexed: 05/25/2023] Open
Abstract
The evolutionarily recent dispersal of anatomically modern humans (AMH) out of Africa (OoA) and across Eurasia provides a unique opportunity to examine the impacts of genetic selection as humans adapted to multiple new environments. Analysis of ancient Eurasian genomic datasets (~1,000 to 45,000 y old) reveals signatures of strong selection, including at least 57 hard sweeps after the initial AMH movement OoA, which have been obscured in modern populations by extensive admixture during the Holocene. The spatiotemporal patterns of these hard sweeps provide a means to reconstruct early AMH population dispersals OoA. We identify a previously unsuspected extended period of genetic adaptation lasting ~30,000 y, potentially in the Arabian Peninsula area, prior to a major Neandertal genetic introgression and subsequent rapid dispersal across Eurasia as far as Australia. Consistent functional targets of selection initiated during this period, which we term the Arabian Standstill, include loci involved in the regulation of fat storage, neural development, skin physiology, and cilia function. Similar adaptive signatures are also evident in introgressed archaic hominin loci and modern Arctic human groups, and we suggest that this signal represents selection for cold adaptation. Surprisingly, many of the candidate selected loci across these groups appear to directly interact and coordinately regulate biological processes, with a number associated with major modern diseases including the ciliopathies, metabolic syndrome, and neurodegenerative disorders. This expands the potential for ancestral human adaptation to directly impact modern diseases, providing a platform for evolutionary medicine.
Collapse
Affiliation(s)
- Raymond Tobler
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
| | - Yassine Souilmi
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
- Environment Institute, The University of Adelaide, Adelaide, SA5005, Australia
| | - Christian D. Huber
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
| | - Nigel Bean
- Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, SA5005, Australia
- School of Mathematical Sciences, The University of Adelaide, Adelaide, SA5005, Australia
| | - Chris S. M. Turney
- Division of Research, University of Technology Sydney, Ultimo, NSW2007, Australia
| | - Shane T. Grey
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, NSW2052, Australia
- Transplantation Immunology Group, Translation Science Pillar, Garvan Institute of Medical Research, Darlinghurst, NSW2010, Australia
| | - Alan Cooper
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
- Blue Sky Genetics, Ashton, SA5137, Australia
| |
Collapse
|
31
|
Key FM, Khadka VD, Romo-González C, Blake KJ, Deng L, Lynn TC, Lee JC, Chiu IM, García-Romero MT, Lieberman TD. On-person adaptive evolution of Staphylococcus aureus during treatment for atopic dermatitis. Cell Host Microbe 2023; 31:593-603.e7. [PMID: 37054679 PMCID: PMC10263175 DOI: 10.1016/j.chom.2023.03.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 02/14/2023] [Accepted: 03/10/2023] [Indexed: 04/15/2023]
Abstract
The opportunistic pathogen Staphylococcus aureus frequently colonizes the inflamed skin of people with atopic dermatitis (AD) and worsens disease severity by promoting skin damage. Here, we show, by longitudinally tracking 23 children treated for AD, that S. aureus adapts via de novo mutations during colonization. Each patient's S. aureus population is dominated by a single lineage, with infrequent invasion by distant lineages. Mutations emerge within each lineage at rates similar to those of S. aureus in other contexts. Some variants spread across the body within months, with signatures of adaptive evolution. Most strikingly, mutations in capsule synthesis gene capD underwent parallel evolution in one patient and across-body sweeps in two patients. We confirm that capD negativity is more common in AD than in other contexts, via reanalysis of S. aureus genomes from 276 people. Together, these findings highlight the importance of the mutation level when dissecting the role of microbes in complex disease.
Collapse
Affiliation(s)
- Felix M Key
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Veda D Khadka
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Carolina Romo-González
- Experimental Bacteriology Laboratory, National Institute for Pediatrics, Mexico City, Mexico
| | - Kimbria J Blake
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Liwen Deng
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Tucker C Lynn
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jean C Lee
- Division of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Isaac M Chiu
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | | | - Tami D Lieberman
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute, Massachusetts Institute of Technology, Cambridge, MA, USA; Ragon Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.
| |
Collapse
|
32
|
Fair T, Pollen AA. Genetic architecture of human brain evolution. Curr Opin Neurobiol 2023; 80:102710. [PMID: 37003107 DOI: 10.1016/j.conb.2023.102710] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 02/20/2023] [Accepted: 02/26/2023] [Indexed: 04/03/2023]
Abstract
Comparative studies of hominids have long sought to identify mutational events that shaped the evolution of the human nervous system. However, functional genetic differences are outnumbered by millions of nearly neutral mutations, and the developmental mechanisms underlying human nervous system specializations are difficult to model and incompletely understood. Candidate-gene studies have attempted to map select human-specific genetic differences to neurodevelopmental functions, but it remains unclear how to contextualize the relative effects of genes that are investigated independently. Considering these limitations, we discuss scalable approaches for probing the functional contributions of human-specific genetic differences. We propose that a systems-level view will enable a more quantitative and integrative understanding of the genetic, molecular and cellular underpinnings of human nervous system evolution.
Collapse
Affiliation(s)
- Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA. https://twitter.com/@TylerFair_
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
33
|
Lotterhos KE. The paradox of adaptive trait clines with nonclinal patterns in the underlying genes. Proc Natl Acad Sci U S A 2023; 120:e2220313120. [PMID: 36917658 PMCID: PMC10041142 DOI: 10.1073/pnas.2220313120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 02/03/2023] [Indexed: 03/16/2023] Open
Abstract
Multivariate climate change presents an urgent need to understand how species adapt to complex environments. Population genetic theory predicts that loci under selection will form monotonic allele frequency clines with their selective environment, which has led to the wide use of genotype-environment associations (GEAs). This study used a set of simulations to elucidate the conditions under which allele frequency clines are more or less likely to evolve as multiple quantitative traits adapt to multivariate environments. Phenotypic clines evolved with nonmonotonic (i.e., nonclinal) patterns in allele frequencies under conditions that promoted unique combinations of mutations to achieve the multivariate optimum in different parts of the landscape. Such conditions resulted from interactions among landscape, demography, pleiotropy, and genetic architecture. GEA methods failed to accurately infer the genetic basis of adaptation under a range of scenarios due to first principles (clinal patterns did not evolve) or statistical issues (clinal patterns evolved but were not detected due to overcorrection for structure). Despite the limitations of GEAs, this study shows that a back-transformation of multivariate ordination can accurately predict individual multivariate traits from genotype and environmental data regardless of whether inference from GEAs was accurate. In addition, frameworks are introduced that can be used by empiricists to quantify the importance of clinal alleles in adaptation. This research highlights that multivariate trait prediction from genotype and environmental data can lead to accurate inference regardless of whether the underlying loci display clinal or nonmonotonic patterns.
Collapse
Affiliation(s)
- Katie E. Lotterhos
- Department of Marine and Environmental Sciences, Northeastern University Marine Science Center, Nahant, MA01908
| |
Collapse
|
34
|
Yu S, Liu Z, Li M, Zhou D, Hua P, Cheng H, Fan W, Xu Y, Liu D, Liang S, Zhang Y, Xie M, Tang J, Jiang Y, Hou S, Zhou Z. Resequencing of a Pekin duck breeding population provides insights into the genomic response to short-term artificial selection. Gigascience 2023; 12:giad016. [PMID: 36971291 PMCID: PMC10041536 DOI: 10.1093/gigascience/giad016] [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: 09/29/2022] [Revised: 02/04/2023] [Accepted: 02/27/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Short-term, intense artificial selection drives fast phenotypic changes in domestic animals and leaves imprints on their genomes. However, the genetic basis of this selection response is poorly understood. To better address this, we employed the Pekin duck Z2 pure line, in which the breast muscle weight was increased nearly 3-fold after 10 generations of breeding. We denovo assembled a high-quality reference genome of a female Pekin duck of this line (GCA_003850225.1) and identified 8.60 million genetic variants in 119 individuals among 10 generations of the breeding population. RESULTS We identified 53 selected regions between the first and tenth generations, and 93.8% of the identified variations were enriched in regulatory and noncoding regions. Integrating the selection signatures and genome-wide association approach, we found that 2 regions covering 0.36 Mb containing UTP25 and FBRSL1 were most likely to contribute to breast muscle weight improvement. The major allele frequencies of these 2 loci increased gradually with each generation following the same trend. Additionally, we found that a copy number variation region containing the entire EXOC4 gene could explain 1.9% of the variance in breast muscle weight, indicating that the nervous system may play a role in economic trait improvement. CONCLUSIONS Our study not only provides insights into genomic dynamics under intense artificial selection but also provides resources for genomics-enabled improvements in duck breeding.
Collapse
Affiliation(s)
- Simeng Yu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Zihua Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Dongke Zhou
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Ping Hua
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Hong Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Wenlei Fan
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yaxi Xu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Dapeng Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Suyun Liang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yunsheng Zhang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ming Xie
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Jing Tang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Shuisheng Hou
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Zhengkui Zhou
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| |
Collapse
|
35
|
Small ST, Costantini C, Sagnon N, Guelbeogo MW, Emrich SJ, Kern AD, Fontaine MC, Besansky NJ. Standing genetic variation and chromosome differences drove rapid ecotype formation in a major malaria mosquito. Proc Natl Acad Sci U S A 2023; 120:e2219835120. [PMID: 36881629 PMCID: PMC10089221 DOI: 10.1073/pnas.2219835120] [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: 11/26/2022] [Accepted: 02/09/2023] [Indexed: 03/08/2023] Open
Abstract
Species distributed across heterogeneous environments often evolve locally adapted ecotypes, but understanding of the genetic mechanisms involved in their formation and maintenance in the face of gene flow is incomplete. In Burkina Faso, the major African malaria mosquito Anopheles funestus comprises two strictly sympatric and morphologically indistinguishable yet karyotypically differentiated forms reported to differ in ecology and behavior. However, knowledge of the genetic basis and environmental determinants of An. funestus diversification was impeded by lack of modern genomic resources. Here, we applied deep whole-genome sequencing and analysis to test the hypothesis that these two forms are ecotypes differentially adapted to breeding in natural swamps versus irrigated rice fields. We demonstrate genome-wide differentiation despite extensive microsympatry, synchronicity, and ongoing hybridization. Demographic inference supports a split only ~1,300 y ago, closely following the massive expansion of domesticated African rice cultivation ~1,850 y ago. Regions of highest divergence, concentrated in chromosomal inversions, were under selection during lineage splitting, consistent with local adaptation. The origin of nearly all variations implicated in adaptation, including chromosomal inversions, substantially predates the ecotype split, suggesting that rapid adaptation was fueled mainly by standing genetic variation. Sharp inversion frequency differences likely facilitated adaptive divergence between ecotypes by suppressing recombination between opposing chromosomal orientations of the two ecotypes, while permitting free recombination within the structurally monomorphic rice ecotype. Our results align with growing evidence from diverse taxa that rapid ecological diversification can arise from evolutionarily old structural genetic variants that modify genetic recombination.
Collapse
Affiliation(s)
- Scott T. Small
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN46556
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN46556
- Institute for Ecology and Evolution, University of Oregon, Eugene, OR97403
| | - Carlo Costantini
- Centre National de Recherche et Formation sur le Paludisme, Ouagadougou01 BP 2208, Burkina Faso
- Infectious Diseases and Vectors: Ecology, Genetics, Evolution and Control (MIVEGEC), Université de Montpellier, CNRS 5290, Institute of Research for Development (IRD) 224, F-34394Montpellier, France
| | - N’Fale Sagnon
- Centre National de Recherche et Formation sur le Paludisme, Ouagadougou01 BP 2208, Burkina Faso
| | - Moussa W. Guelbeogo
- Centre National de Recherche et Formation sur le Paludisme, Ouagadougou01 BP 2208, Burkina Faso
| | - Scott J. Emrich
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN46556
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN46556
| | - Andrew D. Kern
- Institute for Ecology and Evolution, University of Oregon, Eugene, OR97403
| | - Michael C. Fontaine
- Infectious Diseases and Vectors: Ecology, Genetics, Evolution and Control (MIVEGEC), Université de Montpellier, CNRS 5290, Institute of Research for Development (IRD) 224, F-34394Montpellier, France
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, 9747 AGGroningen, The Netherlands
| | - Nora J. Besansky
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN46556
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN46556
| |
Collapse
|
36
|
Torres E, García-Fernández A, Iñigo D, Lara-Romero C, Morente-López J, Prieto-Benítez S, Rubio Teso ML, Iriondo JM. Facilitated Adaptation as A Conservation Tool in the Present Climate Change Context: A Methodological Guide. PLANTS (BASEL, SWITZERLAND) 2023; 12:1258. [PMID: 36986946 PMCID: PMC10053585 DOI: 10.3390/plants12061258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/04/2023] [Accepted: 03/07/2023] [Indexed: 06/18/2023]
Abstract
Climate change poses a novel threat to biodiversity that urgently requires the development of adequate conservation strategies. Living organisms respond to environmental change by migrating to locations where their ecological niche is preserved or by adapting to the new environment. While the first response has been used to develop, discuss and implement the strategy of assisted migration, facilitated adaptation is only beginning to be considered as a potential approach. Here, we present a review of the conceptual framework for facilitated adaptation, integrating advances and methodologies from different disciplines. Briefly, facilitated adaptation involves a population reinforcement that introduces beneficial alleles to enable the evolutionary adaptation of a focal population to pressing environmental conditions. To this purpose, we propose two methodological approaches. The first one (called pre-existing adaptation approach) is based on using pre-adapted genotypes existing in the focal population, in other populations, or even in closely related species. The second approach (called de novo adaptation approach) aims to generate new pre-adapted genotypes from the diversity present in the species through artificial selection. For each approach, we present a stage-by-stage procedure, with some techniques that can be used for its implementation. The associated risks and difficulties of each approach are also discussed.
Collapse
Affiliation(s)
- Elena Torres
- Departamento de Biotecnología-Biología Vegetal, Universidad Politécnica de Madrid, 28040 Madrid, Spain
| | - Alfredo García-Fernández
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| | - Diana Iñigo
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| | - Carlos Lara-Romero
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| | - Javier Morente-López
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
- Grupo de Investigación de Ecología y Evolución en Islas, Instituto de Productos Naturales y Agrobiología (IPNA-CSIC), 38206 Tenerife, Spain
| | - Samuel Prieto-Benítez
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
- Ecotoxicology of Air Pollution, Environmental Department, CIEMAT, 28040 Madrid, Spain
| | - María Luisa Rubio Teso
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| | - José M. Iriondo
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| |
Collapse
|
37
|
Johnson SE, Tittes S, Franks SJ. Rapid, nonparallel genomic evolution of Brassica rapa (field mustard) under experimental drought. J Evol Biol 2023; 36:550-562. [PMID: 36721268 DOI: 10.1111/jeb.14152] [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: 04/20/2022] [Revised: 09/22/2022] [Accepted: 12/08/2022] [Indexed: 02/02/2023]
Abstract
While we know that climate change can potentially cause rapid phenotypic evolution, our understanding of the genetic basis and degree of genetic parallelism of rapid evolutionary responses to climate change is limited. In this study, we combined the resurrection approach with an evolve-and-resequence design to examine genome-wide evolutionary changes following drought. We exposed genetically similar replicate populations of the annual plant Brassica rapa derived from a field population in southern California to four generations of experimental drought or watered conditions in a greenhouse. Genome-wide sequencing of ancestral and descendant population pools identified hundreds of SNPs that showed evidence of rapidly evolving in response to drought. Several of these were in stress response genes, and two were identified in a prior study of drought response in this species. However, almost all genetic changes were unique among experimental populations, indicating that the evolutionary changes were largely nonparallel, despite the fact that genetically similar replicates of the same founder population had experienced controlled and consistent selection regimes. This nonparallelism of evolution at the genetic level is potentially because of polygenetic adaptation allowing for multiple different genetic routes to similar phenotypic outcomes. Our findings help to elucidate the relationship between rapid phenotypic and genomic evolution and shed light on the degree of parallelism and predictability of genomic evolution to environmental change.
Collapse
Affiliation(s)
- Stephen E Johnson
- Department of Biological Sciences and Louis Calder Center, Fordham University, Bronx, New York, USA
| | - Silas Tittes
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA
| | - Steven J Franks
- Department of Biological Sciences and Louis Calder Center, Fordham University, Bronx, New York, USA
| |
Collapse
|
38
|
Mahmoud M, Tost M, Ha NT, Simianer H, Beissinger T. Ghat: an R package for identifying adaptive polygenic traits. G3 (BETHESDA, MD.) 2023; 13:jkac319. [PMID: 36454082 PMCID: PMC9911052 DOI: 10.1093/g3journal/jkac319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 01/21/2022] [Accepted: 11/14/2022] [Indexed: 12/03/2022]
Abstract
Identifying selection on polygenic complex traits in crops and livestock is important for understanding evolution and helps prioritize important characteristics for breeding. Quantitative trait loci (QTL) that contribute to polygenic trait variation often exhibit small or infinitesimal effects. This hinders the ability to detect QTL-controlling polygenic traits because enormously high statistical power is needed for their detection. Recently, we circumvented this challenge by introducing a method to identify selection on complex traits by evaluating the relationship between genome-wide changes in allele frequency and estimates of effect size. The approach involves calculating a composite statistic across all markers that capture this relationship, followed by implementing a linkage disequilibrium-aware permutation test to evaluate if the observed pattern differs from that expected due to drift during evolution and population stratification. In this manuscript, we describe "Ghat," an R package developed to implement this method to test for selection on polygenic traits. We demonstrate the package by applying it to test for polygenic selection on 15 published European wheat traits including yield, biomass, quality, morphological characteristics, and disease resistance traits. Moreover, we applied Ghat to different simulated populations with different breeding histories and genetic architectures. The results highlight the power of Ghat to identify selection on complex traits. The Ghat package is accessible on CRAN, the Comprehensive R Archival Network, and on GitHub.
Collapse
Affiliation(s)
- Medhat Mahmoud
- Department of Crop Science, University of Goettingen, Goettingen 37075, Germany
- Center for Integrated Breeding Research, University of Goettingen, Goettingen 37075, Germany
| | - Mila Tost
- Department of Crop Science, University of Goettingen, Goettingen 37075, Germany
- Center for Integrated Breeding Research, University of Goettingen, Goettingen 37075, Germany
| | - Ngoc-Thuy Ha
- Department of Animal Sciences, University of Goettingen, Goettingen 37075, Germany
| | - Henner Simianer
- Center for Integrated Breeding Research, University of Goettingen, Goettingen 37075, Germany
- Department of Animal Sciences, University of Goettingen, Goettingen 37075, Germany
| | - Timothy Beissinger
- Department of Crop Science, University of Goettingen, Goettingen 37075, Germany
- Center for Integrated Breeding Research, University of Goettingen, Goettingen 37075, Germany
| |
Collapse
|
39
|
Rougemont Q, Xuereb A, Dallaire X, Moore JS, Normandeau E, Perreault-Payette A, Bougas B, Rondeau EB, Withler RE, Van Doornik DM, Crane PA, Naish KA, Garza JC, Beacham TD, Koop BF, Bernatchez L. Long-distance migration is a major factor driving local adaptation at continental scale in Coho salmon. Mol Ecol 2023; 32:542-559. [PMID: 35000273 DOI: 10.1111/mec.16339] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 11/19/2021] [Accepted: 12/23/2021] [Indexed: 01/25/2023]
Abstract
Inferring the genomic basis of local adaptation is a long-standing goal of evolutionary biology. Beyond its fundamental evolutionary implications, such knowledge can guide conservation decisions for populations of conservation and management concern. Here, we investigated the genomic basis of local adaptation in the Coho salmon (Oncorhynchus kisutch) across its entire North American range. We hypothesized that extensive spatial variation in environmental conditions and the species' homing behaviour may promote the establishment of local adaptation. We genotyped 7829 individuals representing 217 sampling locations at more than 100,000 high-quality RADseq loci to investigate how recombination might affect the detection of loci putatively under selection and took advantage of the precise description of the demographic history of the species from our previous work to draw accurate population genomic inferences about local adaptation. The results indicated that genetic differentiation scans and genetic-environment association analyses were both significantly affected by variation in recombination rate as low recombination regions displayed an increased number of outliers. By taking these confounding factors into consideration, we revealed that migration distance was the primary selective factor driving local adaptation and partial parallel divergence among distant populations. Moreover, we identified several candidate single nucleotide polymorphisms associated with long-distance migration and altitude including a gene known to be involved in adaptation to altitude in other species. The evolutionary implications of our findings are discussed along with conservation applications.
Collapse
Affiliation(s)
- Quentin Rougemont
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada.,CEFE, Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, CNRS, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier, Montpellier, France
| | - Amanda Xuereb
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada
| | - Xavier Dallaire
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada
| | - Jean-Sébastien Moore
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada
| | - Eric Normandeau
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada
| | - Alysse Perreault-Payette
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada
| | - Bérénice Bougas
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada
| | - Eric B Rondeau
- Department of Fisheries and Ocean, Pacific Biological Station, Nanaimo, British Columbia, Canada.,Department of Biology, University of Victoria, Victoria, British Columbia, Canada
| | - Ruth E Withler
- Department of Fisheries and Ocean, Pacific Biological Station, Nanaimo, British Columbia, Canada
| | - Donald M Van Doornik
- National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Northwest Fisheries Science Center, Manchester Research Station, Port Orchard, Washington, USA
| | - Penelope A Crane
- Conservation Genetics Laboratory, U.S. Fish and Wildlife Service, Anchorage, Alaska, USA
| | - Kerry A Naish
- School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA
| | - John Carlos Garza
- Department of Ocean Sciences and Institute of Marine Sciences, University of California Santa Cruz, Santa Cruz, California, USA
| | - Terry D Beacham
- Department of Fisheries and Ocean, Pacific Biological Station, Nanaimo, British Columbia, Canada
| | - Ben F Koop
- Department of Biology, University of Victoria, Victoria, British Columbia, Canada
| | - Louis Bernatchez
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada
| |
Collapse
|
40
|
Devi A, Jain K. Polygenic adaptation dynamics in large, finite populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.525607. [PMID: 36747829 PMCID: PMC9901025 DOI: 10.1101/2023.01.25.525607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Although many phenotypic traits are determined by a large number of genetic variants, how a polygenic trait adapts in response to a change in the environment is not completely understood. In the framework of diffusion theory, we study the steady state and the adaptation dynamics of a large but finite population evolving under stabilizing selection and symmetric mutations when selection and mutation are moderately large. We find that in the stationary state, the allele frequency distribution at a locus is unimodal if its effect size is below a threshold effect and bimodal otherwise; these results are the stochastic analog of the deterministic ones where the stable allele frequency becomes bistable when the effect size exceeds a threshold. It is known that following a sudden shift in the phenotypic optimum, in an infinitely large population, selective sweeps at a large-effect locus are prevented and adaptation proceeds exclusively via subtle changes in the allele frequency; in contrast, we find that the chance of sweep is substantially enhanced in large, finite populations and the allele frequency at a large-effect locus can reach a high frequency at short times even for small shifts in the phenotypic optimum.
Collapse
Affiliation(s)
- Archana Devi
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA
| | - Kavita Jain
- Theoretical Sciences Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore 560064, India
| |
Collapse
|
41
|
Aqil A, Speidel L, Pavlidis P, Gokcumen O. Balancing selection on genomic deletion polymorphisms in humans. eLife 2023; 12:79111. [PMID: 36625544 PMCID: PMC9943071 DOI: 10.7554/elife.79111] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 01/05/2023] [Indexed: 01/11/2023] Open
Abstract
A key question in biology is why genomic variation persists in a population for extended periods. Recent studies have identified examples of genomic deletions that have remained polymorphic in the human lineage for hundreds of millennia, ostensibly owing to balancing selection. Nevertheless, genome-wide investigation of ancient and possibly adaptive deletions remains an imperative exercise. Here, we demonstrate an excess of polymorphisms in present-day humans that predate the modern human-Neanderthal split (ancient polymorphisms), which cannot be explained solely by selectively neutral scenarios. We analyze the adaptive mechanisms that underlie this excess in deletion polymorphisms. Using a previously published measure of balancing selection, we show that this excess of ancient deletions is largely owing to balancing selection. Based on the absence of signatures of overdominance, we conclude that it is a rare mode of balancing selection among ancient deletions. Instead, more complex scenarios involving spatially and temporally variable selective pressures are likely more common mechanisms. Our results suggest that balancing selection resulted in ancient deletions harboring disproportionately more exonic variants with GWAS (genome-wide association studies) associations. We further found that ancient deletions are significantly enriched for traits related to metabolism and immunity. As a by-product of our analysis, we show that deletions are, on average, more deleterious than single nucleotide variants. We can now argue that not only is a vast majority of common variants shared among human populations, but a considerable portion of biologically relevant variants has been segregating among our ancestors for hundreds of thousands, if not millions, of years.
Collapse
Affiliation(s)
- Alber Aqil
- Department of Biological Sciences, University at BuffaloBuffaloUnited States
| | - Leo Speidel
- University College London, Genetics InstituteLondonUnited Kingdom
- The Francis Crick InstituteLondonUnited Kingdom
| | - Pavlos Pavlidis
- Institute of Computer Science (ICS), Foundation of Research and Technology-HellasHeraklionGreece
| | - Omer Gokcumen
- Department of Biological Sciences, University at BuffaloBuffaloUnited States
| |
Collapse
|
42
|
Lea AJ, Garcia A, Arevalo J, Ayroles JF, Buetow K, Cole SW, Eid Rodriguez D, Gutierrez M, Highland HM, Hooper PL, Justice A, Kraft T, North KE, Stieglitz J, Kaplan H, Trumble BC, Gurven MD. Natural selection of immune and metabolic genes associated with health in two lowland Bolivian populations. Proc Natl Acad Sci U S A 2023; 120:e2207544120. [PMID: 36574663 PMCID: PMC9910614 DOI: 10.1073/pnas.2207544120] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 09/21/2022] [Indexed: 12/28/2022] Open
Abstract
A growing body of work has addressed human adaptations to diverse environments using genomic data, but few studies have connected putatively selected alleles to phenotypes, much less among underrepresented populations such as Amerindians. Studies of natural selection and genotype-phenotype relationships in underrepresented populations hold potential to uncover previously undescribed loci underlying evolutionarily and biomedically relevant traits. Here, we worked with the Tsimane and the Moseten, two Amerindian populations inhabiting the Bolivian lowlands. We focused most intensively on the Tsimane, because long-term anthropological work with this group has shown that they have a high burden of both macro and microparasites, as well as minimal cardiometabolic disease or dementia. We therefore generated genome-wide genotype data for Tsimane individuals to study natural selection, and paired this with blood mRNA-seq as well as cardiometabolic and immune biomarker data generated from a larger sample that included both populations. In the Tsimane, we identified 21 regions that are candidates for selective sweeps, as well as 5 immune traits that show evidence for polygenic selection (e.g., C-reactive protein levels and the response to coronaviruses). Genes overlapping candidate regions were strongly enriched for known involvement in immune-related traits, such as abundance of lymphocytes and eosinophils. Importantly, we were also able to draw on extensive phenotype information for the Tsimane and Moseten and link five regions (containing PSD4, MUC21 and MUC22, TOX2, ANXA6, and ABCA1) with biomarkers of immune and metabolic function. Together, our work highlights the utility of pairing evolutionary analyses with anthropological and biomedical data to gain insight into the genetic basis of health-related traits.
Collapse
Affiliation(s)
- Amanda J. Lea
- Department of Biological Sciences, Vanderbilt University, Nashville, TN37235
| | - Angela Garcia
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ85287
| | - Jesusa Arevalo
- Department of Medicine, University of California, Los Angeles, CA90095
| | - Julien F. Ayroles
- Department of Ecology and Evolution, Princeton University, Princeton, NJ08544
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ08544
| | - Kenneth Buetow
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ85287
- School of Life Sciences, Arizona State University, Tempe, AZ85287
| | - Steve W. Cole
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA90095
- Department of Medicine, University of California, Los Angeles, CA90095
| | | | | | - Heather M. Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC27516
| | - Paul L. Hooper
- Economic Science Institute, Chapman University, Orange, CA92866
| | | | - Thomas Kraft
- Department of Anthropology, University of Utah, Salt Lake City, UT84112
| | - Kari E. North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC27516
| | | | - Hillard Kaplan
- Institute for Economics and Society, Chapman University, Orange, CA92866
| | - Benjamin C. Trumble
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ85287
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ85287
| | - Michael D. Gurven
- Department of Anthropology, University of California, Santa Barbara, CA93106
| |
Collapse
|
43
|
Parvizi E, Dhami MK, Yan J, McGaughran A. Population genomic insights into invasion success in a polyphagous agricultural pest, Halyomorpha halys. Mol Ecol 2023; 32:138-151. [PMID: 36261398 PMCID: PMC10099481 DOI: 10.1111/mec.16740] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 10/13/2022] [Accepted: 10/17/2022] [Indexed: 01/07/2023]
Abstract
Invasive species are increasingly threatening ecosystems and agriculture by rapidly expanding their range and adapting to environmental and human-imposed selective pressures. The genomic mechanisms that underlie such rapid changes remain unclear, especially for agriculturally important pests. Here, we used genome-wide polymorphisms derived from native, invasive, and intercepted samples and populations of the brown marmorated stink bug (BMSB), Halyomorpha halys, to gain insights into population genomics processes that have promoted the successful global invasion of this polyphagous pest. Our analysis demonstrated that BMSB exhibits spatial structure but admixture rates are high among introduced populations, resulting in similar levels of genomic diversity across native and introduced populations. These spatial genomic patterns suggest a complex invasion scenario, potentially with multiple bridgehead events, posing a challenge for accurately assigning BMSB incursions to their source using reduced-representation genomic data. By associating allele frequencies with the invasion status of BMSB populations, we found significantly differentiated single nucleotide polymorphisms (SNPs) located in close proximity to genes for insecticide resistance and olfaction. Comparing variations in allele frequencies among populations for outlier SNPs suggests that BMSB invasion success has probably evolved from standing genetic variation. In addition to being a major nuisance of households, BMSB has caused significant economic losses to agriculture in recent years and continues to expand its range. Despite no record of BMSB insecticide resistance to date, our results show high capacity for potential evolution of such traits, highlighting the need for future sustainable and targeted management strategies.
Collapse
Affiliation(s)
- Elahe Parvizi
- Te Aka Mātuatua/School of Science, University of Waikato, Hamilton, New Zealand
| | - Manpreet K Dhami
- Biocontrol and Molecular Ecology, Manaaki Whenua Landcare Research, Lincoln, New Zealand
| | - Juncong Yan
- Plant Health and Environment Laboratory, Ministry for Primary Industries, Auckland, New Zealand
| | - Angela McGaughran
- Te Aka Mātuatua/School of Science, University of Waikato, Hamilton, New Zealand
| |
Collapse
|
44
|
Abraham A, Labella AL, Benton ML, Rokas A, Capra JA. GSEL: a fast, flexible python package for detecting signatures of diverse evolutionary forces on genomic regions. Bioinformatics 2023; 39:btad037. [PMID: 36655767 PMCID: PMC9879724 DOI: 10.1093/bioinformatics/btad037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 11/17/2022] [Accepted: 01/18/2023] [Indexed: 01/20/2023] Open
Abstract
SUMMARY GSEL is a computational framework for calculating the enrichment of signatures of diverse evolutionary forces in a set of genomic regions. GSEL can flexibly integrate any sequence-based evolutionary metric and analyze sets of human genomic regions identified by genome-wide assays (e.g. GWAS, eQTL, *-seq). The core of GSEL's approach is the generation of empirical null distributions tailored to the allele frequency and linkage disequilibrium structure of the regions of interest. We illustrate the application of GSEL to variants identified from a GWAS of body mass index, a highly polygenic trait. AVAILABILITY AND IMPLEMENTATION GSEL is implemented as a fast, flexible and user-friendly python package. It is available with demonstration data at https://github.com/abraham-abin13/gsel_vec. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Abin Abraham
- Division of General Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Abigail L Labella
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37232, USA
- Department of Bioinformatics and Genomics, University of North Carolina, Charlotte, NC 28223, USA
- North Carolina Research Center, Kannapolis, NC 28081, USA
| | | | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37232, USA
- Department of Computer Science, Baylor University, Waco, TX 76706, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37232, USA
| | - John A Capra
- Department of Epidemiology and Biostatistics, Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94143, USA
| |
Collapse
|
45
|
Wortel MT, Agashe D, Bailey SF, Bank C, Bisschop K, Blankers T, Cairns J, Colizzi ES, Cusseddu D, Desai MM, van Dijk B, Egas M, Ellers J, Groot AT, Heckel DG, Johnson ML, Kraaijeveld K, Krug J, Laan L, Lässig M, Lind PA, Meijer J, Noble LM, Okasha S, Rainey PB, Rozen DE, Shitut S, Tans SJ, Tenaillon O, Teotónio H, de Visser JAGM, Visser ME, Vroomans RMA, Werner GDA, Wertheim B, Pennings PS. Towards evolutionary predictions: Current promises and challenges. Evol Appl 2023; 16:3-21. [PMID: 36699126 PMCID: PMC9850016 DOI: 10.1111/eva.13513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 11/11/2022] [Accepted: 11/14/2022] [Indexed: 12/14/2022] Open
Abstract
Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.
Collapse
Affiliation(s)
- Meike T. Wortel
- Swammerdam Institute for Life SciencesUniversity of AmsterdamAmsterdamThe Netherlands
| | - Deepa Agashe
- National Centre for Biological SciencesBangaloreIndia
| | | | - Claudia Bank
- Institute of Ecology and EvolutionUniversity of BernBernSwitzerland
- Swiss Institute of BioinformaticsLausanneSwitzerland
- Gulbenkian Science InstituteOeirasPortugal
| | - Karen Bisschop
- Institute for Biodiversity and Ecosystem DynamicsUniversity of AmsterdamAmsterdamThe Netherlands
- Origins CenterGroningenThe Netherlands
- Laboratory of Aquatic Biology, KU Leuven KulakKortrijkBelgium
| | - Thomas Blankers
- Institute for Biodiversity and Ecosystem DynamicsUniversity of AmsterdamAmsterdamThe Netherlands
- Origins CenterGroningenThe Netherlands
| | | | - Enrico Sandro Colizzi
- Origins CenterGroningenThe Netherlands
- Mathematical InstituteLeiden UniversityLeidenThe Netherlands
| | | | | | - Bram van Dijk
- Max Planck Institute for Evolutionary BiologyPlönGermany
| | - Martijn Egas
- Institute for Biodiversity and Ecosystem DynamicsUniversity of AmsterdamAmsterdamThe Netherlands
| | - Jacintha Ellers
- Department of Ecological ScienceVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Astrid T. Groot
- Institute for Biodiversity and Ecosystem DynamicsUniversity of AmsterdamAmsterdamThe Netherlands
| | | | | | - Ken Kraaijeveld
- Leiden Centre for Applied BioscienceUniversity of Applied Sciences LeidenLeidenThe Netherlands
| | - Joachim Krug
- Institute for Biological PhysicsUniversity of CologneCologneGermany
| | - Liedewij Laan
- Department of Bionanoscience, Kavli Institute of NanoscienceTU DelftDelftThe Netherlands
| | - Michael Lässig
- Institute for Biological PhysicsUniversity of CologneCologneGermany
| | - Peter A. Lind
- Department Molecular BiologyUmeå UniversityUmeåSweden
| | - Jeroen Meijer
- Theoretical Biology and Bioinformatics, Department of BiologyUtrecht UniversityUtrechtThe Netherlands
| | - Luke M. Noble
- Institute de Biologie, École Normale Supérieure, CNRS, InsermParisFrance
| | | | - Paul B. Rainey
- Department of Microbial Population BiologyMax Planck Institute for Evolutionary BiologyPlönGermany
- Laboratoire Biophysique et Évolution, CBI, ESPCI Paris, Université PSL, CNRSParisFrance
| | - Daniel E. Rozen
- Institute of Biology, Leiden UniversityLeidenThe Netherlands
| | - Shraddha Shitut
- Origins CenterGroningenThe Netherlands
- Institute of Biology, Leiden UniversityLeidenThe Netherlands
| | | | | | | | | | - Marcel E. Visser
- Department of Animal EcologyNetherlands Institute of Ecology (NIOO‐KNAW)WageningenThe Netherlands
| | - Renske M. A. Vroomans
- Origins CenterGroningenThe Netherlands
- Informatics InstituteUniversity of AmsterdamAmsterdamThe Netherlands
| | | | - Bregje Wertheim
- Groningen Institute for Evolutionary Life SciencesUniversity of GroningenGroningenThe Netherlands
| | | |
Collapse
|
46
|
García-Pérez R, Ramirez JM, Ripoll-Cladellas A, Chazarra-Gil R, Oliveros W, Soldatkina O, Bosio M, Rognon PJ, Capella-Gutierrez S, Calvo M, Reverter F, Guigó R, Aguet F, Ferreira PG, Ardlie KG, Melé M. The landscape of expression and alternative splicing variation across human traits. CELL GENOMICS 2022; 3:100244. [PMID: 36777183 PMCID: PMC9903719 DOI: 10.1016/j.xgen.2022.100244] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/08/2022] [Accepted: 12/07/2022] [Indexed: 12/31/2022]
Abstract
Understanding the consequences of individual transcriptome variation is fundamental to deciphering human biology and disease. We implement a statistical framework to quantify the contributions of 21 individual traits as drivers of gene expression and alternative splicing variation across 46 human tissues and 781 individuals from the Genotype-Tissue Expression project. We demonstrate that ancestry, sex, age, and BMI make additive and tissue-specific contributions to expression variability, whereas interactions are rare. Variation in splicing is dominated by ancestry and is under genetic control in most tissues, with ribosomal proteins showing a strong enrichment of tissue-shared splicing events. Our analyses reveal a systemic contribution of types 1 and 2 diabetes to tissue transcriptome variation with the strongest signal in the nerve, where histopathology image analysis identifies novel genes related to diabetic neuropathy. Our multi-tissue and multi-trait approach provides an extensive characterization of the main drivers of human transcriptome variation in health and disease.
Collapse
Affiliation(s)
- Raquel García-Pérez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Jose Miguel Ramirez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Aida Ripoll-Cladellas
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Ruben Chazarra-Gil
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Winona Oliveros
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Oleksandra Soldatkina
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Mattia Bosio
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Paul Joris Rognon
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain,Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Catalonia 08005, Spain,Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Barcelona, Catalonia 08034, Spain
| | - Salvador Capella-Gutierrez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Miquel Calvo
- Statistics Section, Faculty of Biology, Universitat de Barcelona (UB), Barcelona, Catalonia 08028, Spain
| | - Ferran Reverter
- Statistics Section, Faculty of Biology, Universitat de Barcelona (UB), Barcelona, Catalonia 08028, Spain
| | - Roderic Guigó
- Bioinformatics and Genomics, Center for Genomic Regulation, Barcelona, Catalonia 08003, Spain
| | | | - Pedro G. Ferreira
- Department of Computer Science, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal,Laboratory of Artificial Intelligence and Decision Support, INESC TEC, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal,Institute of Molecular Pathology and Immunology of the University of Porto, Institute for Research and Innovation in Health (i3s), R. Alfredo Allen 208, 4200-135 Porto, Portugal
| | | | - Marta Melé
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain,Corresponding author
| |
Collapse
|
47
|
Harris M, Garud NR. Enrichment of Hard Sweeps on the X Chromosome in Drosophila melanogaster. Mol Biol Evol 2022; 40:6955808. [PMID: 36546413 PMCID: PMC9825254 DOI: 10.1093/molbev/msac268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 11/11/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
The characteristic properties of the X chromosome, such as male hemizygosity and its unique inheritance pattern, expose it to natural selection in a way that can be different from the autosomes. Here, we investigate the differences in the tempo and mode of adaptation on the X chromosome and autosomes in a population of Drosophila melanogaster. Specifically, we test the hypothesis that due to hemizygosity and a lower effective population size on the X, the relative proportion of hard sweeps, which are expected when adaptation is gradual, compared with soft sweeps, which are expected when adaptation is rapid, is greater on the X than on the autosomes. We quantify the incidence of hard versus soft sweeps in North American D. melanogaster population genomic data with haplotype homozygosity statistics and find an enrichment of the proportion of hard versus soft sweeps on the X chromosome compared with the autosomes, confirming predictions we make from simulations. Understanding these differences may enable a deeper understanding of how important phenotypes arise as well as the impact of fundamental evolutionary parameters on adaptation, such as dominance, sex-specific selection, and sex-biased demography.
Collapse
Affiliation(s)
- Mariana Harris
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA
| | | |
Collapse
|
48
|
Souilmi Y, Tobler R, Johar A, Williams M, Grey ST, Schmidt J, Teixeira JC, Rohrlach A, Tuke J, Johnson O, Gower G, Turney C, Cox M, Cooper A, Huber CD. Admixture has obscured signals of historical hard sweeps in humans. Nat Ecol Evol 2022; 6:2003-2015. [PMID: 36316412 PMCID: PMC9715430 DOI: 10.1038/s41559-022-01914-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 09/16/2022] [Indexed: 11/06/2022]
Abstract
The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied on genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has probably been underappreciated in the evolutionary history of humans and suggest that our current understanding of the tempo and mode of selection in natural populations may be inaccurate.
Collapse
Affiliation(s)
- Yassine Souilmi
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
| | - Raymond Tobler
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Evolution of Cultural Diversity Initiative, Australian National University, Canberra, Australian Capital Territory, Australia.
| | - Angad Johar
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA.
| | - Matthew Williams
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Shane T Grey
- Transplantation Immunology Group, Immunology Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- St Vincent's Clinical School, Faculty of Medicine, UNSW, Darlinghurst, New South Wales, Australia
| | - Joshua Schmidt
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - João C Teixeira
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Adam Rohrlach
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, South Australia, Australia
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany
| | - Jonathan Tuke
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, South Australia, Australia
- School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Olivia Johnson
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Graham Gower
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Chris Turney
- Chronos 14Carbon-Cycle Facility and Earth and Sustainability Science Research Centre, University of New South Wales, Sydney, New South Wales, Australia
| | - Murray Cox
- Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North, New Zealand
| | - Alan Cooper
- South Australian Museum, Adelaide, South Australia, Australia.
- BlueSky Genetics, Ashton, South Australia, Australia.
| | - Christian D Huber
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Department of Biology, Penn State University, University Park, PA, USA.
| |
Collapse
|
49
|
Seascape genomics of common dolphins (Delphinus delphis) reveals adaptive diversity linked to regional and local oceanography. BMC Ecol Evol 2022; 22:88. [PMID: 35818031 PMCID: PMC9275043 DOI: 10.1186/s12862-022-02038-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 06/14/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
High levels of standing genomic variation in wide-ranging marine species may enhance prospects for their long-term persistence. Patterns of connectivity and adaptation in such species are often thought to be influenced by spatial factors, environmental heterogeneity, and oceanographic and geomorphological features. Population-level studies that analytically integrate genome-wide data with environmental information (i.e., seascape genomics) have the potential to inform the spatial distribution of adaptive diversity in wide-ranging marine species, such as many marine mammals. We assessed genotype-environment associations (GEAs) in 214 common dolphins (Delphinus delphis) along > 3000 km of the southern coast of Australia.
Results
We identified 747 candidate adaptive SNPs out of a filtered panel of 17,327 SNPs, and five putatively locally-adapted populations with high levels of standing genomic variation were disclosed along environmentally heterogeneous coasts. Current velocity, sea surface temperature, salinity, and primary productivity were the key environmental variables associated with genomic variation. These environmental variables are in turn related to three main oceanographic phenomena that are likely affecting the dispersal of common dolphins: (1) regional oceanographic circulation, (2) localised and seasonal upwellings, and (3) seasonal on-shelf circulation in protected coastal habitats. Signals of selection at exonic gene regions suggest that adaptive divergence is related to important metabolic traits.
Conclusion
To the best of our knowledge, this represents the first seascape genomics study for common dolphins (genus Delphinus). Information from the associations between populations and their environment can assist population management in forecasting the adaptive capacity of common dolphins to climate change and other anthropogenic impacts.
Collapse
|
50
|
Mouterde M, Daali Y, Rollason V, Čížková M, Mulugeta A, Al Balushi KA, Fakis G, Constantinidis TC, Al-Thihli K, Černá M, Makonnen E, Boukouvala S, Al-Yahyaee S, Yimer G, Černý V, Desmeules J, Poloni ES. Joint Analysis of Phenotypic and Genomic Diversity Sheds Light on the Evolution of Xenobiotic Metabolism in Humans. Genome Biol Evol 2022; 14:6852765. [PMID: 36445690 PMCID: PMC9750130 DOI: 10.1093/gbe/evac167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 11/03/2022] [Accepted: 11/22/2022] [Indexed: 11/30/2022] Open
Abstract
Variation in genes involved in the absorption, distribution, metabolism, and excretion of drugs (ADME) can influence individual response to a therapeutic treatment. The study of ADME genetic diversity in human populations has led to evolutionary hypotheses of adaptation to distinct chemical environments. Population differentiation in measured drug metabolism phenotypes is, however, scarcely documented, often indirectly estimated via genotype-predicted phenotypes. We administered seven probe compounds devised to target six cytochrome P450 enzymes and the P-glycoprotein (P-gp) activity to assess phenotypic variation in four populations along a latitudinal transect spanning over Africa, the Middle East, and Europe (349 healthy Ethiopian, Omani, Greek, and Czech volunteers). We demonstrate significant population differentiation for all phenotypes except the one measuring CYP2D6 activity. Genome-wide association studies (GWAS) evidenced that the variability of phenotypes measuring CYP2B6, CYP2C9, CYP2C19, and CYP2D6 activity was associated with genetic variants linked to the corresponding encoding genes, and additional genes for the latter three. Instead, GWAS did not indicate any association between genetic diversity and the phenotypes measuring CYP1A2, CYP3A4, and P-gp activity. Genome scans of selection highlighted multiple candidate regions, a few of which included ADME genes, but none overlapped with the GWAS candidates. Our results suggest that different mechanisms have been shaping the evolution of these phenotypes, including phenotypic plasticity, and possibly some form of balancing selection. We discuss how these contrasting results highlight the diverse evolutionary trajectories of ADME genes and proteins, consistent with the wide spectrum of both endogenous and exogenous molecules that are their substrates.
Collapse
Affiliation(s)
| | - Youssef Daali
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Victoria Rollason
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Martina Čížková
- Institute of Archaeology of the Academy of Sciences of the Czech Republic, Prague, Czech Republic
| | - Anwar Mulugeta
- Department of Pharmacology and Clinical Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Khalid A Al Balushi
- College of Pharmacy, National University of Science and Technology, Muscat, Sultanate of Oman
| | - Giannoulis Fakis
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
| | | | - Khalid Al-Thihli
- Department of Genetics, Sultan Qaboos University Hospital, Muscat, Sultanate of Oman
| | - Marie Černá
- Department of Medical Genetics, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Eyasu Makonnen
- Department of Pharmacology and Clinical Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia,Center for Innovative Drug Development and Therapeutic Trials for Africa, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Sotiria Boukouvala
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
| | - Said Al-Yahyaee
- Department of Genetics, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman
| | - Getnet Yimer
- Center for Global Genomics & Health Equity, Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Viktor Černý
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
| | - Jules Desmeules
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | | |
Collapse
|