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Braichenko S, Borges R, Kosiol C. Polymorphism-Aware Models in RevBayes: Species Trees, Disentangling Balancing Selection, and GC-Biased Gene Conversion. Mol Biol Evol 2024; 41:msae138. [PMID: 38980178 PMCID: PMC11272101 DOI: 10.1093/molbev/msae138] [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: 12/11/2023] [Revised: 04/19/2024] [Accepted: 07/06/2024] [Indexed: 07/10/2024] Open
Abstract
The role of balancing selection is a long-standing evolutionary puzzle. Balancing selection is a crucial evolutionary process that maintains genetic variation (polymorphism) over extended periods of time; however, detecting it poses a significant challenge. Building upon the Polymorphism-aware phylogenetic Models (PoMos) framework rooted in the Moran model, we introduce a PoMoBalance model. This novel approach is designed to disentangle the interplay of mutation, genetic drift, and directional selection (GC-biased gene conversion), along with the previously unexplored balancing selection pressures on ultra-long timescales comparable with species divergence times by analyzing multi-individual genomic and phylogenetic divergence data. Implemented in the open-source RevBayes Bayesian framework, PoMoBalance offers a versatile tool for inferring phylogenetic trees as well as quantifying various selective pressures. The novel aspect of our approach in studying balancing selection lies in polymorphism-aware phylogenetic models' ability to account for ancestral polymorphisms and incorporate parameters that measure frequency-dependent selection, allowing us to determine the strength of the effect and exact frequencies under selection. We implemented validation tests and assessed the model on the data simulated with SLiM and a custom Moran model simulator. Real sequence analysis of Drosophila populations reveals insights into the evolutionary dynamics of regions subject to frequency-dependent balancing selection, particularly in the context of sex-limited color dimorphism in Drosophila erecta.
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Affiliation(s)
- Svitlana Braichenko
- Centre for Biological Diversity, School of Biology, University of St Andrews, Fife KY16 9TH, UK
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Rui Borges
- Institut für Populationsgenetik, Vetmeduni Vienna, Wien 1210, Austria
| | - Carolin Kosiol
- Centre for Biological Diversity, School of Biology, University of St Andrews, Fife KY16 9TH, UK
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2
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Cornetti L, Fields PD, Du Pasquier L, Ebert D. Long-term balancing selection for pathogen resistance maintains trans-species polymorphisms in a planktonic crustacean. Nat Commun 2024; 15:5333. [PMID: 38909039 PMCID: PMC11193740 DOI: 10.1038/s41467-024-49726-8] [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: 06/08/2023] [Accepted: 06/18/2024] [Indexed: 06/24/2024] Open
Abstract
Balancing selection is an evolutionary process that maintains genetic polymorphisms at selected loci and strongly reduces the likelihood of allele fixation. When allelic polymorphisms that predate speciation events are maintained independently in the resulting lineages, a pattern of trans-species polymorphisms may occur. Trans-species polymorphisms have been identified for loci related to mating systems and the MHC, but they are generally rare. Trans-species polymorphisms in disease loci are believed to be a consequence of long-term host-parasite coevolution by balancing selection, the so-called Red Queen dynamics. Here we scan the genomes of three crustaceans with a divergence of over 15 million years and identify 11 genes containing identical-by-descent trans-species polymorphisms with the same polymorphisms in all three species. Four of these genes display molecular footprints of balancing selection and have a function related to immunity. Three of them are located in or close to loci involved in resistance to a virulent bacterial pathogen, Pasteuria, with which the Daphnia host is known to coevolve. This provides rare evidence of trans-species polymorphisms for loci known to be functionally relevant in interactions with a widespread and highly specific parasite. These findings support the theory that specific antagonistic coevolution is able to maintain genetic diversity over millions of years.
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Affiliation(s)
- Luca Cornetti
- Department of Environmental Sciences, Zoology, University of Basel, Basel, Switzerland
- Syngenta Crop Protection AG, Stein, Switzerland
| | - Peter D Fields
- Department of Environmental Sciences, Zoology, University of Basel, Basel, Switzerland
| | - Louis Du Pasquier
- Department of Environmental Sciences, Zoology, University of Basel, Basel, Switzerland
| | - Dieter Ebert
- Department of Environmental Sciences, Zoology, University of Basel, Basel, Switzerland.
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3
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Lockwood C, Vo AS, Bellafard H, Carter AJR. More evidence for widespread antagonistic pleiotropy in polymorphic disease alleles. Front Genet 2024; 15:1404516. [PMID: 38952711 PMCID: PMC11215129 DOI: 10.3389/fgene.2024.1404516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 05/29/2024] [Indexed: 07/03/2024] Open
Abstract
Introduction Many loci segregate alleles classified as "genetic diseases" due to their deleterious effects on health. However, some disease alleles have been reported to show beneficial effects under certain conditions or in certain populations. The beneficial effects of these antagonistically pleiotropic alleles may explain their continued prevalence, but the degree to which antagonistic pleiotropy is common or rare is unresolved. We surveyed the medical literature to identify examples of antagonistic pleiotropy to help determine whether antagonistic pleiotropy appears to be rare or common. Results We identified ten examples of loci with polymorphisms for which the presence of antagonistic pleiotropy is well supported by detailed genetic or epidemiological information in humans. One additional locus was identified for which the supporting evidence comes from animal studies. These examples complement over 20 others reported in other reviews. Discussion The existence of more than 30 identified antagonistically pleiotropic human disease alleles suggests that this phenomenon may be widespread. This poses important implications for both our understanding of human evolutionary genetics and our approaches to clinical treatment and disease prevention, especially therapies based on genetic modification.
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Affiliation(s)
| | | | | | - Ashley J. R. Carter
- California State University Long Beach, Department of Biological Sciences, Long Beach, CA, United States
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4
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Soni V, Jensen JD. Temporal challenges in detecting balancing selection from population genomic data. G3 (BETHESDA, MD.) 2024; 14:jkae069. [PMID: 38551137 DOI: 10.1093/g3journal/jkae069] [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: 12/21/2023] [Revised: 12/21/2023] [Accepted: 03/19/2024] [Indexed: 04/28/2024]
Abstract
The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum- and linkage disequilibrium-based methods under a variety of evolutionarily realistic null models. We find that whilst site frequency spectrum-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, linkage disequilibrium-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that site frequency spectrum-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst linkage disequilibrium-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g. population structure and admixture) as well as of alternative selective processes (e.g. partial selective sweeps).
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ 85281, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ 85281, USA
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5
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Riley R, Mathieson I, Mathieson S. Interpreting generative adversarial networks to infer natural selection from genetic data. Genetics 2024; 226:iyae024. [PMID: 38386895 PMCID: PMC10990424 DOI: 10.1093/genetics/iyae024] [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: 11/10/2023] [Revised: 01/15/2024] [Accepted: 01/19/2024] [Indexed: 02/24/2024] Open
Abstract
Understanding natural selection and other forms of non-neutrality is a major focus for the use of machine learning in population genetics. Existing methods rely on computationally intensive simulated training data. Unlike efficient neutral coalescent simulations for demographic inference, realistic simulations of selection typically require slow forward simulations. Because there are many possible modes of selection, a high dimensional parameter space must be explored, with no guarantee that the simulated models are close to the real processes. Finally, it is difficult to interpret trained neural networks, leading to a lack of understanding about what features contribute to classification. Here we develop a new approach to detect selection and other local evolutionary processes that requires relatively few selection simulations during training. We build upon a generative adversarial network trained to simulate realistic neutral data. This consists of a generator (fitted demographic model), and a discriminator (convolutional neural network) that predicts whether a genomic region is real or fake. As the generator can only generate data under neutral demographic processes, regions of real data that the discriminator recognizes as having a high probability of being "real" do not fit the neutral demographic model and are therefore candidates for targets of selection. To incentivize identification of a specific mode of selection, we fine-tune the discriminator with a small number of custom non-neutral simulations. We show that this approach has high power to detect various forms of selection in simulations, and that it finds regions under positive selection identified by state-of-the-art population genetic methods in three human populations. Finally, we show how to interpret the trained networks by clustering hidden units of the discriminator based on their correlation patterns with known summary statistics.
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Affiliation(s)
- Rebecca Riley
- Department of Computer Science, Haverford College, Haverford, PA 19041, USA
| | - Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sara Mathieson
- Department of Computer Science, Haverford College, Haverford, PA 19041, USA
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6
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Hayeck TJ, Li Y, Mosbruger TL, Bradfield JP, Gleason AG, Damianos G, Shaw GTW, Duke JL, Conlin LK, Turner TN, Fernández-Viña MA, Sarmady M, Monos DS. The Impact of Patterns in Linkage Disequilibrium and Sequencing Quality on the Imprint of Balancing Selection. Genome Biol Evol 2024; 16:evae009. [PMID: 38302106 PMCID: PMC10853003 DOI: 10.1093/gbe/evae009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 01/08/2024] [Accepted: 01/12/2024] [Indexed: 02/03/2024] Open
Abstract
Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima's D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions.
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Affiliation(s)
- Tristan J Hayeck
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yang Li
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy L Mosbruger
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Adam G Gleason
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - George Damianos
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Grace Tzun-Wen Shaw
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jamie L Duke
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Laura K Conlin
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Tychele N Turner
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Marcelo A Fernández-Viña
- Department of Pathology, Stanford University School of Medicine, Palo Alto, CA, USA
- Histocompatibility and Immunogenetics Laboratory, Stanford Blood Center, Palo Alto, CA, USA
| | - Mahdi Sarmady
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dimitri S Monos
- Division of Genomic Diagnostics, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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7
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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.
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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
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8
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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.
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Affiliation(s)
- Ziyue Gao
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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9
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Raja A, Kuiper JJW. Evolutionary immuno-genetics of endoplasmic reticulum aminopeptidase II (ERAP2). Genes Immun 2023; 24:295-302. [PMID: 37925533 PMCID: PMC10721543 DOI: 10.1038/s41435-023-00225-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/18/2023] [Accepted: 10/24/2023] [Indexed: 11/06/2023]
Abstract
Endoplasmic reticulum aminopeptidase 2 (ERAP2) is a proteolytic enzyme involved in adaptive immunity. The ERAP2 gene is highly polymorphic and encodes haplotypes that confer resistance against lethal infectious diseases, but also increase the risk for autoimmune disorders. Identifying how ERAP2 influences susceptibility to these traits requires an understanding of the selective pressures that shaped and maintained allelic variation throughout human evolution. Our review discusses the genetic regulation of haplotypes and diversity in naturally occurring ERAP2 allotypes in the global population. We outline how these ERAP2 haplotypes evolved during human history and highlight the presence of Neanderthal DNA sequences in ERAP2 of modern humans. Recent evidence suggests that human adaptation during the last ~10,000 years and historic pandemics left a significant mark on the ERAP2 gene that determines susceptibility to infectious and inflammatory diseases today.
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Affiliation(s)
- Aroosha Raja
- Department of Ophthalmology, Center for Translational Immunology, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Jonas J W Kuiper
- Department of Ophthalmology, Center for Translational Immunology, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
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10
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Panigrahi M, Rajawat D, Nayak SS, Ghildiyal K, Sharma A, Jain K, Lei C, Bhushan B, Mishra BP, Dutt T. Landmarks in the history of selective sweeps. Anim Genet 2023; 54:667-688. [PMID: 37710403 DOI: 10.1111/age.13355] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 08/28/2023] [Indexed: 09/16/2023]
Abstract
Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next-generation sequencing, high-density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large-scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data.
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Affiliation(s)
- Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | | | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Karan Jain
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Bishnu Prasad Mishra
- Division of Animal Biotechnology, ICAR-National Bureau of Animal Genetic Resources, Karnal, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Bareilly, India
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11
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Urnikyte A, Masiulyte A, Pranckeniene L, Kučinskas V. Disentangling archaic introgression and genomic signatures of selection at human immunity genes. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2023; 116:105528. [PMID: 37977419 DOI: 10.1016/j.meegid.2023.105528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 11/04/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023]
Abstract
Pathogens and infectious diseases have imposed exceptionally strong selective pressure on ancient and modern human genomes and contributed to the current variation in many genes. There is evidence that modern humans acquired immune variants through interbreeding with ancient hominins, but the impact of such variants on human traits is not fully understood. The main objectives of this research were to infer the genetic signatures of positive selection that may be involved in adaptation to infectious diseases and to investigate the function of Neanderthal alleles identified within a set of 50 Lithuanian genomes. Introgressed regions were identified using the machine learning tool ArchIE. Recent positive selection signatures were analysed using iHS. We detected high-scoring signals of positive selection at innate immunity genes (EMB, PARP8, HLAC, and CDSN) and evaluated their interactions with the structural proteins of pathogens. Interactions with human immunodeficiency virus (HIV) 1 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were identified. Overall, genomic regions introgressed from Neanderthals were shown to be enriched in genes related to immunity, keratinocyte differentiation, and sensory perception.
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Affiliation(s)
- Alina Urnikyte
- Faculty of Medicine, Department of Human and Medical Genetics, Institute of Biomedical Sciences, Vilnius University, Santariskiu Street 2, Vilnius LT-08661, Lithuania.
| | - Abigaile Masiulyte
- Faculty of Medicine, Department of Human and Medical Genetics, Institute of Biomedical Sciences, Vilnius University, Santariskiu Street 2, Vilnius LT-08661, Lithuania
| | - Laura Pranckeniene
- Faculty of Medicine, Department of Human and Medical Genetics, Institute of Biomedical Sciences, Vilnius University, Santariskiu Street 2, Vilnius LT-08661, Lithuania.
| | - Vaidutis Kučinskas
- Faculty of Medicine, Department of Human and Medical Genetics, Institute of Biomedical Sciences, Vilnius University, Santariskiu Street 2, Vilnius LT-08661, Lithuania.
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12
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Levi R, Levi L, Louzoun Y. Bw4 ligand and direct T-cell receptor binding induced selection on HLA A and B alleles. Front Immunol 2023; 14:1236080. [PMID: 38077375 PMCID: PMC10703150 DOI: 10.3389/fimmu.2023.1236080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 10/26/2023] [Indexed: 12/18/2023] Open
Abstract
Introduction The HLA region is the hallmark of balancing selection, argued to be driven by the pressure to present a wide variety of viral epitopes. As such selection on the peptide-binding positions has been proposed to drive HLA population genetics. MHC molecules also directly binds to the T-Cell Receptor and killer cell immunoglobulin-like receptors (KIR). Methods We here combine the HLA allele frequencies in over six-million Hematopoietic Stem Cells (HSC) donors with a novel machine-learning-based method to predict allele frequency. Results We show for the first time that allele frequency can be predicted from their sequences. This prediction yields a natural measure for selection. The strongest selection is affecting KIR binding regions, followed by the peptide-binding cleft. The selection from the direct interaction with the KIR and TCR is centered on positively charged residues (mainly Arginine), and some positions in the peptide-binding cleft are not associated with the allele frequency, especially Tyrosine residues. Discussion These results suggest that the balancing selection for peptide presentation is combined with a positive selection for KIR and TCR binding.
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Affiliation(s)
| | | | - Yoram Louzoun
- Department of Mathematics, Bar-Ilan University, Ramat Gan, Israel
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13
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Minias P. The effects of urban life on animal immunity: Adaptations and constraints. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 895:165085. [PMID: 37379938 DOI: 10.1016/j.scitotenv.2023.165085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/21/2023] [Accepted: 06/21/2023] [Indexed: 06/30/2023]
Abstract
Land transformation, including urbanization, is a dominant form of anthropogenic change to the global environment at the dawn of the Anthropocene epoch. More and more species are brought into direct contact with humans, being either required to develop broad-scale adaptations to urban environment or filtered out from urbanized areas. While behavioural or physiological adaptations are at the forefront of urban biology research, there is accumulating evidence for divergent pathogen pressure across urbanization gradients, requiring adjustments in host immune function. At the same time, host immunity may be constrained by unfavourable components of an urban environment, such as poor-quality food resources, disturbance, or pollution. Here, I reviewed existing evidence for adaptations and constrains in the immune system of urban animals, focusing on the recent implementation of metabarcoding, genomic, transcriptomic, and epigenomic approaches in urban biology research. I show that spatial variation in pathogen pressure across urban and non-urban landscapes is highly complex and may be context-dependent, but there is solid evidence for pathogen-driven immunostimulation in urban-dwelling animals. I also show that genes coding for molecules directly involved in interactions with pathogens are the prime candidates for immunogenetic adaptations to urban life. Evidence emerging from landscape genomics and transcriptomics show that immune adaptations to urban life may have a polygenic nature, but immune traits may not be among the key biological functions experiencing broad-scale microevolutionary changes in response to urbanization. Finally, I provided recommendations for future research, including i) a better integration of different 'omic' approaches to obtain a more complete picture of immune adaptations to urban life in non-model animal taxa, ii) quantification of fitness landscapes for immune phenotypes and genotypes across urbanization gradient, and iii) much broader taxonomic coverage (including invertebrates) necessary to draw more robust conclusions on how general (or taxa-specific) are immune responses of animals to urbanization.
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Affiliation(s)
- Piotr Minias
- Department of Biodiversity Studies and Bioeducation, Faculty of Biology and Environmental Protection, University of Łódź, Banacha 1/3, 90-237 Łódź, Poland.
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14
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Pivirotto AM, Platt A, Patel R, Kumar S, Hey J. Analyses of allele age and fitness impact reveal human beneficial alleles to be older than neutral controls. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.09.561569. [PMID: 37873438 PMCID: PMC10592680 DOI: 10.1101/2023.10.09.561569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
A classic population genetic prediction is that alleles experiencing directional selection should swiftly traverse allele frequency space, leaving detectable reductions in genetic variation in linked regions. However, despite this expectation, identifying clear footprints of beneficial allele passage has proven to be surprisingly challenging. We addressed the basic premise underlying this expectation by estimating the ages of large numbers of beneficial and deleterious alleles in a human population genomic data set. Deleterious alleles were found to be young, on average, given their allele frequency. However, beneficial alleles were older on average than non-coding, non-regulatory alleles of the same frequency. This finding is not consistent with directional selection and instead indicates some type of balancing selection. Among derived beneficial alleles, those fixed in the population show higher local recombination rates than those still segregating, consistent with a model in which new beneficial alleles experience an initial period of balancing selection due to linkage disequilibrium with deleterious recessive alleles. Alleles that ultimately fix following a period of balancing selection will leave a modest 'soft' sweep impact on the local variation, consistent with the overall paucity of species-wide 'hard' sweeps in human genomes.
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Affiliation(s)
| | - Alexander Platt
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- University of Pennsylvania, Department of Genetics, Philadelphia PA 19104, USA
| | - Ravi Patel
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- Institute for Genomics and Evolutionary Medicine, Temple University, PA 19122, USA
| | - Sudhir Kumar
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- Institute for Genomics and Evolutionary Medicine, Temple University, PA 19122, USA
| | - Jody Hey
- Temple University, Department of Biology, Philadelphia PA 19122, USA
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15
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Winternitz J, Chakarov N, Rinaud T, Ottensmann M, Krüger O. High functional allelic diversity and copy number in both MHC classes in the common buzzard. BMC Ecol Evol 2023; 23:24. [PMID: 37355591 PMCID: PMC10290333 DOI: 10.1186/s12862-023-02135-9] [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: 11/11/2021] [Accepted: 06/12/2023] [Indexed: 06/26/2023] Open
Abstract
BACKGROUND The major histocompatibility complex (MHC), which encodes molecules that recognize various pathogens and parasites and initiates the adaptive immune response in vertebrates, is renowned for its exceptional polymorphism and is a model of adaptive gene evolution. In birds, the number of MHC genes and sequence diversity varies greatly among taxa, believed due to evolutionary history and differential selection pressures. Earlier characterization studies and recent comparative studies suggest that non-passerine species have relatively few MHC gene copies compared to passerines. Additionally, comparative studies that have looked at partial MHC sequences have speculated that non-passerines have opposite patterns of selection on MHC class I (MHC-I) and class II (MHC-II) loci than passerines: namely, greater sequence diversity and signals of selection on MHC-II than MHC-I. However, new sequencing technology is revealing much greater MHC variation than previously expected while also facilitating full sequence variant detection directly from genomic data. Our study aims to take advantage of high-throughput sequencing methods to fully characterize both classes and domains of MHC of a non-passerine bird of prey, the common buzzard (Buteo buteo), to test predictions of MHC variation and differential selection on MHC classes. RESULTS Using genetic, genomic, and transcriptomic high-throughput sequencing data, we established common buzzards have at least three loci that produce functional alleles at both MHC classes. In total, we characterize 91 alleles from 113 common buzzard chicks for MHC-I exon 3 and 41 alleles from 125 chicks for MHC-IIB exon 2. Among these alleles, we found greater sequence polymorphism and stronger diversifying selection at MHC-IIB exon 2 than MHC-I exon 3, suggesting differential selection pressures on MHC classes. However, upon further investigation of the entire peptide-binding groove by including genomic data from MHC-I exon 2 and MHC-IIA exon 2, this turned out to be false. MHC-I exon 2 was as polymorphic as MHC-IIB exon 2 and MHC-IIA exon 2 was essentially invariant. Thus, comparisons between MHC-I and MHC-II that included both domains of the peptide-binding groove showed no differences in polymorphism nor diversifying selection between the classes. Nevertheless, selection analysis indicates balancing selection has been acting on common buzzard MHC and phylogenetic inference revealed that trans-species polymorphism is present between common buzzards and species separated for over 33 million years for class I and class II. CONCLUSIONS We characterize and confirm the functionality of unexpectedly high copy number and allelic diversity in both MHC classes of a bird of prey. While balancing selection is acting on both classes, there is no evidence of differential selection pressure on MHC classes in common buzzards and this result may hold more generally once more data for understudied MHC exons becomes available.
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Affiliation(s)
- Jamie Winternitz
- Department of Animal Behaviour, Bielefeld University, Morgenbreede 45, 33615 Bielefeld, Germany
| | - Nayden Chakarov
- Department of Animal Behaviour, Bielefeld University, Morgenbreede 45, 33615 Bielefeld, Germany
| | - Tony Rinaud
- Department of Animal Behaviour, Bielefeld University, Morgenbreede 45, 33615 Bielefeld, Germany
| | - Meinolf Ottensmann
- Department of Animal Behaviour, Bielefeld University, Morgenbreede 45, 33615 Bielefeld, Germany
| | - Oliver Krüger
- Department of Animal Behaviour, Bielefeld University, Morgenbreede 45, 33615 Bielefeld, Germany
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16
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Huang G, Wu W, Chen Y, Zhi X, Zou P, Ning Z, Fan Q, Liu Y, Deng S, Zeng K, Zhou R. Balancing selection on an MYB transcription factor maintains the twig trichome color variation in Melastoma normale. BMC Biol 2023; 21:122. [PMID: 37226197 DOI: 10.1186/s12915-023-01611-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 05/03/2023] [Indexed: 05/26/2023] Open
Abstract
BACKGROUND The factors that maintain phenotypic and genetic variation within a population have received long-term attention in evolutionary biology. Here the genetic basis and evolution of the geographically widespread variation in twig trichome color (from red to white) in a shrub Melastoma normale was investigated using Pool-seq and evolutionary analyses. RESULTS The results show that the twig trichome coloration is under selection in different light environments and that a 6-kb region containing an R2R3 MYB transcription factor gene is the major region of divergence between the extreme red and white morphs. This gene has two highly divergent groups of alleles, one of which likely originated from introgression from another species in this genus and has risen to high frequency (> 0.6) within each of the three populations under investigation. In contrast, polymorphisms in other regions of the genome show no sign of differentiation between the two morphs, suggesting that genomic patterns of diversity have been shaped by homogenizing gene flow. Population genetics analysis reveals signals of balancing selection acting on this gene, and it is suggested that spatially varying selection is the most likely mechanism of balancing selection in this case. CONCLUSIONS This study demonstrate that polymorphisms on a single transcription factor gene largely confer the twig trichome color variation in M. normale, while also explaining how adaptive divergence can occur and be maintained in the face of gene flow.
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Affiliation(s)
- Guilian Huang
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Wei Wu
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Yongmei Chen
- College of Chemical Engineering, Sichuan University of Science & Engineering, Zigong, Sichuan, 643000, China
| | - Xueke Zhi
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Peishan Zou
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Zulin Ning
- Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Qiang Fan
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Ying Liu
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Shulin Deng
- Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Kai Zeng
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK.
| | - Renchao Zhou
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China.
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17
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Mathieson I, Day FR, Barban N, Tropf FC, Brazel DM, Vaez A, van Zuydam N, Bitarello BD, Gardner EJ, Akimova ET, Azad A, Bergmann S, Bielak LF, Boomsma DI, Bosak K, Brumat M, Buring JE, Cesarini D, Chasman DI, Chavarro JE, Cocca M, Concas MP, Davey Smith G, Davies G, Deary IJ, Esko T, Faul JD, Franco O, Ganna A, Gaskins AJ, Gelemanovic A, de Geus EJC, Gieger C, Girotto G, Gopinath B, Grabe HJ, Gunderson EP, Hayward C, He C, van Heemst D, Hill WD, Hoffmann ER, Homuth G, Hottenga JJ, Huang H, Hyppӧnen E, Ikram MA, Jansen R, Johannesson M, Kamali Z, Kardia SLR, Kavousi M, Kifley A, Kiiskinen T, Kraft P, Kühnel B, Langenberg C, Liew G, Lind PA, Luan J, Mägi R, Magnusson PKE, Mahajan A, Martin NG, Mbarek H, McCarthy MI, McMahon G, Medland SE, Meitinger T, Metspalu A, Mihailov E, Milani L, Missmer SA, Mitchell P, Møllegaard S, Mook-Kanamori DO, Morgan A, van der Most PJ, de Mutsert R, Nauck M, Nolte IM, Noordam R, Penninx BWJH, Peters A, Peyser PA, Polašek O, Power C, Pribisalic A, Redmond P, Rich-Edwards JW, Ridker PM, Rietveld CA, Ring SM, Rose LM, Rueedi R, Shukla V, Smith JA, Stankovic S, Stefánsson K, Stöckl D, Strauch K, Swertz MA, Teumer A, Thorleifsson G, Thorsteinsdottir U, Thurik AR, Timpson NJ, Turman C, Uitterlinden AG, Waldenberger M, Wareham NJ, Weir DR, Willemsen G, Zhao JH, Zhao W, Zhao Y, Snieder H, den Hoed M, Ong KK, Mills MC, Perry JRB. Genome-wide analysis identifies genetic effects on reproductive success and ongoing natural selection at the FADS locus. Nat Hum Behav 2023; 7:790-801. [PMID: 36864135 DOI: 10.1038/s41562-023-01528-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 01/12/2023] [Indexed: 03/04/2023]
Abstract
Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identified 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology, including puberty timing, age at first birth, sex hormone regulation, endometriosis and age at menopause. Missense variants in ARHGAP27 were associated with higher NEB but shorter reproductive lifespan, suggesting a trade-off at this locus between reproductive ageing and intensity. Other genes implicated by coding variants include PIK3IP1, ZFP82 and LRP4, and our results suggest a new role for the melanocortin 1 receptor (MC1R) in reproductive biology. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Integration with data from historical selection scans highlighted an allele in the FADS1/2 gene locus that has been under selection for thousands of years and remains so today. Collectively, our findings demonstrate that a broad range of biological mechanisms contribute to reproductive success.
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Affiliation(s)
- Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Nicola Barban
- Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Felix C Tropf
- Nuffield College, University of Oxford, Oxford, UK
- École Nationale de la Statistique et de L'administration Économique (ENSAE), Paris, France
- Center for Research in Economics and Statistics (CREST), Paris, France
| | - David M Brazel
- Nuffield College, University of Oxford, Oxford, UK
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK
| | - Ahmad Vaez
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Natalie van Zuydam
- Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Bárbara D Bitarello
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Eugene J Gardner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Evelina T Akimova
- Nuffield College, University of Oxford, Oxford, UK
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK
| | - Ajuna Azad
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Lawrence F Bielak
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, the Netherlands
| | | | - Marco Brumat
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Julie E Buring
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - David Cesarini
- Department of Economics, New York University, New York, NY, USA
- Research Institute for Industrial Economics, Stockholm, Sweden
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Daniel I Chasman
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jorge E Chavarro
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Massimiliano Cocca
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | | | - Gail Davies
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Oscar Franco
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Andrea Ganna
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Audrey J Gaskins
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | | | - Eco J C de Geus
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Giorgia Girotto
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Bamini Gopinath
- Centre for Vision Research, Westmead Institute for Medical Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Hans Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Erica P Gunderson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Chunyan He
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
- Department of Internal Medicine, Division of Medical Oncology, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - W David Hill
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Eva R Hoffmann
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Hongyang Huang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Elina Hyppӧnen
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Zoha Kamali
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Annette Kifley
- Centre for Vision Research, Westmead Institute for Medical Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Tuomo Kiiskinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Gerald Liew
- Centre for Vision Research, Westmead Institute for Medical Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Hamdi Mbarek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Qatar Genome Programme, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - George McMahon
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | | | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Stacey A Missmer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Adolescent and Young Adult Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Obstetrics, Gynecology, and Reproductive Biology, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
| | - Paul Mitchell
- Centre for Vision Research, Westmead Institute for Medical Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Stine Møllegaard
- Department of Sociology, University of Copenhagen, Copenhagen, Denmark
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Anna Morgan
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, the Netherlands
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Ozren Polašek
- University of Split School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Chris Power
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | | | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janet W Rich-Edwards
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Paul M Ridker
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Cornelius A Rietveld
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Applied Economics, Erasmus School of Economics, Rotterdam, the Netherlands
| | - Susan M Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | | | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Vallari Shukla
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Stasa Stankovic
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | | | - Doris Stöckl
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU, Munich, Germany
| | - Morris A Swertz
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | | | | | - A Roy Thurik
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Applied Economics, Erasmus School of Economics, Rotterdam, the Netherlands
- Montpellier Business School, Montpellier, France
| | | | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - André G Uitterlinden
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jing Hau Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Yajie Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Marcel den Hoed
- Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Ken K Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Melinda C Mills
- Nuffield College, University of Oxford, Oxford, UK.
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK.
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
- Department of Economics, Econometrics and Finance, University of Groningen, Groningen, the Netherlands.
| | - John R B Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
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18
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Fluctuating selection and the determinants of genetic variation. Trends Genet 2023; 39:491-504. [PMID: 36890036 DOI: 10.1016/j.tig.2023.02.004] [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: 08/18/2022] [Revised: 02/01/2023] [Accepted: 02/07/2023] [Indexed: 03/08/2023]
Abstract
Recent studies of cosmopolitan Drosophila populations have found hundreds to thousands of genetic loci with seasonally fluctuating allele frequencies, bringing temporally fluctuating selection to the forefront of the historical debate surrounding the maintenance of genetic variation in natural populations. Numerous mechanisms have been explored in this longstanding area of research, but these exciting empirical findings have prompted several recent theoretical and experimental studies that seek to better understand the drivers, dynamics, and genome-wide influence of fluctuating selection. In this review, we evaluate the latest evidence for multilocus fluctuating selection in Drosophila and other taxa, highlighting the role of potential genetic and ecological mechanisms in maintaining these loci and their impacts on neutral genetic variation.
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19
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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.
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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
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20
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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.
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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.
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21
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Polygenic signals of sex differences in selection in humans from the UK Biobank. PLoS Biol 2022; 20:e3001768. [PMID: 36067235 PMCID: PMC9481184 DOI: 10.1371/journal.pbio.3001768] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 09/16/2022] [Accepted: 07/27/2022] [Indexed: 11/19/2022] Open
Abstract
Sex differences in the fitness effects of genetic variants can influence the rate of adaptation and the maintenance of genetic variation. For example, "sexually antagonistic" (SA) variants, which are beneficial for one sex and harmful for the other, can both constrain adaptation and increase genetic variability for fitness components such as survival, fertility, and disease susceptibility. However, detecting variants with sex-differential fitness effects is difficult, requiring genome sequences and fitness measurements from large numbers of individuals. Here, we develop new theory for studying sex-differential selection across a complete life cycle and test our models with genotypic and reproductive success data from approximately 250,000 UK Biobank individuals. We uncover polygenic signals of sex-differential selection affecting survival, reproductive success, and overall fitness, with signals of sex-differential reproductive selection reflecting a combination of SA polymorphisms and sexually concordant polymorphisms in which the strength of selection differs between the sexes. Moreover, these signals hold up to rigorous controls that minimise the contributions of potential confounders, including sequence mapping errors, population structure, and ascertainment bias. Functional analyses reveal that sex-differentiated sites are enriched in phenotype-altering genomic regions, including coding regions and loci affecting a range of quantitative traits. Population genetic analyses show that sex-differentiated sites exhibit evolutionary histories dominated by genetic drift and/or transient balancing selection, but not long-term balancing selection, which is consistent with theoretical predictions of effectively weak SA balancing selection in historically small populations. Overall, our results are consistent with polygenic sex-differential-including SA-selection in humans. Evidence for sex-differential selection is particularly strong for variants affecting reproductive success, in which the potential contributions of nonrandom sampling to signals of sex differentiation can be excluded.
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22
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Collen EJ, Johar AS, Teixeira JC, Llamas B. The immunogenetic impact of European colonization in the Americas. Front Genet 2022; 13:918227. [PMID: 35991555 PMCID: PMC9388791 DOI: 10.3389/fgene.2022.918227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
The introduction of pathogens originating from Eurasia into the Americas during early European contact has been associated with high mortality rates among Indigenous peoples, likely contributing to their historical and precipitous population decline. However, the biological impacts of imported infectious diseases and resulting epidemics, especially in terms of pathogenic effects on the Indigenous immunity, remain poorly understood and highly contentious to this day. Here, we examine multidisciplinary evidence underpinning colonization-related immune genetic change, providing contextualization from anthropological studies, paleomicrobiological evidence of contrasting host-pathogen coevolutionary histories, and the timings of disease emergence. We further summarize current studies examining genetic signals reflecting post-contact Indigenous population bottlenecks, admixture with European and other populations, and the putative effects of natural selection, with a focus on ancient DNA studies and immunity-related findings. Considering current genetic evidence, together with a population genetics theoretical approach, we show that post-contact Indigenous immune adaptation, possibly influenced by selection exerted by introduced pathogens, is highly complex and likely to be affected by multifactorial causes. Disentangling putative adaptive signals from those of genetic drift thus remains a significant challenge, highlighting the need for the implementation of population genetic approaches that model the short time spans and complex demographic histories under consideration. This review adds to current understandings of post-contact immunity evolution in Indigenous peoples of America, with important implications for bettering our understanding of human adaptation in the face of emerging infectious diseases.
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Affiliation(s)
- Evelyn Jane Collen
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- *Correspondence: Evelyn Jane Collen, ; Bastien Llamas,
| | - Angad Singh Johar
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC, Australia
| | - João C. Teixeira
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- School of Culture History and Language, The Australian National University, Canberra, ACT, Australia
- Centre of Excellence for Australian Biodiversity and Heritage (CABAH), School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
| | - Bastien Llamas
- Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- Centre of Excellence for Australian Biodiversity and Heritage (CABAH), School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- National Centre for Indigenous Genomics, Australian National University, Canberra, ACT, Australia
- Telethon Kids Institute, Indigenous Genomics Research Group, Adelaide, SA, Australia
- *Correspondence: Evelyn Jane Collen, ; Bastien Llamas,
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23
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Soni V, Vos M, Eyre-Walker A. A new test suggests hundreds of amino acid polymorphisms in humans are subject to balancing selection. PLoS Biol 2022; 20:e3001645. [PMID: 35653351 PMCID: PMC9162324 DOI: 10.1371/journal.pbio.3001645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 04/25/2022] [Indexed: 11/18/2022] Open
Abstract
The role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here, we introduce a new test, based on the McDonald–Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and provide some evidence that hundreds of nonsynonymous polymorphisms are subject to balancing selection.
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
| | - Michiel Vos
- European Centre for Environment and Human Health, University of Exeter Medical School, Environment and Sustainability Institute, Penryn, United Kingdom
| | - Adam Eyre-Walker
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
- * E-mail:
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24
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Kumar H, Panigrahi M, Panwar A, Rajawat D, Nayak SS, Saravanan KA, Kaisa K, Parida S, Bhushan B, Dutt T. Machine-Learning Prospects for Detecting Selection Signatures Using Population Genomics Data. J Comput Biol 2022; 29:943-960. [PMID: 35639362 DOI: 10.1089/cmb.2021.0447] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Natural selection has been given a lot of attention because it relates to the adaptation of populations to their environments, both biotic and abiotic. An allele is selected when it is favored by natural selection. Consequently, the favored allele increases in frequency in the population and neighboring linked variation diminishes, causing so-called selective sweeps. A high-throughput genomic sequence allows one to disentangle the evolutionary forces at play in populations. With the development of high-throughput genome sequencing technologies, it has become easier to detect these selective sweeps/selection signatures. Various methods can be used to detect selective sweeps, from simple implementations using summary statistics to complex statistical approaches. One of the important problems of these statistical models is the potential to provide inaccurate results when their assumptions are violated. The use of machine learning (ML) in population genetics has been introduced as an alternative method of detecting selection by treating the problem of detecting selection signatures as a classification problem. Since the availability of population genomics data is increasing, researchers may incorporate ML into these statistical models to infer signatures of selection with higher predictive accuracy and better resolution. This article describes how ML can be used to aid in detecting and studying natural selection patterns using population genomic data.
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Affiliation(s)
- Harshit Kumar
- Divisions of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Manjit Panigrahi
- Divisions of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Anuradha Panwar
- Divisions of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Divya Rajawat
- Divisions of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Sonali Sonejita Nayak
- Divisions of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - K A Saravanan
- Divisions of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Kaiho Kaisa
- Divisions of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Subhashree Parida
- Divisions of Pharmacology and Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Bharat Bhushan
- Divisions of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, India
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25
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Velazquez-Arcelay K, Benton ML, Capra JA. Diverse functions associate with non-coding polymorphisms shared between humans and chimpanzees. BMC Ecol Evol 2022; 22:68. [PMID: 35606693 PMCID: PMC9125839 DOI: 10.1186/s12862-022-02020-x] [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: 03/13/2022] [Accepted: 05/09/2022] [Indexed: 11/24/2022] Open
Abstract
Background Long-term balancing selection (LTBS) can maintain allelic variation at a locus over millions of years and through speciation events. Variants shared between species in the state of identity-by-descent, hereafter “trans-species polymorphisms”, can result from LTBS, often due to host–pathogen interactions. For instance, the major histocompatibility complex (MHC) locus contains TSPs present across primates. Several hundred candidate LTBS regions have been identified in humans and chimpanzees; however, because many are in non-protein-coding regions of the genome, the functions and potential adaptive roles for most remain unknown. Results We integrated diverse genomic annotations to explore the functions of 60 previously identified regions with multiple shared polymorphisms (SPs) between humans and chimpanzees, including 19 with strong evidence of LTBS. We analyzed genome-wide functional assays, expression quantitative trait loci (eQTL), genome-wide association studies (GWAS), and phenome-wide association studies (PheWAS) for all the regions. We identify functional annotations for 59 regions, including 58 with evidence of gene regulatory function from GTEx or functional genomics data and 19 with evidence of trait association from GWAS or PheWAS. As expected, the SPs associate in humans with many immune system phenotypes, including response to pathogens, but we also find associations with a range of other phenotypes, including body size, alcohol intake, cognitive performance, risk-taking behavior, and urate levels. Conclusions The diversity of traits associated with non-coding regions with multiple SPs support previous hypotheses that functions beyond the immune system are likely subject to LTBS. Furthermore, several of these trait associations provide support and candidate genetic loci for previous hypothesis about behavioral diversity in human and chimpanzee populations, such as the importance of variation in risk sensitivity. Supplementary Information The online version contains supplementary material available at 10.1186/s12862-022-02020-x.
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26
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Alharbi AF, Sheng N, Nicol K, Strömberg N, Hollox EJ. Balancing selection at the human salivary agglutinin gene (DMBT1) driven by host-microbe interactions. iScience 2022; 25:104189. [PMID: 35494225 PMCID: PMC9038570 DOI: 10.1016/j.isci.2022.104189] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 02/07/2022] [Accepted: 03/30/2022] [Indexed: 11/19/2022] Open
Abstract
Discovering loci under balancing selection in humans can identify loci with alleles that affect response to the environment and disease. Genome variation data have identified the 5′ region of the DMBT1 gene as undergoing balancing selection in humans. DMBT1 encodes the pattern-recognition glycoprotein DMBT1, also known as SALSA, gp340, or salivary agglutinin. DMBT1 binds to a variety of pathogens through a tandemly arranged scavenger receptor cysteine-rich (SRCR) domain, with the number of domains polymorphic in humans. We show that the signal of balancing selection is driven by one haplotype usually carrying a shorter SRCR repeat and another usually carrying a longer SRCR repeat. DMBT1 encoded by a shorter SRCR repeat allele does not bind a cariogenic and invasive Streptococcus mutans strain, in contrast to the long SRCR allele that shows binding. Our results suggest that balancing selection at DMBT1 is due to host-microbe interactions of encoded SRCR tandem repeat alleles. Clear evidence from many analyses show balancing selection at DMBT1 Scavenger-receptor cysteine-rich domain array associated with balancing selection Genetic variation, not alternative splicing, responsible for protein isoforms Long, but not short, DMBT1 isoforms bind a cariogenic strain of Streptococcus mutans
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Affiliation(s)
- Adel F. Alharbi
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
- Medina Regional Laboratory, General Directorate of Health Affairs, Ministry of Health, Medina, Saudi Arabia
| | - Nongfei Sheng
- Department of Odontology, Umeå University, Umeå, Sweden
| | - Katie Nicol
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | | | - Edward J. Hollox
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
- Corresponding author
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27
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Maróstica AS, Nunes K, Castelli EC, Silva NSB, Weir BS, Goudet J, Meyer D. How HLA diversity is apportioned: influence of selection and relevance to transplantation. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200420. [PMID: 35430892 PMCID: PMC9014195 DOI: 10.1098/rstb.2020.0420] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
In his 1972 paper ‘The apportionment of human diversity’, Lewontin showed that, when averaged over loci, genetic diversity is predominantly attributable to differences among individuals within populations. However, selection can alter the apportionment of diversity of specific genes or genomic regions. We examine genetic diversity at the human leucocyte antigen (HLA) loci, located within the major histocompatibility complex (MHC) region. HLA genes code for proteins that are critical to adaptive immunity and are well-documented targets of balancing selection. The single-nucleotide polymorphisms (SNPs) within HLA genes show strong signatures of balancing selection on large timescales and are broadly shared among populations, displaying low FST values. However, when we analyse haplotypes defined by these SNPs (which define ‘HLA alleles’), we find marked differences in frequencies between geographic regions. These differences are not reflected in the FST values because of the extreme polymorphism at HLA loci, illustrating challenges in interpreting FST. Differences in the frequency of HLA alleles among geographic regions are relevant to bone-marrow transplantation, which requires genetic identity at HLA loci between patient and donor. We discuss the case of Brazil's bone marrow registry, where a deficit of enrolled volunteers with African ancestry reduces the chance of finding donors for individuals with an MHC region of African ancestry. This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.
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Affiliation(s)
- André Silva Maróstica
- Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Kelly Nunes
- Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Erick C. Castelli
- Departamento de Patologia, Universidade Estadual Paulista - Unesp, Faculdade de Medicina de Botucatu, Botucatu, SP, Brazil
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit, School of Medicine, São Paulo State University - Unesp, Botucatu, SP, Brazil
| | - Nayane S. B. Silva
- Molecular Genetics and Bioinformatics Laboratory, Experimental Research Unit, School of Medicine, São Paulo State University - Unesp, Botucatu, SP, Brazil
| | - Bruce S. Weir
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Jérôme Goudet
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
- Swiss Institute of Bioinformatics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Diogo Meyer
- Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, SP, Brazil
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28
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Stover DA, Housman G, Stone AC, Rosenberg MS, Verrelli BC. Evolutionary Genetic Signatures of Selection on Bone-Related Variation within Human and Chimpanzee Populations. Genes (Basel) 2022; 13:genes13020183. [PMID: 35205228 PMCID: PMC8871609 DOI: 10.3390/genes13020183] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/19/2022] [Accepted: 01/19/2022] [Indexed: 02/06/2023] Open
Abstract
Bone strength and the incidence and severity of skeletal disorders vary significantly among human populations, due in part to underlying genetic differentiation. While clinical models predict that this variation is largely deleterious, natural population variation unrelated to disease can go unnoticed, altering our perception of how natural selection has shaped bone morphologies over deep and recent time periods. Here, we conduct the first comparative population-based genetic analysis of the main bone structural protein gene, collagen type I α 1 (COL1A1), in clinical and 1000 Genomes Project datasets in humans, and in natural populations of chimpanzees. Contrary to predictions from clinical studies, we reveal abundant COL1A1 amino acid variation, predicted to have little association with disease in the natural population. We also find signatures of positive selection associated with intron haplotype structure, linkage disequilibrium, and population differentiation in regions of known gene expression regulation in humans and chimpanzees. These results recall how recent and deep evolutionary regimes can be linked, in that bone morphology differences that developed among vertebrates over 450 million years of evolution are the result of positive selection on subtle type I collagen functional variation segregating within populations over time.
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Affiliation(s)
- Daryn A. Stover
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA;
- Arizona State University at Lake Havasu, Lake Havasu, AZ 86403, USA
| | - Genevieve Housman
- Section of Genetic Medicine, University of Chicago, Chicago, IL 60637, USA;
| | - Anne C. Stone
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287, USA;
| | - Michael S. Rosenberg
- Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA 23284, USA;
| | - Brian C. Verrelli
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA;
- Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA 23284, USA;
- Correspondence:
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29
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Grace CA, Forrester S, Silva VC, Carvalho KSS, Kilford H, Chew YP, James S, Costa DL, Mottram JC, Costa CCHN, Jeffares DC. Candidates for Balancing Selection in Leishmania donovani Complex Parasites. Genome Biol Evol 2021; 13:6448231. [PMID: 34865011 PMCID: PMC8717319 DOI: 10.1093/gbe/evab265] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/22/2021] [Indexed: 12/19/2022] Open
Abstract
The Leishmania donovani species complex is the causative agent of visceral leishmaniasis, which cause 20–40,000 fatalities a year. Here, we conduct a screen for balancing selection in this species complex. We used 384 publicly available L. donovani and L. infantum genomes, and sequence 93 isolates of L. infantum from Brazil to describe the global diversity of this species complex. We identify five genetically distinct populations that are sufficiently represented by genomic data to search for signatures of selection. We find that signals of balancing selection are generally not shared between populations, consistent with transient adaptive events, rather than long-term balancing selection. We then apply multiple diversity metrics to identify candidate genes with robust signatures of balancing selection, identifying a curated set of 24 genes with robust signatures. These include zeta toxin, nodulin-like, and flagellum attachment proteins. This study highlights the extent of genetic divergence between L. donovani complex parasites and provides genes for further study.
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Affiliation(s)
- Cooper Alastair Grace
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
| | - Sarah Forrester
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
| | - Vladimir Costa Silva
- Instituto de Doenças do Sertão, Instituto de Doenças Tropicais Natan Portella, Centro de Ciências da Saúde da Universidade Federal do Piauí, Teresina-PI, Brazil
| | - Kátia Silene Sousa Carvalho
- Instituto de Doenças do Sertão, Instituto de Doenças Tropicais Natan Portella, Centro de Ciências da Saúde da Universidade Federal do Piauí, Teresina-PI, Brazil
| | - Hannah Kilford
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
| | - Yen Peng Chew
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom.,Institute of Molecular Plant Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Sally James
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
| | - Dorcas L Costa
- Instituto de Doenças do Sertão, Instituto de Doenças Tropicais Natan Portella, Centro de Ciências da Saúde da Universidade Federal do Piauí, Teresina-PI, Brazil
| | - Jeremy C Mottram
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
| | - Carlos C H N Costa
- Instituto de Doenças do Sertão, Instituto de Doenças Tropicais Natan Portella, Centro de Ciências da Saúde da Universidade Federal do Piauí, Teresina-PI, Brazil
| | - Daniel C Jeffares
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
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30
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Cheng X, DeGiorgio M. BalLeRMix +: mixture model approaches for robust joint identification of both positive selection and long-term balancing selection. Bioinformatics 2021; 38:861-863. [PMID: 34664624 PMCID: PMC8756184 DOI: 10.1093/bioinformatics/btab720] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 09/13/2021] [Accepted: 10/13/2021] [Indexed: 02/03/2023] Open
Abstract
SUMMARY The growing availability of genomewide polymorphism data has fueled interest in detecting diverse selective processes affecting population diversity. However, no model-based approaches exist to jointly detect and distinguish the two complementary processes of balancing and positive selection. We extend the BalLeRMix B-statistic framework described in Cheng and DeGiorgio (2020) for detecting balancing selection and present BalLeRMix+, which implements five B statistic extensions based on mixture models to robustly identify both types of selection. BalLeRMix+ is implemented in Python and computes the composite likelihood ratios and associated model parameters for each genomic test position. AVAILABILITY AND IMPLEMENTATION BalLeRMix+ is freely available at https://github.com/bioXiaoheng/BallerMixPlus. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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31
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Jacovas VC, Michita RT, Bisso-Machado R, Reales G, Tarazona-Santos EM, Sandoval JR, Salazar-Granara A, Chies JAB, Bortolini MC. HLA-G 3'UTR haplotype frequencies in highland and lowland South Native American populations. Hum Immunol 2021; 83:27-38. [PMID: 34563386 DOI: 10.1016/j.humimm.2021.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 08/09/2021] [Accepted: 09/01/2021] [Indexed: 11/30/2022]
Abstract
Human Leukocyte Antigen (HLA)-G participates in several biological processes, including reproduction, vascular remodeling, immune tolerance, and hypoxia response. HLA-G is a potential candidate gene for high altitude adaptation since its expression is modulated in both micro and macro environment under hypoxia and constant cellular stress. Besides the promoter region, the HLA-G 3'untranslated region (UTR) influences HLA-G expression patterns through several post-transcriptional mechanisms. Currently, the 3'UTR genetic diversity in terms of altitude adaptation of Native American populations is still unexplored, particularly at high altitude ecoregions. Here, we evaluated 288 Native Americans from 9 communities located in the Andes [highland (HL); ≥2,500 m (range = 2,838-4,433 m)] and 8 populations located in lowland (LL) regions [<2,500 m (range = 80-431 m); Amazonian tropical forest, Brazilian central plateau, and Chaco] of South America. In total, nine polymorphic sites and ten haplotypes were observed. The most frequent haplotypes (UTR-1, UTR-2, and UTR-3) accounted for ∼ 77% of haplotypes found in LL, while in the HL, the same haplotypes reach ∼ 93%. Also, a remarkable high frequency of putative ancestral UTR-5 haplotype was observed in LL (21.5%), while in HL UTR-2 reaches up to 47%. Further, UTR-2 frequency positively correlates with altitude-related variables, while a negative correlation for UTR-5 was observed. From an evolutionary perspective, we observed a tendency towards balancing selection in HL and LL populations thus suggesting that haplotypes of ancient and more derived alleles may have been co-opted for relatively recent adaptations such as those experienced by modern humans in the highland and lowland of South America. We also discuss how long-term balancing selection can be a reservoir of genetic variants that can be positively selected. Finally, our study provides some pieces of evidence that HLA-G 3'UTR haplotypes may have contributed to high altitude adaptation in the Andes.
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Affiliation(s)
- Vanessa Cristina Jacovas
- Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Rafael Tomoya Michita
- Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Human Molecular Genetics Laboratory, Universidade Luterana do Brasil (ULBRA), Canoas, Rio Grande do Sul, Brazil
| | - Rafael Bisso-Machado
- Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Guillermo Reales
- Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Eduardo M Tarazona-Santos
- Departamento de Biologia Geral, Universidade Federal de Minas Gerais, Instituto de Ciências Biológicas, Belo Horizonte, Minas Gerais, Brazil
| | - José Raul Sandoval
- Departamento de Biologia Geral, Universidade Federal de Minas Gerais, Instituto de Ciências Biológicas, Belo Horizonte, Minas Gerais, Brazil
| | | | - José Artur Bogo Chies
- Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
| | - Maria Cátira Bortolini
- Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
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32
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Aguiar VRC, Augusto DG, Castelli EC, Hollenbach JA, Meyer D, Nunes K, Petzl-Erler ML. An immunogenetic view of COVID-19. Genet Mol Biol 2021; 44:e20210036. [PMID: 34436508 PMCID: PMC8388242 DOI: 10.1590/1678-4685-gmb-2021-0036] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 06/12/2021] [Indexed: 02/06/2023] Open
Abstract
Meeting the challenges brought by the COVID-19 pandemic requires an interdisciplinary approach. In this context, integrating knowledge of immune function with an understanding of how genetic variation influences the nature of immunity is a key challenge. Immunogenetics can help explain the heterogeneity of susceptibility and protection to the viral infection and disease progression. Here, we review the knowledge developed so far, discussing fundamental genes for triggering the innate and adaptive immune responses associated with a viral infection, especially with the SARS-CoV-2 mechanisms. We emphasize the role of the HLA and KIR genes, discussing what has been uncovered about their role in COVID-19 and addressing methodological challenges of studying these genes. Finally, we comment on questions that arise when studying admixed populations, highlighting the case of Brazil. We argue that the interplay between immunology and an understanding of genetic associations can provide an important contribution to our knowledge of COVID-19.
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Affiliation(s)
- Vitor R. C. Aguiar
- Universidade de São Paulo, Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
| | - Danillo G. Augusto
- University of California, UCSF Weill Institute for Neurosciences,
Department of Neurology, San Francisco, CA, USA
- Universidade Federal do Paraná, Departamento de Genética, Curitiba,
PR, Brazil
| | - Erick C. Castelli
- Universidade Estadual Paulista, Faculdade de Medicina de Botucatu,
Departamento de Patologia, Botucatu, SP, Brazil
| | - Jill A. Hollenbach
- University of California, UCSF Weill Institute for Neurosciences,
Department of Neurology, San Francisco, CA, USA
| | - Diogo Meyer
- Universidade de São Paulo, Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
| | - Kelly Nunes
- Universidade de São Paulo, Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
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33
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Bezerra OCDL, Alvarado-Arnez LE, Mabunda N, Salomé G, de Sousa A, Kehdy FDSG, Sales-Marques C, Manta FSDN, Andrade RM, Ferreira LP, Leal-Calvo T, Cardoso CC, Nunes K, Gouveia MH, Mbulaiteve SM, Yeboah ED, Hsing A, Latini ACP, Leturiondo AL, Rodrigues FDC, Noronha AB, Ferreira CDO, Talhari C, Rêgo JL, Castellucci LCDC, Tarazona-Santos E, de Carvalho EF, Meyer D, Pinheiro RO, Jani IV, Pacheco AG, Moraes MO. Putative pathogen-selected polymorphisms in the PKLR gene are associated with mycobacterial susceptibility in Brazilian and African populations. PLoS Negl Trop Dis 2021; 15:e0009434. [PMID: 34449765 PMCID: PMC8396769 DOI: 10.1371/journal.pntd.0009434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 05/03/2021] [Indexed: 01/19/2023] Open
Abstract
Pyruvate kinase (PK), encoded by the PKLR gene, is a key player in glycolysis controlling the integrity of erythrocytes. Due to Plasmodium selection, mutations for PK deficiency, which leads to hemolytic anemia, are associated with resistance to malaria in sub-Saharan Africa and with susceptibility to intracellular pathogens in experimental models. In this case-control study, we enrolled 4,555 individuals and investigated whether PKLR single nucleotide polymorphisms (SNPs) putatively selected for malaria resistance are associated with susceptibility to leprosy across Brazil (Manaus-North; Salvador-Northeast; Rondonópolis-Midwest and Rio de Janeiro-Southeast) and with tuberculosis in Mozambique. Haplotype T/G/G (rs1052176/rs4971072/rs11264359) was associated with leprosy susceptibility in Rio de Janeiro (OR = 2.46, p = 0.00001) and Salvador (OR = 1.57, p = 0.04), and with tuberculosis in Mozambique (OR = 1.52, p = 0.07). This haplotype downregulates PKLR expression in nerve and skin, accordingly to GTEx, and might subtly modulate ferritin and haptoglobin levels in serum. Furthermore, we observed genetic signatures of positive selection in the HCN3 gene (xpEHH>2 -recent selection) in Europe but not in Africa, involving 6 SNPs which are PKLR/HCN3 eQTLs. However, this evidence was not corroborated by the other tests (FST, Tajima's D and iHS). Altogether, we provide evidence that a common PKLR locus in Africans contribute to mycobacterial susceptibility in African descent populations and also highlight, for first, PKLR as a susceptibility gene for leprosy and TB.
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Affiliation(s)
| | - Lucia Elena Alvarado-Arnez
- Laboratory of Leprosy, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro, Brazil
- National Research Coordination, Franz Tamayo University (UNIFRAZ), Cochabamba, Bolivia
| | - Nédio Mabunda
- Laboratory of Molecular Virology, Instituto Nacional de Saúde, Maputo, Mozambique
| | - Graça Salomé
- Medical Faculty, Eduardo Mondlane University, Maputo, Mozambique
| | - Amina de Sousa
- Laboratory of Molecular Virology, Instituto Nacional de Saúde, Maputo, Mozambique
| | | | - Carolinne Sales-Marques
- Laboratory of Leprosy, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro, Brazil
- Laboratory of Cellular Biology and Genetics, Federal University of Alagoas, Arapiraca, Brazil
| | | | | | | | - Thyago Leal-Calvo
- Laboratory of Leprosy, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro, Brazil
| | - Cynthia Chester Cardoso
- Laboratory of Leprosy, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro, Brazil
- Laboratory of Molecular Virology, Department of Genetics, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Kelly Nunes
- Laboratory of Evolutionary Genetics and Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Mateus H. Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Sam M. Mbulaiteve
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Ann Hsing
- Stanford Cancer Institute, Stanford University, Stanford, California, United States of America
| | | | | | | | | | | | - Carolina Talhari
- Laboratory of Molecular Biology, Alfredo da Matta Foundation, Manaus, Brazil
| | - Jamile Leão Rêgo
- Immunology Service, Professor Edgard Santos University Hospital, Federal University of Bahia, Salvador, Brazil
| | | | - Eduardo Tarazona-Santos
- Departament of Biology, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | | | - Diogo Meyer
- Laboratory of Evolutionary Genetics and Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | | | - Ilesh V. Jani
- Laboratory of Molecular Virology, Instituto Nacional de Saúde, Maputo, Mozambique
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34
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Bourgeois Y, Fields P, Bento G, Ebert D. Balancing selection for pathogen resistance reveals an intercontinental signature of Red Queen coevolution. Mol Biol Evol 2021; 38:4918-4933. [PMID: 34289047 PMCID: PMC8557431 DOI: 10.1093/molbev/msab217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The link between long-term host–parasite coevolution and genetic diversity is key to understanding genetic epidemiology and the evolution of resistance. The model of Red Queen host–parasite coevolution posits that high genetic diversity is maintained when rare host resistance variants have a selective advantage, which is believed to be the mechanistic basis for the extraordinarily high levels of diversity at disease-related genes such as the major histocompatibility complex in jawed vertebrates and R-genes in plants. The parasites that drive long-term coevolution are, however, often elusive. Here we present evidence for long-term balancing selection at the phenotypic (variation in resistance) and genomic (resistance locus) level in a particular host–parasite system: the planktonic crustacean Daphnia magna and the bacterium Pasteuria ramosa. The host shows widespread polymorphisms for pathogen resistance regardless of geographic distance, even though there is a clear genome-wide pattern of isolation by distance at other sites. In the genomic region of a previously identified resistance supergene, we observed consistent molecular signals of balancing selection, including higher genetic diversity, older coalescence times, and lower differentiation between populations, which set this region apart from the rest of the genome. We propose that specific long-term coevolution by negative-frequency-dependent selection drives this elevated diversity at the host's resistance loci on an intercontinental scale and provide an example of a direct link between the host’s resistance to a virulent pathogen and the large-scale diversity of its underlying genes.
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Affiliation(s)
- Yann Bourgeois
- University of Basel, Department of Environmental Sciences, Zoology, Vesalgasse 1, 4051 Basel, Switzerland
| | - Peter Fields
- University of Basel, Department of Environmental Sciences, Zoology, Vesalgasse 1, 4051 Basel, Switzerland
| | - Gilberto Bento
- University of Basel, Department of Environmental Sciences, Zoology, Vesalgasse 1, 4051 Basel, Switzerland
| | - Dieter Ebert
- University of Basel, Department of Environmental Sciences, Zoology, Vesalgasse 1, 4051 Basel, Switzerland
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35
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Hollox EJ, Zuccherato LW, Tucci S. Genome structural variation in human evolution. Trends Genet 2021; 38:45-58. [PMID: 34284881 DOI: 10.1016/j.tig.2021.06.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/21/2021] [Accepted: 06/22/2021] [Indexed: 01/01/2023]
Abstract
Structural variation (SV) is a large difference (typically >100 bp) in the genomic structure of two genomes and includes both copy number variation and variation that does not change copy number of a genomic region, such as an inversion. Improved reference genomes, combined with widespread genome sequencing using short-read sequencing technology, and increasingly using long-read sequencing, have reignited interest in SV. Recent large-scale studies and functional focused analyses have highlighted the role of SV in human evolution. In this review, we highlight human-specific SVs involved in changes in the brain, population-specific SVs that affect response to the environment, including adaptation to diet and infectious diseases, and summarise the contribution of archaic hominin admixture to present-day human SV.
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Affiliation(s)
- Edward J Hollox
- Department of Genetics and Genome Biology, University of Leicester, UK.
| | - Luciana W Zuccherato
- Núcleo de Ensino e Pesquisa, Instituto Mário Penna, Belo Horizonte, Brazil; Departmento de Bioquímica e Imunologia, Universidade de Minas Gerais, Belo Horizonte, Brazil
| | - Serena Tucci
- Department of Anthropology, Yale University, New Haven, CT, USA
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36
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Nunes K, Maia MHT, Dos Santos EJM, Dos Santos SEB, Guerreiro JF, Petzl-Erler ML, Bedoya G, Gallo C, Poletti G, Llop E, Tsuneto L, Bortolini MC, Rothhammer F, Single R, Ruiz-Linares A, Rocha J, Meyer D. How natural selection shapes genetic differentiation in the MHC region: A case study with Native Americans. Hum Immunol 2021; 82:523-531. [PMID: 33812704 PMCID: PMC8217218 DOI: 10.1016/j.humimm.2021.03.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 02/15/2021] [Accepted: 03/09/2021] [Indexed: 12/19/2022]
Abstract
The Human Leukocyte Antigen (HLA) loci are extremely well documented targets of balancing selection, yet few studies have explored how selection affects population differentiation at these loci. In the present study we investigate genetic differentiation at HLA genes by comparing differentiation at microsatellites distributed genomewide to those in the MHC region. Our study uses a sample of 494 individuals from 30 human populations, 28 of which are Native Americans, all of whom were typed for genomewide and MHC region microsatellites. We find greater differentiation in the MHC than in the remainder of the genome (FST-MHC = 0.130 and FST-Genomic = 0.087), and use a permutation approach to show that this difference is statistically significant, and not accounted for by confounding factors. This finding lies in the opposite direction to the expectation that balancing selection reduces population differentiation. We interpret our findings as evidence that selection favors different sets of alleles in distinct localities, leading to increased differentiation. Thus, balancing selection at HLA genes simultaneously increases intra-population polymorphism and inter-population differentiation in Native Americans.
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Affiliation(s)
- Kelly Nunes
- Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, Brazil.
| | | | | | | | | | | | - Gabriel Bedoya
- Instituto de Biología, Universidad de Antioquia, Medellín, Colombia
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Giovanni Poletti
- Facultad de Medicina, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Elena Llop
- Instituto de Ciencias Biomédicas, Faculdad de Medicina, Universidade de Chile, Santiago, Chile
| | - Luiza Tsuneto
- Departamento de Ciências Básicas da Saúde, Universidade Estadual de Maringá, Maringá, Brazil
| | - Maria Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | | | - Richard Single
- Department of Mathematics and Statistics, University of Vermont, Burlington, VT, USA
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai 200433, China; D Aix-Marseille University, CNRS, EFS, ADES, Marseille 13007, France
| | - Jorge Rocha
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal; CIBIO - Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Porto, Portugal.
| | - Diogo Meyer
- Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, Brazil.
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37
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Liu Q, Mishra M, Saxena AS, Wu H, Qiu Y, Zhang X, You X, Ding S, Miyamoto MM. Balancing selection maintains ancient polymorphisms at conserved enhancers for the olfactory receptor genes of a Chinese marine fish. Mol Ecol 2021; 30:4023-4038. [PMID: 34107131 DOI: 10.1111/mec.16016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 05/10/2021] [Accepted: 06/01/2021] [Indexed: 12/22/2022]
Abstract
The study of balancing selection, as a selective force maintaining adaptive genetic variation in gene pools longer than expected by drift, is currently experiencing renewed interest due to the increased availability of new data, methods of analysis, and case studies. In this investigation, evidence of balancing selection operating on conserved enhancers of the olfactory receptor (OR) genes is presented for the Chinese sleeper (Bostrychus sinensis), a coastal marine fish that is emerging as a model species for evolutionary studies in the Northwest Pacific marginal seas. Coupled with tests for Gene Ontology enrichment and transcription factor binding, population genomic data allow for the identification of an OR cluster in the sleeper with a downstream flanking region containing three enhancers that are conserved with human and other fish species. Phylogenetic and population genetic analyses indicate that the enhancers are under balancing selection as evidenced by their translineage polymorphisms, excess common alleles, and increased within-group diversities. Age comparisons between the translineage polymorphisms and most recent common ancestors of neutral genealogies substantiate that the former are old, and thus, due to ancient balancing selection. The survival and reproduction of vertebrates depend on their sense of smell, and thereby, on their ORs. In addition to locus duplication and allelic variation of structural genes, this study highlights a third mechanism by which receptor diversity can be achieved for detecting and responding to the huge variety of environmental odorants (i.e., by balancing selection acting on OR gene expression through their enhancer variability).
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Affiliation(s)
- Qiaohong Liu
- Xiamen Key Laboratory of Urban Sea Ecological Conservation and Restoration, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Mrinal Mishra
- Department of Biology, University of Florida, Gainesville, FL, USA
| | - Ayush S Saxena
- Department of Biology, University of Florida, Gainesville, FL, USA
| | - Haohao Wu
- Xiamen Key Laboratory of Urban Sea Ecological Conservation and Restoration, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Ying Qiu
- Shenzhen Key Laboratory of Marine Genomics, Guangdong Provincial Key Laboratory of Molecular Breeding in Marine Economic Animals, BGI Academy of Sciences, BGI Marine, Shenzhen, China
| | - Xinhui Zhang
- Shenzhen Key Laboratory of Marine Genomics, Guangdong Provincial Key Laboratory of Molecular Breeding in Marine Economic Animals, BGI Academy of Sciences, BGI Marine, Shenzhen, China
| | - Xinxin You
- Shenzhen Key Laboratory of Marine Genomics, Guangdong Provincial Key Laboratory of Molecular Breeding in Marine Economic Animals, BGI Academy of Sciences, BGI Marine, Shenzhen, China
| | - Shaoxiong Ding
- Xiamen Key Laboratory of Urban Sea Ecological Conservation and Restoration, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
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38
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Bourgeois YXC, Warren BH. An overview of current population genomics methods for the analysis of whole-genome resequencing data in eukaryotes. Mol Ecol 2021; 30:6036-6071. [PMID: 34009688 DOI: 10.1111/mec.15989] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 04/26/2021] [Accepted: 05/11/2021] [Indexed: 01/01/2023]
Abstract
Characterizing the population history of a species and identifying loci underlying local adaptation is crucial in functional ecology, evolutionary biology, conservation and agronomy. The constant improvement of high-throughput sequencing techniques has facilitated the production of whole genome data in a wide range of species. Population genomics now provides tools to better integrate selection into a historical framework, and take into account selection when reconstructing demographic history. However, this improvement has come with a profusion of analytical tools that can confuse and discourage users. Such confusion limits the amount of information effectively retrieved from complex genomic data sets, and impairs the diffusion of the most recent analytical tools into fields such as conservation biology. It may also lead to redundancy among methods. To address these isssues, we propose an overview of more than 100 state-of-the-art methods that can deal with whole genome data. We summarize the strategies they use to infer demographic history and selection, and discuss some of their limitations. A website listing these methods is available at www.methodspopgen.com.
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Affiliation(s)
| | - Ben H Warren
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum National d'Histoire Naturelle, CNRS, Sorbonne Université, EPHE, UA, CP 51, Paris, France
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39
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Vogl C, Mikula LC. A nearly-neutral biallelic Moran model with biased mutation and linear and quadratic selection. Theor Popul Biol 2021; 139:1-17. [PMID: 33964284 DOI: 10.1016/j.tpb.2021.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 03/28/2021] [Accepted: 03/29/2021] [Indexed: 01/27/2023]
Abstract
In this article, a biallelic reversible mutation model with linear and quadratic selection is analysed. The approach reconnects to one proposed by Kimura (1979), who starts from a diffusion model and derives its equilibrium distribution up to a constant. We use a boundary-mutation Moran model, which approximates a general mutation model for small effective mutation rates, and derive its equilibrium distribution for polymorphic and monomorphic variants in small to moderately sized populations. Using this model, we show that biased mutation rates and linear selection alone can cause patterns of polymorphism within and substitution rates between populations that are usually ascribed to balancing or overdominant selection. We illustrate this using a data set of short introns and fourfold degenerate sites from Drosophila simulans and Drosophila melanogaster.
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Affiliation(s)
- Claus Vogl
- Department of Biomedical Sciences, Vetmeduni Vienna, Veterinärplatz 1, A-1210 Wien, Austria; Vienna Graduate School of Population Genetics, A-1210 Wien, Austria.
| | - Lynette Caitlin Mikula
- Centre for Biological Diversity, School of Biology, University of St. Andrews, St Andrews KY16 9TH, UK.
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40
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Meisel RP. The maintenance of polygenic sex determination depends on the dominance of fitness effects which are predictive of the role of sexual antagonism. G3 (BETHESDA, MD.) 2021; 11:6261074. [PMID: 33930135 PMCID: PMC8496315 DOI: 10.1093/g3journal/jkab149] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 04/23/2021] [Indexed: 12/18/2022]
Abstract
In species with polygenic sex determination (PSD), multiple male- and female-determining loci on different proto-sex chromosomes segregate as polymorphisms within populations. The extent to which these polymorphisms are at stable equilibria is not yet resolved. Previous work demonstrated that PSD is most likely to be maintained as a stable polymorphism when the proto-sex chromosomes have opposite (sexually antagonistic) fitness effects in males and females. However, these models usually consider PSD systems with only two proto-sex chromosomes, or they do not broadly consider the dominance of the alleles under selection. To address these shortcomings, I used forward population genetic simulations to identify selection pressures that can maintain PSD under different dominance scenarios in a system with more than two proto-sex chromosomes (modeled after the house fly). I found that overdominant fitness effects of male-determining proto-Y chromosomes are more likely to maintain PSD than dominant, recessive, or additive fitness effects. The overdominant fitness effects that maintain PSD tend to have proto-Y chromosomes with sexually antagonistic effects (male-beneficial and female-detrimental). In contrast, dominant fitness effects that maintain PSD tend to have sexually antagonistic multi-chromosomal genotypes, but the individual proto-sex chromosomes do not have sexually antagonistic effects. These results demonstrate that sexual antagonism can be an emergent property of the multi-chromosome genotype without individual sexually antagonistic chromosomes. My results further illustrate how the dominance of fitness effects has consequences for both the likelihood that PSD will be maintained as well as the role sexually antagonistic selection is expected to play in maintaining the polymorphism.
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Affiliation(s)
- Richard P Meisel
- Department of Biology and Biochemistry, University of Houston, Houston, TX 77204, USA
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41
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Zeng K, Charlesworth B, Hobolth A. Studying models of balancing selection using phase-type theory. Genetics 2021; 218:6237896. [PMID: 33871627 DOI: 10.1093/genetics/iyab055] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 03/25/2021] [Indexed: 11/15/2022] Open
Abstract
Balancing selection (BLS) is the evolutionary force that maintains high levels of genetic variability in many important genes. To further our understanding of its evolutionary significance, we analyze models with BLS acting on a biallelic locus: an equilibrium model with long-term BLS, a model with long-term BLS and recent changes in population size, and a model of recent BLS. Using phase-type theory, a mathematical tool for analyzing continuous time Markov chains with an absorbing state, we examine how BLS affects polymorphism patterns in linked neutral regions, as summarized by nucleotide diversity, the expected number of segregating sites, the site frequency spectrum, and the level of linkage disequilibrium (LD). Long-term BLS affects polymorphism patterns in a relatively small genomic neighborhood, and such selection targets are easier to detect when the equilibrium frequencies of the selected variants are close to 50%, or when there has been a population size reduction. For a new mutation subject to BLS, its initial increase in frequency in the population causes linked neutral regions to have reduced diversity, an excess of both high and low frequency derived variants, and elevated LD with the selected locus. These patterns are similar to those produced by selective sweeps, but the effects of recent BLS are weaker. Nonetheless, compared to selective sweeps, nonequilibrium polymorphism and LD patterns persist for a much longer period under recent BLS, which may increase the chance of detecting such selection targets. An R package for analyzing these models, among others (e.g., isolation with migration), is available.
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Affiliation(s)
- Kai Zeng
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Asger Hobolth
- Department of Mathematics, Aarhus University, Aarhus DK-8000, Denmark
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42
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Tennessen JA, Duraisingh MT. Three Signatures of Adaptive Polymorphism Exemplified by Malaria-Associated Genes. Mol Biol Evol 2021; 38:1356-1371. [PMID: 33185667 PMCID: PMC8042748 DOI: 10.1093/molbev/msaa294] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Malaria has been one of the strongest selective pressures on our species. Many of the best-characterized cases of adaptive evolution in humans are in genes tied to malaria resistance. However, the complex evolutionary patterns at these genes are poorly captured by standard scans for nonneutral evolution. Here, we present three new statistical tests for selection based on population genetic patterns that are observed more than once among key malaria resistance loci. We assess these tests using forward-time evolutionary simulations and apply them to global whole-genome sequencing data from humans, and thus we show that they are effective at distinguishing selection from neutrality. Each test captures a distinct evolutionary pattern, here called Divergent Haplotypes, Repeated Shifts, and Arrested Sweeps, associated with a particular period of human prehistory. We clarify the selective signatures at known malaria-relevant genes and identify additional genes showing similar adaptive evolutionary patterns. Among our top outliers, we see a particular enrichment for genes involved in erythropoiesis and for genes previously associated with malaria resistance, consistent with a major role for malaria in shaping these patterns of genetic diversity. Polymorphisms at these genes are likely to impact resistance to malaria infection and contribute to ongoing host-parasite coevolutionary dynamics.
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43
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Reinscheid RK, Mafessoni F, Lüttjohann A, Jüngling K, Pape HC, Schulz S. Neandertal introgression and accumulation of hypomorphic mutations in the neuropeptide S (NPS) system promote attenuated functionality. Peptides 2021; 138:170506. [PMID: 33556445 DOI: 10.1016/j.peptides.2021.170506] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 01/14/2021] [Accepted: 02/03/2021] [Indexed: 12/21/2022]
Abstract
The neuropeptide S (NPS) system plays an important role in fear and fear memory processing but has also been associated with allergic and inflammatory diseases. Genes for NPS and its receptor NPSR1 are found in all tetrapods. Compared to non-human primates, several non-synonymous single-nucleotide polymorphisms (SNPs) occur in both human genes that collectively result in functional attenuation, suggesting adaptive mechanisms in a human context. To investigate historic and geographic origins of these hypomorphic mutations and explore genetic signs of selection, we analyzed ancient genomes and worldwide genotype frequencies of four prototypic SNPs in the NPS system. Neandertal and Denisovan genomes contain exclusively ancestral alleles for NPSR1 while all derived alleles occur in ancient genomes of anatomically modern humans, indicating that they arose in modern Homo sapiens. Worldwide genotype frequencies for three hypomorphic NPSR1 SNPs show significant regional homogeneity but follow a gradient towards increasing derived allele frequencies that supports an out-of-Africa scenario. Increased density of high-frequency polymorphisms around the three NPSR1 loci suggests weak or possibly balancing selection. A hypomorphic mutation in the NPS precursor, however, was detected at high frequency in Eurasian Neandertal genomes and shows genetic signatures indicating that it was introgressed into the human gene pool, particularly in Southern Europe, by interbreeding with Neandertals. We discuss potential evolutionary scenarios including behavior and immune-based natural selection.
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Affiliation(s)
- Rainer K Reinscheid
- Institute of Pharmacology & Toxicology, Friedrich-Schiller-University, Jena, Germany; Institute of Physiology I, Westfälische-Wilhelms-University, Münster, Germany.
| | | | - Annika Lüttjohann
- Institute of Physiology I, Westfälische-Wilhelms-University, Münster, Germany
| | - Kay Jüngling
- Institute of Physiology I, Westfälische-Wilhelms-University, Münster, Germany
| | - Hans-Christian Pape
- Institute of Physiology I, Westfälische-Wilhelms-University, Münster, Germany
| | - Stefan Schulz
- Institute of Pharmacology & Toxicology, Friedrich-Schiller-University, Jena, Germany
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44
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Abstract
Age is a common risk factor in many diseases, but the molecular basis for this relationship is elusive. In this study we identified 4 disease clusters from 116 diseases in the UK Biobank data, defined by their age-of-onset profiles, and found that diseases with the same onset profile are genetically more similar, suggesting a common etiology. This similarity was not explained by disease categories, co-occurrences or disease cause-effect relationships. Two of the four disease clusters had an increased risk of occurrence from age 20 and 40 years respectively. They both showed an association with known aging-related genes, yet differed in functional enrichment and evolutionary profiles. Moreover, they both had age-related expression and methylation changes. We also tested mutation accumulation and antagonistic pleiotropy theories of aging and found support for both.
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45
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Isildak U, Stella A, Fumagalli M. Distinguishing between recent balancing selection and incomplete sweep using deep neural networks. Mol Ecol Resour 2021; 21:2706-2718. [PMID: 33749134 DOI: 10.1111/1755-0998.13379] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 03/01/2021] [Accepted: 03/05/2021] [Indexed: 12/12/2022]
Abstract
Balancing selection is an important adaptive mechanism underpinning a wide range of phenotypes. Despite its relevance, the detection of recent balancing selection from genomic data is challenging as its signatures are qualitatively similar to those left by ongoing positive selection. In this study, we developed and implemented two deep neural networks and tested their performance to predict loci under recent selection, either due to balancing selection or incomplete sweep, from population genomic data. Specifically, we generated forward-in-time simulations to train and test an artificial neural network (ANN) and a convolutional neural network (CNN). ANN received as input multiple summary statistics calculated on the locus of interest, while CNN was applied directly on the matrix of haplotypes. We found that both architectures have high accuracy to identify loci under recent selection. CNN generally outperformed ANN to distinguish between signals of balancing selection and incomplete sweep and was less affected by incorrect training data. We deployed both trained networks on neutral genomic regions in European populations and demonstrated a lower false-positive rate for CNN than ANN. We finally deployed CNN within the MEFV gene region and identified several common variants predicted to be under incomplete sweep in a European population. Notably, two of these variants are functional changes and could modulate susceptibility to familial Mediterranean fever, possibly as a consequence of past adaptation to pathogens. In conclusion, deep neural networks were able to characterize signals of selection on intermediate frequency variants, an analysis currently inaccessible by commonly used strategies.
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Affiliation(s)
- Ulas Isildak
- Department of Biological Sciences, Middle East Technical University, Ankara, Turkey
| | - Alessandro Stella
- Laboratory of Medical Genetics, Department of Biomedical Sciences and Human Oncology, Università degli Studi di Bari Aldo Moro, Bari, Italy
| | - Matteo Fumagalli
- Department of Life Sciences, Silwood Park Campus, Imperial College London, London, UK
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46
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Long X, Xue H. Genetic-variant hotspots and hotspot clusters in the human genome facilitating adaptation while increasing instability. Hum Genomics 2021; 15:19. [PMID: 33741065 PMCID: PMC7976700 DOI: 10.1186/s40246-021-00318-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 03/04/2021] [Indexed: 12/25/2022] Open
Abstract
Background Genetic variants, underlining phenotypic diversity, are known to distribute unevenly in the human genome. A comprehensive understanding of the distributions of different genetic variants is important for insights into genetic functions and disorders. Methods Herein, a sliding-window scan of regional densities of eight kinds of germline genetic variants, including single-nucleotide-polymorphisms (SNPs) and four size-classes of copy-number-variations (CNVs) in the human genome has been performed. Results The study has identified 44,379 hotspots with high genetic-variant densities, and 1135 hotspot clusters comprising more than one type of hotspots, accounting for 3.1% and 0.2% of the genome respectively. The hotspots and clusters are found to co-localize with different functional genomic features, as exemplified by the associations of hotspots of middle-size CNVs with histone-modification sites, work with balancing and positive selections to meet the need for diversity in immune proteins, and facilitate the development of sensory-perception and neuroactive ligand-receptor interaction pathways in the function-sparse late-replicating genomic sequences. Genetic variants of different lengths co-localize with retrotransposons of different ages on a “long-with-young” and “short-with-all” basis. Hotspots and clusters are highly associated with tumor suppressor genes and oncogenes (p < 10−10), and enriched with somatic tumor CNVs and the trait- and disease-associated SNPs identified by genome-wise association studies, exceeding tenfold enrichment in clusters comprising SNPs and extra-long CNVs. Conclusions In conclusion, the genetic-variant hotspots and clusters represent two-edged swords that spearhead both positive and negative genomic changes. Their strong associations with complex traits and diseases also open up a potential “Common Disease-Hotspot Variant” approach to the missing heritability problem. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-021-00318-3.
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Affiliation(s)
- Xi Long
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China.,HKUST Shenzhen Research Institute, 9 Yuexing First Road, Nanshan, Shenzhen, China
| | - Hong Xue
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China. .,HKUST Shenzhen Research Institute, 9 Yuexing First Road, Nanshan, Shenzhen, China. .,Centre for Cancer Genomics, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
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47
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Siewert KM, Voight BF. BetaScan2: Standardized Statistics to Detect Balancing Selection Utilizing Substitution Data. Genome Biol Evol 2020; 12:3873-3877. [PMID: 32011695 PMCID: PMC7058154 DOI: 10.1093/gbe/evaa013] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2020] [Indexed: 12/24/2022] Open
Abstract
Long-term balancing selection results in a build-up of alleles at similar frequencies and a deficit of substitutions when compared with an outgroup at a locus. The previously published β(1) statistics detect balancing selection using only polymorphism data. We now propose the β(2) statistic which detects balancing selection using both polymorphism and substitution data. In addition, we derive the variance of all β statistics, allowing for their standardization and thereby reducing the influence of parameters which can confound other selection tests. The standardized β statistics outperform existing summary statistics in simulations, indicating β is a well-powered and widely applicable approach for detecting balancing selection. We apply the β(2) statistic to 1000 Genomes data and report two missense mutations with high β scores in the ACSBG2 gene. An implementation of all β statistics and their standardization are available in the BetaScan2 software package at https://github.com/ksiewert/BetaScan.
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Affiliation(s)
- Katherine M Siewert
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania
| | - Benjamin F Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania.,Department of Genetics, Perelman School of Medicine, University of Pennsylvania.,Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania
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48
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Browning SR, Browning BL. Probabilistic Estimation of Identity by Descent Segment Endpoints and Detection of Recent Selection. Am J Hum Genet 2020; 107:895-910. [PMID: 33053335 PMCID: PMC7553009 DOI: 10.1016/j.ajhg.2020.09.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 09/25/2020] [Indexed: 12/18/2022] Open
Abstract
Most methods for fast detection of identity by descent (IBD) segments report identity by state segments without any quantification of the uncertainty in the endpoints and lengths of the IBD segments. We present a method for determining the posterior probability distribution of IBD segment endpoints. Our approach accounts for genotype errors, recent mutations, and gene conversions which disrupt DNA sequence identity within IBD segments, and it can be applied to large cohorts with whole-genome sequence or SNP array data. We find that our method's estimates of uncertainty are well calibrated for homogeneous samples. We quantify endpoint uncertainty for 77.7 billion IBD segments from 408,883 individuals of white British ancestry in the UK Biobank, and we use these IBD segments to find regions showing evidence of recent natural selection. We show that many spurious selection signals are eliminated by the use of unbiased estimates of IBD segment endpoints and a pedigree-based genetic map. Eleven of the twelve regions with the greatest evidence for recent selection in our scan have been identified as selected in previous analyses using different approaches. Our computationally efficient method for quantifying IBD segment endpoint uncertainty is implemented in the open source ibd-ends software package.
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Affiliation(s)
- Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
| | - Brian L Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
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49
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50
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Cheng X, DeGiorgio M. Flexible Mixture Model Approaches That Accommodate Footprint Size Variability for Robust Detection of Balancing Selection. Mol Biol Evol 2020; 37:3267-3291. [PMID: 32462188 PMCID: PMC7820363 DOI: 10.1093/molbev/msaa134] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. They also display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Moreover, we applied a specific version of the B statistics, termed B2, to a human population-genomic data set and recovered many top candidates from prior studies, including the then-uncharacterized STPG2 and CCDC169-SOHLH2, both of which are related to gamete functions. We further applied B2 on a bonobo population-genomic data set. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and SCN9A, associated with pain perception. Finally, we show that our methods can be extended to account for multiallelic balancing selection and integrated the set of statistics into open-source software named BalLeRMix for future applications by the scientific community.
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Affiliation(s)
- Xiaoheng Cheng
- Huck Institutes of Life Sciences, Pennsylvania State University, University Park, PA
- Department of Biology, Pennsylvania State University, University Park, PA
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL
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