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Abstract Stomata play a critical role in regulating plant responses to climate. Where sister species differ in stomatal traits, interspecific gene flow can influence the evolutionary trajectory of trait variation, with consequences to adaptation.Leveraging six latitudinally-distributed transects spanning the natural hybrid zone betweenPopulus trichocarpa–P. balsamifera, we used whole genome resequencing and replicate common garden experiments to test the role that interspecific gene flow and selection play to stomatal trait evolution.While species-specific differences in the distribution of stomata persist betweenP. balsamiferaandP. trichocarpa, hybrids on average resembledP. trichocarpa. Admixture mapping identified several candidate genes associated with stomatal trait variation in hybrids includingTWIST, a homolog ofSPEECHLESSinArabidopsis, that initiates stomatal development via asymmetric cell divisions. Geographic clines revealed candidate genes deviating from genome-wide average patterns of introgression, suggesting restricted gene flow and the maintenance of adaptive differences. Climate associations, particularly with precipitation, indicated selection shapes local ancestry at candidate genes across transects.These results highlight the role of climate in shaping stomatal trait evolution inPopulusand demonstrate how interspecific gene flow creates novel genetic combinations that may enhance adaptive potential in changing environments. 

Abstract Co-adaptation of cytoplasmic and nuclear genomes are critical to physiological function for many species. Despite this understanding, hybridization can disrupt co-adaptation leading to a mismatch between maternally-inherited cytoplasmic genomes and biparentally inherited nuclear genomes. Few studies have examined the consequences of cytonuclear interactions to physiological function across environments. Here, we quantify the degree of co-introgression between chloroplast and nuclear-chloroplast (N-cp) genes across repeated hybrid zones and its consequences to physiological function across environments. We use whole-genome resequencing and common garden experiments with clonally replicated genotypes sampled across the natural hybrid zone betweenPopulus trichocarpaandP. balsamifera. We use geographic clines to test for co-introgression of the chloroplast genome with N-cp and non-interacting nuclear genes. Co-introgression of chloroplast and N-cp genes was limited although contact zone-specific patterns suggest that local environments may influence co-introgression. Combining ancestry estimates with phenotypic data across common gardens revealed that mismatches between chloroplast and nuclear ancestry can influence physiological performance, but the strength and direction of these effects vary depending on the environment. Overall, this study highlights the importance of cytonuclear interactions to adaptation, and the role of environment in modifying the effect of those interactions. 

Abstract In a rapidly changing environment, predicting changes in the growth and survival of local populations can inform conservation and management. Plastic responses vary as a result of genetic differentiation within and among species, so accurate rangewide predictions require characterization of genotype-specific reaction norms across the continuum of historic and future climate conditions comprising a species’ range. Natural hybrid zones can give rise to novel recombinant genotypes associated with high phenotypic variability, further increasing the variance of plastic responses within the ranges of the hybridizing species. Experiments that plant replicated genotypes across a range of environments can characterize genotype-specific reaction norms; identify genetic, geographic, and climatic factors affecting variation in climate responses; and make predictions of climate responses across complex genetic and geographic landscapes. The North American hybrid zone ofPopulus trichocarpaandP. balsamiferarepresents a natural system in which reaction norms are likely to vary with underlying genetic variation that has been shaped by climate, geography, and introgression. Here, we leverage a dataset containing 45 clonal genotypes of varying ancestry from this natural hybrid zone, planted across 17 replicated common garden experiments spanning a broad climatic range, including sites warmer than the natural species ranges. Growth and mortality were measured over two years, enabling us to model reaction norms for each genotype across these tested environments. Genomic variation associated with species ancestry and northern/southern regions significantly influenced growth across environments, with genotypic variation in reaction norms reflecting a trade-off between cold tolerance and growth. Using modeled reaction norms for each genotype, we predicted that genotypes with moreP. trichocarpaancestry may gain an advantage under warmer climates. Spatial shifts of the hybrid zone could facilitate the spread of beneficial alleles into novel climates. These results highlight that genotypic variation in responses to temperature will have landscape-level effects. 

Abstract Closely related species often use the same genes to adapt to similar environments. However, we know little about why such genes possess increased adaptive potential and whether this is conserved across deeper evolutionary lineages. Adaptation to climate presents a natural laboratory to test these ideas, as even distantly related species must contend with similar stresses. Here, we re-analyse genomic data from thousands of individuals from 25 plant species as diverged as lodgepole pine andArabidopsis(~300 Myr). We test for genetic repeatability based on within-species associations between allele frequencies in genes and variation in 21 climate variables. Our results demonstrate significant statistical evidence for genetic repeatability across deep time that is not expected under randomness, identifying a suite of 108 gene families (orthogroups) and gene functions that repeatedly drive local adaptation to climate. This set includes many orthogroups with well-known functions in abiotic stress response. Using gene co-expression networks to quantify pleiotropy, we find that orthogroups with stronger evidence for repeatability exhibit greater network centrality and broader expression across tissues (higher pleiotropy), contrary to the ‘cost of complexity’ theory. These gene families may be important in helping wild and crop species cope with future climate change, representing important candidates for future study. 

Abstract Population demographic changes, alongside landscape, geographic and climate heterogeneity, can influence the timing, stability and extent of introgression where species hybridise. Thus, quantifying interactions across diverged lineages, and the relative contributions of interspecific genetic exchange and selection to divergence at the genome‐wide level is needed to better understand the drivers of hybrid zone formation and maintenance. We used seven latitudinally arrayed transects to quantify the contributions of climate, geography and landscape features to broad patterns of genetic structure across the hybrid zone ofPopulus trichocarpaandP. balsamiferaand evaluated the demographic context of hybridisation over time. We found genetic structure differed among the seven transects. While ancestry was structured by climate, landscape features influenced gene flow dynamics. Demographic models indicated a secondary contact event may have influenced contemporary hybrid zone formation with the origin of a putative hybrid lineage that inhabits regions with higher aridity than either of the ancestral groups. Phylogenetic relationships based on chloroplast genomes support the origin of this hybrid lineage inferred from demographic models based on the nuclear data. Our results point towards the importance of climate and landscape patterns in structuring the contact zones betweenP. trichocarpaandP. balsamiferaand emphasise the value whole genome sequencing can have to advancing our understanding of how neutral processes influence divergence across space and time. 

Abstract Changes in telomere length are increasingly used to indicate species' response to environmental stress across diverse taxa. Despite this broad use, few studies have explored telomere length in plants. Thus, evaluation of new approaches for measuring telomeres in plants is needed. Rapid advances in sequencing approaches and bioinformatic tools now allow estimation of telomere content from whole‐genome sequencing (WGS) data, a proxy for telomere length. While telomere content has been quantified extensively using quantitative polymerase chain reaction (qPCR) and WGS in humans, no study to date has compared the effectiveness of WGS in estimating telomere length in plants relative to qPCR approaches. In this study, we use 100Populusclones re‐sequenced using short‐read Illumina sequencing to quantify telomere length comparing three different bioinformatic approaches (Computel, K‐seek and TRIP) in addition to qPCR. Overall, telomere length estimates varied across different bioinformatic approaches, but were highly correlated across methods for individual genotypes. A positive correlation was observed between WGS estimates and qPCR, however, Computel estimates exhibited the greatest correlation. Computel incorporates genome coverage into telomere length calculations, suggesting that genome coverage is likely important to telomere length quantification when using WGS data. Overall, telomere estimates from WGS provided greater precision and accuracy of telomere length estimates relative to qPCR. The findings suggest WGS is a promising approach for assessing telomere length and, as the field of telomere ecology evolves, may provide added value to assaying response to biotic and abiotic environments for plants needed to accelerate plant breeding and conservation management. 

Abstract Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF‐predicted environmental association of adapted alleles and a new environment (GF Offset) is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here, we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic “population genetic” model with a single environmentally adapted locus; and (3) a polygenic “quantitative genetic” model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation. 

Black cottonwood (Populus trichocarpa) is a species of economic interest and an outstanding study model. The aspen borer (Saperda calcarata) causes irreversible damage to poplars and other riparian species in North America. The insect can produce multiple effects ranging from the presence of some galleries in the stem to tree death. Despite the ecological and commercial importance of this tree–insect interaction, the genetic mechanisms underlying the response of P. trichocarpa to S. calcarata are scarcely understood. In this study, a common garden trial of P. trichocarpa provenances, established in Davis, California, was assessed at the second year of growth, regarding the infestation of S. calcarata from a natural outbreak. A genome-wide association study (GWAS) was conducted using 629k of exonic SNPs to assess the relationship between genomic variation and insect attack. Tree architecture, in terms of stem number per plant, and the wood metabolome were also included. Insect attack was independent of the number of stems per tree. The performed GWAS identified three significantly associated SNP markers (q-value < 0.2) belonging to the same number of gene models, encoding proteins involved in signal transduction mechanisms and secondary metabolite production, including that of R-mandelonitrile lyase, Chromodomain-helicase-DNA-binding family protein, and Leucine-rich repeat protein. These results are aligned with the current knowledge of defensive pathways in plants and trees, helping to expand the understanding of the defensive response mechanisms of black cottonwood against wood borer insects.