Predicting genotype environmental range from genome–environment associations

Abstract

Genome-environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single-locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random single nucleotide polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity-associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress-aridity conditions and could be used to improve the resistance of cultivated varieties to aridity.

Local adaptation across a complex bioclimatic landscape in two montane bumble bee species

“…Like many species facing environmental change, the distributions of numerous bumble bee species are contracting (Cameron et al, ; Goulson, Lye, & Darvill, ; Kerr et al, ), driven in part by mismatches with local climate niches (Kerr et al, ). The distribution of adaptive genomic variation within species ranges may be crucial for resilience to climate change (Fitzpatrick & Keller, ; Manel et al, ), with wild bees of special interest because of the implications for pollination services (Garibaldi et al, ). Understanding climate adaptation in bumble bees, and similarities between species, will provide insights relevant for conserving intra‐ and interspecific diversity in this group.…”

Incorporating putatively neutral and adaptive genomic data into marine conservation planning

“…The second metric, adaptive score ( S adapt ) (Manel et al. 2018) was calculated for each individual as the proportion of alleles positively associated with mean bottom temperature divided by 2 C , where C is the number of candidate SNPs. In our case, individuals with high adaptive scores are expected to have higher fitness under warmer conditions and populations containing a high proportion of these individuals are thus considered to exhibit high potential for local adaptation under a scenario of increasing temperature, which we refer to as predicted “adaptedness.” To obtain a within‐site value, we estimated the mean adaptive score over all individuals within a site.…”

Latitudinal variation in climate‐associated genes imperils range edge populations

“…This is difficult for nonmodel species due to a lack of information about adaptive traits and their distribution across geographical and climatic ranges. The rapidly growing field of landscape genomics circumvents some of the issues of experimentally measuring adaptation in wild populations (Grummer et al., 2019; Manel et al., 2018; Schoville et al., 2012). Landscape genomics integrates spatial and environmental analyses of population genomic data across heterogeneous landscapes to address previously intractable questions, such as forecasting of adaptive capacity (Grummer et al., 2019).…”