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Mackay TFC, Anholt RRH. Pleiotropy, epistasis and the genetic architecture of quantitative traits. Nat Rev Genet 2024:10.1038/s41576-024-00711-3. [PMID: 38565962 DOI: 10.1038/s41576-024-00711-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/14/2024] [Indexed: 04/04/2024]
Abstract
Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.
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Affiliation(s)
- Trudy F C Mackay
- Center for Human Genetics, Clemson University, Greenwood, SC, USA.
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC, USA.
| | - Robert R H Anholt
- Center for Human Genetics, Clemson University, Greenwood, SC, USA.
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC, USA.
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3
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Freudiger A, Jovanovic VM, Huang Y, Snyder-Mackler N, Conrad DF, Miller B, Montague MJ, Westphal H, Stadler PF, Bley S, Horvath JE, Brent LJN, Platt ML, Ruiz-Lambides A, Tung J, Nowick K, Ringbauer H, Widdig A. Taking identity-by-descent analysis into the wild: Estimating realized relatedness in free-ranging macaques. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.09.574911. [PMID: 38260273 PMCID: PMC10802400 DOI: 10.1101/2024.01.09.574911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Biological relatedness is a key consideration in studies of behavior, population structure, and trait evolution. Except for parent-offspring dyads, pedigrees capture relatedness imperfectly. The number and length of DNA segments that are identical-by-descent (IBD) yield the most precise estimates of relatedness. Here, we leverage novel methods for estimating locus-specific IBD from low coverage whole genome resequencing data to demonstrate the feasibility and value of resolving fine-scaled gradients of relatedness in free-living animals. Using primarily 4-6× coverage data from a rhesus macaque (Macaca mulatta) population with available long-term pedigree data, we show that we can call the number and length of IBD segments across the genome with high accuracy even at 0.5× coverage. The resulting estimates demonstrate substantial variation in genetic relatedness within kin classes, leading to overlapping distributions between kin classes. They identify cryptic genetic relatives that are not represented in the pedigree and reveal elevated recombination rates in females relative to males, which allows us to discriminate maternal and paternal kin using genotype data alone. Our findings represent a breakthrough in the ability to understand the predictors and consequences of genetic relatedness in natural populations, contributing to our understanding of a fundamental component of population structure in the wild.
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Affiliation(s)
- Annika Freudiger
- Behavioral Ecology Research Group, Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Vladimir M Jovanovic
- Human Biology and Primate Evolution, Institut für Zoologie, Freie Universität Berlin, Berlin, Germany
- Bioinformatics Solution Center, Freie Universität Berlin, Berlin, Germany
| | - Yilei Huang
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Bioinformatics Group, Institute of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
| | - Noah Snyder-Mackler
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, USA
| | - Donald F Conrad
- Division of Genetics, Oregon National Primate Research Center, Portland, Oregon, USA
| | - Brian Miller
- Division of Genetics, Oregon National Primate Research Center, Portland, Oregon, USA
| | - Michael J Montague
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Hendrikje Westphal
- Behavioral Ecology Research Group, Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Bioinformatics Group, Institute of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
| | - Peter F Stadler
- Bioinformatics Group, Institute of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
- Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
- Institute for Theoretical Chemistry, University of Vienna, Austria
- Facultad de Ciencias, Universidad Nacional de Colombia, Bogotá, Colombia
- Santa Fe Institute, Santa Fe, NM, USA
| | - Stefanie Bley
- Behavioral Ecology Research Group, Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Julie E Horvath
- Department of Biological and Biomedical Sciences, North Carolina Central University, North Carolina, Durham, USA
- Research and Collections Section, North Carolina Museum of Natural Sciences, North Carolina, Raleigh, USA
- Department of Biological Sciences, North Carolina State University, North Carolina, Raleigh, USA
- Department of Evolutionary Anthropology, Duke University, North Carolina, Durham, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Lauren J N Brent
- Centre for Research in Animal Behaviour, University of Exeter, Exeter, UK
| | - Michael L Platt
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Marketing Department, the Wharton School of Business, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Angelina Ruiz-Lambides
- Cayo Santiago Field Station, Caribbean Primate Research Center, University of Puerto Rico, Punta Santiago, Puerto Rico
| | - Jenny Tung
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Department of Evolutionary Anthropology, Duke University, North Carolina, Durham, USA
- Department of Biology, Duke University, Durham, North Carolina, USA
- Duke University Population Research Institute, Durham, North Carolina, USA
| | - Katja Nowick
- Human Biology and Primate Evolution, Institut für Zoologie, Freie Universität Berlin, Berlin, Germany
- Bioinformatics Solution Center, Freie Universität Berlin, Berlin, Germany
| | - Harald Ringbauer
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Anja Widdig
- Behavioral Ecology Research Group, Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany
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Kurland S, Saha A, Keehnen N, de la Paz Celorio-Mancera M, Díez-Del-Molino D, Ryman N, Laikre L. New indicators for monitoring genetic diversity applied to alpine brown trout populations using whole genome sequence data. Mol Ecol 2024; 33:e17213. [PMID: 38014725 DOI: 10.1111/mec.17213] [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: 06/12/2023] [Revised: 11/03/2023] [Accepted: 11/07/2023] [Indexed: 11/29/2023]
Abstract
International policy recently adopted commitments to maintain genetic diversity in wild populations to secure their adaptive potential, including metrics to monitor temporal trends in genetic diversity - so-called indicators. A national programme for assessing trends in genetic diversity was recently initiated in Sweden. Relating to this effort, we systematically assess contemporary genome-wide temporal trends (40 years) in wild populations using the newly adopted indicators and whole genome sequencing (WGS). We use pooled and individual WGS data from brown trout (Salmo trutta) in eight alpine lakes in protected areas. Observed temporal trends in diversity metrics (nucleotide diversity, Watterson's ϴ and heterozygosity) lie within proposed acceptable threshold values for six of the lakes, but with consistently low values in lakes above the tree line and declines observed in these northern-most lakes. Local effective population size is low in all lakes, highlighting the importance of continued protection of interconnected systems to allow genetic connectivity for long-term viability of these populations. Inbreeding (FROH ) spans 10%-30% and is mostly represented by ancient (<1 Mb) runs of homozygosity, with observations of little change in mutational load. We also investigate adaptive dynamics over evolutionarily short time frames (a few generations); identifying putative parallel selection across all lakes within a gene pertaining to skin pigmentation as well as candidates of selection unique to specific lakes and lake systems involved in reproduction and immunity. We demonstrate the utility of WGS for systematic monitoring of natural populations, a priority concern if genetic diversity is to be protected.
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Affiliation(s)
- Sara Kurland
- Division of Population Genetics, Department of Zoology, Stockholm University, Stockholm, Sweden
- Department of Earth Sciences, Natural Resources and Sustainable Development, Uppsala University, Uppsala, Sweden
| | - Atal Saha
- Division of Population Genetics, Department of Zoology, Stockholm University, Stockholm, Sweden
- Centre for Coastal Research, Department of Natural Sciences, University of Agder, Kristiansand, Norway
| | - Naomi Keehnen
- Division of Population Genetics, Department of Zoology, Stockholm University, Stockholm, Sweden
- Department of Ecology, SLU, Uppsala, Sweden
| | | | - David Díez-Del-Molino
- Division of Population Genetics, Department of Zoology, Stockholm University, Stockholm, Sweden
- Centre for Palaeogenetics, Stockholm, Sweden
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Nils Ryman
- Division of Population Genetics, Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Linda Laikre
- Division of Population Genetics, Department of Zoology, Stockholm University, Stockholm, Sweden
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