LEA 3: Factor models in population genetics and ecological genomics with R

Origin and evolution of the bread wheat D genome

Bread wheat (Triticum aestivum) is a globally dominant crop and major source of calories and proteins for the human diet. Compared with its wild ancestors, modern bread wheat shows lower genetic diversity, caused by polyploidisation, domestication and breeding bottlenecks1,2. Wild wheat relatives represent genetic reservoirs, and harbour diversity and beneficial alleles that have not been incorporated into bread wheat. Here we establish and analyse extensive genome resources for Tausch's goatgrass (Aegilops tauschii), the donor of the bread wheat D genome. Our analysis of 46 Ae. tauschii genomes enabled us to clone a disease resistance gene and perform haplotype analysis across a complex disease resistance locus, allowing us to discern alleles from paralogous gene copies. We also reveal the complex genetic composition and history of the bread wheat D genome, which involves contributions from genetically and geographically discrete Ae. tauschii subpopulations. Together, our results reveal the complex history of the bread wheat D genome and demonstrate the potential of wild relatives in crop improvement.

Global, asynchronous partial sweeps at multiple insecticide resistance genes in Aedes mosquitoes

Aedes aegypti (yellow fever mosquito) and Ae. albopictus (Asian tiger mosquito) are globally invasive pests that confer the world's dengue burden. Insecticide-based management has led to the evolution of insecticide resistance in both species, though the genetic architecture and geographical spread of resistance remains incompletely understood. This study investigates partial selective sweeps at resistance genes on two chromosomes and characterises their spread across populations. Sweeps at the voltage-sensitive sodium channel (VSSC) gene on chromosome 3 correspond to one resistance-associated nucleotide substitution in Ae. albopictus and three in Ae. aegypti, including two substitutions at the same nucleotide position (F1534C) that have evolved and spread independently. In Ae. aegypti, we also identify partial sweeps at a second locus on chromosome 2. This locus contains 15 glutathione S-transferase (GST) epsilon class genes with significant copy number variation among populations and where three distinct genetic backgrounds have spread across the Indo-Pacific region, the Americas, and Australia. Local geographical patterns and linkage networks indicate VSSC and GST backgrounds probably spread at different times and interact locally with different genes to produce resistance phenotypes. These findings highlight the rapid global spread of resistance and are evidence for the critical importance of GST genes in resistance evolution.

Robustness in population-structure and demographic-inference results derived from the Aedes aegypti genotyping chip and whole-genome sequencing data

The mosquito Aedes aegypti is the primary vector of many human arboviruses such as dengue, yellow fever, chikungunya, and Zika, which affect millions of people worldwide. Population genetic studies on this mosquito have been important in understanding its invasion pathways and success as a vector of human disease. The Axiom aegypti1 SNP chip was developed from a sample of geographically diverse A. aegypti populations to facilitate genomic studies on this species. We evaluate the utility of the Axiom aegypti1 SNP chip for population genetics and compare it with a low-depth shotgun sequencing approach using mosquitoes from the native (Africa) and invasive ranges (outside Africa). These analyses indicate that results from the SNP chip are highly reproducible and have a higher sensitivity to capture alternative alleles than a low-coverage whole-genome sequencing approach. Although the SNP chip suffers from ascertainment bias, results from population structure, ancestry, demographic, and phylogenetic analyses using the SNP chip were congruent with those derived from low-coverage whole-genome sequencing, and consistent with previous reports on Africa and outside Africa populations using microsatellites. More importantly, we identified a subset of SNPs that can be reliably used to generate merged databases, opening the door to combined analyses. We conclude that the Axiom aegypti1 SNP chip is a convenient, more accurate, low-cost alternative to low-depth whole-genome sequencing for population genetic studies of A. aegypti that do not rely on full allelic frequency spectra. Whole-genome sequencing and SNP chip data can be easily merged, extending the usefulness of both approaches.

Predicting species invasiveness with genomic data: Is genomic offset related to establishment probability?

Predicting the risk of establishment and spread of populations outside their native range represents a major challenge in evolutionary biology. Various methods have recently been developed to estimate population (mal)adaptation to a new environment with genomic data via so-called Genomic Offset (GO) statistics. These approaches are particularly promising for studying invasive species but have still rarely been used in this context. Here, we evaluated the relationship between GO and the establishment probability of a population in a new environment using both in silico and empirical data. First, we designed invasion simulations to evaluate the ability to predict establishment probability of two GO computation methods (Geometric GO and Gradient Forest) under several conditions. Additionally, we aimed to evaluate the interpretability of absolute Geometric GO values, which theoretically represent the adaptive genetic distance between populations from distinct environments. Second, utilizing public empirical data from the crop pest species Bactrocera tryoni, a fruit fly native from Northern Australia, we computed GO between "source" populations and a diverse range of locations within invaded areas. This practical application of GO within the context of a biological invasion underscores its potential in providing insights and guiding recommendations for future invasion risk assessment. Overall, our results suggest that GO statistics represent good predictors of the establishment probability and may thus inform invasion risk, although the influence of several factors on prediction performance (e.g., propagule pressure or admixture) will need further investigation.

Limited evidence for genetic differentiation or adaptation in two amphibian species across replicated rural-urban gradients

Urbanization leads to complex environmental changes and poses multiple challenges to organisms. Amphibians are highly susceptible to the effects of urbanization, with land use conversion, habitat destruction, and degradation ranked as the most significant threats. Consequently, amphibians are declining in urban areas, in both population numbers and abundance, however, the effect of urbanization on population genetic parameters remains unclear. Here, we studied the genomic response to urbanization in two widespread European species, the common toad Bufo bufo (26 localities, 480 individuals), and the smooth newt Lissotriton vulgaris (30 localities, 516 individuals) in three geographic regions: southern and northern Poland and southern Norway. We assessed genome-wide SNP variation using RADseq (ca. 42 and 552 thousand SNPs in toads and newts, respectively) and adaptively relevant major histocompatibility complex (MHC) class I and II genes. The results linked most of the genetic differentiation in both marker types to regional (latitudinal) effects, which also correspond to historical biogeography. Further, we did not find any association between genetic differentiation and level of urbanization at local scales for either species. However, urban smooth newts, but not toads, have lower levels of within-population genome-wide diversity, suggesting higher susceptibility to the negative effects of urbanization. A decreasing level of genetic diversity linked to increasing urbanization was also found for MHC II in smooth newts, while the relationship between MHC class I diversity and urbanization differed between geographic regions. We did not find any effects of urbanization on MHC diversity in the toad populations. Although two genetic environment association analyses of genome-wide data, LFMM and BayPass, revealed numerous (219 in B. bufo and 7040 in L. vulgaris) SNPs statistically associated with urbanization, we found a marked lack of repeatability between geographic regions, suggesting a complex and multifaceted response to natural selection elicited by life in the city.

Geogenomic Predictors of Genetree Heterogeneity Explain Phylogeographic and Introgression History: A Case Study in an Amazonian Bird (Thamnophilus aethiops)

Can knowledge about genome architecture inform biogeographic and phylogenetic inference? Selection, drift, recombination, and gene flow interact to produce a genomic landscape of divergence wherein patterns of differentiation and genealogy vary nonrandomly across the genomes of diverging populations. For instance, genealogical patterns that arise due to gene flow should be more likely to occur on smaller chromosomes, which experience high recombination, whereas those tracking histories of geographic isolation (reduced gene flow caused by a barrier) and divergence should be more likely to occur on larger and sex chromosomes. In Amazonia, populations of many bird species diverge and introgress across rivers, resulting in reticulated genomic signals. Herein, we used reduced representation genomic data to disentangle the evolutionary history of 4 populations of an Amazonian antbird, Thamnophilus aethiops, whose biogeographic history was associated with the dynamic evolution of the Madeira River Basin. Specifically, we evaluate whether a large river capture event ca. 200 Ka, gave rise to reticulated genealogies in the genome by making spatially explicit predictions about isolation and gene flow based on knowledge about genomic processes. We first estimated chromosome-level phylogenies and recovered 2 primary topologies across the genome. The first topology (T1) was most consistent with predictions about population divergence and was recovered for the Z-chromosome. The second (T2), was consistent with predictions about gene flow upon secondary contact. To evaluate support for these topologies, we trained a convolutional neural network to classify our data into alternative diversification models and estimate demographic parameters. The best-fit model was concordant with T1 and included gene flow between non-sister taxa. Finally, we modeled levels of divergence and introgression as functions of chromosome length and found that smaller chromosomes experienced higher gene flow. Given that (1) genetrees supporting T2 were more likely to occur on smaller chromosomes and (2) we found lower levels of introgression on larger chromosomes (and especially the Z-chromosome), we argue that T1 represents the history of population divergence across rivers and T2 the history of secondary contact due to barrier loss. Our results suggest that a significant portion of genomic heterogeneity arises due to extrinsic biogeographic processes such as river capture interacting with intrinsic processes associated with genome architecture. Future phylogeographic studies would benefit from accounting for genomic processes, as different parts of the genome reveal contrasting, albeit complementary histories, all of which are relevant for disentangling the intricate geogenomic mechanisms of biotic diversification. [Amazonia; biogeography; demographic modeling; gene flow; gene tree; genome architecture; geogenomics; introgression; linked selection; neural network; phylogenomic; phylogeography; reproductive isolation; speciation; species tree.].

First Evidence of Thalassochory in the Ficus Genus: Seed Dispersal Using the Kuroshio Oceanic Current

AIM

Plants distributed between southern Taiwan and the north of the Philippines are spread among numerous small islands in an area crossed by the powerful Kuroshio current. Oceanic currents can be effective seed-dispersal agents for coastal plant species. Moreover, the Luzon Strait is an area prone to tropical cyclones. The aim of this study is to look at the dispersal capability of an endangered coastal plant species, the Mearns fig (Ficus pedunculosa var. mearnsii), using both experimental and population genetics methods.

LOCATION

Southern Taiwan, the Philippines, and the islands between Luzon and Taiwan Island.

METHODS

This study combined two types of analysis, i.e., buoyancy experiments on syconia and double digest restriction-associated DNA sequencing (ddRAD), to analyze the population genetics of the Mearns fig.

RESULTS

We first discovered that mature Mearns fig syconia could float in seawater. They have a mean float duration of 10 days to a maximum of 21 days. Germination rates varied significantly between Mearns fig seeds that had undergone different durations of flotation treatment. Population genetic analysis shows a high degree of inbreeding among various Mearns fig populations. Moreover, no isolation by distance was found between the populations and individuals.

MAIN CONCLUSIONS

From our analysis of the genetic structure of the Mearns fig populations, we can clearly highlight the effect of the Kuroshio oceanic current on the seed dispersal of this fig tree. Comprehensive analysis has shown that Mearns fig seeds are still viable before the mature syconium sinks into the seawater, and so they could use the Kuroshio Current to float to the current population locations in Taiwan.

Selection signatures and landscape genomics analysis to reveal climate adaptation of goat breeds

Goats have achieved global prominence as essential livestock since their initial domestication, primarily owing to their remarkable adaptability to diverse environmental and production systems. Differential selection pressures influenced by climate have led to variations in their physical attributes, leaving genetic imprints within the genomes of goat breeds raised in diverse agroecological settings. In light of this, our study pursued a comprehensive analysis, merging environmental data with single nucleotide polymorphism (SNP) variations, to unearth indications of selection shaped by climate-mediated forces in goats. Through the examination of 43,300 SNPs from 51 indigenous goat breeds adapting to different climatic conditions using four analytical methods: latent factor mixed models (LFMM), F-statistics (Fst), Extended haplotype homozygosity across populations (XPEHH), and spatial analysis method (SAM), A total of 74 genes were revealed to display clear signs of selection, which are believed to be influenced by climatic conditions. Among these genes, 32 were consistently identified by at least two of the applied methods, and three genes (DENND1A, PLCB1, and ITPR2) were confirmed by all four approaches. Moreover, our investigation yielded 148 Gene Ontology (GO) terms based on these 74 genes, underlining pivotal biological pathways crucial for environmental adaptation. These pathways encompass functions like vascular smooth muscle contraction, cellular response to heat, GTPase regulator activity, rhythmic processes, and responses to temperature stimuli. Of significance, GO terms about endocrine regulation and energy metabolic responses, key for local adaptation were also uncovered, including biological processes, such as cell differentiation, regulation of peptide hormone secretion, and lipid metabolism. These findings contribute to our knowledge of the genetic structure of climate-triggered adaptation across the goat genome and have practical implications for marker-assisted breeding in goats.

Genetic diversity, disease resistance, and environmental adaptation of Arachis duranensis L.: New insights from landscape genomics

The genetic diversity that exists in natural populations of Arachis duranensis, the wild diploid donor of the A subgenome of cultivated tetraploid peanut, has the potential to improve crop adaptability, resilience to major pests and diseases, and drought tolerance. Despite its potential value for peanut improvement, limited research has been focused on the association between allelic variation, environmental factors, and response to early (ELS) and late leaf spot (LLS) diseases. The present study implemented a landscape genomics approach to gain a better understanding of the genetic variability of A. duranensis represented in the ex-situ peanut germplasm collection maintained at the U.S. Department of Agriculture, which spans the entire geographic range of the species in its center of origin in South America. A set of 2810 single nucleotide polymorphism (SNP) markers allowed a high-resolution genome-wide characterization of natural populations. The analysis of population structure showed a complex pattern of genetic diversity with five putative groups. The incorporation of bioclimatic variables for genotype-environment associations, using the latent factor mixed model (LFMM2) method, provided insights into the genomic signatures of environmental adaptation, and led to the identification of SNP loci whose allele frequencies were correlated with elevation, temperature, and precipitation-related variables (q < 0.05). The LFMM2 analysis for ELS and LLS detected candidate SNPs and genomic regions on chromosomes A02, A03, A04, A06, and A08. These findings highlight the importance of the application of landscape genomics in ex situ collections of peanut and other crop wild relatives to effectively identify favorable alleles and germplasm for incorporation into breeding programs. We report new sources of A. duranensis germplasm harboring adaptive allelic variation, which have the potential to be utilized in introgression breeding for a single or multiple environmental factors, as well as for resistance to leaf spot diseases.

Mousa K, Istanbuli T, Abd El-Maksoud MM, Tawkaz S, Hamwieh A. Unveiling the genetic basis of Fusarium wilt resistance in chickpea using GWAS analysis and characterization of candidate genes

Introduction: Chickpea is a legume crop that thrives in regions with semi-arid or temperate climates. Its seeds are an excellent source of proteins, carbohydrates, and minerals, especially high-quality proteins. Chickpea cultivation faces several challenges including Fusarium wilt (FW), a major fungal disease that significantly reduces productivity. Methods: In this study, a Genome-wide Association Analysis (GWAS) was conducted to identify multiple genomic loci associated with FW resistance in chickpea. We conducted a comprehensive evaluation of 180 chickpea genotypes for FW resistance across three distinct locations (Ethiopia, Tunisia, and Lebanon) during the 2-year span from 2015 to 2016. Disease infection measurements were recorded, and the wilt incidence of each genotype was calculated. We employed a set of 11,979 single nucleotide polymorphisms (SNPs) markers distributed across the entire chickpea genome for SNP genotyping. Population structure analysis was conducted to determine the genetic structure of the genotypes. Results and Discussion: The population structure unveiled that the analyzed chickpea germplasm could be categorized into four sub-populations. Notably, these sub-populations displayed diverse geographic origins. The GWAS identified 11 SNPs associated with FW resistance, dispersed across the genome. Certain SNPs were consistent across trials, while others were specific to particular environments. Chromosome CA2 harbored five SNP markers, CA5 featured two, and CA4, CA6, CA7, and CA8 each had one representative marker. Four SNPs demonstrated an association with FW resistance, consistently observed across a minimum of three distinct environments. These SNPs included SNP5826041, SNP5825086, SNP11063413, SNP5825195, which located in CaFeSOD, CaS13like, CaNTAQ1, and CaAARS genes, respectively. Further investigations were conducted to gain insights into the functions of these genes and their role in FW resistance. This progress holds promise for reducing the negative impact of the disease on chickpea production.

The genomic response to urbanization in the damselfly Ischnura elegans

The complex and rapid environmental changes brought about by urbanization pose significant challenges to organisms. The multifaceted effects of urbanization often make it difficult to define and pinpoint the very nature of adaptive urban phenotypes. In such situations, scanning genomes for regions differentiated between urban and non-urban populations may be an attractive approach. Here, we investigated the genomic signatures of adaptation to urbanization in the damselfly Ischnura elegans sampled from 31 rural and urban localities in three geographic regions: southern and northern Poland, and southern Sweden. Genome-wide variation was assessed using more than 370,000 single nucleotide polymorphisms (SNPs) genotyped by ddRADseq. Associations between SNPs and the level of urbanization were tested using two genetic environment association methods: Latent Factors Mixed Models and BayPass. While we found numerous candidate SNPs and a highly significant overlap between candidates identified by the two methods within the geographic regions, there was a distinctive lack of repeatability between the geographic regions both at the level of individual SNPs and of genomic regions. However, we found "synapse organization" at the top of the functional categories enriched among the genes located in the proximity of the candidate urbanization SNPs. Interestingly, the overall significance of "synapse organization" was built up by the accretion of different genes associated with candidate SNPs in different geographic regions. This finding is consistent with the highly polygenic nature of adaptation, where the response may be achieved through a subtle adjustment of allele frequencies in different genes that contribute to adaptive phenotypes. Taken together, our results point to a polygenic adaptive response in the nervous system, specifically implicating genes involved in synapse organization, which mirrors the findings from several genomic and behavioral studies of adaptation to urbanization in other taxa.

Genome-wide association analysis identifies natural allelic variants associated with panicle architecture variation in African rice, Oryza glaberrima Steud

African rice (Oryza glaberrima Steud), a short-day cereal crop closely related to Asian rice (Oryza sativa L.), has been cultivated in Sub-Saharan Africa for ∼ 3,000 years. Although less cultivated globally, it is a valuable genetic resource in creating high-yielding cultivars that are better adapted to diverse biotic and abiotic stresses. While inflorescence architecture, a key trait for rice grain yield improvement, has been extensively studied in Asian rice, the morphological and genetic determinants of this complex trait are less understood in African rice. In this study, using a previously developed association panel of 162 O. glaberrima accessions and new SNP variants characterized through mapping to a new version of the O. glaberrima reference genome, we conducted a genome-wide association study of four major morphological panicle traits. We have found a total of 41 stable genomic regions that are significantly associated with these traits, of which 13 co-localized with previously identified QTLs in O. sativa populations and 28 were unique for this association panel. Additionally, we found a genomic region of interest on chromosome 3 that was associated with the number of spikelets and primary and secondary branches. Within this region was localized the O. sativa ortholog of the PHYTOCHROME B gene (Oglab_006903/OgPHYB). Haplotype analysis revealed the occurrence of natural sequence variants at the OgPHYB locus associated with panicle architecture variation through modulation of the flowering time phenotype, whereas no equivalent alleles were found in O. sativa. The identification in this study of genomic regions specific to O. glaberrima indicates panicle-related intra-specific genetic variation in this species, increasing our understanding of the underlying molecular processes governing panicle architecture. Identified candidate genes and major haplotypes may facilitate the breeding of new African rice cultivars with preferred panicle traits.

Genomic Signatures of Local Adaptation under High Gene Flow in Lumpfish-Implications for Broodstock Provenance Sourcing and Larval Production

Aquaculture of the lumpfish (Cyclopterus lumpus L.) has become a large, lucrative industry owing to the escalating demand for "cleaner fish" to minimise sea lice infestations in Atlantic salmon mariculture farms. We used over 10K genome-wide single nucleotide polymorphisms (SNPs) to investigate the spatial patterns of genomic variation in the lumpfish along the coast of Norway and across the North Atlantic. Moreover, we applied three genome scans for outliers and two genotype-environment association tests to assess the signatures and patterns of local adaptation under extensive gene flow. With our 'global' sampling regime, we found two major genetic groups of lumpfish, i.e., the western and eastern Atlantic. Regionally in Norway, we found marginal evidence of population structure, where the population genomic analysis revealed a small portion of individuals with a different genetic ancestry. Nevertheless, we found strong support for local adaption under high gene flow in the Norwegian lumpfish and identified over 380 high-confidence environment-associated loci linked to gene sets with a key role in biological processes associated with environmental pressures and embryonic development. Our results bridge population genetic/genomics studies with seascape genomics studies and will facilitate genome-enabled monitoring of the genetic impacts of escapees and allow for genetic-informed broodstock selection and management in Norway.

Phylogeography of the Sunda pangolin, Manis javanica: Implications for taxonomy, conservation management and wildlife forensics

The Sunda pangolin (Manis javanica) is the most widely distributed Asian pangolin species, occurring across much of Southeast Asia and in southern China. It is classified as Critically Endangered and is one of the most trafficked mammals in the world, which not only negatively impacts wild Sunda pangolin populations but also poses a potential disease risk to other species, including humans and livestock. Here, we aimed to investigate the species' phylogeography across its distribution to improve our understanding of the species' evolutionary history, elucidate any taxonomic uncertainties and enhance the species' conservation genetic management and potential wildlife forensics applications. We sequenced mtDNA genomes from 23 wild Sunda pangolins of known provenance originating from Malaysia to fill sampling gaps in previous studies, particularly in Borneo. To conduct phylogenetic and population genetic analyses of Sunda pangolins across their range, we integrated these newly generated mitochondrial genomes with previously generated mtDNA and nuclear DNA data sets (RAD-seq SNP data). We identified an evolutionarily distinct mtDNA lineage in north Borneo, estimated to be ~1.6 million years divergent from lineages in west/south Borneo and the mainland, comparable to the divergence time from the Palawan pangolin. There appeared to be mitonuclear discordance, with no apparent genetic structure across Borneo based on analysis of nuclear SNPs. These findings are consistent with the 'out of Borneo hypothesis', whereby Sunda pangolins diversified in Borneo before subsequently migrating throughout Sundaland, and/or a secondary contact scenario between mainland and Borneo. We have elucidated possible taxonomic issues in the Sunda/Palawan pangolin complex and highlight the critical need for additional georeferenced samples to accurately apportion its range-wide genetic variation into appropriate taxonomic and conservation units. Additionally, these data have improved forensic identification testing involving these species and permit the implementation of geographic provenance testing in some scenarios.

Population transcriptomics uncover the relative roles of positive selection and differential expression in Batrachium bungei adaptation to the Qinghai-Tibetan plateau

KEY MESSAGE

Positive selection genes are related to metabolism, while differentially expressed genes are related to photosynthesis, suggesting that genetic adaptation and expression regulation may play independent roles in different gene classes. Genome-wide investigation of the molecular mechanisms for high-altitude adaptation is an intriguing topic in evolutionary biology. The Qinghai-Tibet Plateau (QTP) with its extremely variable environments is an ideal site for studying high-altitude adaptation. Here, we used transcriptome data of 100 individuals from 20 populations collected from various altitudes on the QTP to investigate the adaptive mechanisms of the aquatic plant Batrachium bungei at both the genetic and transcriptional level. To explore genes and biological pathways that may contribute to QTP adaptation, we employed a two-step approach, in which we identified positively selected genes and differentially expressed genes using the landscape genomic and differential expression approaches. The positive selection analysis showed that genes involved in metabolic regulation played a crucial role in B. bungei adaptation to the extreme environments of the QTP, especially intense ultraviolet radiation. Altitude-based differential expression analysis suggested that B. bungei could increase the rate of energy dissipation or reduce the efficiency of light energy absorption by down regulating the expression of photosynthesis-related genes to adapt to the strong ultraviolet radiation. Weighted gene co-expression network analysis identified ribosomal genes as hubs of altitude adaptation in B. bungei. Only a small part of genes (about 10%) overlapped between positively selected genes and differentially expressed genes in B. bungei, suggesting that genetic adaptation and gene expression regulation might play relatively independent roles in different categories of functional genes. Taken together, this study enriches our understanding of the high-altitude adaptation mechanism of B. bungei on the QTP.

Re-thinking the environment in landscape genomics

Detecting the extrinsic selective pressures shaping genomic variation is critical for a better understanding of adaptation and for forecasting evolutionary responses of natural populations to changing environmental conditions. With increasing availability of geo-referenced environmental data, landscape genomics provides unprecedented insights into how genomic variation and underlying gene functions affect traits potentially under selection. Yet, the robustness of genotype-environment associations used in landscape genomics remains tempered due to various limitations, including the characteristics of environmental data used, sampling designs employed, and statistical frameworks applied. Here, we argue that using complementary or new environmental data sources and well-informed sampling designs may help improve the detection of selective pressures underlying patterns of local adaptation in various organisms and environments.

Museum Genomics of an Agricultural Super-Pest, the Colorado Potato Beetle, Leptinotarsa decemlineata (Chrysomelidae), Provides Evidence of Adaptation from Standing Variation

Despite extensive research on agricultural pests, our knowledge about their evolutionary history is often limited. A mechanistic understanding of the demographic changes and modes of adaptation remains an important goal, as it improves our understanding of organismal responses to environmental change and our ability to sustainably manage pest populations. Emerging genomic datasets now allow for characterization of demographic and adaptive processes, but face limits when they are drawn from contemporary samples, especially in the context of strong demographic change, repeated selection, or adaptation involving modest shifts in allele frequency at many loci. Temporal sampling, however, can improve our ability to reconstruct evolutionary events. Here, we leverage museum samples to examine whether population genomic diversity and structure has changed over time, and to identify genomic regions that appear to be under selection. We focus on the Colorado potato beetle (CPB), Leptinotarsa decemlineata (Say 1824; Coleoptera: Chrysomelidae), which is widely regarded as a super-pest due to its rapid, and repeated, evolution to insecticides. By combining whole genome resequencing data from 78 museum samples with modern sampling, we demonstrate that CPB expanded rapidly in the 19th century, leading to a reduction in diversity and limited genetic structure from the Midwest to Northeast United States. Temporal genome scans provide extensive evidence for selection acting in resistant field populations in Wisconsin and New York, including numerous known insecticide resistance genes. We also validate these results by showing that known selective sweeps in modern populations are identified by our genome scan. Perhaps most importantly, temporal analysis indicates selection on standing genetic variation, as we find evidence for parallel evolution in the two geographical regions. Parallel evolution involves a range of phenotypic traits not previously identified as under selection in CPB, such as reproductive and morphological functional pathways that might be important for adaptation to agricultural habitats.

Genomic footprints of selection in early-and late-flowering pearl millet landraces

Pearl millet is among the top three-cereal production in one of the most climate vulnerable regions, sub-Saharan Africa. Its Sahelian origin makes it adapted to grow in poor sandy soils under low soil water regimes. Pearl millet is thus considered today as one of the most interesting crops to face the global warming. Flowering time, a trait highly correlated with latitude, is one of the key traits that could be modulated to face future global changes. West African pearl millet landraces, can be grouped into early- (EF) and late-flowering (LF) varieties, each flowering group playing a specific role in the functioning and resilience of Sahelian smallholders. The aim of this study was thus to detect genes linked to flowering but also linked to relevant traits within each flowering group. We thus investigated genomic and phenotypic diversity in 109 pearl millet landrace accessions, i.e., 66 early-flowering and 43 late-flowering, grown in the groundnut basin, the first area of rainfed agriculture in Senegal dominated by dry cereals (millet, maize, and sorghum) and legumes (groundnuts, cowpeas). We were able to confirm the role of PhyC gene in pearl millet flowering and identify several other genes that appear to be as much as important, such as FSR12 and HAC1. HAC1 and two other genes appear to be part of QTLs previously identified and deserve further investigation. At the same time, we were able to highlight a several genes and variants that could contribute to the improvement of pearl millet yield, especially since their impact was demonstrated across flowering cycles.

Genome-wide analysis identified candidate variants and genes associated with heat stress adaptation in Egyptian sheep breeds

Heat stress caused by climatic changes is one of the most significant stresses on livestock in hot and dry areas. It has particularly adverse effects on the ability of the breed to maintain homeothermy. Developing countries are advised to protect and prepare their animal resources in the face of potential threats such as climate change. The current study was conducted in Egypt's three hot and dry agro-ecological zones. Three local sheep breeds (Saidi, Wahati, and Barki) were studied with a total of 206 ewes. The animals were exercised under natural heat stress. The heat tolerance index of the animals was calculated to identify animals with high and low heat tolerance based on their response to meteorological and physiological parameters. Genomic variation in these breeds was assessed using 64,756 single nucleotide polymorphic markers (SNPs). From the perspective of comparative adaptability to harsh conditions, our objective was to investigate the genomic structure that might control the adaptability of local sheep breeds to environmental stress under hot and dry conditions. In addition, indices of population structure and diversity of local breeds were examined. Measures of genetic diversity showed a significant influence of breed and location on populations. The standardized index of association (rbarD) ranged from 0.0012 (Dakhla) to 0.026 (Assuit), while for the breed, they ranged from 0.004 (Wahati) to 0.0103 (Saidi). The index of association analysis (Ia) ranged from 1.42 (Dakhla) to 35.88 (Assuit) by location and from 6.58 (Wahati) to 15.36 (Saidi) by breed. The most significant SNPs associated with heat tolerance were found in the MYO5A, PRKG1, GSTCD, and RTN1 genes (p ≤ 0.0001). MYO5A produces a protein widely distributed in the melanin-producing neural crest of the skin. Genetic association between genetic and phenotypic variations showed that OAR1_18300122.1, located in ST3GAL3, had the greatest positive effect on heat tolerance. Genome-wide association analysis identified SNPs associated with heat tolerance in the PLCB1, STEAP3, KSR2, UNC13C, PEBP4, and GPAT2 genes.

Physiological and genetic control of transpiration efficiency in African rice, Oryza glaberrima Steud

Improving crop water use efficiency, the amount of carbon assimilated as biomass per unit of water used by a plant, is of major importance as water for agriculture becomes scarcer. In rice, the genetic bases of transpiration efficiency, the derivation of water use efficiency at the whole-plant scale, and its putative component trait transpiration restriction under high evaporative demand remain unknown. These traits were measured in 2019 in a panel of 147 African rice (Oryza glaberrima) genotypes known to be potential sources of tolerance genes to biotic and abiotic stresses. Our results reveal that higher transpiration efficiency is associated with transpiration restriction in African rice. Detailed measurements in a subset of highly contrasted genotypes in terms of biomass accumulation and transpiration confirmed these associations and suggested that root to shoot ratio played an important role in transpiration restriction. Genome wide association studies identified marker-trait associations for transpiration response to evaporative demand, transpiration efficiency, and its residuals, with links to genes involved in water transport and cell wall patterning. Our data suggest that root-shoot partitioning is an important component of transpiration restriction that has a positive effect on transpiration efficiency in African rice. Both traits are heritable and define targets for breeding rice with improved water use strategies.

The use of various statistical methods for authenticity and detection of adulteration in fish and seafood

Various methodologies including genetic analyses, morphometrics, proteomics, lipidomics, metabolomics, etc. are now used or being developed to authenticate fish and seafood. Such techniques usually lead to the generation of enormous amounts of data. The analysis and interpretation of this information can be particularly challenging. Statistical techniques are therefore commonly used to assist in analyzing these data, visualizing trends and differences and extracting conclusions. This review article aims at presenting and discussing statistical methods used in studies on fish and seafood authenticity and adulteration, allowing researchers to consider their options based on previous successes/failures but also offering some recommendations about the future of such techniques. Techniques such as PCA, AMOVA and FST statistics, that allow the differentiation of genetic groups, or techniques such as MANOVA that allow large data sets of morphometric characteristics or elemental differences to be analyzed are discussed. Furthermore, methods such as cluster analysis, DFA, CVA, CDA and heatmaps/Circos plots that allow samples to be differentiated based on their geographical origin are also reviewed and their advantages and disadvantages as found in past studies are given. Finally, mathematical simulations and modeling are presented in a detailed review of studies using them, together with their advantages and limitations.

AlleleShift: an R package to predict and visualize population-level changes in allele frequencies in response to climate change

Background

At any particular location, frequencies of alleles that are associated with adaptive traits are expected to change in future climates through local adaption and migration, including assisted migration (human-implemented when climate change is more rapid than natural migration rates). Making the assumption that the baseline frequencies of alleles across environmental gradients can act as a predictor of patterns in changed climates (typically future but possibly paleo-climates), a methodology is provided by AlleleShift of predicting changes in allele frequencies at the population level.

Methods

The prediction procedure involves a first calibration and prediction step through redundancy analysis (RDA), and a second calibration and prediction step through a generalized additive model (GAM) with a binomial family. As such, the procedure is fundamentally different to an alternative approach recently proposed to predict changes in allele frequencies from canonical correspondence analysis (CCA). The RDA step is based on the Euclidean distance that is also the typical distance used in Analysis of Molecular Variance (AMOVA). Because the RDA step or CCA approach sometimes predict negative allele frequencies, the GAM step ensures that allele frequencies are in the range of 0 to 1.

Results

AlleleShift provides data sets with predicted frequencies and several visualization methods to depict the predicted shifts in allele frequencies from baseline to changed climates. These visualizations include 'dot plot' graphics (function shift.dot.ggplot), pie diagrams (shift.pie.ggplot), moon diagrams (shift.moon.ggplot), 'waffle' diagrams (shift.waffle.ggplot) and smoothed surface diagrams of allele frequencies of baseline or future patterns in geographical space (shift.surf.ggplot). As these visualizations were generated through the ggplot2 package, methods of generating animations for a climate change time series are straightforward, as shown in the documentation of AlleleShift and in the supplemental videos.

Availability

AlleleShift is available as an open-source R package from https://cran.r-project.org/package=AlleleShift and https://github.com/RoelandKindt/AlleleShift. Genetic input data is expected to be in the adegenet::genpop format, which can be generated from the adegenet::genind format. Climate data is available from various resources such as WorldClim and Envirem.

How well do genetic markers inform about responses to intraspecific admixture? A comparative analysis of microsatellites and RADseq

Background

Fitness consequences of intraspecific genetic admixture can vary from positive to negative depending on the genetic composition of the populations and environmental conditions. Because admixture has potential to influence the success of management and conservation efforts, genetic similarity has been suggested to be used as a proxy to predict the outcome. Studies utilizing microsatellites (a neutral marker) to investigate associations between genetic distance and admixture effects show conflicting results. Marker types that yield information on genome-wide and/or adaptive variation might be more useful for predicting responses to inter-population hybridization. In this study we utilized published data for three populations of pike (Esox lucius) to investigate associations between offspring performance (hatching success) and parental genetic similarity in experimentally purebred and admixed families, based on neutral (microsatellites), genome-wide neutral (RADseq SNPs), and adaptive (SNPs under selection) markers.

Results

Estimated similarity varied among the markers, likely reflecting differences in their inherent properties, but was consistently higher in purebred than admixed families. A significant interaction between marker type and admixture treatment reflected that neutral SNPs yielded higher estimates than adaptive SNPs for admixed families whereas no difference was found for purebred families, which indicates that neutral similarity was not reflective of adaptive similarity. When all samples were pooled, no association between similarity and performance was found for any marker. For microsatellites, similarity was positively correlated with hatching success in purebred families, whereas no association was found in admixed families; however, the direction of the effect differed between the population combinations.

Conclusions

The results strengthen the notion that, as of today, there is no proxy that can reliably predicted the outcome of admixture. This emphasizes the need of further studies to advance knowledge that can shed light on how to safeguard against negative consequences of admixture, and thereby inform management and promote conservation of biological diversity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00974-3.

Prospects and limitations of genomic offset in conservation management

In nature conservation, there is keen interest in predicting how populations will respond to environmental changes such as climate change. These predictions can help determine whether a population can be self-sustaining under future alterations of its habitat or whether it may require human intervention such as protection, restoration, or assisted migration. An increasingly popular approach in this respect is the concept of genomic offset, which combines genomic and environmental data from different time points and/or locations to assess the degree of possible maladaptation to new environmental conditions. Here, we argue that the concept of genomic offset holds great potential, but an exploration of its risks and limitations is needed to use it for recommendations in conservation or assisted migration. After briefly describing the concept, we list important issues to consider (e.g., statistical frameworks, population genetic structure, migration, independent evidence) when using genomic offset or developing these methods further. We conclude that genomic offset is an area of development that still lacks some important features and should be used in combination with other approaches to inform conservation measures.