Regarding the F‐word: The effects of data filtering on inferred genotype‐environment associations

Ahrens, Collin W.; Jordan, Rebecca; Bragg, Jason G.; Harrison, Peter A.; Hopley, Tara; Bothwell, Helen M.; Murray, Kevin; Steane, Dorothy A.; Whale, John W.; Byrne, Margaret; Andrew, Rose L.; Rymer, Paul D.

doi:10.1111/1755-0998.13351

Cited by 19 publications

(21 citation statements)

References 66 publications

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“…Spline plots were calculated from generalised dissimilarity models across the three environmental variables: (a) mean annual precipitation, (b) maximum temperature of the warmest month, and (c) topographic wetness index [Colour figure can be viewed at wileyonlinelibrary.com] a study of the Amazonian forest tree Eperua falcata (Brousseau et al, 2020), suggestive of the presence of multiple adaptation optima occurring through different genetic architectures. Similarly to our study, Brousseau et al (2020) found a substantial number of SNPs in nongenic regions of the genome that were associated with environmental variation, highlighting the ways that experimental designs including multiple spatial scales and annotated reference genomes can increase the potential for identifying false positives (Ahrens et al, 2021). A study of great tits (Parus major)…”

Section: Spatial Scale and Patterns Of Putative Selectionsupporting

confidence: 75%

“…A total of 51 SNPs were under putative selection at both spatial scales, of which 39 were genic or near-genic, associated with 28 individual genes. No SNP was identified by both LFMM and RDA at both spatial scales, highlighting the substantially different results that can be obtained depending on the choice of GEA method and spatial scale of sampling (Ahrens et al, 2021).…”

Section: Discussionmentioning

confidence: 91%

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Scale‐dependent signatures of local adaptation in a foundation tree species

et al. 2021

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Understanding local adaptation is critical for conservation management under rapidly changing environmental conditions. Local adaptation inferred from genotype‐environment associations may show different genomic patterns depending on the spatial scale of sampling, due to differences in the slope of environmental gradients and the level of gene flow. We compared signatures of local adaptation across the genome of mountain ash (Eucalyptus regnans) at two spatial scales: A species‐wide data set and a topographically‐complex subregional data set. We genotyped 367 individual trees at over 3700 single‐nucleotide polymorphisms (SNPs), quantified patterns of spatial genetic structure among populations, and used two analytical methods to identify loci associated with at least one of three environmental variables at each spatial scale. Together, the analyses identified 549 potentially adaptive SNPs at the subregion scale, and 435 SNPs at the range‐wide scale. A total of 39 genic or near‐genic SNPs, associated with 28 genes, were identified at both spatial scales, although no SNP was identified by both methods at both scales. We observed that nongenic regions had significantly higher homozygote excess than genic regions, possibly due to selective elimination of inbred genotypes during stand development. Our results suggest that strong environmental selection occurs in mountain ash, and that the identification of putatively adaptive loci can differ substantially depending on the spatial scale of analyses. We also highlight the importance of multiple adaptive genetic architectures for understanding patterns of local adaptation across large heterogenous landscapes, with comparison of putatively adaptive loci among spatial scales providing crucial insights into the process of adaptation.

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Section: Spatial Scale and Patterns Of Putative Selectionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 91%

Scale‐dependent signatures of local adaptation in a foundation tree species

et al. 2021

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“…Missing data was set to 6% across individuals (minimum of 263 individuals scored for each SNP). These thresholds were chosen because this translates to, on average, an estimation of a population-level allele frequency from nine individuals, which is adequate for EAA type of method and identifying SNPs under selection (Ahrens et al, 2021a). Linkage disequilibrium (LD) was calculated within each of the chromosomes using the function LD.Measures inLDcorSV (Mangin et al, 2012).…”

Section: Genotyping By Dartseq Platformmentioning

confidence: 99%

“…Like LFMM, BAYPASS is based on a mixed linear model to account for potentially confounding allele frequency variances due to population structure. However, the difference between the two approaches may provide a means of identifying any influence of population structure (Forester et al, 2018;Ahrens et al, 2021a).…”

Section: Environmental Association Analysismentioning

confidence: 99%

“…One limitation of EEAs is the identification of SNPs that are found to be under selection but are in fact not (false positives). While false positives are an inherent limitation in EAA studies, it is considered that they are useful in consistently identifying adaptive SNPs, even if the adaptive coefficient is small (Ahrens et al, 2021a). We focus our interpretation on SNPs that are within gene space to lessen the impact of false positives, despite that candidate SNPs identified outside of gene space could also be true positives.…”

Section: Signatures Of Adaptationmentioning

confidence: 99%

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Signatures of natural selection in a foundation tree along Mediterranean climatic gradients

Filipe

Rymer

Byrne³

et al. 2021

Preprint

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Temperature and precipitation regimes are rapidly changing, resulting in forest dieback and local extinction events, particularly in Mediterranean-type climates. Strategic forest management approaches that enhance forests’ resilience to future climates are urgently required, however adaptation to climates in heterogeneous landscapes with multiple selection pressures may be complex. For widespread trees in Mediterranean-type climates 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. To test our hypotheses, we sampled 28 populations across the geographic and climatic distribution of Eucalyptus marginata (jarrah), in south-west Western Australia, and obtained 13,534 independent single nucleotide polymorphic (SNP) markers across the genome. While overall levels of population differentiation were low (FST=0.04), environmental association analyses found a total of 2,336 unique SNPs potentially associated with five climate variables of temperature and precipitation. Allelic turnover was identified for SNPs associated with temperate seasonality and mean precipitation of the warmest quarter (39.2% and 36.9% deviance explained, respectively), suggesting that both temperature and precipitation are important factors in adaptation. SNPs within similarly function genes, according to gene ontology enrichment analysis, had analogous allelic turnover along climate gradients, while SNPs among temperature and precipitation variables had orthogonal patterns of adaptation. These contrasting patterns of adaptation provide evidence that there may be standing genomic variation adapted to changing climates, providing the substrate needed to promote adaptive management strategies to bolster forest resilience in the future.

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Reduced-representation libraries in insect genetics

Hopper

2023

Current Opinion in Insect Science

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Regarding the F‐word: The effects of data filtering on inferred genotype‐environment associations

Cited by 19 publications

References 66 publications

Scale‐dependent signatures of local adaptation in a foundation tree species

Scale‐dependent signatures of local adaptation in a foundation tree species

Signatures of natural selection in a foundation tree along Mediterranean climatic gradients

Reduced-representation libraries in insect genetics

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