Single-Locus versus Multilocus Patterns of Local Adaptation to Climate in Eastern White Pine (Pinus strobus, Pinaceae)

Genetic Diversity, Structure and Effective Population Size of Old-Growth vs. Second-Growth Populations of Keystone and Long-Lived Conifer, Eastern White Pine (Pinus strobus): Conservation Value and Climate Adaptation Potential

Whether old-growth (OG) forests have higher genetic diversity and effective population size, consequently higher conservation value and climate adaptive potential than second-growth (SG) forests, remain an unresolved issue. We have tested the hypothesis that old-growth forest tree populations have higher genetic diversity, effective population size (NE ), climate adaptive potential and conservation value and lower genetic differentiation than second-growth forest tree populations, employing a keystone and long-lived conifer, eastern white pine (EWP; Pinus strobus). Genetic diversity and population structure of old-growth and second-growth populations of eastern white pine (EWP) were examined using microsatellites of the nuclear and chloroplast genomes and single nucleotide polymorphisms (SNPs) in candidate nuclear genes putatively involved in adaptive responses to climate and underlying multilocus genetic architecture of local adaptation to climate in EWP. Old-growth and second-growth EWP populations had statistically similar genetic diversity, inbreeding coefficient and inter-population genetic differentiation based on nuclear microsatellites (nSSRs) and SNPs. However, old-growth populations had significantly higher chloroplast microsatellites (cpSSRs) haploid diversity than second-growth populations. Old-growth EWP populations had significantly higher coalescence-based historical long-term NE than second-growth EWP populations, but the linkage disequilibrium (LD)-based contemporary NE estimates were statistically similar between the old-growth and second-growth EWP populations. Analyses of population genetic structure and inter-population genetic relationships revealed some genetic constitution differences between the old-growth and second-growth EWP populations. Overall, our results suggest that old-growth and second-growth EWP populations have similar genetic resource conservation value. Because old-growth and second-growth EWP populations have similar levels of genetic diversity in genes putatively involved in adaptive responses to climate, old-growth, and second-growth populations may have similar adaptive potential under climate change. Our results could potentially be generalized across most of the boreal and temperate conifer forest trees. Our study contributes to address a long-standing issue, advances research field and knowledge about conservation and ecological and climate adaptation of forest trees.

Candidate gene SNP variation in floodplain populations of pedunculate oak (Quercus robur L.) near the species' southern range margin: Weak differentiation yet distinct associations with water availability

Populations residing near species' low-latitude range margins (LLMs) often occur in warmer and drier environments than those in the core range. Thus, their genetic composition could be shaped by climatic drivers that differ from those occurring at higher latitudes, resulting in potentially adaptive variants of conservation value. Such variants could facilitate the adaptation of populations from other portions of the geographical range to similar future conditions anticipated under ongoing climate change. However, very few studies have assessed standing genetic variation at potentially adaptive loci in natural LLM populations. We investigated standing genetic variation at single nucleotide polymorphisms (SNPs) located within 117 candidate genes and its links to putative climatic selection pressures across 19 pedunculate oak (Quercus robur L.) populations distributed along a regional climatic gradient near the species' southern range margin in southeastern Europe. These populations are restricted to floodplain forests along large lowland rivers, whose hydric regime is undergoing significant shifts under modern rapid climate change. The populations showed very weak geographical structure, suggesting extensive genetic connectivity and gene flow or shared ancestry. We identified eight (6.2%) positive F_ST -outlier loci, and genotype-environment association analyses revealed consistent associations between SNP allele frequencies and several climatic variables linked to water availability. A total of 61 associations involving 37 SNPs (28.5%) from 35 annotated genes provided important insights into putative functional mechanisms in our system. Our findings provide empirical support for the role of LLM populations as sources of potentially adaptive variation that could enhance species' resilience to climate change-related pressures.

Knowledge status and sampling strategies to maximize cost-benefit ratio of studies in landscape genomics of wild plants

To avoid local extinction due to the changes in their natural ecosystems, introduced by anthropogenic activities, species undergo local adaptation. Landscape genomics approach, through genome–environment association studies, has helped evaluate the local adaptation in natural populations. Landscape genomics, is still a developing discipline, requiring refinement of guidelines in sampling design, especially for studies conducted in the backdrop of stark socioeconomic realities of the rainforest ecologies, which are global biodiversity hotspots. In this study we aimed to devise strategies to improve the cost-benefit ratio of landscape genomics studies by surveying sampling designs and genome sequencing strategies used in existing studies. We conducted meta-analyses to evaluate the importance of sampling designs, in terms of (i) number of populations sampled, (ii) number of individuals sampled per population, (iii) total number of individuals sampled, and (iv) number of SNPs used in different studies, in discerning the molecular mechanisms underlying local adaptation of wild plant species. Using the linear mixed effects model, we demonstrated that the total number of individuals sampled and the number of SNPs used, significantly influenced the detection of loci underlying the local adaptation. Thus, based on our findings, in order to optimize the cost-benefit ratio of landscape genomics studies, we suggest focusing on increasing the total number of individuals sampled and using a targeted (e.g. sequencing capture) Pool-Seq approach and/or a random (e.g. RAD-Seq) Pool-Seq approach to detect SNPs and identify SNPs under selection for a given environmental cline. We also found that the existing molecular evidences are inadequate in predicting the local adaptations to climate change in tropical forest ecosystems.

Gene Flow and Genetic Variation Explain Signatures of Selection across a Climate Gradient in Two Riparian Species

Many species occur across environmental gradients and it is expected that these species will exhibit some signals of adaptation as heterogeneous environments and localized gene flow may facilitate local adaptation. While riparian zones can cross climate gradients, many of which are being impacted by climate change, they also create microclimates for the vegetation, reducing environmental heterogeneity. Species with differing distributions in these environments provide an opportunity to investigate the importance of genetic connectivity in influencing signals of adaptation over relatively short geographical distance. Association analysis with genomic data was used to compare signals of selection to climate variables in two species that have differing distributions along a river traversing a climate gradient. Results demonstrate links between connectivity, standing genetic variation, and the development of signals of selection. In the restricted species, the combination of high gene flow in the middle and lower catchment and occurrence in a microclimate created along riverbanks likely mitigated the development of selection to most climatic variables. In contrast the more widely distributed species with low gene flow showed a stronger signal of selection. Together these results strengthen our knowledge of the drivers and scale of adaptation and reinforce the importance of connectivity across a landscape to maintain adaptive potential of plant species.

Tree rings provide a new class of phenotypes for genetic associations that foster insights into adaptation of conifers to climate change

Local adaptation in tree species has been documented through a long history of common garden experiments where functional traits (height, bud phenology) are used as proxies for fitness. However, the ability to identify genes or genomic regions related to adaptation to climate requires the evaluation of traits that precisely reflect how and when climate exerts selective constraints. We combine dendroecology with association genetics to establish a link between genotypes, phenotypes and interannual climatic fluctuations. We illustrate this approach by examining individual tree responses embedded in the annual rings of 233 Pinus strobus trees growing in a common garden experiment representing 38 populations from the majority of its range. We found that interannual variability in growth was affected by low temperatures during spring and autumn, and by summer heat and drought. Among-population variation in climatic sensitivity was significantly correlated with the mean annual temperature of the provenance, suggesting local adaptation. Genotype-phenotype associations using these new tree-ring phenotypes validated nine candidate genes identified in a previous genetic-environment association study. Combining dendroecology with association genetics allowed us to assess tree vulnerability to past climate at fine temporal scales and provides avenues for future genomic studies on functional adaptation in forest trees.

The search for loci under selection: trends, biases and progress

Detecting genetic variants under selection using F_ST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field-based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP-based selection studies and help to progress landscape and evolutionary genomics.

Genetic Diversity and Population Structure of Whitebark Pine (Pinus albicaulis Engelm.) in Western North America

Whitebark pine (WBP, Pinus albicaulis Engelm.) is an endangered conifer species due to heavy mortality from white pine blister rust (WPBR, caused by Cronartium ribicola) and mountain pine beetle (Dendroctonus ponderosae). Information about genetic diversity and population structure is of fundamental importance for its conservation and restoration. However, current knowledge on the genetic constitution and genomic variation is still limited for WBP. In this study, an integrated genomics approach was applied to characterize seed collections from WBP breeding programs in western North America. RNA-seq analysis was used for de novo assembly of the WBP needle transcriptome, which contains 97,447 protein-coding transcripts. Within the transcriptome, single nucleotide polymorphisms (SNPs) were discovered, and more than 22,000 of them were non-synonymous SNPs (ns-SNPs). Following the annotation of genes with ns-SNPs, 216 ns-SNPs within candidate genes with putative functions in disease resistance and plant defense were selected to design SNP arrays for high-throughput genotyping. Among these SNP loci, 71 were highly polymorphic, with sufficient variation to identify a unique genotype for each of the 371 individuals originating from British Columbia (Canada), Oregon and Washington (USA). A clear genetic differentiation was evident among seed families. Analyses of genetic spatial patterns revealed varying degrees of diversity and the existence of several genetic subgroups in the WBP breeding populations. Genetic components were associated with geographic variables and phenotypic rating of WPBR disease severity across landscapes, which may facilitate further identification of WBP genotypes and gene alleles contributing to local adaptation and quantitative resistance to WPBR. The WBP genomic resources developed here provide an invaluable tool for further studies and for exploitation and utilization of the genetic diversity preserved within this endangered conifer and other five-needle pines.

The challenge of separating signatures of local adaptation from those of isolation by distance and colonization history: The case of two white pines

Accurately detecting signatures of local adaptation using genetic‐environment associations (GEAs) requires controlling for neutral patterns of population structure to reduce the risk of false positives. However, a high degree of collinearity between climatic gradients and neutral population structure can greatly reduce power, and the performance of GEA methods in such case is rarely evaluated in empirical studies. In this study, we attempted to disentangle the effects of local adaptation and isolation by environment (IBE) from those of isolation by distance (IBD) and isolation by colonization from glacial refugia (IBC) using range‐wide samples in two white pine species. For this, SNPs from 168 genes, including 52 candidate genes for growth and phenology, were genotyped in 133 and 61 populations of Pinus strobus and P. monticola, respectively. For P. strobus and using all 153 SNPs, climate (IBE) did not significantly explained among‐population variation when controlling for IBD and IBC in redundancy analyses (RDAs). However, 26 SNPs were significantly associated with climate in single‐locus GEA analyses (Bayenv2 and LFMM), suggesting that local adaptation took place in the presence of high gene flow. For P. monticola, we found no evidence of IBE using RDAs and weaker signatures of local adaptation using GEA and F_ST outlier tests, consistent with adaptation via phenotypic plasticity. In both species, the majority of the explained among‐population variation (69 to 96%) could not be partitioned between the effects of IBE, IBD, and IBC. GEA methods can account differently for this confounded variation, and this could explain the small overlap of SNPs detected between Bayenv2 and LFMM. Our study illustrates the inherent difficulty of taking into account neutral structure in natural populations and the importance of sampling designs that maximize climatic variation, while minimizing collinearity between climatic gradients and neutral structure.