1
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Bourret A, Leung C, Puncher GN, Le Corre N, Deslauriers D, Skanes K, Bourdages H, Cassista-Da Ros M, Walkusz W, Jeffery NW, Stanley RRE, Parent GJ. Diving into broad-scale and high-resolution population genomics to decipher drivers of structure and climatic vulnerability in a marine invertebrate. Mol Ecol 2024; 33:e17448. [PMID: 38946210 DOI: 10.1111/mec.17448] [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: 01/31/2024] [Revised: 06/11/2024] [Accepted: 06/19/2024] [Indexed: 07/02/2024]
Abstract
Species with widespread distributions play a crucial role in our understanding of climate change impacts on population structure. In marine species, population structure is often governed by both high connectivity potential and selection across strong environmental gradients. Despite the complexity of factors influencing marine populations, studying species with broad distribution can provide valuable insights into the relative importance of these factors and the consequences of climate-induced alterations across environmental gradients. We used the northern shrimp Pandalus borealis and its wide latitudinal distribution to identify current drivers of population structure and predict the species' vulnerability to climate change. A total of 1514 individuals sampled across 24° latitude were genotyped at high geographic (54 stations) and genetic (14,331 SNPs) resolutions to assess genetic variation and environmental correlations. Four populations were identified in addition to finer substructure associated with local adaptation. Geographic patterns of neutral population structure reflected predominant oceanographic currents, while a significant proportion of the genetic variation was associated with gradients in salinity and temperature. Adaptive landscapes generated using climate projections suggest a larger genomic offset in the southern extent of the P. borealis range, where shrimp had the largest adaptive standing genetic variation. Our genomic results combined with recent observations point to further deterioration in southern regions and an impending vulnerable status in the regions at higher latitudes for P. borealis. They also provide rare insights into the drivers of population structure and climatic vulnerability of a widespread meroplanktonic species, which is crucial to understanding future challenges associated with invertebrates essential to ecosystem functioning.
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Affiliation(s)
- Audrey Bourret
- Maurice Lamontagne Institute, Fisheries and Oceans Canada, Mont-Joli, Quebec, Canada
| | - Christelle Leung
- Maurice Lamontagne Institute, Fisheries and Oceans Canada, Mont-Joli, Quebec, Canada
| | - Gregory N Puncher
- Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia, Canada
| | - Nicolas Le Corre
- Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John's, Newfoundland and Labrador, Canada
| | - David Deslauriers
- Institut des Sciences de la Mer de Rimouski, Université du Québec à Rimouski, Rimouski, Quebec, Canada
| | - Katherine Skanes
- Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John's, Newfoundland and Labrador, Canada
| | - Hugo Bourdages
- Maurice Lamontagne Institute, Fisheries and Oceans Canada, Mont-Joli, Quebec, Canada
| | - Manon Cassista-Da Ros
- Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia, Canada
| | - Wojciech Walkusz
- Freshwater Institute, Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - Nicholas W Jeffery
- Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia, Canada
| | - Ryan R E Stanley
- Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia, Canada
| | - Geneviève J Parent
- Maurice Lamontagne Institute, Fisheries and Oceans Canada, Mont-Joli, Quebec, Canada
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2
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Aitken SN, Jordan R, Tumas HR. Conserving Evolutionary Potential: Combining Landscape Genomics with Established Methods to Inform Plant Conservation. ANNUAL REVIEW OF PLANT BIOLOGY 2024; 75:707-736. [PMID: 38594931 DOI: 10.1146/annurev-arplant-070523-044239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
Biodiversity conservation requires conserving evolutionary potential-the capacity for wild populations to adapt. Understanding genetic diversity and evolutionary dynamics is critical for informing conservation decisions that enhance adaptability and persistence under environmental change. We review how emerging landscape genomic methods provide plant conservation programs with insights into evolutionary dynamics, including local adaptation and its environmental drivers. Landscape genomic approaches that explore relationships between genomic variation and environments complement rather than replace established population genomic and common garden approaches for assessing adaptive phenotypic variation, population structure, gene flow, and demography. Collectively, these approaches inform conservation actions, including genetic rescue, maladaptation prediction, and assisted gene flow. The greatest on-the-ground impacts from such studies will be realized when conservation practitioners are actively engaged in research and monitoring. Understanding the evolutionary dynamics shaping the genetic diversity of wild plant populations will inform plant conservation decisions that enhance the adaptability and persistence of species in an uncertain future.
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Affiliation(s)
- Sally N Aitken
- Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, Canada; ,
| | | | - Hayley R Tumas
- Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, Canada; ,
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3
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Izaguirre-Toriz V, Aguirre-Liguori JA, Latorre-Cárdenas MC, Arima EY, González-Rodríguez A. Local adaptation of Pinus leiophylla under climate and land use change models in the Avocado Belt of Michoacán. Mol Ecol 2024; 33:e17424. [PMID: 38813851 DOI: 10.1111/mec.17424] [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: 02/27/2024] [Revised: 05/01/2024] [Accepted: 05/17/2024] [Indexed: 05/31/2024]
Abstract
Climate change and land use change are two main drivers of global biodiversity decline, decreasing the genetic diversity that populations harbour and altering patterns of local adaptation. Landscape genomics allows measuring the effect of these anthropogenic disturbances on the adaptation of populations. However, both factors have rarely been considered simultaneously. Based on a set of 3660 SNPs from which 130 were identified as outliers by a genome-environment association analysis (LFMM), we modelled the spatial turnover of allele frequencies in 19 localities of Pinus leiophylla across the Avocado Belt in Michoacán state, Mexico. Then, we evaluated the effect of climate change and land use change scenarios, in addition to evaluating assisted gene flow strategies and connectivity metrics across the landscape to identify priority conservation areas for the species. We found that localities in the centre-east of the Avocado Belt would be more vulnerable to climate change, while localities in the western area are more threatened by land conversion to avocado orchards. Assisted gene flow actions could aid in mitigating both threats. Connectivity patterns among forest patches will also be modified by future habitat loss, with central and eastern parts of the Avocado Belt maintaining the highest connectivity. These results suggest that areas with the highest priority for conservation are in the eastern part of the Avocado Belt, including the Monarch Butterfly Biosphere Reserve. This work is useful as a framework that incorporates distinct layers of information to provide a more robust representation of the response of tree populations to anthropogenic disturbances.
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Affiliation(s)
- Vanessa Izaguirre-Toriz
- Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, Morelia, Mexico
- Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México (Posgrado en Ciencias Biológicas, Unidad de Posgrado, Edificio D, 1° Piso, Circuito de Posgrados, Ciudad Universitaria), Coyoacán, Mexico
| | - Jonás A Aguirre-Liguori
- Departamento de Ecología Tropical, Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Mérida, Mexico
| | - María Camila Latorre-Cárdenas
- Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, Morelia, Mexico
| | - Eugenio Y Arima
- Department of Geography and the Environment, University of Texas at Austin, Austin, Texas, USA
| | - Antonio González-Rodríguez
- Laboratorio Nacional de Innovación Ecotecnológica Para la Sustentabilidad (LANIES), Instituto de Investigaciones en Ecosistemas y Sustentabilidad, UNAM Campus Morelia, Morelia, Mexico
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4
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Hämälä T, Moore C, Cowan L, Carlile M, Gopaulchan D, Brandrud MK, Birkeland S, Loose M, Kolář F, Koch MA, Yant L. Impact of whole-genome duplications on structural variant evolution in Cochlearia. Nat Commun 2024; 15:5377. [PMID: 38918389 PMCID: PMC11199601 DOI: 10.1038/s41467-024-49679-y] [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: 10/08/2023] [Accepted: 06/14/2024] [Indexed: 06/27/2024] Open
Abstract
Polyploidy, the result of whole-genome duplication (WGD), is a major driver of eukaryote evolution. Yet WGDs are hugely disruptive mutations, and we still lack a clear understanding of their fitness consequences. Here, we study whether WGDs result in greater diversity of genomic structural variants (SVs) and how they influence evolutionary dynamics in a plant genus, Cochlearia (Brassicaceae). By using long-read sequencing and a graph-based pangenome, we find both negative and positive interactions between WGDs and SVs. Masking of recessive mutations due to WGDs leads to a progressive accumulation of deleterious SVs across four ploidal levels (from diploids to octoploids), likely reducing the adaptive potential of polyploid populations. However, we also discover putative benefits arising from SV accumulation, as more ploidy-specific SVs harbor signals of local adaptation in polyploids than in diploids. Together, our results suggest that SVs play diverse and contrasting roles in the evolutionary trajectories of young polyploids.
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Affiliation(s)
- Tuomas Hämälä
- School of Life Sciences, University of Nottingham, Nottingham, UK.
- Production Systems, Natural Resources Institute Finland, Jokioinen, Finland.
| | | | - Laura Cowan
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Matthew Carlile
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | | | | | - Siri Birkeland
- Natural History Museum, University of Oslo, Oslo, Norway
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway
| | - Matthew Loose
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Filip Kolář
- Department of Botany, Faculty of Science, Charles University, Prague, Czech Republic
- Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic
| | - Marcus A Koch
- Centre for Organismal Studies, University of Heidelberg, Heidelberg, Germany
| | - Levi Yant
- School of Life Sciences, University of Nottingham, Nottingham, UK.
- Department of Botany, Faculty of Science, Charles University, Prague, Czech Republic.
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5
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Camus L, Gautier M, Boitard S. Predicting species invasiveness with genomic data: Is genomic offset related to establishment probability? Evol Appl 2024; 17:e13709. [PMID: 38884022 PMCID: PMC11178484 DOI: 10.1111/eva.13709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/30/2024] [Accepted: 05/04/2024] [Indexed: 06/18/2024] Open
Abstract
Predicting the risk of establishment and spread of populations outside their native range represents a major challenge in evolutionary biology. Various methods have recently been developed to estimate population (mal)adaptation to a new environment with genomic data via so-called Genomic Offset (GO) statistics. These approaches are particularly promising for studying invasive species but have still rarely been used in this context. Here, we evaluated the relationship between GO and the establishment probability of a population in a new environment using both in silico and empirical data. First, we designed invasion simulations to evaluate the ability to predict establishment probability of two GO computation methods (Geometric GO and Gradient Forest) under several conditions. Additionally, we aimed to evaluate the interpretability of absolute Geometric GO values, which theoretically represent the adaptive genetic distance between populations from distinct environments. Second, utilizing public empirical data from the crop pest species Bactrocera tryoni, a fruit fly native from Northern Australia, we computed GO between "source" populations and a diverse range of locations within invaded areas. This practical application of GO within the context of a biological invasion underscores its potential in providing insights and guiding recommendations for future invasion risk assessment. Overall, our results suggest that GO statistics represent good predictors of the establishment probability and may thus inform invasion risk, although the influence of several factors on prediction performance (e.g., propagule pressure or admixture) will need further investigation.
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Affiliation(s)
- Louise Camus
- CBGP, INRAE, CIRAD, IRD, L'institut Agro, Université de Montpellier Montpellier France
| | - Mathieu Gautier
- CBGP, INRAE, CIRAD, IRD, L'institut Agro, Université de Montpellier Montpellier France
| | - Simon Boitard
- CBGP, INRAE, CIRAD, IRD, L'institut Agro, Université de Montpellier Montpellier France
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6
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Sun PW, Chang JT, Luo MX, Liao PC. Genomic insights into local adaptation and vulnerability of Quercus longinux to climate change. BMC PLANT BIOLOGY 2024; 24:279. [PMID: 38609850 PMCID: PMC11015620 DOI: 10.1186/s12870-024-04942-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 03/22/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND Climate change is expected to alter the factors that drive changes in adaptive variation. This is especially true for species with long life spans and limited dispersal capabilities. Rapid climate changes may disrupt the migration of beneficial genetic variations, making it challenging for them to keep up with changing environments. Understanding adaptive genetic variations in tree species is crucial for conservation and effective forest management. Our study used landscape genomic analyses and phenotypic traits from a thorough sampling across the entire range of Quercus longinux, an oak species native to Taiwan, to investigate the signals of adaptation within this species. RESULTS Using ecological data, phenotypic traits, and 1,933 single-nucleotide polymorphisms (SNPs) from 205 individuals, we classified three genetic groups, which were also phenotypically and ecologically divergent. Thirty-five genes related to drought and freeze resistance displayed signatures of natural selection. The adaptive variation was driven by diverse environmental pressures such as low spring precipitation, low annual temperature, and soil grid sizes. Using linear-regression-based methods, we identified isolation by environment (IBE) as the optimal model for adaptive SNPs. Redundancy analysis (RDA) further revealed a substantial joint influence of demography, geology, and environments, suggesting a covariation between environmental gradients and colonization history. Lastly, we utilized adaptive signals to estimate the genetic offset for each individual under diverse climate change scenarios. The required genetic changes and migration distance are larger in severe climates. Our prediction also reveals potential threats to edge populations in northern and southeastern Taiwan due to escalating temperatures and precipitation reallocation. CONCLUSIONS We demonstrate the intricate influence of ecological heterogeneity on genetic and phenotypic adaptation of an oak species. The adaptation is also driven by some rarely studied environmental factors, including wind speed and soil features. Furthermore, the genetic offset analysis predicted that the edge populations of Q. longinux in lower elevations might face higher risks of local extinctions under climate change.
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Affiliation(s)
- Pei-Wei Sun
- School of Life Science, National Taiwan Normal University, No. 88 Ting-Chow Rd., Sec. 4, Taipei, 116, Taiwan
| | - Jui-Tse Chang
- School of Life Science, National Taiwan Normal University, No. 88 Ting-Chow Rd., Sec. 4, Taipei, 116, Taiwan
| | - Min-Xin Luo
- School of Life Science, National Taiwan Normal University, No. 88 Ting-Chow Rd., Sec. 4, Taipei, 116, Taiwan
| | - Pei-Chun Liao
- School of Life Science, National Taiwan Normal University, No. 88 Ting-Chow Rd., Sec. 4, Taipei, 116, Taiwan.
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7
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Lind BM, Candido-Ribeiro R, Singh P, Lu M, Obreht Vidakovic D, Booker TR, Whitlock MC, Yeaman S, Isabel N, Aitken SN. How useful are genomic data for predicting maladaptation to future climate? GLOBAL CHANGE BIOLOGY 2024; 30:e17227. [PMID: 38558300 DOI: 10.1111/gcb.17227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 12/18/2023] [Accepted: 12/27/2023] [Indexed: 04/04/2024]
Abstract
Methods using genomic information to forecast potential population maladaptation to climate change or new environments are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare the validation of maladaptation estimates derived from two methods-Gradient Forests (GFoffset) and the risk of non-adaptedness (RONA)-using exome capture pool-seq data from 35 to 39 populations across three conifer taxa: two Douglas-fir varieties and jack pine. We evaluate sensitivity of these algorithms to the source of input loci (markers selected from genotype-environment associations [GEA] or those selected at random). We validate these methods against 2- and 52-year growth and mortality measured in independent transplant experiments. Overall, we find that both methods often better predict transplant performance than climatic or geographic distances. We also find that GFoffset and RONA models are surprisingly not improved using GEA candidates. Even with promising validation results, variation in model projections to future climates makes it difficult to identify the most maladapted populations using either method. Our work advances understanding of the sensitivity and applicability of these approaches, and we discuss recommendations for their future use.
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Affiliation(s)
- Brandon M Lind
- Centre for Forest Conservation Genetics and Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Rafael Candido-Ribeiro
- Centre for Forest Conservation Genetics and Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Pooja Singh
- Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Mengmeng Lu
- Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Dragana Obreht Vidakovic
- Centre for Forest Conservation Genetics and Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tom R Booker
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Michael C Whitlock
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Sam Yeaman
- Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Nathalie Isabel
- Canada Research Chair in Forest Genomics, Centre for Forest Research and Institute for Systems and Integrative Biology, Université Laval, Québec, Quebec, Canada
- Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, Quebec, Canada
| | - Sally N Aitken
- Centre for Forest Conservation Genetics and Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia, Canada
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8
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Jeffery NW, Vercaemer B, Stanley RRE, Kess T, Dufresne F, Noisette F, O'Connor MI, Wong MC. Variation in genomic vulnerability to climate change across temperate populations of eelgrass ( Zostera marina). Evol Appl 2024; 17:e13671. [PMID: 38650965 PMCID: PMC11033490 DOI: 10.1111/eva.13671] [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: 01/20/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 04/25/2024] Open
Abstract
A global decline in seagrass populations has led to renewed calls for their conservation as important providers of biogenic and foraging habitat, shoreline stabilization and carbon storage. Eelgrass (Zostera marina) occupies the largest geographic range among seagrass species spanning a commensurately broad spectrum of environmental conditions. In Canada, eelgrass is managed as a single phylogroup despite occurring across three oceans and a range of ocean temperatures and salinity gradients. Previous research has focused on applying relatively few markers to reveal population structure of eelgrass, whereas a whole-genome approach is warranted to investigate cryptic structure among populations inhabiting different ocean basins and localized environmental conditions. We used a pooled whole-genome re-sequencing approach to characterize population structure, gene flow and environmental associations of 23 eelgrass populations ranging from the Northeast United States to Atlantic, subarctic and Pacific Canada. We identified over 500,000 SNPs, which when mapped to a chromosome-level genome assembly revealed six broad clades of eelgrass across the study area, with pairwise F ST ranging from 0 among neighbouring populations to 0.54 between Pacific and Atlantic coasts. Genetic diversity was highest in the Pacific and lowest in the subarctic, consistent with colonization of the Arctic and Atlantic oceans from the Pacific less than 300 kya. Using redundancy analyses and two climate change projection scenarios, we found that subarctic populations are predicted to be potentially more vulnerable to climate change through genomic offset predictions. Conservation planning in Canada should thus ensure that representative populations from each identified clade are included within a national network so that latent genetic diversity is protected, and gene flow is maintained. Northern populations, in particular, may require additional mitigation measures given their potential susceptibility to a rapidly changing climate.
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Affiliation(s)
- Nicholas W. Jeffery
- Fisheries and Oceans CanadaBedford Institute of OceanographyDartmouthNova ScotiaCanada
| | - Benedikte Vercaemer
- Fisheries and Oceans CanadaBedford Institute of OceanographyDartmouthNova ScotiaCanada
| | - Ryan R. E. Stanley
- Fisheries and Oceans CanadaBedford Institute of OceanographyDartmouthNova ScotiaCanada
| | - Tony Kess
- Fisheries and Oceans Canada, Northwest Atlantic Fisheries CentreSt. John'sNewfoundland and LabradorCanada
| | - France Dufresne
- Département de BiologieUniversité du Québec à RimouskiRimouskiQuebecCanada
| | - Fanny Noisette
- Institut des Sciences de la mer, Université du Québec à RimouskiRimouskiQuebecCanada
| | - Mary I. O'Connor
- Department of Zoology and Biodiversity Research CentreUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Melisa C. Wong
- Fisheries and Oceans CanadaBedford Institute of OceanographyDartmouthNova ScotiaCanada
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9
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Cheng J, Zhang Z, Li Y, Zhang L, Hui M, Sha Z. Rolling with the punches: Organism-environment interactions shape spatial pattern of adaptive differentiation in the widespread mantis shrimp Oratosquilla oratoria. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170244. [PMID: 38278258 DOI: 10.1016/j.scitotenv.2024.170244] [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: 09/12/2023] [Revised: 01/12/2024] [Accepted: 01/15/2024] [Indexed: 01/28/2024]
Abstract
Investigating spatial pattern of adaptive variation and its underlying processes can inform the adaptive potential distributed within species ranges, which is increasingly important in the context of a changing climate. A correct interpretation of adaptive variation pattern requires that population history and the ensuing population genetic structure are taken into account. Here we carried out such a study by integrating population genomic analyses, demographic model testing and species distribution modeling to investigate patterns and causes of adaptive differentiation in a widespread mantis shrimp, Oratosquilla oratoria, along a replicated, broad-scale temperature gradient in the northwestern Pacific (NWP). Our results supported a strong hierarchical ecogeographic structure dominated by habitat-linked divergence among O. oratoria populations accompanied with introgressive hybridization. A combined FST outlier and environmental correlation analyses revealed remarkable temperature-associated clines in allele frequency across paired North-South populations on Chinese and Japanese coasts, and identified a suite of loci associated with temperature adaptation. Further demographic model testing revealed the observed clinal variation derived partly from Pleistocene divergence followed by recent secondary contact. More importantly, the likelihood of hybridization is predicted to increase as climate change progresses, which would break barriers to gene flow and enable the spread of adaptive genetic variation. These results support that not only is temperature-driven adaptive differentiation occurs in O. oratoria but that such pattern is likely attributed to ancient adaptive variation, sustained by contemporary ocean conditions and a semi-permeable barrier to gene flow maintained by selection. They moreover provide genomic insights into the distribution of adaptive potential across O. oratoria' s species range. This work can serve as a case study to characterize adaptive diversity of marine species in the NWP by integrating environmental and genetic data at temporal and spatial scales in a population genomic framework, which would improve management and conservation actions under climate change.
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Affiliation(s)
- Jiao Cheng
- Department of Marine Organism Taxonomy & Phylogeny, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao 266237, China; Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Zhixin Zhang
- CAS Key Laboratory of Tropical Marine Bio-Resources and Ecology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Global Ocean and Climate Research Center, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510275, China
| | - Yulong Li
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Liwen Zhang
- Department of Marine Organism Taxonomy & Phylogeny, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Min Hui
- Department of Marine Organism Taxonomy & Phylogeny, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao 266237, China; Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Zhongli Sha
- Department of Marine Organism Taxonomy & Phylogeny, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao 266237, China; Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China.
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10
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Bernatchez L, Ferchaud AL, Berger CS, Venney CJ, Xuereb A. Genomics for monitoring and understanding species responses to global climate change. Nat Rev Genet 2024; 25:165-183. [PMID: 37863940 DOI: 10.1038/s41576-023-00657-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/29/2023] [Indexed: 10/22/2023]
Abstract
All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.
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Affiliation(s)
- Louis Bernatchez
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Anne-Laure Ferchaud
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada.
- Parks Canada, Office of the Chief Ecosystem Scientist, Protected Areas Establishment, Quebec City, Quebec, Canada.
| | - Chloé Suzanne Berger
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Clare J Venney
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Amanda Xuereb
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
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11
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Layton KKS, Brieuc MSO, Castilho R, Diaz-Arce N, Estévez-Barcia D, Fonseca VG, Fuentes-Pardo AP, Jeffery NW, Jiménez-Mena B, Junge C, Kaufmann J, Leinonen T, Maes SM, McGinnity P, Reed TE, Reisser CMO, Silva G, Vasemägi A, Bradbury IR. Predicting the future of our oceans-Evaluating genomic forecasting approaches in marine species. GLOBAL CHANGE BIOLOGY 2024; 30:e17236. [PMID: 38519845 DOI: 10.1111/gcb.17236] [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: 12/18/2023] [Revised: 02/21/2024] [Accepted: 02/25/2024] [Indexed: 03/25/2024]
Abstract
Climate change is restructuring biodiversity on multiple scales and there is a pressing need to understand the downstream ecological and genomic consequences of this change. Recent advancements in the field of eco-evolutionary genomics have sought to include evolutionary processes in forecasting species' responses to climate change (e.g., genomic offset), but to date, much of this work has focused on terrestrial species. Coastal and offshore species, and the fisheries they support, may be even more vulnerable to climate change than their terrestrial counterparts, warranting a critical appraisal of these approaches in marine systems. First, we synthesize knowledge about the genomic basis of adaptation in marine species, and then we discuss the few examples where genomic forecasting has been applied in marine systems. Next, we identify the key challenges in validating genomic offset estimates in marine species, and we advocate for the inclusion of historical sampling data and hindcasting in the validation phase. Lastly, we describe a workflow to guide marine managers in incorporating these predictions into the decision-making process.
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Affiliation(s)
- K K S Layton
- Department of Biology, University of Toronto Mississauga, Mississauga, Ontario, Canada
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
| | | | - R Castilho
- University of the Algarve, Faro, Portugal
- Centre for Marine Sciences, University of the Algarve, Faro, Portugal
- Pattern Institute, Faro, Portugal
| | - N Diaz-Arce
- AZTI Marine Research, Basque Research and Technology Alliance (BRTA), Sukarrieta, Spain
| | - D Estévez-Barcia
- Department of Fish and Shellfish, Greenland Institute of Natural Resources, Nuuk, Greenland
| | - V G Fonseca
- Centre for Environment, Fisheries and Aquaculture Science, Weymouth, UK
| | - A P Fuentes-Pardo
- Department of Immunology, Genetics and Pathology, SciLifeLab Data Centre, Uppsala University, Uppsala, Sweden
| | - N W Jeffery
- Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia, Canada
| | - B Jiménez-Mena
- Section for Marine Living Resources, National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
| | - C Junge
- Institute of Marine Research, Tromso, Norway
| | | | - T Leinonen
- Natural Resources Institute Finland, Helsinki, Finland
| | - S M Maes
- Flanders Research Institute for Agriculture, Fisheries and Food, Ostend, Belgium
| | - P McGinnity
- School of Biological, Earth & Environmental Sciences, University College Cork, Cork, Ireland
| | - T E Reed
- School of Biological, Earth & Environmental Sciences, University College Cork, Cork, Ireland
| | - C M O Reisser
- MARBEC, University of Montpellier, CNRS, IFREMER, IRD, Montpellier, France
| | - G Silva
- MARE-Marine and Environmental Sciences Centre/ARNET-Aquatic Research Network, ISPA-Instituto Universitário, Lisbon, Portugal
| | - A Vasemägi
- Swedish University of Agricultural Sciences, Drottningholm, Sweden
- Estonian University of Life Sciences, Tartu, Estonia
| | - I R Bradbury
- Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John's, Newfoundland and Labrador, Canada
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12
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Schmidt TL, Thia JA, Hoffmann AA. How Can Genomics Help or Hinder Wildlife Conservation? Annu Rev Anim Biosci 2024; 12:45-68. [PMID: 37788416 DOI: 10.1146/annurev-animal-021022-051810] [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] [Indexed: 10/05/2023]
Abstract
Genomic data are becoming increasingly affordable and easy to collect, and new tools for their analysis are appearing rapidly. Conservation biologists are interested in using this information to assist in management and planning but are typically limited financially and by the lack of genomic resources available for non-model taxa. It is therefore important to be aware of the pitfalls as well as the benefits of applying genomic approaches. Here, we highlight recent methods aimed at standardizing population assessments of genetic variation, inbreeding, and forms of genetic load and methods that help identify past and ongoing patterns of genetic interchange between populations, including those subjected to recent disturbance. We emphasize challenges in applying some of these methods and the need for adequate bioinformatic support. We also consider the promises and challenges of applying genomic approaches to understand adaptive changes in natural populations to predict their future adaptive capacity.
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Affiliation(s)
- Thomas L Schmidt
- School of BioSciences, Bio21 Institute, University of Melbourne, Parkville, Victoria, Australia;
| | - Joshua A Thia
- School of BioSciences, Bio21 Institute, University of Melbourne, Parkville, Victoria, Australia;
| | - Ary A Hoffmann
- School of BioSciences, Bio21 Institute, University of Melbourne, Parkville, Victoria, Australia;
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13
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Andersson L, Bekkevold D, Berg F, Farrell ED, Felkel S, Ferreira MS, Fuentes-Pardo AP, Goodall J, Pettersson M. How Fish Population Genomics Can Promote Sustainable Fisheries: A Road Map. Annu Rev Anim Biosci 2024; 12:1-20. [PMID: 37906837 DOI: 10.1146/annurev-animal-021122-102933] [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] [Indexed: 11/02/2023]
Abstract
Maintenance of genetic diversity in marine fishes targeted by commercial fishing is a grand challenge for the future. Most of these species are abundant and therefore important for marine ecosystems and food security. Here, we present a road map of how population genomics can promote sustainable fisheries. In these species, the development of reference genomes and whole genome sequencing is key, because genetic differentiation at neutral loci is usually low due to large population sizes and gene flow. First, baseline allele frequencies representing genetically differentiated populations within species must be established. These can then be used to accurately determine the composition of mixed samples, forming the basis for population demographic analysis to inform sustainably set fish quotas. SNP-chip analysis is a cost-effective method for determining baseline allele frequencies and for population identification in mixed samples. Finally, we describe how genetic marker analysis can transform stock identification and management.
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Affiliation(s)
- Leif Andersson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden;
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, USA
| | - Dorte Bekkevold
- National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
| | | | - Edward D Farrell
- Killybegs Fishermen's Organisation, Killybegs, County Donegal, Ireland
| | - Sabine Felkel
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden;
| | - Mafalda S Ferreira
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden;
| | - Angela P Fuentes-Pardo
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden;
| | - Jake Goodall
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden;
| | - Mats Pettersson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden;
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14
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Hipp AL, Lazic D. Ancient tree genomes for old questions. Mol Ecol 2024; 33:e17259. [PMID: 38179684 DOI: 10.1111/mec.17259] [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: 09/21/2023] [Revised: 11/19/2023] [Accepted: 12/19/2023] [Indexed: 01/06/2024]
Abstract
Most foundational work on the evolution and migration of plant species relies on genomic data from contemporary samples. Ancient plant samples can give us access to allele sequences and distributions on the landscape dating back to the mid Holocene or earlier (Gugerli et al., 2005). Nuclear DNA from ancient wood, however, has been mostly inaccessible until now. In a From the Cover article in this issue of Molecular Ecology, Wagner et al. (2023) present the first resequenced nuclear genomes from ancient oak wood, including two samples dated to the 15th century and one that dates to more than 3500 years ago. These ancient tree genomes open the possibility for investigating species adaptation, migration, divergence, and hybridisation in the deep past. They pave the way for what we hope will be a new era in the use of paleogenomics to study Holocene tree histories.
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Affiliation(s)
- Andrew L Hipp
- Herbarium and Center for Tree Science, The Morton Arboretum, Lisle, Illinois, USA
- Botany Department, The Field Museum, Chicago, Illinois, USA
| | - Desanka Lazic
- Department of Forest Genetics and Forest Tree Breeding, University of Göttingen, Göttingen, Germany
- Thünen Institute of Forest Genetics, Grosshansdorf, Germany
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15
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Lovell RSL, Collins S, Martin SH, Pigot AL, Phillimore AB. Space-for-time substitutions in climate change ecology and evolution. Biol Rev Camb Philos Soc 2023; 98:2243-2270. [PMID: 37558208 DOI: 10.1111/brv.13004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 07/20/2023] [Accepted: 07/24/2023] [Indexed: 08/11/2023]
Abstract
In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.
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Affiliation(s)
- Rebecca S L Lovell
- Ashworth Laboratories, Institute of Ecology and Evolution, The University of Edinburgh, Charlotte Auerbach Road, Edinburgh, EH9 3FL, UK
| | - Sinead Collins
- Ashworth Laboratories, Institute of Ecology and Evolution, The University of Edinburgh, Charlotte Auerbach Road, Edinburgh, EH9 3FL, UK
| | - Simon H Martin
- Ashworth Laboratories, Institute of Ecology and Evolution, The University of Edinburgh, Charlotte Auerbach Road, Edinburgh, EH9 3FL, UK
| | - Alex L Pigot
- Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, Gower Street, London, WC1E 6BT, UK
| | - Albert B Phillimore
- Ashworth Laboratories, Institute of Ecology and Evolution, The University of Edinburgh, Charlotte Auerbach Road, Edinburgh, EH9 3FL, UK
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16
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Wu R, Qi J, Li W, Wang L, Shen Y, Liu J, Teng Y, Roos C, Li M. Landscape genomics analysis provides insights into future climate change-driven risk in rhesus macaque. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 899:165746. [PMID: 37495138 DOI: 10.1016/j.scitotenv.2023.165746] [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: 02/27/2023] [Revised: 07/01/2023] [Accepted: 07/21/2023] [Indexed: 07/28/2023]
Abstract
Climate change significantly affects the suitability of wildlife habitats. Thus, understanding how animals adapt ecologically and genetically to climate change is important for targeted species protection. Rhesus macaques (Macaca mulatta) are widely distributed and multi-climatically adapted primates. This study explored how rhesus macaques adapt to climate change by integrating ecological and genetic methods and applying species distribution models (SDMs) and a gradient forest (GF) model. The findings suggested that temperature seasonality primarily affects habitat suitability and indicated that climate change will have a dramatic impact on macaque populations in the future. We also applied genotype-environment association (GEA) analyses and selection signature analyses to identify genes associated with climate change and provide possible explanations for the adaptation of rhesus macaques to climatic environments. The population genomics analyses suggested that the Taihang population has the highest genomic vulnerability with inbreeding and low heterozygosity. Combined with the higher ecological vulnerability, additional conservation strategies are required for this population under higher risk of climate change. Our work measured the impact of climate change and enabled the identification of populations that exhibit high vulnerability to severe climate change. Such information is useful for selecting populations of rhesus macaques as subject of long-term monitoring or evolutionary rescue under future climate change.
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Affiliation(s)
- Ruifeng Wu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiwei Qi
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Wenbo Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Ling Wang
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ying Shen
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiawen Liu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yang Teng
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Christian Roos
- Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Ming Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China.
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17
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Hung TH, So T, Thammavong B, Chamchumroon V, Theilade I, Phourin C, Bouamanivong S, Hartvig I, Gaisberger H, Jalonen R, Boshier DH, MacKay JJ. Range-wide differential adaptation and genomic offset in critically endangered Asian rosewoods. Proc Natl Acad Sci U S A 2023; 120:e2301603120. [PMID: 37549265 PMCID: PMC10438386 DOI: 10.1073/pnas.2301603120] [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: 01/29/2023] [Accepted: 06/15/2023] [Indexed: 08/09/2023] Open
Abstract
In the billion-dollar global illegal wildlife trade, rosewoods have been the world's most trafficked wild product since 2005. Dalbergia cochinchinensis and Dalbergia oliveri are the most sought-after rosewoods in the Greater Mekong Subregion. They are exposed to significant genetic risks and the lack of knowledge on their adaptability limits the effectiveness of conservation efforts. Here, we present genome assemblies and range-wide genomic scans of adaptive variation, together with predictions of genomic offset to climate change. Adaptive genomic variation was differentially associated with temperature and precipitation-related variables between the species, although their natural ranges overlap. The findings are consistent with differences in pioneering ability and in drought tolerance. We predict their genomic offsets will increase over time and with increasing carbon emission pathway but at a faster pace in D. cochinchinensis than in D. oliveri. These results and the distinct gene-environment association in the eastern coastal edge of Vietnam suggest species-specific conservation actions: germplasm representation across the range in D. cochinchinensis and focused on hotspots of genomic offset in D. oliveri. We translated our genomic models into a seed source matching application, seedeR, to rapidly inform restoration efforts. Our ecological genomic research uncovering contrasting selection forces acting in sympatric rosewoods is of relevance to conserving tropical trees globally and combating risks from climate change.
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Affiliation(s)
- Tin Hang Hung
- Department of Biology, University of Oxford, OxfordOX1 3RB, United Kingdom
| | - Thea So
- Institute of Forest and Wildlife Research and Development, Phnom Penh, Cambodia
| | - Bansa Thammavong
- National Agriculture and Forestry Research Institute, Forestry Research Center, Vientiane, Laos
| | - Voradol Chamchumroon
- The Forest Herbarium, Department of National Park, Wildlife and Plant Conservation, Ministry of Natural Resources and Environment, Bangkok10900, Thailand
| | - Ida Theilade
- Department of Food and Resource Economics, Faculty of Science, University of Copenhagen, Rolighedsvej 23, 1958Frederiksberg C, Denmark
| | - Chhang Phourin
- Institute of Forest and Wildlife Research and Development, Phnom Penh, Cambodia
| | - Somsanith Bouamanivong
- National Herbarium of Laos, Biotechnology and Ecology Institute, Ministry of Science and Technology, Vientiane, Laos
| | - Ida Hartvig
- Forest Genetics and Diversity, Department of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej 23, 1958Frederiksberg C, Denmark
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Øster Farimagsgade 5, 1353 Copenhagen K, Denmark
| | - Hannes Gaisberger
- Bioversity International, I-00057Rome, Italy
- Department of Geoinformatics, Paris Lodron University, 5020Salzburg, Austria
| | | | - David H. Boshier
- Department of Biology, University of Oxford, OxfordOX1 3RB, United Kingdom
| | - John J. MacKay
- Department of Biology, University of Oxford, OxfordOX1 3RB, United Kingdom
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18
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Forester BR, Day CC, Ruegg K, Landguth EL. Evolutionary potential mitigates extinction risk under climate change in the endangered southwestern willow flycatcher. J Hered 2023; 114:341-353. [PMID: 36738446 PMCID: PMC10287148 DOI: 10.1093/jhered/esac067] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 12/09/2022] [Indexed: 02/05/2023] Open
Abstract
The complexity of global anthropogenic change makes forecasting species responses and planning effective conservation actions challenging. Additionally, important components of a species' adaptive capacity, such as evolutionary potential, are often not included in quantitative risk assessments due to lack of data. While genomic proxies for evolutionary potential in at-risk species are increasingly available, they have not yet been included in extinction risk assessments at a species-wide scale. In this study, we used an individual-based, spatially explicit, dynamic eco-evolutionary simulation model to evaluate the extinction risk of an endangered desert songbird, the southwestern willow flycatcher (Empidonax traillii extimus), in response to climate change. Using data from long-term demographic and habitat studies in conjunction with genome-wide ecological genomics research, we parameterized simulations that include 418 sites across the breeding range, genomic data from 225 individuals, and climate change forecasts spanning 3 generalized circulation models and 3 emissions scenarios. We evaluated how evolutionary potential, and the lack of it, impacted population trajectories in response to climate change. We then investigated the compounding impact of drought and warming temperatures on extinction risk through the mechanism of increased nest failure. Finally, we evaluated how rapid action to reverse greenhouse gas emissions would influence population responses and species extinction risk. Our results illustrate the value of incorporating evolutionary, demographic, and dispersal processes in a spatially explicit framework to more comprehensively evaluate the extinction risk of threatened and endangered species and conservation actions to promote their recovery.
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Affiliation(s)
- Brenna R Forester
- Department of Biology, Colorado State University, Fort Collins, CO, United States
| | - Casey C Day
- Computational Ecology Lab, School of Public and Community Health Sciences, University of Montana, Missoula, MT, United States
| | - Kristen Ruegg
- Department of Biology, Colorado State University, Fort Collins, CO, United States
| | - Erin L Landguth
- Computational Ecology Lab, School of Public and Community Health Sciences, University of Montana, Missoula, MT, United States
- Center for Population Health Research, School of Public and Community Health Sciences, University of Montana, Missoula, MT, United States
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19
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Zhang L, Chen J, Zhao R, Zhong J, Lin L, Li H, Ji X, Qu Y. Genomic insights into local adaptation in the Asiatic toad Bufo gargarizans, and its genomic offset to climate warming. Evol Appl 2023; 16:1071-1083. [PMID: 37216027 PMCID: PMC10197391 DOI: 10.1111/eva.13555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 03/31/2023] [Accepted: 04/20/2023] [Indexed: 05/24/2023] Open
Abstract
Genomic signatures of local adaptation have been identified in many species but remain sparsely studied in amphibians. Here, we explored genome-wide divergence within the Asiatic toad, Bufo gargarizans, to study local adaptation and genomic offset (i.e., the mismatch between current and future genotype-environment relationships) under climate warming scenarios. We obtained high-quality SNP data for 94 Asiatic toads from 21 populations in China to study spatial patterns of genomic variation, local adaptation, and genomic offset to warming in this wide-ranging species. Population structure and genetic diversity analysis based on high-quality SNPs revealed three clusters of B. gargarizans in the western, central-eastern, and northeastern portions of the species' range in China. Populations generally dispersed along two migration routes, one from the west to the central-east and one from the central-east to the northeast. Both genetic diversity and pairwise F ST were climatically correlated, and pairwise F ST was also correlated with geographic distance. Spatial genomic patterns in B. gargarizans were determined by the local environment and geographic distance. Global warming will increase the extirpation risk of B. gargarizans.
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Affiliation(s)
- Lu‐Wen Zhang
- College of Life SciencesNanjing Normal UniversityNanjingChina
| | - Jun‐Qiong Chen
- College of Life SciencesNanjing Normal UniversityNanjingChina
| | - Ru‐Meng Zhao
- College of Life SciencesNanjing Normal UniversityNanjingChina
| | - Jun Zhong
- Zhejiang Provincial Key Laboratory for Water Environment and Marine Biological Resources Protection, College of Life and Environmental SciencesWenzhou UniversityWenzhouChina
| | - Long‐Hui Lin
- College of Life and Environmental SciencesHangzhou Normal UniversityHangzhouChina
| | - Hong Li
- College of Life SciencesNanjing Normal UniversityNanjingChina
| | - Xiang Ji
- Zhejiang Provincial Key Laboratory for Water Environment and Marine Biological Resources Protection, College of Life and Environmental SciencesWenzhou UniversityWenzhouChina
| | - Yan‐Fu Qu
- College of Life SciencesNanjing Normal UniversityNanjingChina
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20
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Lotterhos KE. The paradox of adaptive trait clines with nonclinal patterns in the underlying genes. Proc Natl Acad Sci U S A 2023; 120:e2220313120. [PMID: 36917658 PMCID: PMC10041142 DOI: 10.1073/pnas.2220313120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 02/03/2023] [Indexed: 03/16/2023] Open
Abstract
Multivariate climate change presents an urgent need to understand how species adapt to complex environments. Population genetic theory predicts that loci under selection will form monotonic allele frequency clines with their selective environment, which has led to the wide use of genotype-environment associations (GEAs). This study used a set of simulations to elucidate the conditions under which allele frequency clines are more or less likely to evolve as multiple quantitative traits adapt to multivariate environments. Phenotypic clines evolved with nonmonotonic (i.e., nonclinal) patterns in allele frequencies under conditions that promoted unique combinations of mutations to achieve the multivariate optimum in different parts of the landscape. Such conditions resulted from interactions among landscape, demography, pleiotropy, and genetic architecture. GEA methods failed to accurately infer the genetic basis of adaptation under a range of scenarios due to first principles (clinal patterns did not evolve) or statistical issues (clinal patterns evolved but were not detected due to overcorrection for structure). Despite the limitations of GEAs, this study shows that a back-transformation of multivariate ordination can accurately predict individual multivariate traits from genotype and environmental data regardless of whether inference from GEAs was accurate. In addition, frameworks are introduced that can be used by empiricists to quantify the importance of clinal alleles in adaptation. This research highlights that multivariate trait prediction from genotype and environmental data can lead to accurate inference regardless of whether the underlying loci display clinal or nonmonotonic patterns.
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Affiliation(s)
- Katie E. Lotterhos
- Department of Marine and Environmental Sciences, Northeastern University Marine Science Center, Nahant, MA01908
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21
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Dauphin B, Rellstab C, Wüest RO, Karger DN, Holderegger R, Gugerli F, Manel S. Re-thinking the environment in landscape genomics. Trends Ecol Evol 2023; 38:261-274. [PMID: 36402651 DOI: 10.1016/j.tree.2022.10.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/20/2022] [Accepted: 10/28/2022] [Indexed: 11/19/2022]
Abstract
Detecting the extrinsic selective pressures shaping genomic variation is critical for a better understanding of adaptation and for forecasting evolutionary responses of natural populations to changing environmental conditions. With increasing availability of geo-referenced environmental data, landscape genomics provides unprecedented insights into how genomic variation and underlying gene functions affect traits potentially under selection. Yet, the robustness of genotype-environment associations used in landscape genomics remains tempered due to various limitations, including the characteristics of environmental data used, sampling designs employed, and statistical frameworks applied. Here, we argue that using complementary or new environmental data sources and well-informed sampling designs may help improve the detection of selective pressures underlying patterns of local adaptation in various organisms and environments.
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Affiliation(s)
- Benjamin Dauphin
- Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland.
| | | | - Rafael O Wüest
- Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland
| | - Dirk N Karger
- Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland
| | - Rolf Holderegger
- Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland; Institute of Integrative Biology (IBZ), ETH, Zurich, 8092 Zurich, Switzerland
| | - Felix Gugerli
- Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland
| | - Stéphanie Manel
- Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland; CEFE, University of Montpellier, CNRS, EPHE-PSL University, IRD, 34000 Montpellier, France; Institut Universitaire de France, Paris, France
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22
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Dauphin B, Peter M. Advancing research on ectomycorrhizal fungal adaptation with landscape genomics. Trends Microbiol 2023; 31:439-443. [PMID: 36868897 DOI: 10.1016/j.tim.2023.02.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/10/2023] [Accepted: 02/13/2023] [Indexed: 03/05/2023]
Abstract
Ectomycorrhizal (ECM) fungi serve key functions in forest ecosystems by supplying water and nutrients to tree hosts, yet mutualistic plant-fungi interactions are jeopardised by environmental alterations. Here, we discuss the great potential and current limitations of landscape genomics in investigating signatures of local adaptation in natural populations of ECM fungi.
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Affiliation(s)
| | - Martina Peter
- Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
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23
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Exposito-Alonso M. Understanding local plant extinctions before it is too late: bridging evolutionary genomics with global ecology. THE NEW PHYTOLOGIST 2023; 237:2005-2011. [PMID: 36604850 DOI: 10.1111/nph.18718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 12/04/2022] [Indexed: 06/17/2023]
Abstract
Understanding evolutionary genomic and population processes within a species range is key to anticipating the extinction of plant species before it is too late. However, most models of biodiversity risk under global change do not account for the genetic variation and local adaptation of different populations. Population diversity is critical to understanding extinction because different populations may be more or less susceptible to global change and, if lost, would reduce the total diversity within a species. Two new modeling frameworks advance our understanding of extinction from a population and evolutionary angle: Rapid climate change-driven disruptions in population adaptation are predicted from associations between genomes and local climates. Furthermore, losses of population diversity from global land-use transformations are estimated by scaling relationships of species' genomic diversity with habitat area. Overall, these global eco-evolutionary methods advance the predictability - and possibly the preventability - of the ongoing extinction of plant species.
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Affiliation(s)
- Moi Exposito-Alonso
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA, 94305, USA
- Department of Biology, Stanford University, Stanford, CA, 94305, USA
- Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, 94305, USA
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24
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Vanhove M, Launey S. Estimating resistance surfaces using gradient forest and allelic frequencies. Mol Ecol Resour 2023. [PMID: 36847356 DOI: 10.1111/1755-0998.13778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 02/06/2023] [Accepted: 02/22/2023] [Indexed: 03/01/2023]
Abstract
Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Connectivity methods that use link-based methods traditionally rely on relating pairwise genetic distance between individuals or demes to their landscape distance (e.g., geographic distance, cost distance). In this study, we present an alternative to conventional statistical approaches to refine cost surfaces by adapting the gradient forest approach to produce a resistance surface. Used in community ecology, gradient forest is an extension of random forest, and has been implemented in genomic studies to model species genetic offset under future climatic scenarios. By design, this adapted method, resGF, has the ability to handle multiple environmental predicators and is not subjected to traditional assumptions of linear models such as independence, normality and linearity. Using genetic simulations, resistance Gradient Forest (resGF) performance was compared to other published methods (maximum likelihood population effects model, random forest-based least-cost transect analysis and species distribution model). In univariate scenarios, resGF was able to distinguish the true surface contributing to genetic diversity among competing surfaces better than the compared methods. In multivariate scenarios, the gradient forest approach performed similarly to the other random forest-based approach using least-cost transect analysis but outperformed MLPE-based methods. Additionally, two worked examples are provided using two previously published data sets. This machine learning algorithm has the potential to improve our understanding of landscape connectivity and inform long-term biodiversity conservation strategies.
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Affiliation(s)
- Mathieu Vanhove
- DECOD (Ecosystem Dynamics and Sustainability), INRAE, Institut Agro, IFREMER, Rennes, France
| | - Sophie Launey
- DECOD (Ecosystem Dynamics and Sustainability), INRAE, Institut Agro, IFREMER, Rennes, France
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25
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Chung MY, Merilä J, Li J, Mao K, López-Pujol J, Tsumura Y, Chung MG. Neutral and adaptive genetic diversity in plants: An overview. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2023.1116814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023] Open
Abstract
Genetic diversity is a prerequisite for evolutionary change in all kinds of organisms. It is generally acknowledged that populations lacking genetic variation are unable to evolve in response to new environmental conditions (e.g., climate change) and thus may face an increased risk of extinction. Although the importance of incorporating genetic diversity into the design of conservation measures is now well understood, less attention has been paid to the distinction between neutral (NGV) and adaptive (AGV) genetic variation. In this review, we first focus on the utility of NGV by examining the ways to quantify it, reviewing applications of NGV to infer ecological and evolutionary processes, and by exploring its utility in designing conservation measures for plant populations and species. Against this background, we then summarize the ways to identify and estimate AGV and discuss its potential use in plant conservation. After comparing NGV and AGV and considering their pros and cons in a conservation context, we conclude that there is an urgent need for a better understanding of AGV and its role in climate change adaptation. To date, however, there are only a few AGV studies on non-model plant species aimed at deciphering the genetic and genomic basis of complex trait variation. Therefore, conservation researchers and practitioners should keep utilizing NGV to develop relevant strategies for rare and endangered plant species until more estimates of AGV are available.
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26
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Abstract
Insects constitute vital components of ecosystems. There is alarming evidence for global declines in insect species diversity, abundance, and biomass caused by anthropogenic drivers such as habitat degradation or loss, agricultural practices, climate change, and environmental pollution. This raises important concerns about human food security and ecosystem functionality and calls for more research to assess insect population trends and identify threatened species and the causes of declines to inform conservation strategies. Analysis of genetic diversity is a powerful tool to address these goals, but so far animal conservation genetics research has focused strongly on endangered vertebrates, devoting less attention to invertebrates, such as insects, that constitute most biodiversity. Insects' shorter generation times and larger population sizes likely necessitate different analytical methods and management strategies. The availability of high-quality reference genome assemblies enables population genomics to address several key issues. These include precise inference of past demographic fluctuations and recent declines, measurement of genetic load levels, delineation of evolutionarily significant units and cryptic species, and analysis of genetic adaptation to stressors. This enables identification of populations that are particularly vulnerable to future threats, considering their potential to adapt and evolve. We review the application of population genomics to insect conservation and the outlook for averting insect declines.
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Affiliation(s)
- Matthew T Webster
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden;
| | - Alexis Beaurepaire
- Institute of Bee Health, Vetsuisse Faculty, University of Bern, Bern, Switzerland.,Agroscope, Swiss Bee Research Centre, Bern, Switzerland
| | - Peter Neumann
- Institute of Bee Health, Vetsuisse Faculty, University of Bern, Bern, Switzerland.,Agroscope, Swiss Bee Research Centre, Bern, Switzerland
| | - Eckart Stolle
- Leibniz Institute for the Analysis of Biodiversity Change, Museum Koenig, Bonn, Germany
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27
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Nocchi G, Wang J, Yang L, Ding J, Gao Y, Buggs RJA, Wang N. Genomic signals of local adaptation and hybridization in Asian white birch. Mol Ecol 2023; 32:595-612. [PMID: 36394364 DOI: 10.1111/mec.16788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 11/03/2022] [Accepted: 11/08/2022] [Indexed: 11/19/2022]
Abstract
Disentangling the numerous processes that affect patterns of genome-wide diversity in widespread tree species has important implications for taxonomy, conservation, and forestry. Here, we investigate the population genomic structure of Asian white birch (Betula platyphylla) in China and seek to explain it in terms of hybridization, demography and adaptation. We generate whole genome sequence data from 83 individuals across the species range in China. Combining this with an existing data set for 79 European and Russian white birches, we show a clear distinction between B. pendula and B. platyphylla, which have sometimes been lumped taxonomically. Genomic diversity of B. platyphylla in north-western China and Central Russia is affected greatly by hybridization with B. pendula. Excluding these hybridized populations, B. platyphylla in China has a linear distribution from north-eastern to south-western China, along the edge of the inland mountainous region. Within this distribution, three genetic clusters are found, which we model as long diverged with subsequent episodes of gene flow. Patterns of covariation between allele frequencies and environmental variables in B. platyphylla suggest the role of natural selection in the distribution of diversity at 7609 SNPs of which 3767 were significantly differentiated among the genetic clusters. The putative adaptive SNPs are distributed throughout the genome and span 1633 genic regions. Of these genic regions, 87 were previously identified as candidates for selective sweeps in Eurasian B. pendula. We use the 7609 environmentally associated SNPs to estimate the risk of nonadaptedness for each sequenced B. platyphylla individual under a scenario of future climate change, highlighting areas where populations may be under future threat from rising temperatures.
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Affiliation(s)
- Gabriele Nocchi
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.,Royal Botanic Gardens Kew, Richmond, Surrey, UK
| | - Jing Wang
- Key Laboratory for Bio-resources and Eco-environment, College of Life Science, Sichuan University, Chengdu, China
| | - Long Yang
- Agricultural Big-Data Research Centre and College of Plant Protection, Shandong Agricultural University, Tai'an, China
| | - Junyi Ding
- State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, College of Forestry, Shandong Agricultural University, Tai'an, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, College of Forestry, Shandong Agricultural University, Tai'an, China
| | - Ying Gao
- Agricultural Big-Data Research Centre and College of Plant Protection, Shandong Agricultural University, Tai'an, China
| | - Richard J A Buggs
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.,Royal Botanic Gardens Kew, Richmond, Surrey, UK
| | - Nian Wang
- State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, College of Forestry, Shandong Agricultural University, Tai'an, China.,Mountain Tai Forest Ecosystem Research Station of State Forestry and Grassland Administration, College of Forestry, Shandong Agricultural University, Tai'an, China.,State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai'an, China
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28
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Gallegos C, Hodgins KA, Monro K. Climate adaptation and vulnerability of foundation species in a global change hotspot. Mol Ecol 2023; 32:1990-2004. [PMID: 36645732 DOI: 10.1111/mec.16848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 01/05/2023] [Indexed: 01/17/2023]
Abstract
Climate change is altering species ranges, and relative abundances within ranges, as populations become differentially adapted and vulnerable to the climates they face. Understanding present species ranges, whether species harbour and exchange adaptive variants, and how variants are distributed across landscapes undergoing rapid change, is therefore crucial to predicting responses to future climates and informing conservation strategies. Such insights are nonetheless lacking for most species of conservation concern. We assess genomic patterns of neutral variation, climate adaptation and climate vulnerability (offsets in predicted distributions of putatively adaptive variants across present and future landscapes) for sister foundation species, the marine tubeworms Galeolaria caespitosa and Galeolaria gemineoa, in a sentinel region for climate change impacts. We find that species are genetically isolated despite uncovering sympatry in their ranges, show parallel and nonparallel signals of thermal adaptation on spatial scales smaller than gene flow across their ranges, and are predicted to face different risks of maladaptation under future temperatures across their ranges. Our findings have implications for understanding local adaptation in the face of gene flow, and generate spatially explicit predictions for climatic disruption of adaptation and species distributions in coastal ecosystems that could guide experimental validation and conservation planning.
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Affiliation(s)
- Cristóbal Gallegos
- School of Biological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Kathryn A Hodgins
- School of Biological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Keyne Monro
- School of Biological Sciences, Monash University, Melbourne, Victoria, Australia
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29
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Yuan S, Shi Y, Zhou BF, Liang YY, Chen XY, An QQ, Fan YR, Shen Z, Ingvarsson PK, Wang B. Genomic vulnerability to climate change in Quercus acutissima, a dominant tree species in East Asian deciduous forests. Mol Ecol 2023; 32:1639-1655. [PMID: 36626136 DOI: 10.1111/mec.16843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 12/30/2022] [Accepted: 01/05/2023] [Indexed: 01/11/2023]
Abstract
Understanding the evolutionary processes that shape the landscape of genetic variation and influence the response of species to future climate change is critical for biodiversity conservation. Here, we sampled 27 populations across the distribution range of a dominant forest tree, Quercus acutissima, in East Asia, and applied genome-wide analyses to track the evolutionary history and predict the fate of populations under future climate. We found two genetic groups (East and West) in Q. acutissima that diverged during Pliocene. We also found a heterogeneous landscape of genomic variation in this species, which may have been shaped by population demography and linked selections. Using genotype-environment association analyses, we identified climate-associated SNPs in a diverse set of genes and functional categories, indicating a model of polygenic adaptation in Q. acutissima. We further estimated three genetic offset metrics to quantify genomic vulnerability of this species to climate change due to the complex interplay between local adaptation and migration. We found that marginal populations are under higher risk of local extinction because of future climate change, and may not be able to track suitable habitats to maintain the gene-environment relationships observed under the current climate. We also detected higher reverse genetic offsets in northern China, indicating that genetic variation currently present in the whole range of Q. acutissima may not adapt to future climate conditions in this area. Overall, this study illustrates how evolutionary processes have shaped the landscape of genomic variation, and provides a comprehensive genome-wide view of climate maladaptation in Q. acutissima.
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Affiliation(s)
- Shuai Yuan
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
| | - Yong Shi
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
| | - Biao-Feng Zhou
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
| | - Yi-Ye Liang
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
| | - Xue-Yan Chen
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
| | - Qing-Qing An
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
| | - Yan-Ru Fan
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
| | - Zhao Shen
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
| | - Pär K Ingvarsson
- Department of Plant Biology, Linnean Center for Plant Biology, Uppsala BioCenter, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Baosheng Wang
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Guangdong Provincial Key Laboratory of Applied Botany, Guangzhou, China.,South China National Botanical Garden, Guangzhou, China
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30
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Wang Y, Zhang L, Zhou Y, Ma W, Li M, Guo P, Feng L, Fu C. Using landscape genomics to assess local adaptation and genomic vulnerability of a perennial herb Tetrastigma hemsleyanum (Vitaceae) in subtropical China. Front Genet 2023; 14:1150704. [PMID: 37144128 PMCID: PMC10151583 DOI: 10.3389/fgene.2023.1150704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 04/04/2023] [Indexed: 05/06/2023] Open
Abstract
Understanding adaptive genetic variation of plant populations and their vulnerabilities to climate change are critical to preserve biodiversity and subsequent management interventions. To this end, landscape genomics may represent a cost-efficient approach for investigating molecular signatures underlying local adaptation. Tetrastigma hemsleyanum is, in its native habitat, a widespread perennial herb of warm-temperate evergreen forest in subtropical China. Its ecological and medicinal values constitute a significant revenue for local human populations and ecosystem. Using 30,252 single nucleotide polymorphisms (SNPs) derived from reduced-representation genome sequencing in 156 samples from 24 sites, we conducted a landscape genomics study of the T. hemsleyanum to elucidate its genomic variation across multiple climate gradients and genomic vulnerability to future climate change. Multivariate methods identified that climatic variation explained more genomic variation than that of geographical distance, which implied that local adaptation to heterogeneous environment might represent an important source of genomic variation. Among these climate variables, winter precipitation was the strongest predictor of the contemporary genetic structure. F ST outlier tests and environment association analysis totally identified 275 candidate adaptive SNPs along the genetic and environmental gradients. SNP annotations of these putatively adaptive loci uncovered gene functions associated with modulating flowering time and regulating plant response to abiotic stresses, which have implications for breeding and other special agricultural aims on the basis of these selection signatures. Critically, modelling revealed that the high genomic vulnerability of our focal species via a mismatch between current and future genotype-environment relationships located in central-northern region of the T. hemsleyanum's range, where populations require proactive management efforts such as assistant adaptation to cope with ongoing climate change. Taken together, our results provide robust evidence of local climate adaption for T. hemsleyanum and further deepen our understanding of adaptation basis of herbs in subtropical China.
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Affiliation(s)
- Yihan Wang
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
| | - Lin Zhang
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
- College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou, China
| | - Yuchao Zhou
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
| | - Wenxin Ma
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
| | - Manyu Li
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
| | - Peng Guo
- College of Life Sciences, Henan Agricultural University, Zhengzhou, China
- Henan Engineering Research Center for Osmanthus Germplasm Innovation and Resource Utilization, Henan Agricultural University, Zhengzhou, China
- *Correspondence: Peng Guo, ; Li Feng,
| | - Li Feng
- School of Pharmacy, Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Peng Guo, ; Li Feng,
| | - Chengxin Fu
- Key Laboratory of Conservation Biology for Endangered Wildlife of the Ministry of Education, College of Life Sciences, Zhejiang University, Hangzhou, China
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31
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Lotterhos KE, Fitzpatrick MC, Blackmon H. Simulation Tests of Methods in Evolution, Ecology, and Systematics: Pitfalls, Progress, and Principles. ANNUAL REVIEW OF ECOLOGY, EVOLUTION, AND SYSTEMATICS 2022; 53:113-136. [PMID: 38107485 PMCID: PMC10723108 DOI: 10.1146/annurev-ecolsys-102320-093722] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Complex statistical methods are continuously developed across the fields of ecology, evolution, and systematics (EES). These fields, however, lack standardized principles for evaluating methods, which has led to high variability in the rigor with which methods are tested, a lack of clarity regarding their limitations, and the potential for misapplication. In this review, we illustrate the common pitfalls of method evaluations in EES, the advantages of testing methods with simulated data, and best practices for method evaluations. We highlight the difference between method evaluation and validation and review how simulations, when appropriately designed, can refine the domain in which a method can be reliably applied. We also discuss the strengths and limitations of different evaluation metrics. The potential for misapplication of methods would be greatly reduced if funding agencies, reviewers, and journals required principled method evaluation.
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Affiliation(s)
- Katie E Lotterhos
- Department of Marine and Environmental Sciences, Northeastern University, Nahant, Massachusetts, USA
| | - Matthew C Fitzpatrick
- Appalachian Lab, University of Maryland Center for Environmental Science, Frostburg, Maryland, USA
| | - Heath Blackmon
- Department of Biology, Texas A&M University, College Station, Texas, USA
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32
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Van Daele F, Honnay O, De Kort H. Genomic analyses point to a low evolutionary potential of prospective source populations for assisted migration in a forest herb. Evol Appl 2022; 15:1859-1874. [DOI: 10.1111/eva.13485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 08/13/2022] [Accepted: 09/17/2022] [Indexed: 11/26/2022] Open
Affiliation(s)
- Frederik Van Daele
- Department of Biology, Plant Conservation and Population Biology KU Leuven Leuven Belgium
| | - Olivier Honnay
- Department of Biology, Plant Conservation and Population Biology KU Leuven Leuven Belgium
| | - Hanne De Kort
- Department of Biology, Plant Conservation and Population Biology KU Leuven Leuven Belgium
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33
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DeSaix MG, George TL, Seglund AE, Spellman GM, Zavaleta ES, Ruegg KC. Forecasting climate change response in an alpine specialist songbird reveals the importance of considering novel climate. DIVERS DISTRIB 2022. [DOI: 10.1111/ddi.13628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
- Matthew G. DeSaix
- Department of Biology Colorado State University Fort Collins Colorado USA
| | - T. Luke George
- Department of Fish, Wildlife, and Conservation Biology Colorado State University Fort Collins Colorado USA
| | | | - Garth M. Spellman
- Department of Zoology Denver Museum of Nature and Science Denver Colorado USA
| | - Erika S. Zavaleta
- Department of Ecology and Evolutionary Biology University of California Santa Cruz California USA
| | - Kristen C. Ruegg
- Department of Biology Colorado State University Fort Collins Colorado USA
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34
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Tournebize R, Borner L, Manel S, Meynard CN, Vigouroux Y, Crouzillat D, Fournier C, Kassam M, Descombes P, Tranchant-Dubreuil C, Parrinello H, Kiwuka C, Sumirat U, Legnate H, Kambale JL, Sonké B, Mahinga JC, Musoli P, Janssens SB, Stoffelen P, de Kochko A, Poncet V. Ecological and genomic vulnerability to climate change across native populations of Robusta coffee (Coffea canephora). GLOBAL CHANGE BIOLOGY 2022; 28:4124-4142. [PMID: 35527235 DOI: 10.1111/gcb.16191] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 02/11/2022] [Accepted: 03/17/2022] [Indexed: 06/14/2023]
Abstract
The assessment of population vulnerability under climate change is crucial for planning conservation as well as for ensuring food security. Coffea canephora is, in its native habitat, an understorey tree that is mainly distributed in the lowland rainforests of tropical Africa. Also known as Robusta, its commercial value constitutes a significant revenue for many human populations in tropical countries. Comparing ecological and genomic vulnerabilities within the species' native range can provide valuable insights about habitat loss and the species' adaptive potential, allowing to identify genotypes that may act as a resource for varietal improvement. By applying species distribution models, we assessed ecological vulnerability as the decrease in climatic suitability under future climatic conditions from 492 occurrences. We then quantified genomic vulnerability (or risk of maladaptation) as the allelic composition change required to keep pace with predicted climate change. Genomic vulnerability was estimated from genomic environmental correlations throughout the native range. Suitable habitat was predicted to diminish to half its size by 2050, with populations near coastlines and around the Congo River being the most vulnerable. Whole-genome sequencing revealed 165 candidate SNPs associated with climatic adaptation in C. canephora, which were located in genes involved in plant response to biotic and abiotic stressors. Genomic vulnerability was higher for populations in West Africa and in the region at the border between DRC and Uganda. Despite an overall low correlation between genomic and ecological vulnerability at broad scale, these two components of vulnerability overlap spatially in ways that may become damaging. Genomic vulnerability was estimated to be 23% higher in populations where habitat will be lost in 2050 compared to regions where habitat will remain suitable. These results highlight how ecological and genomic vulnerabilities are relevant when planning on how to cope with climate change regarding an economically important species.
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Affiliation(s)
- Rémi Tournebize
- DIADE, CIRAD, IRD, Univ. Montpellier, Montpellier, France
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Leyli Borner
- CBGP, INRAE, CIRAD, IRD, Montpellier SupAgro, Univ Montpellier, Montpellier, France
- INRAE, Le Rheu, France
| | - Stéphanie Manel
- CEFE, CNRS, EPHE-PSL University, IRD, Univ Montpellier, Montpellier, France
| | - Christine N Meynard
- CBGP, INRAE, CIRAD, IRD, Montpellier SupAgro, Univ Montpellier, Montpellier, France
| | - Yves Vigouroux
- DIADE, CIRAD, IRD, Univ. Montpellier, Montpellier, France
| | | | - Coralie Fournier
- Nestlé Research, Société des Produits Nestlé S.A., EPFL Innovation Park, Lausanne, Switzerland
- School of Medicine, University of Geneva, Geneva, Switzerland
| | - Mohamed Kassam
- Nestlé Research, Société des Produits Nestlé S.A., EPFL Innovation Park, Lausanne, Switzerland
- Danone Nutricia Research, Singapore
| | - Patrick Descombes
- Nestlé Research, Société des Produits Nestlé S.A., EPFL Innovation Park, Lausanne, Switzerland
| | | | - Hugues Parrinello
- CNRS, INSERM, Univ. Montpellier, Montpellier, France
- Montpellier GenomiX, France Génomique, Montpellier, France
| | | | | | | | - Jean-Léon Kambale
- University of Kisangani, Kisangani, Democratic Republic of the Congo
| | | | | | | | - Steven B Janssens
- Meise Botanic Garden, Meise, Belgium
- Department of Biology, KU Leuven, Leuven, Belgium
| | | | | | - Valérie Poncet
- DIADE, CIRAD, IRD, Univ. Montpellier, Montpellier, France
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35
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Walters SJ, Robinson TP, Byrne M, Nevill P. Seed sourcing in the genomics era: Multispecies provenance delineation for current and future climates. Restor Ecol 2022. [DOI: 10.1111/rec.13718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Sheree J. Walters
- ARC Centre for Mine Site Restoration, School of Molecular and Life Sciences Curtin University Bentley WA 6102 Australia
| | - Todd P. Robinson
- School of Earth and Planetary Sciences Curtin University Bentley WA 6102 Australia
| | - Margaret Byrne
- Biodiversity and Conservation Science, Department of Biodiversity Conservation and Attractions, Locked Bag 104, Bentley Delivery Centre WA 6983 Australia
- School of Molecular and Life Sciences Curtin University Bentley WA 6102 Australia
| | - Paul Nevill
- ARC Centre for Mine Site Restoration, School of Molecular and Life Sciences Curtin University Bentley WA 6102 Australia
- Trace and Environmental DNA Laboratory, School of Molecular and Life Sciences Curtin University Bentley WA 6102 Australia
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Láruson ÁJ, Fitzpatrick MC, Keller SR, Haller BC, Lotterhos KE. Seeing the forest for the trees: Assessing genetic offset predictions from gradient forest. Evol Appl 2022; 15:403-416. [PMID: 35386401 PMCID: PMC8965365 DOI: 10.1111/eva.13354] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 01/22/2022] [Accepted: 01/30/2022] [Indexed: 12/02/2022] Open
Abstract
Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF-predicted environmental association of adapted alleles and a new environment (GF Offset) is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here, we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic "population genetic" model with a single environmentally adapted locus; and (3) a polygenic "quantitative genetic" model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation.
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Affiliation(s)
- Áki Jarl Láruson
- Department of Natural ResourcesCornell UniversityIthacaNew YorkUSA
| | - Matthew C. Fitzpatrick
- Appalachian LaboratoryUniversity of Maryland Center for Environmental ScienceFrostburgMarylandUSA
| | - Stephen R. Keller
- Department of Plant BiologyUniversity of VermontBurlingtonVermontUSA
| | | | - Katie E. Lotterhos
- Department of Marine and Environmental SciencesNortheastern University Marine Science CenterNahantMassachusettsUSA
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Genetic load: genomic estimates and applications in non-model animals. Nat Rev Genet 2022; 23:492-503. [PMID: 35136196 DOI: 10.1038/s41576-022-00448-x] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2022] [Indexed: 12/11/2022]
Abstract
Genetic variation, which is generated by mutation, recombination and gene flow, can reduce the mean fitness of a population, both now and in the future. This 'genetic load' has been estimated in a wide range of animal taxa using various approaches. Advances in genome sequencing and computational techniques now enable us to estimate the genetic load in populations and individuals without direct fitness estimates. Here, we review the classic and contemporary literature of genetic load. We describe approaches to quantify the genetic load in whole-genome sequence data based on evolutionary conservation and annotations. We show that splitting the load into its two components - the realized load (or expressed load) and the masked load (or inbreeding load) - can improve our understanding of the population genetics of deleterious mutations.
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Marques AJD, Hanson JO, Camacho-Sanchez M, Martínez-Solano I, Moritz C, Tarroso P, Velo-Antón G, Veríssimo A, Carvalho SB. Range-wide genomic scans and tests for selection identify non-neutral spatial patterns of genetic variation in a non-model amphibian species (Pelobates cultripes). CONSERV GENET 2022. [DOI: 10.1007/s10592-021-01425-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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de Aquino SO, Kiwuka C, Tournebize R, Gain C, Marraccini P, Mariac C, Bethune K, Couderc M, Cubry P, Andrade AC, Lepelley M, Darracq O, Crouzillat D, Anten N, Musoli P, Vigouroux Y, de Kochko A, Manel S, François O, Poncet V. Adaptive potential of
Coffea canephora
from Uganda in response to climate change. Mol Ecol 2022; 31:1800-1819. [DOI: 10.1111/mec.16360] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 11/12/2021] [Accepted: 01/06/2022] [Indexed: 11/28/2022]
Affiliation(s)
| | - Catherine Kiwuka
- NARO Kampala Uganda
- Centre for Crop Systems Analysis Wageningen Univ. Wageningen Netherlands
| | | | - Clément Gain
- U. Grenoble‐Alpes, TIMC‐IMAG, CNRS UMR 5525, Grenoble, France and LJK, Inria, CNRS UMR 5224 Grenoble France
| | | | - Cédric Mariac
- DIADE, Univ. Montpellier, CIRAD, IRD Montpellier France
| | - Kévin Bethune
- DIADE, Univ. Montpellier, CIRAD, IRD Montpellier France
| | - Marie Couderc
- DIADE, Univ. Montpellier, CIRAD, IRD Montpellier France
| | | | | | | | | | | | - Niels Anten
- Centre for Crop Systems Analysis Wageningen Univ. Wageningen Netherlands
| | | | | | | | - Stéphanie Manel
- CEFE, Univ Montpellier, CNRS, EPHE‐PSL University, IRD Montpellier France
| | - Olivier François
- U. Grenoble‐Alpes, TIMC‐IMAG, CNRS UMR 5525, Grenoble, France and LJK, Inria, CNRS UMR 5224 Grenoble France
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The evolutionary genomics of species' responses to climate change. Nat Ecol Evol 2021; 5:1350-1360. [PMID: 34373621 DOI: 10.1038/s41559-021-01526-9] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 07/05/2021] [Indexed: 02/06/2023]
Abstract
Climate change is a threat to biodiversity. One way that this threat manifests is through pronounced shifts in the geographical range of species over time. To predict these shifts, researchers have primarily used species distribution models. However, these models are based on assumptions of niche conservatism and do not consider evolutionary processes, potentially limiting their accuracy and value. To incorporate evolution into the prediction of species' responses to climate change, researchers have turned to landscape genomic data and examined information about local genetic adaptation using climate models. Although this is an important advancement, this approach currently does not include other evolutionary processes-such as gene flow, population dispersal and genomic load-that are critical for predicting the fate of species across the landscape. Here, we briefly review the current practices for the use of species distribution models and for incorporating local adaptation. We next discuss the rationale and theory for considering additional processes, reviewing how they can be incorporated into studies of species' responses to climate change. We summarize with a conceptual framework of how manifold layers of information can be combined to predict the potential response of specific populations to climate change. We illustrate all of the topics using an exemplar dataset and provide the source code as potential tutorials. This Perspective is intended to be a step towards a more comprehensive integration of population genomics with climate change science.
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