51
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Lancaster LT, Fuller ZL, Berger D, Barbour MA, Jentoft S, Wellenreuther M. Understanding climate change response in the age of genomics. J Anim Ecol 2022; 91:1056-1063. [PMID: 35668551 DOI: 10.1111/1365-2656.13711] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
| | - Zachary L Fuller
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - David Berger
- Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden
| | - Matthew A Barbour
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - Sissel Jentoft
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Oslo, Norway
| | - Maren Wellenreuther
- The New Zealand Institute for Plant and Food Research Limited, Nelson, New Zealand.,School of Biological Sciences, The University of Auckland, Auckland, New Zealand
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52
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Ye Z, Yuan J, Damgaard J, Berchi GM, Cianferoni F, Pintar MR, Olosutean H, Zhu X, Jiang K, Yang X, Fu S, Bu W. Climate Warming Since the Holocene Accelerates West-East Communication for the Eurasian Temperate Water Strider Species Aquarius paludum. Mol Biol Evol 2022; 39:6575397. [PMID: 35482393 PMCID: PMC9087890 DOI: 10.1093/molbev/msac089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Holocene climate warming has dramatically altered biological diversity and distributions. Recent human-induced emissions of greenhouse gases will exacerbate global warming and thus induce threats to cold-adapted taxa. However, the impacts of this major climate change on transcontinental temperate species are still poorly understood. Here, we generated extensive genomic datasets for a water strider, Aquarius paludum, which was sampled across its entire distribution in Eurasia and used these datasets in combination with ecological niche modeling (ENM) to elucidate the influence of the Holocene and future climate warming on its population structure and demographic history. We found that A. paludum consisted of two phylogeographic lineages that diverged in the middle Pleistocene, which resulted in a “west–east component” genetic pattern that was probably triggered by Central Asia-Mongoxin aridification and Pleistocene glaciations. The diverged western and eastern lineages had a second contact in the Holocene, which shaped a temporary hybrid zone located at the boundary of the arid–semiarid regions of China. Future predictions detected a potentially novel northern corridor to connect the western and eastern populations, indicating west–east gene flow would possibly continue to intensify under future warming climate conditions. Further integrating phylogeographic and ENM analyses of multiple Eurasian temperate taxa based on published studies reinforced our findings on the “west–east component” genetic pattern and the predicted future northern corridor for A. paludum. Our study provided a detailed paradigm from a phylogeographic perspective of how transcontinental temperate species differ from cold-adapted taxa in their response to climate warming.
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Affiliation(s)
- Zhen Ye
- Institute of Entomology, College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Juanjuan Yuan
- College of Life Sciences, Zaozhuang University, 1 Beian Road, Shandong 277000, China
| | - Jakob Damgaard
- Natural History Museum of Denmark, Zoological Museum, Universitetsparken 15, 2100 Copenhagen Ø, Denmark
| | - Gavril Marius Berchi
- Department of Taxonomy & Ecology, Faculty of Biology & Geology, Babeş-Bolyai University, 5-7 Clinicilor Street, 400015 Cluj-Napoca, Romania.,Institute for Advanced Environmental Research, West University of Timișoara, 4 Oituz Street, 300086 Timișoara, Romania
| | - Fabio Cianferoni
- Research Institute on Terrestrial Ecosystems, National Research Council of Italy, Via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italy.,Zoology, "La Specola", Natural History Museum, University of Florence, Via Romana 17, I-50125 Florence, Italy
| | - Matthew R Pintar
- Institute of Environment, Florida International University, Miami, FL, USA
| | - Horea Olosutean
- Applied Ecology Research Center, Lucian Blaga University of Sibiu, 5-7 Ion Ratiu Street, 550012 Sibiu, Romania
| | - Xiuxiu Zhu
- Institute of Entomology, College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Kun Jiang
- Institute of Entomology, College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Xin Yang
- School of Sports, Taiyuan University of Science and Technology, 66 Waliu Road, Shanxi 030024, China
| | - Siying Fu
- Institute of Entomology, College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Wenjun Bu
- Institute of Entomology, College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
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53
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Oomen RA, Hutchings JA. Genomic reaction norms inform predictions of plastic and adaptive responses to climate change. J Anim Ecol 2022; 91:1073-1087. [PMID: 35445402 PMCID: PMC9325537 DOI: 10.1111/1365-2656.13707] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 04/05/2022] [Indexed: 12/11/2022]
Abstract
Genomic reaction norms represent the range of gene expression phenotypes (usually mRNA transcript levels) expressed by a genotype along an environmental gradient. Reaction norms derived from common‐garden experiments are powerful approaches for disentangling plastic and adaptive responses to environmental change in natural populations. By treating gene expression as a phenotype in itself, genomic reaction norms represent invaluable tools for exploring causal mechanisms underlying organismal responses to climate change across multiple levels of biodiversity. Our goal is to provide the context, framework and motivation for applying genomic reaction norms to study the responses of natural populations to climate change. Here, we describe the utility of integrating genomics with common‐garden‐gradient experiments under a reaction norm analytical framework to answer fundamental questions about phenotypic plasticity, local adaptation, their interaction (i.e. genetic variation in plasticity) and future adaptive potential. An experimental and analytical framework for constructing and analysing genomic reaction norms is presented within the context of polygenic climate change responses of structured populations with gene flow. Intended for a broad eco‐evo readership, we first briefly review adaptation with gene flow and the importance of understanding the genomic basis and spatial scale of adaptation for conservation and management of structured populations under anthropogenic change. Then, within a high‐dimensional reaction norm framework, we illustrate how to distinguish plastic, differentially expressed (difference in reaction norm intercepts) and differentially plastic (difference in reaction norm slopes) genes, highlighting the areas of opportunity for applying these concepts. We conclude by discussing how genomic reaction norms can be incorporated into a holistic framework to understand the eco‐evolutionary dynamics of climate change responses from molecules to ecosystems. We aim to inspire researchers to integrate gene expression measurements into common‐garden experimental designs to investigate the genomics of climate change responses as sequencing costs become increasingly accessible.
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Affiliation(s)
- Rebekah A Oomen
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Oslo, Norway.,Centre for Coastal Research (CCR), University of Agder, Kristiansand, Norway
| | - Jeffrey A Hutchings
- Centre for Coastal Research (CCR), University of Agder, Kristiansand, Norway.,Department of Biology, Dalhousie University, Halifax, Nova Scotia, Canada.,Institute of Marine Research, Flødevigen Marine Research Station, His, Norway
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54
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Fournier-Level A, Taylor MA, Paril JF, Martínez-Berdeja A, Stitzer MC, Cooper MD, Roe JL, Wilczek AM, Schmitt J. Adaptive significance of flowering time variation across natural seasonal environments in Arabidopsis thaliana. THE NEW PHYTOLOGIST 2022; 234:719-734. [PMID: 35090191 DOI: 10.1111/nph.17999] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 01/04/2022] [Indexed: 06/14/2023]
Abstract
The relevance of flowering time variation and plasticity to climate adaptation requires a comprehensive empirical assessment. We investigated natural selection and the genetic architecture of flowering time in Arabidopsis through field experiments in Europe across multiple sites and seasons. We estimated selection for flowering time, plasticity and canalization. Loci associated with flowering time, plasticity and canalization by genome-wide association studies were tested for a geographic signature of climate adaptation. Selection favored early flowering and increased canalization, except at the northernmost site, but was rarely detected for plasticity. Genome-wide association studies revealed significant associations with flowering traits and supported a substantial polygenic inheritance. Alleles associated with late flowering, including functional FRIGIDA variants, were more common in regions experiencing high annual temperature variation. Flowering time plasticity to fall vs spring and summer environments was associated with GIGANTEA SUPPRESSOR 5, which promotes early flowering under decreasing day length and temperature. The finding that late flowering genotypes and alleles are associated with climate is evidence for past adaptation. Real-time phenotypic selection analysis, however, reveals pervasive contemporary selection for rapid flowering in agricultural settings across most of the species range. The response to this selection may involve genetic shifts in environmental cuing compared to the ancestral state.
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Affiliation(s)
| | - Mark A Taylor
- Department of Evolution and Ecology, University of California at Davis, Davis, CA, 95616, USA
| | - Jefferson F Paril
- School of BioSciences, The University of Melbourne, Parkville, Vic., 3010, Australia
| | | | - Michelle C Stitzer
- Department of Evolution and Ecology, University of California at Davis, Davis, CA, 95616, USA
| | - Martha D Cooper
- Department of Ecology and Evolution, Brown University, Providence, RI, 02912, USA
| | - Judith L Roe
- College of Arts and Sciences, Biology, Agricultural Science & Agribusiness, University of Maine at Presque Isle, Presque Isle, ME, 04769, USA
| | | | - Johanna Schmitt
- Department of Evolution and Ecology, University of California at Davis, Davis, CA, 95616, USA
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55
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VanWallendael A, Lowry DB, Hamilton JA. One hundred years into the study of ecotypes, new advances are being made through large-scale field experiments in perennial plant systems. CURRENT OPINION IN PLANT BIOLOGY 2022; 66:102152. [PMID: 35065527 DOI: 10.1016/j.pbi.2021.102152] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 10/31/2021] [Accepted: 11/03/2021] [Indexed: 06/14/2023]
Abstract
A hundred years after Turesson first clearly described how locally adaptive variation is distributed within species, plant biologists are making major breakthroughs in our understanding of mechanisms underlying adaptation from local populations to the scale of continents. Although the genetics of local adaptation has typically been studied in smaller reciprocal transplant experiments, it is now being evaluated with whole genomes in large-scale networks of common garden experiments with perennial switchgrass and poplar trees. These studies support the hypothesis that a complex combination of loci, both with and without adaptive trade-offs, underlies local adaptation and that hybridization and adaptive introgression play a key role in the evolution of these species. Future studies incorporating high-throughput phenotyping, gene expression, and modeling will be used to predict responses of these species to climate change.
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Affiliation(s)
- Acer VanWallendael
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA; Department of Energy Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI, 48824, USA; Program in Ecology, Evolution, and Behaviour, Michigan State University, East Lansing, MI, 48824, USA; Plant Resilience Institute, Michigan State University, East Lansing, MI, 48824, USA
| | - David B Lowry
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA; Department of Energy Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI, 48824, USA; Program in Ecology, Evolution, and Behaviour, Michigan State University, East Lansing, MI, 48824, USA; Plant Resilience Institute, Michigan State University, East Lansing, MI, 48824, USA.
| | - Jill A Hamilton
- Department of Ecosystem Science and Management, Pennsylvania State University, University Park, PA, 16801, USA
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56
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Nakamichi R, Kitada S, Kishino H. Exploratory analysis of multi‐trait coadaptations in light of population history. Ecol Evol 2022; 12:e8755. [PMID: 35342584 PMCID: PMC8933610 DOI: 10.1002/ece3.8755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 02/18/2022] [Indexed: 11/15/2022] Open
Abstract
During the process of range expansion, populations encounter a variety of environments. They respond to the local environments by modifying their mutually interacting traits. Common approaches of landscape analysis include first focusing on the genes that undergo diversifying selection or directional selection in response to environmental variation. To understand the whole history of populations, it is ideal to capture the history of their range expansion with reference to the series of surrounding environments and to infer the multitrait coadaptation. To this end, we propose a complementary approach; it is an exploratory analysis using up‐to‐date methods that integrate population genetic features and features of selection on multiple traits. First, we conduct correspondence analysis of site frequency spectra, traits, and environments with auxiliary information of population‐specific fixation index (FST). This visualizes the structure and the ages of populations and helps infer the history of range expansion, encountered environmental changes, and selection on multiple traits. Next, we further investigate the inferred history using an admixture graph that describes the population split and admixture. Finally, principal component analysis of the selection on edge‐by‐trait (SET) matrix identifies multitrait coadaptation and the associated edges of the admixture graph. We introduce a newly defined factor loadings of environmental variables in order to identify the environmental factors that caused the coadaptation. A numerical simulation of one‐dimensional stepping‐stone population expansion showed that the exploratory analysis reconstructed the pattern of the environmental selection that was missed by analysis of individual traits. Analysis of a public dataset of natural populations of black cottonwood in northwestern America identified the first principal component (PC) coadaptation of photosynthesis‐ vs growth‐related traits responding to the geographical clines of temperature and day length. The second PC coadaptation of volume‐related traits suggested that soil condition was a limiting factor for aboveground environmental selection.
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Affiliation(s)
| | - Shuichi Kitada
- Tokyo University of Marine Science and Technology Tokyo Japan
| | - Hirohisa Kishino
- Graduate School of Agriculture and Life Sciences The University of Tokyo Tokyo Japan
- The Research Institute of Evolutionary Biology Tokyo Japan
- AI/Data Science Social Implementation Laboratory Chuo University Tokyo Japan
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57
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Brown JI, Harrigan RJ, Lavretsky P. Evolutionary and Ecological Drivers of Local Adaptation and Speciation in a North American Avian Species Complex. Mol Ecol 2022; 31:2578-2593. [PMID: 35263000 DOI: 10.1111/mec.16423] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 01/31/2022] [Accepted: 02/28/2022] [Indexed: 11/26/2022]
Abstract
Throughout the speciation process, genomic divergence can be differentially impacted by selective pressures, as well as gene flow and genetic drift. Disentangling the effects of these evolutionary mechanisms remains challenging, especially for non-model organisms. Accounting for complex evolutionary histories and contemporary population structure often requires sufficient sample sizes, for which the expense of full genomes remains prohibitive. Here, we demonstrate the utility of partial-genome sequence data for range-wide samples to shed light into the divergence process of two closely related ducks, the Mexican duck (Anas diazi) and mallard (A. platyrhynchos). We determine the role of selective and neutral processes during speciation of Mexican ducks by integrating evolutionary and demographic modelling with genotype-environment and genotype-phenotype association testing. First, evolutionary models and demographic analyses support the hypothesis that Mexican ducks originally diverged ~300,000 years ago in a climate refugia arising during a glacial period in in a southwestern North America, and that subsequent environmental selective pressures played a key role in divergence. Mexican ducks then showed cyclical demographic patterns that likely reflected repeated range expansions and contractions, along with bouts of gene flow with mallards during glacial cycles. Finally, we provide evidence that sexual selection acted on several phenotypic traits as a co-evolutionary process, facilitating the development of reproductive barriers that initially arose due to strong ecological selection. More broadly, this work reveals that the genomic and phenotypic patterns observed across species complexes are the result of myriad factors that contribute in dynamic ways to the evolutionary trajectories of a lineage.
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Affiliation(s)
- Joshua I Brown
- Department of Biological Sciences, University of Texas at El Paso, El Paso, TX, 79668, USA
| | - Ryan J Harrigan
- Center for Tropical Research, University of California, Los Angeles, La Kretz Hall, Suite 300, Los Angeles, CA, 90095, U.S.A
| | - Philip Lavretsky
- Department of Biological Sciences, University of Texas at El Paso, El Paso, TX, 79668, USA
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58
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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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59
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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] [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 Resources Cornell University Ithaca NY 14853 USA
| | - Matthew C. Fitzpatrick
- Appalachian Laboratory University of Maryland Center for Environmental Science Frostburg Maryland 21532 USA
| | - Stephen R. Keller
- Department of Plant Biology University of Vermont Burlington Vermont 05405 USA
| | - Benjamin C. Haller
- Department of Computational Biology Cornell University Ithaca NY 14853 USA
| | - Katie E. Lotterhos
- Department of Marine and Environmental Sciences Northeastern University Marine Science Center Nahant MA 01908 USA
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60
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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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61
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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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62
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Filipe JC, Rymer PD, Byrne M, Hardy G, Mazanec R, Ahrens CW. Signatures of natural selection in a foundation tree along Mediterranean climatic gradients. Mol Ecol 2022; 31:1735-1752. [PMID: 35038378 PMCID: PMC9305101 DOI: 10.1111/mec.16351] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 01/04/2022] [Accepted: 01/10/2022] [Indexed: 11/30/2022]
Abstract
Temperature and precipitation regimes are rapidly changing, resulting in forest dieback and extinction events, particularly in Mediterranean‐type climates (MTC). Forest management that enhance forests’ resilience is urgently required, however adaptation to climates in heterogeneous landscapes with multiple selection pressures is complex. For widespread trees in MTC we hypothesized that: patterns of local adaptation are associated with climate; precipitation is a stronger factor of adaptation than temperature; functionally related genes show similar signatures of adaptation; and adaptive variants are independently sorting across the landscape. We sampled 28 populations across the geographic distribution of Eucalyptus marginata (jarrah), in South‐west Western Australia, and obtained 13,534 independent single nucleotide polymorphic (SNP) markers across the genome. Three genotype‐association analyses that employ different ways of correcting population structure were used to identify putatively adapted SNPs associated with independent climate variables. While overall levels of population differentiation were low (FST = 0.04), environmental association analyses found a total of 2336 unique SNPs associated with temperature and precipitation variables, with 1440 SNPs annotated to genic regions. Considerable allelic turnover was identified for SNPs associated with temperature seasonality and mean precipitation of the warmest quarter, suggesting that both temperature and precipitation are important factors in adaptation. SNPs with similar gene functions had analogous allelic turnover along climate gradients, while SNPs among temperature and precipitation variables had uncorrelated patterns of adaptation. These contrasting patterns provide evidence that there may be standing genomic variation adapted to current climate gradients, providing the basis for adaptive management strategies to bolster forest resilience in the future.
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Affiliation(s)
- J C Filipe
- Centre for Terrestrial Ecosystem Science and Sustainability, Harry Butler Institute, Murdoch University
| | - P D Rymer
- Hawkesbury Institute for the Environment, Western Sydney University
| | - M Byrne
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions
| | - G Hardy
- Centre for Terrestrial Ecosystem Science and Sustainability, Harry Butler Institute, Murdoch University
| | - R Mazanec
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions
| | - C W Ahrens
- Hawkesbury Institute for the Environment, Western Sydney University
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63
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Perry A, Wachowiak W, Beaton J, Iason G, Cottrell J, Cavers S. Identifying and testing marker‐trait associations for growth and phenology in three pine species: implications for genomic prediction. Evol Appl 2022; 15:330-348. [PMID: 35233251 PMCID: PMC8867712 DOI: 10.1111/eva.13345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 12/08/2021] [Accepted: 12/09/2021] [Indexed: 12/02/2022] Open
Abstract
In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker–trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 single nucleotide polymorphisms (SNPs) from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034–0.037) and negatively associated with budburst timing at the other (YA: r = −0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments.
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Affiliation(s)
- Annika Perry
- UK Centre for Ecology & Hydrology Edinburgh Penicuik Midlothian EH26 0QB UK
| | - Witold Wachowiak
- Institute of Environmental Biology Faculty of Biology Adam Mickiewicz University Poznań Poland
| | - Joan Beaton
- James Hutton Institute Craigiebuckler, Aberdeen AB15 8QH UK
| | - Glenn Iason
- James Hutton Institute Craigiebuckler, Aberdeen AB15 8QH UK
| | - Joan Cottrell
- Northern Research Station, Forest Research Roslin EH25 9SY UK
| | - Stephen Cavers
- UK Centre for Ecology & Hydrology Edinburgh Penicuik Midlothian EH26 0QB UK
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64
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Willi Y, Kristensen TN, Sgrò CM, Weeks AR, Ørsted M, Hoffmann AA. Conservation genetics as a management tool: The five best-supported paradigms to assist the management of threatened species. Proc Natl Acad Sci U S A 2022; 119:e2105076119. [PMID: 34930821 PMCID: PMC8740573 DOI: 10.1073/pnas.2105076119] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
About 50 y ago, Crow and Kimura [An Introduction to Population Genetics Theory (1970)] and Ohta and Kimura [Genet. Res. 22, 201-204 (1973)] laid the foundations of conservation genetics by predicting the relationship between population size and genetic marker diversity. This work sparked an enormous research effort investigating the importance of population dynamics, in particular small population size, for population mean performance, population viability, and evolutionary potential. In light of a recent perspective [J. C. Teixeira, C. D. Huber, Proc. Natl. Acad. Sci. U.S.A. 118, 10 (2021)] that challenges some fundamental assumptions in conservation genetics, it is timely to summarize what the field has achieved, what robust patterns have emerged, and worthwhile future research directions. We consider theory and methodological breakthroughs that have helped management, and we outline some fundamental and applied challenges for conservation genetics.
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Affiliation(s)
- Yvonne Willi
- Department of Environmental Sciences, University of Basel, 4056 Basel, Switzerland
| | - Torsten N Kristensen
- Department of Chemistry and Bioscience, Aalborg University, Aalborg 9220, Denmark
| | - Carla M Sgrò
- School of Biological Sciences, Monash University, Melbourne, VIC 3800, Australia
| | - Andrew R Weeks
- School of BioSciences, Bio21 Institute, University of Melbourne, Melbourne, VIC 3010, Australia
- Cesar Australia, Brunswick, VIC 3056, Australia
| | - Michael Ørsted
- Department of Chemistry and Bioscience, Aalborg University, Aalborg 9220, Denmark
- Department of Biology, Aarhus University, Aarhus 8000, Denmark
| | - Ary A Hoffmann
- School of BioSciences, Bio21 Institute, University of Melbourne, Melbourne, VIC 3010, Australia;
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65
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Feng L, Du FK. Landscape Genomics in Tree Conservation Under a Changing Environment. FRONTIERS IN PLANT SCIENCE 2022; 13:822217. [PMID: 35283901 PMCID: PMC8908315 DOI: 10.3389/fpls.2022.822217] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 01/10/2022] [Indexed: 05/11/2023]
Abstract
Understanding the genetic basis of how species respond to changing environments is essential to the conservation of species. However, the molecular mechanisms of adaptation remain largely unknown for long-lived tree species which always have large population sizes, long generation time, and extensive gene flow. Recent advances in landscape genomics can reveal the signals of adaptive selection linking genetic variations and landscape characteristics and therefore have created novel insights into tree conservation strategies. In this review article, we first summarized the methods of landscape genomics used in tree conservation and elucidated the advantages and disadvantages of these methods. We then highlighted the newly developed method "Risk of Non-adaptedness," which can predict the genetic offset or genomic vulnerability of species via allele frequency change under multiple scenarios of climate change. Finally, we provided prospects concerning how our introduced approaches of landscape genomics can assist policymaking and improve the existing conservation strategies for tree species under the ongoing global changes.
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Affiliation(s)
- Li Feng
- School of Pharmacy, Xi’an Jiaotong University, Xi’an, China
| | - Fang K. Du
- School of Ecology and Nature Conservation, Beijing Forestry University, Beijing, China
- *Correspondence: Fang K. Du,
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66
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Faske TM, Agneray AC, Jahner JP, Sheta LM, Leger EA, Parchman TL. Genomic and common garden approaches yield complementary results for quantifying environmental drivers of local adaptation in rubber rabbitbrush, a foundational Great Basin shrub. Evol Appl 2021; 14:2881-2900. [PMID: 34950235 PMCID: PMC8674890 DOI: 10.1111/eva.13323] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/17/2021] [Accepted: 11/03/2021] [Indexed: 01/21/2023] Open
Abstract
The spatial structure of genomic and phenotypic variation across populations reflects historical and demographic processes as well as evolution via natural selection. Characterizing such variation can provide an important perspective for understanding the evolutionary consequences of changing climate and for guiding ecological restoration. While evidence for local adaptation has been traditionally evaluated using phenotypic data, modern methods for generating and analyzing landscape genomic data can directly quantify local adaptation by associating allelic variation with environmental variation. Here, we analyze both genomic and phenotypic variation of rubber rabbitbrush (Ericameria nauseosa), a foundational shrub species of western North America. To quantify landscape genomic structure and provide perspective on patterns of local adaptation, we generated reduced representation sequencing data for 17 wild populations (222 individuals; 38,615 loci) spanning a range of environmental conditions. Population genetic analyses illustrated pronounced landscape genomic structure jointly shaped by geography and environment. Genetic-environment association (GEA) analyses using both redundancy analysis (RDA) and a machine-learning approach (Gradient Forest) indicated environmental variables (precipitation seasonality, slope, aspect, elevation, and annual precipitation) influenced spatial genomic structure and were correlated with allele frequency shifts indicative of local adaptation at a consistent set of genomic regions. We compared our GEA-based inference of local adaptation with phenotypic data collected by growing seeds from each population in a greenhouse common garden. Population differentiation in seed weight, emergence, and seedling traits was associated with environmental variables (e.g., precipitation seasonality) that were also implicated in GEA analyses, suggesting complementary conclusions about the drivers of local adaptation across different methods and data sources. Our results provide a baseline understanding of spatial genomic structure for E. nauseosa across the western Great Basin and illustrate the utility of GEA analyses for detecting the environmental causes and genetic signatures of local adaptation in a widely distributed plant species of restoration significance.
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Affiliation(s)
- Trevor M. Faske
- Department of BiologyUniversity of NevadaRenoNevadaUSA
- Ecology, Evolution, and Conservation Biology ProgramUniversity of NevadaRenoNevadaUSA
| | - Alison C. Agneray
- Department of BiologyUniversity of NevadaRenoNevadaUSA
- Ecology, Evolution, and Conservation Biology ProgramUniversity of NevadaRenoNevadaUSA
| | | | - Lana M. Sheta
- Department of BiologyUniversity of NevadaRenoNevadaUSA
| | - Elizabeth A. Leger
- Department of BiologyUniversity of NevadaRenoNevadaUSA
- Ecology, Evolution, and Conservation Biology ProgramUniversity of NevadaRenoNevadaUSA
| | - Thomas L. Parchman
- Department of BiologyUniversity of NevadaRenoNevadaUSA
- Ecology, Evolution, and Conservation Biology ProgramUniversity of NevadaRenoNevadaUSA
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67
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New developments in the field of genomic technologies and their relevance to conservation management. CONSERV GENET 2021. [DOI: 10.1007/s10592-021-01415-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
AbstractRecent technological advances in the field of genomics offer conservation managers and practitioners new tools to explore for conservation applications. Many of these tools are well developed and used by other life science fields, while others are still in development. Considering these technological possibilities, choosing the right tool(s) from the toolbox is crucial and can pose a challenging task. With this in mind, we strive to inspire, inform and illuminate managers and practitioners on how conservation efforts can benefit from the current genomic and biotechnological revolution. With inspirational case studies we show how new technologies can help resolve some of the main conservation challenges, while also informing how implementable the different technologies are. We here focus specifically on small population management, highlight the potential for genetic rescue, and discuss the opportunities in the field of gene editing to help with adaptation to changing environments. In addition, we delineate potential applications of gene drives for controlling invasive species. We illuminate that the genomic toolbox offers added benefit to conservation efforts, but also comes with limitations for the use of these novel emerging techniques.
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68
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Buckley LB, Kingsolver JG. Evolution of Thermal Sensitivity in Changing and Variable Climates. ANNUAL REVIEW OF ECOLOGY, EVOLUTION, AND SYSTEMATICS 2021. [DOI: 10.1146/annurev-ecolsys-011521-102856] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Evolutionary adaptation to temperature and climate depends on both the extent to which organisms experience spatial and temporal environmental variation (exposure) and how responsive they are to the environmental variation (sensitivity). Theoretical models and experiments suggesting substantial potential for thermal adaptation have largely omitted realistic environmental variation. Environmental variation can drive fluctuations in selection that slow adaptive evolution. We review how carefully filtering environmental conditions based on how organisms experience their environment and further considering organismal sensitivity can improve predictions of thermal adaptation. We contrast taxa differing in exposure and sensitivity. Plasticity can increase the rate of evolutionary adaptation in taxa exposed to pronounced environmental variation. However, forms of plasticity that severely limit exposure, such as behavioral thermoregulation and phenological shifts, can hinder thermal adaptation. Despite examples of rapid thermal adaptation, experimental studies often reveal evolutionary constraints. Further investigating these constraints and issues of timescale and thermal history are needed to predict evolutionary adaptation and, consequently, population persistence in changing and variable environments.
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Affiliation(s)
- Lauren B. Buckley
- Department of Biology, University of Washington, Seattle, Washington 98195‐1800, USA
| | - Joel G. Kingsolver
- Department of Biology, University of North Carolina, Chapel Hill, North Carolina 27599, USA
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69
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Boulanger E, Benestan L, Guerin PE, Dalongeville A, Mouillot D, Manel S. Climate differently influences the genomic patterns of two sympatric marine fish species. J Anim Ecol 2021; 91:1180-1195. [PMID: 34716929 DOI: 10.1111/1365-2656.13623] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 10/21/2021] [Indexed: 12/19/2022]
Abstract
Climate influences population genetic variation in marine species. Capturing these impacts remains challenging for marine fishes which disperse over large geographical scales spanning steep environmental gradients. It requires the extensive spatial sampling of individuals or populations, representative of seascape heterogeneity, combined with a set of highly informative molecular markers capable of revealing climatic-associated genetic variations. We explored how space, dispersal and environment shape the genomic patterns of two sympatric fish species in the Mediterranean Sea, which ranks among the oceanic basins most affected by climate change and human pressure. We hypothesized that the population structure and climate-associated genomic signatures of selection would be stronger in the less mobile species, as restricted gene flow tends to facilitate the fixation of locally adapted alleles. To test our hypothesis, we genotyped two species with contrasting dispersal abilities: the white seabream Diplodus sargus and the striped red mullet Mullus surmuletus. We collected 823 individuals and used genotyping by sequencing (GBS) to detect 8,206 single nucleotide polymorphisms (SNPs) for the seabream and 2,794 for the mullet. For each species, we identified highly differentiated genomic regions (i.e. outliers) and disentangled the relative contribution of space, dispersal and environmental variables (climate, marine primary productivity) on the outliers' genetic structure to test the prevalence of gene flow and local adaptation. We observed contrasting patterns of gene flow and adaptive genetic variation between the two species. The seabream showed a distinct Alboran sea population and panmixia across the Mediterranean Sea. The mullet revealed additional differentiation within the Mediterranean Sea that was significantly correlated to summer and winter temperatures, as well as marine primary productivity. Functional annotation of the climate-associated outlier SNPs then identified candidate genes involved in heat tolerance that could be examined to further predict species' responses to climate change. Our results illustrate the key steps of a comparative seascape genomics study aiming to unravel the evolutionary processes at play in marine species, to better anticipate their response to climate change. Defining population adaptation capacities and environmental niches can then serve to incorporate evolutionary processes into species conservation planning.
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Affiliation(s)
- Emilie Boulanger
- CEFE, University of Montpellier, CNRS, EPHE-PSL University, IRD, Montpellier, France.,MARBEC, University of Montpellier, CNRS, Ifremer, IRD, Montpellier, France
| | - Laura Benestan
- CEFE, University of Montpellier, CNRS, EPHE-PSL University, IRD, Montpellier, France
| | - Pierre-Edouard Guerin
- CEFE, University of Montpellier, CNRS, EPHE-PSL University, IRD, Montpellier, France
| | | | - David Mouillot
- MARBEC, University of Montpellier, CNRS, Ifremer, IRD, Montpellier, France.,Institut Universitaire de France, Paris, France
| | - Stéphanie Manel
- CEFE, University of Montpellier, CNRS, EPHE-PSL University, IRD, Montpellier, France
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70
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Kebaïli C, Sherpa S, Rioux D, Després L. Demographic inferences and climatic niche modelling shed light on the evolutionary history of the emblematic cold-adapted Apollo butterfly at regional scale. Mol Ecol 2021; 31:448-466. [PMID: 34687582 DOI: 10.1111/mec.16244] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/01/2021] [Accepted: 10/08/2021] [Indexed: 11/29/2022]
Abstract
Cold-adapted species escape climate warming by latitudinal and/or altitudinal range shifts, and currently occur in Southern Europe in isolated mountain ranges within "sky islands". Here, we studied the genetic structure of the Apollo butterfly in five such sky islands (above 1,000 m) in France, and infer its demographic history since the last interglacial, using single nucleotide polymorphisms (ddRADseq SNPs). The Auvergne and Alps populations show strong genetic differentiation but not alpine massifs, although separated by deep valleys. Combining three complementary demographic inference methods and species distribution models (SDMs) we show that the LIG period was highly unfavourable for Apollo that probably survived in small population in the highest summits of Auvergne. The population shifted downslope and expanded eastward between LIG and LGM throughout the large climatically suitable Rhône valley between the glaciated summits of Auvergne and Alps. The Auvergne and Alps populations started diverging before the LGM but remained largely connected till the mid-Holocene. Population decline in Auvergne was more gradual but started before (~7 kya vs. 800 ya), and was much stronger with current population size ten times lower than in the Alps. In the Alps, the low genetic structure and limited evidence for isolation by distance suggest a nonequilibrium metapopulation functioning. The core Apollo population experienced cycles of contraction-expansion with climate fluctuations with largely interconnected populations overtime according to a "metapopulation-pulsar" functioning. This study demonstrates the power of combining demographic inferences and SDMs to determine past and future evolutionary trajectories of an endangered species at a regional scale.
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Affiliation(s)
- Caroline Kebaïli
- Laboratoire d'Ecologie Alpine (LECA), CNRS, Université Grenoble Alpes, Grenoble, France.,Parc Naturel Régional du Haut Jura, Lajoux, France
| | - Stéphanie Sherpa
- Laboratoire d'Ecologie Alpine (LECA), CNRS, Université Grenoble Alpes, Grenoble, France
| | - Delphine Rioux
- Laboratoire d'Ecologie Alpine (LECA), CNRS, Université Grenoble Alpes, Grenoble, France
| | - Laurence Després
- Laboratoire d'Ecologie Alpine (LECA), CNRS, Université Grenoble Alpes, Grenoble, France
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71
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Layton KKS, Bradbury IR. Harnessing the power of multi-omics data for predicting climate change response. J Anim Ecol 2021; 91:1064-1072. [PMID: 34679193 DOI: 10.1111/1365-2656.13619] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 10/11/2021] [Indexed: 01/19/2023]
Abstract
Predicting how species will respond to future climate change is of central importance in the midst of the global biodiversity crisis, and recent work has demonstrated the utility of population genomics for improving these predictions. Here, we suggest a broadening of the approach to include other types of genomic variants that play an important role in adaptation, like structural (e.g. copy number variants) and epigenetic variants (e.g. DNA methylation). These data could provide additional power for forecasting response, especially in weakly structured or panmictic species. Incorporating structural and epigenetic variation into estimates of climate change vulnerability, or maladaptation, may not only improve prediction power but also provide insight into the molecular mechanisms underpinning species' response to climate change.
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Affiliation(s)
- Kara K S Layton
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
| | - Ian R Bradbury
- Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John's, Canada
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72
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Capblancq T, Forester BR. Redundancy analysis: A Swiss Army Knife for landscape genomics. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13722] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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73
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Sofi IA, Rashid I, Lone JY, Tyagi S, Reshi ZA, Mir RR. Genetic diversity may help evolutionary rescue in a clonal endemic plant species of Western Himalaya. Sci Rep 2021; 11:19595. [PMID: 34599214 PMCID: PMC8486807 DOI: 10.1038/s41598-021-98648-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 08/25/2021] [Indexed: 02/08/2023] Open
Abstract
Habitat loss due to climate change may cause the extinction of the clonal species with a limited distribution range. Thus, determining the genetic diversity required for adaptability by these species in sensitive ecosystems can help infer the chances of their survival and spread in changing climate. We studied the genetic diversity and population structure of Sambucus wightiana-a clonal endemic plant species of the Himalayan region for understanding its possible survival chances in anticipated climate change. Eight polymorphic microsatellite markers were used to study the allelic/genetic diversity and population structure. In addition, ITS1-ITS4 Sanger sequencing was used for phylogeny and SNP detection. A total number of 73 alleles were scored for 37 genotypes at 17 loci for 8 SSRs markers. The population structural analysis using the SSR marker data led to identifying two sub-populations in our collection of 37 S. wightiana genotypes, with 11 genotypes having mixed ancestry. The ITS sequence data show a specific allele in higher frequency in a particular sub-population, indicating variation in different S. wightiana accessions at the sequence level. The genotypic data of SSR markers and trait data of 11 traits of S. wightiana, when analyzed together, revealed five significant Marker-Trait Associations (MTAs) through Single Marker Analysis (SMA) or regression analysis. Most of the SSR markers were found to be associated with more than one trait, indicating the usefulness of these markers for working out marker-trait associations. Moderate to high genetic diversity observed in the present study may provide insurance against climate change to S. wightiana and help its further spread.
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Affiliation(s)
- Irshad Ahmad Sofi
- grid.412997.00000 0001 2294 5433Department of Botany, University of Kashmir, Srinagar, Jammu and Kashmir 190006 India
| | - Irfan Rashid
- grid.412997.00000 0001 2294 5433Department of Botany, University of Kashmir, Srinagar, Jammu and Kashmir 190006 India
| | - Javaid Yousuf Lone
- grid.412997.00000 0001 2294 5433Department of Botany, University of Kashmir, Srinagar, Jammu and Kashmir 190006 India
| | - Sandhya Tyagi
- grid.418196.30000 0001 2172 0814Department of Plant Physiology, Indian Agricultural Research Institute, New Delhi, Delhi 110012 India
| | - Zafar A. Reshi
- grid.412997.00000 0001 2294 5433Department of Botany, University of Kashmir, Srinagar, Jammu and Kashmir 190006 India
| | - Reyazul Rouf Mir
- grid.444725.40000 0004 0500 6225Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura Campus, Sopore, Jammu and Kashmir 193201 India
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74
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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: 42] [Impact Index Per Article: 14.0] [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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75
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Couper LI, Farner JE, Caldwell JM, Childs ML, Harris MJ, Kirk DG, Nova N, Shocket M, Skinner EB, Uricchio LH, Exposito-Alonso M, Mordecai EA. How will mosquitoes adapt to climate warming? eLife 2021; 10:69630. [PMID: 34402424 PMCID: PMC8370766 DOI: 10.7554/elife.69630] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 07/13/2021] [Indexed: 12/14/2022] Open
Abstract
The potential for adaptive evolution to enable species persistence under a changing climate is one of the most important questions for understanding impacts of future climate change. Climate adaptation may be particularly likely for short-lived ectotherms, including many pest, pathogen, and vector species. For these taxa, estimating climate adaptive potential is critical for accurate predictive modeling and public health preparedness. Here, we demonstrate how a simple theoretical framework used in conservation biology-evolutionary rescue models-can be used to investigate the potential for climate adaptation in these taxa, using mosquito thermal adaptation as a focal case. Synthesizing current evidence, we find that short mosquito generation times, high population growth rates, and strong temperature-imposed selection favor thermal adaptation. However, knowledge gaps about the extent of phenotypic and genotypic variation in thermal tolerance within mosquito populations, the environmental sensitivity of selection, and the role of phenotypic plasticity constrain our ability to make more precise estimates. We describe how common garden and selection experiments can be used to fill these data gaps. Lastly, we investigate the consequences of mosquito climate adaptation on disease transmission using Aedes aegypti-transmitted dengue virus in Northern Brazil as a case study. The approach outlined here can be applied to any disease vector or pest species and type of environmental change.
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Affiliation(s)
- Lisa I Couper
- Department of Biology, Stanford University, Stanford, United States
| | | | - Jamie M Caldwell
- Department of Biology, Stanford University, Stanford, United States.,Department of Biology, University of Hawaii at Manoa, Honolulu, United States
| | - Marissa L Childs
- Emmett Interdisciplinary Program in Environment and Resources, Stanford University, Stanford, United States
| | - Mallory J Harris
- Department of Biology, Stanford University, Stanford, United States
| | - Devin G Kirk
- Department of Biology, Stanford University, Stanford, United States.,Department of Zoology, University of Toronto, Toronto, Canada
| | - Nicole Nova
- Department of Biology, Stanford University, Stanford, United States
| | - Marta Shocket
- Department of Biology, Stanford University, Stanford, United States.,Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, United States
| | - Eloise B Skinner
- Department of Biology, Stanford University, Stanford, United States.,Environmental Futures Research Institute, Griffith University, Brisbane, Australia
| | - Lawrence H Uricchio
- Department of Integrative Biology, University of California, Berkeley, Berkeley, United States
| | - Moises Exposito-Alonso
- Department of Biology, Stanford University, Stanford, United States.,Department of Plant Biology, Carnegie Institution for Science, Stanford, United States
| | - Erin A Mordecai
- Department of Biology, Stanford University, Stanford, United States
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76
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Gompert Z, Springer A, Brady M, Chaturvedi S, Lucas LK. Genomic time-series data show that gene flow maintains high genetic diversity despite substantial genetic drift in a butterfly species. Mol Ecol 2021; 30:4991-5008. [PMID: 34379852 DOI: 10.1111/mec.16111] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 07/09/2021] [Accepted: 07/19/2021] [Indexed: 11/29/2022]
Abstract
Effective population size affects the efficacy of selection, rate of evolution by drift, and neutral diversity levels. When species are subdivided into multiple populations connected by gene flow, evolutionary processes can depend on global or local effective population sizes. Theory predicts that high levels of diversity might be maintained by gene flow, even very low levels of gene flow, consistent with species long-term effective population size, but tests of this idea are mostly lacking. Here, we show that Lycaeides buttery populations maintain low contemporary (variance) effective population sizes (e.g., ~200 individuals) and thus evolve rapidly by genetic drift. In contrast, populations harbored high levels of genetic diversity consistent with an effective population size several orders of magnitude larger. We hypothesized that the differences in the magnitude and variability of contemporary versus long-term effective population sizes were caused by gene flow of sufficient magnitude to maintain diversity but only subtly affect evolution on generational time scales. Consistent with this hypothesis, we detected low but non-trivial gene flow among populations. Furthermore, using short-term population-genomic time-series data, we documented patterns consistent with predictions from this hypothesis, including a weak but detectable excess of evolutionary change in the direction of the mean (migrant gene pool) allele frequencies across populations, and consistency in the direction of allele frequency change over time. The documented decoupling of diversity levels and short-term change by drift in Lycaeides has implications for our understanding of contemporary evolution and the maintenance of genetic variation in the wild.
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Affiliation(s)
- Zachariah Gompert
- Department of Biology, Utah State University, Logan, UT, 84322, USA.,Ecology Center, Utah State University, Logan, UT, 84322, USA
| | - Amy Springer
- Department of Biology, Utah State University, Logan, UT, 84322, USA
| | - Megan Brady
- Department of Biology, Utah State University, Logan, UT, 84322, USA
| | - Samridhi Chaturvedi
- Department of Biology, Utah State University, Logan, UT, 84322, USA.,Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Lauren K Lucas
- Department of Biology, Utah State University, Logan, UT, 84322, USA
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77
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Terasaki Hart DE, Bishop AP, Wang IJ. Geonomics: forward-time, spatially explicit, and arbitrarily complex landscape genomic simulations. Mol Biol Evol 2021; 38:4634-4646. [PMID: 34117771 PMCID: PMC8476160 DOI: 10.1093/molbev/msab175] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Understanding the drivers of spatial patterns of genomic diversity has emerged as a major
goal of evolutionary genetics. The flexibility of forward-time simulation makes it
especially valuable for these efforts, allowing for the simulation of arbitrarily complex
scenarios in a way that mimics how real populations evolve. Here, we present Geonomics, a
Python package for performing complex, spatially explicit, landscape genomic simulations
with full spatial pedigrees that dramatically reduces user workload yet remains
customizable and extensible because it is embedded within a popular, general-purpose
language. We show that Geonomics results are consistent with expectations for a variety of
validation tests based on classic models in population genetics and then demonstrate its
utility and flexibility with a trio of more complex simulation scenarios that feature
polygenic selection, selection on multiple traits, simulation on complex landscapes, and
nonstationary environmental change. We then discuss runtime, which is primarily sensitive
to landscape raster size, memory usage, which is primarily sensitive to maximum population
size and recombination rate, and other caveats related to the model’s methods for
approximating recombination and movement. Taken together, our tests and demonstrations
show that Geonomics provides an efficient and robust platform for population genomic
simulations that capture complex spatial and evolutionary dynamics.
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Affiliation(s)
- Drew E Terasaki Hart
- Department of Environmental Science, Policy, and Management, College of Natural Resources, University of California, Berkeley, CA, 94720, USA
| | - Anusha P Bishop
- Department of Environmental Science, Policy, and Management, College of Natural Resources, University of California, Berkeley, CA, 94720, USA
| | - Ian J Wang
- Department of Environmental Science, Policy, and Management, College of Natural Resources, University of California, Berkeley, CA, 94720, USA
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Thomson AI, Archer FI, Coleman MA, Gajardo G, Goodall‐Copestake WP, Hoban S, Laikre L, Miller AD, O’Brien D, Pérez‐Espona S, Segelbacher G, Serrão EA, Sjøtun K, Stanley MS. Charting a course for genetic diversity in the UN Decade of Ocean Science. Evol Appl 2021; 14:1497-1518. [PMID: 34178100 PMCID: PMC8210796 DOI: 10.1111/eva.13224] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 03/04/2021] [Accepted: 03/04/2021] [Indexed: 02/06/2023] Open
Abstract
The health of the world's oceans is intrinsically linked to the biodiversity of the ecosystems they sustain. The importance of protecting and maintaining ocean biodiversity has been affirmed through the setting of the UN Sustainable Development Goal 14 to conserve and sustainably use the ocean for society's continuing needs. The decade beginning 2021-2030 has additionally been declared as the UN Decade of Ocean Science for Sustainable Development. This program aims to maximize the benefits of ocean science to the management, conservation, and sustainable development of the marine environment by facilitating communication and cooperation at the science-policy interface. A central principle of the program is the conservation of species and ecosystem components of biodiversity. However, a significant omission from the draft version of the Decade of Ocean Science Implementation Plan is the acknowledgment of the importance of monitoring and maintaining genetic biodiversity within species. In this paper, we emphasize the importance of genetic diversity to adaptive capacity, evolutionary potential, community function, and resilience within populations, as well as highlighting some of the major threats to genetic diversity in the marine environment from direct human impacts and the effects of global climate change. We then highlight the significance of ocean genetic diversity to a diverse range of socioeconomic factors in the marine environment, including marine industries, welfare and leisure pursuits, coastal communities, and wider society. Genetic biodiversity in the ocean, and its monitoring and maintenance, is then discussed with respect to its integral role in the successful realization of the 2030 vision for the Decade of Ocean Science. Finally, we suggest how ocean genetic diversity might be better integrated into biodiversity management practices through the continued interaction between environmental managers and scientists, as well as through key leverage points in industry requirements for Blue Capital financing and social responsibility.
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Affiliation(s)
| | | | - Melinda A. Coleman
- New South Wales FisheriesNational Marine Science CentreCoffs HarbourNSWAustralia
- National Marine Science CentreSouthern Cross UniversityCoffs HarbourNSWAustralia
- Oceans Institute and School of Biological SciencesUniversity of Western AustraliaCrawleyWAAustralia
| | - Gonzalo Gajardo
- Laboratory of Genetics, Aquaculture & BiodiversityUniversidad de Los LagosOsornoChile
| | | | - Sean Hoban
- Centre for Tree ScienceThe Morton ArboretumLisleILUSA
| | - Linda Laikre
- Centre for Tree ScienceThe Morton ArboretumLisleILUSA
- The Wildlife Analysis UnitThe Swedish Environmental Protection AgencyStockholmSweden
| | - Adam D. Miller
- School of Life and Environmental SciencesCentre for Integrative EcologyDeakin UniversityGeelongVicAustralia
- Deakin Genomics CentreDeakin UniversityGeelongVic.Australia
| | | | - Sílvia Pérez‐Espona
- The Royal (Dick) School of Veterinary Studies and The Roslin InstituteMidlothianUK
| | - Gernot Segelbacher
- Chair of Wildlife Ecology and ManagementUniversity FreiburgFreiburgGermany
| | - Ester A. Serrão
- CCMARCentre of Marine SciencesFaculty of Sciences and TechnologyUniversity of AlgarveFaroPortugal
| | - Kjersti Sjøtun
- Department of Biological SciencesUniversity of BergenBergenNorway
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79
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Cortés AJ, López-Hernández F. Harnessing Crop Wild Diversity for Climate Change Adaptation. Genes (Basel) 2021; 12:783. [PMID: 34065368 PMCID: PMC8161384 DOI: 10.3390/genes12050783] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/28/2021] [Accepted: 05/19/2021] [Indexed: 12/20/2022] Open
Abstract
Warming and drought are reducing global crop production with a potential to substantially worsen global malnutrition. As with the green revolution in the last century, plant genetics may offer concrete opportunities to increase yield and crop adaptability. However, the rate at which the threat is happening requires powering new strategies in order to meet the global food demand. In this review, we highlight major recent 'big data' developments from both empirical and theoretical genomics that may speed up the identification, conservation, and breeding of exotic and elite crop varieties with the potential to feed humans. We first emphasize the major bottlenecks to capture and utilize novel sources of variation in abiotic stress (i.e., heat and drought) tolerance. We argue that adaptation of crop wild relatives to dry environments could be informative on how plant phenotypes may react to a drier climate because natural selection has already tested more options than humans ever will. Because isolated pockets of cryptic diversity may still persist in remote semi-arid regions, we encourage new habitat-based population-guided collections for genebanks. We continue discussing how to systematically study abiotic stress tolerance in these crop collections of wild and landraces using geo-referencing and extensive environmental data. By uncovering the genes that underlie the tolerance adaptive trait, natural variation has the potential to be introgressed into elite cultivars. However, unlocking adaptive genetic variation hidden in related wild species and early landraces remains a major challenge for complex traits that, as abiotic stress tolerance, are polygenic (i.e., regulated by many low-effect genes). Therefore, we finish prospecting modern analytical approaches that will serve to overcome this issue. Concretely, genomic prediction, machine learning, and multi-trait gene editing, all offer innovative alternatives to speed up more accurate pre- and breeding efforts toward the increase in crop adaptability and yield, while matching future global food demands in the face of increased heat and drought. In order for these 'big data' approaches to succeed, we advocate for a trans-disciplinary approach with open-source data and long-term funding. The recent developments and perspectives discussed throughout this review ultimately aim to contribute to increased crop adaptability and yield in the face of heat waves and drought events.
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Affiliation(s)
- Andrés J. Cortés
- Corporación Colombiana de Investigación Agropecuaria AGROSAVIA, C.I. La Selva, Km 7 Vía Rionegro, Las Palmas, Rionegro 054048, Colombia;
- Departamento de Ciencias Forestales, Facultad de Ciencias Agrarias, Universidad Nacional de Colombia, Sede Medellín, Medellín 050034, Colombia
| | - Felipe López-Hernández
- Corporación Colombiana de Investigación Agropecuaria AGROSAVIA, C.I. La Selva, Km 7 Vía Rionegro, Las Palmas, Rionegro 054048, Colombia;
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80
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Capblancq T, Munson H, Butnor JR, Keller SR. Genomic drivers of early-life fitness in Picea rubens. CONSERV GENET 2021. [DOI: 10.1007/s10592-021-01378-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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81
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Baduel P, Leduque B, Ignace A, Gy I, Gil J, Loudet O, Colot V, Quadrana L. Genetic and environmental modulation of transposition shapes the evolutionary potential of Arabidopsis thaliana. Genome Biol 2021; 22:138. [PMID: 33957946 PMCID: PMC8101250 DOI: 10.1186/s13059-021-02348-5] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 04/09/2021] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND How species can adapt to abrupt environmental changes, particularly in the absence of standing genetic variation, is poorly understood and a pressing question in the face of ongoing climate change. Here we leverage publicly available multi-omic and bio-climatic data for more than 1000 wild Arabidopsis thaliana accessions to determine the rate of transposable element (TE) mobilization and its potential to create adaptive variation in natural settings. RESULTS We demonstrate that TE insertions arise at almost the same rate as base substitutions. Mobilization activity of individual TE families varies greatly between accessions, in association with genetic and environmental factors as well as through complex gene-environment interactions. Although the distribution of TE insertions across the genome is ultimately shaped by purifying selection, reflecting their typically strong deleterious effects when located near or within genes, numerous recent TE-containing alleles show signatures of positive selection. Moreover, high rates of transposition appear positively selected at the edge of the species' ecological niche. Based on these findings, we predict through mathematical modeling higher transposition activity in Mediterranean regions within the next decades in response to global warming, which in turn should accelerate the creation of large-effect alleles. CONCLUSIONS Our study reveals that TE mobilization is a major generator of genetic variation in A. thaliana that is finely modulated by genetic and environmental factors. These findings and modeling indicate that TEs may be essential genomic players in the demise or rescue of native populations in times of climate crises.
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Affiliation(s)
- Pierre Baduel
- Institut de Biologie de l'École Normale Supérieure, ENS, 46 rue d'Ulm, 75005, Paris, France
| | - Basile Leduque
- Institut de Biologie de l'École Normale Supérieure, ENS, 46 rue d'Ulm, 75005, Paris, France
| | - Amandine Ignace
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France
| | - Isabelle Gy
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France
| | - José Gil
- Institut de Biologie de l'École Normale Supérieure, ENS, 46 rue d'Ulm, 75005, Paris, France
- Present Address: Institut Curie, 26 rue d'Ulm, 75005, Paris, France
| | - Olivier Loudet
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France
| | - Vincent Colot
- Institut de Biologie de l'École Normale Supérieure, ENS, 46 rue d'Ulm, 75005, Paris, France.
| | - Leandro Quadrana
- Institut de Biologie de l'École Normale Supérieure, ENS, 46 rue d'Ulm, 75005, Paris, France.
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82
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Rellstab C, Dauphin B, Exposito‐Alonso M. Prospects and limitations of genomic offset in conservation management. Evol Appl 2021; 14:1202-1212. [PMID: 34025760 PMCID: PMC8127717 DOI: 10.1111/eva.13205] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 02/06/2021] [Accepted: 02/09/2021] [Indexed: 12/12/2022] Open
Abstract
In nature conservation, there is keen interest in predicting how populations will respond to environmental changes such as climate change. These predictions can help determine whether a population can be self-sustaining under future alterations of its habitat or whether it may require human intervention such as protection, restoration, or assisted migration. An increasingly popular approach in this respect is the concept of genomic offset, which combines genomic and environmental data from different time points and/or locations to assess the degree of possible maladaptation to new environmental conditions. Here, we argue that the concept of genomic offset holds great potential, but an exploration of its risks and limitations is needed to use it for recommendations in conservation or assisted migration. After briefly describing the concept, we list important issues to consider (e.g., statistical frameworks, population genetic structure, migration, independent evidence) when using genomic offset or developing these methods further. We conclude that genomic offset is an area of development that still lacks some important features and should be used in combination with other approaches to inform conservation measures.
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Affiliation(s)
| | | | - Moises Exposito‐Alonso
- Department of Plant BiologyCarnegie Institution for ScienceStanfordCAUSA
- Department of BiologyStanford UniversityStanfordCAUSA
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83
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Allelic Diversity at Abiotic Stress Responsive Genes in Relationship to Ecological Drought Indices for Cultivated Tepary Bean, Phaseolus acutifolius A. Gray, and Its Wild Relatives. Genes (Basel) 2021; 12:genes12040556. [PMID: 33921270 PMCID: PMC8070098 DOI: 10.3390/genes12040556] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 04/01/2021] [Accepted: 04/09/2021] [Indexed: 12/22/2022] Open
Abstract
Some of the major impacts of climate change are expected in regions where drought stress is already an issue. Grain legumes are generally drought susceptible. However, tepary bean and its wild relatives within Phaseolus acutifolius or P. parvifolius are from arid areas between Mexico and the United States. Therefore, we hypothesize that these bean accessions have diversity signals indicative of adaptation to drought at key candidate genes such as: Asr2, Dreb2B, and ERECTA. By sequencing alleles of these genes and comparing to estimates of drought tolerance indices from climate data for the collection site of geo-referenced, tepary bean accessions, we determined the genotype x environmental association (GEA) of each gene. Diversity analysis found that cultivated and wild P. acutifolius were intermingled with var. tenuifolius and P. parvifolius, signifying that allele diversity was ample in the wild and cultivated clade over a broad sense (sensu lato) evaluation. Genes Dreb2B and ERECTA harbored signatures of directional selection, represented by six SNPs correlated with the environmental drought indices. This suggests that wild tepary bean is a reservoir of novel alleles at genes for drought tolerance, as expected for a species that originated in arid environments. Our study corroborated that candidate gene approach was effective for marker validation across a broad genetic base of wild tepary accessions.
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84
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Rochat E, Selmoni O, Joost S. Spatial areas of genotype probability: Predicting the spatial distribution of adaptive genetic variants under future climatic conditions. DIVERS DISTRIB 2021. [DOI: 10.1111/ddi.13256] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Affiliation(s)
- Estelle Rochat
- Laboratory of Geographic Information Systems (LASIG) School of Architecture, Civil and Environmental Engineering (ENAC) Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
| | - Oliver Selmoni
- Laboratory of Geographic Information Systems (LASIG) School of Architecture, Civil and Environmental Engineering (ENAC) Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
| | - Stéphane Joost
- Laboratory of Geographic Information Systems (LASIG) School of Architecture, Civil and Environmental Engineering (ENAC) Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
- The NEXTGEN Consortium
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85
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Fitzpatrick MC, Chhatre VE, Soolanayakanahally RY, Keller SR. Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests. Mol Ecol Resour 2021; 21:2749-2765. [PMID: 33683822 DOI: 10.1111/1755-0998.13374] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 02/12/2021] [Accepted: 02/23/2021] [Indexed: 12/21/2022]
Abstract
Gradient Forests (GF) is a machine learning algorithm that is gaining in popularity for studying the environmental drivers of genomic variation and for incorporating genomic information into climate change impact assessments. Here we (i) provide the first experimental evaluation of the ability of "genomic offsets" - a metric of climate maladaptation derived from Gradient Forests - to predict organismal responses to environmental change, and (ii) explore the use of GF for identifying candidate SNPs. We used high-throughput sequencing, genome scans, and several methods, including GF, to identify candidate loci associated with climate adaptation in balsam poplar (Populus balsamifera L.). Individuals collected throughout balsam poplar's range also were planted in two common garden experiments. We used GF to relate candidate loci to environmental gradients and predict the expected magnitude of the response (i.e., the genetic offset metric of maladaptation) of populations when transplanted from their "home" environment to the common gardens. We then compared the predicted genetic offsets from different sets of candidate and randomly selected SNPs to measurements of population performance in the common gardens. We found the expected inverse relationship between genetic offset and performance: populations with larger predicted genetic offsets performed worse in the common gardens than populations with smaller offsets. Also, genetic offset better predicted performance than did "naive" climate transfer distances. However, sets of randomly selected SNPs predicted performance slightly better than did candidate SNPs. Our study provides evidence that genetic offsets represent a first order estimate of the degree of expected maladaptation of populations exposed to rapid environmental change and suggests GF may have some promise as a method for identifying candidate SNPs.
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Affiliation(s)
- Matthew C Fitzpatrick
- Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, USA
| | - Vikram E Chhatre
- Department of Plant Biology, University of Vermont, Burlington, VT, USA.,Wyoming INBRE Data Science Core, University of Wyoming, Laramie, WY, USA
| | | | - Stephen R Keller
- Department of Plant Biology, University of Vermont, Burlington, VT, USA
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86
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Gain C, François O. LEA 3: Factor models in population genetics and ecological genomics with R. Mol Ecol Resour 2021; 21:2738-2748. [PMID: 33638893 DOI: 10.1111/1755-0998.13366] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 01/21/2021] [Accepted: 02/23/2021] [Indexed: 12/12/2022]
Abstract
A major objective of evolutionary biology is to understand the processes by which organisms have adapted to various environments, and to predict the response of organisms to new or future conditions. The availability of large genomic and environmental data sets provides an opportunity to address those questions, and the R package LEA has been introduced to facilitate population and ecological genomic analyses in this context. By using latent factor models, the program computes ancestry coefficients from population genetic data and performs genotype-environment association analyses with correction for unobserved confounding variables. In this study, we present new functionalities of LEA, which include imputation of missing genotypes, fast algorithms for latent factor mixed models using multivariate predictors for genotype-environment association studies, population differentiation tests for admixed or continuous populations, and estimation of genetic offset based on climate models. The new functionalities are implemented in version 3.1 and higher releases of the package. Using simulated and real data sets, our study provides evaluations and examples of applications, outlining important practical considerations when analysing ecological genomic data in R.
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Affiliation(s)
- Clément Gain
- Centre National de la Recherche Scientifique, Grenoble INP, TIMC-IMAG CNRS UMR 5525, Université Grenoble-Alpes, Grenoble, France
| | - Olivier François
- Centre National de la Recherche Scientifique, Grenoble INP, TIMC-IMAG CNRS UMR 5525, Université Grenoble-Alpes, Grenoble, France
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87
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Lasky JR, Hooten MB, Adler PB. What processes must we understand to forecast regional-scale population dynamics? Proc Biol Sci 2020; 287:20202219. [PMID: 33290672 PMCID: PMC7739927 DOI: 10.1098/rspb.2020.2219] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 11/12/2020] [Indexed: 12/14/2022] Open
Abstract
An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.
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Affiliation(s)
- Jesse R. Lasky
- Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - Mevin B. Hooten
- U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, Fort Collins, CO, USA
- Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA
- Department of Statistics, Colorado State University, Fort Collins, CO, USA
| | - Peter B. Adler
- Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, USA
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