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)

The population genetics of convergent adaptation in maize and teosinte is not locally restricted

What is the genetic architecture of local adaptation and what is the geographic scale over which it operates? We investigated patterns of local and convergent adaptation in five sympatric population pairs of traditionally cultivated maize and its wild relative teosinte (Zea mays subsp. parviglumis). We found that signatures of local adaptation based on the inference of adaptive fixations and selective sweeps are frequently exclusive to individual populations, more so in teosinte compared to maize. However, for both maize and teosinte, selective sweeps are also frequently shared by several populations, and often between subspecies. We were further able to infer that selective sweeps were shared among populations most often via migration, though sharing via standing variation was also common. Our analyses suggest that teosinte has been a continued source of beneficial alleles for maize, even after domestication, and that maize populations have facilitated adaptation in teosinte by moving beneficial alleles across the landscape. Taken together, our results suggest local adaptation in maize and teosinte has an intermediate geographic scale, one that is larger than individual populations but smaller than the species range.

Why Do Some Lineages Radiate While Others Do Not? Perspectives for Future Research on Adaptive Radiations

Understanding the processes that drive phenotypic diversification and underpin speciation is key to elucidating how biodiversity has evolved. Although these processes have been studied across a wide array of clades, adaptive radiations (ARs), which are systems with multiple closely related species and broad phenotypic diversity, have been particularly fruitful for teasing apart the factors that drive and constrain diversification. As such, ARs have become popular candidate study systems for determining the extent to which ecological features, including aspects of organisms and the environment, and inter- and intraspecific interactions, led to evolutionary diversification. Despite substantial past empirical and theoretical work, understanding mechanistically how ARs evolve remains a major challenge. Here, we highlight a number of understudied components of the environment and of lineages themselves, which may help further our understanding of speciation and AR. We also outline some substantial remaining challenges to achieving a detailed understanding of adaptation, speciation, and the role of ecology in these processes. These major challenges include identifying factors that have a causative impact in promoting or constraining ARs, gaining a more holistic understanding of features of organisms and their environment that interact resulting in adaptation and speciation, and understanding whether the role of these organismal and environmental features varies throughout the radiation process. We conclude by providing perspectives on how future investigations into the AR process can overcome these challenges, allowing us to glean mechanistic insights into adaptation and speciation.

Tools and Resources at the Maize Genetics and Genomics Database (MaizeGDB)

The Maize Genetics and Genomics Database (MaizeGDB) is the community resource for maize researchers, offering a suite of tools, informatics resources, and curated data sets to support maize genetics, genomics, and breeding research. Here, we provide an overview of the key resources available at MaizeGDB, including maize genomes, comparative genomics, and pan-genomics tools. This review aims to familiarize users with the range of options available for maize research and highlights the importance of MaizeGDB as a central hub for the maize research community. By providing a detailed snapshot of the database's capabilities, we hope to enable researchers to make use of MaizeGDB's resources, ultimately assisting them to better study the evolution and diversity of maize.

Teosinte populations exhibit weak local adaptation to their rhizosphere biota despite strong effects of biota source on teosinte fitness and traits

While biotic interactions often impose selection, species and populations vary in whether they are locally adapted to biotic interactions. Evolutionary theory predicts that environmental conditions drive this variable local adaptation by altering the fitness impacts of species interactions. To investigate the influence of an environmental gradient on adaptation between a plant and its associated rhizosphere biota, we cross-combined teosinte (Zea mays ssp. mexicana) and rhizosphere biota collected across a gradient of decreasing temperature, precipitation, and nutrients in a greenhouse common garden experiment. We measured both fitness and phenotypes expected to be influenced by biota, including concentrations of nutrients in leaves. Independent, main effects of teosinte and biota source explained most variation in teosinte fitness and traits. For example, biota from warmer sites provided population-independent fitness benefits across teosinte hosts. Effects of biota that depended on teosinte genotype were often not specific to their local hosts, and most traits had similar relationships to fitness across biota treatments. However, we found weak patterns of local adaptation between teosinte and biota from colder sites, suggesting environmental gradients may alter the importance of local adaptation in teosinte-biota interactions, as evolutionary theory predicts.

Genome-Wide Diversity in Lowland and Highland Maize Landraces From Southern South America: Population Genetics Insights to Assist Conservation

Maize (Zea mays ssp. mays L.) landraces are traditional American crops with high genetic variability that conform a source of original alleles for conventional maize breeding. Northern Argentina, one the southernmost regions of traditional maize cultivation in the Americas, harbours around 57 races traditionally grown in two regions with contrasting environmental conditions, namely, the Andean mountains in the Northwest and the tropical grasslands and Atlantic Forest in the Northeast. These races encounter diverse threats to their genetic diversity and persistence in their regions of origin, with climate change standing out as one of the major challenges. In this work, we use genome-wide SNPs derived from ddRADseq to study the genetic diversity of individuals representing the five groups previously described for this area. This allowed us to distinguish two clearly differentiated gene pools, the highland northwestern maize (HNWA) and the floury northeastern maize (FNEA). Subsequently, we employed essential biodiversity variables at the genetic level, as proposed by the Group on Earth Observations Biodiversity Observation Network (GEO BON), to evaluate the conservation status of these two groups. This assessment encompassed genetic diversity (Pi), inbreeding coefficient (F) and effective population size (Ne). FNEA showed low Ne values and high F values, while HNWA showed low Ne values and low Pi values, indicating that further genetic erosion is imminent for these landraces. Outlier detection methods allowed identification of putative adaptive genomic regions, consistent with previously reported flowering-time loci and chromosomal regions displaying introgression from the teosinte Zea mays ssp. mexicana. Finally, species distribution models were obtained for two future climate scenarios, showing a notable reduction in the potential planting area of HNWA and a shift in the cultivation areas of FNEA. These results suggest that maize landraces from Northern Argentina may be unable to cope with climate change. Therefore, active conservation policies are advisable.

The ancestral environment of teosinte populations shapes their root microbiome

BACKGROUND

The composition of the root microbiome affects the host's growth, with variation in the host genome associated with microbiome variation. However, it is not known whether this intra-specific variation of root microbiomes is a consequence of plants performing targeted manipulations of them to adapt to their local environment or varying passively with other traits. To explore the relationship between the genome, environment and microbiome, we sampled seeds from teosinte populations across its native range in Mexico. We then grew teosinte accessions alongside two modern maize lines in a common garden experiment. Metabarcoding was performed using universal bacterial and fungal primers to profile their root microbiomes.

RESULTS

The root microbiome varied between the two modern maize lines and the teosinte accessions. We further found that variation of the teosinte genome, the ancestral environment (temperature/elevation) and root microbiome were all correlated. Multiple microbial groups significantly varied in relative abundance with temperature/elevation, with an increased abundance of bacteria associated with cold tolerance found in teosinte accessions taken from high elevations.

CONCLUSIONS

Our results suggest that variation in the root microbiome is pre-conditioned by the genome for the local environment (i.e. non-random). Ultimately, these claims would be strengthened by confirming that these differences in the root microbiome impact host phenotype, for example, by confirming that the root microbiomes of high-elevation teosinte populations enhance cold tolerance.

Enhanced pan-genomic resources at the maize genetics and genomics database

Pan-genomes, encompassing the entirety of genetic sequences found in a collection of genomes within a clade, are more useful than single reference genomes for studying species diversity. This is especially true for a species like Zea mays, which has a particularly diverse and complex genome. Presenting pan-genome data, analyses, and visualization is challenging, especially for a diverse species, but more so when pan-genomic data is linked to extensive gene model and gene data, including classical gene information, markers, insertions, expression and proteomic data, and protein structures as is the case at MaizeGDB. Here, we describe MaizeGDB's expansion to include the genic subset of the Zea pan-genome in a pan-gene data center featuring the maize genomes hosted at MaizeGDB, and the outgroup teosinte Zea genomes from the Pan-Andropoganeae project. The new data center offers a variety of browsing and visualization tools, including sequence alignment visualization, gene trees and other tools, to explore pan-genes in Zea that were calculated by the pipeline Pandagma. Combined, these data will help maize researchers study the complexity and diversity of Zea, and to use the comparative functions to validate pan-gene relationships for a selected gene model.

Genomic insights into local adaptation and vulnerability of Quercus longinux to climate change

BACKGROUND

Climate change is expected to alter the factors that drive changes in adaptive variation. This is especially true for species with long life spans and limited dispersal capabilities. Rapid climate changes may disrupt the migration of beneficial genetic variations, making it challenging for them to keep up with changing environments. Understanding adaptive genetic variations in tree species is crucial for conservation and effective forest management. Our study used landscape genomic analyses and phenotypic traits from a thorough sampling across the entire range of Quercus longinux, an oak species native to Taiwan, to investigate the signals of adaptation within this species.

RESULTS

Using ecological data, phenotypic traits, and 1,933 single-nucleotide polymorphisms (SNPs) from 205 individuals, we classified three genetic groups, which were also phenotypically and ecologically divergent. Thirty-five genes related to drought and freeze resistance displayed signatures of natural selection. The adaptive variation was driven by diverse environmental pressures such as low spring precipitation, low annual temperature, and soil grid sizes. Using linear-regression-based methods, we identified isolation by environment (IBE) as the optimal model for adaptive SNPs. Redundancy analysis (RDA) further revealed a substantial joint influence of demography, geology, and environments, suggesting a covariation between environmental gradients and colonization history. Lastly, we utilized adaptive signals to estimate the genetic offset for each individual under diverse climate change scenarios. The required genetic changes and migration distance are larger in severe climates. Our prediction also reveals potential threats to edge populations in northern and southeastern Taiwan due to escalating temperatures and precipitation reallocation.

CONCLUSIONS

We demonstrate the intricate influence of ecological heterogeneity on genetic and phenotypic adaptation of an oak species. The adaptation is also driven by some rarely studied environmental factors, including wind speed and soil features. Furthermore, the genetic offset analysis predicted that the edge populations of Q. longinux in lower elevations might face higher risks of local extinctions under climate change.

Genomics for monitoring and understanding species responses to global climate change

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.

Genomic diversity and population structure of teosinte (Zea spp.) and its conservation implications

The wild species of the genus Zea commonly named teosintes, comprise nine different taxa, distributed from northern Mexico to Costa Rica. Although this genus of plants has been extensively studied from a morphological, ecogeographical and genetic point of view, most contributions have been limited to the study of a few populations and taxa. To understand the great variability that exists between and within teosinte species, it is necessary to include the vast majority of known populations. In this context, the objective of this work was to evaluate the diversity and genomic structure of 276 teosinte populations. Molecular analyzes were performed with 3,604 plants and with data from 33,929 SNPs. The levels of genetic diversity by taxonomic group show a marked difference between species, races and sections, where the highest values of genomic diversity was found in ssp. parviglumis and ssp. mexicana. The lower values were obtained for the Luxuriantes section as well as ssp. huehuetenagensis of the section Zea. The results of structure show that there is a great genetic differentiation in all the taxonomic groups considered. For ssp. parviglumis and mexicana, which are the taxa with the largest number of populations, a marked genomic differentiation was found that is consistent with their geographic distribution patterns. These results showed a loss of diversity in several teosinte populations, making a strong case for further collection, and ex situ and in situ conservation. Also, this study highlights the importance of integrating genomic diversity and structure for the applications of conservation and management.

Genome sequencing reveals evidence of adaptive variation in the genus Zea

Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in wild relatives of maize. Here, we characterize a high-density genomic variation map from 744 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 70 million single-nucleotide polymorphisms. The variation map reveals evidence of selection within taxa displaying novel adaptations. We focus on adaptive alleles in highland teosinte and temperate maize, highlighting the key role of flowering-time-related pathways in their adaptation. To show the utility of variants in these data, we generate mutant alleles for two flowering-time candidate genes. This work provides an extensive sampling of the genetic diversity of Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding.

The pho1;2a'-m1.1 allele of Phosphate1 conditions misregulation of the phosphorus starvation response in maize (Zea mays ssp. mays L.)

Plant PHO1 proteins play a central role in the translocation and sensing of inorganic phosphate. The maize (Zea mays ssp. mays) genome encodes two co-orthologs of the Arabidopsis PHO1 gene, designated ZmPho1;2a and ZmPho1;2b. Here, we report the characterization of the transposon footprint allele Zmpho1;2a'-m1.1, which we refer to hereafter as pho1;2a. The pho1;2a allele is a stable derivative formed by excision of an Activator transposable element from the ZmPho1;2a gene. The pho1;2a allele contains an 8-bp insertion at the point of transposon excision that disrupts the reading frame and is predicted to generate a premature translational stop. We show that the pho1;2a allele is linked to a dosage-dependent reduction in Pho1;2a transcript accumulation and a mild reduction in seedling growth. Characterization of shoot and root transcriptomes under full nutrient, low nitrogen, low phosphorus, and combined low nitrogen and low phosphorus conditions identified 1100 differentially expressed genes between wild-type plants and plants carrying the pho1;2a mutation. Of these 1100 genes, 966 were upregulated in plants carrying pho1;2a, indicating the wild-type PHO1;2a to predominantly impact negative gene regulation. Gene set enrichment analysis of the pho1;2a-misregulated genes revealed associations with phytohormone signaling and the phosphate starvation response. In roots, differential expression was broadly consistent across all nutrient conditions. In leaves, differential expression was largely specific to low phosphorus and combined low nitrogen and low phosphorus conditions. Of 276 genes upregulated in the leaves of pho1;2a mutants in the low phosphorus condition, 153 were themselves induced in wild-type plants with respect to the full nutrient condition. Our observations suggest that Pho1;2a functions in the fine-tuning of the transcriptional response to phosphate starvation through maintenance and/or sensing of plant phosphate status.

Selective sorting of ancestral introgression in maize and teosinte along an elevational cline

While often deleterious, hybridization can also be a key source of genetic variation and pre-adapted haplotypes, enabling rapid evolution and niche expansion. Here we evaluate these opposing selection forces on introgressed ancestry between maize (Zea mays ssp. mays) and its wild teosinte relative, mexicana (Zea mays ssp. mexicana). Introgression from ecologically diverse teosinte may have facilitated maize's global range expansion, in particular to challenging high elevation regions (> 1500 m). We generated low-coverage genome sequencing data for 348 maize and mexicana individuals to evaluate patterns of introgression in 14 sympatric population pairs, spanning the elevational range of mexicana, a teosinte endemic to the mountains of Mexico. While recent hybrids are commonly observed in sympatric populations and mexicana demonstrates fine-scale local adaptation, we find that the majority of mexicana ancestry tracts introgressed into maize over 1000 generations ago. This mexicana ancestry seems to have maintained much of its diversity and likely came from a common ancestral source, rather than contemporary sympatric populations, resulting in relatively low FST between mexicana ancestry tracts sampled from geographically distant maize populations. Introgressed mexicana ancestry in maize is reduced in lower-recombination rate quintiles of the genome and around domestication genes, consistent with pervasive selection against introgression. However, we also find mexicana ancestry increases across the sampled elevational gradient and that high introgression peaks are most commonly shared among high-elevation maize populations, consistent with introgression from mexicana facilitating adaptation to the highland environment. In the other direction, we find patterns consistent with adaptive and clinal introgression of maize ancestry into sympatric mexicana at many loci across the genome, suggesting that maize also contributes to adaptation in mexicana, especially at the lower end of its elevational range. In sympatric maize, in addition to high introgression regions we find many genomic regions where selection for local adaptation maintains steep gradients in introgressed mexicana ancestry across elevation, including at least two inversions: the well-characterized 14 Mb Inv4m on chromosome 4 and a novel 3 Mb inversion Inv9f surrounding the macrohairless1 locus on chromosome 9. Most outlier loci with high mexicana introgression show no signals of sweeps or local sourcing from sympatric populations and so likely represent ancestral introgression sorted by selection, resulting in correlated but distinct outcomes of introgression in different contemporary maize populations.

Multidimensional divergent selection, local adaptation, and speciation

Divergent selection applied to one or more traits drives local adaptation and may lead to ecological speciation. Divergent selection on many traits might be termed "multidimensional" divergent selection. There is a commonly held view that multidimensional divergent selection is likely to promote local adaptation and speciation to a greater extent than unidimensional divergent selection. We disentangle the core concepts underlying dimensionality as a property of the environment, phenotypes, and genome. In particular, we identify a need to separate the overall strength of selection and the number of loci affected from dimensionality per se, and to distinguish divergence dimensionality from dimensionality of stabilizing selection. We then critically scrutinize this commonly held view that multidimensional selection promotes speciation, re-examining the evidence base from theory, experiments, and nature. We conclude that the evidence base is currently weak and generally suffers from confounding of possible causal effects. Finally, we propose several mechanisms by which multidimensional divergent selection and related processes might influence divergence, both as a driver and as a barrier.

High-Throughput Feeding Bioassay for Lepidoptera Larvae

Finding plant cultivars that are resistant or tolerant against lepidopteran pests, takes time, effort and is costly. We present here a high throughput leaf-disk consumption assay system, to screen plants for resistance or chemicals for their deterrence. A webcam capturing images at regular intervals can follow the feeding activities of 150 larvae placed into individual cages. We developed a computer program running under an open source image analysis program to analyze and measure the surface of each leaf disk over time. We further developed new statistical procedures to analyze the time course of the feeding activities of the larvae and to compare them between treatments. As a test case, we compared how European corn borer larvae respond to a commercial antifeedant containing azadirachtin, and to quinine, which is a bitter alkaloid for many organisms. As expected, increasing doses of azadirachtin reduced and delayed feeding. However, quinine was poorly effective at the range of concentrations tested (10-5 M to 10-2 M). The model cage, the camera holder, the plugins, and the R scripts are freely available, and can be modified according to the users' needs.

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 ecology of Agave: distribution patterns, phylogeny, and coevolution (an homage to Howard S. Gentry)

With more than 200 species, the genus Agave is one of the most interesting and complex groups of plants in the world, considering for instance its great diversity and adaptations. The adaptations include the production of a single, massive inflorescence (the largest among plants) where after growing for many years, sometimes more than 30, the rosette dies shortly afterward, and the remarkable coevolution with their main pollinators, nectarivorous bats, in particular of the genus Leptonycteris. The physiological adaptations of Agave species include a photosynthetic metabolism that allows efficient use of water and a large degree of succulence, helping to store water and resources for their massive flowering event. Ecologically, the agaves are keystone species on which numerous animal species depend for their subsistence due to the large amounts of pollen and nectar they produce, that support many pollinators, including bats, perching birds, hummingbirds, moths, and bees. Moreover, in many regions of Mexico and in the southwestern United States, agaves are dominant species. We describe the contributions of H. S. Gentry to the understanding of agaves and review recent advances on the study of the ecology and evolution of the genus. We analyze the present and inferred past distribution patterns of different species in the genus, describing differences in their climatic niche and adaptations to dry conditions. We interpret these patterns using molecular clock data and phylogenetic analyses and information of their coevolving pollinators and from phylogeographic, morphological, and ecological studies and discuss the prospects for their future conservation and management.

The role of environment, local adaptation, and past climate fluctuation on the amount and distribution of genetic diversity in two subspecies of Mexican wild Zea mays

PREMISE

Past climate fluctuations during the Holocene and Pleistocene shaped the distribution of several plant species in temperate areas over the world. Wild maize, commonly known as teosinte, is a good system to evaluate the effects of historical climate fluctuations on genetic diversity due to its wide distribution in Mexico with contrasting environmental conditions. We explored the influence of contemporary factors and historical environmental shifts on genetic diversity, including present and three historical periods using neutral markers.

METHODS

We used 22 nuclear microsatellite loci to examine the genetic diversity of 14 populations of Zea mays subsp. parviglumis and 15 populations of Zea mays subsp. mexicana (527 individuals total). We implemented genetic structure analyses to evaluate genetic differentiation between and within subspecies. We applied coalescent-based demographic analysis and species distribution modeling to evaluate the effects of historical environmental shifts.

RESULTS

We found 355 alleles in total for the two subspecies and variable levels of diversity in each (Z. mays subsp. parviglumis expected heterozygosity H_E = 0.3646-0.7699; Z. mays subsp. mexicana H_E = 0.5885-0.7671). We detected significant genetic structure among populations (D_EST = 0.4332) with significant heterozygote deficiency (F_IS = 0.1796), and variable selfing rates (sg₂ = 0.0-0.3090). The Bayesian assignment analysis differentiated four genetic groups. Demographic and species distribution modeling analysis suggested that environmental shifts were influential in the amount of genetic diversity.

CONCLUSIONS

Our analyses suggest that the current genetic diversity in teosinte is shaped by factors such as local adaptation and genetic isolation, along with historical environmental fluctuations.

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.

Abandonment of pearl millet cropping and homogenization of its diversity over a 40 year period in Senegal

Cultivated diversity is considered an insurance against major climatic variability. However, since the 1980s, several studies have shown that climate variability and agricultural changes may already have locally eroded crop genetic diversity. We studied pearl millet diversity in Senegal through a comparison of pearl millet landraces collected 40 years apart. We found that more than 20% of villages visited in 1976 had stopped growing pearl millet. Despite this, its overall genetic diversity has been maintained but differentiation between early- and late-flowering accessions has been reduced. We also found stronger crop-to-wild gene flow than wild-to-crop gene flow and that wild-to-crop gene flow was weaker in 2016 than in 1976. In conclusion, our results highlight genetic homogenization in Senegal. This homogenization within cultivated pearl millet and between wild and cultivated forms is a key factor in genetic erosion and it is often overlooked. Improved assessment and conservation strategies are needed to promote and conserve both wild and cultivated pearl millet diversity.

Genetic Diversity and Phylogeography of the Important Medical Herb, Cultivated Huang-Lian Populations, and the Wild Relatives Coptis Species in China

Huang-lian (Coptis plants in China) are essential medicinal plants in China, C. chinensis var. chinensis and C. deltoidea have been domesticated and cultivated for 700 years. In this study, the genetic diversity patterns and biogeographical information of cultivated Huang-lian and their wild relatives Coptis species were assessed using three plastids DNA regions. A total of 186 individuals from twenty-seven populations representing two species of cultivated Huang-lian and four species of wild relatives were collected and analyzed. Twenty-four haplotypes of six species were identified when three plastid spacers were combined. Historical biogeography inference revealed multiple dispersal events in the groups of cultivated Huang-lian and C. omeiensis. This evidence can infer that large initial population size and interbreeding with co-existing wild relatives in expanding new planting areas might be the main reason for maintaining the high genetic diversity of cultivated Huang-lian. Nevertheless, the multimodal curve of mismatch analysis and positive or negative differed among species and populations by neutrality tests indicated some groups of cultivated Huang-lian experienced genetic bottlenecks. Phylogeny analysis (NJ, MP, BI) showed that cultivated Huang-lian and C. omeiensis were clustered into a monophyletic group while C. chinensis var. brevisepala was paraphyletic, having earlier divergence time from C. chinensis var. chinensis (7.6 Ma) than C. omeiensis. Parsimony network demonstrated that C. deltoidea had more shared haplotypes with C. omeiensis than C. chinensis var. chinensis, and other haplotypes of C. deltoidea and C. omeiensis had less mutation steps than that of C. chinensis var. chinensis and C. omeiensis. This evidence suggests that C. omeiensis has a closer relationship with cultivated Huang-lian and might be a potential wild relative to C. deltoidea. The results reported here provide the baseline data for preserving genetic resources of Huang-lian and also evaluating the genetic impacts of long-term cultivation on medicinal plants, which could be instructive to future cultivation projects of traditional Chinese medicinal plants.

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.

Phylogeographic and population genetic analyses of Cucurbita moschata reveal divergence of two mitochondrial lineages linked to an elevational gradient

PREMISE

Domestication usually involves local adaptation to environmental conditions. Cucurbita species are a promising model for studying these processes. Cucurbita moschata is the third major crop in the genus because of its economic value and because it displays high landrace diversity, but research about its genetic diversity, population structure, and phylogeography is limited. We aimed at understanding how geography and elevation shape the distribution of genetic diversity in C. moschata landraces in Mexico.

METHODS

We sampled fruits from 24 localities throughout Mexico. We assessed 11 nuclear microsatellite loci, one mtDNA region, and three cpDNA regions but found no variation in cpDNA. We explored genetic structure with cluster analysis, and phylogeographic relationships with haplotype network analysis.

RESULTS

Mitochondrial genetic diversity was high, and nuclear genetic differentiation among localities was intermediate compared to other domesticated Cucurbita. We found high levels of inbreeding. We recovered two mitochondrial lineages: highland (associated with the Trans-Mexican Volcanic Belt) and lowland. Nuclear microsatellites show that localities from the Yucatan Peninsula constitute a well-differentiated group.

CONCLUSIONS

Mexico is an area of high diversity for C. moschata, and these landraces represent important plant genetic resources. In Mexico this species is characterized by divergence processes linked to an elevational gradient, which could be related to adaptation and may be of value for applications in agriculture. The Isthmus of Tehuantepec may be a partial barrier to gene flow. Morphological variation, agricultural management, and cultural differences may be related to this pattern of genetic structure, but further studies are needed.

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.