1
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James C, Pemberton JM, Navarro P, Knott S. The impact of SNP density on quantitative genetic analyses of body size traits in a wild population of Soay sheep. Ecol Evol 2022; 12:e9639. [PMID: 36532132 PMCID: PMC9750819 DOI: 10.1002/ece3.9639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 11/01/2022] [Accepted: 11/29/2022] [Indexed: 12/23/2022] Open
Abstract
Understanding the genetic architecture underpinning quantitative traits in wild populations is pivotal to understanding the processes behind trait evolution. The 'animal model' is a popular method for estimating quantitative genetic parameters such as heritability and genetic correlation and involves fitting an estimate of relatedness between individuals in the study population. Genotypes at genome-wide markers can be used to estimate relatedness; however, relatedness estimates vary with marker density, potentially affecting results. Increasing density of markers is also expected to increase the power to detect quantitative trait loci (QTL). In order to understand how the density of genetic markers affects the results of quantitative genetic analyses, we estimated heritability and performed genome-wide association studies (GWAS) on five body size traits in an unmanaged population of Soay sheep using two different SNP densities: a dataset of 37,037 genotyped SNPs and an imputed dataset of 417,373 SNPs. Heritability estimates did not differ between the two SNP densities, but the high-density imputed SNP dataset revealed four new SNP-trait associations that were not found with the lower density dataset, as well as confirming all previously-found QTL. We also demonstrated that fitting fixed and random effects in the same step as performing GWAS is a more powerful approach than pre-correcting for covariates in a separate model.
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Affiliation(s)
- Caelinn James
- Institute of Ecology and EvolutionSchool of Biological SciencesThe University of EdinburghEdinburghScotland
| | - Josephine M. Pemberton
- Institute of Ecology and EvolutionSchool of Biological SciencesThe University of EdinburghEdinburghScotland
| | - Pau Navarro
- MRC Human Genetics UnitInstitute of Genetics and CancerThe University of EdinburghEdinburghScotland
| | - Sara Knott
- Institute of Ecology and EvolutionSchool of Biological SciencesThe University of EdinburghEdinburghScotland
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2
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Gervais L, Morellet N, David I, Hewison AJM, Réale D, Goulard M, Chaval Y, Lourtet B, Cargnelutti B, Merlet J, Quéméré E, Pujol B. Quantifying heritability and estimating evolutionary potential in the wild when individuals that share genes also share environments. J Anim Ecol 2022; 91:1239-1250. [DOI: 10.1111/1365-2656.13677] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 02/01/2022] [Indexed: 11/29/2022]
Affiliation(s)
- L. Gervais
- Université de Toulouse, INRAE, CEFS, Castanet‐Tolosan, France ZA France
- PSL Université Paris : EHPE‐UPVD‐CNRS Perpignan France
| | - N. Morellet
- Université de Toulouse, INRAE, CEFS, Castanet‐Tolosan, France ZA France
| | - I. David
- Université de Toulouse Castanet Tolosan France
| | - A. J. M. Hewison
- Université de Toulouse, INRAE, CEFS, Castanet‐Tolosan, France ZA France
| | - D. Réale
- Département des sciences biologiques Université du Québec à Montréal QC Canada
| | - M. Goulard
- Université de Toulouse Castanet‐Tolosan France
| | - Y. Chaval
- Université de Toulouse, INRAE, CEFS, Castanet‐Tolosan, France ZA France
| | - B. Lourtet
- Université de Toulouse, INRAE, CEFS, Castanet‐Tolosan, France ZA France
| | - B. Cargnelutti
- Université de Toulouse, INRAE, CEFS, Castanet‐Tolosan, France ZA France
| | - J. Merlet
- Université de Toulouse, INRAE, CEFS, Castanet‐Tolosan, France ZA France
| | - E. Quéméré
- Université de Toulouse, INRAE, CEFS, Castanet‐Tolosan, France ZA France
- INRAE, DECOD (Ecosystem Dynamics and Sustainability), Institut Agro, IFREMER Rennes France
| | - B. Pujol
- PSL Université Paris : EHPE‐UPVD‐CNRS Perpignan France
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3
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Fokkema RW, Korsten P, Schmoll T, Wilson AJ. Social competition as a driver of phenotype-environment correlations: implications for ecology and evolution. Biol Rev Camb Philos Soc 2021; 96:2561-2572. [PMID: 34145714 PMCID: PMC9290562 DOI: 10.1111/brv.12768] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Revised: 06/09/2021] [Accepted: 06/11/2021] [Indexed: 12/27/2022]
Abstract
While it is universally recognised that environmental factors can cause phenotypic trait variation via phenotypic plasticity, the extent to which causal processes operate in the reverse direction has received less consideration. In fact individuals are often active agents in determining the environments, and hence the selective regimes, they experience. There are several important mechanisms by which this can occur, including habitat selection and niche construction, that are expected to result in phenotype–environment correlations (i.e. non‐random assortment of phenotypes across heterogeneous environments). Here we highlight an additional mechanism – intraspecific competition for preferred environments – that may be widespread, and has implications for phenotypic evolution that are currently underappreciated. Under this mechanism, variation among individuals in traits determining their competitive ability leads to phenotype–environment correlation; more competitive phenotypes are able to acquire better patches. Based on a concise review of the empirical evidence we argue that competition‐induced phenotype–environment correlations are likely to be common in natural populations before highlighting the major implications of this for studies of natural selection and microevolution. We focus particularly on two central issues. First, competition‐induced phenotype–environment correlation leads to the expectation that positive feedback loops will amplify phenotypic and fitness variation among competing individuals. As a result of being able to acquire a better environment, winners gain more resources and even better phenotypes – at the expense of losers. The distinction between individual quality and environmental quality that is commonly made by researchers in evolutionary ecology thus becomes untenable. Second, if differences among individuals in competitive ability are underpinned by heritable traits, competition results in both genotype–environment correlations and an expectation of indirect genetic effects (IGEs) on resource‐dependent life‐history traits. Theory tells us that these IGEs will act as (partial) constraints, reducing the amount of genetic variance available to facilitate evolutionary adaptation. Failure to recognise this will lead to systematic overestimation of the adaptive potential of populations. To understand the importance of these issues for ecological and evolutionary processes in natural populations we therefore need to identify and quantify competition‐induced phenotype–environment correlations in our study systems. We conclude that both fundamental and applied research will benefit from an improved understanding of when and how social competition causes non‐random distribution of phenotypes, and genotypes, across heterogeneous environments.
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Affiliation(s)
- Rienk W Fokkema
- Department of Animal Behaviour, Bielefeld University, Konsequenz 45, Bielefeld, 33615, Germany.,Evolutionary Biology, Bielefeld University, Konsequenz 45, Bielefeld, 33615, Germany.,Conservation Ecology Group, Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Nijenborgh 7, Groningen, 9747AG, The Netherlands
| | - Peter Korsten
- Department of Animal Behaviour, Bielefeld University, Konsequenz 45, Bielefeld, 33615, Germany
| | - Tim Schmoll
- Evolutionary Biology, Bielefeld University, Konsequenz 45, Bielefeld, 33615, Germany
| | - Alastair J Wilson
- Centre for Ecology and Conservation, University of Exeter (Penryn Campus), Penryn, Cornwall, TR10 9FE, United Kingdom
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4
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Santostefano F, Allegue H, Garant D, Bergeron P, Réale D. Indirect genetic and environmental effects on behaviors, morphology, and life-history traits in a wild Eastern chipmunk population. Evolution 2021; 75:1492-1512. [PMID: 33855713 DOI: 10.1111/evo.14232] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 03/18/2021] [Accepted: 03/22/2021] [Indexed: 12/24/2022]
Abstract
Additive genetic variance in a trait reflects its potential to respond to selection, which is key for adaptive evolution in the wild. Social interactions contribute to this genetic variation through indirect genetic effects-the effect of an individual's genotype on the expression of a trait in a conspecific. However, our understanding of the evolutionary importance of indirect genetic effects in the wild and of their strength relative to direct genetic effects is limited. In this study, we assessed how indirect genetic effects contribute to genetic variation of behavioral, morphological, and life-history traits in a wild Eastern chipmunk population. We also compared the contribution of direct and indirect genetic effects to traits evolvabilities and related these effects to selection strength across traits. We implemented a novel approach integrating the spatial structure of social interactions in quantitative genetic analyses, and supported the reliability of our results with power analyses. We found indirect genetic effects for trappability and relative fecundity, little direct genetic effects in all traits and a large role for direct and indirect permanent environmental effects. Our study highlights the potential evolutionary role of social permanent environmental effects in shaping phenotypes of conspecifics through adaptive phenotypic plasticity.
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Affiliation(s)
- Francesca Santostefano
- Département des Sciences Biologiques, Université du Québec à Montréal, Montréal, Québec, Canada
| | - Hassen Allegue
- Département des Sciences Biologiques, Université du Québec à Montréal, Montréal, Québec, Canada
| | - Dany Garant
- Département de Biologie, Faculté des Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Patrick Bergeron
- Department of Biological Sciences, Bishop's University, Sherbrooke, Québec, Canada
| | - Denis Réale
- Département des Sciences Biologiques, Université du Québec à Montréal, Montréal, Québec, Canada
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5
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Albery GF, Morris A, Morris S, Pemberton JM, Clutton-Brock TH, Nussey DH, Firth JA. Multiple spatial behaviours govern social network positions in a wild ungulate. Ecol Lett 2021; 24:676-686. [PMID: 33583128 DOI: 10.1111/ele.13684] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 12/22/2020] [Accepted: 12/23/2020] [Indexed: 01/19/2023]
Abstract
The structure of wild animal social systems depends on a complex combination of intrinsic and extrinsic drivers. Population structuring and spatial behaviour are key determinants of individuals' observed social behaviour, but quantifying these spatial components alongside multiple other drivers remains difficult due to data scarcity and analytical complexity. We used a 43-year dataset detailing a wild red deer population to investigate how individuals' spatial behaviours drive social network positioning, while simultaneously assessing other potential contributing factors. Using Integrated Nested Laplace Approximation (INLA) multi-matrix animal models, we demonstrate that social network positions are shaped by two-dimensional landscape locations, pairwise space sharing, individual range size, and spatial and temporal variation in population density, alongside smaller but detectable impacts of a selection of individual-level phenotypic traits. These results indicate strong, multifaceted spatiotemporal structuring in this society, emphasising the importance of considering multiple spatial components when investigating the causes and consequences of sociality.
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Affiliation(s)
- Gregory F Albery
- Department of Biology, Georgetown University, Washington, DC, USA.,Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Alison Morris
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Sean Morris
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | | | - Tim H Clutton-Brock
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.,Department of Zoology, University of Cambridge, Cambridge, UK
| | - Daniel H Nussey
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Josh A Firth
- Department of Zoology, University of Oxford, Oxford, UK.,Merton College, University of Oxford, Oxford, UK
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6
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7
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Evans SR, Postma E, Sheldon BC. It takes two: Heritable male effects on reproductive timing but not clutch size in a wild bird population*. Evolution 2020; 74:2320-2331. [DOI: 10.1111/evo.13980] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 03/19/2020] [Accepted: 04/02/2020] [Indexed: 12/29/2022]
Affiliation(s)
- Simon R. Evans
- Edward Grey Institute, Department of Zoology University of Oxford Oxford OX1 3SZ UK
- Centre for Ecology and Conservation University of Exeter Penryn TR10 9FE UK
| | - Erik Postma
- Centre for Ecology and Conservation University of Exeter Penryn TR10 9FE UK
| | - Ben C. Sheldon
- Edward Grey Institute, Department of Zoology University of Oxford Oxford OX1 3SZ UK
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8
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Gervais L, Hewison AJM, Morellet N, Bernard M, Merlet J, Cargnelutti B, Chaval Y, Pujol B, Quéméré E. Pedigree-free quantitative genetic approach provides evidence for heritability of movement tactics in wild roe deer. J Evol Biol 2020; 33:595-607. [PMID: 31985133 DOI: 10.1111/jeb.13594] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 01/07/2020] [Accepted: 01/13/2020] [Indexed: 11/30/2022]
Abstract
Assessing the evolutionary potential of animal populations in the wild is crucial to understanding how they may respond to selection mediated by rapid environmental change (e.g. habitat loss and fragmentation). A growing number of studies have investigated the adaptive role of behaviour, but assessments of its genetic basis in a natural setting remain scarce. We combined intensive biologging technology with genome-wide data and a pedigree-free quantitative genetic approach to quantify repeatability, heritability and evolvability for a suite of behaviours related to the risk avoidance-resource acquisition trade-off in a wild roe deer (Capreolus capreolus) population inhabiting a heterogeneous, human-dominated landscape. These traits, linked to the stress response, movement and space-use behaviour, were all moderately to highly repeatable. Furthermore, the repeatable among-individual component of variation in these traits was partly due to additive genetic variance, with heritability estimates ranging from 0.21 ± 0.08 to 0.70 ± 0.11 and evolvability ranging from 1.1% to 4.3%. Changes in the trait mean can therefore occur under hypothetical directional selection over just a few generations. To the best of our knowledge, this is the first empirical demonstration of additive genetic variation in space-use behaviour in a free-ranging population based on genomic relatedness data. We conclude that wild animal populations may have the potential to adjust their spatial behaviour to human-driven environmental modifications through microevolutionary change.
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Affiliation(s)
- Laura Gervais
- CEFS, INRAE, Université de Toulouse, Castanet-Tolosan, France.,LTSER ZA PYRénées GARonne, Auzeville-Tolosane, France.,Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), CNRS, IRD, UPS, Université Fédérale de Toulouse Midi-Pyrénées, Toulouse, France
| | - Aidan J M Hewison
- CEFS, INRAE, Université de Toulouse, Castanet-Tolosan, France.,LTSER ZA PYRénées GARonne, Auzeville-Tolosane, France
| | - Nicolas Morellet
- CEFS, INRAE, Université de Toulouse, Castanet-Tolosan, France.,LTSER ZA PYRénées GARonne, Auzeville-Tolosane, France
| | - Maria Bernard
- INRAE, GABI, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France.,INRAE, SIGENAE, Jouy-en-Josas, France
| | - Joël Merlet
- CEFS, INRAE, Université de Toulouse, Castanet-Tolosan, France.,LTSER ZA PYRénées GARonne, Auzeville-Tolosane, France
| | - Bruno Cargnelutti
- CEFS, INRAE, Université de Toulouse, Castanet-Tolosan, France.,LTSER ZA PYRénées GARonne, Auzeville-Tolosane, France
| | - Yannick Chaval
- CEFS, INRAE, Université de Toulouse, Castanet-Tolosan, France.,LTSER ZA PYRénées GARonne, Auzeville-Tolosane, France
| | - Benoit Pujol
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), CNRS, IRD, UPS, Université Fédérale de Toulouse Midi-Pyrénées, Toulouse, France.,USR 3278 CRIOBE, PSL Université Paris: EPHE-UPVD-CNRS, Université de Perpignan, Perpignan Cedex, France
| | - Erwan Quéméré
- CEFS, INRAE, Université de Toulouse, Castanet-Tolosan, France.,LTSER ZA PYRénées GARonne, Auzeville-Tolosane, France.,ESE, Ecology and Ecosystems Health, Ouest, INRAE, Rennes, France
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9
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Santostefano F, Garant D, Bergeron P, Montiglio P, Réale D. Social selection acts on behavior and body mass but does not contribute to the total selection differential in eastern chipmunks. Evolution 2019; 74:89-102. [DOI: 10.1111/evo.13875] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 09/23/2019] [Accepted: 10/21/2019] [Indexed: 11/27/2022]
Affiliation(s)
- Francesca Santostefano
- Département des Sciences BiologiquesUniversité du Québec à Montréal Montréal Canada
- Département de Biologie, Faculté des SciencesUniversité de Sherbrooke Sherbrooke Québec Canada
| | - Dany Garant
- Département de Biologie, Faculté des SciencesUniversité de Sherbrooke Sherbrooke Québec Canada
| | - Patrick Bergeron
- Department of Biological SciencesBishop's University Sherbrooke Québec Canada
| | | | - Denis Réale
- Département des Sciences BiologiquesUniversité du Québec à Montréal Montréal Canada
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10
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Gold S, Regan CE, McLoughlin PD, Gilleard JS, Wilson AJ, Poissant J. Quantitative genetics of gastrointestinal strongyle burden and associated body condition in feral horses. INTERNATIONAL JOURNAL FOR PARASITOLOGY-PARASITES AND WILDLIFE 2019; 9:104-111. [PMID: 31011533 PMCID: PMC6462499 DOI: 10.1016/j.ijppaw.2019.03.010] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 02/16/2019] [Accepted: 03/10/2019] [Indexed: 12/12/2022]
Abstract
Variability in host resistance or tolerance to parasites is nearly ubiquitous, and is of key significance in understanding the evolutionary processes shaping host-parasite interactions. While ample research has been conducted on the genetics of parasite burden in livestock, relatively little has been done in free-living populations. Here, we investigate the sources of (co)variation in strongyle nematode faecal egg count (FEC) and body condition in Sable Island horses, a feral population in which parasite burden has previously been shown to negatively correlate with body condition. We used the quantitative genetic "animal model" to understand the sources of (co)variation in these traits, and tested for impacts of an important spatial gradient in habitat quality on the parameter estimates. Although FEC is significantly heritable (h 2 = 0.43 ± 0.11), there was no evidence for significant additive genetic variation in body condition (h 2 = 0.04 ± 0.07), and therefore there was also no significant genetic covariance between the two traits. The negative phenotypic covariance between these traits therefore does not derive principally from additive genetic effects. We also found that both FEC and body condition increase from east to west across the island, which indicates that the longitudinal environmental gradient is not responsible for the negative phenotypic association observed between these traits. There was also little evidence to suggest that quantitative genetic parameters were biased when an individual's location along the island's environmental gradient was not incorporated into the analysis. This research provides new and important insights into the genetic basis and adaptive potential of parasite resistance in free-living animals, and highlights the importance of environmental heterogeneity in modulating host-parasite interactions in wild vertebrate systems.
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Affiliation(s)
- Susannah Gold
- College of Life and Environmental Sciences, University of Exeter, Cornwall Campus, Penryn, TR10 9FE, UK
| | - Charlotte E Regan
- Department of Biology, University of Saskatchewan, 112 Science Place, Saskatoon, SK, S7N 5E2, Canada
| | - Philip D McLoughlin
- Department of Biology, University of Saskatchewan, 112 Science Place, Saskatoon, SK, S7N 5E2, Canada
| | - John S Gilleard
- Department of Comparative Biology and Experimental Medicine, University of Calgary, 3280 Hospital Drive, Calgary, AB, T2N 4Z6, Canada
| | - Alastair J Wilson
- College of Life and Environmental Sciences, University of Exeter, Cornwall Campus, Penryn, TR10 9FE, UK
| | - Jocelyn Poissant
- Department of Ecosystem and Public Health, University of Calgary, 3280 Hospital Drive, Calgary, AB, T2N 4Z6, Canada
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11
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Fisher DN, Wilson AJ, Boutin S, Dantzer B, Lane JE, Coltman DW, Gorrell JC, McAdam AG. Social effects of territorial neighbours on the timing of spring breeding in North American red squirrels. J Evol Biol 2019; 32:559-571. [DOI: 10.1111/jeb.13437] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 02/25/2019] [Accepted: 03/01/2019] [Indexed: 02/06/2023]
Affiliation(s)
- David N. Fisher
- Department for Integrative Biology University of Guelph Guelph Ontario Canada
- Department of Psychology, Neuroscience & Behaviour McMaster University Hamilton Ontario Canada
| | - Alastair J. Wilson
- Centre for Ecology and Conservation University of Exeter Penryn Cornwall UK
| | - Stan Boutin
- Department of Biological Sciences University of Alberta Edmonton Alberta Canada
| | - Ben Dantzer
- Department of Psychology University of Michigan Ann Arbour Michigan
- Department of Ecology and Evolutionary Biology University of Michigan Ann Arbour Michigan
| | - Jeffrey E. Lane
- Department of Biology University of Saskatchewan Saskatoon Saskatchewan Canada
| | - David W. Coltman
- Department of Biological Sciences University of Alberta Edmonton Alberta Canada
| | - Jamie C. Gorrell
- Biology Department University of Vancouver Island Nanaimo British Columbia Canada
| | - Andrew G. McAdam
- Department for Integrative Biology University of Guelph Guelph Ontario Canada
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12
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Thomson CE, Winney IS, Salles OC, Pujol B. A guide to using a multiple-matrix animal model to disentangle genetic and nongenetic causes of phenotypic variance. PLoS One 2018; 13:e0197720. [PMID: 30312317 PMCID: PMC6193571 DOI: 10.1371/journal.pone.0197720] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 09/19/2018] [Indexed: 11/19/2022] Open
Abstract
Non-genetic influences on phenotypic traits can affect our interpretation of genetic variance and the evolutionary potential of populations to respond to selection, with consequences for our ability to predict the outcomes of selection. Long-term population surveys and experiments have shown that quantitative genetic estimates are influenced by nongenetic effects, including shared environmental effects, epigenetic effects, and social interactions. Recent developments to the "animal model" of quantitative genetics can now allow us to calculate precise individual-based measures of non-genetic phenotypic variance. These models can be applied to a much broader range of contexts and data types than used previously, with the potential to greatly expand our understanding of nongenetic effects on evolutionary potential. Here, we provide the first practical guide for researchers interested in distinguishing between genetic and nongenetic causes of phenotypic variation in the animal model. The methods use matrices describing individual similarity in nongenetic effects, analogous to the additive genetic relatedness matrix. In a simulation of various phenotypic traits, accounting for environmental, epigenetic, or cultural resemblance between individuals reduced estimates of additive genetic variance, changing the interpretation of evolutionary potential. These variances were estimable for both direct and parental nongenetic variances. Our tutorial outlines an easy way to account for these effects in both wild and experimental populations. These models have the potential to add to our understanding of the effects of genetic and nongenetic effects on evolutionary potential. This should be of interest both to those studying heritability, and those who wish to understand nongenetic variance.
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Affiliation(s)
- Caroline E. Thomson
- Laboratoire Evolution & Diversité Biologique (EDB UMR 5174), Université Fédérale Toulouse, Midi-Pyrénées, CNRS, ENSFEA, IRD, UPS, France
| | - Isabel S. Winney
- Laboratoire Evolution & Diversité Biologique (EDB UMR 5174), Université Fédérale Toulouse, Midi-Pyrénées, CNRS, ENSFEA, IRD, UPS, France
| | - Océane C. Salles
- Laboratoire Evolution & Diversité Biologique (EDB UMR 5174), Université Fédérale Toulouse, Midi-Pyrénées, CNRS, ENSFEA, IRD, UPS, France
| | - Benoit Pujol
- Laboratoire Evolution & Diversité Biologique (EDB UMR 5174), Université Fédérale Toulouse, Midi-Pyrénées, CNRS, ENSFEA, IRD, UPS, France
- Laboratoire d’Excellence “CORAIL”, Perpignan, France
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13
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Pujol B, Blanchet S, Charmantier A, Danchin E, Facon B, Marrot P, Roux F, Scotti I, Teplitsky C, Thomson CE, Winney I. The Missing Response to Selection in the Wild. Trends Ecol Evol 2018; 33:337-346. [PMID: 29628266 PMCID: PMC5937857 DOI: 10.1016/j.tree.2018.02.007] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 02/26/2018] [Accepted: 02/28/2018] [Indexed: 01/28/2023]
Abstract
Although there are many examples of contemporary directional selection, evidence for responses to selection that match predictions are often missing in quantitative genetic studies of wild populations. This is despite the presence of genetic variation and selection pressures – theoretical prerequisites for the response to selection. This conundrum can be explained by statistical issues with accurate parameter estimation, and by biological mechanisms that interfere with the response to selection. These biological mechanisms can accelerate or constrain this response. These mechanisms are generally studied independently but might act simultaneously. We therefore integrated these mechanisms to explore their potential combined effect. This has implications for explaining the apparent evolutionary stasis of wild populations and the conservation of wildlife. Recent discoveries at the intersection of quantitative genetics and evolutionary ecology are challenging our views on the potential of wild populations to respond to selection. Multiple biological mechanisms can disconnect genetic variation from the response to selection in the wild. We highlight areas for future research. We provide an integrative framework that can be used to qualitatively assess the combined influence of these mechanisms on the response to selection.
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Affiliation(s)
- Benoit Pujol
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), Université Fédérale de Toulouse Midi-Pyrénées, CNRS, IRD, UPS, 31062 Toulouse, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France.
| | - Simon Blanchet
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), Université Fédérale de Toulouse Midi-Pyrénées, CNRS, IRD, UPS, 31062 Toulouse, France; Station d'Ecologie Théorique Expérimentale (SETE), CNRS UMR 5321, Université Paul Sabatier, 09200 Moulis, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Anne Charmantier
- Centre d'Ecologie Fonctionnelle et Evolutive (CEFE), CNRS UMR 5175, 34293 Montpellier, France; Département des Sciences Biologiques, Université du Québec à Montréal, CP 888 Succursale Centre-Ville, H3P 3P8 QC, Canada; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Etienne Danchin
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), Université Fédérale de Toulouse Midi-Pyrénées, CNRS, IRD, UPS, 31062 Toulouse, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Benoit Facon
- UMR Peuplements Végétaux et Bioagresseurs en Milieu Tropical (PVBMT), Institut National de la Recherche Agronomique (INRA), Saint Pierre, Réunion, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Pascal Marrot
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), Université Fédérale de Toulouse Midi-Pyrénées, CNRS, IRD, UPS, 31062 Toulouse, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Fabrice Roux
- Laboratoire des Interactions Plantes-Microorganismes (LIPM), INRA, CNRS, Université de Toulouse, 31326 Castanet-Tolosan, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Ivan Scotti
- INRA Unité de Recherche 0629 Ecologie des Forêts Méditerranéennes, 84914 Avignon, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Céline Teplitsky
- Centre d'Ecologie Fonctionnelle et Evolutive (CEFE), CNRS UMR 5175, 34293 Montpellier, France; Muséum National d'Histoire Naturelle, CNRS UMR 7204 Centre d'Écologie et des Sciences de la Conservation (CESCO), 75005 Paris, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Caroline E Thomson
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), Université Fédérale de Toulouse Midi-Pyrénées, CNRS, IRD, UPS, 31062 Toulouse, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
| | - Isabel Winney
- Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), Université Fédérale de Toulouse Midi-Pyrénées, CNRS, IRD, UPS, 31062 Toulouse, France; Groupement de Recherche de l'Institut Ecologie et Environnement 6448, Génétique Quantitative dans les Populations Naturelles (GQPN), c/o EDB, 31062 Toulouse, France
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14
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Morrissey MB, Janeiro MJ, Sparks AM, White S, Pigeon G, Teplitsky C, Réale D, Milot E. Into the wild-WAMBAM goes to Canada. Mol Ecol 2018; 27:1098-1102. [PMID: 29411456 DOI: 10.1111/mec.14510] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 01/18/2018] [Accepted: 01/22/2018] [Indexed: 11/28/2022]
Abstract
The sixth Wild Animal Models Bi-Annual Meeting was held in July 2017 in Québec, with 42 participants. This report documents the evolution of questions asked and approaches used in evolutionary quantitative genetic studies of wild populations in recent decades, and how these questions and approaches were represented at the recent meeting. We explore how ideas from previous meetings in this series have developed to their present states, and consider how the format of the meetings may be particularly useful at fostering the rapid development and proliferation of ideas and approaches.
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Affiliation(s)
| | - Maria João Janeiro
- School of Biology, University of St Andrews, St Andrews, UK.,CESAM, Department of Biology, University of Aveiro, Aveiro, Portugal
| | - Alexandra M Sparks
- Institutes of Evolutionary Biology, Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - Stephen White
- Centre for Ecology and Conservation, University of Exeter (Penryn Campus), Cornwall, UK
| | - Gabriel Pigeon
- Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
| | - Céline Teplitsky
- CEFE, CNRS, Univ Montpellier, EPHE, IRD, Univ Paul Valéry Montpellier 3, Montpellier, France
| | - Denis Réale
- Département des Sciences Biologiques, Université du Québec À Montréal, Montréal, QC, Canada
| | - Emmanuel Milot
- Department of chemistry, biochemistry and physics, Université du Québec à Trois-Rivières, Trois-Rivières, QC, Canada
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15
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Fisher DN, McAdam AG. Social traits, social networks and evolutionary biology. J Evol Biol 2017; 30:2088-2103. [DOI: 10.1111/jeb.13195] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Revised: 10/08/2017] [Accepted: 10/12/2017] [Indexed: 01/20/2023]
Affiliation(s)
- D. N. Fisher
- Department for Integrative Biology; University of Guelph; Guelph Ontario Canada
| | - A. G. McAdam
- Department for Integrative Biology; University of Guelph; Guelph Ontario Canada
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