Genomic Approaches in Landscape Genetics

Storfer, Andrew; Antolin, Michael F.; Manel, Stéphanie; Epperson, Bryan K.; Scribner, Kim T.

doi:10.1002/9781118525258.ch09

Cited by 8 publications

(9 citation statements)

References 131 publications

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“…, Storfer et al. ). We argue that a similar conceptual leap remains to be accomplished in order to investigate the historical broad‐scale imprint of natural selection on modern‐day genetic variation by assessing the molecular signature of adaptation to Quaternary environmental variation (Davis et al.…”

Section: The Neutral Genetic Legacy Of the Quaternary Ice Agesmentioning

confidence: 98%

“…, Storfer et al. ). Although such analyses show great promise to uncover the genetic basis of past adaptation to Quaternary environments, they have important limitations because any approach that does not rely on phenotypic data is prone to significant challenges and potential pitfalls (Barrett and Hoekstra , Hoban et al.…”

Section: Empirical Evidence For Adaptation To Quaternary Climate Flucmentioning

confidence: 98%

“…, Storfer et al. ). A number of studies have sought to provide evidence for local adaptation related to modern climate (1950–2010) (e.g., for forest trees, Jump et al.…”

Section: Empirical Evidence For Adaptation To Quaternary Climate Flucmentioning

confidence: 98%

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Invoking adaptation to decipher the genetic legacy of past climate change

Lafontaine

Napier

Petit

et al. 2018

Ecology

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Persistence of natural populations during periods of climate change is likely to depend on migration (range shifts) or adaptation. These responses were traditionally considered discrete processes and conceptually divided into the realms of ecology and evolution. In a milestone paper, Davis and Shaw (2001) Science 292:673 argued that the interplay of adaptation and migration was central to biotic responses to Quaternary climate, but since then there has been no synthesis of efforts made to set up this research program. Here we review some of the salient findings from molecular genetic studies assessing ecological and evolutionary responses to Quaternary climate change. These studies have revolutionized our understanding of population processes associated with past species migration. However, knowledge remains limited about the role of natural selection for local adaptation of populations to Quaternary environmental fluctuations and associated range shifts, and for the footprints this might have left on extant populations. Next-generation sequencing technologies, high-resolution paleoclimate analyses, and advances in population genetic theory offer an unprecedented opportunity to test hypotheses about adaptation through time. Recent population genomics studies have greatly improved our understanding of the role of contemporary adaptation to local environments in shaping spatial patterns of genetic diversity across modern-day landscapes. Advances in this burgeoning field provide important conceptual and methodological bases to decipher the historical role of natural selection and assess adaptation to past environmental variation. We suggest that a process called "temporal conditional neutrality" has taken place: some alleles favored in glacial environments become selectively neutral in modern-day conditions, whereas some alleles that had been neutral during glacial periods become under selection in modern environments. Building on this view, we present a new integrative framework for addressing the interplay of demographic and adaptive evolutionary responses to Quaternary climate dynamics, the research agenda initially envisioned by Davis and Shaw (2001) Science 292:673.

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Section: The Neutral Genetic Legacy Of the Quaternary Ice Agesmentioning

confidence: 98%

Section: Empirical Evidence For Adaptation To Quaternary Climate Flucmentioning

confidence: 98%

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Invoking adaptation to decipher the genetic legacy of past climate change

Lafontaine

Napier

Petit

et al. 2018

Ecology

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“…Landscape genomics is sometimes conflated with genotype–environment association (GEA) analysis, which includes a wide variety of statistical approaches for identifying candidate adaptive loci that covary with environmental predictors (Rellstab, Gugerli, Eckert, Hancock, & Holderegger, 2015). However, landscape genomics includes many other techniques for identifying and analyzing spatially structured, selection‐driven variation, including GWAS across multiple environments, simulation studies, experimental approaches such as environmentally stratified common gardens, epigenetic and transcriptomic studies, and innovative approaches that combine analytical techniques (Berg & Coop, 2014; Lasky, Forester, & Reimherr, 2018; Storfer, Antolin, Manel, Epperson, & Scribner, 2015). …”

Section: Improving Downstream Computational Analysesmentioning

confidence: 99%

Recent advances in conservation and population genomics data analysis

Hendricks

Anderson

Antão

et al. 2018

Evolutionary Applications

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New computational methods and next‐generation sequencing (NGS) approaches have enabled the use of thousands or hundreds of thousands of genetic markers to address previously intractable questions. The methods and massive marker sets present both new data analysis challenges and opportunities to visualize, understand, and apply population and conservation genomic data in novel ways. The large scale and complexity of NGS data also increases the expertise and effort required to thoroughly and thoughtfully analyze and interpret data. To aid in this endeavor, a recent workshop entitled “Population Genomic Data Analysis,” also known as “ConGen 2017,” was held at the University of Montana. The ConGen workshop brought 15 instructors together with knowledge in a wide range of topics including NGS data filtering, genome assembly, genomic monitoring of effective population size, migration modeling, detecting adaptive genomic variation, genomewide association analysis, inbreeding depression, and landscape genomics. Here, we summarize the major themes of the workshop and the important take‐home points that were offered to students throughout. We emphasize increasing participation by women in population and conservation genomics as a vital step for the advancement of science. Some important themes that emerged during the workshop included the need for data visualization and its importance in finding problematic data, the effects of data filtering choices on downstream population genomic analyses, the increasing availability of whole‐genome sequencing, and the new challenges it presents. Our goal here is to help motivate and educate a worldwide audience to improve population genomic data analysis and interpretation, and thereby advance the contribution of genomics to molecular ecology, evolutionary biology, and especially to the conservation of biodiversity.

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“…An alternative approach to identify candidate loci is through landscape genomics, an emerging discipline which aims to discover genome–environment associations, making it possible to simultaneously identify potential candidate loci and the specific selective pressures acting on them (Storfer et al ., ). Briefly, genome–environment association tests identify loci (i.e.…”

Section: Introductionmentioning

confidence: 97%

Soil environment is a key driver of adaptation in Medicago truncatula: new insights from landscape genomics

et al. 2018

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Spatial differences in environmental selective pressures interact with the genomes of organisms, ultimately leading to local adaptation. Landscape genomics is an emergent research area that uncovers genome-environment associations, thus allowing researchers to identify candidate loci for adaptation to specific environmental variables. In the present study, we used latent factor mixed models (LFMMs) and Moran spectral outlier detection/randomization (MSOD-MSR) to identify candidate loci for adaptation to 10 environmental variables (climatic, soil and atmospheric) among 43 515 single nucleotide polymorphisms (SNPs) from 202 accessions of the model legume Medicago truncatula. Soil variables were associated with a large number of candidate loci identified through both LFMMs and MSOD-MSR. Genes tagged by candidate loci associated with drought and salinity are involved in the response to biotic and abiotic stresses, while those tagged by candidates associated with soil nitrogen and atmospheric nitrogen, participate in the legume-rhizobia symbiosis. Candidate SNPs identified through both LFMMs and MSOD-MSR explained up to 56% of variance in flowering traits. Our findings highlight the importance of soil in driving adaptation in the system and elucidate the basis of evolutionary potential of M. truncatula to respond to global climate change and anthropogenic disruption of the nitrogen cycle.

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Genomic Approaches in Landscape Genetics

Cited by 8 publications

References 131 publications

Invoking adaptation to decipher the genetic legacy of past climate change

Invoking adaptation to decipher the genetic legacy of past climate change

Recent advances in conservation and population genomics data analysis

Soil environment is a key driver of adaptation in Medicago truncatula: new insights from landscape genomics

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