Evidence for extensive parallelism but divergent genomic architecture of adaptation along altitudinal and latitudinal gradients in Populus trichocarpa

The genetic architecture of repeated local adaptation to climate in distantly related plants

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 and Arabidopsis (~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.

Integrative analysis of physiology and genomics provides insights into freeze tolerance adaptations of Acacia koa along an elevational cline

Natural selection for plant species in heterogeneous environments creates genetic variation for traits such as cold tolerance. While physiological or molecular analyses have been used to evaluate stress tolerance adaptations, combining these approaches may provide deeper insight. Acacia koa (koa) occurs from sea level to 2300 m in Hawai'i, USA. At high elevations, natural koa populations have declined due to deforestation, and freeze tolerance is a limiting factor for tree regeneration. We used physiology and molecular analyses to evaluate cold tolerance of koa populations from low (300-750 m), middle (750-1500 m), and high elevations (1500-2100 m). Half of the seedlings were cold acclimated by exposure to progressively lowered air temperatures for eight weeks (from 25.6/22.2°C to 8/4°C, day/night). Using the whole plant physiology-freezing test and koa C-repeat Binding Factor CBF genes, our results indicated that koa can be cold-acclimated when exposed to low, non-freezing temperatures. Seedlings from high elevations had consistently higher expression of Koa CBF genes associated with cold tolerance, helping to explain variation in cold-hardy phenotypes. Evaluation of the genetic background of 22 koa families across the elevations with low coverage RNA sequencing indicated that high elevation koa had relatively low values of heterozygosity, suggesting that adaptation is more likely to arise in the middle and low elevation sources. This physiology and molecular data for cold tolerance of koa across the elevation gradient of the Hawaiian Islands provides insights into natural selection processes and may help to support guidelines for conservation and seed transfer in forest restoration efforts.

Convergent genomic signatures of local adaptation across a continental-scale environmental gradient

Convergent local adaptation offers a glimpse into the role of constraint and stochasticity in adaptive evolution, in particular the extent to which similar genetic mechanisms drive adaptation to common selective forces. Here, we investigated the genomics of local adaptation in two nonsister woodpeckers that are codistributed across an entire continent and exhibit remarkably convergent patterns of geographic variation. We sequenced the genomes of 140 individuals of Downy (Dryobates pubescens) and Hairy (Dryobates villosus) woodpeckers and used a suite of genomic approaches to identify loci under selection. We showed evidence that convergent genes have been targeted by selection in response to shared environmental pressures, such as temperature and precipitation. Among candidates, we found multiple genes putatively linked to key phenotypic adaptations to climate, including differences in body size (e.g., IGFPB) and plumage (e.g., MREG). These results are consistent with genetic constraints limiting the pathways of adaptation to broad climatic gradients, even after genetic backgrounds diverge.

Speciation genomics and the role of depth in the divergence of rockfishes ( Sebastes ) revealed through Pool‐seq analysis of enriched sequences

Speciation in the marine environment is challenged by the wide geographic distribution of many taxa and potential for high rates of gene flow through larval dispersal mechanisms. Depth has recently been proposed as a potential driver of ecological divergence in fishes, and yet it is unclear how adaptation along these gradients' shapes genomic divergence. The genus Sebastes contains numerous species pairs that are depth‐segregated and can provide a better understanding of the mode and tempo of genomic diversification. Here, we present exome data on two species pairs of rockfishes that are depth‐segregated and have different degrees of divergence: S. chlorostictus–S. rosenblatti and S. crocotulus–S. miniatus. We were able to reliably identify “islands of divergence” in the species pair with more recent divergence (S. chlorostictus–S. rosenblatti) and discovered a number of genes associated with neurosensory function, suggesting a role for this pathway in the early speciation process. We also reconstructed demographic histories of divergence and found the best supported model was isolation followed by asymmetric secondary contact for both species pairs. These results suggest past ecological/geographic isolation followed by asymmetric secondary contact of deep to shallow species. Our results provide another example of using rockfish as a model for studying speciation and support the role of depth as an important mechanism for diversification in the marine environment.

Genome-Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome-environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat-based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change. "I shall endeavor to find out how nature's forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature" Alexander von Humboldt-Letter to Karl Freiesleben, June 1799.

One hundred years into the study of ecotypes, new advances are being made through large-scale field experiments in perennial plant systems

A hundred years after Turesson first clearly described how locally adaptive variation is distributed within species, plant biologists are making major breakthroughs in our understanding of mechanisms underlying adaptation from local populations to the scale of continents. Although the genetics of local adaptation has typically been studied in smaller reciprocal transplant experiments, it is now being evaluated with whole genomes in large-scale networks of common garden experiments with perennial switchgrass and poplar trees. These studies support the hypothesis that a complex combination of loci, both with and without adaptive trade-offs, underlies local adaptation and that hybridization and adaptive introgression play a key role in the evolution of these species. Future studies incorporating high-throughput phenotyping, gene expression, and modeling will be used to predict responses of these species to climate change.

Evolution of polygenic traits under global vs local adaptation

Observations about the number, frequency, effect size, and genomic distribution of alleles associated with complex traits must be interpreted in light of evolutionary process. These characteristics, which constitute a trait's genetic architecture, can dramatically affect evolutionary outcomes in applications from agriculture to medicine, and can provide a window into how evolution works. Here, I review theoretical predictions about the evolution of genetic architecture under spatially homogeneous, global adaptation as compared with spatially heterogeneous, local adaptation. Due to the tension between divergent selection and migration, local adaptation can favor "concentrated" genetic architectures that are enriched for alleles of larger effect, clustered in a smaller number of genomic regions, relative to expectations under global adaptation. However, the evolution of such architectures may be limited by many factors, including the genotypic redundancy of the trait, mutation rate, and temporal variability of environment. I review the circumstances in which predictions differ for global vs local adaptation and discuss where progress can be made in testing hypotheses using data from natural populations and lab experiments. As the field of comparative population genomics expands in scope, differences in architecture among traits and species will provide insights into how evolution works, and such differences must be interpreted in light of which kind of selection has been operating.

Genetic structure in Louisiana Iris species reveals patterns of recent and historical admixture

PREMISE

When divergent lineages come into secondary contact, reproductive isolation may be incomplete, thus providing an opportunity to investigate how speciation is manifested in the genome. The Louisiana Irises (Iris, series Hexagonae) comprise a group of three or more ecologically and reproductively divergent lineages that can produce hybrids where they come into contact. We estimated standing genetic variation to understand the current distribution of population structure in the Louisiana Irises.

METHODS

We used genotyping-by-sequencing techniques to sample the genomes of Louisiana Iris species across their ranges. We sampled 20 populations (n = 632 individuals) across 11,249 loci and used Entropy and PCA models to assess population genetic data.

RESULTS

We discovered evidence for interspecific gene flow in parts of the range. Our analysis revealed patterns of population structure at odds with widely accepted nominal taxonomy. We discovered undescribed hybrid populations, designated as belonging to the I. brevicaulis lineage. Iris nelsonii shared significant ancestry with only one of the purported parent species, I. fulva, evidence inconsistent with a hybrid origin.

CONCLUSIONS

This study provides several key findings important to the investigation of standing genetic variation in the Louisiana Iris species complex. Compared to the other nominal species, I. brevicaulis contains a large amount of genetic diversity. In addition, we discovered a previously unknown hybrid zone between I. brevicaulis and I. hexagona along the Texas coast. Finally, our results do not support the long-standing hypothesis that I. nelsonii has mixed ancestry from three parental taxa.

Molecular Parallelism Underlies Convergent Highland Adaptation of Maize Landraces

Convergent phenotypic evolution provides some of the strongest evidence for adaptation. However, the extent to which recurrent phenotypic adaptation has arisen via parallelism at the molecular level remains unresolved, as does the evolutionary origin of alleles underlying such adaptation. Here, we investigate genetic mechanisms of convergent highland adaptation in maize landrace populations and evaluate the genetic sources of recurrently selected alleles. Population branch excess statistics reveal substantial evidence of parallel adaptation at the level of individual single-nucleotide polymorphism (SNPs), genes, and pathways in four independent highland maize populations. The majority of convergently selected SNPs originated via migration from a single population, most likely in the Mesoamerican highlands, while standing variation introduced by ancient gene flow was also a contributor. Polygenic adaptation analyses of quantitative traits reveal that alleles affecting flowering time are significantly associated with elevation, indicating the flowering time pathway was targeted by highland adaptation. In addition, repeatedly selected genes were significantly enriched in the flowering time pathway, indicating their significance in adapting to highland conditions. Overall, our study system represents a promising model to study convergent evolution in plants with potential applications to crop adaptation across environmental gradients.

Repetitive genomic regions and the inference of demographic history

Inference of demographic histories using whole-genome datasets has provided insights into diversification, adaptation, hybridization, and plant-pathogen interactions, and stimulated debate on the impact of anthropogenic interventions and past climate on species demography. However, the impact of repetitive genomic regions on these inferences has mostly been ignored by masking of repeats. We use the Populus trichocarpa genome (Pop_tri_v3) to show that masking of repeat regions leads to lower estimates of effective population size (Ne) in the distant past in contrast to an increase in Ne estimates in recent times. However, in human datasets, masking of repeats resulted in lower estimates of Ne at all time points. We demonstrate that repeats affect demographic inferences using diverse methods like PSMC, MSMC, SMC++, and the Stairway plot. Our genomic analysis revealed that the biases in Ne estimates were dependent on the repeat class type and its abundance in each atomic interval. Notably, we observed a weak, yet consistently significant negative correlation between the repeat abundance of an atomic interval and the Ne estimates for that interval, which potentially reflects the recombination rate variation within the genome. The rationale for the masking of repeats has been that variants identified within these regions are erroneous. We find that polymorphisms in some repeat classes occur in callable regions and reflect reliable coalescence histories (e.g., LTR Gypsy, LTR Copia). The current demography inference methods do not handle repeats explicitly, and hence the effect of individual repeat classes needs careful consideration in comparative analysis. Deciphering the repeat demographic histories might provide a clear understanding of the processes involved in repeat accumulation.

Nothing in Evolution Makes Sense Except in the Light of Biology

A key question in biology is the predictability of the evolutionary process. If we can correctly predict the outcome of evolution, we may be better equipped to anticipate and manage species' adaptation to climate change, habitat loss, invasive species, or emerging infectious diseases, as well as improve our basic understanding of the history of life on Earth. In the present article, we ask the questions when, why, and if the outcome of future evolution is predictable. We first define predictable and then discuss two conflicting views: that evolution is inherently unpredictable and that evolution is predictable given the ability to collect the right data. We identify factors that generate unpredictability, the data that might be required to make predictions at some level of precision or at a specific timescale, and the intellectual and translational value of understanding when prediction is or is not possible.

Genomic analyses provide insights into peach local adaptation and responses to climate change

The environment has constantly shaped plant genomes, but the genetic bases underlying how plants adapt to environmental influences remain largely unknown. We constructed a high-density genomic variation map of 263 geographically representative peach landraces and wild relatives. A combination of whole-genome selection scans and genome-wide environmental association studies (GWEAS) was performed to reveal the genomic bases of peach adaptation to diverse climates. A total of 2092 selective sweeps that underlie local adaptation to both mild and extreme climates were identified, including 339 sweeps conferring genomic pattern of adaptation to high altitudes. Using genome-wide environmental association studies (GWEAS), a total of 2755 genomic loci strongly associated with 51 specific environmental variables were detected. The molecular mechanism underlying adaptive evolution of high drought, strong UVB, cold hardiness, sugar content, flesh color, and bloom date were revealed. Finally, based on 30 yr of observation, a candidate gene associated with bloom date advance, representing peach responses to global warming, was identified. Collectively, our study provides insights into molecular bases of how environments have shaped peach genomes by natural selection and adds candidate genes for future studies on evolutionary genetics, adaptation to climate changes, and breeding.

The Evolutionary Genomics of Serpentine Adaptation

Serpentine barrens are among the most challenging settings for plant life. Representing a perfect storm of hazards, serpentines consist of broadly skewed elemental profiles, including abundant toxic metals and low nutrient contents on drought-prone, patchily distributed substrates. Accordingly, plants that can tolerate the challenges of serpentine have fascinated biologists for decades, yielding important insights into adaptation to novel ecologies through physiological change. Here we highlight recent progress from studies which demonstrate the power of serpentine as a model for the genomics of adaptation. Given the moderate - but still tractable - complexity presented by the mix of hazards on serpentine, these venues are well-suited for the experimental inquiry of adaptation both in natural and manipulated conditions. Moreover, the island-like distribution of serpentines across landscapes provides abundant natural replicates, offering power to evolutionary genomic inference. Exciting recent insights into the genomic basis of serpentine adaptation point to a partly shared basis that involves sampling from common allele pools available from retained ancestral polymorphism or via gene flow. However, a lack of integrated studies deconstructing complex adaptations and linking candidate alleles with fitness consequences leaves room for much deeper exploration. Thus, we still seek the crucial direct link between the phenotypic effect of candidate alleles and their measured adaptive value - a prize that is exceedingly rare to achieve in any study of adaptation. We expect that closing this gap is not far off using the promising model systems described here.

Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate

Studying the genetics of adaptation to new environments in ecologically and industrially important tree species is currently a major research line in the fields of plant science and genetic improvement for tolerance to abiotic stress. Specifically, exploring the genomic basis of local adaptation is imperative for assessing the conditions under which trees will successfully adapt in situ to global climate change. However, this knowledge has scarcely been used in conservation and forest tree improvement because woody perennials face major research limitations such as their outcrossing reproductive systems, long juvenile phase, and huge genome sizes. Therefore, in this review we discuss predictive genomic approaches that promise increasing adaptive selection accuracy and shortening generation intervals. They may also assist the detection of novel allelic variants from tree germplasm, and disclose the genomic potential of adaptation to different environments. For instance, natural populations of tree species invite using tools from the population genomics field to study the signatures of local adaptation. Conventional genetic markers and whole genome sequencing both help identifying genes and markers that diverge between local populations more than expected under neutrality, and that exhibit unique signatures of diversity indicative of "selective sweeps." Ultimately, these efforts inform the conservation and breeding status capable of pivoting forest health, ecosystem services, and sustainable production. Key long-term perspectives include understanding how trees' phylogeographic history may affect the adaptive relevant genetic variation available for adaptation to environmental change. Encouraging "big data" approaches (machine learning-ML) capable of comprehensively merging heterogeneous genomic and ecological datasets is becoming imperative, too.

Population genomics of parallel adaptation

Parallel evolution is one of the striking patterns in nature. The presence of repeated evolution of the same phenotypes, suites of traits, and adaptations suggests a strong role for natural selection in shaping biological diversity. The reasoning is straightforward: each instance of repeated evolution makes it less likely that these features evolved neutrally or due to stochastic forces in each population or species. With the growing sequencing capability, we are now poised to examine the genetic basis of parallel evolution in model and nonmodel systems. On pages 4102-4117 of this issue of Molecular Ecology, van Boheemen and Hodgins (2020) provide an exemplar study of this kind, using common ragweed (Ambrosia artemisiifolia; Figure 1a). Their study is noteworthy and ambitious in many respects, and we think will serve as a model for studying parallel adaptation, even in nonmodel species.

Whole-exome sequencing reveals a long-term decline in effective population size of red spruce (Picea rubens)

Understanding the factors influencing the current distribution of genetic diversity across a species range is one of the main questions of evolutionary biology, especially given the increasing threat to biodiversity posed by climate change. Historical demographic processes such as population expansion or bottlenecks and decline are known to exert a predominant influence on past and current levels of genetic diversity, and revealing this demo-genetic history can have immediate conservation implications. We used a whole-exome capture sequencing approach to analyze polymorphism across the gene space of red spruce (Picea rubens Sarg.), an endemic and emblematic tree species of eastern North America high-elevation forests that are facing the combined threat of global warming and increasing human activities. We sampled a total of 340 individuals, including populations from the current core of the range in northeastern USA and southeastern Canada and from the southern portions of its range along the Appalachian Mountains, where populations occur as highly fragmented mountaintop "sky islands." Exome capture baits were designed from the closely relative white spruce (P. glauca Voss) transcriptome, and sequencing successfully captured most regions on or near our target genes, resulting in the generation of a new and expansive genomic resource for studying standing genetic variation in red spruce applicable to its conservation. Our results, based on over 2 million exome-derived variants, indicate that red spruce is structured into three distinct ancestry groups that occupy different geographic regions of its highly fragmented range. Moreover, these groups show small Ne , with a temporal history of sustained population decline that has been ongoing for thousands (or even hundreds of thousands) of years. These results demonstrate the broad potential of genomic studies for revealing details of the demographic history that can inform management and conservation efforts of nonmodel species with active restoration programs, such as red spruce.

Genetic adaptation of Tibetan poplar (Populus szechuanica var. tibetica) to high altitudes on the Qinghai-Tibetan Plateau

Plant adaptation to high altitudes has long been a substantial focus of ecological and evolutionary research. However, the genetic mechanisms underlying such adaptation remain poorly understood. Here, we address this issue by sampling, genotyping, and comparing populations of Tibetan poplar, Populus szechuanica var. tibetica, distributed from low (~2,000 m) to high altitudes (~3,000 m) of Sejila Mountain on the Qinghai-Tibet Plateau. Population structure analyses allow clear classification of two groups according to their altitudinal distributions. However, in contrast to the genetic variation within each population, differences between the two populations only explain a small portion of the total genetic variation (3.64%). We identified asymmetrical gene flow from high- to low-altitude populations. Integrating population genomic and landscape genomic analyses, we detected two hotspot regions, one containing four genes associated with altitudinal variation, and the other containing ten genes associated with response to solar radiation. These genes participate in abiotic stress resistance and regulation of reproductive processes. Our results provide insight into the genetic mechanisms underlying high-altitude adaptation in Tibetan poplar.

Genomic Signatures of Local Adaptation in Clam Shrimp (Eulimnadia texana) from Natural Vernal Pools

Vernal pools are unique in their isolation and the strong selection acting on their resident species. Vernal pool clam shrimp (Eulimnadia texana) are a promising model due to ease of culturing, short generation time, small genomes, and obligate desiccated diapaused eggs. Clam shrimp are also androdioecious (sexes include males and hermaphrodites), and here we use population-scaled recombination rates to support the hypothesis that the heterogametic sex is recombination free in these shrimp. We collected short-read sequence data from pooled samples from different vernal pools to gain insights into local adaptation. We identify genomic regions in which some populations have allele frequencies that differ significantly from the metapopulation. BayPass (Gautier M. 2015. Genome-wide scan for adaptive divergence and association with population-specific covariates. Genetics 201(4):1555-1579.) detected 19 such genomic regions showing an excess of population subdivision. These regions on average are 550 bp in size and had 2.5 genes within 5 kb of them. Genes located near these regions are involved in Malpighian tubule function and osmoregulation, an essential function in vernal pools. It is likely that salinity profiles vary between pools and over time, and variants at these genes are adapted to local salinity conditions.

Rapid repeatable phenotypic and genomic adaptation following multiple introductions

Uncovering the genomic basis of repeated adaption can provide important insights into the constraints and biases that limit the diversity of genetic responses. Demographic processes such as admixture or bottlenecks affect genetic variation underlying traits experiencing selection. The impact of these processes on the genetic basis of adaptation remains, however, largely unexamined empirically. We here test repeatability in phenotypes and genotypes along parallel climatic clines within the native North American and introduced European and Australian Ambrosia artemisiifolia ranges. To do this, we combined multiple lines of evidence from phenotype-environment associations, F_ST -like outlier tests, genotype-environment associations and genotype-phenotype associations. We used 853 individuals grown in common garden from 84 sampling locations, targeting 19 phenotypes, >83 k SNPs and 22 environmental variables. We found that 17%-26% of loci with adaptive signatures were repeated among ranges, despite alternative demographic histories shaping genetic variation and genetic associations. Our results suggest major adaptive changes can occur on short timescales, with seemingly minimum impacts due to demographic changes linked to introduction. These patterns reveal some predictability of evolutionary change during range expansion, key in a world facing ongoing climate change, and rapid invasive spread.

Environmental Genome-Wide Association Reveals Climate Adaptation Is Shaped by Subtle to Moderate Allele Frequency Shifts in Loblolly Pine

Understanding the genomic basis of local adaptation is crucial to determine the potential of long-lived woody species to withstand changes in their natural environment. In the past, efforts to dissect the genomic architecture in gymnosperms species have been limited due to the absence of reference genomes. Recently, the genomes of some commercially important conifers, such as loblolly pine, have become available, allowing whole-genome studies of these species. In this study, we test for associations between 87k SNPs, obtained from whole-genome resequencing of loblolly pine individuals, and 270 environmental variables and combinations of them. We determine the geographic location of significant loci and identify their genomic location using our newly constructed ultradense 26k SNP linkage map. We found that water availability is the main climatic variable shaping local adaptation of the species, and found 821 SNPs showing significant associations with climatic variables or combinations of them based on the consistent results of three different genotype–environment association methods. Our results suggest that adaptation to climate in the species might have occurred by many changes in the frequency of alleles with moderate to small effect sizes, and by the smaller contribution of large effect alleles in genes related to moisture deficit, temperature and precipitation. Genomic regions of low recombination and high population differentiation harbored SNPs associated with groups of environmental variables, suggesting climate adaptation might have evolved as a result of different selection pressures acting on groups of genes associated with an aspect of climate rather than on individual environmental variables.

Phenotypic and Genomic Local Adaptation across Latitude and Altitude in Populus trichocarpa

Local adaptation to climate allows plants to cope with temporally and spatially heterogeneous environments, and parallel phenotypic clines provide a natural experiment to uncover the genomic architecture of adaptation. Though extensive effort has been made to investigate the genomic basis of local adaptation to climate across the latitudinal range of tree species, less is known for altitudinal clines. We used exome capture to genotype 451 Populus trichocarpa genotypes across altitudinal and latitudinal gradients spanning the natural species range, and phenotyped these trees for a variety of adaptive traits in two common gardens. We observed clinal variation in phenotypic traits across the two transects, which indicates climate-driven selection, and coupled gene-based genotype–phenotype and genotype–environment association scans to identify imprints of climatic adaptation on the genome. Although many of the phenotype- and climate-associated genes were unique to one transect, we found evidence of parallelism between latitude and altitude, as well as significant convergence when we compared our outlier genes with those putatively involved in climatic adaptation in two gymnosperm species. These results suggest that not only genomic constraint during adaptation to similar environmental gradients in poplar but also different environmental contexts, spatial scale, and perhaps redundant function among potentially adaptive genes and polymorphisms lead to divergent adaptive architectures.

Genetic diversity and population structure of black cottonwood (Populus deltoides) revealed using simple sequence repeat markers

Background

Black cottonwood (Populus deltoides) is one of the keystone forest tree species, and has become the main breeding parents in poplar hybrid breeding. However, the genetic diversity and population structure of the introduced resources are not fully understood.

Results

In the present study, five loci containing null alleles were excluded and 15 pairs of SSR (simple sequence repeat) primers were used to analyze the genetic diversity and population structure of 384 individuals from six provenances (Missouri, Iowa, Washington, Louisiana, and Tennessee (USA), and Quebec in Canada) of P. deltoides. Ultimately, 108 alleles (N_a) were detected; the expected heterozygosity (H_e) per locus ranged from 0.070 to 0.905, and the average polymorphic information content (PIC) was 0.535. The provenance ‘Was’ had a relatively low genetic diversity, while ‘Que’, ‘Lou’, and ‘Ten’ provenances had high genetic diversity, with Shannon’s information index (I) above 1.0. The mean coefficient of genetic differentiation (F_st) and gene flow (N_m) were 0.129 and 1.931, respectively. Analysis of molecular variance (AMOVA) showed that 84.88% of the genetic variation originated from individuals. Based on principal coordinate analysis (PCoA) and STRUCTURE cluster analysis, individuals distributed in the Mississippi River Basin were roughly classified as one group, while those distributed in the St. Lawrence River Basin and Columbia River Basin were classified as another group. The cluster analysis based on the population level showed that provenance ‘Iow’ had a small gene flow and high degree of genetic differentiation compared with the other provenances, and was classified into one group. There was a significant relationship between genetic distance and geographical distance.

Conclusions

P. deltoides resources have high genetic diversity and there is a moderate level of genetic differentiation among provenances. Geographical isolation and natural conditions may be the main factors causing genetic differences among individuals. Individuals reflecting population genetic information can be selected to build a core germplasm bank. Meanwhile, the results could provide theoretical support for the scientific management and efficient utilization of P. deltoides genetic resources, and promote the development of molecular marker-assisted breeding of poplar.

Exome resequencing and GWAS for growth, ecophysiology, and chemical and metabolomic composition of wood of Populus trichocarpa

Background

Populus trichocarpa is an important forest tree species for the generation of lignocellulosic ethanol. Understanding the genomic basis of biomass production and chemical composition of wood is fundamental in supporting genetic improvement programs. Considerable variation has been observed in this species for complex traits related to growth, phenology, ecophysiology and wood chemistry. Those traits are influenced by both polygenic control and environmental effects, and their genome architecture and regulation are only partially understood. Genome wide association studies (GWAS) represent an approach to advance that aim using thousands of single nucleotide polymorphisms (SNPs). Genotyping using exome capture methodologies represent an efficient approach to identify specific functional regions of genomes underlying phenotypic variation.

Results

We identified 813 K SNPs, which were utilized for genotyping 461 P. trichocarpa clones, representing 101 provenances collected from Oregon and Washington, and established in California. A GWAS performed on 20 traits, considering single SNP-marker tests identified a variable number of significant SNPs (p-value < 6.1479E-8) in association with diameter, height, leaf carbon and nitrogen contents, and δ¹⁵N. The number of significant SNPs ranged from 2 to 220 per trait. Additionally, multiple-marker analyses by sliding-windows tests detected between 6 and 192 significant windows for the analyzed traits. The significant SNPs resided within genes that encode proteins belonging to different functional classes as such protein synthesis, energy/metabolism and DNA/RNA metabolism, among others.

Conclusions

SNP-markers within genes associated with traits of importance for biomass production were detected. They contribute to characterize the genomic architecture of P. trichocarpa biomass required to support the development and application of marker breeding technologies.

Multitrait genome-wide association analysis of Populus trichocarpa identifies key polymorphisms controlling morphological and physiological traits

Genome-wide association studies (GWAS) have great promise for identifying the loci that contribute to adaptive variation, but the complex genetic architecture of many quantitative traits presents a substantial challenge. We measured 14 morphological and physiological traits and identified single nucleotide polymorphism (SNP)-phenotype associations in a Populus trichocarpa population distributed from California, USA to British Columbia, Canada. We used whole-genome resequencing data of 882 trees with more than 6.78 million SNPs, coupled with multitrait association to detect polymorphisms with potentially pleiotropic effects. Candidate genes were validated with functional data. Broad-sense heritability (H² ) ranged from 0.30 to 0.56 for morphological traits and 0.08 to 0.36 for physiological traits. In total, 4 and 20 gene models were detected using the single-trait and multitrait association methods, respectively. Several of these associations were corroborated by additional lines of evidence, including co-expression networks, metabolite analyses, and direct confirmation of gene function through RNAi. Multitrait association identified many more significant associations than single-trait association, potentially revealing pleiotropic effects of individual genes. This approach can be particularly useful for challenging physiological traits such as water-use efficiency or complex traits such as leaf morphology, for which we were able to identify credible candidate genes by combining multitrait association with gene co-expression and co-methylation data.

Ancient introgression drives adaptation to cooler and drier mountain habitats in a cypress species complex

Introgression may act as an important source of new genetic variation to facilitate the adaptation of organisms to new environments, yet how introgression might enable tree species to adapt to higher latitudes and elevations remains unclear. Applying whole-transcriptome sequencing and population genetic analyses, we present an example of ancient introgression from a cypress species (Cupressus gigantea) that occurs at higher latitude and elevation on the Qinghai-Tibet Plateau into a related species (C. duclouxiana), which has likely aided the latter species to extend its range by colonizing cooler and drier mountain habitats during postglacial periods. We show that 16 introgressed candidate adaptive loci could have played pivotal roles in response to diverse stresses experienced in a high-elevation environment. Our findings provide new insights into the evolutionary history of Qinghai-Tibet Plateau plants and the importance of introgression in the adaptation of species to climate change.

Hybridization between pollination syndromes as an ecological and evolutionary resource

In plants, pollination syndromes (the correlated presence of many features of relevance to pollination mode, for instance pollination by a particular animal clade) are a striking feature of plant biodiversity, providing great floral phenotypic diversity (Fenster et al. ). Adaptation to a particular animal pollinator provides an explanation for why recently diverged plants can have such extreme differentiation in floral form. One might expect such elaborate adaptations to provide a high degree of pollinator specificity and hence reproductive isolation, but there are many cases where substantial gene flow exists between extreme floral morphs (see Table 1), and the resulting hybrids may be highly fertile. This gene flow provides tremendous opportunities to study the genetics and biology of the pollination syndromes by providing intermediate forms and segregating genotypes. If it is true that pollination syndromes result from adaptation under strong selection, we will expect such flowers to be crucibles of natural selection. If strong selection for particular floral phenotypes can be shown, then this, when coupled with hybridization, will give us one of the most valuable of all experimental systems for evolutionary research: gene flow and selection in balance. In this issue of Molecular Ecology, the paper of Milano et al. () delivers this. It shows that in populations of the Ipomopsis aggregata complex, gene flow between pollination morphs is high and selection to stabilize those morphs is also high: a probable case of gene flow-selection balance.

Parallel colonization of subalpine habitats in the central European mountains by Primula elatior

The island-like distribution of subalpine habitats across mountain ranges can trigger the parallel evolution of locally adapted ecotypes. Such naturally replicated scenarios allow testing hypotheses on how elevational differentiation structures genetic diversity within species. Nevertheless, the parallel colonization of subalpine habitats across different mountain ranges has only rarely been documented with molecular data. We chose Primula elatior (Primulaceae), naturally spanning entire elevation range in multiple mountain regions of central Europe, to test for the origin of its scattered subalpine populations. Nuclear microsatellite variation revealed three genetic groups corresponding with the distinct study regions. We found that genetic differentiation between foothill and subalpine populations within each region was relatively low, suggesting that the colonization of subalpine habitats occurred independently within each mountain range. Furthermore, the strongest differentiation was usually found between the subalpine populations suggesting that mountain ridges may act as migration barriers that can reduce gene flow more strongly than elevational differences between foothill and subalpine populations. Finally, we found that subalpine colonization did not result in a loss of genetic diversity relative to foothill populations in agreement with the high migration rates that we document here between the subalpine and the foothill populations. In summary, our study shows subalpine Primula elatior populations are genetically diverse and distinct results of parallel colonization events from multiple foothill gene pools.

Using Genomic Data to Infer Historic Population Dynamics of Nonmodel Organisms

Genome sequence data are now being routinely obtained from many nonmodel organisms. These data contain a wealth of information about the demographic history of the populations from which they originate. Many sophisticated statistical inference procedures have been developed to infer the demographic history of populations from this type of genomic data. In this review, we discuss the different statistical methods available for inference of demography, providing an overview of the underlying theory and logic behind each approach. We also discuss the types of data required and the pros and cons of each method. We then discuss how these methods have been applied to a variety of nonmodel organisms. We conclude by presenting some recommendations for researchers looking to use genomic data to infer demographic history.

Population genomics of parallel evolution in gene expression and gene sequence during ecological adaptation

Natural selection often produces parallel phenotypic changes in response to a similar adaptive challenge. However, the extent to which parallel gene expression differences and genomic divergence underlie parallel phenotypic traits and whether they are decoupled or not remains largely unexplored. We performed a population genomic study of parallel ecological adaptation among replicate ecotype pairs of the rough periwinkle (Littorina saxatilis) at a regional geographical scale (NW Spain). We show that genomic changes underlying parallel phenotypic divergence followed a complex pattern of both repeatable differences and of differences unique to specific ecotype pairs, in which parallel changes in expression or sequence are restricted to a limited set of genes. Yet, the majority of divergent genes were divergent either for gene expression or coding sequence, but not for both simultaneously. Overall, our findings suggest that divergent selection significantly contributed to the process of parallel molecular differentiation among ecotype pairs, and that changes in expression and gene sequence underlying phenotypic divergence could, at least to a certain extent, be considered decoupled processes.

Functional and evolutionary genomic inferences in Populus through genome and population sequencing of American and European aspen

We performed de novo, full-genome sequence analysis of two Populus species, North American quaking and Eurasian trembling aspen, that contain striking levels of genetic variation. Our results showed that positive and negative selection broadly affects patterns of genomic variation, but to varying degrees across coding and noncoding regions. The strength of selection and rates of sequence divergence were strongly related to differences in gene expression and coexpression network connectivity. These results highlight the importance of both positive and negative selection in shaping genome-wide levels of genetic variation in an obligately outcrossing, perennial plant. The resources we present establish aspens as a powerful study system enabling future studies for understanding the genomic determinants of adaptive evolution.

The Populus genus is one of the major plant model systems, but genomic resources have thus far primarily been available for poplar species, and primarily Populus trichocarpa (Torr. & Gray), which was the first tree with a whole-genome assembly. To further advance evolutionary and functional genomic analyses in Populus, we produced genome assemblies and population genetics resources of two aspen species, Populus tremula L. and Populus tremuloides Michx. The two aspen species have distributions spanning the Northern Hemisphere, where they are keystone species supporting a wide variety of dependent communities and produce a diverse array of secondary metabolites. Our analyses show that the two aspens share a similar genome structure and a highly conserved gene content with P. trichocarpa but display substantially higher levels of heterozygosity. Based on population resequencing data, we observed widespread positive and negative selection acting on both coding and noncoding regions. Furthermore, patterns of genetic diversity and molecular evolution in aspen are influenced by a number of features, such as expression level, coexpression network connectivity, and regulatory variation. To maximize the community utility of these resources, we have integrated all presented data within the PopGenIE web resource (PopGenIE.org).

Quantifying how constraints limit the diversity of viable routes to adaptation

Convergent adaptation occurs at the genome scale when independently evolving lineages use the same genes to respond to similar selection pressures. These patterns of genetic repeatability provide insights into the factors that facilitate or constrain the diversity of genetic responses that contribute to adaptive evolution. A first step in studying such factors is to quantify the observed amount of repeatability relative to expectations under a null hypothesis. Here, we formulate a novel index to quantify the constraints driving the observed amount of repeated adaptation in pairwise contrasts based on the hypergeometric distribution, and then generalize this for simultaneous analysis of multiple lineages. This index is explicitly based on the probability of observing a given amount of repeatability by chance under a given null hypothesis and is readily compared among different species and types of trait. We also formulate an index to quantify the effective proportion of genes in the genome that have the potential to contribute to adaptation. As an example of how these indices can be used to draw inferences, we assess the amount of repeatability observed in existing datasets on adaptation to stress in yeast and climate in conifers. This approach provides a method to test a wide range of hypotheses about how different kinds of factors can facilitate or constrain the diversity of genetic responses observed during adaptive evolution.

How many ways can evolution solve the same adaptive problem? While convergent adaptation is evident in many organisms at the phenotypic level, we are only beginning to understand how commonly this convergence extends to the genome scale. Quantifying the repeatability of adaptation at the genome scale is therefore critical for assessing how constraints affect the diversity of viable genetic responses. Here, we develop probability-based indices to quantify the deviation between observed repeatability and expectations under a range of null hypotheses, and an estimator of the proportion of loci in the genome that can contribute to adaptation. We demonstrate the usage of these indices with individual-based simulations and example datasets from yeast and conifers and discuss how they differ from previously developed approaches to studying repeatability. Because these indices are unitless, they provide a general approach to quantifying and comparing how constraints drive convergence at the genome scale across a wide range of traits and taxa.

Trait differentiation and adaptation of plants along elevation gradients

Studies of genetic adaptation in plant populations along elevation gradients in mountains have a long history, but there has until now been neither a synthesis of how frequently plant populations exhibit adaptation to elevation nor an evaluation of how consistent underlying trait differences across species are. We reviewed studies of adaptation along elevation gradients (i) from a meta-analysis of phenotypic differentiation of three traits (height, biomass and phenology) from plants growing in 70 common garden experiments; (ii) by testing elevation adaptation using three fitness proxies (survival, reproductive output and biomass) from 14 reciprocal transplant experiments; (iii) by qualitatively assessing information at the molecular level, from 10 genomewide surveys and candidate gene approaches. We found that plants originating from high elevations were generally shorter and produced less biomass, but phenology did not vary consistently. We found significant evidence for elevation adaptation in terms of survival and biomass, but not for reproductive output. Variation in phenotypic and fitness responses to elevation across species was not related to life history traits or to environmental conditions. Molecular studies, which have focussed mainly on loci related to plant physiology and phenology, also provide evidence for adaptation along elevation gradients. Together, these studies indicate that genetically based trait differentiation and adaptation to elevation are widespread in plants. We conclude that a better understanding of the mechanisms underlying adaptation, not only to elevation but also to environmental change, will require more studies combining the ecological and molecular approaches.

Horizontal gene cluster transfer increased hallucinogenic mushroom diversity

Secondary metabolites are a heterogeneous class of chemicals that often mediate interactions between species. The tryptophan‐derived secondary metabolite, psilocin, is a serotonin receptor agonist that induces altered states of consciousness. A phylogenetically disjunct group of mushroom‐forming fungi in the Agaricales produce the psilocin prodrug, psilocybin. Spotty phylogenetic distributions of fungal compounds are sometimes explained by horizontal transfer of metabolic gene clusters among unrelated fungi with overlapping niches. We report the discovery of a psilocybin gene cluster in three hallucinogenic mushroom genomes, and evidence for its horizontal transfer between fungal lineages. Patterns of gene distribution and transmission suggest that synthesis of psilocybin may have provided a fitness advantage in the dung and late wood‐decay fungal niches, which may serve as reservoirs of fungal indole‐based metabolites that alter behavior of mycophagous and wood‐eating invertebrates. These hallucinogenic mushroom genomes will serve as models in neurochemical ecology, advancing the (bio)prospecting and synthetic biology of novel neuropharmaceuticals.

Specialized plant biochemistry drives gene clustering in fungi

The fitness and evolution of prokaryotes and eukaryotes are affected by the organization of their genomes. In particular, the physical clustering of genes can coordinate gene expression and can prevent the breakup of co-adapted alleles. Although clustering may thus result from selection for phenotype optimization and persistence, the impact of environmental selection pressures on eukaryotic genome organization has rarely been systematically explored. Here, we investigated the organization of fungal genes involved in the degradation of phenylpropanoids, a class of plant-produced secondary metabolites that mediate many ecological interactions between plants and fungi. Using a novel gene cluster detection method, we identified 1110 gene clusters and many conserved combinations of clusters in a diverse set of fungi. We demonstrate that congruence in genome organization over small spatial scales is often associated with similarities in ecological lifestyle. Additionally, we find that while clusters are often structured as independent modules with little overlap in content, certain gene families merge multiple modules into a common network, suggesting they are important components of phenylpropanoid degradation strategies. Together, our results suggest that phenylpropanoids have repeatedly selected for gene clustering in fungi, and highlight the interplay between genome organization and ecological evolution in this ancient eukaryotic lineage.

Development of Target Sequence Capture and Estimation of Genomic Relatedness in a Mixed Oak Stand

Anticipating the evolutionary responses of long-lived organisms, such as trees, to environmental changes, requires the assessment of genetic variation of adaptive traits in natural populations. To this end, high-density markers are needed to calculate genomic relatedness between individuals allowing to estimate the genetic variance of traits in wild populations. We designed a targeted capture-based, next-generation sequencing assay based on the highly heterozygous pedunculate oak (Quercus robur) reference genome, for the sequencing of 3 Mb of genic and intergenic regions. Using a mixed stand of 293 Q. robur and Q. petraea genotypes we successfully captured over 97% of the target sequences, corresponding to 0.39% of the oak genome, with sufficient depth (97×) for the detection of about 190,000 SNPs evenly spread over the targeted regions. We validated the technique by evaluating its reproducibility, and comparing the genomic relatedness of trees with their known pedigree relationship. We explored the use of the technique on other related species and highlighted the advantages and limitations of this approach. We found that 92.07% of target sequences in Q. suber and 70.36% of sequences in Fagus sylvatica were captured. We used this SNP resource to estimate genetic relatedness in the mixed oak stand. Mean pairwise genetic relatedness was low within each species with a few values exceeding 0.25 (half-sibs) or 0.5 (full-sibs). Finally, we applied the technique to a long-standing issue in population genetics of trees regarding the relationship between inbreeding and components of fitness. We found very weak signals for inbreeding depression for reproductive success and no signal for growth within both species.

Comparison of Single Genome and Allele Frequency Data Reveals Discordant Demographic Histories

Inference of demographic history from genetic data is a primary goal of population genetics of model and nonmodel organisms. Whole genome-based approaches such as the pairwise/multiple sequentially Markovian coalescent methods use genomic data from one to four individuals to infer the demographic history of an entire population, while site frequency spectrum (SFS)-based methods use the distribution of allele frequencies in a sample to reconstruct the same historical events. Although both methods are extensively used in empirical studies and perform well on data simulated under simple models, there have been only limited comparisons of them in more complex and realistic settings. Here we use published demographic models based on data from three human populations (Yoruba, descendants of northwest-Europeans, and Han Chinese) as an empirical test case to study the behavior of both inference procedures. We find that several of the demographic histories inferred by the whole genome-based methods do not predict the genome-wide distribution of heterozygosity, nor do they predict the empirical SFS. However, using simulated data, we also find that the whole genome methods can reconstruct the complex demographic models inferred by SFS-based methods, suggesting that the discordant patterns of genetic variation are not attributable to a lack of statistical power, but may reflect unmodeled complexities in the underlying demography. More generally, our findings indicate that demographic inference from a small number of genomes, routine in genomic studies of nonmodel organisms, should be interpreted cautiously, as these models cannot recapitulate other summaries of the data.

Population genomics of the eastern cottonwood (Populus deltoides)

Despite its economic importance as a bioenergy crop and key role in riparian ecosystems, little is known about genetic diversity and adaptation of the eastern cottonwood (Populus deltoides). Here, we report the first population genomics study for this species, conducted on a sample of 425 unrelated individuals collected in 13 states of the southeastern United States. The trees were genotyped by targeted resequencing of 18,153 genes and 23,835 intergenic regions, followed by the identification of single nucleotide polymorphisms (SNPs). This natural P. deltoides population showed low levels of subpopulation differentiation (F_ST = 0.022–0.106), high genetic diversity (θ_W = 0.00100, π = 0.00170), a large effective population size (N_e ≈ 32,900), and low to moderate levels of linkage disequilibrium. Additionally, genomewide scans for selection (Tajima's D), subpopulation differentiation (X^TX), and environmental association analyses with eleven climate variables carried out with two different methods (LFMM and BAYENV2) identified genes putatively involved in local adaptation. Interestingly, many of these genes were also identified as adaptation candidates in another poplar species, Populus trichocarpa, indicating possible convergent evolution. This study constitutes the first assessment of genetic diversity and local adaptation in P. deltoides throughout the southern part of its range, information we expect to be of use to guide management and breeding strategies for this species in future, especially in the face of climate change.

Water availability drives signatures of local adaptation in whitebark pine (Pinus albicaulis Engelm.) across fine spatial scales of the Lake Tahoe Basin, USA

Patterns of local adaptation at fine spatial scales are central to understanding how evolution proceeds, and are essential to the effective management of economically and ecologically important forest tree species. Here, we employ single and multilocus analyses of genetic data (n = 116 231 SNPs) to describe signatures of fine-scale adaptation within eight whitebark pine (Pinus albicaulis Engelm.) populations across the local extent of the environmentally heterogeneous Lake Tahoe Basin, USA. We show that despite highly shared genetic variation (F_ST  = 0.0069), there is strong evidence for adaptation to the rain shadow experienced across the eastern Sierra Nevada. Specifically, we build upon evidence from a common garden study and find that allele frequencies of loci associated with four phenotypes (mean = 236 SNPs), 18 environmental variables (mean = 99 SNPs), and those detected through genetic differentiation (n = 110 SNPs) exhibit significantly higher signals of selection (covariance of allele frequencies) than could be expected to arise, given the data. We also provide evidence that this covariance tracks environmental measures related to soil water availability through subtle allele frequency shifts across populations. Our results replicate empirical support for theoretical expectations of local adaptation for populations exhibiting strong gene flow and high selective pressures and suggest that ongoing adaptation of many P. albicaulis populations within the Lake Tahoe Basin will not be constrained by the lack of genetic variation. Even so, some populations exhibit low levels of heritability for the traits presumed to be related to fitness. These instances could be used to prioritize management to maintain adaptive potential. Overall, we suggest that established practices regarding whitebark pine conservation be maintained, with the additional context of fine-scale adaptation.

Novel Insights into Tree Biology and Genome Evolution as Revealed Through Genomics

Reference genome sequences are the key to the discovery of genes and gene families that determine traits of interest. Recent progress in sequencing technologies has enabled a rapid increase in genome sequencing of tree species, allowing the dissection of complex characters of economic importance, such as fruit and wood quality and resistance to biotic and abiotic stresses. Although the number of reference genome sequences for trees lags behind those for other plant species, it is not too early to gain insight into the unique features that distinguish trees from nontree plants. Our review of the published data suggests that, although many gene families are conserved among herbaceous and tree species, some gene families, such as those involved in resistance to biotic and abiotic stresses and in the synthesis and transport of sugars, are often expanded in tree genomes. As the genomes of more tree species are sequenced, comparative genomics will further elucidate the complexity of tree genomes and how this relates to traits unique to trees.

The genomic basis of adaptation in plants

Plants are powerful models for the study of adaptive evolution. Since they are rooted in place, they must directly face environmental insults, making adaptation to local conditions vital. In addition to adaptation to natural conditions, some plant species have held a central role in human subsistence over the past several thousand years. In these species, humans exerted strong selective pressures on traits of agricultural importance. Recently, an increasing number of studies have aimed to identify the genomic basis of adaptation. These studies have provided insights into the mechanisms through which the raw materials of adaptation were introduced as well as the modes of adaptation in wild and domesticated species.

Advances in ecological genomics in forest trees and applications to genetic resources conservation and breeding

Forest trees are an unparalleled group of organisms in their combined ecological, economic and societal importance. With widespread distributions, predominantly random mating systems and large population sizes, most tree species harbour extensive genetic variation both within and among populations. At the same time, demographic processes associated with Pleistocene climate oscillations and land-use change have affected contemporary range-wide diversity and may impinge on the potential for future adaptation. Understanding how these adaptive and neutral processes have shaped the genomes of trees species is therefore central to their management and conservation. As for many other taxa, the advent of high-throughput sequencing methods is expected to yield an understanding of the interplay between the genome and environment at a level of detail and depth not possible only a few years ago. An international conference entitled 'Genomics and Forest Tree Genetics' was held in May 2016, in Arcachon (France), and brought together forest geneticists with a wide range of research interests to disseminate recent efforts that leverage contemporary genomic tools to probe the population, quantitative and evolutionary genomics of trees. An important goal of the conference was to discuss how such data can be applied to both genome-enabled breeding and the conservation of forest genetic resources under land use and climate change. Here, we report discoveries presented at the meeting and discuss how the ecological genomic toolkit can be used to address both basic and applied questions in tree biology.

Photoperiod- and temperature-mediated control of phenology in trees - a molecular perspective

Contents 511 I. 511 II. 512 III. 513 IV. 513 V. 517 VI. 517 VII. 521 VIII. 521 Acknowledgements 521 References 521 SUMMARY: Trees growing in boreal and temperate regions synchronize their growth with seasonal climatic changes in adaptive responses that are essential for their survival. These trees cease growth before the winter and establish a dormant state during which growth cessation is maintained by repression of responses to growth-promotive signals. Reactivation of growth in the spring follows the release from dormancy promoted by prolonged exposure to low temperature during the winter. The timing of the key events and regulation of the molecular programs associated with the key stages of the annual growth cycle are controlled by two main environmental cues: photoperiod and temperature. Recently, key components mediating photoperiodic control of growth cessation and bud set have been identified, and striking similarities have been observed in signaling pathways controlling growth cessation in trees and floral transition in Arabidopsis. Although less well understood, the regulation of bud dormancy and bud burst may involve cell-cell communication and chromatin remodeling. Here, we discuss current knowledge of the molecular-level regulation of the annual growth cycle of woody trees in temperate and boreal regions, and identify key questions that need to be addressed in the future.

Landscape genomics reveals altered genome wide diversity within revegetated stands of Eucalyptus microcarpa (Grey Box)

In order to contribute to evolutionary resilience and adaptive potential in highly modified landscapes, revegetated areas should ideally reflect levels of genetic diversity within and across natural stands. Landscape genomic analyses enable such diversity patterns to be characterized at genome and chromosomal levels. Landscape-wide patterns of genomic diversity were assessed in Eucalyptus microcarpa, a dominant tree species widely used in revegetation in Southeastern Australia. Trees from small and large patches within large remnants, small isolated remnants and revegetation sites were assessed across the now highly fragmented distribution of this species using the DArTseq genomic approach. Genomic diversity was similar within all three types of remnant patches analysed, although often significantly but only slightly lower in revegetation sites compared with natural remnants. Differences in diversity between stand types varied across chromosomes. Genomic differentiation was higher between small, isolated remnants, and among revegetated sites compared with natural stands. We conclude that small remnants and revegetated sites of our E. microcarpa samples largely but not completely capture patterns in genomic diversity across the landscape. Genomic approaches provide a powerful tool for assessing restoration efforts across the landscape.

Towards integration of population and comparative genomics in forest trees

Contents 338 I. 338 II. 339 III. 340 IV. 342 343 References 343 SUMMARY: The past decade saw the initiation of an ongoing revolution in sequencing technologies that is transforming all fields of biology. This has been driven by the advent and widespread availability of high-throughput, massively parallel short-read sequencing (MPS) platforms. These technologies have enabled previously unimaginable studies, including draft assemblies of the massive genomes of coniferous species and population-scale resequencing. Transcriptomics studies have likewise been transformed, with RNA-sequencing enabling studies in nonmodel organisms, the discovery of previously unannotated genes (novel transcripts), entirely new classes of RNAs and previously unknown regulatory mechanisms. Here we touch upon current developments in the areas of genome assembly, comparative regulomics and population genetics as they relate to studies of forest tree species.