Local adaptation of Pinus leiophylla under climate and land use change models in the Avocado Belt of Michoacán.

Climate change and land use change are two main drivers of global biodiversity decline, decreasing the genetic diversity that populations harbour and altering patterns of local adaptation. Landscape genomics allows measuring the effect of these anthropogenic disturbances on the adaptation of populations. However, both factors have rarely been considered simultaneously. Based on a set of 3660 SNPs from which 130 were identified as outliers by a genome-environment association analysis (LFMM), we modelled the spatial turnover of allele frequencies in 19 localities of Pinus leiophylla across the Avocado Belt in Michoacán state, Mexico. Then, we evaluated the effect of climate change and land use change scenarios, in addition to evaluating assisted gene flow strategies and connectivity metrics across the landscape to identify priority conservation areas for the species. We found that localities in the centre-east of the Avocado Belt would be more vulnerable to climate change, while localities in the western area are more threatened by land conversion to avocado orchards. Assisted gene flow actions could aid in mitigating both threats. Connectivity patterns among forest patches will also be modified by future habitat loss, with central and eastern parts of the Avocado Belt maintaining the highest connectivity. These results suggest that areas with the highest priority for conservation are in the eastern part of the Avocado Belt, including the Monarch Butterfly Biosphere Reserve. This work is useful as a framework that incorporates distinct layers of information to provide a more robust representation of the response of tree populations to anthropogenic disturbances.

Sampling effect in predicting the evolutionary response of populations to climate change.

Genomic data and machine learning approaches have gained interest due to their potential to identify adaptive genetic variation across populations and to assess species vulnerability to climate change. By identifying gene-environment associations for putatively adaptive loci, these approaches project changes to adaptive genetic composition as a function of future climate change (genetic offsets), which are interpreted as measuring the future maladaptation of populations due to climate change. In principle, higher genetic offsets relate to increased population vulnerability and therefore can be used to set priorities for conservation and management. However, it is not clear how sensitive these metrics are to the intensity of population and individual sampling. Here, we use five genomic datasets with varying numbers of SNPs (NSNPs = 7006-1,398,773), sampled populations (Npop = 23-47) and individuals (Nind = 185-595) to evaluate the estimation sensitivity of genetic offsets to varying degrees of sampling intensity. We found that genetic offsets are sensitive to the number of populations being sampled, especially with less than 10 populations and when genetic structure is high. We also found that the number of individuals sampled per population had small effects on the estimation of genetic offsets, with more robust results when five or more individuals are sampled. Finally, uncertainty associated with the use of different future climate scenarios slightly increased estimation uncertainty in the genetic offsets. Our results suggest that sampling efforts should focus on increasing the number of populations, rather than the number of individuals per populations, and that multiple future climate scenarios should be evaluated to ascertain estimation sensitivity.

Evaluating the persistence and utility of five wild Vitis species in the context of climate change.

Crop wild relatives (CWRs) have the capacity to contribute novel traits to agriculture. Given climate change, these contributions may be especially vital for the persistence of perennial crops, because perennials are often clonally propagated and consequently do not evolve rapidly. By studying the landscape genomics of samples from five Vitis CWRs (V. arizonica, V. mustangensis, V. riparia, V. berlandieri and V. girdiana) in the context of projected climate change, we addressed two goals. The first was to assess the relative potential of different CWR accessions to persist in the face of climate change. By integrating species distribution models with adaptive genetic variation, additional genetic features such as genomic load and a phenotype (resistance to Pierce's Disease), we predicted that accessions from one species (V. mustangensis) are particularly well-suited to persist in future climates. The second goal was to identify which CWR accessions may contribute to bioclimatic adaptation for grapevine (V. vinifera) cultivation. To do so, we evaluated whether CWR accessions have the allelic capacity to persist if moved to locations where grapevines are cultivated in the United States. We identified six candidates from V. mustangensis and hypothesized that they may prove useful for contributing alleles that can mitigate climate impacts on viticulture. By identifying candidate germplasm, this study takes a conceptual step toward assessing the genomic and bioclimatic characteristics of CWRs.

Introgression among North American wild grapes (Vitis) fuels biotic and abiotic adaptation.

BACKGROUND: Introgressive hybridization can reassort genetic variants into beneficial combinations, permitting adaptation to new ecological niches. To evaluate evolutionary patterns and dynamics that contribute to introgression, we investigate six wild Vitis species that are native to the Southwestern United States and useful for breeding grapevine (V. vinifera) rootstocks. RESULTS: By creating a reference genome assembly from one wild species, V. arizonica, and by resequencing 130 accessions, we focus on identifying putatively introgressed regions (pIRs) between species. We find six species pairs with signals of introgression between them, comprising up to ~ 8% of the extant genome for some pairs. The pIRs tend to be gene poor, located in regions of high recombination and enriched for genes implicated in disease resistance functions. To assess potential pIR function, we explore SNP associations to bioclimatic variables and to bacterial levels after infection with the causative agent of Pierce's disease (Xylella fastidiosa). pIRs are enriched for SNPs associated with both climate and bacterial levels, suggesting that introgression is driven by adaptation to biotic and abiotic stressors. CONCLUSIONS: Altogether, this study yields insights into the genomic extent of introgression, potential pressures that shape adaptive introgression, and the evolutionary history of economically important wild relatives of a critical crop.

The evolutionary genomics of species' responses to climate change.

Climate change is a threat to biodiversity. One way that this threat manifests is through pronounced shifts in the geographical range of species over time. To predict these shifts, researchers have primarily used species distribution models. However, these models are based on assumptions of niche conservatism and do not consider evolutionary processes, potentially limiting their accuracy and value. To incorporate evolution into the prediction of species' responses to climate change, researchers have turned to landscape genomic data and examined information about local genetic adaptation using climate models. Although this is an important advancement, this approach currently does not include other evolutionary processes-such as gene flow, population dispersal and genomic load-that are critical for predicting the fate of species across the landscape. Here, we briefly review the current practices for the use of species distribution models and for incorporating local adaptation. We next discuss the rationale and theory for considering additional processes, reviewing how they can be incorporated into studies of species' responses to climate change. We summarize with a conceptual framework of how manifold layers of information can be combined to predict the potential response of specific populations to climate change. We illustrate all of the topics using an exemplar dataset and provide the source code as potential tutorials. This Perspective is intended to be a step towards a more comprehensive integration of population genomics with climate change science.

The domestication of Cucurbita argyrosperma as revealed by the genome of its wild relative.

Despite their economic importance and well-characterized domestication syndrome, the genomic impact of domestication and the identification of variants underlying the domestication traits in Cucurbita species (pumpkins and squashes) is currently lacking. Cucurbita argyrosperma, also known as cushaw pumpkin or silver-seed gourd, is a Mexican crop consumed primarily for its seeds rather than fruit flesh. This makes it a good model to study Cucurbita domestication, as seeds were an essential component of early Mesoamerican diet and likely the first targets of human-guided selection in pumpkins and squashes. We obtained population-level data using tunable Genotype by Sequencing libraries for 192 individuals of the wild and domesticated subspecies of C. argyrosperma across Mexico. We also assembled the first high-quality wild Cucurbita genome. Comparative genomic analyses revealed several structural variants and presence/absence of genes related to domestication. Our results indicate a monophyletic origin of this domesticated crop in the lowlands of Jalisco. We found evidence of gene flow between the domesticated and wild subspecies, which likely alleviated the effects of the domestication bottleneck. We uncovered candidate domestication genes that are involved in the regulation of growth hormones, plant defense mechanisms, seed development, and germination. The presence of shared selected alleles with the closely related species Cucurbita moschata suggests domestication-related introgression between both taxa.

Evaluation of the Minimum Sampling Design for Population Genomic and Microsatellite Studies: An Analysis Based on Wild Maize.

Massive parallel sequencing (MPS) is revolutionizing the field of molecular ecology by allowing us to understand better the evolutionary history of populations and species, and to detect genomic regions that could be under selection. However, the economic and computational resources needed generate a tradeoff between the amount of loci that can be obtained and the number of populations or individuals that can be sequenced. In this work, we analyzed and compared two simulated genomic datasets fitting a hierarchical structure, two extensive empirical genomic datasets, and a dataset comprising microsatellite information. For all datasets, we generated different subsampling designs by changing the number of loci, individuals, populations, and individuals per population to test for deviations in classic population genetics parameters (H S , F IS , F ST ). For the empirical datasets we also analyzed the effect of sampling design on landscape genetic tests (isolation by distance and environment, central abundance hypothesis). We also tested the effect of sampling a different number of populations in the detection of outlier SNPs. We found that the microsatellite dataset is very sensitive to the number of individuals sampled when obtaining summary statistics. F IS was particularly sensitive to a low sampling of individuals in the simulated, genomic, and microsatellite datasets. For the empirical and simulated genomic datasets, we found that as long as many populations are sampled, few individuals and loci are needed. For the empirical datasets, we found that increasing the number of populations sampled was important in obtaining precise landscape genetic estimates. Finally, we corroborated that outlier tests are sensitive to the number of populations sampled. We conclude by proposing different sampling designs depending on the objectives.

Population genomics of Vibrionaceae isolated from an endangered oasis reveals local adaptation after an environmental perturbation.

BACKGROUND: In bacteria, pan-genomes are the result of an evolutionary "tug of war" between selection and horizontal gene transfer (HGT). High rates of HGT increase the genetic pool and the effective population size (Ne), resulting in open pan-genomes. In contrast, selective pressures can lead to local adaptation by purging the variation introduced by HGT and mutation, resulting in closed pan-genomes and clonal lineages. In this study, we explored both hypotheses, elucidating the pan-genome of Vibrionaceae isolates after a perturbation event in the endangered oasis of Cuatro Ciénegas Basin (CCB), Mexico, and looking for signals of adaptation to the environments in their genomes. RESULTS: We obtained 42 genomes of Vibrionaceae distributed in six lineages, two of them did not showed any close reference strain in databases. Five of the lineages showed closed pan-genomes and were associated to either water or sediment environment; their high Ne estimates suggest that these lineages are not from a recent origin. The only clade with an open pan-genome was found in both environments and was formed by ten genetic groups with low Ne, suggesting a recent origin. The recombination and mutation estimators (r/m) ranged from 0.005 to 2.725, which are similar to oceanic Vibrionaceae estimations. However, we identified 367 gene families with signals of positive selection, most of them found in the core genome; suggesting that despite recombination, natural selection moves the Vibrionaceae CCB lineages to local adaptation, purging the genomes and keeping closed pan-genome patterns. Moreover, we identify 598 SNPs associated with an unstructured environment; some of the genes associated with these SNPs were related to sodium transport. CONCLUSIONS: Different lines of evidence suggest that the sampled Vibrionaceae, are part of the rare biosphere usually living under famine conditions. Two of these lineages were reported for the first time. Most Vibrionaceae lineages of CCB are adapted to their micro-habitats rather than to the sampled environments. This pattern of adaptation is concordant with the association of closed pan-genomes and local adaptation.

The relevance of gene flow with wild relatives in understanding the domestication process.

The widespread use of genomic tools has allowed for a deeper understanding of the genetics and the evolutionary dynamics of domestication. Recent studies have suggested that multiple domestications and introgression are more common than previously thought. However, the ability to correctly infer the many aspects of domestication process depends on having an adequate representation of wild relatives. Cultivated maize (Zea mays ssp. mays) is one of the most important crops in the world, with a long and a relatively well-documented history of domestication. The current consensus points towards a single domestication event from teosinte Zea mays ssp. parviglumis from the Balsas Basin in Southwestern Mexico. However, the underlying diversity of teosintes from Z. mays ssp. parviglumis and Zea mays ssp. mexicana was not taken into account in early studies. We used 32 739 single nucleotide polymorphisms (SNPs) obtained from 29 teosinte populations and 43 maize landraces to explore the relationship between wild and cultivated members of Zea. We then inferred the levels of gene flow among teosinte populations and maize, the degree of population structure of Zea mays subspecies, and the potential domestication location of maize. We confirmed a strong geographic structure within Z. mays ssp. parviglumis and documented multiple gene flow events with other members of the genus, including an event between Z. mays ssp. mexicana and maize. Our results suggest that the likely ancestor of maize may have been domesticated in Jalisco or in the southern Pacific Coast and not in the Balsas Basin as previously thought. In this context, different populations of both teosinte subspecies have contributed to modern maize's gene pool. Our results point towards a long period of domestication marked by gene flow with wild relatives, confirming domestication as long and ongoing process.

Common gardens in teosintes reveal the establishment of a syndrome of adaptation to altitude.

In plants, local adaptation across species range is frequent. Yet, much has to be discovered on its environmental drivers, the underlying functional traits and their molecular determinants. Genome scans are popular to uncover outlier loci potentially involved in the genetic architecture of local adaptation, however links between outliers and phenotypic variation are rarely addressed. Here we focused on adaptation of teosinte populations along two elevation gradients in Mexico that display continuous environmental changes at a short geographical scale. We used two common gardens, and phenotyped 18 traits in 1664 plants from 11 populations of annual teosintes. In parallel, we genotyped these plants for 38 microsatellite markers as well as for 171 outlier single nucleotide polymorphisms (SNPs) that displayed excess of allele differentiation between pairs of lowland and highland populations and/or correlation with environmental variables. Our results revealed that phenotypic differentiation at 10 out of the 18 traits was driven by local selection. Trait covariation along the elevation gradient indicated that adaptation to altitude results from the assembly of multiple co-adapted traits into a complex syndrome: as elevation increases, plants flower earlier, produce less tillers, display lower stomata density and carry larger, longer and heavier grains. The proportion of outlier SNPs associating with phenotypic variation, however, largely depended on whether we considered a neutral structure with 5 genetic groups (73.7%) or 11 populations (13.5%), indicating that population stratification greatly affected our results. Finally, chromosomal inversions were enriched for both SNPs whose allele frequencies shifted along elevation as well as phenotypically-associated SNPs. Altogether, our results are consistent with the establishment of an altitudinal syndrome promoted by local selective forces in teosinte populations in spite of detectable gene flow. Because elevation mimics climate change through space, SNPs that we found underlying phenotypic variation at adaptive traits may be relevant for future maize breeding.

Climate change is predicted to disrupt patterns of local adaptation in wild and cultivated maize.

Climate change is one of the most important threats to biodiversity and crop sustainability. The impact of climate change is often evaluated on the basis of expected changes in species' geographical distributions. Genomic diversity, local adaptation, and migration are seldom integrated into future species projections. Here, we examine how climate change will impact populations of two wild relatives of maize, the teosintes Zea mays ssp. mexicana and Z. mays ssp. parviglumis. Despite high levels of genetic diversity within populations and widespread future habitat suitability, we predict that climate change will alter patterns of local adaptation and decrease migration probabilities in more than two-thirds of present-day teosinte populations. These alterations are geographically heterogeneous and suggest that the possible impacts of climate change will vary considerably among populations. The population-specific effects of climate change are also evident in maize landraces, suggesting that climate change may result in maize landraces becoming maladapted to the climates in which they are currently cultivated. The predicted alterations to habitat distribution, migration potential, and patterns of local adaptation in wild and cultivated maize raise a red flag for the future of populations. The heterogeneous nature of predicted populations' responses underscores that the selective impact of climate change may vary among populations and that this is affected by different processes, including past adaptation.

Divergence with gene flow is driven by local adaptation to temperature and soil phosphorus concentration in teosinte subspecies (Zea mays parviglumis and Zea mays mexicana).

Patterns of genomic divergence between hybridizing taxa can be heterogeneous along the genome. Both differential introgression and local adaptation may contribute to this pattern. Here, we analysed two teosinte subspecies, Zea mays ssp. parviglumis and ssp. mexicana, to test whether their divergence has occurred in the face of gene flow and to infer which environmental variables have been important drivers of their ecological differentiation. We generated 9,780 DArTseqTM SNPs for 47 populations, and used an additional data set containing 33,454 MaizeSNP50 SNPs for 49 populations. With these data, we inferred features of demographic history and performed genome wide scans to determine the number of outlier SNPs associated with climate and soil variables. The two data sets indicate that divergence has occurred or been maintained despite continuous gene flow and/or secondary contact. Most of the significant SNP associations were to temperature and to phosphorus concentration in the soil. A large proportion of these candidate SNPs were located in regions of high differentiation that had been identified previously as putative inversions. We therefore propose that genomic differentiation in teosintes has occurred by a process of adaptive divergence, with putative inversions contributing to reduced gene flow between locally adapted populations.

Gypsum soil restriction drives genetic differentiation in Fouquieria shrevei (Fouquieriaceae).

PREMISE OF THE STUDY: Although species adapted to grow in unusual soils contribute importantly to regional diversity, the microevolutionary processes responsible for that diversity remain to be understood. We aimed to answer this question by analyzing which processes are responsible for the genetic differentiation in Fouquieria shrevei (Fouquieriaceae), a species confined to gypsum soils of northern Mexico. METHODS: We analyzed sequence variation in three chloroplast intergenic spacers from five populations. KEY RESULTS: Total genetic diversity was high (Hd = 0.743). Genetic differentiation was high (FST = 0.651), as most haplotypes were unique to individual populations, and three populations had only one haplotype. Haplotypes were more similar in nearby populations, resulting in a phylogeographic structure (i.e., GST = 0.850 was significantly lower than NST = 0.930) and a significant Mantel test (P = 0.04). Tajima's D (-0.019, not significant) indicates that effective population size has remained constant. CONCLUSIONS: We conclude that genetic drift has been intense and gene flow low in differentiating populations that follow an island-like pattern of gypsum deposits of the deserts of North America. The interaction between these forces could promote speciation events that in turn would increase regional diversity and may explain the high number of narrow endemics associated with soil restrictions.