1
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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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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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3
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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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4
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Zhou Y, Song L, Li H. Full resolution HLA and KIR genes annotation for human genome assemblies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576452. [PMID: 38328160 PMCID: PMC10849470 DOI: 10.1101/2024.01.20.576452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The HLA (Human Leukocyte Antigen) genes and the KIR (Killer cell Immunoglobulin-like Receptor) genes are critical to immune responses and are associated with many immune-related diseases. Located in highly polymorphic regions, they are hard to be studied with traditional short-read alignment-based methods. Although modern long-read assemblers can often assemble these genes, using existing tools to annotate HLA and KIR genes in these assemblies remains a non-trivial task. Here, we describe Immuannot, a new computation tool to annotate the gene structures of HLA and KIR genes and to type the allele of each gene. Applying Immuannot to 56 regional and 212 whole-genome assemblies from previous studies, we annotated 9,931 HLA and KIR genes and found that almost half of these genes, 4,068, had novel sequences compared to the current Immuno Polymorphism Database (IPD). These novel gene sequences were represented by 2,664 distinct alleles, some of which contained non-synonymous variations resulting in 92 novel protein sequences. We demonstrated the complex haplotype structures at the two loci and reported the linkage between HLA/KIR haplotypes and gene alleles. We anticipate that Immuannot will speed up the discovery of new HLA/KIR alleles and enable the association of HLA/KIR haplotype structures with clinical outcomes in the future.
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Affiliation(s)
- Ying Zhou
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
| | - Li Song
- Department of Biomedical Data Science, Dartmouth College, Hanover, NH, 03755, USA
| | - Heng Li
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
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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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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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7
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Zhao S, Chi L, Chen H. CEGA: a method for inferring natural selection by comparative population genomic analysis across species. Genome Biol 2023; 24:219. [PMID: 37789379 PMCID: PMC10548728 DOI: 10.1186/s13059-023-03068-8] [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: 07/26/2022] [Accepted: 09/20/2023] [Indexed: 10/05/2023] Open
Abstract
We developed maximum likelihood method for detecting positive selection or balancing selection using multilocus or genomic polymorphism and divergence data from two species. The method is especially useful for investigating natural selection in noncoding regions. Simulations demonstrate that the method outperforms existing methods in detecting both positive and balancing selection. We apply the method to population genomic data from human and chimpanzee. The list of genes identified under selection in the noncoding regions is prominently enriched in pathways related to the brain and nervous system. Therefore, our method will serve as a useful tool for comparative population genomic analysis.
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Affiliation(s)
- Shilei Zhao
- CAS Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
- China National Center for Bioinformation, Beijing, 100101, China
- School of Future Technology, College of Life Sciences and Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lianjiang Chi
- CAS Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
- China National Center for Bioinformation, Beijing, 100101, China
| | - Hua Chen
- CAS Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.
- China National Center for Bioinformation, Beijing, 100101, China.
- School of Future Technology, College of Life Sciences and Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100049, China.
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
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8
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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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9
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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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10
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Schield DR, Perry BW, Adams RH, Holding ML, Nikolakis ZL, Gopalan SS, Smith CF, Parker JM, Meik JM, DeGiorgio M, Mackessy SP, Castoe TA. The roles of balancing selection and recombination in the evolution of rattlesnake venom. Nat Ecol Evol 2022; 6:1367-1380. [PMID: 35851850 PMCID: PMC9888523 DOI: 10.1038/s41559-022-01829-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 06/15/2022] [Indexed: 02/02/2023]
Abstract
The origin of snake venom involved duplication and recruitment of non-venom genes into venom systems. Several studies have predicted that directional positive selection has governed this process. Venom composition varies substantially across snake species and venom phenotypes are locally adapted to prey, leading to coevolutionary interactions between predator and prey. Venom origins and contemporary snake venom evolution may therefore be driven by fundamentally different selection regimes, yet investigations of population-level patterns of selection have been limited. Here, we use whole-genome data from 68 rattlesnakes to test hypotheses about the factors that drive genomic diversity and differentiation in major venom gene regions. We show that selection has resulted in long-term maintenance of genetic diversity within and between species in multiple venom gene families. Our findings are inconsistent with a dominant role of directional positive selection and instead support a role of long-term balancing selection in shaping venom evolution. We also detect rapid decay of linkage disequilibrium due to high recombination rates in venom regions, suggesting that venom genes have reduced selective interference with nearby loci, including other venom paralogues. Our results provide an example of long-term balancing selection that drives trans-species polymorphism and help to explain how snake venom keeps pace with prey resistance.
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Affiliation(s)
- Drew R Schield
- Department of Biology, University of Texas at Arlington, Arlington, TX, USA.
- Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA.
| | - Blair W Perry
- Department of Biology, University of Texas at Arlington, Arlington, TX, USA
- School of Biological Sciences, Washington State University, Pullman, WA, USA
| | - Richard H Adams
- Department of Biological and Environmental Sciences, Georgia College and State University, Milledgeville, GA, USA
| | | | | | | | - Cara F Smith
- School of Biological Sciences, University of Northern Colorado, Greeley, CO, USA
| | - Joshua M Parker
- Life Science Department, Fresno City College, Fresno, CA, USA
| | - Jesse M Meik
- Department of Biological Sciences, Tarleton State University, Stephenville, TX, USA
| | - Michael DeGiorgio
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA
| | - Stephen P Mackessy
- School of Biological Sciences, University of Northern Colorado, Greeley, CO, USA
| | - Todd A Castoe
- Department of Biology, University of Texas at Arlington, Arlington, TX, USA.
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11
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Ruzicka F, Holman L, Connallon T. 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] [MESH Headings] [Grants] [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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Affiliation(s)
- Filip Ruzicka
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
| | - Luke Holman
- School of BioSciences, University of Melbourne, Parkville, Victoria, Australia
- School of Applied Sciences, Edinburgh Napier University, Edinburgh, United Kingdom
| | - Tim Connallon
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
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12
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Setter D, Ebdon S, Jackson B, Lohse K. Estimating the rates of crossover and gene conversion from individual genomes. Genetics 2022; 222:iyac100. [PMID: 35771626 PMCID: PMC9434185 DOI: 10.1093/genetics/iyac100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 06/01/2022] [Indexed: 11/14/2022] Open
Abstract
Recombination can occur either as a result of crossover or gene conversion events. Population genetic methods for inferring the rate of recombination from patterns of linkage disequilibrium generally assume a simple model of recombination that only involves crossover events and ignore gene conversion. However, distinguishing the 2 processes is not only necessary for a complete description of recombination, but also essential for understanding the evolutionary consequences of inversions and other genomic partitions in which crossover (but not gene conversion) is reduced. We present heRho, a simple composite likelihood scheme for coestimating the rate of crossover and gene conversion from individual diploid genomes. The method is based on analytic results for the distance-dependent probability of heterozygous and homozygous states at 2 loci. We apply heRho to simulations and data from the house mouse Mus musculus castaneus, a well-studied model. Our analyses show (1) that the rates of crossover and gene conversion can be accurately coestimated at the level of individual chromosomes and (2) that previous estimates of the population scaled rate of recombination ρ=4Ner under a pure crossover model are likely biased.
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Affiliation(s)
- Derek Setter
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Sam Ebdon
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Ben Jackson
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Konrad Lohse
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
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13
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Persani L, Campi I. Variation in Thyroid Hormone Metabolism May Affect COVID-19 Outcome. J Clin Endocrinol Metab 2022; 107:e3078-e3079. [PMID: 35325144 PMCID: PMC8992329 DOI: 10.1210/clinem/dgac152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Indexed: 11/19/2022]
Affiliation(s)
- Luca Persani
- Correspondence: Luca Persani, MD, PhD, Department of Endocrine and Metabolic Diseases, San Luca Hospital, Istituto Auxologico Italiano IRCCS, Piazzale Brescia 20, 20149 Milan, Italy.
| | - Irene Campi
- Department of Endocrine and Metabolic Diseases, Istituto Auxologico Italiano IRCCS, 20149 Milan, Italy
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14
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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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15
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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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16
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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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17
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Stolyarova AV, Neretina TV, Zvyagina EA, Fedotova AV, Kondrashov A, Bazykin GA. Complex fitness landscape shapes variation in a hyperpolymorphic species. eLife 2022; 11:76073. [PMID: 35532122 PMCID: PMC9187340 DOI: 10.7554/elife.76073] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 05/09/2022] [Indexed: 11/13/2022] Open
Abstract
It is natural to assume that patterns of genetic variation in hyperpolymorphic species can reveal large-scale properties of the fitness landscape that are hard to detect by studying species with ordinary levels of genetic variation. Here, we study such patterns in a fungus Schizophyllum commune, the most polymorphic species known. Throughout the genome, short-range linkage disequilibrium (LD) caused by attraction of minor alleles is higher between pairs of nonsynonymous than of synonymous variants. This effect is especially pronounced for pairs of sites that are located within the same gene, especially if a large fraction of the gene is covered by haploblocks, genome segments where the gene pool consists of two highly divergent haplotypes, which is a signature of balancing selection. Haploblocks are usually shorter than 1000 nucleotides, and collectively cover about 10% of the S. commune genome. LD tends to be substantially higher for pairs of nonsynonymous variants encoding amino acids that interact within the protein. There is a substantial correlation between LDs at the same pairs of nonsynonymous mutations in the USA and the Russian populations. These patterns indicate that selection in S. commune involves positive epistasis due to compensatory interactions between nonsynonymous alleles. When less polymorphic species are studied, analogous patterns can be detected only through interspecific comparisons. Changes to DNA known as mutations may alter how the proteins and other components of a cell work, and thus play an important role in allowing living things to evolve new traits and abilities over many generations. Whether a mutation is beneficial or harmful may differ depending on the genetic background of the individual – that is, depending on other mutations present in other positions within the same gene – due to a phenomenon called epistasis. Epistasis is known to affect how various species accumulate differences in their DNA compared to each other over time. For example, a mutation that is rare in humans and known to cause disease may be widespread in other primates because its negative effect is canceled out by another mutation that is standard for these species but absent in humans. However, it remains unclear whether epistasis plays a significant part in shaping genetic differences between individuals of the same species. A type of fungus known as Schizophyllum commune lives on rotting wood and is found across the world. It is one of the most genetically diverse species currently known, so there is a higher chance of pairs of compensatory mutations occurring and persisting for a long time in S. commune than in most other species, providing a unique opportunity to study epistasis. Here, Stolyarova et al. studied two distinct populations of S. commune, one from the USA and one from Russia. The team found that – unlike in humans, flies and other less genetically diverse species – epistasis maintains combinations of mutations in S. commune that individually would be harmful to the fungus but together compensate for each other. For example, pairs of mutations affecting specific molecules known as amino acids – the building blocks of proteins – that physically interact with each other tended to be found together in the same individuals. One potential downside of having pairs of compensatory mutations in the genome is that when the organism reproduces, the process of making sex cells may split up these pairs so that harmful mutations are inherited without their partner mutations. Thus, epistasis may have helped shape the way S. commune and other genetically diverse species have evolved.
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Affiliation(s)
| | - Tatiana V Neretina
- Biological Faculty, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Elena A Zvyagina
- Biological Faculty, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Anna V Fedotova
- Skolkovo Institute of Science and Technology, Moscow, Russian Federation
| | - Alexey Kondrashov
- Department of Ecology and Evolutionary Biology, University of Michigan-Ann Arbor, Ann Arbor, United States
| | - Georgii A Bazykin
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russian Federation
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18
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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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19
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DeGiorgio M, Szpiech ZA. A spatially aware likelihood test to detect sweeps from haplotype distributions. PLoS Genet 2022; 18:e1010134. [PMID: 35404934 PMCID: PMC9022890 DOI: 10.1371/journal.pgen.1010134] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 04/21/2022] [Accepted: 03/04/2022] [Indexed: 01/13/2023] Open
Abstract
The inference of positive selection in genomes is a problem of great interest in evolutionary genomics. By identifying putative regions of the genome that contain adaptive mutations, we are able to learn about the biology of organisms and their evolutionary history. Here we introduce a composite likelihood method that identifies recently completed or ongoing positive selection by searching for extreme distortions in the spatial distribution of the haplotype frequency spectrum along the genome relative to the genome-wide expectation taken as neutrality. Furthermore, the method simultaneously infers two parameters of the sweep: the number of sweeping haplotypes and the "width" of the sweep, which is related to the strength and timing of selection. We demonstrate that this method outperforms the leading haplotype-based selection statistics, though strong signals in low-recombination regions merit extra scrutiny. As a positive control, we apply it to two well-studied human populations from the 1000 Genomes Project and examine haplotype frequency spectrum patterns at the LCT and MHC loci. We also apply it to a data set of brown rats sampled in NYC and identify genes related to olfactory perception. To facilitate use of this method, we have implemented it in user-friendly open source software.
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Affiliation(s)
- Michael DeGiorgio
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida, United States of America
| | - Zachary A. Szpiech
- Department of Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
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20
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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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21
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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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22
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Kidner J, Theodorou P, Engler JO, Taubert M, Husemann M. A brief history and popularity of methods and tools used to estimate micro-evolutionary forces. Ecol Evol 2021; 11:13723-13743. [PMID: 34707813 PMCID: PMC8525119 DOI: 10.1002/ece3.8076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 07/12/2021] [Accepted: 08/12/2021] [Indexed: 11/30/2022] Open
Abstract
Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.
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Affiliation(s)
- Jonathan Kidner
- General Zoology Institute for Biology Martin Luther University Halle-Wittenberg Halle (Saale) Germany
| | - Panagiotis Theodorou
- General Zoology Institute for Biology Martin Luther University Halle-Wittenberg Halle (Saale) Germany
| | - Jan O Engler
- Terrestrial Ecology Unit Department of Biology Ghent University Ghent Belgium
| | - Martin Taubert
- Aquatic Geomicrobiology Institute for Biodiversity Friedrich Schiller University Jena Jena Germany
| | - Martin Husemann
- General Zoology Institute for Biology Martin Luther University Halle-Wittenberg Halle (Saale) Germany
- Centrum für Naturkunde University of Hamburg Hamburg Germany
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23
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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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24
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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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25
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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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26
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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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27
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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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28
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Harris AM, DeGiorgio M. A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data. Mol Biol Evol 2021; 37:3023-3046. [PMID: 32392293 PMCID: PMC7530616 DOI: 10.1093/molbev/msaa115] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Selective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverages the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole-genome polymorphism data sets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data.
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Affiliation(s)
- Alexandre M Harris
- Department of Biology, Pennsylvania State University, University Park, PA.,Molecular, Cellular, and Integrative Biosciences, Huck Institutes of the Life Sciences, 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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29
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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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30
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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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31
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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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32
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Zhu S, Chen J, Zhao J, Comes HP, Li P, Fu C, Xie X, Lu R, Xu W, Feng Y, Ye W, Sakaguchi S, Isagi Y, Li L, Lascoux M, Qiu Y. Genomic insights on the contribution of balancing selection and local adaptation to the long-term survival of a widespread living fossil tree, Cercidiphyllum japonicum. THE NEW PHYTOLOGIST 2020; 228:1674-1689. [PMID: 32643803 DOI: 10.1111/nph.16798] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 06/27/2020] [Indexed: 05/25/2023]
Abstract
'Living fossils' are testimonies of long-term sustained ecological success, but how demographic history and natural selection contributed to their survival, resilience, and persistence in the face of Quaternary climate fluctuations remains unclear. To better understand the interplay between demographic history and selection in shaping genomic diversity and evolution of such organisms, we assembled the whole genome of Cercidiphyllum japonicum, a widespread East Asian Tertiary relict tree, and resequenced 99 individuals of C. japonicum and its sister species, Cercidiphyllum magnificum (Central Japan). We dated this speciation event to the mid-Miocene, and the intraspecific lineage divergence of C. japonicum (China vs Japan) to the Early Pliocene. Throughout climatic upheavals of the late Tertiary/Quaternary, population bottlenecks greatly reduced the genetic diversity of C. japonicum. However, this polymorphism loss was likely counteracted by, first, long-term balancing selection at multiple chromosomal and heterozygous gene regions, potentially reflecting overdominance, and, second, selective sweeps at stress response and growth-related genes likely involved in local adaptation. Our findings contribute to a better understanding of how living fossils have survived climatic upheaval and maintained an extensive geographic range; that is, both types of selection could be major factors contributing to the species' survival, resilience, and persistence.
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Affiliation(s)
- Shanshan Zhu
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Jun Chen
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Jing Zhao
- Novogene Bioinformatics Institute, Beijing, 100083, China
| | - Hans Peter Comes
- Department of Biosciences, Salzburg University, Salzburg, A-5020, Austria
| | - Pan Li
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Chengxin Fu
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Xiao Xie
- School of Marine Sciences, Ningbo University, Ningbo, Zhejiang, 315211, China
| | - Ruisen Lu
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Wuqin Xu
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Yu Feng
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Wenqing Ye
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Shota Sakaguchi
- Graduate School of Human and Environmental Studies, Kyoto University, Yoshida-nihonmatsu-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Yuji Isagi
- Graduate School of Agriculture, Kyoto University, Kitashirakawa-Oiwake-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Linfeng Li
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, 200433, China
| | - Martin Lascoux
- Plant Ecology and Evolution, Department of Ecology and Genetics and Science for Life Laboratory, Uppsala University, Norbyvägen 18D, Uppsala, 75236, Sweden
| | - Yingxiong Qiu
- Systematic & Evolutionary Botany and Biodiversity Group, MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
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33
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Zhang H, Fu Q, Shi X, Pan Z, Yang W, Huang Z, Tang T, He X, Zhang R. Human A-to-I RNA editing SNP loci are enriched in GWAS signals for autoimmune diseases and under balancing selection. Genome Biol 2020; 21:288. [PMID: 33256812 PMCID: PMC7702712 DOI: 10.1186/s13059-020-02205-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 11/16/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Adenosine-to-inosine (A-to-I) RNA editing plays important roles in diversifying the transcriptome and preventing MDA5 sensing of endogenous dsRNA as nonself. To date, few studies have investigated the population genomic signatures of A-to-I editing due to the lack of editing sites overlapping with SNPs. RESULTS In this study, we applied a pipeline to robustly identify SNP editing sites from population transcriptomic data and combined functional genomics, GWAS, and population genomics approaches to study the function and evolution of A-to-I editing. We find that the G allele, which is equivalent to edited I, is overrepresented in editing SNPs. Functionally, A/G editing SNPs are highly enriched in GWAS signals of autoimmune and immune-related diseases. Evolutionarily, derived allele frequency distributions of A/G editing SNPs for both A and G alleles as the ancestral alleles are skewed toward intermediate frequency alleles relative to neutral SNPs, a hallmark of balancing selection, suggesting that both A and G alleles are functionally important. The signal of balancing selection is confirmed by a number of additional population genomic analyses. CONCLUSIONS We uncovered a hidden layer of A-to-I RNA editing SNP loci as a common target of balancing selection, and we propose that the maintenance of such editing SNP variations may be at least partially due to constraints on the resolution of the balance between immune activity and self-tolerance.
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Affiliation(s)
- Hui Zhang
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, People's Republic of China
| | - Qiang Fu
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Xinrui Shi
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Ziqing Pan
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Wenbing Yang
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Zichao Huang
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Tian Tang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Xionglei He
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China
| | - Rui Zhang
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, People's Republic of China.
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China.
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34
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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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35
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Ruzicka F, Dutoit L, Czuppon P, Jordan CY, Li X, Olito C, Runemark A, Svensson EI, Yazdi HP, Connallon T. The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics. Evol Lett 2020; 4:398-415. [PMID: 33014417 PMCID: PMC7523564 DOI: 10.1002/evl3.192] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 07/13/2020] [Accepted: 07/28/2020] [Indexed: 12/16/2022] Open
Abstract
Sexually antagonistic (SA) genetic variation-in which alleles favored in one sex are disfavored in the other-is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterization of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research-including F ST and F IS statistics, genome-wide association studies, pedigree analyses, reciprocal transplant studies, and evolve-and-resequence experiments-to evaluate methods for identifying SA genes and genome-wide signals of SA genetic variation. We begin by developing theoretical models for between-sex F ST and F IS, including explicit null distributions for each statistic, and using them to critically evaluate putative multilocus signals of sex-specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of F ST and F IS, along with applications of more direct approaches for characterizing SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work.
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Affiliation(s)
- Filip Ruzicka
- School of Biological SciencesMonash UniversityClaytonVIC 3800Australia
| | - Ludovic Dutoit
- Department of ZoologyUniversity of OtagoDunedin9054New Zealand
| | - Peter Czuppon
- Institute of Ecology and Environmental Sciences, UPEC, CNRS, IRD, INRASorbonne UniversitéParis75252France
- Center for Interdisciplinary Research in Biology, CNRS, Collège de FrancePSL Research UniversityParis75231France
| | - Crispin Y. Jordan
- School of Biomedical SciencesUniversity of EdinburghEdinburghEH8 9XDUnited Kingdom
| | - Xiang‐Yi Li
- Institute of BiologyUniversity of NeuchâtelNeuchatelCH‐2000Switzerland
| | - Colin Olito
- Department of BiologyLund UniversityLundSE‐22362Sweden
| | - Anna Runemark
- Department of BiologyLund UniversityLundSE‐22362Sweden
| | | | | | - Tim Connallon
- School of Biological SciencesMonash UniversityClaytonVIC 3800Australia
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36
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Ebert D, Fields PD. Host-parasite co-evolution and its genomic signature. Nat Rev Genet 2020; 21:754-768. [PMID: 32860017 DOI: 10.1038/s41576-020-0269-1] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/16/2020] [Indexed: 01/14/2023]
Abstract
Studies in diverse biological systems have indicated that host-parasite co-evolution is responsible for the extraordinary genetic diversity seen in some genomic regions, such as major histocompatibility (MHC) genes in jawed vertebrates and resistance genes in plants. This diversity is believed to evolve under balancing selection on hosts by parasites. However, the mechanisms that link the genomic signatures in these regions to the underlying co-evolutionary process are only slowly emerging. We still lack a clear picture of the co-evolutionary concepts and of the genetic basis of the co-evolving phenotypic traits in the interacting antagonists. Emerging genomic tools that provide new options for identifying underlying genes will contribute to a fuller understanding of the co-evolutionary process.
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Affiliation(s)
- Dieter Ebert
- Department of Environmental Sciences, Zoology, University of Basel, Basel, Switzerland. .,Wissenschaftskolleg zu Berlin, Berlin, Germany.
| | - Peter D Fields
- Department of Environmental Sciences, Zoology, University of Basel, Basel, Switzerland
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37
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Mughal MR, Koch H, Huang J, Chiaromonte F, DeGiorgio M. Learning the properties of adaptive regions with functional data analysis. PLoS Genet 2020; 16:e1008896. [PMID: 32853200 PMCID: PMC7480868 DOI: 10.1371/journal.pgen.1008896] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 09/09/2020] [Accepted: 05/29/2020] [Indexed: 12/12/2022] Open
Abstract
Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.
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Affiliation(s)
- Mehreen R. Mughal
- Bioinformatics and Genomics at the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Hillary Koch
- Department of Statistics, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Jinguo Huang
- Bioinformatics and Genomics at the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Francesca Chiaromonte
- Department of Statistics, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida, United States of America
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VolcanoFinder: Genomic scans for adaptive introgression. PLoS Genet 2020; 16:e1008867. [PMID: 32555579 PMCID: PMC7326285 DOI: 10.1371/journal.pgen.1008867] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 06/30/2020] [Accepted: 05/18/2020] [Indexed: 12/16/2022] Open
Abstract
Recent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method—VolcanoFinder—to detect recent events of adaptive introgression using polymorphism data from the recipient species only. VolcanoFinder detects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity. Using coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show that VolcanoFinder has high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implement VolcanoFinder to detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such as TSHR in Europeans and TCHH-RPTN in Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications of VolcanoFinder. The process by which beneficial alleles are introduced into a species from a closely-related species is termed adaptive introgression. We present an analytically-tractable model for the effects of adaptive introgression on non-adaptive genetic variation in the genomic region surrounding the beneficial allele. The result we describe is a characteristic volcano-shaped pattern of increased variability that arises around the positively-selected site, and we introduce an open-source method VolcanoFinder to detect this signal in genomic data. Importantly, VolcanoFinder is a population-genetic likelihood-based approach, rather than a comparative-genomic approach, and can therefore probe genomic variation data from a single population for footprints of adaptive introgression, even from a priori unknown and possibly extinct donor species.
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Lundberg M, Zhong X, Konrad A, Olsen RA, Råberg L. Balancing selection in Pattern Recognition Receptor signalling pathways is associated with gene function and pleiotropy in a wild rodent. Mol Ecol 2020; 29:1990-2003. [PMID: 32374503 DOI: 10.1111/mec.15459] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 04/20/2020] [Accepted: 04/28/2020] [Indexed: 12/13/2022]
Abstract
Pathogen-mediated balancing selection is commonly considered to play an important role in the maintenance of genetic diversity, in particular in immune genes. However, the factors that may influence which immune genes are the targets of such selection are largely unknown. To address this, here we focus on Pattern Recognition Receptor (PRR) signalling pathways, which play a key role in innate immunity. We used whole-genome resequencing data from a population of bank voles (Myodes glareolus) to test for associations between balancing selection, pleiotropy and gene function in a set of 123 PRR signalling pathway genes. To investigate the effect of gene function, we compared genes encoding (a) receptors for microbial ligands versus downstream signalling proteins, and (b) receptors recognizing components of microbial cell walls, flagella and capsids versus receptors recognizing features of microbial nucleic acids. Analyses based on the nucleotide diversity of full coding sequences showed that balancing selection primarily targeted receptor genes with a low degree of pleiotropy. Moreover, genes encoding receptors recognizing components of microbial cell walls etc. were more important targets of balancing selection than receptors recognizing nucleic acids. Tests for localized signatures of balancing selection in coding and noncoding sequences showed that such signatures were mostly located in introns, and more evenly distributed among different functional categories of PRR pathway genes. The finding that signatures of balancing selection in full coding sequences primarily occur in receptor genes, in particular those encoding receptors for components of microbial cell walls etc., is consistent with the idea that coevolution between hosts and pathogens is an important cause of balancing selection on immune genes.
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Affiliation(s)
- Max Lundberg
- Department of Biology, Lund University, Lund, Sweden
| | - Xiuqin Zhong
- Department of Biology, Lund University, Lund, Sweden
| | - Anna Konrad
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden
| | - Remi-André Olsen
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden
| | - Lars Råberg
- Department of Biology, Lund University, Lund, Sweden
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40
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Rees JS, Castellano S, Andrés AM. The Genomics of Human Local Adaptation. Trends Genet 2020; 36:415-428. [DOI: 10.1016/j.tig.2020.03.006] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 03/16/2020] [Accepted: 03/18/2020] [Indexed: 01/23/2023]
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Mathieson I. Human adaptation over the past 40,000 years. Curr Opin Genet Dev 2020; 62:97-104. [PMID: 32745952 PMCID: PMC7484260 DOI: 10.1016/j.gde.2020.06.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 05/10/2020] [Accepted: 06/01/2020] [Indexed: 02/07/2023]
Abstract
Over the past few years several methodological and data-driven advances have greatly improved our ability to robustly detect genomic signatures of selection in humans. New methods applied to large samples of present-day genomes provide increased power, while ancient DNA allows precise estimation of timing and tempo. However, despite these advances, we are still limited in our ability to translate these signatures into understanding about which traits were actually under selection, and why. Combining information from different populations and timescales may allow interpretation of selective sweeps. Other modes of selection have proved more difficult to detect. In particular, despite strong evidence of the polygenicity of most human traits, evidence for polygenic selection is weak, and its importance in recent human evolution remains unclear. Balancing selection and archaic introgression seem important for the maintenance of potentially adaptive immune diversity, but perhaps less so for other traits.
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Affiliation(s)
- Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, United States.
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Barreiro LB, Quintana-Murci L. Evolutionary and population (epi)genetics of immunity to infection. Hum Genet 2020; 139:723-732. [PMID: 32285198 PMCID: PMC7285878 DOI: 10.1007/s00439-020-02167-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 04/07/2020] [Indexed: 12/29/2022]
Abstract
Immune response is one of the functions that have been more strongly targeted by natural selection during human evolution. The evolutionary genetic dissection of the immune system has greatly helped to distinguish genes and functions that are essential, redundant or advantageous for human survival. It is also becoming increasingly clear that admixture between early Eurasians with now-extinct hominins such as Neanderthals or Denisovans, or admixture between modern human populations, can be beneficial for human adaptation to pathogen pressures. In this review, we discuss how the integration of population genetics with functional genomics in diverse human populations can inform about the changes in immune functions related to major lifestyle transitions (e.g., from hunting and gathering to farming), the action of natural selection to the evolution of the immune system, and the history of past epidemics. We also highlight the need of expanding the characterization of the immune system to a larger array of human populations-particularly neglected human groups historically exposed to different pathogen pressures-to fully capture the relative contribution of genetic, epigenetic, and environmental factors to immune response variation in humans.
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Affiliation(s)
- Luis B Barreiro
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, 60637, USA.
| | - Lluis Quintana-Murci
- Unit of Human Evolutionary Genetics, CNRS UMR2000, Institut Pasteur, 75015, Paris, France
- Collège de France, 75005, Paris, France
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Sazzini M, Abondio P, Sarno S, Gnecchi-Ruscone GA, Ragno M, Giuliani C, De Fanti S, Ojeda-Granados C, Boattini A, Marquis J, Valsesia A, Carayol J, Raymond F, Pirazzini C, Marasco E, Ferrarini A, Xumerle L, Collino S, Mari D, Arosio B, Monti D, Passarino G, D'Aquila P, Pettener D, Luiselli D, Castellani G, Delledonne M, Descombes P, Franceschi C, Garagnani P. Genomic history of the Italian population recapitulates key evolutionary dynamics of both Continental and Southern Europeans. BMC Biol 2020; 18:51. [PMID: 32438927 PMCID: PMC7243322 DOI: 10.1186/s12915-020-00778-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 04/01/2020] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The cline of human genetic diversity observable across Europe is recapitulated at a micro-geographic scale by variation within the Italian population. Besides resulting from extensive gene flow, this might be ascribable also to local adaptations to diverse ecological contexts evolved by people who anciently spread along the Italian Peninsula. Dissecting the evolutionary history of the ancestors of present-day Italians may thus improve the understanding of demographic and biological processes that contributed to shape the gene pool of European populations. However, previous SNP array-based studies failed to investigate the full spectrum of Italian variation, generally neglecting low-frequency genetic variants and examining a limited set of small effect size alleles, which may represent important determinants of population structure and complex adaptive traits. To overcome these issues, we analyzed 38 high-coverage whole-genome sequences representative of population clusters at the opposite ends of the cline of Italian variation, along with a large panel of modern and ancient Euro-Mediterranean genomes. RESULTS We provided evidence for the early divergence of Italian groups dating back to the Late Glacial and for Neolithic and distinct Bronze Age migrations having further differentiated their gene pools. We inferred adaptive evolution at insulin-related loci in people from Italian regions with a temperate climate, while possible adaptations to pathogens and ultraviolet radiation were observed in Mediterranean Italians. Some of these adaptive events may also have secondarily modulated population disease or longevity predisposition. CONCLUSIONS We disentangled the contribution of multiple migratory and adaptive events in shaping the heterogeneous Italian genomic background, which exemplify population dynamics and gene-environment interactions that played significant roles also in the formation of the Continental and Southern European genomic landscapes.
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Affiliation(s)
- Marco Sazzini
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy.
- Interdepartmental Centre Alma Mater Research Institute on Global Challenges and Climate Change, University of Bologna, Bologna, Italy.
| | - Paolo Abondio
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Stefania Sarno
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | | | - Matteo Ragno
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Cristina Giuliani
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Sara De Fanti
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Claudia Ojeda-Granados
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
- Department of Molecular Biology in Medicine, Civil Hospital of Guadalajara "Fray Antonio Alcalde" and Health Sciences Center, University of Guadalajara, Guadalajara, Jalisco, Mexico
| | - Alessio Boattini
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Julien Marquis
- Nestlé Research, EPFL Innovation Park, Lausanne, Switzerland
- Current Address: Lausanne Genomic Technologies Facility, University of Lausanne, Lausanne, Switzerland
| | - Armand Valsesia
- Nestlé Research, EPFL Innovation Park, Lausanne, Switzerland
| | - Jerome Carayol
- Nestlé Research, EPFL Innovation Park, Lausanne, Switzerland
| | | | - Chiara Pirazzini
- IRCCS Bologna Institute of Neurological Sciences, Bologna, Italy
| | - Elena Marasco
- Department of Experimental, Diagnostic, and Specialty Medicine, University of Bologna, Bologna, Italy
- Applied Biomedical Research Center (CRBA), S. Orsola-Malpighi Polyclinic, Bologna, Italy
| | - Alberto Ferrarini
- Functional Genomics Laboratory, Department of Biotechnology, University of Verona, Verona, Italy
- Current Address: Menarini Silicon Biosystems SpA, Castel Maggiore, Bologna, Italy
| | - Luciano Xumerle
- Functional Genomics Laboratory, Department of Biotechnology, University of Verona, Verona, Italy
| | | | - Daniela Mari
- Geriatric Unit, Fondazione Ca' Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | - Beatrice Arosio
- Geriatric Unit, Fondazione Ca' Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | - Daniela Monti
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy
| | - Patrizia D'Aquila
- Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy
| | - Davide Pettener
- Laboratory of Molecular Anthropology & Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Donata Luiselli
- Department of Cultural Heritage, University of Bologna, Ravenna, Italy
| | - Gastone Castellani
- Interdepartmental Centre Alma Mater Research Institute on Global Challenges and Climate Change, University of Bologna, Bologna, Italy
- Department of Experimental, Diagnostic, and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Massimo Delledonne
- Functional Genomics Laboratory, Department of Biotechnology, University of Verona, Verona, Italy
| | | | - Claudio Franceschi
- Department of Applied Mathematics, Institute of Information Technology, Lobachevsky University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Paolo Garagnani
- Interdepartmental Centre Alma Mater Research Institute on Global Challenges and Climate Change, University of Bologna, Bologna, Italy.
- Department of Experimental, Diagnostic, and Specialty Medicine, University of Bologna, Bologna, Italy.
- Clinical Chemistry, Department of Laboratory Medicine, Karolinska Institutet at Huddinge University Hospital, Stockholm, Sweden.
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Popitsch N, Huber CD, Buchumenski I, Eisenberg E, Jantsch M, von Haeseler A, Gallach M. A-to-I RNA Editing Uncovers Hidden Signals of Adaptive Genome Evolution in Animals. Genome Biol Evol 2020; 12:345-357. [PMID: 32145015 PMCID: PMC7186786 DOI: 10.1093/gbe/evaa046] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/03/2020] [Indexed: 02/06/2023] Open
Abstract
In animals, the most common type of RNA editing is the deamination of adenosines (A) into inosines (I). Because inosines basepair with cytosines (C), they are interpreted as guanosines (G) by the cellular machinery and genomically encoded G alleles at edited sites mimic the function of edited RNAs. The contribution of this hardwiring effect on genome evolution remains obscure. We looked for population genomics signatures of adaptive evolution associated with A-to-I RNA edited sites in humans and Drosophila melanogaster. We found that single nucleotide polymorphisms at edited sites occur 3 (humans) to 15 times (Drosophila) more often than at unedited sites, the nucleotide G is virtually the unique alternative allele at edited sites and G alleles segregate at higher frequency at edited sites than at unedited sites. Our study reveals that a significant fraction of coding synonymous and nonsynonymous as well as silent and intergenic A-to-I RNA editing sites are likely adaptive in the distantly related human and Drosophila lineages.
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Affiliation(s)
- Niko Popitsch
- Oxford NIHR Biomedical Research Center, Wellcome Trust Center for Human Genetics, University of Oxford, Oxford, United Kingdom
- Institute of Molecular Biotechnology (IMBA), Vienna BioCenter (VBC), Vienna, Austria
| | - Christian D Huber
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Ilana Buchumenski
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel
| | - Eli Eisenberg
- Raymond and Beverly Sackler School of Physics and Astronomy and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Michael Jantsch
- Department for Cell and Developmental Biology, Center for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
- Department for Medical Biochemistry, Max F. Perutz Laboratories, Medical University of Vienna, Vienna, Austria
| | - Arndt von Haeseler
- Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria
- Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna and Medical University of Vienna, Vienna, Austria
| | - Miguel Gallach
- Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna and Medical University of Vienna, Vienna, Austria
- iLabSystems, C/Alicante, Castellón, Spain
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Oussalah A, Jeannesson-Thivisol E, Chéry C, Perrin P, Rouyer P, Josse T, Cano A, Barth M, Fouilhoux A, Mention K, Labarthe F, Arnoux JB, Maillot F, Lenaerts C, Dumesnil C, Wagner K, Terral D, Broué P, De Parscau L, Gay C, Kuster A, Bédu A, Besson G, Lamireau D, Odent S, Masurel A, Rodriguez-Guéant RM, Feillet F, Guéant JL, Namour F. Population and evolutionary genetics of the PAH locus to uncover overdominance and adaptive mechanisms in phenylketonuria: Results from a multiethnic study. EBioMedicine 2020; 51:102623. [PMID: 31923802 PMCID: PMC7000351 DOI: 10.1016/j.ebiom.2019.102623] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Revised: 12/20/2019] [Accepted: 12/22/2019] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Phenylketonuria (PKU) is the most common inborn error of amino acid metabolism in Europe. The reasons underlying the high prevalence of heterozygous carriers are not clearly understood. We aimed to look for pathogenic PAH variant enrichment according to geographical areas and patients' ethnicity using a multiethnic nationwide cohort of patients with PKU in France. We subsequently appraised the population differentiation, balancing selection and the molecular evolutionary history of the PAH locus. METHODS The French nationwide PKU study included patients who have been referred at the national level to the University Hospital of Nancy, and for whom a molecular diagnosis of phenylketonuria was made by Sanger sequencing. We performed enrichment analyses by comparing alternative allele frequencies using Fisher's exact test with Bonferroni adjustment. We estimated the amount of genetic differentiation among populations using Wright's fixation index (Fst). To estimate the molecular evolutionary history of the PAH gene, we performed phylogenetic and evolutionary analyses using whole-genome and exome-sequencing data from healthy individuals and non-PKU patients, respectively. Finally, we used exome-wide association study to decipher potential genetic loci associated with population divergence on PAH. FINDINGS The study included 696 patients and revealed 132 pathogenic PAH variants. Three geographical areas showed significant enrichment for a pathogenic PAH variant: North of France (p.Arg243Leu), North-West of France (p.Leu348Val), and Mediterranean coast (p.Ala403Val). One PAH variant (p.Glu280Gln) was significantly enriched among North-Africans (OR = 23·23; 95% CI: 9·75-55·38). PAH variants exhibiting a strong genetic differentiation were significantly enriched in the 'Biopterin_H' domain (OR = 6·45; 95% CI: 1·99-20·84), suggesting a balancing selection pressure on the biopterin function of PAH. Phylogenetic and timetree analyses were consistent with population differentiation events on European-, African-, and Asian-ancestry populations. The five PAH variants most strongly associated with a high selection pressure were phylogenetically close and were located within the biopterin domain coding region of PAH or in its vicinity. Among the non-PAH loci potentially associated with population divergence, two reached exome-wide significance: SSPO (SCO-spondin) and DBH (dopamine beta-hydroxylase), involved in neuroprotection and metabolic adaptation, respectively. INTERPRETATION Our data provide evidence on the combination of evolutionary and adaptive events in populations with distinct ancestries, which may explain the overdominance of some genetic variants on PAH. FUNDING French National Institute of Health and Medical Research (INSERM) UMR_S 1256.
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Affiliation(s)
- Abderrahim Oussalah
- University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, Nancy, France; Department of Molecular Medicine, Division of Biochemistry, Molecular Biology, Nutrition, and Metabolism, University Hospital of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France.
| | - Elise Jeannesson-Thivisol
- Department of Molecular Medicine, Division of Biochemistry, Molecular Biology, Nutrition, and Metabolism, University Hospital of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France
| | - Céline Chéry
- University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, Nancy, France; Department of Molecular Medicine, Division of Biochemistry, Molecular Biology, Nutrition, and Metabolism, University Hospital of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France
| | - Pascal Perrin
- Department of Molecular Medicine, Division of Biochemistry, Molecular Biology, Nutrition, and Metabolism, University Hospital of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France
| | - Pierre Rouyer
- University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, Nancy, France
| | - Thomas Josse
- Department of Molecular Medicine, Division of Biochemistry, Molecular Biology, Nutrition, and Metabolism, University Hospital of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France
| | - Aline Cano
- Centre of Reference for Inborn Metabolic Diseases, University Hospital La Timone, Marseille, France
| | - Magalie Barth
- Department of Genetics, University Hospital of Angers, Angers, France
| | - Alain Fouilhoux
- Metabolic Diseases Unit, Woman-Mother-Child Hospital, University Hospital of Lyon, Lyon, France
| | | | | | - Jean-Baptiste Arnoux
- Reference Centre for Inherited Metabolic Diseases, Necker-Sick Children's Hospital, Imagine Institute, Paris Descartes University, Paris, France
| | - François Maillot
- Department of Internal Medicine, University Hospital of Tours, François Rabelais University, Tours, France
| | - Catherine Lenaerts
- Department of Paediatrics, University Hospital of Amiens, Amiens, France
| | - Cécile Dumesnil
- Paediatric Haematology and Oncology, University Hospital of Rouen, Rouen, France
| | - Kathy Wagner
- Department of Paediatrics, Lenval Hospital, Nice, France
| | - Daniel Terral
- Department of Paediatrics, University Hospital of Clermont-Ferrand, Clermont-Ferrand, France
| | - Pierre Broué
- Reference Centre for Inborn Errors of Metabolism, University Children Hospital, Toulouse, France
| | - Loic De Parscau
- Department of Paediatrics, University Hospital Morvan, Brest, France
| | - Claire Gay
- Department of Paediatrics, University Hospital of Saint-Etienne, Saint-Etienne, France
| | - Alice Kuster
- Paediatric Department, University Hospital of Nantes, Nantes, France
| | - Antoine Bédu
- Department of Neonatology, Mother and Child Hospital, Limoges, France
| | - Gérard Besson
- Department of Neurology, University Hospital of Grenoble, Grenoble, France
| | - Delphine Lamireau
- Department of Paediatrics, Pellegrin-Enfants Hospital, Bordeaux, France
| | - Sylvie Odent
- Department of Clinical Genetics, University Hospital of Rennes, Rennes, France
| | - Alice Masurel
- Department of Medical Genetics, Dijon Bourgogne University Hospital, Dijon, France
| | - Rosa-Maria Rodriguez-Guéant
- University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, Nancy, France; Department of Molecular Medicine, Division of Biochemistry, Molecular Biology, Nutrition, and Metabolism, University Hospital of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France
| | - François Feillet
- University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France; Department of Paediatrics, University Hospital of Nancy, Nancy, France
| | - Jean-Louis Guéant
- University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, Nancy, France; Department of Molecular Medicine, Division of Biochemistry, Molecular Biology, Nutrition, and Metabolism, University Hospital of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France.
| | - Fares Namour
- University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, Nancy, France; Department of Molecular Medicine, Division of Biochemistry, Molecular Biology, Nutrition, and Metabolism, University Hospital of Nancy, Nancy, France; Reference Centre for Inborn Errors of Metabolism (ORPHA67872), University Hospital of Nancy, Nancy F-54000, France
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D'Antonio M, Reyna J, Jakubosky D, Donovan MKR, Bonder MJ, Matsui H, Stegle O, Nariai N, D'Antonio-Chronowska A, Frazer KA. Systematic genetic analysis of the MHC region reveals mechanistic underpinnings of HLA type associations with disease. eLife 2019; 8:e48476. [PMID: 31746734 PMCID: PMC6904215 DOI: 10.7554/elife.48476] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 11/19/2019] [Indexed: 02/06/2023] Open
Abstract
The MHC region is highly associated with autoimmune and infectious diseases. Here we conduct an in-depth interrogation of associations between genetic variation, gene expression and disease. We create a comprehensive map of regulatory variation in the MHC region using WGS from 419 individuals to call eight-digit HLA types and RNA-seq data from matched iPSCs. Building on this regulatory map, we explored GWAS signals for 4083 traits, detecting colocalization for 180 disease loci with eQTLs. We show that eQTL analyses taking HLA type haplotypes into account have substantially greater power compared with only using single variants. We examined the association between the 8.1 ancestral haplotype and delayed colonization in Cystic Fibrosis, postulating that downregulation of RNF5 expression is the likely causal mechanism. Our study provides insights into the genetic architecture of the MHC region and pinpoints disease associations that are due to differential expression of HLA genes and non-HLA genes.
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Affiliation(s)
- Matteo D'Antonio
- Institute for Genomic MedicineUniversity of California, San DiegoSan DiegoUnited States
- Department of PediatricsRady Children’s Hospital, University of California, San DiegoSan DiegoUnited States
| | - Joaquin Reyna
- Department of PediatricsRady Children’s Hospital, University of California, San DiegoSan DiegoUnited States
- Biomedical Sciences Graduate ProgramUniversity of California, San DiegoLa JollaUnited States
| | - David Jakubosky
- Biomedical Sciences Graduate ProgramUniversity of California, San DiegoLa JollaUnited States
- Bioinformatics and Systems Biology Graduate ProgramUniversity of California, San DiegoSan DiegoUnited States
| | - Margaret KR Donovan
- Bioinformatics and Systems Biology Graduate ProgramUniversity of California, San DiegoSan DiegoUnited States
- Department of Biomedical InformaticsUniversity of California, San DiegoSan DiegoUnited States
| | - Marc-Jan Bonder
- European Molecular Biology Laboratory, European Bioinformatics InstituteCambridgeUnited Kingdom
| | - Hiroko Matsui
- Institute for Genomic MedicineUniversity of California, San DiegoSan DiegoUnited States
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics InstituteCambridgeUnited Kingdom
| | - Naoki Nariai
- Department of PediatricsRady Children’s Hospital, University of California, San DiegoSan DiegoUnited States
| | - Agnieszka D'Antonio-Chronowska
- Institute for Genomic MedicineUniversity of California, San DiegoSan DiegoUnited States
- Department of PediatricsRady Children’s Hospital, University of California, San DiegoSan DiegoUnited States
| | - Kelly A Frazer
- Institute for Genomic MedicineUniversity of California, San DiegoSan DiegoUnited States
- Department of PediatricsRady Children’s Hospital, University of California, San DiegoSan DiegoUnited States
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Gupta MK, Vadde R. Genetic Basis of Adaptation and Maladaptation via Balancing Selection. ZOOLOGY 2019; 136:125693. [PMID: 31513936 DOI: 10.1016/j.zool.2019.125693] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 07/03/2019] [Indexed: 10/26/2022]
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Chapman JR, Hill T, Unckless RL. Balancing Selection Drives the Maintenance of Genetic Variation in Drosophila Antimicrobial Peptides. Genome Biol Evol 2019; 11:2691-2701. [PMID: 31504505 PMCID: PMC6764478 DOI: 10.1093/gbe/evz191] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/29/2019] [Indexed: 12/19/2022] Open
Abstract
Genes involved in immune defense against pathogens provide some of the most well-known examples of both directional and balancing selection. Antimicrobial peptides (AMPs) are innate immune effector genes, playing a key role in pathogen clearance in many species, including Drosophila. Conflicting lines of evidence have suggested that AMPs may be under directional, balancing, or purifying selection. Here, we use both a linear model and control-gene-based approach to show that balancing selection is an important force shaping AMP diversity in Drosophila. In Drosophila melanogaster, this is most clearly observed in ancestral African populations. Furthermore, the signature of balancing selection is even more striking once background selection has been accounted for. Balancing selection also acts on AMPs in Drosophila mauritiana, an isolated island endemic separated from D. melanogaster by about 4 Myr of evolution. This suggests that balancing selection may be broadly acting to maintain adaptive diversity in Drosophila AMPs, as has been found in other taxa.
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Affiliation(s)
| | - Tom Hill
- Department of Molecular Biosciences, University of Kansas
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Castillo JA, Agathos SN. A genome-wide scan for genes under balancing selection in the plant pathogen Ralstonia solanacearum. BMC Evol Biol 2019; 19:123. [PMID: 31208326 PMCID: PMC6580516 DOI: 10.1186/s12862-019-1456-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 06/10/2019] [Indexed: 02/07/2023] Open
Abstract
Background Plant pathogens are under significant selective pressure by the plant host. Consequently, they are expected to have adapted to this condition or contribute to evading plant defenses. In order to acquire long-term fitness, plant bacterial pathogens are usually forced to maintain advantageous genetic diversity in populations. This strategy ensures that different alleles in the pathogen’s gene pool are maintained in a population at frequencies larger than expected under neutral evolution. This selective process, known as balancing selection, is the subject of this work in the context of a common bacterial phytopathogen. We performed a genome-wide scan of Ralstonia solanacearum species complex, an aggressive plant bacterial pathogen that shows broad host range and causes a devastating disease called ‘bacterial wilt’. Results Using a sliding window approach, we analyzed 57 genomes from three phylotypes of the R. solanacearum species complex to detect signatures of balancing selection. A total of 161 windows showed extreme values in three summary statistics of population genetics: Tajima’s D, θw and Fu & Li’s D*. We discarded any confounding effects due to demographic events by means of coalescent simulations of genetic data. The prospective windows correspond to 78 genes with known function that map in any of the two main replicons (1.7% of total number of genes). The candidate genes under balancing selection are related to primary metabolism and other basal activities (51.3%) or directly associated to virulence (48.7%), the latter being involved in key functions targeted to dismantle plant defenses or to participate in critical stages in the pathogenic process. Conclusions We identified various genes under balancing selection that play a significant role in basic metabolism as well as in virulence of the R. solanacearum species complex. These genes are useful to understand and monitor the evolution of bacterial pathogen populations and emerge as potential candidates for future treatments to induce specific plant immune responses. Electronic supplementary material The online version of this article (10.1186/s12862-019-1456-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- José A Castillo
- School of Biological Sciences and Engineering, Yachay Tech University, Hacienda San Jose s/n and Proyecto Yachay, Urcuquí, Ecuador.
| | - Spiros N Agathos
- School of Biological Sciences and Engineering, Yachay Tech University, Hacienda San Jose s/n and Proyecto Yachay, Urcuquí, Ecuador
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Bourgeois Y, Boissinot S. On the Population Dynamics of Junk: A Review on the Population Genomics of Transposable Elements. Genes (Basel) 2019; 10:genes10060419. [PMID: 31151307 PMCID: PMC6627506 DOI: 10.3390/genes10060419] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 05/05/2019] [Accepted: 05/21/2019] [Indexed: 01/18/2023] Open
Abstract
Transposable elements (TEs) play an important role in shaping genomic organization and structure, and may cause dramatic changes in phenotypes. Despite the genetic load they may impose on their host and their importance in microevolutionary processes such as adaptation and speciation, the number of population genetics studies focused on TEs has been rather limited so far compared to single nucleotide polymorphisms (SNPs). Here, we review the current knowledge about the dynamics of transposable elements at recent evolutionary time scales, and discuss the mechanisms that condition their abundance and frequency. We first discuss non-adaptive mechanisms such as purifying selection and the variable rates of transposition and elimination, and then focus on positive and balancing selection, to finally conclude on the potential role of TEs in causing genomic incompatibilities and eventually speciation. We also suggest possible ways to better model TEs dynamics in a population genomics context by incorporating recent advances in TEs into the rich information provided by SNPs about the demography, selection, and intrinsic properties of genomes.
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Affiliation(s)
- Yann Bourgeois
- New York University Abu Dhabi, P.O. 129188, Saadiyat Island, Abu Dhabi, United Arab Emirates.
| | - Stéphane Boissinot
- New York University Abu Dhabi, P.O. 129188, Saadiyat Island, Abu Dhabi, United Arab Emirates.
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