Quantifying heritability and estimating evolutionary potential in the wild when individuals that share genes also share environments.

Accurate heritability estimates for fitness-related traits are required to predict an organism's ability to respond to global change. Heritability estimates are theoretically expected to be inflated if, due to limited dispersal, individuals that share genes are also likely to share similar environments. However, if relatives occupy similar environments due, at least partly, to genetic variation for habitat selection, then accounting for environmental similarity in quantitative genetic models may result in diminished heritability estimates in wild populations. This potential issue has been pointed out in the literature, but has not been evaluated by empirical studies. Here, we investigate whether environmental similarity among individuals can be partly explained by genetic variation for habitat selection, and how this link potentially blurs estimates for heritability in fitness-related traits. Using intensive GPS monitoring, we quantified home-range habitat composition for 293 roe deer inhabiting a heterogeneous landscape to assess environmental similarity. To investigate if environmental similarity might harbour genetic variation, we combined genome-wide data in a quantitative genetic framework to evaluate genetic variation for home-range habitat composition, which is partly the result of habitat selection at settlement. Finally, we explored how environmental similarity affects heritability estimates for behaviours related to the risk avoidance-resource acquisition trade-off (i.e. being in open habitat and distance to roads) and proxies of individual performance (i.e. body mass and hind foot length). We found substantial heritability for home-range habitat composition, with estimates ranging from 0.40 (proportion of meadows) to 0.85 (proportion of refuge habitat). Accounting for similarity in habitat composition between relatives decreased the heritability estimates for both behavioural and morphological traits (reduction ranging from 55% to 100% and from 22% to 41% respectively). As a consequence, only half of these heritability estimates remained significantly different from zero. Our results show that similar genotypes occupy similar environments, which could lead to heritable variation being incorrectly attributed to environmental effects. To accurately distinguish the sources of phenotypic variation and predict the ability of organisms to respond to global change, it is necessary to develop quantitative genetic studies investigating the mechanisms underpinning environmental similarity among relatives.

Pedigree-free quantitative genetic approach provides evidence for heritability of movement tactics in wild roe deer.

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.

Wild snapdragon plant pedigree sheds light on limited connectivity enhanced by higher migrant reproductive success in a fragmented landscape.

Background: In contrast with historical knowledge, a recent view posits that a non-negligible proportion of populations thrive in a fragmented landscape. One underlying mechanism is the maintenance of functional connectivity, i.e., the net flow of individuals or their genes moving among suitable habitat patches. Alternatively, functional connectivity might be typically limited but enhanced by a higher reproductive success of migrants. Methods: We tested for this hypothesis in wild snapdragon plants inhabiting six patches separated by seawater in a fragmented Mediterranean scrubland landscape. We reconstructed their pedigree by using a parentage assignment method based on microsatellite genetic markers. We then estimated functional connectivity and the reproductive success of plants resulting from between-patch dispersal events. Results: We found that wild snapdragon plants thrived in this fragmented landscape, although functional connectivity between habitat patches was low (i.e. 2.9%). The progeny resulting from between-patch dispersal events had a higher reproductive success than residents. Conclusion: Our findings imply that low functional connectivity in a fragmented landscapes may have been enhanced by higher reproductive success after migration. This original mechanisms might be partly compensating the negative impact of fragmentation.

RAD-sequencing for estimating genomic relatedness matrix-based heritability in the wild: A case study in roe deer.

Estimating the evolutionary potential of quantitative traits and reliably predicting responses to selection in wild populations are important challenges in evolutionary biology. The genomic revolution has opened up opportunities for measuring relatedness among individuals with precision, enabling pedigree-free estimation of trait heritabilities in wild populations. However, until now, most quantitative genetic studies based on a genomic relatedness matrix (GRM) have focused on long-term monitored populations for which traditional pedigrees were also available, and have often had access to knowledge of genome sequence and variability. Here, we investigated the potential of RAD-sequencing for estimating heritability in a free-ranging roe deer (Capreolous capreolus) population for which no prior genomic resources were available. We propose a step-by-step analytical framework to optimize the quality and quantity of the genomic data and explore the impact of the single nucleotide polymorphism (SNP) calling and filtering processes on the GRM structure and GRM-based heritability estimates. As expected, our results show that sequence coverage strongly affects the number of recovered loci, the genotyping error rate and the amount of missing data. Ultimately, this had little effect on heritability estimates and their standard errors, provided that the GRM was built from a minimum number of loci (above 7,000). Genomic relatedness matrix-based heritability estimates thus appear robust to a moderate level of genotyping errors in the SNP data set. We also showed that quality filters, such as the removal of low-frequency variants, affect the relatedness structure of the GRM, generating lower h2 estimates. Our work illustrates the huge potential of RAD-sequencing for estimating GRM-based heritability in virtually any natural population.