1
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Forsythe ES, Gatts TC, Lane LE, deRoux C, Berggren MJ, Rehmann EA, Zak EN, Bartel T, L’Argent LA, Sloan DB. ERCnet: Phylogenomic Prediction of Interaction Networks in the Presence of Gene Duplication. Mol Biol Evol 2025; 42:msaf089. [PMID: 40247660 PMCID: PMC12062884 DOI: 10.1093/molbev/msaf089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2024] [Revised: 03/10/2025] [Accepted: 03/26/2025] [Indexed: 04/19/2025] Open
Abstract
Assigning gene function from genome sequences is a rate-limiting step in molecular biology research. A protein's position within an interaction network can potentially provide insights into its molecular mechanisms. Phylogenetic analysis of evolutionary rate covariation (ERC) in protein sequence has been shown to be effective for large-scale prediction of functional relationships and interactions. However, gene duplication, gene loss, and other sources of phylogenetic incongruence are barriers for analyzing ERC on a genome-wide basis. Here, we developed ERCnet, a bioinformatic program designed to overcome these challenges, facilitating efficient all-versus-all ERC analyses for large protein sequence datasets. We simulated proteome datasets and found that ERCnet achieves combined false positive and negative error rates well below 10% and that our novel "branch-by-branch" length measurements outperforms "root-to-tip" approaches in most cases, offering a valuable new strategy for performing ERC. We also compiled a sample set of 35 angiosperm genomes to test the performance of ERCnet on empirical data, including its sensitivity to user-defined analysis parameters such as input dataset size and branch-length measurement strategy. We investigated the overlap between ERCnet runs with different species samples to understand how species number and composition affect predicted interactions and to identify the protein sets that consistently exhibit ERC across angiosperms. Our systematic exploration of the performance of ERCnet provides a roadmap for design of future ERC analyses to predict functional interactions in a wide array of genomic datasets. ERCnet code is freely available at https://github.com/EvanForsythe/ERCnet.
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Affiliation(s)
- Evan S Forsythe
- Department of Integrative Biology, Oregon State University, Corvallis, OR, USA
- Biology Program, Oregon State University-Cascades, Bend, OR, USA
- Biochemistry and Molecular Biology Program, Oregon State University-Cascades, Bend, OR, USA
| | - Tony C Gatts
- Department of Biology, Colorado State University, Fort Collins, CO, USA
| | - Linnea E Lane
- Biology Program, Oregon State University-Cascades, Bend, OR, USA
| | - Chris deRoux
- Department of Biology, Colorado State University, Fort Collins, CO, USA
| | - Monica J Berggren
- Department of Biology, Colorado State University, Fort Collins, CO, USA
| | - Elizabeth A Rehmann
- Biochemistry and Molecular Biology Program, Oregon State University-Cascades, Bend, OR, USA
| | - Emily N Zak
- Biology Program, Oregon State University-Cascades, Bend, OR, USA
| | - Trinity Bartel
- Biology Program, Oregon State University-Cascades, Bend, OR, USA
| | - Luna A L’Argent
- Biochemistry and Molecular Biology Program, Oregon State University-Cascades, Bend, OR, USA
| | - Daniel B Sloan
- Department of Biology, Colorado State University, Fort Collins, CO, USA
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2
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Thomas GWC, Hughes JJ, Kumon T, Berv JS, Nordgren CE, Lampson M, Levine M, Searle JB, Good JM. The Genomic Landscape, Causes, and Consequences of Extensive Phylogenomic Discordance in Murine Rodents. Genome Biol Evol 2025; 17:evaf017. [PMID: 39903560 PMCID: PMC11837218 DOI: 10.1093/gbe/evaf017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Revised: 01/08/2025] [Accepted: 01/23/2025] [Indexed: 02/06/2025] Open
Abstract
A species tree is a central concept in evolutionary biology whereby a single branching phylogeny reflects relationships among species. However, the phylogenies of different genomic regions often differ from the species tree. Although tree discordance is widespread in phylogenomic studies, we still lack a clear understanding of how variation in phylogenetic patterns is shaped by genome biology or the extent to which discordance may compromise comparative studies. We characterized patterns of phylogenomic discordance across the murine rodents-a large and ecologically diverse group that gave rise to the laboratory mouse and rat model systems. Combining recently published linked-read genome assemblies for seven murine species with other available rodent genomes, we first used ultraconserved elements (UCEs) to infer a robust time-calibrated species tree. We then used whole genomes to examine finer-scale patterns of discordance across ∼12 million years of divergence. We found that proximate chromosomal regions tended to have more similar phylogenetic histories. There was no clear relationship between local tree similarity and recombination rates in house mice, but we did observe a correlation between recombination rates and average similarity to the species tree. We also detected a strong influence of linked selection whereby purifying selection at UCEs led to appreciably less discordance. Finally, we show that assuming a single species tree can result in substantial deviation from the results with gene trees when testing for positive selection under different models. Collectively, our results highlight the complex relationship between phylogenetic inference and genome biology and underscore how failure to account for this complexity can mislead comparative genomic studies.
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Affiliation(s)
- Gregg W C Thomas
- Division of Biological Sciences, University of Montana, Missoula, MT 59801, USA
- Informatics Group, Harvard University, Cambridge, MA 02138, USA
| | - Jonathan J Hughes
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA
- Department of Evolution, Ecology, and Organismal Biology, University of California Riverside, Riverside, CA 92521, USA
| | - Tomohiro Kumon
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jacob S Berv
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - C Erik Nordgren
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael Lampson
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Mia Levine
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jeremy B Searle
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA
| | - Jeffrey M Good
- Division of Biological Sciences, University of Montana, Missoula, MT 59801, USA
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3
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Dewar AE, Belcher LJ, West SA. A phylogenetic approach to comparative genomics. Nat Rev Genet 2025:10.1038/s41576-024-00803-0. [PMID: 39779997 PMCID: PMC7617348 DOI: 10.1038/s41576-024-00803-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/05/2024] [Indexed: 01/11/2025]
Abstract
Comparative genomics, whereby the genomes of different species are compared, has the potential to address broad and fundamental questions at the intersection of genetics and evolution. However, species, genomes and genes cannot be considered as independent data points within statistical tests. Closely related species tend to be similar because they share genes by common descent, which must be accounted for in analyses. This problem of non-independence may be exacerbated when examining genomes or genes but can be addressed by applying phylogeny-based methods to comparative genomic analyses. Here, we review how controlling for phylogeny can change the conclusions of comparative genomics studies. We address common questions on how to apply these methods and illustrate how they can be used to test causal hypotheses. The combination of rapidly expanding genomic datasets and phylogenetic comparative methods is set to revolutionize the biological insights possible from comparative genomic studies.
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Affiliation(s)
- Anna E Dewar
- Department of Biology, University of Oxford, Oxford, UK.
- St John's College, Oxford, UK.
| | | | - Stuart A West
- Department of Biology, University of Oxford, Oxford, UK
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4
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Pollard MD, Meyer WK, Puckett EE. Convergent relaxation of molecular constraint in herbivores reveals the changing role of liver and kidney functions across mammalian diets. Genome Res 2024; 34:2176-2189. [PMID: 39578099 PMCID: PMC11694762 DOI: 10.1101/gr.278930.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Accepted: 10/16/2024] [Indexed: 11/24/2024]
Abstract
Mammalia comprises a great diversity of diet types and associated adaptations. An understanding of the genomic mechanisms underlying these adaptations may offer insights for improving human health. Comparative genomic studies of diet that employ taxonomically restricted analyses or simplified diet classifications may suffer reduced power to detect molecular convergence associated with diet evolution. Here, we use a quantitative carnivory score-indicative of the amount of animal protein in the diet-for 80 mammalian species to detect significant correlations between the relative evolutionary rates of genes and changes in diet. We have identified six genes-ACADSB, CLDN16, CPB1, PNLIP, SLC13A2, and SLC14A2-that experienced significant changes in evolutionary constraint alongside changes in carnivory score, becoming less constrained in lineages evolving more herbivorous diets. We further consider the biological functions associated with diet evolution and observe that pathways related to amino acid and lipid metabolism, biological oxidation, and small molecule transport experienced reduced purifying selection as lineages became more herbivorous. Liver and kidney functions show similar patterns of constraint with dietary change. Our results indicate that these functions are important for the consumption of animal matter and become less important with the evolution of increasing herbivory. So, genes expressed in these tissues experience a relaxation of evolutionary constraint in more herbivorous lineages.
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Affiliation(s)
- Matthew D Pollard
- Department of Biological Sciences, University of Memphis, Memphis, Tennessee 38152, USA;
- Center for Biodiversity Research, University of Memphis, Memphis, Tennessee 38152, USA
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania 18015, USA
| | - Emily E Puckett
- Department of Biological Sciences, University of Memphis, Memphis, Tennessee 38152, USA
- Center for Biodiversity Research, University of Memphis, Memphis, Tennessee 38152, USA
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5
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Sullivan SA, Orosco JC, Callejas-Hernández F, Blow F, Lee H, Ranallo-Benavidez T, Peters A, Raidal S, Girard YA, Johnson CK, Rogers K, Gerhold R, Mangelson H, Liachko I, Srivastava H, Chandler C, Berenberg D, Bonneau RA, Huang PJ, Yeh YM, Lee CC, Liu H, Tang P, Chen TW, Schatz MC, Carlton JM. Comparative genomics of the sexually transmitted parasite Trichomonas vaginalis reveals relaxed and convergent evolution and genes involved in spillover from birds to humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.22.629724. [PMID: 39763951 PMCID: PMC11703204 DOI: 10.1101/2024.12.22.629724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/14/2025]
Abstract
Trichomonas vaginalis is the causative agent of the venereal disease trichomoniasis which infects men and women globally and is associated with serious outcomes during pregnancy and cancers of the human reproductive tract. Trichomonads parasitize a range of hosts in addition to humans including birds, livestock, and domesticated animals. Recent genetic analysis of trichomonads recovered from columbid birds has provided evidence that these parasite species undergo frequent host-switching, and that a current epoch spillover event from columbids likely gave rise to T. vaginalis in humans. We undertook a comparative evolutionary genomics study of seven trichomonad species, generating chromosome-scale reference genomes for T. vaginalis and its avian sister species Trichomonas stableri, and assemblies of five other species that infect birds and mammals. Human-infecting trichomonad lineages have undergone recent and convergent genome size expansions compared to their avian sister species, and the major contributor to their increased genome size is increased repeat expansions, especially multicopy gene families and transposable elements, with genetic drift likely a driver due to relaxed selection. Trichomonads have independently host-switched twice from birds to humans, and genes implicated in the transition to the human host include those associated with host tissue adherence and phagocytosis, extracellular vesicles, and CAZyme virulence factors.
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Affiliation(s)
- Steven A. Sullivan
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Jordan C. Orosco
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Francisco Callejas-Hernández
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Frances Blow
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
| | - Hayan Lee
- Department of Computer Science, Johns Hopkins Whiting School of Engineering, 3400 N Charles St Malone Hall 323, Baltimore, MD 21211, USA
| | - Timothy Ranallo-Benavidez
- Department of Computer Science, Johns Hopkins Whiting School of Engineering, 3400 N Charles St Malone Hall 323, Baltimore, MD 21211, USA
| | - Andrew Peters
- Charles Sturt University, The Grange Chancellery, Panorama Avenue, Bathurst, New South Wales, Australia 2795
| | - Shane Raidal
- Charles Sturt University, The Grange Chancellery, Panorama Avenue, Bathurst, New South Wales, Australia 2795
| | - Yvette A. Girard
- One Health Institute, School of Veterinary Medicine, University of California, Davis, 1089 Veterinary Medicine Drive, Davis, CA, 95616, USA
| | - Christine K. Johnson
- One Health Institute, School of Veterinary Medicine, University of California, Davis, 1089 Veterinary Medicine Drive, Davis, CA, 95616, USA
| | - Krysta Rogers
- Wildlife Health Laboratory, California Department of Fish & Wildlife, 1701 Nimbus Road, Suite D Rancho Cordova, CA 95670, USA
| | - Richard Gerhold
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN, 37996, USA
| | | | - Ivan Liachko
- Phase Genomics, 1617 8th Ave N, Seattle, WA 98109, USA
| | - Harsh Srivastava
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Chris Chandler
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
| | - Daniel Berenberg
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
| | - Richard A. Bonneau
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
| | - Po-Jung Huang
- Molecular Medicine Research Center, Chang Gung University, Taoyuan 333, Taiwan
| | - Yuan-Ming Yeh
- Molecular Medicine Research Center, Chang Gung University, Taoyuan 333, Taiwan
| | - Chi-Ching Lee
- Molecular Medicine Research Center, Chang Gung University, Taoyuan 333, Taiwan
| | - Hsuan Liu
- Molecular Medicine Research Center, Chang Gung University, Taoyuan 333, Taiwan
| | - Petrus Tang
- Molecular Medicine Research Center, Chang Gung University, Taoyuan 333, Taiwan
- Molecular Infectious Disease Research Center, Chang Gung Memorial Hospital, Linkou, Taoyuan 333, Taiwan
| | - Ting-Wen Chen
- Molecular Infectious Disease Research Center, Chang Gung Memorial Hospital, Linkou, Taoyuan 333, Taiwan
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins Whiting School of Engineering, 3400 N Charles St Malone Hall 323, Baltimore, MD 21211, USA
| | - Jane M. Carlton
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY 10003, USA
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
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6
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Kopania EEK, Thomas GWC, Hutter CR, Mortimer SME, Callahan CM, Roycroft E, Achmadi AS, Breed WG, Clark NL, Esselstyn JA, Rowe KC, Good JM. Sperm competition intensity shapes divergence in both sperm morphology and reproductive genes across murine rodents. Evolution 2024; 79:11-27. [PMID: 39392918 DOI: 10.1093/evolut/qpae146] [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: 02/14/2024] [Revised: 09/19/2024] [Accepted: 10/09/2024] [Indexed: 10/13/2024]
Abstract
It remains unclear how variation in the intensity of sperm competition shapes phenotypic and molecular evolution across clades. Mice and rats in the subfamily Murinae are a rapid radiation exhibiting incredible diversity in sperm morphology and production. We combined phenotypic and genomic data to perform phylogenetic comparisons of male reproductive traits and genes across 78 murine species. We identified several shifts towards smaller relative testes mass (RTM), presumably reflecting reduced sperm competition. Several sperm traits were associated with RTM, suggesting that mating system evolution selects for convergent suites of traits related to sperm competitive ability. We predicted that sperm competition would also drive more rapid molecular divergence in species with large testes. Contrary to this, we found that many spermatogenesis genes evolved more rapidly in species with smaller RTM due to relaxed purifying selection. While some reproductive genes evolved rapidly under recurrent positive selection, relaxed selection played a greater role in underlying rapid evolution in small testes species. Our work demonstrates that postcopulatory sexual selection can impose strong purifying selection shaping the evolution of male reproduction and that broad patterns of molecular evolution may help identify genes that contribute to male fertility.
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Affiliation(s)
- Emily E K Kopania
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Gregg W C Thomas
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
- Informatics Group, Harvard University, Cambridge, MA, USA
| | - Carl R Hutter
- Museum of Natural Science and Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA
| | | | - Colin M Callahan
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Emily Roycroft
- School of BioSciences, The University of Melbourne, Parkville, VIC, Australia
- Department of Sciences, Museums Victoria Research Institute, Melbourne, VIC, Australia
- Division of Ecology and Evolution, Research School of Biology, The Australian National University, Acton, ACT, Australia
| | - Anang S Achmadi
- Museum Zoologicum Bogoriense, Research Center for Biology, Cibinong, Indonesia
| | - William G Breed
- School of Biological Sciences and Robinson Research Institute, The University of Adelaide, Adelaide, SA, Australia
| | - Nathan L Clark
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jacob A Esselstyn
- Museum of Natural Science and Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA
| | - Kevin C Rowe
- School of BioSciences, The University of Melbourne, Parkville, VIC, Australia
- Department of Sciences, Museums Victoria Research Institute, Melbourne, VIC, Australia
| | - Jeffrey M Good
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
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7
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Santos PKF, Kapheim KM. Convergent Evolution Associated with the Loss of Developmental Diapause May Promote Extended Lifespan in Bees. Genome Biol Evol 2024; 16:evae255. [PMID: 39579066 PMCID: PMC11632380 DOI: 10.1093/gbe/evae255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 11/11/2024] [Accepted: 11/14/2024] [Indexed: 11/25/2024] Open
Abstract
Diapause has long been proposed to play a significant role in the evolution of eusociality in Hymenoptera. Recent studies have shown that shifts in the diapause stage precede social evolution in wasps and bees; however, the genomic basis remains unknown. Given the overlap in molecular pathways that regulate diapause and lifespan, we hypothesized that the evolutionary loss of developmental diapause may lead to extended lifespan among adults, which is a prerequisite for the evolution of eusociality. To test whether the loss of prepupal diapause is followed by genomic changes associated with lifespan extension, we compared 27 bee genomes with or without prepupal diapause. Our results point to several potential mechanisms for lifespan extension in species lacking prepupal diapause, including the loss of the growth hormone PTTH and its receptor TORSO, along with convergent selection in genes known to regulate lifespan in animals. Specifically, we observed purifying selection of prolongevity genes and relaxed selection of antilongevity genes within the IIS/TOR pathway in species that have lost prepupal diapause. Changes in selection pressures on this pathway may lead to the evolution of new phenotypes, such as lifespan extension and altered responses to nutritional signals that are crucial for social evolution.
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Affiliation(s)
| | - Karen M Kapheim
- Department of Biology, Utah State University, Logan, UT 84322, USA
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8
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Bjornson S, Verbruggen H, Upham NS, Steenwyk JL. Reticulate evolution: Detection and utility in the phylogenomics era. Mol Phylogenet Evol 2024; 201:108197. [PMID: 39270765 DOI: 10.1016/j.ympev.2024.108197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2024] [Revised: 08/13/2024] [Accepted: 09/08/2024] [Indexed: 09/15/2024]
Abstract
Phylogenomics has enriched our understanding that the Tree of Life can have network-like or reticulate structures among some taxa and genes. Two non-vertical modes of evolution - hybridization/introgression and horizontal gene transfer - deviate from a strictly bifurcating tree model, causing non-treelike patterns. However, these reticulate processes can produce similar patterns to incomplete lineage sorting or recombination, potentially leading to ambiguity. Here, we present a brief overview of a phylogenomic workflow for inferring organismal histories and compare methods for distinguishing modes of reticulate evolution. We discuss how the timing of coalescent events can help disentangle introgression from incomplete lineage sorting and how horizontal gene transfer events can help determine the relative timing of speciation events. In doing so, we identify pitfalls of certain methods and discuss how to extend their utility across the Tree of Life. Workflows, methods, and future directions discussed herein underscore the need to embrace reticulate evolutionary patterns for understanding the timing and rates of evolutionary events, providing a clearer view of life's history.
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Affiliation(s)
- Saelin Bjornson
- School of BioSciences, University of Melbourne, Victoria, Australia
| | - Heroen Verbruggen
- School of BioSciences, University of Melbourne, Victoria, Australia; CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Portugal
| | - Nathan S Upham
- School of Life Sciences, Arizona State University, Tempe, AZ, USA.
| | - Jacob L Steenwyk
- Howards Hughes Medical Institute and the Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA.
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9
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Vazquez JM, Lauterbur ME, Mottaghinia S, Bucci M, Fraser D, Gray-Sandoval G, Gaucherand L, Haidar ZR, Han M, Kohler W, Lama TM, Le Corf A, Loyer C, Maesen S, McMillan D, Li S, Lo J, Rey C, Capel SLR, Singer M, Slocum K, Thomas W, Tyburec JD, Villa S, Miller R, Buchalski M, Vazquez-Medina JP, Pfeffer S, Etienne L, Enard D, Sudmant PH. Extensive longevity and DNA virus-driven adaptation in nearctic Myotis bats. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.10.617725. [PMID: 39416019 PMCID: PMC11482938 DOI: 10.1101/2024.10.10.617725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
The genus Myotis is one of the largest clades of bats, and exhibits some of the most extreme variation in lifespans among mammals alongside unique adaptations to viral tolerance and immune defense. To study the evolution of longevity-associated traits and infectious disease, we generated near-complete genome assemblies and cell lines for 8 closely related species of Myotis. Using genome-wide screens of positive selection, analyses of structural variation, and functional experiments in primary cell lines, we identify new patterns of adaptation contributing to longevity, cancer resistance, and viral interactions in bats. We find that Myotis bats have some of the most significant variation in cancer risk across mammals and demonstrate a unique DNA damage response in primary cells of the long-lived M. lucifugus. We also find evidence of abundant adaptation in response to DNA viruses - but not RNA viruses - in Myotis and other bats in sharp contrast with other mammals, potentially contributing to the role of bats as reservoirs of zoonoses. Together, our results demonstrate how genomics and primary cells derived from diverse taxa uncover the molecular bases of extreme adaptations in non-model organisms.
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Affiliation(s)
- Juan M Vazquez
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA USA
- These authors contributed equally
| | - M. Elise Lauterbur
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ USA
- Current affiliation: Department of Biology, University of Vermont, Burlington, VT USA
- These authors contributed equally
| | - Saba Mottaghinia
- Centre International de Recherche en Infectiologie (CIRI), Inserm U1111, UCBL1, CNRS UMR5308, Ecole Normale Supérieure ENS de Lyon, Université de Lyon, Lyon, France
| | - Melanie Bucci
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ USA
| | - Devaughn Fraser
- Wildlife Genetics Research Unit, Wildlife Health Laboratory, California Department of Fish and Wildlife, Sacramento, CA, United States
- Current affiliation: Wildlife Diversity Program, Wildlife Division, Connecticut Department of Energy and Environmental Protection, Burlington, CT, United States
| | | | - Léa Gaucherand
- Université de Strasbourg, Architecture et Réactivité de l’ARN, Institut de Biologie Moléculaire et Cellulaire du CNRS, Strasbourg, France
| | - Zeinab R Haidar
- Department of Biology, California State Polytechnic University, Humboldt, Arcata, CA USA
- Current affiliation: Western EcoSystems Technology Inc, Cheyenne, WY USA
| | - Melissa Han
- Department of Pathology and Clinical Laboratories, University of Michigan, Ann Arbor, MI USA
| | - William Kohler
- Department of Pathology and Clinical Laboratories, University of Michigan, Ann Arbor, MI USA
| | - Tanya M. Lama
- Department of Biological Sciences, Smith College, Northampton, MA USA
| | - Amandine Le Corf
- Centre International de Recherche en Infectiologie (CIRI), Inserm U1111, UCBL1, CNRS UMR5308, Ecole Normale Supérieure ENS de Lyon, Université de Lyon, Lyon, France
| | - Clara Loyer
- Centre International de Recherche en Infectiologie (CIRI), Inserm U1111, UCBL1, CNRS UMR5308, Ecole Normale Supérieure ENS de Lyon, Université de Lyon, Lyon, France
| | - Sarah Maesen
- Centre International de Recherche en Infectiologie (CIRI), Inserm U1111, UCBL1, CNRS UMR5308, Ecole Normale Supérieure ENS de Lyon, Université de Lyon, Lyon, France
| | - Dakota McMillan
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA USA
- Department of Science and Biotechnology, Berkeley City College, Berkeley, CA USA
| | - Stacy Li
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA USA
| | - Johnathan Lo
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA USA
| | - Carine Rey
- Centre International de Recherche en Infectiologie (CIRI), Inserm U1111, UCBL1, CNRS UMR5308, Ecole Normale Supérieure ENS de Lyon, Université de Lyon, Lyon, France
| | - Samantha LR Capel
- Current affiliation: Wildlife Diversity Program, Wildlife Division, Connecticut Department of Energy and Environmental Protection, Burlington, CT, United States
| | - Michael Singer
- Department of Molecular and Cellular Biology, University of California, Berkeley, Berkeley, CA USA
| | | | - William Thomas
- Department of Ecology and Evolution, Stony Brook University, Stony Brook NY USA
| | | | - Sarah Villa
- Department of Molecular and Cellular Biology, University of California, Berkeley, Berkeley, CA USA
| | - Richard Miller
- Department of Pathology and Clinical Laboratories, University of Michigan, Ann Arbor, MI USA
| | - Michael Buchalski
- Wildlife Genetics Research Unit, Wildlife Health Laboratory, California Department of Fish and Wildlife, Sacramento, CA, United States
| | | | - Sébastien Pfeffer
- Université de Strasbourg, Architecture et Réactivité de l’ARN, Institut de Biologie Moléculaire et Cellulaire du CNRS, Strasbourg, France
| | - Lucie Etienne
- Centre International de Recherche en Infectiologie (CIRI), Inserm U1111, UCBL1, CNRS UMR5308, Ecole Normale Supérieure ENS de Lyon, Université de Lyon, Lyon, France
- Senior author
| | - David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ USA
- Senior author
- These authors contributed equally
| | - Peter H Sudmant
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA USA
- Senior author
- These authors contributed equally
- Lead contact
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10
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Li X, Zhu K, Zhen Y. A versatile pipeline to identify convergently lost ancestral conserved fragments associated with convergent evolution of vocal learning. Brief Bioinform 2024; 26:bbae614. [PMID: 39581870 PMCID: PMC11586126 DOI: 10.1093/bib/bbae614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 10/10/2024] [Accepted: 11/12/2024] [Indexed: 11/26/2024] Open
Abstract
Molecular convergence in convergently evolved lineages provides valuable insights into the shared genetic basis of converged phenotypes. However, most methods are limited to coding regions, overlooking the potential contribution of regulatory regions. We focused on the independently evolved vocal learning ability in multiple avian lineages, and developed a whole-genome-alignment-free approach to identify genome-wide Convergently Lost Ancestral Conserved fragments (CLACs) in these lineages, encompassing noncoding regions. We discovered 2711 CLACs that are overrepresented in noncoding regions. Proximal genes of these CLACs exhibit significant enrichment in neurological pathways, including glutamate receptor signaling pathway and axon guidance pathway. Moreover, their expression is highly enriched in brain tissues associated with speech formation. Notably, several have known functions in speech and language learning, including ROBO family, SLIT2, GRIN1, and GRIN2B. Additionally, we found significantly enriched motifs in noncoding CLACs, which match binding motifs of transcriptional factors involved in neurogenesis and gene expression regulation in brain. Furthermore, we discovered 19 candidate genes that harbor CLACs in both human and multiple avian vocal learning lineages, suggesting their potential contribution to the independent evolution of vocal learning in both birds and humans.
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Affiliation(s)
- Xiaoyi Li
- School of Life Sciences, Fudan University, 220 Handan Road, Yangpu District, Shanghai 200433, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences and Research Center for Industries of the Future, Westlake University, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang 310030, China
- Westlake Laboratory of Life Sciences and Biomedicine, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang 310030, China
| | - Kangli Zhu
- Westlake Laboratory of Life Sciences and Biomedicine, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang 310030, China
| | - Ying Zhen
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences and Research Center for Industries of the Future, Westlake University, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang 310030, China
- Westlake Laboratory of Life Sciences and Biomedicine, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang 310030, China
- Institute of Biology, Westlake Institute for Advanced Study, 18 Shilongshan Road, Xihu District, Hangzhou, Zhejiang 310024, China
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11
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Thomas GWC, Gemmell P, Shakya SB, Hu Z, Liu JS, Sackton TB, Edwards SV. Practical Guidance and Workflows for Identifying Fast Evolving Non-Coding Genomic Elements Using PhyloAcc. Integr Comp Biol 2024; 64:1513-1525. [PMID: 38816211 PMCID: PMC11579529 DOI: 10.1093/icb/icae056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 06/01/2024] Open
Abstract
Comparative genomics provides ample ways to study genome evolution and its relationship to phenotypic traits. By developing and testing alternate models of evolution throughout a phylogeny, one can estimate rates of molecular evolution along different lineages in a phylogeny and link these rates with observations in extant species, such as convergent phenotypes. Pipelines for such work can help identify when and where genomic changes may be associated with, or possibly influence, phenotypic traits. We recently developed a set of models called PhyloAcc, using a Bayesian framework to estimate rates of nucleotide substitution on different branches of a phylogenetic tree and evaluate their association with pre-defined or estimated phenotypic traits. PhyloAcc-ST and PhyloAcc-GT both allow users to define a priori a set of target lineages and then compare different models to identify loci accelerating in one or more target lineages. Whereas ST considers only one species tree across all input loci, GT considers alternate topologies for every locus. PhyloAcc-C simultaneously models molecular rates and rates of continuous trait evolution, allowing the user to ask whether the two are associated. Here, we describe these models and provide tips and workflows on how to prepare the input data and run PhyloAcc.
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Affiliation(s)
| | - Patrick Gemmell
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Statistics, Harvard University, Cambridge, MA 02138, USA
| | - Subir B Shakya
- Informatics Group, Harvard University, Cambridge, MA 02138, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
| | - Zhirui Hu
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA
| | - Jun S Liu
- Department of Statistics, Harvard University, Cambridge, MA 02138, USA
| | | | - Scott V Edwards
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
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12
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Redlich R, Kowalczyk A, Tene M, Sestili HH, Foley K, Saputra E, Clark N, Chikina M, Meyer WK, Pfenning AR. RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution. Mol Biol Evol 2024; 41:msae210. [PMID: 39404101 PMCID: PMC11529301 DOI: 10.1093/molbev/msae210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 10/01/2024] [Accepted: 10/08/2024] [Indexed: 10/23/2024] Open
Abstract
Comparative genomics approaches seek to associate molecular evolution with the evolution of phenotypes across a phylogeny. Many of these methods lack the ability to analyze non-ordinal categorical traits with more than two categories. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogeny-aware permutations, "permulations", on categorical traits. We demonstrate our new method on a three-category diet phenotype, and we compare its performance to binary RERconverge analyses and two existing methods for comparative genomic analyses of categorical traits: phylogenetic simulations and a phylogenetic signal based method. We present an analysis of how the categorical permulations scale with the number of species and the number of categories included in the analysis. Our results show that our new categorical method outperforms phylogenetic simulations at identifying genes and enriched pathways significantly associated with the diet phenotypes and that the categorical ancestral state reconstruction drives an improvement in our ability to capture diet-related enriched pathways compared to binary RERconverge when implemented without user input on phenotype evolution. The categorical expansion to RERconverge will provide a strong foundation for applying the comparative method to categorical traits on larger data sets with more species and more complex trait evolution than have previously been analyzed.
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Affiliation(s)
- Ruby Redlich
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Amanda Kowalczyk
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Michael Tene
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Heather H Sestili
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kathleen Foley
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Elysia Saputra
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Nathan Clark
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Maria Chikina
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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13
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Kopania EEK, Thomas GWC, Hutter CR, Mortimer SME, Callahan CM, Roycroft E, Achmadi AS, Breed WG, Clark NL, Esselstyn JA, Rowe KC, Good JM. Sperm competition intensity shapes divergence in both sperm morphology and reproductive genes across murine rodents. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.30.555585. [PMID: 37693452 PMCID: PMC10491253 DOI: 10.1101/2023.08.30.555585] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
It remains unclear how variation in the intensity of sperm competition shapes phenotypic and molecular evolution across clades. Mice and rats in the subfamily Murinae are a rapid radiation exhibiting incredible diversity in sperm morphology and production. We combined phenotypic and genomic data to perform phylogenetic comparisons of male reproductive traits and genes across 78 murine species. We identified several shifts towards smaller relative testes mass, presumably reflecting reduced sperm competition. Several sperm traits were associated with relative testes mass, suggesting that mating system evolution selects for convergent suites of traits related to sperm competitive ability. We predicted that sperm competition would also drive more rapid molecular divergence in species with large testes. Contrary to this, we found that many spermatogenesis genes evolved more rapidly in species with smaller relative testes mass due to relaxed purifying selection. While some reproductive genes evolved rapidly under recurrent positive selection, relaxed selection played a greater role in underlying rapid evolution in small testes species. Our work demonstrates that postcopulatory sexual selection can impose strong purifying selection shaping the evolution of male reproduction, and that broad patterns of molecular evolution may help identify genes that contribute to male fertility.
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14
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Schraiber JG, Edge MD, Pennell M. Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations. PLoS Biol 2024; 22:e3002847. [PMID: 39383205 PMCID: PMC11493298 DOI: 10.1371/journal.pbio.3002847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 10/21/2024] [Accepted: 09/17/2024] [Indexed: 10/11/2024] Open
Abstract
In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype or environment and a focal trait. In these 2 fields, there are sophisticated but disparate statistical traditions aimed at these tasks. The disconnect between their respective approaches is becoming untenable as questions in medicine, conservation biology, and evolutionary biology increasingly rely on integrating data from within and among species, and once-clear conceptual divisions are becoming increasingly blurred. To help bridge this divide, we lay out a general model describing the covariance between the genetic contributions to the quantitative phenotypes of different individuals. Taking this approach shows that standard models in both statistical genetics (e.g., genome-wide association studies; GWAS) and phylogenetic comparative biology (e.g., phylogenetic regression) can be interpreted as special cases of this more general quantitative-genetic model. The fact that these models share the same core architecture means that we can build a unified understanding of the strengths and limitations of different methods for controlling for genetic structure when testing for associations. We develop intuition for why and when spurious correlations may occur analytically and conduct population-genetic and phylogenetic simulations of quantitative traits. The structural similarity of problems in statistical genetics and phylogenetics enables us to take methodological advances from one field and apply them in the other. We demonstrate by showing how a standard GWAS technique-including both the genetic relatedness matrix (GRM) as well as its leading eigenvectors, corresponding to the principal components of the genotype matrix, in a regression model-can mitigate spurious correlations in phylogenetic analyses. As a case study, we re-examine an analysis testing for coevolution of expression levels between genes across a fungal phylogeny and show that including eigenvectors of the covariance matrix as covariates decreases the false positive rate while simultaneously increasing the true positive rate. More generally, this work provides a foundation for more integrative approaches for understanding the genetic architecture of phenotypes and how evolutionary processes shape it.
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Affiliation(s)
- Joshua G. Schraiber
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, United States of America
| | - Michael D. Edge
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, United States of America
| | - Matt Pennell
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, United States of America
- Department of Biological Sciences, University of Southern California, Los Angeles, California, United States of America
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15
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Morales AE, Burbrink FT, Segall M, Meza M, Munegowda C, Webala PW, Patterson BD, Thong VD, Ruedi M, Hiller M, Simmons NB. Distinct Genes with Similar Functions Underlie Convergent Evolution in Myotis Bat Ecomorphs. Mol Biol Evol 2024; 41:msae165. [PMID: 39116340 PMCID: PMC11371419 DOI: 10.1093/molbev/msae165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 07/01/2024] [Accepted: 07/24/2024] [Indexed: 08/10/2024] Open
Abstract
Convergence offers an opportunity to explore to what extent evolution can be predictable when genomic composition and environmental triggers are similar. Here, we present an emergent model system to study convergent evolution in nature in a mammalian group, the bat genus Myotis. Three foraging strategies-gleaning, trawling, and aerial hawking, each characterized by different sets of phenotypic features-have evolved independently multiple times in different biogeographic regions in isolation for millions of years. To investigate the genomic basis of convergence and explore the functional genomic changes linked to ecomorphological convergence, we sequenced and annotated 17 new genomes and screened 16,426 genes for positive selection and associations between relative evolutionary rates and foraging strategies across 30 bat species representing all Myotis ecomorphs across geographic regions as well as among sister groups. We identify genomic changes that describe both phylogenetic and ecomorphological trends. We infer that colonization of new environments may have first required changes in genes linked to hearing sensory perception, followed by changes linked to fecundity and development, metabolism of carbohydrates, and heme degradation. These changes may be linked to prey acquisition and digestion and match phylogenetic trends. Our findings also suggest that the repeated evolution of ecomorphs does not always involve changes in the same genes but rather in genes with the same molecular functions such as developmental and cellular processes.
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Affiliation(s)
- Ariadna E Morales
- Department of Mammalogy, Division of Vertebrate Zoology, American Museum of Natural History, New York, USA
- Department of Herpetology, Division of Vertebrate Zoology, American Museum of Natural History, New York, USA
- Centre for Translational Biodiversity Genomics, Frankfurt am Main, Hessen, Germany
- Senckenberg Research Institute, Frankfurt am Main, Hessen, Germany
- Faculty of Biosciences, Goethe-University, Frankfurt am Main, Hessen, Germany
| | - Frank T Burbrink
- Department of Herpetology, Division of Vertebrate Zoology, American Museum of Natural History, New York, USA
| | - Marion Segall
- Department of Herpetology, Division of Vertebrate Zoology, American Museum of Natural History, New York, USA
- Institut de Systématique, Evolution, Biodiversité (ISYEB), UMR 7205, Muséum National d’Histoire Naturelle, CNRS, SU, EPHE, UA, CP 50, Paris, France
- Department of Life Sciences, The Natural History Museum, London SW7 5BD, UK
| | - Maria Meza
- Department of Mammalogy, Division of Vertebrate Zoology, American Museum of Natural History, New York, USA
- Escuela de Biología, Universidad Industrial de Santander, Bucaramanga, Santander, Colombia
| | - Chetan Munegowda
- Centre for Translational Biodiversity Genomics, Frankfurt am Main, Hessen, Germany
- Senckenberg Research Institute, Frankfurt am Main, Hessen, Germany
- Faculty of Biosciences, Goethe-University, Frankfurt am Main, Hessen, Germany
| | - Paul W Webala
- Department of Forestry and Wildlife Management, Maasai Mara University, Narok 20500, Kenya
| | - Bruce D Patterson
- Negaunee Integrative Research Center, Field Museum of Natural History, Chicago, USA
| | - Vu Dinh Thong
- Institute of Ecology and Biological Resources, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet Road, Cau Giay District, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet Road, Cau Giay District, Hanoi, Vietnam
| | - Manuel Ruedi
- Department of Mammalogy and Ornithology, Natural History Museum of Geneva, Geneva 1208, Switzerland
| | - Michael Hiller
- Centre for Translational Biodiversity Genomics, Frankfurt am Main, Hessen, Germany
- Senckenberg Research Institute, Frankfurt am Main, Hessen, Germany
- Faculty of Biosciences, Goethe-University, Frankfurt am Main, Hessen, Germany
| | - Nancy B Simmons
- Department of Mammalogy, Division of Vertebrate Zoology, American Museum of Natural History, New York, USA
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16
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Zou D, Huang S, Tian S, Kilunda FK, Murphy RW, Dahn HA, Zhou Y, Lee PS, Chen JM. Comparative genomics sheds new light on the convergent evolution of infrared vision in snakes. Proc Biol Sci 2024; 291:20240818. [PMID: 39043244 PMCID: PMC11265913 DOI: 10.1098/rspb.2024.0818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/30/2024] [Accepted: 06/19/2024] [Indexed: 07/25/2024] Open
Abstract
Infrared vision is a highly specialized sensory system that evolved independently in three clades of snakes. Apparently, convergent evolution occurred in the transient receptor potential ankyrin 1 (TRPA1) proteins of infrared-sensing snakes. However, this gene can only explain how infrared signals are received, and not the transduction and processing of those signals. We sequenced the genome of Xenopeltis unicolor, a key outgroup species of pythons, and performed a genome-wide analysis of convergence between two clades of infrared-sensing snakes. Our results revealed pervasive molecular adaptation in pathways associated with neural development and other functions, with parallel selection on loci associated with trigeminal nerve structural organization. In addition, we found evidence of convergent amino acid substitutions in a set of genes, including TRPA1 and TRPM2. The analysis also identified convergent accelerated evolution in non-coding elements near 12 genes involved in facial nerve structural organization and optic nerve development. Thus, convergent evolution occurred across multiple dimensions of infrared vision in vipers and pythons, as well as amino acid substitutions, non-coding elements, genes and functions. These changes enabled independent groups of snakes to develop and use infrared vision.
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Affiliation(s)
- Dahu Zou
- Engineering Research Center of Eco-Environment in Three Gorges Reservoir Region of Ministry of Education, China Three Gorges University, Yichang, Hubei443002, People’s Republic of China
| | - Song Huang
- The Anhui Provincial Key Laboratory of Biodiversity Conservation and Ecological Security in the Yangtze River Basin, College of Life Sciences, Anhui Normal University, Wuhu, Anhui241000, People’s Republic of China
| | - Shilin Tian
- Novogene Bioinformatics Institute, Beijing100000, People’s Republic of China
| | - Felista Kasyoka Kilunda
- Key Laboratory of Genetic Evolution and Animal Models and Yunnan Key Laboratory of Biodiversity and Ecological Conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan650223, People’s Republic of China
| | - Robert W. Murphy
- Reptilia Zoo and Education Centre, 2501 Rutherford Road, Vaughan, ONL4K 2N6, Canada
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ONM5S 2C6, Canada
| | - Hollis A. Dahn
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ONM5S 2C6, Canada
| | - Youbing Zhou
- Engineering Research Center of Eco-Environment in Three Gorges Reservoir Region of Ministry of Education, China Three Gorges University, Yichang, Hubei443002, People’s Republic of China
| | - Ping-Shin Lee
- The Anhui Provincial Key Laboratory of Biodiversity Conservation and Ecological Security in the Yangtze River Basin, College of Life Sciences, Anhui Normal University, Wuhu, Anhui241000, People’s Republic of China
| | - Jin-Min Chen
- The Anhui Provincial Key Laboratory of Biodiversity Conservation and Ecological Security in the Yangtze River Basin, College of Life Sciences, Anhui Normal University, Wuhu, Anhui241000, People’s Republic of China
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17
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Matsuda Y, Makino T. Comparative genomics reveals convergent signals associated with the high metabolism and longevity in birds and bats. Proc Biol Sci 2024; 291:20241068. [PMID: 39191281 DOI: 10.1098/rspb.2024.1068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 06/27/2024] [Accepted: 07/24/2024] [Indexed: 08/29/2024] Open
Abstract
Birds and bats have long lifespans relative to their body size compared with non-flying animals. However, the genomic basis associated with longer lifespan of flying species despite their higher metabolism was unclear. In this study, we hypothesized that genes involved in the regulation of metabolism and lifespan changed with the acquisition of flight and searched for genes that show specific evolutionary patterns in flying species. As a result, we identified several genes that show different evolutionary rates in bird and bat lineages. Genes in pathways involved in lifespan regulation were conserved in birds, while they evolved at an accelerated rate in bats. We also searched for genes in which convergent amino acid substitutions occurred in birds and bats and found such substitutions in genes involved in cancer, reactive oxygen species control and immunity. Our study revealed genomic changes associated with the acquisition of flight in birds and bats and suggested that multiple genes involved in the regulation of lifespan and metabolism support both high metabolism and longevity in flying species.
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Affiliation(s)
- Yuki Matsuda
- United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology, Saiwai-cho , Fuchu-shi, Tokyo 183-8509, Japan
- Graduate School of Life Sciences, Tohoku University, Aoba-ku , Sendai 980-8578, Japan
| | - Takashi Makino
- Graduate School of Life Sciences, Tohoku University, Aoba-ku , Sendai 980-8578, Japan
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18
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Huang X, Dong G, Fan H, Zhou W, Huang G, Guan D, Zhang D, Wei F. The genome of African manatee Trichechus senegalensis reveals secondary adaptation to the aquatic environment. iScience 2024; 27:110394. [PMID: 39092175 PMCID: PMC11292518 DOI: 10.1016/j.isci.2024.110394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 05/26/2024] [Accepted: 06/25/2024] [Indexed: 08/04/2024] Open
Abstract
Sirenians exhibit unique aquatic adaptations, showcasing both convergent adaptive features shared with cetaceans and unique characteristics such as cold sensitivity and dense bones. Here, we report a chromosome-level genome of the African manatee (Trichechus senegalensis) with high continuity, completeness, and accuracy. We found that genes associated with osteopetrosis have undergone positive selection (CSF1R and LRRK1) or pseudogenized (FAM111A and IGSF23) in the African manatee, potentially contributing to the dense bone formation. The loss of KCNK18 may have increased their sensitivity to cold water temperatures. Moreover, we identified convergent evolutionary signatures in 392 genes among fully aquatic mammals, primarily enriched in skin or skeletal system development and circadian rhythm, which contributed to the transition from terrestrial to fully aquatic lifestyles. The African manatee currently possesses a small effective population size and low genome-wide heterozygosity. Overall, our study provides genetic resources for understanding the evolutionary characteristics and conservation efforts of this species.
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Affiliation(s)
- Xin Huang
- Center for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guixin Dong
- Guangdong Chimelong Group, Co., Ltd., Guangzhou 511400, China
| | - Huizhong Fan
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Wenliang Zhou
- Center for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
| | - Guangping Huang
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Jiangxi Provincial Key Laboratory of Conservation Biology, College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China
| | - Dengfeng Guan
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Delu Zhang
- Chimelong Ocean Kingdom, Zhuhai 519000, China
| | - Fuwen Wei
- Center for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Jiangxi Provincial Key Laboratory of Conservation Biology, College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China
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19
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Whittle CA, Extavour CG. Gene Protein Sequence Evolution Can Predict the Rapid Divergence of Ovariole Numbers in the Drosophila melanogaster Subgroup. Genome Biol Evol 2024; 16:evae118. [PMID: 38848313 PMCID: PMC11272079 DOI: 10.1093/gbe/evae118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 05/01/2024] [Accepted: 05/30/2024] [Indexed: 06/09/2024] Open
Abstract
Ovaries play key roles in fitness and evolution: they are essential female reproductive structures that develop and house the eggs in sexually reproducing animals. In Drosophila, the mature ovary contains multiple tubular egg-producing structures known as ovarioles. Ovarioles arise from somatic cellular structures in the larval ovary called terminal filaments (TFs), formed by TF cells and subsequently enclosed by sheath (SH) cells. As in many other insects, ovariole number per female varies extensively in Drosophila. At present, however, there is a striking gap of information on genetic mechanisms and evolutionary forces that shape the well-documented rapid interspecies divergence of ovariole numbers. To address this gap, here we studied genes associated with Drosophila melanogaster ovariole number or functions based on recent experimental and transcriptional datasets from larval ovaries, including TFs and SH cells, and assessed their rates and patterns of molecular evolution in five closely related species of the melanogaster subgroup that exhibit species-specific differences in ovariole numbers. From comprehensive analyses of protein sequence evolution (dN/dS), branch-site positive selection, expression specificity (tau), and phylogenetic regressions (phylogenetic generalized least squares), we report evidence of 42 genes that showed signs of playing roles in the genetic basis of interspecies evolutionary change of Drosophila ovariole number. These included the signaling genes upd2 and Ilp5 and extracellular matrix genes vkg and Col4a1, whose dN/dS predicted ovariole numbers among species. Together, we propose a model whereby a set of ovariole-involved gene proteins have an enhanced evolvability, including adaptive evolution, facilitating rapid shifts in ovariole number among Drosophila species.
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Affiliation(s)
- Carrie A Whittle
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Cassandra G Extavour
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
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20
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Dong Z, Wang C, Qu Q. WGCCRR: a web-based tool for genome-wide screening of convergent indels and substitutions of amino acids. BIOINFORMATICS ADVANCES 2024; 4:vbae070. [PMID: 38808070 PMCID: PMC11132816 DOI: 10.1093/bioadv/vbae070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 04/05/2024] [Accepted: 05/23/2024] [Indexed: 05/30/2024]
Abstract
Summary Genome-wide analyses of proteincoding gene sequences are being employed to examine the genetic basis of adaptive evolution in many organismal groups. Previous studies have revealed that convergent/parallel adaptive evolution may be caused by convergent/parallel amino acid changes. Similarly, detailed analysis of lineage-specific amino acid changes has shown correlations with certain lineage-specific traits. However, experimental validation remains the ultimate measure of causality. With the increasing availability of genomic data, a streamlined tool for such analyses would facilitate and expedite the screening of genetic loci that hold potential for adaptive evolution, while alleviating the bioinformatic burden for experimental biologists. In this study, we present a user-friendly web-based tool called WGCCRR (Whole Genome Comparative Coding Region Read) designed to screen both convergent/parallel and lineage-specific amino acid changes on a genome-wide scale. Our tool allows users to replicate previous analyses with just a few clicks, and the exported results are straightforward to interpret. In addition, we have also included amino acid indels that are usually neglected in previous work. Our website provides an efficient platform for screening candidate loci for downstream experimental tests. Availability and Implementation The tool is available at: https://fishevo.xmu.edu.cn/.
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Affiliation(s)
- Zheng Dong
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xià-Mén, Fú-Jiàn 361102, China
| | - Chen Wang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xià-Mén, Fú-Jiàn 361102, China
| | - Qingming Qu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xià-Mén, Fú-Jiàn 361102, China
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21
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De-Kayne R, Perry BW, McGowan KL, Landers J, Arias-Rodriguez L, Greenway R, Rodríguez Peña CM, Tobler M, Kelley JL. Evolutionary Rate Shifts in Coding and Regulatory Regions Underpin Repeated Adaptation to Sulfidic Streams in Poeciliid Fishes. Genome Biol Evol 2024; 16:evae087. [PMID: 38788745 PMCID: PMC11126329 DOI: 10.1093/gbe/evae087] [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] [Accepted: 04/13/2024] [Indexed: 05/26/2024] Open
Abstract
Adaptation to extreme environments often involves the evolution of dramatic physiological changes. To better understand how organisms evolve these complex phenotypic changes, the repeatability and predictability of evolution, and possible constraints on adapting to an extreme environment, it is important to understand how adaptive variation has evolved. Poeciliid fishes represent a particularly fruitful study system for investigations of adaptation to extreme environments due to their repeated colonization of toxic hydrogen sulfide-rich springs across multiple species within the clade. Previous investigations have highlighted changes in the physiology and gene expression in specific species that are thought to facilitate adaptation to hydrogen sulfide-rich springs. However, the presence of adaptive nucleotide variation in coding and regulatory regions and the degree to which convergent evolution has shaped the genomic regions underpinning sulfide tolerance across taxa are unknown. By sampling across seven independent lineages in which nonsulfidic lineages have colonized and adapted to sulfide springs, we reveal signatures of shared evolutionary rate shifts across the genome. We found evidence of genes, promoters, and putative enhancer regions associated with both increased and decreased convergent evolutionary rate shifts in hydrogen sulfide-adapted lineages. Our analysis highlights convergent evolutionary rate shifts in sulfidic lineages associated with the modulation of endogenous hydrogen sulfide production and hydrogen sulfide detoxification. We also found that regions with shifted evolutionary rates in sulfide spring fishes more often exhibited convergent shifts in either the coding region or the regulatory sequence of a given gene, rather than both.
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Affiliation(s)
- Rishi De-Kayne
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | - Blair W Perry
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA
| | - Kerry L McGowan
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA
| | - Jake Landers
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA
| | - Lenin Arias-Rodriguez
- División Académica de Ciencias Biológicas, Universidad Juárez Autónoma de Tabasco (UJAT), Villahermosa, México
| | - Ryan Greenway
- Division of Biology, Kansas State University, Manhattan, KS 66506, USA
| | - Carlos M Rodríguez Peña
- Instituto de Investigaciones Botánicas y Zoológicas, Universidad Autónoma de Santo Domingo, Santo Domingo 10105, Dominican Republic
| | - Michael Tobler
- Department of Biology, University of Missouri–St. Louis, St. Louis, MO 63131, USA
- Whitney R. Harris World Ecology Center, University of Missouri–St. Louis, St. Louis, MO 63121, USA
- WildCare Institute, Saint Louis Zoo, St. Louis, MO 63110, USA
| | - Joanna L Kelley
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95060, USA
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22
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Wirthlin ME, Schmid TA, Elie JE, Zhang X, Kowalczyk A, Redlich R, Shvareva VA, Rakuljic A, Ji MB, Bhat NS, Kaplow IM, Schäffer DE, Lawler AJ, Wang AZ, Phan BN, Annaldasula S, Brown AR, Lu T, Lim BK, Azim E, Clark NL, Meyer WK, Pond SLK, Chikina M, Yartsev MM, Pfenning AR. Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements. Science 2024; 383:eabn3263. [PMID: 38422184 PMCID: PMC11313673 DOI: 10.1126/science.abn3263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/20/2024] [Indexed: 03/02/2024]
Abstract
Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.
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Affiliation(s)
- Morgan E. Wirthlin
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Tobias A. Schmid
- Helen Wills Neuroscience Institute, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Julie E. Elie
- Helen Wills Neuroscience Institute, University of California, Berkeley; Berkeley, CA 94708, USA
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Amanda Kowalczyk
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Ruby Redlich
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Varvara A. Shvareva
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Ashley Rakuljic
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Maria B. Ji
- Department of Psychology, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Ninad S. Bhat
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Irene M. Kaplow
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Daniel E. Schäffer
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Alyssa J. Lawler
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
- Department of Biological Sciences, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Andrew Z. Wang
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - BaDoi N. Phan
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Siddharth Annaldasula
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Ashley R. Brown
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Present address: Department of Biomedical Engineering, Duke University; Durham, NC 27705
| | - Tianyu Lu
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Byung Kook Lim
- Neurobiology section, Division of Biological Science, University of California, San Diego; La Jolla, CA 92093, USA
| | - Eiman Azim
- Molecular Neurobiology Laboratory, Salk Institute for Biological Studies; La Jolla, CA 92037, USA
| | - Nathan L. Clark
- Department of Biological Sciences, University of Pittsburgh; Pittsburgh, PA 15213, USA
| | - Wynn K. Meyer
- Department of Biological Sciences, Lehigh University; Bethlehem, PA 18015, USA
| | | | - Maria Chikina
- Department of Computational and Systems Biology, University of Pittsburgh; Pittsburgh, PA 15213, USA
| | - Michael M. Yartsev
- Helen Wills Neuroscience Institute, University of California, Berkeley; Berkeley, CA 94708, USA
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA 94708, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, Carnegie Mellon University; Pittsburgh, PA 15213, USA
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23
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Perron N, Kirst M, Chen S. Bringing CAM photosynthesis to the table: Paving the way for resilient and productive agricultural systems in a changing climate. PLANT COMMUNICATIONS 2024; 5:100772. [PMID: 37990498 PMCID: PMC10943566 DOI: 10.1016/j.xplc.2023.100772] [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: 06/20/2023] [Revised: 07/27/2023] [Accepted: 11/20/2023] [Indexed: 11/23/2023]
Abstract
Modern agricultural systems are directly threatened by global climate change and the resulting freshwater crisis. A considerable challenge in the coming years will be to develop crops that can cope with the consequences of declining freshwater resources and changing temperatures. One approach to meeting this challenge may lie in our understanding of plant photosynthetic adaptations and water use efficiency. Plants from various taxa have evolved crassulacean acid metabolism (CAM), a water-conserving adaptation of photosynthetic carbon dioxide fixation that enables plants to thrive under semi-arid or seasonally drought-prone conditions. Although past research on CAM has led to a better understanding of the inner workings of plant resilience and adaptation to stress, successful introduction of this pathway into C3 or C4 plants has not been reported. The recent revolution in molecular, systems, and synthetic biology, as well as innovations in high-throughput data generation and mining, creates new opportunities to uncover the minimum genetic tool kit required to introduce CAM traits into drought-sensitive crops. Here, we propose four complementary research avenues to uncover this tool kit. First, genomes and computational methods should be used to improve understanding of the nature of variations that drive CAM evolution. Second, single-cell 'omics technologies offer the possibility for in-depth characterization of the mechanisms that trigger environmentally controlled CAM induction. Third, the rapid increase in new 'omics data enables a comprehensive, multimodal exploration of CAM. Finally, the expansion of functional genomics methods is paving the way for integration of CAM into farming systems.
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Affiliation(s)
- Noé Perron
- Plant Molecular and Cellular Biology Program, University of Florida, Gainesville, FL 32608, USA
| | - Matias Kirst
- Plant Molecular and Cellular Biology Program, University of Florida, Gainesville, FL 32608, USA; School of Forest, Fisheries and Geomatics Sciences, University of Florida, Gainesville, FL 32603, USA.
| | - Sixue Chen
- Department of Biology, University of Mississippi, Oxford, MS 38677-1848, USA.
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24
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Schraiber JG, Edge MD, Pennell M. Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.10.579721. [PMID: 38496530 PMCID: PMC10942266 DOI: 10.1101/2024.02.10.579721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype or environment and a focal trait. In these two fields, there are sophisticated but disparate statistical traditions aimed at these tasks. The disconnect between their respective approaches is becoming untenable as questions in medicine, conservation biology, and evolutionary biology increasingly rely on integrating data from within and among species, and once-clear conceptual divisions are becoming increasingly blurred. To help bridge this divide, we derive a general model describing the covariance between the genetic contributions to the quantitative phenotypes of different individuals. Taking this approach shows that standard models in both statistical genetics (e.g., Genome-Wide Association Studies; GWAS) and phylogenetic comparative biology (e.g., phylogenetic regression) can be interpreted as special cases of this more general quantitative-genetic model. The fact that these models share the same core architecture means that we can build a unified understanding of the strengths and limitations of different methods for controlling for genetic structure when testing for associations. We develop intuition for why and when spurious correlations may occur using analytical theory and conduct population-genetic and phylogenetic simulations of quantitative traits. The structural similarity of problems in statistical genetics and phylogenetics enables us to take methodological advances from one field and apply them in the other. We demonstrate this by showing how a standard GWAS technique-including both the genetic relatedness matrix (GRM) as well as its leading eigenvectors, corresponding to the principal components of the genotype matrix, in a regression model-can mitigate spurious correlations in phylogenetic analyses. As a case study of this, we re-examine an analysis testing for co-evolution of expression levels between genes across a fungal phylogeny, and show that including covariance matrix eigenvectors as covariates decreases the false positive rate while simultaneously increasing the true positive rate. More generally, this work provides a foundation for more integrative approaches for understanding the genetic architecture of phenotypes and how evolutionary processes shape it.
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25
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Sakamoto F, Kanamori S, Díaz LM, Cádiz A, Ishii Y, Yamaguchi K, Shigenobu S, Nakayama T, Makino T, Kawata M. Detection of evolutionary conserved and accelerated genomic regions related to adaptation to thermal niches in Anolis lizards. Ecol Evol 2024; 14:e11117. [PMID: 38455144 PMCID: PMC10920033 DOI: 10.1002/ece3.11117] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 02/18/2024] [Accepted: 02/22/2024] [Indexed: 03/09/2024] Open
Abstract
Understanding the genetic basis for adapting to thermal environments is important due to serious effects of global warming on ectothermic species. Various genes associated with thermal adaptation in lizards have been identified mainly focusing on changes in gene expression or the detection of positively selected genes using coding regions. Only a few comprehensive genome-wide analyses have included noncoding regions. This study aimed to identify evolutionarily conserved and accelerated genomic regions using whole genomes of eight Anolis lizard species that have repeatedly adapted to similar thermal environments in multiple lineages. Evolutionarily conserved genomic regions were extracted as regions with overall sequence conservation (regions with fewer base substitutions) across all lineages compared with the neutral model. Genomic regions that underwent accelerated evolution in the lineage of interest were identified as those with more base substitutions in the target branch than in the entire background branch. Conserved elements across all branches were relatively abundant in "intergenic" genomic regions among noncoding regions. Accelerated regions (ARs) of each lineage contained a significantly greater proportion of noncoding RNA genes than the entire multiple alignment. Common genes containing ARs within 5 kb of their vicinity in lineages with similar thermal habitats were identified. Many genes associated with circadian rhythms and behavior were found in hot-open and cool-shaded habitat lineages. These genes might play a role in contributing to thermal adaptation and assist future studies examining the function of genes involved in thermal adaptation via genome editing.
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Affiliation(s)
- Fuku Sakamoto
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
| | | | - Luis M. Díaz
- National Museum of Natural History of CubaHavanaCuba
| | - Antonio Cádiz
- Faculty of BiologyUniversity of HavanaHavanaCuba
- Present address:
Department of BiologyUniversity of MiamiCoral GablesFloridaUSA
| | - Yuu Ishii
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
| | | | - Shuji Shigenobu
- Trans‐Omics FacilityNational Institute for Basic BiologyOkazakiJapan
- Department of Basic Biology, School of Life ScienceThe Graduate University for Advanced Studies, SOKENDAIOkazakiJapan
| | - Takuro Nakayama
- Division of Life Sciences, Center for Computational SciencesUniversity of TsukubaTsukubaJapan
| | - Takashi Makino
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
| | - Masakado Kawata
- Graduate School of Life SciencesTohoku UniversitySendaiJapan
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26
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Little J, Chikina M, Clark NL. Evolutionary rate covariation is a reliable predictor of co-functional interactions but not necessarily physical interactions. eLife 2024; 12:RP93333. [PMID: 38415754 PMCID: PMC10942632 DOI: 10.7554/elife.93333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024] Open
Abstract
Co-functional proteins tend to have rates of evolution that covary over time. This correlation between evolutionary rates can be measured over the branches of a phylogenetic tree through methods such as evolutionary rate covariation (ERC), and then used to construct gene networks by the identification of proteins with functional interactions. The cause of this correlation has been hypothesized to result from both compensatory coevolution at physical interfaces and nonphysical forces such as shared changes in selective pressure. This study explores whether coevolution due to compensatory mutations has a measurable effect on the ERC signal. We examined the difference in ERC signal between physically interacting protein domains within complexes compared to domains of the same proteins that do not physically interact. We found no generalizable relationship between physical interaction and high ERC, although a few complexes ranked physical interactions higher than nonphysical interactions. Therefore, we conclude that coevolution due to physical interaction is weak, but present in the signal captured by ERC, and we hypothesize that the stronger signal instead comes from selective pressures on the protein as a whole and maintenance of the general function.
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Affiliation(s)
- Jordan Little
- Department of Human Genetics, University of UtahSalt Lake CityUnited States
| | - Maria Chikina
- Department of Computational Biology, University of PittsburghPittsburghUnited States
| | - Nathan L Clark
- Department of Human Genetics, University of UtahSalt Lake CityUnited States
- Department of Biological Sciences, University of PittsburghPittsburghUnited States
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27
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Ports BL, Jensen-Seaman MI. Convergent rates of protein evolution identify novel targets of sexual selection in primates. Evolution 2024; 78:364-377. [PMID: 37864838 PMCID: PMC10834059 DOI: 10.1093/evolut/qpad188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 10/02/2023] [Accepted: 10/19/2023] [Indexed: 10/23/2023]
Abstract
Sexual selection is the differential reproductive success of individuals, resulting from competition for mates, mate choice, or success in fertilization. In primates, this selective pressure often leads to the development of exaggerated traits which play a role in sexual competition and successful reproduction. In order to gain insight into the mechanisms driving the development of sexually selected traits, we used an unbiased genome-wide approach across 21 primate species to correlate individual rates of protein evolution to relative testes size and sexual dimorphism in body size, 2 anatomical hallmarks of sexual selection in mammals. Among species with presumed high levels of sperm competition, we detected strong conservation of testes-specific proteins responsible for spermatogenesis and ciliary form and function. In contrast, we identified accelerated evolution of female reproductive proteins expressed in the vagina, cervix, and fallopian tubes in these same species. Additionally, we found accelerated protein evolution in lymphoid tissue, indicating that adaptive immune functions may also be influenced by sexual selection. This study demonstrates the distinct complexity of sexual selection in primates revealing contrasting patterns of protein evolution between male and female reproductive tissues.
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Affiliation(s)
- Bri L Ports
- Department of Biological Sciences, Duquesne University, Pittsburgh, PA, United States
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28
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Redlich R, Kowalczyk A, Tene M, Sestili HH, Foley K, Saputra E, Clark N, Chikina M, Meyer WK, Pfenning A. RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.06.570425. [PMID: 38106136 PMCID: PMC10723433 DOI: 10.1101/2023.12.06.570425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Comparative genomics approaches seek to associate evolutionary genetic changes with the evolution of phenotypes across a phylogeny. Many of these methods, including our evolutionary rates based method, RERconverge, lack the capability of analyzing non-ordinal, multicategorical traits. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of multi-categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogenetic permulations on multi-categorical traits. In addition to demonstrating our new method on a three-category diet phenotype, we compare its performance to naive pairwise binary RERconverge analyses and two existing methods for comparative genomic analyses of categorical traits: phylogenetic simulations and a phylogenetic signal based method. We also present a diagnostic analysis of the new permulations approach demonstrating how the method scales with the number of species and the number of categories included in the analysis. Our results show that our new categorical method outperforms phylogenetic simulations at identifying genes and enriched pathways significantly associated with the diet phenotype and that the new ancestral reconstruction drives an improvement in our ability to capture diet-related enriched pathways. Our categorical permulations were able to account for non-uniform null distributions and correct for non-independence in gene rank during pathway enrichment analysis. The categorical expansion to RERconverge will provide a strong foundation for applying the comparative method to categorical traits on larger data sets with more species and more complex trait evolution.
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29
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Steenwyk JL, Li Y, Zhou X, Shen XX, Rokas A. Incongruence in the phylogenomics era. Nat Rev Genet 2023; 24:834-850. [PMID: 37369847 PMCID: PMC11499941 DOI: 10.1038/s41576-023-00620-x] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2023] [Indexed: 06/29/2023]
Abstract
Genome-scale data and the development of novel statistical phylogenetic approaches have greatly aided the reconstruction of a broad sketch of the tree of life and resolved many of its branches. However, incongruence - the inference of conflicting evolutionary histories - remains pervasive in phylogenomic data, hampering our ability to reconstruct and interpret the tree of life. Biological factors, such as incomplete lineage sorting, horizontal gene transfer, hybridization, introgression, recombination and convergent molecular evolution, can lead to gene phylogenies that differ from the species tree. In addition, analytical factors, including stochastic, systematic and treatment errors, can drive incongruence. Here, we review these factors, discuss methodological advances to identify and handle incongruence, and highlight avenues for future research.
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Affiliation(s)
- Jacob L Steenwyk
- Howards Hughes Medical Institute and the Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN, USA
| | - Yuanning Li
- Institute of Marine Science and Technology, Shandong University, Qingdao, China
| | - Xiaofan Zhou
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou, China
| | - Xing-Xing Shen
- Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Insect Sciences, Zhejiang University, Hangzhou, China
| | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA.
- Vanderbilt Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN, USA.
- Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.
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30
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Liao X, Zhou S, Zeng D, Ying W, Lian D, Zhang M, Ge J, Chen M, Liu Y, Lin Y. Roles of the crucial mitochondrial DNA in hypertrophic cardiomyopathy prognosis and diagnosis: A review. Medicine (Baltimore) 2023; 102:e36368. [PMID: 38050313 PMCID: PMC10695538 DOI: 10.1097/md.0000000000036368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/08/2023] [Indexed: 12/06/2023] Open
Abstract
Mitochondrial DNA is implicated in hypertrophic cardiomyopathy (HCM) development. We aimed to identify valuable mtDNAs that contribute to the development of HCM. Differentially expressed mitochondrial DNAs (DEMGs) between HCM and controls were screened. GO and KEGG functional enrichment analyses were performed, and the optimum genes were explored using the LASSO regression mode and SVM-RFE model. A diagnostic scoring model was constructed and verified using ROC curves. Mitochondria-based subtypes were identified. Immune performance among the subtypes including immune cells, immune checkpoint genes, and HLA family genes was analyzed. Finally, an mRNA-transcription factor (TF)-miRNA network was constructed using Cytoscape software. Twelve DEMGs in HCM were selected. Among them, 6 DEMGs, including PDK4, MGST1, TOMM40, LYPLAL1, GATM, and CPT1B were demonstrated as DEMGs at the point of intersection of Lasso regression and SVM-RFE. The ROC of the model for the training and validation datasets was 0.999 and 0.958, respectively. Two clusters were divided, and 4 immune cell types were significantly different between the 2 clusters, including resting mast cells, macrophages M2, and plasma cells. Nine upregulated KEGG pathways were enriched in cluster 1 vs. cluster 2 including O-glycan biosynthesis, the ErbB signaling pathway, and the GnRH signaling pathway. Meanwhile, 49 down-regulated pathways were enriched such as the toll-like signaling pathway and natural killer cell-mediated cytotoxicity pathway. The 6 gene-based mRNA-TF-miRNA networks included other 133 TFs and 18 miRNAs. Six DEMGs in HCM, including PDK4, MGST1, TOMM40, LYPLAL1, GATM, and CPT1B, can be indicative of HCM prognosis or disease progression.
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Affiliation(s)
- Xuewen Liao
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou City, China
| | - Shunkai Zhou
- Department of Thoracic and Cardiac Surgery, 900th Hospital of the Joint Logistics Support Force of the Chinese People’s Liberation Army, Fuzhou City, China
| | - Dehua Zeng
- Department of Pathology, 900th Hospital of the Joint Logistics Support Force of the Chinese People’s Liberation Army, Fuzhou City, China
| | - Wenmin Ying
- Department of Radiotherapy, Fuding Hospital, Fuding City, China
| | - Duohuang Lian
- Department of Thoracic and Cardiac Surgery, 900th Hospital of the Joint Logistics Support Force of the Chinese People’s Liberation Army, Fuzhou City, China
| | - Meiqing Zhang
- Department of Thoracic and Cardiac Surgery, 900th Hospital of the Joint Logistics Support Force of the Chinese People’s Liberation Army, Fuzhou City, China
| | - Jianjun Ge
- Department of Thoracic Surgery, No. 2 Hospital of Nanping City, Nanping City, China
| | - Mengmeng Chen
- Department of Thoracic and Cardiac Surgery, 900th Hospital of the Joint Logistics Support Force of the Chinese People’s Liberation Army, Fuzhou City, China
| | - Yaming Liu
- Department of Thoracic and Cardiac Surgery, 900th Hospital of the Joint Logistics Support Force of the Chinese People’s Liberation Army, Fuzhou City, China
| | - Yazhou Lin
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou City, China
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31
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Ramos E, Selleghin-Veiga G, Magpali L, Daros B, Silva F, Picorelli A, Freitas L, Nery MF. Molecular Footprints on Osmoregulation-Related Genes Associated with Freshwater Colonization by Cetaceans and Sirenians. J Mol Evol 2023; 91:865-881. [PMID: 38010516 DOI: 10.1007/s00239-023-10141-0] [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: 02/04/2023] [Accepted: 10/29/2023] [Indexed: 11/29/2023]
Abstract
The genetic basis underlying adaptive physiological mechanisms has been extensively explored in mammals after colonizing the seas. However, independent lineages of aquatic mammals exhibit complex patterns of secondary colonization in freshwater environments. This change in habitat represents new osmotic challenges, and additional changes in key systems, such as the osmoregulatory system, are expected. Here, we studied the selective regime on coding and regulatory regions of 20 genes related to the osmoregulation system in strict aquatic mammals from independent evolutionary lineages, cetaceans, and sirenians, with representatives in marine and freshwater aquatic environments. We identified positive selection signals in genes encoding the protein vasopressin (AVP) in mammalian lineages with secondary colonization in the fluvial environment and in aquaporins for lineages inhabiting the marine and fluvial environments. A greater number of sites with positive selection signals were found for the dolphin species compared to the Amazonian manatee. Only the AQP5 and AVP genes showed selection signals in more than one independent lineage of these mammals. Furthermore, the vasopressin gene tree indicates greater similarity in river dolphin sequences despite the independence of their lineages based on the species tree. Patterns of distribution and enrichment of Transcription Factors in the promoter regions of target genes were analyzed and appear to be phylogenetically conserved among sister species. We found accelerated evolution signs in genes ACE, AQP1, AQP5, AQP7, AVP, NPP4, and NPR1 for the fluvial mammals. Together, these results allow a greater understanding of the molecular bases of the evolution of genes responsible for osmotic control in aquatic mammals.
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Affiliation(s)
- Elisa Ramos
- Laboratório de Genômica Evolutiva., Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas, Cidade Universitária, Campinas, SP, 13083970, Brazil
| | - Giovanna Selleghin-Veiga
- Laboratório de Genômica Evolutiva., Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas, Cidade Universitária, Campinas, SP, 13083970, Brazil
| | - Letícia Magpali
- Laboratório de Genômica Evolutiva., Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas, Cidade Universitária, Campinas, SP, 13083970, Brazil
| | - Beatriz Daros
- Laboratório de Genômica Evolutiva., Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas, Cidade Universitária, Campinas, SP, 13083970, Brazil
| | - Felipe Silva
- Laboratório de Genômica Evolutiva., Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas, Cidade Universitária, Campinas, SP, 13083970, Brazil
| | - Agnello Picorelli
- Laboratório de Genômica Evolutiva., Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas, Cidade Universitária, Campinas, SP, 13083970, Brazil
| | - Lucas Freitas
- Laboratório de Genômica Evolutiva., Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas, Cidade Universitária, Campinas, SP, 13083970, Brazil
| | - Mariana F Nery
- Laboratório de Genômica Evolutiva., Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas, Cidade Universitária, Campinas, SP, 13083970, Brazil.
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32
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Johnson MR, Li S, Guerrero-Juarez CF, Miller P, Brack BJ, Mereby SA, Moreno JA, Feigin CY, Gaska J, Rivera-Perez JA, Nie Q, Ploss A, Shvartsman SY, Mallarino R. A multifunctional Wnt regulator underlies the evolution of rodent stripe patterns. Nat Ecol Evol 2023; 7:2143-2159. [PMID: 37813945 PMCID: PMC10839778 DOI: 10.1038/s41559-023-02213-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 08/27/2023] [Indexed: 10/11/2023]
Abstract
Animal pigment patterns are excellent models to elucidate mechanisms of biological organization. Although theoretical simulations, such as Turing reaction-diffusion systems, recapitulate many animal patterns, they are insufficient to account for those showing a high degree of spatial organization and reproducibility. Here, we study the coat of the African striped mouse (Rhabdomys pumilio) to uncover how periodic stripes form. Combining transcriptomics, mathematical modelling and mouse transgenics, we show that the Wnt modulator Sfrp2 regulates the distribution of hair follicles and establishes an embryonic prepattern that foreshadows pigment stripes. Moreover, by developing in vivo gene editing in striped mice, we find that Sfrp2 knockout is sufficient to alter the stripe pattern. Strikingly, mutants exhibited changes in pigmentation, revealing that Sfrp2 also regulates hair colour. Lastly, through evolutionary analyses, we find that striped mice have evolved lineage-specific changes in regulatory elements surrounding Sfrp2, many of which may be implicated in modulating the expression of this gene. Altogether, our results show that a single factor controls coat pattern formation by acting both as an orienting signalling mechanism and a modulator of pigmentation. More broadly, our work provides insights into how spatial patterns are established in developing embryos and the mechanisms by which phenotypic novelty originates.
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Affiliation(s)
- Matthew R Johnson
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Sha Li
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Christian F Guerrero-Juarez
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA
- Department of Mathematics, University of California, Irvine, CA, USA
- Center for Complex Biological Systems, University of California, Irvine, CA, USA
- NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA, USA
| | - Pearson Miller
- Center for Computational Biology, Flatiron Institute, New York, NY, USA
| | - Benjamin J Brack
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Sarah A Mereby
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Jorge A Moreno
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Charles Y Feigin
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Jenna Gaska
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | | | - Qing Nie
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA
- Department of Mathematics, University of California, Irvine, CA, USA
- Center for Complex Biological Systems, University of California, Irvine, CA, USA
- NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA, USA
| | - Alexander Ploss
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Stanislav Y Shvartsman
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
- Center for Computational Biology, Flatiron Institute, New York, NY, USA
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Ricardo Mallarino
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA.
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33
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Li S, Vazquez JM, Sudmant PH. The evolution of aging and lifespan. Trends Genet 2023; 39:830-843. [PMID: 37714733 PMCID: PMC11147682 DOI: 10.1016/j.tig.2023.08.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/17/2023]
Abstract
Aging is a nearly inescapable trait among organisms yet lifespan varies tremendously across different species and spans several orders of magnitude in vertebrates alone. This vast phenotypic diversity is driven by distinct evolutionary trajectories and tradeoffs that are reflected in patterns of diversification and constraint in organismal genomes. Age-specific impacts of selection also shape allele frequencies in populations, thus impacting disease susceptibility and environment-specific mortality risk. Further, the mutational processes that spawn this genetic diversity in both germline and somatic cells are strongly influenced by age and life history. We discuss recent advances in our understanding of the evolution of aging and lifespan at organismal, population, and cellular scales, and highlight outstanding questions that remain unanswered.
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Affiliation(s)
- Stacy Li
- Department of Integrative Biology, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA. USA
| | - Juan Manuel Vazquez
- Department of Integrative Biology, University of California, Berkeley, CA, USA
| | - Peter H Sudmant
- Department of Integrative Biology, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA. USA.
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34
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Eliason CM, Mellenthin LE, Hains T, McCullough JM, Pirro S, Andersen MJ, Hackett SJ. Genomic signatures of convergent shifts to plunge-diving behavior in birds. Commun Biol 2023; 6:1011. [PMID: 37875535 PMCID: PMC10598022 DOI: 10.1038/s42003-023-05359-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 09/14/2023] [Indexed: 10/26/2023] Open
Abstract
Understanding the genetic basis of convergence at broad phylogenetic scales remains a key challenge in biology. Kingfishers (Aves: Alcedinidae) are a cosmopolitan avian radiation with diverse colors, diets, and feeding behaviors-including the archetypal plunge-dive into water. Given the sensory and locomotor challenges associated with air-water transitions, kingfishers offer a powerful opportunity to explore the effects of convergent behaviors on the evolution of genomes and phenotypes, as well as direct comparisons between continental and island lineages. Here, we use whole-genome sequencing of 30 diverse kingfisher species to identify the genomic signatures associated with convergent feeding behaviors. We show that species with smaller ranges (i.e., on islands) have experienced stronger demographic fluctuations than those on continents, and that these differences have influenced the dynamics of molecular evolution. Comparative genomic analyses reveal positive selection and genomic convergence in brain and dietary genes in plunge-divers. These findings enhance our understanding of the connections between genotype and phenotype in a diverse avian radiation.
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Affiliation(s)
- Chad M Eliason
- Grainger Bioinformatics Center, The Field Museum, Chicago, IL, USA.
- Negaunee Integrative Research Center, The Field Museum, Chicago, IL, USA.
| | - Lauren E Mellenthin
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT, USA
| | - Taylor Hains
- Grainger Bioinformatics Center, The Field Museum, Chicago, IL, USA
- Negaunee Integrative Research Center, The Field Museum, Chicago, IL, USA
- Committee on Evolution Biology, University of Chicago, Chicago, IL, USA
| | - Jenna M McCullough
- Department of Biology and Museum of Southwestern Biology, University of New Mexico, Albuquerque, NM, USA
| | - Stacy Pirro
- Iridian Genomes, Inc., 6213 Swords Way, Bethesda, MD, USA
| | - Michael J Andersen
- Department of Biology and Museum of Southwestern Biology, University of New Mexico, Albuquerque, NM, USA
| | - Shannon J Hackett
- Committee on Evolution Biology, University of Chicago, Chicago, IL, USA
- Negaunee Integrative Research Center, The Field Museum, Chicago, IL, USA
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35
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Fouks B, Harrison MC, Mikhailova AA, Marchal E, English S, Carruthers M, Jennings EC, Chiamaka EL, Frigard RA, Pippel M, Attardo GM, Benoit JB, Bornberg-Bauer E, Tobe SS. Live-bearing cockroach genome reveals convergent evolutionary mechanisms linked to viviparity in insects and beyond. iScience 2023; 26:107832. [PMID: 37829199 PMCID: PMC10565785 DOI: 10.1016/j.isci.2023.107832] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 02/13/2023] [Accepted: 09/01/2023] [Indexed: 10/14/2023] Open
Abstract
Live birth (viviparity) has arisen repeatedly and independently among animals. We sequenced the genome and transcriptome of the viviparous Pacific beetle-mimic cockroach and performed comparative analyses with two other viviparous insect lineages, tsetse flies and aphids, to unravel the basis underlying the transition to viviparity in insects. We identified pathways undergoing adaptive evolution for insects, involved in urogenital remodeling, tracheal system, heart development, and nutrient metabolism. Transcriptomic analysis of cockroach and tsetse flies revealed that uterine remodeling and nutrient production are increased and the immune response is altered during pregnancy, facilitating structural and physiological changes to accommodate and nourish the progeny. These patterns of convergent evolution of viviparity among insects, together with similar adaptive mechanisms identified among vertebrates, highlight that the transition to viviparity requires changes in urogenital remodeling, enhanced tracheal and heart development (corresponding to angiogenesis in vertebrates), altered nutrient metabolism, and shifted immunity in animal systems.
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Affiliation(s)
- Bertrand Fouks
- University of Münster, Institute for Evolution and Biodiversity, Molecular Evolution and Bioinformatics, Hüfferstrasse 1, 48149 Münster, Germany
| | - Mark C. Harrison
- University of Münster, Institute for Evolution and Biodiversity, Molecular Evolution and Bioinformatics, Hüfferstrasse 1, 48149 Münster, Germany
| | - Alina A. Mikhailova
- University of Münster, Institute for Evolution and Biodiversity, Molecular Evolution and Bioinformatics, Hüfferstrasse 1, 48149 Münster, Germany
| | - Elisabeth Marchal
- Department of Biology, Molecular Developmental Physiology and Signal Transduction Lab., Division of Animal Physiology and Neurobiology, Naamsestraat 59-Box 2465, B-3000 Leuven, Belgium
| | - Sinead English
- School of Biological Sciences, University of Bristol, Bristol BS8 1TQ, UK
| | | | - Emily C. Jennings
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Ezemuoka L. Chiamaka
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Ronja A. Frigard
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Martin Pippel
- Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany
| | - Geoffrey M. Attardo
- Department of Entomology and Nematology, College of Agriculture and Environmental Sciences, University of California, Davis, Davis, CA, USA
| | - Joshua B. Benoit
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Erich Bornberg-Bauer
- University of Münster, Institute for Evolution and Biodiversity, Molecular Evolution and Bioinformatics, Hüfferstrasse 1, 48149 Münster, Germany
- Department of Protein Evolution, Max Planck Institute for Biology, Max-Planck-Ring 5, 72076 Tübingen, Germany
| | - Stephen S. Tobe
- Department of Biology, Molecular Developmental Physiology and Signal Transduction Lab., Division of Animal Physiology and Neurobiology, Naamsestraat 59-Box 2465, B-3000 Leuven, Belgium
- Department of Cell and Systems Biology, University of Toronto, Toronto, Canada
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36
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Yusuf LH, Saldívar Lemus Y, Thorpe P, Macías Garcia C, Ritchie MG. Genomic Signatures Associated with Transitions to Viviparity in Cyprinodontiformes. Mol Biol Evol 2023; 40:msad208. [PMID: 37789509 PMCID: PMC10568250 DOI: 10.1093/molbev/msad208] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 08/23/2023] [Accepted: 09/19/2023] [Indexed: 10/05/2023] Open
Abstract
The transition from oviparity to viviparity has occurred independently over 150 times across vertebrates, presenting one of the most compelling cases of phenotypic convergence. However, whether the repeated, independent evolution of viviparity is driven by redeployment of similar genetic mechanisms and whether these leave a common signature in genomic divergence remains largely unknown. Although recent investigations into the evolution of viviparity have demonstrated striking similarity among the genes and molecular pathways involved across disparate vertebrate groups, quantitative tests for genome-wide convergent have provided ambivalent answers. Here, we investigate the potential role of molecular convergence during independent transitions to viviparity across an order of ray-finned freshwater fish (Cyprinodontiformes). We assembled de novo genomes and utilized publicly available genomes of viviparous and oviparous species to test for molecular convergence across both coding and noncoding regions. We found no evidence for an excess of molecular convergence in amino acid substitutions and in rates of sequence divergence, implying independent genetic changes are associated with these transitions. However, both statistical power and biological confounds could constrain our ability to detect significant correlated evolution. We therefore identified candidate genes with potential signatures of molecular convergence in viviparous Cyprinodontiformes lineages. Motif enrichment and gene ontology analyses suggest transcriptional changes associated with early morphogenesis, brain development, and immunity occurred alongside the evolution of viviparity. Overall, however, our findings indicate that independent transitions to viviparity in these fish are not strongly associated with an excess of molecular convergence, but a few genes show convincing evidence of convergent evolution.
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Affiliation(s)
- Leeban H Yusuf
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, UK
| | - Yolitzi Saldívar Lemus
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, UK
- Department of Biology, Texas State University, San Marcos, TX, USA
| | - Peter Thorpe
- The Data Analysis Group, School of Life Sciences, University of Dundee, Dundee, UK
- School of Medicine, University of North Haugh, St Andrews KY16 9TF, UK
| | - Constantino Macías Garcia
- Instituto de Ecologia, Universidad Nacional Autónoma de México, Ciudad Universitaria, Mexico City CdMx, Mexico
| | - Michael G Ritchie
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, UK
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37
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Barteri F, Valenzuela A, Farré X, de Juan D, Muntané G, Esteve-Altava B, Navarro A. CAAStools: a toolbox to identify and test Convergent Amino Acid Substitutions. Bioinformatics 2023; 39:btad623. [PMID: 37846039 PMCID: PMC10598582 DOI: 10.1093/bioinformatics/btad623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 08/04/2023] [Accepted: 10/13/2023] [Indexed: 10/18/2023] Open
Abstract
MOTIVATION Coincidence of Convergent Amino Acid Substitutions (CAAS) with phenotypic convergences allow pinpointing genes and even individual mutations that are likely to be associated with trait variation within their phylogenetic context. Such findings can provide useful insights into the genetic architecture of complex phenotypes. RESULTS Here we introduce CAAStools, a set of bioinformatics tools to identify and validate CAAS in orthologous protein alignments for predefined groups of species representing the phenotypic values targeted by the user. AVAILABILITY AND IMPLEMENTATION CAAStools source code is available at http://github.com/linudz/caastools, along with documentation and examples.
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Affiliation(s)
- Fabio Barteri
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. C. Doctor Aiguader 88, Barcelona 08003, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, C/ Wellington 30, Barcelona 08006, Spain
| | - Alejandro Valenzuela
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. C. Doctor Aiguader 88, Barcelona 08003, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, C/ Wellington 30, Barcelona 08006, Spain
| | - Xavier Farré
- Genomes for Life-GCAT Lab, GermanTrias i Pujol Research Institute (IGTP), Camí de les Escoles, s/n, Badalona 08916, Spain
| | - David de Juan
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. C. Doctor Aiguader 88, Barcelona 08003, Spain
| | - Gerard Muntané
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. C. Doctor Aiguader 88, Barcelona 08003, Spain
- Institut d’Investigació Sanitària Pere Virgili (IISPV), Hospital Universitari Institut Pere Mata, Universitat Rovira i Virgili. Avda. Josep Laporte, 2 – Planta 0 – E2 color taronja, Reus 43204, Spain
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Av. Monforte de Lemos, 3-5. Pabellón 11. Planta 0. Madrid 28029, Spain
| | - Borja Esteve-Altava
- European Molecular Biology Laboratory, Meyerhofstraße 1, Heidelberg 69117, Germany
| | - Arcadi Navarro
- IBE, Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra. C. Doctor Aiguader 88, Barcelona 08003, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, C/ Wellington 30, Barcelona 08006, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) and Universitat Pompeu Fabra, Pg. Lluís Companys 23, Barcelona 08010, Spain
- Center for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, C. Doctor Aiguader N88, Barcelona 08003, Spain
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38
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Gonçalves C, Harrison MC, Steenwyk JL, Opulente DA, LaBella AL, Wolters JF, Zhou X, Shen XX, Groenewald M, Hittinger CT, Rokas A. Diverse signatures of convergent evolution in cacti-associated yeasts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.14.557833. [PMID: 37745407 PMCID: PMC10515907 DOI: 10.1101/2023.09.14.557833] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question. Here, we leverage a comprehensive dataset of genomic and phenotypic data from 1,049 yeast species in the subphylum Saccharomycotina (Kingdom Fungi, Phylum Ascomycota) to explore signatures of convergent evolution in cactophilic yeasts, ecological specialists associated with cacti. We inferred that the ecological association of yeasts with cacti arose independently ~17 times. Using machine-learning, we further found that cactophily can be predicted with 76% accuracy from functional genomic and phenotypic data. The most informative feature for predicting cactophily was thermotolerance, which is likely associated with duplication and altered evolutionary rates of genes impacting the cell envelope in several cactophilic lineages. We also identified horizontal gene transfer and duplication events of plant cell wall-degrading enzymes in distantly related cactophilic clades, suggesting that putatively adaptive traits evolved through disparate molecular mechanisms. Remarkably, multiple cactophilic lineages and their close relatives are emerging human opportunistic pathogens, suggesting that the cactophilic lifestyle-and perhaps more generally lifestyles favoring thermotolerance-may preadapt yeasts to cause human disease. This work underscores the potential of a multifaceted approach involving high throughput genomic and phenotypic data to shed light onto ecological adaptation and highlights how convergent evolution to wild environments could facilitate the transition to human pathogenicity.
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Affiliation(s)
- Carla Gonçalves
- Vanderbilt University, Department of Biological Sciences, VU Station B #35-1634, Nashville, TN 37235, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
- Present address: Associate Laboratory i4HB—Institute for Health and Bioeconomy and UCIBIO—Applied Molecular Biosciences Unit, Department of Life Sciences, NOVA School of Science and Technology, Universidade NOVA de Lisboa, Caparica, Portugal
- Present address: UCIBIO-i4HB, Departamento de Ciências da Vida, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
| | - Marie-Claire Harrison
- Vanderbilt University, Department of Biological Sciences, VU Station B #35-1634, Nashville, TN 37235, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
| | - Jacob L. Steenwyk
- Vanderbilt University, Department of Biological Sciences, VU Station B #35-1634, Nashville, TN 37235, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
- Howards Hughes Medical Institute and the Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Dana A. Opulente
- Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, Wisconsin Energy Institu te, University of Wisconsin-Madison, Madison, WI 53726, USA
- Biology Department, Villanova University, Villanova, PA 19085, USA
| | - Abigail L. LaBella
- Vanderbilt University, Department of Biological Sciences, VU Station B #35-1634, Nashville, TN 37235, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte NC 28223
| | - John F. Wolters
- Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, Wisconsin Energy Institu te, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Xiaofan Zhou
- Vanderbilt University, Department of Biological Sciences, VU Station B #35-1634, Nashville, TN 37235, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
- Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Center, South China Agricultural University, Guangzhou 510642, China
| | - Xing-Xing Shen
- Vanderbilt University, Department of Biological Sciences, VU Station B #35-1634, Nashville, TN 37235, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
- College of Agriculture and Biotechnology and Centre for Evolutionary & Organismal Biology, Zhejiang University, Hangzhou 310058, China
| | | | - Chris Todd Hittinger
- Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, Wisconsin Energy Institu te, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Antonis Rokas
- Vanderbilt University, Department of Biological Sciences, VU Station B #35-1634, Nashville, TN 37235, United States of America
- Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA
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Yan H, Hu Z, Thomas GWC, Edwards SV, Sackton TB, Liu JS. PhyloAcc-GT: A Bayesian Method for Inferring Patterns of Substitution Rate Shifts on Targeted Lineages Accounting for Gene Tree Discordance. Mol Biol Evol 2023; 40:msad195. [PMID: 37665177 PMCID: PMC10540510 DOI: 10.1093/molbev/msad195] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 08/15/2023] [Accepted: 09/01/2023] [Indexed: 09/05/2023] Open
Abstract
An important goal of evolutionary genomics is to identify genomic regions whose substitution rates differ among lineages. For example, genomic regions experiencing accelerated molecular evolution in some lineages may provide insight into links between genotype and phenotype. Several comparative genomics methods have been developed to identify genomic accelerations between species, including a Bayesian method called PhyloAcc, which models shifts in substitution rate in multiple target lineages on a phylogeny. However, few methods consider the possibility of discordance between the trees of individual loci and the species tree due to incomplete lineage sorting, which might cause false positives. Here, we present PhyloAcc-GT, which extends PhyloAcc by modeling gene tree heterogeneity. Given a species tree, we adopt the multispecies coalescent model as the prior distribution of gene trees, use Markov chain Monte Carlo (MCMC) for inference, and design novel MCMC moves to sample gene trees efficiently. Through extensive simulations, we show that PhyloAcc-GT outperforms PhyloAcc and other methods in identifying target lineage-specific accelerations and detecting complex patterns of rate shifts, and is robust to specification of population size parameters. PhyloAcc-GT is usually more conservative than PhyloAcc in calling convergent rate shifts because it identifies more accelerations on ancestral than on terminal branches. We apply PhyloAcc-GT to two examples of convergent evolution: flightlessness in ratites and marine mammal adaptations, and show that PhyloAcc-GT is a robust tool to identify shifts in substitution rate associated with specific target lineages while accounting for incomplete lineage sorting.
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Affiliation(s)
- Han Yan
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Zhirui Hu
- Department of Statistics, Harvard University, Cambridge, MA, USA
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
| | | | - Scott V Edwards
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | | | - Jun S Liu
- Department of Statistics, Harvard University, Cambridge, MA, USA
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40
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Thomas GWC, Hughes JJ, Kumon T, Berv JS, Nordgren CE, Lampson M, Levine M, Searle JB, Good JM. The genomic landscape, causes, and consequences of extensive phylogenomic discordance in Old World mice and rats. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.28.555178. [PMID: 37693498 PMCID: PMC10491188 DOI: 10.1101/2023.08.28.555178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
A species tree is a central concept in evolutionary biology whereby a single branching phylogeny reflects relationships among species. However, the phylogenies of different genomic regions often differ from the species tree. Although tree discordance is often widespread in phylogenomic studies, we still lack a clear understanding of how variation in phylogenetic patterns is shaped by genome biology or the extent to which discordance may compromise comparative studies. We characterized patterns of phylogenomic discordance across the murine rodents (Old World mice and rats) - a large and ecologically diverse group that gave rise to the mouse and rat model systems. Combining new linked-read genome assemblies for seven murine species with eleven published rodent genomes, we first used ultra-conserved elements (UCEs) to infer a robust species tree. We then used whole genomes to examine finer-scale patterns of discordance and found that phylogenies built from proximate chromosomal regions had similar phylogenies. However, there was no relationship between tree similarity and local recombination rates in house mice, suggesting that genetic linkage influences phylogenetic patterns over deeper timescales. This signal may be independent of contemporary recombination landscapes. We also detected a strong influence of linked selection whereby purifying selection at UCEs led to less discordance, while genes experiencing positive selection showed more discordant and variable phylogenetic signals. Finally, we show that assuming a single species tree can result in high error rates when testing for positive selection under different models. Collectively, our results highlight the complex relationship between phylogenetic inference and genome biology and underscore how failure to account for this complexity can mislead comparative genomic studies.
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Affiliation(s)
- Gregg W. C. Thomas
- Division of Biological Sciences, University of Montana, Missoula, MT, 59801
- Informatics Group, Harvard University, Cambridge, MA, 02138
| | - Jonathan J. Hughes
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, 14853
- Department of Evolution, Ecology, and Organismal Biology, University of California Riverside, Riverside, CA, 92521
| | - Tomohiro Kumon
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104
| | - Jacob S. Berv
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, 14853
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, 48109
| | - C. Erik Nordgren
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104
| | - Michael Lampson
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104
| | - Mia Levine
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104
| | - Jeremy B. Searle
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, 14853
| | - Jeffrey M. Good
- Division of Biological Sciences, University of Montana, Missoula, MT, 59801
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41
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Richardson R, Feigin CY, Bano-Otalora B, Johnson MR, Allen AE, Park J, McDowell RJ, Mereby SA, Lin IH, Lucas RJ, Mallarino R. The genomic basis of temporal niche evolution in a diurnal rodent. Curr Biol 2023; 33:3289-3298.e6. [PMID: 37480852 PMCID: PMC10529858 DOI: 10.1016/j.cub.2023.06.068] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 05/05/2023] [Accepted: 06/26/2023] [Indexed: 07/24/2023]
Abstract
Patterns of diel activity-how animals allocate their activity throughout the 24-h daily cycle-play key roles in shaping the internal physiology of an animal and its relationship with the external environment.1,2,3,4,5 Although shifts in diel activity patterns have occurred numerous times over the course of vertebrate evolution,6 the genomic correlates of such transitions remain unknown. Here, we use the African striped mouse (Rhabdomys pumilio), a species that transitioned from the ancestrally nocturnal diel niche of its close relatives to a diurnal one,7,8,9,10,11 to define patterns of naturally occurring molecular variation in diel niche traits. First, to facilitate genomic analyses, we generate a chromosome-level genome assembly of the striped mouse. Next, using transcriptomics, we show that the switch to daytime activity in this species is associated with a realignment of daily rhythms in peripheral tissues with respect to the light:dark cycle and the central circadian clock. To uncover selection pressures associated with this temporal niche shift, we perform comparative genomic analyses with closely related rodent species and find evidence of relaxation of purifying selection on striped mouse genes in the rod phototransduction pathway. In agreement with this, electroretinogram measurements demonstrate that striped mice have functional differences in dim-light visual responses compared with nocturnal rodents. Taken together, our results show that striped mice have undergone a drastic change in circadian organization and provide evidence that the visual system has been a major target of selection as this species transitioned to a novel temporal niche.
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Affiliation(s)
- Rose Richardson
- Centre for Biological Timing, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Division of Neuroscience, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Charles Y Feigin
- Department of Molecular Biology, Princeton University, Princeton, NJ 08540, USA; School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Beatriz Bano-Otalora
- Centre for Biological Timing, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Division of Neuroscience, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Division of Diabetes, Endocrinology, & Gastroenterology, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Matthew R Johnson
- Department of Molecular Biology, Princeton University, Princeton, NJ 08540, USA
| | - Annette E Allen
- Centre for Biological Timing, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Division of Neuroscience, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Jongbeom Park
- Department of Molecular Biology, Princeton University, Princeton, NJ 08540, USA
| | - Richard J McDowell
- Centre for Biological Timing, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Division of Neuroscience, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Sarah A Mereby
- Department of Molecular Biology, Princeton University, Princeton, NJ 08540, USA
| | - I-Hsuan Lin
- Bioinformatics Core Facility, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PL, UK
| | - Robert J Lucas
- Centre for Biological Timing, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK; Division of Neuroscience, Faculty of Biology Medicine and Health, University of Manchester, Manchester M13 9PT, UK.
| | - Ricardo Mallarino
- Department of Molecular Biology, Princeton University, Princeton, NJ 08540, USA.
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42
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Pereira AG, Kohlsdorf T. Repeated evolution of similar phenotypes: Integrating comparative methods with developmental pathways. Genet Mol Biol 2023; 46:e20220384. [PMID: 37486083 PMCID: PMC10364090 DOI: 10.1590/1678-4685-gmb-2022-0384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/24/2023] [Indexed: 07/25/2023] Open
Abstract
Repeated phenotypes, often referred to as 'homoplasies' in cladistic analyses, may evolve through changes in developmental processes. Genetic bases of recurrent evolution gained attention and have been studied in the past years using approaches that combine modern analytical phylogenetic tools with the stunning assemblage of new information on developmental mechanisms. In this review, we evaluated the topic under an integrated perspective, revisiting the classical definitions of convergence and parallelism and detailing comparative methods used to evaluate evolution of repeated phenotypes, which include phylogenetic inference, estimates of evolutionary rates and reconstruction of ancestral states. We provide examples to illustrate how a given methodological approach can be used to identify evolutionary patterns and evaluate developmental mechanisms associated with the intermittent expression of a given trait along the phylogeny. Finally, we address why repeated trait loss challenges strict definitions of convergence and parallelism, discussing how changes in developmental pathways might explain the high frequency of repeated trait loss in specific lineages.
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Affiliation(s)
- Anieli Guirro Pereira
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Departamento de Biologia, Ribeirão Preto, SP, Brazil
| | - Tiana Kohlsdorf
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Departamento de Biologia, Ribeirão Preto, SP, Brazil
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43
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Tseng ZJ, Garcia-Lara S, Flynn JJ, Holmes E, Rowe TB, Dickson BV. A switch in jaw form-function coupling during the evolution of mammals. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220091. [PMID: 37183899 PMCID: PMC10184249 DOI: 10.1098/rstb.2022.0091] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023] Open
Abstract
The evolutionary shift from a single-element ear, multi-element jaw to a multi-element ear, single-element jaw during the transition to crown mammals marks one of the most dramatic structural transformations in vertebrates. Research on this transformation has focused on mammalian middle-ear evolution, but a mandible comprising only the dentary is equally emblematic of this evolutionary radiation. Here, we show that the remarkably diverse jaw shapes of crown mammals are coupled with surprisingly stereotyped jaw stiffness. This strength-based morphofunctional regime has a genetic basis and allowed mammalian jaws to effectively resist deformation as they radiated into highly disparate forms with markedly distinct diets. The main functional consequences for the mandible of decoupling hearing and mastication were a trade-off between higher jaw stiffness versus decreased mechanical efficiency and speed compared with non-mammals. This fundamental and consequential shift in jaw form-function underpins the ecological and taxonomic diversification of crown mammals. This article is part of the theme issue 'The mammalian skull: development, structure and function'.
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Affiliation(s)
- Z Jack Tseng
- Department of Integrative Biology, University of California, Berkeley, CA 94720, USA
- Museum of Paleontology, University of California, Berkeley, CA 94720, USA
- Division of Paleontology, American Museum of Natural History, New York, NY 10024, USA
| | - Sergio Garcia-Lara
- Department of Integrative Biology, University of California, Berkeley, CA 94720, USA
- Museum of Paleontology, University of California, Berkeley, CA 94720, USA
| | - John J Flynn
- Division of Paleontology, American Museum of Natural History, New York, NY 10024, USA
- Richard Gilder Graduate School, American Museum of Natural History, New York, NY 10024, USA
| | - Emily Holmes
- Department of Integrative Biology, University of California, Berkeley, CA 94720, USA
| | - Timothy B Rowe
- Jackson School of Geological Sciences, University of Texas, Austin, TX 78712, USA
| | - Blake V Dickson
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
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44
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Kaplow IM, Lawler AJ, Schäffer DE, Srinivasan C, Sestili HH, Wirthlin ME, Phan BN, Prasad K, Brown AR, Zhang X, Foley K, Genereux DP, Karlsson EK, Lindblad-Toh K, Meyer WK, Pfenning AR. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning. Science 2023; 380:eabm7993. [PMID: 37104615 PMCID: PMC10322212 DOI: 10.1126/science.abm7993] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 02/23/2023] [Indexed: 04/29/2023]
Abstract
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.
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Affiliation(s)
- Irene M. Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alyssa J. Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Daniel E. Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Chaitanya Srinivasan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Heather H. Sestili
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Morgan E. Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - BaDoi N. Phan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kavya Prasad
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ashley R. Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Kathleen Foley
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Diane P. Genereux
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | - Elinor K. Karlsson
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Kerstin Lindblad-Toh
- Broad Institute, Cambridge, MA, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Wynn K. Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
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45
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Christmas MJ, Kaplow IM, Genereux DP, Dong MX, Hughes GM, Li X, Sullivan PF, Hindle AG, Andrews G, Armstrong JC, Bianchi M, Breit AM, Diekhans M, Fanter C, Foley NM, Goodman DB, Goodman L, Keough KC, Kirilenko B, Kowalczyk A, Lawless C, Lind AL, Meadows JRS, Moreira LR, Redlich RW, Ryan L, Swofford R, Valenzuela A, Wagner F, Wallerman O, Brown AR, Damas J, Fan K, Gatesy J, Grimshaw J, Johnson J, Kozyrev SV, Lawler AJ, Marinescu VD, Morrill KM, Osmanski A, Paulat NS, Phan BN, Reilly SK, Schäffer DE, Steiner C, Supple MA, Wilder AP, Wirthlin ME, Xue JR, Birren BW, Gazal S, Hubley RM, Koepfli KP, Marques-Bonet T, Meyer WK, Nweeia M, Sabeti PC, Shapiro B, Smit AFA, Springer MS, Teeling EC, Weng Z, Hiller M, Levesque DL, Lewin HA, Murphy WJ, Navarro A, Paten B, Pollard KS, Ray DA, Ruf I, Ryder OA, Pfenning AR, Lindblad-Toh K, Karlsson EK. Evolutionary constraint and innovation across hundreds of placental mammals. Science 2023; 380:eabn3943. [PMID: 37104599 PMCID: PMC10250106 DOI: 10.1126/science.abn3943] [Citation(s) in RCA: 101] [Impact Index Per Article: 50.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 12/16/2022] [Indexed: 04/29/2023]
Abstract
Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.
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Affiliation(s)
- Matthew J. Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Irene M. Kaplow
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | | | - Michael X. Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Xue Li
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Allyson G. Hindle
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Joel C. Armstrong
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ana M. Breit
- School of Biology and Ecology, University of Maine, Orono, ME 04469, USA
| | - Mark Diekhans
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Cornelia Fanter
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Nicole M. Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Daniel B. Goodman
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | | | - Kathleen C. Keough
- Fauna Bio, Inc., Emeryville, CA 94608, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Bogdan Kirilenko
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | - Amanda Kowalczyk
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Colleen Lawless
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Abigail L. Lind
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Lucas R. Moreira
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Ruby W. Redlich
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Louise Ryan
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Ross Swofford
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Alejandro Valenzuela
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Franziska Wagner
- Museum of Zoology, Senckenberg Natural History Collections Dresden, 01109 Dresden, Germany
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ashley R. Brown
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Joana Damas
- The Genome Center, University of California Davis, Davis, CA 95616, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - John Gatesy
- Division of Vertebrate Zoology, American Museum of Natural History, New York, NY 10024, USA
| | - Jenna Grimshaw
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Jeremy Johnson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Sergey V. Kozyrev
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Alyssa J. Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Voichita D. Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Kathleen M. Morrill
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Austin Osmanski
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Nicole S. Paulat
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - BaDoi N. Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Daniel E. Schäffer
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Cynthia Steiner
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Megan A. Supple
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Aryn P. Wilder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Morgan E. Wirthlin
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - James R. Xue
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | | | - Bruce W. Birren
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Steven Gazal
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | | | - Klaus-Peter Koepfli
- Center for Species Survival, Smithsonian’s National Zoo and Conservation Biology Institute, Washington, DC 20008, USA
- Computer Technologies Laboratory, ITMO University, St. Petersburg 197101, Russia
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630, USA
| | - Tomas Marques-Bonet
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08036 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Wynn K. Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Martin Nweeia
- Department of Comprehensive Care, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Vertebrate Zoology, Canadian Museum of Nature, Ottawa, Ontario K2P 2R1, Canada
- Department of Vertebrate Zoology, Smithsonian Institution, Washington, DC 20002, USA
- Narwhal Genome Initiative, Department of Restorative Dentistry and Biomaterials Sciences, Harvard School of Dental Medicine, Boston, MA 02115, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | | | - Mark S. Springer
- Department of Evolution, Ecology and Organismal Biology, University of California Riverside, Riverside, CA 92521, USA
| | - Emma C. Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Michael Hiller
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | | | - Harris A. Lewin
- The Genome Center, University of California Davis, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California Davis, Davis, CA 95616, USA
- John Muir Institute for the Environment, University of California Davis, Davis, CA 95616, USA
| | - William J. Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Arcadi Navarro
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, 08005 Barcelona, Spain
- CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Benedict Paten
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Katherine S. Pollard
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - David A. Ray
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Irina Ruf
- Division of Messel Research and Mammalogy, Senckenberg Research Institute and Natural History Museum Frankfurt, 60325 Frankfurt am Main, Germany
| | - Oliver A. Ryder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
- Department of Evolution, Behavior and Ecology, School of Biological Sciences, University of California San Diego, La Jolla, CA 92039, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Elinor K. Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
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Zhang X, Kuang T, Dong W, Qian Z, Zhang H, Landis JB, Feng T, Li L, Sun Y, Huang J, Deng T, Wang H, Sun H. Genomic convergence underlying high-altitude adaptation in alpine plants. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2023. [PMID: 36960823 DOI: 10.1111/jipb.13485] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 03/21/2023] [Indexed: 06/18/2023]
Abstract
Evolutionary convergence is one of the most striking examples of adaptation driven by natural selection. However, genomic evidence for convergent adaptation to extreme environments remains scarce. Here, we assembled reference genomes of two alpine plants, Saussurea obvallata (Asteraceae) and Rheum alexandrae (Polygonaceae), with 37,938 and 61,463 annotated protein-coding genes. By integrating an additional five alpine genomes, we elucidated genomic convergence underlying high-altitude adaptation in alpine plants. Our results detected convergent contractions of disease-resistance genes in alpine genomes, which might be an energy-saving strategy for surviving in hostile environments with only a few pathogens present. We identified signatures of positive selection on a set of genes involved in reproduction and respiration (e.g., MMD1, NBS1, and HPR), and revealed signatures of molecular convergence on genes involved in self-incompatibility, cell wall modification, DNA repair and stress resistance, which may underlie adaptation to extreme cold, high ultraviolet radiation and hypoxia environments. Incorporating transcriptomic data, we further demonstrated that genes associated with cuticular wax and flavonoid biosynthetic pathways exhibit higher expression levels in leafy bracts, shedding light on the genetic mechanisms of the adaptive "greenhouse" morphology. Our integrative data provide novel insights into convergent evolution at a high-taxonomic level, aiding in a deep understanding of genetic adaptation to complex environments.
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Affiliation(s)
- Xu Zhang
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, 430074, China
- Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan, 430074, China
| | - Tianhui Kuang
- Yunnan International Joint Laboratory for Biodiversity of Central Asia, Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, The Chinese Academy of Sciences, Kunming, 650201, China
| | - Wenlin Dong
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, 430074, China
- Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan, 430074, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhihao Qian
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, 430074, China
- Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan, 430074, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Huajie Zhang
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, 430074, China
- Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan, 430074, China
| | - Jacob B Landis
- School of Integrative Plant Science, Section of Plant Biology and the L. H. Bailey Hortorium, Cornell University, Ithaca, New York, 14850, USA
- BTI Computational Biology Center, Boyce Thompson Institute, Ithaca, New York, 14853, USA
| | - Tao Feng
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, 430074, China
- Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan, 430074, China
| | - Lijuan Li
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, 430074, China
- Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan, 430074, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yanxia Sun
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, 430074, China
- Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan, 430074, China
| | - Jinling Huang
- Yunnan International Joint Laboratory for Biodiversity of Central Asia, Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, The Chinese Academy of Sciences, Kunming, 650201, China
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, 475004, China
- Department of Biology, East Carolina University, Greenville, North Carolina, 27858, USA
| | - Tao Deng
- Yunnan International Joint Laboratory for Biodiversity of Central Asia, Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, The Chinese Academy of Sciences, Kunming, 650201, China
| | - Hengchang Wang
- CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, 430074, China
- Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan, 430074, China
| | - Hang Sun
- Yunnan International Joint Laboratory for Biodiversity of Central Asia, Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, The Chinese Academy of Sciences, Kunming, 650201, China
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Feigin C, Li S, Moreno J, Mallarino R. The GRN concept as a guide for evolutionary developmental biology. JOURNAL OF EXPERIMENTAL ZOOLOGY. PART B, MOLECULAR AND DEVELOPMENTAL EVOLUTION 2023; 340:92-104. [PMID: 35344632 PMCID: PMC9515236 DOI: 10.1002/jez.b.23132] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 03/08/2022] [Accepted: 03/11/2022] [Indexed: 12/13/2022]
Abstract
Organismal phenotypes result largely from inherited developmental programs, usually executed during embryonic and juvenile life stages. These programs are not blank slates onto which natural selection can draw arbitrary forms. Rather, the mechanisms of development play an integral role in shaping phenotypic diversity and help determine the evolutionary trajectories of species. Modern evolutionary biology must, therefore, account for these mechanisms in both theory and in practice. The gene regulatory network (GRN) concept represents a potent tool for achieving this goal whose utility has grown in tandem with advances in "omic" technologies and experimental techniques. However, while the GRN concept is widely utilized, it is often less clear what practical implications it has for conducting research in evolutionary developmental biology. In this Perspective, we attempt to provide clarity by discussing how experiments and projects can be designed in light of the GRN concept. We first map familiar biological notions onto the more abstract components of GRN models. We then review how diverse functional genomic approaches can be directed toward the goal of constructing such models and discuss current methods for functionally testing evolutionary hypotheses that arise from them. Finally, we show how the major steps of GRN model construction and experimental validation suggest generalizable workflows that can serve as a scaffold for project design. Taken together, the practical implications that we draw from the GRN concept provide a set of guideposts for studies aiming at unraveling the molecular basis of phenotypic diversity.
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Affiliation(s)
- Charles Feigin
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA,School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Sha Li
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
| | - Jorge Moreno
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
| | - Ricardo Mallarino
- Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
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48
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Genome Evolution and the Future of Phylogenomics of Non-Avian Reptiles. Animals (Basel) 2023; 13:ani13030471. [PMID: 36766360 PMCID: PMC9913427 DOI: 10.3390/ani13030471] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 01/13/2023] [Accepted: 01/15/2023] [Indexed: 02/01/2023] Open
Abstract
Non-avian reptiles comprise a large proportion of amniote vertebrate diversity, with squamate reptiles-lizards and snakes-recently overtaking birds as the most species-rich tetrapod radiation. Despite displaying an extraordinary diversity of phenotypic and genomic traits, genomic resources in non-avian reptiles have accumulated more slowly than they have in mammals and birds, the remaining amniotes. Here we review the remarkable natural history of non-avian reptiles, with a focus on the physical traits, genomic characteristics, and sequence compositional patterns that comprise key axes of variation across amniotes. We argue that the high evolutionary diversity of non-avian reptiles can fuel a new generation of whole-genome phylogenomic analyses. A survey of phylogenetic investigations in non-avian reptiles shows that sequence capture-based approaches are the most commonly used, with studies of markers known as ultraconserved elements (UCEs) especially well represented. However, many other types of markers exist and are increasingly being mined from genome assemblies in silico, including some with greater information potential than UCEs for certain investigations. We discuss the importance of high-quality genomic resources and methods for bioinformatically extracting a range of marker sets from genome assemblies. Finally, we encourage herpetologists working in genomics, genetics, evolutionary biology, and other fields to work collectively towards building genomic resources for non-avian reptiles, especially squamates, that rival those already in place for mammals and birds. Overall, the development of this cross-amniote phylogenomic tree of life will contribute to illuminate interesting dimensions of biodiversity across non-avian reptiles and broader amniotes.
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49
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Treaster S, Deelen J, Daane JM, Murabito J, Karasik D, Harris MP. Convergent genomics of longevity in rockfishes highlights the genetics of human life span variation. SCIENCE ADVANCES 2023; 9:eadd2743. [PMID: 36630509 PMCID: PMC9833670 DOI: 10.1126/sciadv.add2743] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 12/09/2022] [Indexed: 05/16/2023]
Abstract
Longevity is a defining, heritable trait that varies dramatically between species. To resolve the genetic regulation of this trait, we have mined genomic variation in rockfishes, which range in longevity from 11 to over 205 years. Multiple shifts in rockfish longevity have occurred independently and in a short evolutionary time frame, thus empowering convergence analyses. Our analyses reveal a common network of genes under convergent evolution, encompassing established aging regulators such as insulin signaling, yet also identify flavonoid (aryl-hydrocarbon) metabolism as a pathway modulating longevity. The selective pressures on these pathways indicate the ancestral state of rockfishes was long lived and that the changes in short-lived lineages are adaptive. These pathways were also used to explore genome-wide association studies of human longevity, identifying the aryl-hydrocarbon metabolism pathway to be significantly associated with human survival to the 99th percentile. This evolutionary intersection defines and cross-validates a previously unappreciated genetic architecture that associates with the evolution of longevity across vertebrates.
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Affiliation(s)
- Stephen Treaster
- Department of Orthopaedic Surgery, Boston Children’s Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Joris Deelen
- Max Planck Institute for Biology of Ageing, Joseph-Stelzmann-Str. 9b, D-50931 Köln, Germany
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Jacob M. Daane
- Department of Biology and Biochemistry, University of Houston, Houston TX, USA
| | - Joanne Murabito
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - David Karasik
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
- Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA
| | - Matthew P. Harris
- Department of Orthopaedic Surgery, Boston Children’s Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
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50
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Tong C, Avilés L, Rayor LS, Mikheyev AS, Linksvayer TA. Genomic signatures of recent convergent transitions to social life in spiders. Nat Commun 2022; 13:6967. [PMID: 36414623 PMCID: PMC9681848 DOI: 10.1038/s41467-022-34446-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 10/25/2022] [Indexed: 11/24/2022] Open
Abstract
The transition from solitary to social life is a major phenotypic innovation, but its genetic underpinnings are largely unknown. To identify genomic changes associated with this transition, we compare the genomes of 22 spider species representing eight recent and independent origins of sociality. Hundreds of genes tend to experience shifts in selection during the repeated transition to social life. These genes are associated with several key functions, such as neurogenesis, behavior, and metabolism, and include genes that previously have been implicated in animal social behavior and human behavioral disorders. In addition, social species have elevated genome-wide rates of molecular evolution associated with relaxed selection caused by reduced effective population size. Altogether, our study provides unprecedented insights into the genomic signatures of social evolution and the specific genetic changes that repeatedly underpin the evolution of sociality. Our study also highlights the heretofore unappreciated potential of transcriptomics using ethanol-preserved specimens for comparative genomics and phylotranscriptomics.
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Affiliation(s)
- Chao Tong
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Biological Sciences, Texas Tech University, Lubbock, TX, 79409, USA.
| | - Leticia Avilés
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, V6T 1Z4, Canada
| | - Linda S Rayor
- Department of Entomology, Cornell University, Ithaca, NY, 14853, USA
| | - Alexander S Mikheyev
- Evolutionary Genomics Group, Research School of Biology, Australian National University, Canberra, 0200, Australia
| | - Timothy A Linksvayer
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Biological Sciences, Texas Tech University, Lubbock, TX, 79409, USA.
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