Abiotic Stress Tolerance Boosted by Genetic Diversity in Plants.

Plant breeding [...].

Molecular Genetics Enhances Plant Breeding.

Human-driven plant selection, a practice as ancient as agriculture itself, has laid the foundations of plant breeding and contemporary farming [...].

Whole Transcriptome Sequencing Unveils the Genomic Determinants of Putative Somaclonal Variation in Mint (Mentha L.).

Mint (Mentha L., Lamiaceae) is a strongly scented herb of the family Lamiaceae that is grown mostly by clonal propagation, making it a valuable species for the study of somaclonal variation and its phenotypic consequences. The recent introduction of a few species of mint in South America, followed by a presumably rampant propagation, make this region particularly ideal for studying the extent of somaclonal genetic diversity. Hence, the objective of this work was to offer a preliminary characterization of somaclonal genetically coding diversity of the mint in the northern Andes in order to address the question of whether somaclonal variants may have emerged despite relatively recent introductions in a region where mint is not native. A total of 29 clonally propagated specimens, collected in mint export farms in the province of Antioquia, a major region for mint production in the northwest Andes of Colombia, were genotyped using RNA sequencing (RNA-Seq). SNP calling was carried out from the leaves' transcriptome profiles of each plant by combining the GATK4 and TRINITY protocols, obtaining a total of 2033 loci across 912 transcripts with a minimum read depth of 20X and 4% of missing data. Unsupervised machine learning algorithms considered the K-means, AGNES and UPGMA approaches, all of which suggested three genetic clusters for M. spicata and a unique cluster for M. × piperita. The results indicate that at least two different origins of M. spicata reached the eastern region of the Antioquia province, clonally propagated in the locality ever since for local consumption and export. One of these ancestries had more population structure, possibly due to environmental or anthropological pressures that intervened in the fragmentation of this genetic group or to a higher somaclonal mutation rate. This work offers a first step into the study of the accumulation and transmission of presumably quasi-neutral somatic mutations at coding regions in an herbaceous clonally propagated scented species such as mint, likely favored by an expected population expansion after its Andean introduction. These ad hoc hypotheses warrant further study as part of future research.

On how role versatility boosts an STI.

The prevalence of the HIV-1 infection has decayed in the last decades in western heterosexual populations. However, among men who have sex with men (MSM) the prevalence is still high, despite intensive campaigns and treatment programs that keep infected men as undetectable (Beyrer et al. 2012). Promiscuity and condom fatigue (Adam et al. 2005), which are not unique to the MSM community, are making unprotected anal intercourse (UAI) more common and sexually transmitted infections (STIs) presumably harder to track. Yet, MSM communities are peculiar in the sense that men can adopt fixed (insertive or receptive) or versatile (both practices) roles. Some old theoretical work (Wiley & Herschkorn 1989, Van Druten et al. 1992, Trichopoulos et al. 1998) predicted that the transmission of HIV-1 would be enhanced in MSM populations engaged more in role versatility than in role segregation, in which fixed roles are predominantly adopted. These predictions were based on the assumption that the probability of acquisition from unprotected insertive anal (UIA) sex was neglectable. However, as later shown (Vittinghoff et al. 1999, Goodreau et al. 2005), this assumption is inappropriate and HIV-1 may still be acquired via UIA sex. Here I show through a stochastic model that the increase of the HIV-1 prevalence among MSM due to role versatility holds under a stronger assumption of bidirectional virus transmission.

Small-scale drivers: the importance of nutrient availability and snowmelt timing on performance of the alpine shrub Salix herbacea.

Alpine plant communities are predicted to face range shifts and possibly extinctions with climate change. Fine-scale environmental variation such as nutrient availability or snowmelt timing may contribute to the ability of plant species to persist locally; however, variation in nutrient availability in alpine landscapes is largely unmeasured. On three mountains around Davos, Switzerland, we deployed Plant Root Simulator probes around 58 Salix herbacea plants along an elevational and microhabitat gradient to measure nutrient availability during the first 5 weeks of the summer growing season, and used in situ temperature loggers and observational data to determine date of spring snowmelt. We also visited the plants weekly to assess performance, as measured by stem number, fruiting, and herbivory damage. We found a wide snowmelt gradient which determined growing season length, as well as variations of an order of magnitude or more in the accumulation of 12 nutrients between different microhabitats. Higher nutrient availability had negative effects on most shrub performance metrics, for instance decreasing stem number and the proportion of stems producing fruits. High nutrient availability was associated with increased herbivory damage in early-melting microhabitats, but among late-emerging plants this pattern was reversed. We demonstrate that nutrient availability is highly variable in alpine settings, and that it strongly influences performance in an alpine dwarf shrub, sometimes modifying the response of shrubs to snowmelt timing. As the climate warms and human-induced nitrogen deposition continues in the Alps, these factors may contribute to patterns of local plants persistence.

A high-throughput SNP marker system for parental polymorphism screening, and diversity analysis in common bean (Phaseolus vulgaris L.).

Single nucleotide polymorphism (SNP) detection has become a marker system of choice, because of the high abundance of source polymorphisms and the ease with which allele calls are automated. Various technologies exist for the evaluation of SNP loci and previously we validated two medium throughput technologies. In this study, our goal was to utilize a 768 feature, Illumina GoldenGate assay for common bean (Phaseolus vulgaris L.) developed from conserved legume gene sequences and to use the new technology for (1) the evaluation of parental polymorphisms in a mini-core set of common bean accessions and (2) the analysis of genetic diversity in the crop. A total of 736 SNPs were scored on 236 diverse common bean genotypes with the GoldenGate array. Missing data and heterozygosity levels were low and 94 % of the SNPs were scorable. With the evaluation of the parental polymorphism genotypes, we estimated the utility of the SNP markers in mapping for inter-genepool and intra-genepool populations, the latter being of lower polymorphism than the former. When we performed the diversity analysis with the diverse genotypes, we found Illumina GoldenGate SNPs to provide equivalent evaluations as previous gene-based SNP markers, but less fine-distinctions than with previous microsatellite marker analysis. We did find, however, that the gene-based SNPs in the GoldenGate array had some utility in race structure analysis despite the low polymorphism. Furthermore the SNPs detected high heterozygosity in wild accessions which was probably a reflection of ascertainment bias. The Illumina SNPs were shown to be effective in distinguishing between the genepools, and therefore were most useful in saturation of inter-genepool genetic maps. The implications of these results for breeding in common bean are discussed as well as the advantages and disadvantages of the GoldenGate system for SNP detection.

Nucleotide diversity patterns at the drought-related DREB2 encoding genes in wild and cultivated common bean (Phaseolus vulgaris L.).

Common beans are an important food legume faced with a series of abiotic stresses the most severe of which is drought. The crop is interesting as a model for the analysis of gene phylogenies due to its domestication process, race structure, and origins in a group of wild common beans found along the South American Andes and the region of Mesoamerica. Meanwhile, the DREB2 transcription factors have been implicated in controlling non-ABA dependent responses to drought stress. With this in mind our objective was to study in depth the genetic diversity for two DREB2 genes as possible candidates for association with drought tolerance through a gene phylogenetic analysis. In this genetic diversity assessment, we analyzed nucleotide diversity at the two candidate genes Dreb2A and Dreb2B, in partial core collections of 104 wild and 297 cultivated common beans with a total of 401 common bean genotypes from world-wide germplasm analyzed. Our wild population sample covered a range of semi-mesic to very dry habitats, while our cultivated samples presented a wide spectrum of low to high drought tolerance. Both genes showed very different patterns of nucleotide variation. Dreb2B exhibited very low nucleotide diversity relative to neutral reference loci previously surveyed in these populations. This suggests that strong purifying selection has been acting on this gene. In contrast, Dreb2A exhibited higher levels of nucleotide diversity, which is indicative of adaptive selection and population expansion. These patterns were more distinct in wild compared to cultivated common beans. These approximations suggested the importance of Dreb2 genes in the context of drought tolerance, and constitute the first steps towards an association study between genetic polymorphism of this gene family and variation in drought tolerance traits. We discuss the utility of allele mining in the DREB gene family for the discovery of new drought tolerance traits from wild common bean.

Molecular ecology and selection in the drought-related Asr gene polymorphisms in wild and cultivated common bean (Phaseolus vulgaris L.).

BACKGROUND: The abscisic acid (ABA) pathway plays an important role in the plants' reaction to drought stress and ABA-stress response (Asr) genes are important in controlling this process. In this sense, we accessed nucleotide diversity at two candidate genes for drought tolerance (Asr1 and Asr2), involved in an ABA signaling pathway, in the reference collection of cultivated common bean (Phaseolus vulgaris L.) and a core collection of wild common bean accessions. RESULTS: Our wild population samples covered a range of mesic (semi-arid) to very dry (desert) habitats, while our cultivated samples presented a wide spectrum of drought tolerance. Both genes showed very different patterns of nucleotide variation. Asr1 exhibited very low nucleotide diversity relative to the neutral reference loci that were previously surveyed in these populations. This suggests that strong purifying selection has been acting on this gene. In contrast, Asr2 exhibited higher levels of nucleotide diversity, which is indicative of adaptive selection. These patterns were more notable in wild beans than in cultivated common beans indicting that natural selection has played a role over long time periods compared to farmer selection since domestication. CONCLUSIONS: Together these results suggested the importance of Asr1 in the context of drought tolerance, and constitute the first steps towards an association study between genetic polymorphism of this gene family and variation in drought tolerance traits. Furthermore, one of our major successes was to find that wild common bean is a reservoir of genetic variation and selection signatures at Asr genes, which may be useful for breeding drought tolerance in cultivated common bean.

Gene-based single nucleotide polymorphism markers for genetic and association mapping in common bean.

BACKGROUND: In common bean, expressed sequence tags (ESTs) are an underestimated source of gene-based markers such as insertion-deletions (Indels) or single-nucleotide polymorphisms (SNPs). However, due to the nature of these conserved sequences, detection of markers is difficult and portrays low levels of polymorphism. Therefore, development of intron-spanning EST-SNP markers can be a valuable resource for genetic experiments such as genetic mapping and association studies. RESULTS: In this study, a total of 313 new gene-based markers were developed at target genes. Intronic variation was deeply explored in order to capture more polymorphism. Introns were putatively identified after comparing the common bean ESTs with the soybean genome, and the primers were designed over intron-flanking regions. The intronic regions were evaluated for parental polymorphisms using the single strand conformational polymorphism (SSCP) technique and Sequenom MassARRAY system. A total of 53 new marker loci were placed on an integrated molecular map in the DOR364 × G19833 recombinant inbred line (RIL) population. The new linkage map was used to build a consensus map, merging the linkage maps of the BAT93 × JALO EEP558 and DOR364 × BAT477 populations. A total of 1,060 markers were mapped, with a total map length of 2,041 cM across 11 linkage groups. As a second application of the generated resource, a diversity panel with 93 genotypes was evaluated with 173 SNP markers using the MassARRAY-platform and KASPar technology. These results were coupled with previous SSR evaluations and drought tolerance assays carried out on the same individuals. This agglomerative dataset was examined, in order to discover marker-trait associations, using general linear model (GLM) and mixed linear model (MLM). Some significant associations with yield components were identified, and were consistent with previous findings. CONCLUSIONS: In short, this study illustrates the power of intron-based markers for linkage and association mapping in common bean. The utility of these markers is discussed in relation with the usefulness of microsatellites, the molecular markers by excellence in this crop.

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.

Genetic differentiation of grain, fodder and pod vegetable type cowpeas (Vigna unguiculata L.) identified through single nucleotide polymorphisms from genotyping-by-sequencing.

The species Vigna unguiculata L. (Walp), commonly known as cowpea, is a multi-purpose legume that has been selected into three subspecies that are divided into grain, fodder and pod (yardlong bean) types. However, genetic bases for distinctions are not well understood. The purpose of this study was to apply genotyping-by-sequencing (GBS) and current reference genome for V. unguiculata to distinguish three subspecies and identify signatures of divergence. The collection of 130 accessions included 128 cultivated from: 1) ssp. cylindrica, fodder type; 2) ssp. sesquipedalis, pod vegetable type; and 3) ssp. unguiculata, grain type. Two wilds genotypes from spp. dekindtiana and spp. pubescens, were used to anchor phylogeny. A total of 11,083 highly informative single nucleotide polymorphisms (SNPs) were discovered. Wild accessions showed distinct genetic fingerprints and were separated from cultivated subspecies. Principal component analysis showed closer relationship between ssp. unguiculata and ssp. cylindrica compared to ssp. sesquipedalis. Relative differentiation of cultivated subspecies (with Fixation Index, FST) indicated the existence of discrete signatures of selection. This work clarifies the population structure, phylogeny, and domestication of cultivated cowpeas. Furthermore, significant genetic differences between grain and pod vegetable types can provide valuable information for future breeding in three cowpea groups.

Inheritance of Yield Components and Morphological Traits in Avocado cv. Hass From "Criollo" "Elite Trees" via Half-Sib Seedling Rootstocks.

Grafting induces precocity and maintains clonal integrity in fruit tree crops. However, the complex rootstock × scion interaction often precludes understanding how the tree phenotype is shaped, limiting the potential to select optimum rootstocks. Therefore, it is necessary to assess (1) how seedling progenies inherit trait variation from elite 'plus trees', and (2) whether such family superiority may be transferred after grafting to the clonal scion. To bridge this gap, we quantified additive genetic parameters (i.e., narrow sense heritability-h 2, and genetic-estimated breeding values-GEBVs) across landraces, "criollo", "plus trees" of the super-food fruit tree crop avocado (Persea americana Mill.), and their open-pollinated (OP) half-sib seedling families. Specifically, we used a genomic best linear unbiased prediction (G-BLUP) model to merge phenotypic characterization of 17 morpho-agronomic traits with genetic screening of 13 highly polymorphic SSR markers in a diverse panel of 104 avocado "criollo" "plus trees." Estimated additive genetic parameters were validated at a 5-year-old common garden trial (i.e., provenance test), in which 22 OP half-sib seedlings from 82 elite "plus trees" served as rootstocks for the cv. Hass clone. Heritability (h 2) scores in the "criollo" "plus trees" ranged from 0.28 to 0.51. The highest h 2 values were observed for ribbed petiole and adaxial veins with 0.47 (CI 95%0.2-0.8) and 0.51 (CI 0.2-0.8), respectively. The h 2 scores for the agronomic traits ranged from 0.34 (CI 0.2-0.6) to 0.39 (CI 0.2-0.6) for seed weight, fruit weight, and total volume, respectively. When inspecting yield variation across 5-year-old grafted avocado cv. Hass trees with elite OP half-sib seedling rootstocks, the traits total number of fruits and fruits' weight, respectively, exhibited h 2 scores of 0.36 (± 0.23) and 0.11 (± 0.09). Our results indicate that elite "criollo" "plus trees" may serve as promissory donors of seedling rootstocks for avocado cv. Hass orchards due to the inheritance of their outstanding trait values. This reinforces the feasibility to leverage natural variation from "plus trees" via OP half-sib seedling rootstock families. By jointly estimating half-sib family effects and rootstock-mediated heritability, this study promises boosting seedling rootstock breeding programs, while better discerning the consequences of grafting in fruit tree crops.

SNP marker diversity in common bean (Phaseolus vulgaris L.).

Single nucleotide polymorphism (SNP) markers have become a genetic technology of choice because of their automation and high precision of allele calls. In this study, our goal was to develop 94 SNPs and test them across well-chosen common bean (Phaseolus vulgaris L.) germplasm. We validated and accessed SNP diversity at 84 gene-based and 10 non-genic loci using KASPar technology in a panel of 70 genotypes that have been used as parents of mapping populations and have been previously evaluated for SSRs. SNPs exhibited high levels of genetic diversity, an excess of middle frequency polymorphism, and a within-genepool mismatch distribution as expected for populations affected by sudden demographic expansions after domestication bottlenecks. This set of markers was useful for distinguishing Andean and Mesoamerican genotypes but less useful for distinguishing within each gene pool. In summary, slightly greater polymorphism and race structure was found within the Andean gene pool than within the Mesoamerican gene pool but polymorphism rate between genotypes was consistent with genepool and race identity. Our survey results represent a baseline for the choice of SNP markers for future applications because gene-associated SNPs could themselves be causative SNPs for traits. Finally, we discuss that the ideal genetic marker combination with which to carry out diversity, mapping and association studies in common bean should consider a mix of both SNP and SSR markers.

Harnessing Crop Wild Diversity for Climate Change Adaptation.

Warming and drought are reducing global crop production with a potential to substantially worsen global malnutrition. As with the green revolution in the last century, plant genetics may offer concrete opportunities to increase yield and crop adaptability. However, the rate at which the threat is happening requires powering new strategies in order to meet the global food demand. In this review, we highlight major recent 'big data' developments from both empirical and theoretical genomics that may speed up the identification, conservation, and breeding of exotic and elite crop varieties with the potential to feed humans. We first emphasize the major bottlenecks to capture and utilize novel sources of variation in abiotic stress (i.e., heat and drought) tolerance. We argue that adaptation of crop wild relatives to dry environments could be informative on how plant phenotypes may react to a drier climate because natural selection has already tested more options than humans ever will. Because isolated pockets of cryptic diversity may still persist in remote semi-arid regions, we encourage new habitat-based population-guided collections for genebanks. We continue discussing how to systematically study abiotic stress tolerance in these crop collections of wild and landraces using geo-referencing and extensive environmental data. By uncovering the genes that underlie the tolerance adaptive trait, natural variation has the potential to be introgressed into elite cultivars. However, unlocking adaptive genetic variation hidden in related wild species and early landraces remains a major challenge for complex traits that, as abiotic stress tolerance, are polygenic (i.e., regulated by many low-effect genes). Therefore, we finish prospecting modern analytical approaches that will serve to overcome this issue. Concretely, genomic prediction, machine learning, and multi-trait gene editing, all offer innovative alternatives to speed up more accurate pre- and breeding efforts toward the increase in crop adaptability and yield, while matching future global food demands in the face of increased heat and drought. In order for these 'big data' approaches to succeed, we advocate for a trans-disciplinary approach with open-source data and long-term funding. The recent developments and perspectives discussed throughout this review ultimately aim to contribute to increased crop adaptability and yield in the face of heat waves and drought events.

Evolutionary Genetics of Crop-Wild Complexes.

Since Darwin's time, the role of crop wild relatives (CWR), landraces, and cultivated genepools in shaping plant diversity and boosting food resources has been a major question [...].

Integrative Pre-Breeding for Biotic Resistance in Forest Trees.

Climate change is unleashing novel biotic antagonistic interactions for forest trees that may jeopardize populations' persistence. Therefore, this review article envisions highlighting major opportunities from ecological evolutionary genomics to assist the identification, conservation, and breeding of biotic resistance in forest tree species. Specifically, we first discuss how assessing the genomic architecture of biotic stress resistance enables us to recognize a more polygenic nature for a trait typically regarded Mendelian, an expectation from the Fisherian runaway pathogen-host concerted arms-race evolutionary model. Secondly, we outline innovative pipelines to capture and harness natural tree pre-adaptations to biotic stresses by merging tools from the ecology, phylo-geography, and omnigenetics fields within a predictive breeding platform. Promoting integrative ecological genomic studies promises a better understanding of antagonistic co-evolutionary interactions, as well as more efficient breeding utilization of resistant phenotypes.

Rootstock-Mediated Genetic Variance in Cadmium Uptake by Juvenile Cacao (Theobroma cacao L.) Genotypes, and Its Effect on Growth and Physiology.

Grafting typically offers a shortcut to breed tree orchards throughout a multidimensional space of traits. Despite an overwhelming spectrum of rootstock-mediated effects on scion traits observed across several species, the exact nature and mechanisms underlying the rootstock-mediated effects on scion traits in cacao (Theobroma cacao L.) plants often remain overlooked. Therefore, we aimed to explicitly quantify rootstock-mediated genetic contributions in recombinant juvenile cacao plants across target traits, specifically cadmium (Cd) uptake, and its correlation with growth and physiological traits. Content of chloroplast pigments, fluorescence of chlorophyll a, leaf gas exchange, nutrient uptake, and plant biomass were examined across ungrafted saplings and target rootstock × scion combinations in soils with contrasting levels of Cd. This panel considered a total of 320 progenies from open-pollinated half-sib families and reciprocal full-sib progenies (derived from controlled crosses between the reference genotypes IMC67 and PA121). Both family types were used as rootstocks in grafts with two commercial clones (ICS95 and CCN51) commonly grown in Colombia. A pedigree-based best linear unbiased prediction (A-BLUP) mixed model was implemented to quantify rootstock-mediated narrow-sense heritability (h 2) for target traits. A Cd effect measured on rootstocks before grafting was observed in plant biomass, nutrient uptake, and content of chloroplast pigments. After grafting, damage to the Photosystem II (PSII) was also evident in some rootstock × scion combinations. Differences in the specific combining ability for Cd uptake were mostly detected in ungrafted rootstocks, or 2 months after grafting with the clonal CCN51 scion. Moderate rootstock effects (h 2> 0.1) were detected before grafting for five growth traits, four nutrient uptake properties, and chlorophylls and carotenoids content (h 2 = 0.19, 95% CI 0.05-0.61, r = 0.7). Such rootstock effects faded (h 2< 0.1) when rootstock genotypes were examined in soils without Cd, or 4 months after grafting. These results suggest a pervasive genetic conflict between the rootstock and the scion genotypes, involving the triple rootstock × scion × soil interaction when it refers to Cd and nutrient uptake, early growth, and photosynthetic process in juvenile cacao plants. Overall, deepening on these findings will harness early breeding schemes of cacao rootstock genotypes compatible with commercial clonal scions and adapted to soils enriched with toxic levels of Cd.

Allelic Diversity at Abiotic Stress Responsive Genes in Relationship to Ecological Drought Indices for Cultivated Tepary Bean, Phaseolus acutifolius A. Gray, and Its Wild Relatives.

Some of the major impacts of climate change are expected in regions where drought stress is already an issue. Grain legumes are generally drought susceptible. However, tepary bean and its wild relatives within Phaseolus acutifolius or P. parvifolius are from arid areas between Mexico and the United States. Therefore, we hypothesize that these bean accessions have diversity signals indicative of adaptation to drought at key candidate genes such as: Asr2, Dreb2B, and ERECTA. By sequencing alleles of these genes and comparing to estimates of drought tolerance indices from climate data for the collection site of geo-referenced, tepary bean accessions, we determined the genotype x environmental association (GEA) of each gene. Diversity analysis found that cultivated and wild P. acutifolius were intermingled with var. tenuifolius and P. parvifolius, signifying that allele diversity was ample in the wild and cultivated clade over a broad sense (sensu lato) evaluation. Genes Dreb2B and ERECTA harbored signatures of directional selection, represented by six SNPs correlated with the environmental drought indices. This suggests that wild tepary bean is a reservoir of novel alleles at genes for drought tolerance, as expected for a species that originated in arid environments. Our study corroborated that candidate gene approach was effective for marker validation across a broad genetic base of wild tepary accessions.

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.

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.