Genome-wide patterns of differentiation and spatially varying selection between postglacial recolonization lineages of Populus alba (Salicaceae), a widespread forest tree

The genomic and epigenetic footprint of local adaptation to variable climates in kiwifruit

A full understanding of adaptive genetic variation at the genomic level will help address questions of how organisms adapt to diverse climates. Actinidia eriantha is a shade-tolerant species, widely distributed in the southern tropical region of China, occurring in spatially heterogeneous environments. In the present study we combined population genomic, epigenomic, and environmental association analyses to infer population genetic structure and positive selection across a climatic gradient, and to assess genomic offset to climatic change for A. eriantha. The population structure is strongly shaped by geography and influenced by restricted gene flow resulting from isolation by distance due to habitat fragmentation. In total, we identified 102 outlier loci and annotated 455 candidate genes associated with the genomic basis of climate adaptation, which were enriched in functional categories related to development processes and stress response; both temperature and precipitation are important factors driving adaptive variation. In addition to single-nucleotide polymorphisms (SNPs), a total of 27 single-methylation variants (SMVs) had significant correlation with at least one of four climatic variables and 16 SMVs were located in or adjacent to genes, several of which were predicted to be involved in plant response to abiotic or biotic stress. Gradient forest analysis indicated that the central/east populations were predicted to be at higher risk of future population maladaptation under climate change. Our results demonstrate that local climate factors impose strong selection pressures and lead to local adaptation. Such information adds to our understanding of adaptive mechanisms to variable climates revealed by both population genome and epigenome analysis.

Improving Coconut Using Modern Breeding Technologies: Challenges and Opportunities

Coconut (Cocos nucifera L.) is a perennial palm with a wide range of distribution across tropical islands and coastlines. Multitude use of coconut by nature is important in the socio-economic fabric framework among rural smallholders in producing countries. It is a major source of income for 30 million farmers, while 60 million households rely on the coconut industry directly as farm workers and indirectly through the distribution, marketing, and processing of coconut and coconut-based products. Stagnant production, inadequate planting materials, the effects of climate change, as well as pests and diseases are among the key issues that need to be urgently addressed in the global coconut industry. Biotechnology has revolutionized conventional breeding approaches in creating genetic variation for trait improvement in a shorter period of time. In this review, we highlighted the challenges of current breeding strategies and the potential of biotechnological approaches, such as genomic-assisted breeding, next-generation sequencing (NGS)-based genotyping and genome editing tools in improving the coconut. Also, combining these technologies with high-throughput phenotyping approaches and speed breeding could speed up the rate of genetic gain in coconut breeding to solve problems that have been plaguing the industry for decades.

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.

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.

Predicting Thermal Adaptation by Looking Into Populations' Genomic Past

Molecular evolution offers an insightful theory to interpret the genomic consequences of thermal adaptation to previous events of climate change beyond range shifts. However, disentangling often mixed footprints of selective and demographic processes from those due to lineage sorting, recombination rate variation, and genomic constrains is not trivial. Therefore, here we condense current and historical population genomic tools to study thermal adaptation and outline key developments (genomic prediction, machine learning) that might assist their utilization for improving forecasts of populations' responses to thermal variation. We start by summarizing how recent thermal-driven selective and demographic responses can be inferred by coalescent methods and in turn how quantitative genetic theory offers suitable multi-trait predictions over a few generations via the breeder's equation. We later assume that enough generations have passed as to display genomic signatures of divergent selection to thermal variation and describe how these footprints can be reconstructed using genome-wide association and selection scans or, alternatively, may be used for forward prediction over multiple generations under an infinitesimal genomic prediction model. Finally, we move deeper in time to comprehend the genomic consequences of thermal shifts at an evolutionary time scale by relying on phylogeographic approaches that allow for reticulate evolution and ecological parapatric speciation, and end by envisioning the potential of modern machine learning techniques to better inform long-term predictions. We conclude that foreseeing future thermal adaptive responses requires bridging the multiple spatial scales of historical and predictive environmental change research under modern cohesive approaches such as genomic prediction and machine learning frameworks.

Identification of winter moth (Operophtera brumata) refugia in North Africa and the Italian Peninsula during the last glacial maximum

Numerous studies have shown that the genetic diversity of species inhabiting temperate regions has been shaped by changes in their distributions during the Quaternary climatic oscillations. For some species, the genetic distinctness of isolated populations is maintained during secondary contact, while for others, admixture is frequently observed. For the winter moth (Operophtera brumata), an important defoliator of oak forests across Europe and northern Africa, we previously determined that contemporary populations correspond to genetic diversity obtained during the last glacial maximum (LGM) through the use of refugia in the Iberian and Aegean peninsulas, and to a lesser extent the Caucasus region. Missing from this sampling were populations from the Italian peninsula and from North Africa, both regions known to have played important roles as glacial refugia for other species. Therefore, we genotyped field-collected winter moth individuals from southern Italy and northwestern Tunisia-the latter a region where severe oak forest defoliation by winter moth has recently been reported-using polymorphic microsatellite. We reconstructed the genetic relationships of these populations in comparison to moths previously sampled from the Iberian and Aegean peninsulas, the Caucasus region, and western Europe using genetic distance, Bayesian clustering, and approximate Bayesian computation (ABC) methods. Our results indicate that both the southern Italian and the Tunisian populations are genetically distinct from other sampled populations, and likely originated in their respective refugium during the LGM after diverging from a population that eventually settled in the Iberian refugium. These suggest that winter moth populations persisted in at least five Mediterranean LGM refugia. Finally, we comment that outbreaks by winter moth in northwestern Tunisia are not the result of a recent introduction of a nonnative species, but rather are most likely due to land use or environmental changes.

Searching for Sympatric Speciation in the Genomic Era

Sympatric speciation illustrates how natural and sexual selection may create new species in isolation without geographic barriers. However, recent genomic reanalyses of classic examples of sympatric speciation reveal complex histories of secondary gene flow from outgroups into the radiation. In contrast, the rich theoretical literature on this process distinguishes among a diverse range of models based on simple genetic histories and different types of reproductive isolating barriers. Thus, there is a need to revisit how to connect theoretical models of sympatric speciation and their predictions to empirical case studies in the face of widespread gene flow. Here, theoretical differences among different types of sympatric speciation and speciation-with-gene-flow models are reviewed and summarized, and genomic analyses are proposed for distinguishing which models apply to case studies based on the timing and function of adaptive introgression. Investigating whether secondary gene flow contributed to reproductive isolation is necessary to test whether predictions of theory are ultimately borne out in nature.

Comparing Pool-seq, Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost-effective sequencing approaches, namely Pool-seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping-by-sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool-seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool-seq data showed F ST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar F ST estimates, indicating that individual-based approaches provided more congruent results than Pool-seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost-effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.

Identification of Arabis alpina genomic regions associated with climatic variables along an elevation gradient through whole genome scan

We performed a pooled whole-genome sequencing on samples of the alpine plant Arabis alpina, harvested in ten populations along an elevation gradient in the French Alps. A large dataset of genetic variations was produced as single nucleotide polymorphisms (SNPs). A combined genome scan approach enabled detecting genomic regions associated with a synthetic environmental variable characterizing the climate at each sampling location. Positive loci detected by two methods were retained and belong to 19 regions in the Arabis alpina genome. The most significant region harbors an ortholog of the AtNAC062 gene, encoding a membrane-bound transcription factor described as linking the cold response and pathogen resistance that may confer protection to plants under extended snow coverage at high elevations. Other genes involved in the stress response or in flowering regulation were also detected. Altogether, our results indicated that Arabis alpina represent a suitable model for studying genomic adaptation in alpine perennial plants.

Allele Frequency Difference AFD⁻An Intuitive Alternative to FST for Quantifying Genetic Population Differentiation

Measuring the magnitude of differentiation between populations based on genetic markers is commonplace in ecology, evolution, and conservation biology. The predominant differentiation metric used for this purpose is F_ST. Based on a qualitative survey, numerical analyses, simulations, and empirical data, I here argue that F_ST does not express the relationship to allele frequency differentiation between populations generally considered interpretable and desirable by researchers. In particular, F_ST (1) has low sensitivity when population differentiation is weak, (2) is contingent on the minor allele frequency across the populations, (3) can be strongly affected by asymmetry in sample sizes, and (4) can differ greatly among the available estimators. Together, these features can complicate pattern recognition and interpretation in population genetic and genomic analysis, as illustrated by empirical examples, and overall compromise the comparability of population differentiation among markers and study systems. I argue that a simple differentiation metric displaying intuitive properties, the absolute allele frequency difference AFD, provides a valuable alternative to F_ST. I provide a general definition of AFD applicable to both bi- and multi-allelic markers and conclude by making recommendations on the sample sizes needed to achieve robust differentiation estimates using AFD.

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).

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.

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.

Genome scans for divergent selection in natural populations of the widespread hardwood species Eucalyptus grandis (Myrtaceae) using microsatellites

Identification of loci or genes under natural selection is important for both understanding the genetic basis of local adaptation and practical applications, and genome scans provide a powerful means for such identification purposes. In this study, genome-wide simple sequence repeats markers (SSRs) were used to scan for molecular footprints of divergent selection in Eucalyptus grandis, a hardwood species occurring widely in costal areas from 32° S to 16° S in Australia. High population diversity levels and weak population structure were detected with putatively neutral genomic SSRs. Using three FST outlier detection methods, a total of 58 outlying SSRs were collectively identified as loci under divergent selection against three non-correlated climatic variables, namely, mean annual temperature, isothermality and annual precipitation. Using a spatial analysis method, nine significant associations were revealed between FST outlier allele frequencies and climatic variables, involving seven alleles from five SSR loci. Of the five significant SSRs, two (EUCeSSR1044 and Embra394) contained alleles of putative genes with known functional importance for response to climatic factors. Our study presents critical information on the population diversity and structure of the important woody species E. grandis and provides insight into the adaptive responses of perennial trees to climatic variations.

Adaptive evolution and segregating load contribute to the genomic landscape of divergence in two tree species connected by episodic gene flow

Speciation often involves repeated episodes of genetic contact between divergent populations before reproductive isolation (RI) is complete. Whole-genome sequencing (WGS) holds great promise for unravelling the genomic bases of speciation. We have studied two ecologically divergent, hybridizing species of the 'model tree' genus Populus (poplars, aspens, cottonwoods), Populus alba and P. tremula, using >8.6 million single nucleotide polymorphisms (SNPs) from WGS of population pools. We used the genomic data to (i) scan these species' genomes for regions of elevated and reduced divergence, (ii) assess key aspects of their joint demographic history based on genomewide site frequency spectra (SFS) and (iii) infer the potential roles of adaptive and deleterious coding mutations in shaping the genomic landscape of divergence. We identified numerous small, unevenly distributed genome regions without fixed polymorphisms despite high overall genomic differentiation. The joint SFS was best explained by ancient and repeated gene flow and allowed pinpointing candidate interspecific migrant tracts. The direction of selection (DoS) differed between genes in putative migrant tracts and the remainder of the genome, thus indicating the potential roles of adaptive divergence and segregating deleterious mutations on the evolution and breakdown of RI. Genes affected by positive selection during divergence were enriched for several functionally interesting groups, including well-known candidate 'speciation genes' involved in plant innate immunity. Our results suggest that adaptive divergence affects RI in these hybridizing species mainly through intrinsic and demographic processes. Integrating genomic with molecular data holds great promise for revealing the effects of particular genetic pathways on speciation.

Effects of hybridization and evolutionary constraints on secondary metabolites: the genetic architecture of phenylpropanoids in European populus species

The mechanisms responsible for the origin, maintenance and evolution of plant secondary metabolite diversity remain largely unknown. Decades of phenotypic studies suggest hybridization as a key player in generating chemical diversity in plants. Knowledge of the genetic architecture and selective constraints of phytochemical traits is key to understanding the effects of hybridization on plant chemical diversity and ecological interactions. Using the European Populus species P. alba (White poplar) and P. tremula (European aspen) and their hybrids as a model, we examined levels of inter- and intraspecific variation, heritabilities, phenotypic correlations, and the genetic architecture of 38 compounds of the phenylpropanoid pathway measured by liquid chromatography and mass spectrometry (UHPLC-MS). We detected 41 quantitative trait loci (QTL) for chlorogenic acids, salicinoids and flavonoids by genetic mapping in natural hybrid crosses. We show that these three branches of the phenylpropanoid pathway exhibit different geographic patterns of variation, heritabilities, and genetic architectures, and that they are affected differently by hybridization and evolutionary constraints. Flavonoid abundances present high species specificity, clear geographic structure, and strong genetic determination, contrary to salicinoids and chlorogenic acids. Salicinoids, which represent important defence compounds in Salicaceae, exhibited pronounced genetic correlations on the QTL map. Our results suggest that interspecific phytochemical differentiation is concentrated in downstream sections of the phenylpropanoid pathway. In particular, our data point to glycosyltransferase enzymes as likely targets of rapid evolution and interspecific differentiation in the 'model forest tree' Populus.