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.

Genomic evidence for climate-linked diversity loss and increased vulnerability of wild barley spanning 28 years of climate warming

The information on how plant populations respond genetically to climate warming is scarce. Here, landscape genomic and machine learning approaches were integrated to assess genetic response of 10 wild barley (Hordeum vulgare ssp. spontaneum; WB) populations in the past and future, using whole genomic sequencing (WGS) data. The WB populations were sampled in 1980 and again in 2008. Phylogeny of accessions was roughly in conformity with sampling sites, which accompanied by admixture/introgressions. The 28-y climate warming resulted in decreased genetic diversity, increased selection pressure, and an increase in deleterious single nucleotide polymorphism (dSNP) numbers, heterozygous deleterious and total deleterious burdens for WB. Genome-environment associations identified some candidate genes belonging to peroxidase family (HORVU2Hr1G057450, HORVU4Hr1G052060 and HORVU4Hr1G057210) and heat shock protein 70 family (HORVU2Hr1G112630). The gene HORVU2Hr1G120170 identified by selective sweep analysis was under strong selection during the climate warming of the 28-y, and its derived haplotypes were fixed by WB when faced with the 28-y increasingly severe environment. Temperature variables were found to be more important than precipitation variables in influencing genomic variation, with an eco-physiological index gdd5 (growing degree-days at the baseline threshold temperature of 5 °C) being the most important determinant. Gradient forest modelling revealed higher predicted genomic vulnerability in Sede Boqer under future climate scenarios at 2041-2070 and 2071-2100. Additionally, estimates of effective population size (Ne) tracing back to 250 years indicated a forward decline in all populations over time. Our assessment about past genetic response and future vulnerability of WB under climate warming is crucial for informing conservation efforts for wild cereals and rational use strategies.

Genomic signatures of local adaptation in recent invasive Aedes aegypti populations in California

BACKGROUND

Rapid adaptation to new environments can facilitate species invasions and range expansions. Understanding the mechanisms of adaptation used by invasive disease vectors in new regions has key implications for mitigating the prevalence and spread of vector-borne disease, although they remain relatively unexplored.

RESULTS

Here, we integrate whole-genome sequencing data from 96 Aedes aegypti mosquitoes collected from various sites in southern and central California with 25 annual topo-climate variables to investigate genome-wide signals of local adaptation among populations. Patterns of population structure, as inferred using principal components and admixture analysis, were consistent with three genetic clusters. Using various landscape genomics approaches, which all remove the confounding effects of shared ancestry on correlations between genetic and environmental variation, we identified 112 genes showing strong signals of local environmental adaptation associated with one or more topo-climate factors. Some of them have known effects in climate adaptation, such as heat-shock proteins, which shows selective sweep and recent positive selection acting on these genomic regions.

CONCLUSIONS

Our results provide a genome wide perspective on the distribution of adaptive loci and lay the foundation for future work to understand how environmental adaptation in Ae. aegypti impacts the arboviral disease landscape and how such adaptation could help or hinder efforts at population control.

Deciphering local adaptation of native Indian cattle (Bos indicus) breeds using landscape genomics and in-silico prediction of deleterious SNP effects on protein structure and function

India has 50 registered breeds of native cattle (Bos indicus) which are locally adapted to diverse environmental conditions. This study aimed to investigate the genomic basis of adaptation of native Indian cattle and to predict the impact of key SNPs on the amino acid changes that affect protein function. The Illumina 777 K BovineHD BeadChip was used to genotype 178 native cattle belonging to contrasting landscapes and agro-climatic conditions. The genotype-environment association was investigated with R. SamBada, using 5,74,382 QC passed SNPs and 11 predictor variables (10 multi-collinearity controlled environmental variables and 1 variable as "score of PCA" on ancestry coefficients of individuals). In total, 1,12,780 models were selected as significant (q < 0.05) based on G score. The pathway ontology of the annotated genes revealed many important pathways and genes having a direct and indirect role in cold and hot adaptation. Only ten SNP variants had a SIFT score of < 0.05 (deleterious), and only two of them, each lying in the genes CRYBA1 and USP18, were predicted to be deleterious with high confidence. RaptorX predicted the tertiary structures of proteins encoded by wild and mutant variants of these genes. The quality of the models was determined using Ramachandran plots and RaptorX parameters, indicating that they are accurate. RaptorX and I-Mutant 2.0 softwares revealed significant differences among wild and mutant proteins. Adaptive alleles identified in the present investigation might be responsible for the local adaptation of these cattle breeds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03493-3.

A brief history of population genetic research in California and an evaluation of its utility for conservation decision-making

A recently published macrogenetic dataset of California's flora and fauna, CaliPopGen, comprehensively summarizes population genetic research published between 1985-2020. Integrating these genetic data into the requisite "best available science" upon which conservation professionals rely should facilitate the prioritization of populations based on genetic health. We evaluate the extent to which the CaliPopGen Dataset provides genetic diversity estimates that are 1) unbiased, 2) sufficient in quantity, 3) cover entire species' ranges, and 4) include potentially adaptive loci. We identified genetic diversity estimates for 4,462 spatially-referenced populations of 432 species, confirming California's rich published history of population genetics research. Most recent studies used microsatellites markers, which have uniquely high levels of variation, and estimates of all genetic metrics varied significantly across marker types. Most studies used less than 10 loci for inferences, rendering parameter estimates potentially unreliable, and covered small spatial extents that include only a fraction of the studied species' California distribution (median 16.3%). In contrast, the ongoing California Conservation Genomics Project (CCGP) aims to cover the full geographical and environmental breadth of each species' occupied habitats, and uses a consistent approach based on whole-genome data. However, the CCGP will sequence only 12% of the number of individuals, and covers only about half the evolutionary diversity, of the CaliPopGen Database. There is clearly a place in the evaluation of the genetic health of California for both approaches going forward, especially if differences among studies can be minimized, and overlap emphasized. A complementary use of both datasets is warranted to inform optimal conservation decision-making.

Land use and life history constrain adaptive genetic variation and reduce the capacity for climate change adaptation in turtles

BACKGROUND

Rapid anthropogenic climate change will require species to adapt to shifting environmental conditions, with successful adaptation dependent upon current patterns of genetic variation. While landscape genomic approaches allow for exploration of local adaptation in non-model systems, most landscape genomics studies of adaptive capacity are limited to exploratory identification of potentially important functional genes, often without a priori expectations as to the gene functions that may be most important for climate change responses. In this study, we integrated targeted sequencing of genes of known function and genotyping of single-nucleotide polymorphisms to examine spatial, environmental, and species-specific patterns of potential local adaptation in two co-occuring turtle species: the Blanding's turtle (Emydoidea blandingii) and the snapping turtle (Chelydra serpentina).

RESULTS

We documented divergent patterns of spatial clustering between neutral and putatively adaptive genetic variation in both species. Environmental associations varied among gene regions and between species, with stronger environmental associations detected for genes involved in stress response and for the more specialized Blanding's turtle. Land cover appeared to be more important than climate in shaping spatial variation in functional genes, indicating that human landscape alterations may affect adaptive capacity important for climate change responses.

CONCLUSIONS

Our study provides evidence that responses to climate change will be contingent on species-specific adaptive capacity and past history of exposure to human land cover change.

Multi-Approach Analysis Reveals Local Adaptation in a Widespread Forest Tree of Reunion Island

Detecting processes of local adaptation in forest trees and identifying environmental selective drivers are of primary importance for forest management and conservation. Transplant experiments, functional genomics and population genomics are complementary tools to efficiently characterize heritable phenotypic traits and to decipher the genetic bases of adaptive traits. Using an integrative approach combining phenotypic assessment in common garden, transcriptomics and landscape genomics, we investigated leaf adaptive traits in Coffea mauritiana, a forest tree endemic to Reunion Island. Eight populations of C. mauritiana originating from sites with contrasted environmental conditions were sampled in common garden to assess several leaf morphological traits, to analyze the leaf transcriptome and leaf cuticular wax composition. The relative alkane content of cuticular waxes was significantly correlated with major climatic gradients, paving the way for further transcriptome-based analyses. The expression pattern of cuticle biosynthetic genes was consistent with a modulation of alkane accumulation across the population studied, supporting the hypothesis that the composition of cuticular wax is involved in the local adaptation of C. mauritiana. Association tests in landscape genomics performed using RNA-seq-derived single-nucleotide polymorphisms revealed that genes associated with cell wall remodeling also likely play an adaptive role. By combining these different approaches, this study efficiently identified local adaptation processes in a non-model species. Our results provide the first evidence for local adaptation in trees endemic to Reunion Island and highlight the importance of cuticle composition for the adaptation of trees to the high evaporative demand in warm climates.

Hybridization and introgression between Helicoverpa armigera and H. zea: an adaptational bridge

BACKGROUND

Invasion of organisms into new ecosystems is increasingly common, due to the global trade in commodities. One of the most complex post-invasion scenarios occurs when an invasive species is related to a native pest, and even more so when they can hybridize and produce fertile progeny. The global pest Helicoverpa armigera was first detected in Brazil in 2013 and generated a wave of speculations about the possibility of hybridization with the native sister taxon Helicoverpa zea. In the present study, we used genome-wide single nucleotide polymorphisms from field-collected individuals to estimate hybridization between H. armigera and H. zea in different Brazilian agricultural landscapes.

RESULTS

The frequency of hybridization varied from 15 to 30% depending on the statistical analyses. These methods showed more congruence in estimating that hybrids contained approximately 10% mixed ancestry (i.e. introgression) from either species. Hybridization also varied considerably depending on the geographic locations where the sample was collected, forming a 'mosaic' hybrid zone where introgression may be facilitated by environmental and landscape variables. Both landscape composition and bioclimatic variables indicated that maize and soybean cropland are the main factors responsible for high levels of introgression in agricultural landscapes. The impact of multiple H. armigera incursions is reflected in the structured and inbred pattern of genetic diversity.

CONCLUSIONS

Our data showed that the landscape composition and bioclimatic variables influence the introgression rate between H. armigera and H. zea in agricultural areas. Continuous monitoring of the hybridization process in the field is necessary, since agricultural expansion, climatic fluctuations, changing composition of crop species and varieties, and dynamic planting seasons are some factors in South America that could cause a sudden alteration in the introgression rate between Helicoverpa species. Introgression between invasive and native pests can dramatically impact the evolution of host ranges and resistance management.

Adaptive genetic differentiation in Pterocarya stenoptera (Juglandaceae) driven by multiple environmental variables were revealed by landscape genomics

BACKGROUND

The investigation of the genetic basis of local adaptation in non-model species is an interesting focus of evolutionary biologists and molecular ecologists. Identifying these adaptive genetic variabilities on the genome responsible can provide insight into the genetic mechanism of local adaptation.

RESULTS

We investigated the spatial distribution of genetic variation in 22 natural populations of Pterocarya stenoptera across its distribution area in China to provide insights into the complex interplay between multiple environmental variables and adaptive genetic differentiation. The Bayesian analysis of population structure showed that the 22 populations of P. stenoptera were subdivided into two groups. Redundancy analysis demonstrated that this genetic differentiation was caused by the divergent selection of environmental difference. A total of 44 outlier loci were mutually identified by Arlequin and BayeScan, 43 of which were environment-associated loci (EAL). The results of latent factor mixed model analysis showed that solar radiation in June (Sr6), minimum temperature of the coldest month (Bio6), temperature seasonality (Bio4), and water vapor pressure in January (Wvp1) were associated with the highest numbers of EAL. Sr6 was associated with the ecological habitat of "prefered light", and Bio6 and Wvp1 were associated with the ecological habitat of "warm and humid environment".

CONCLUSIONS

Our results provided empirical evidence that environmental variables related to the ecological habitats of species play key roles in driving adaptive differentiation of species genome.

Modularity of genes involved in local adaptation to climate despite physical linkage

BACKGROUND

Linkage among genes experiencing different selection pressures can make natural selection less efficient. Theory predicts that when local adaptation is driven by complex and non-covarying stresses, increased linkage is favored for alleles with similar pleiotropic effects, with increased recombination favored among alleles with contrasting pleiotropic effects. Here, we introduce a framework to test these predictions with a co-association network analysis, which clusters loci based on differing associations. We use this framework to study the genetic architecture of local adaptation to climate in lodgepole pine, Pinus contorta, based on associations with environments.

RESULTS

We identify many clusters of candidate genes and SNPs associated with distinct environments, including aspects of aridity and freezing, and discover low recombination rates among some candidate genes in different clusters. Only a few genes contain SNPs with effects on more than one distinct aspect of climate. There is limited correspondence between co-association networks and gene regulatory networks. We further show how associations with environmental principal components can lead to misinterpretation. Finally, simulations illustrate both benefits and caveats of co-association networks.

CONCLUSIONS

Our results support the prediction that different selection pressures favor the evolution of distinct groups of genes, each associating with a different aspect of climate. But our results went against the prediction that loci experiencing different sources of selection would have high recombination among them. These results give new insight into evolutionary debates about the extent of modularity, pleiotropy, and linkage in the evolution of genetic architectures.

Landscape genomics reveal that ecological character determines adaptation: a case study in smoke tree (Cotinus coggygria Scop.)

Background

The adaptive evolution of species response to environment are the key issues in molecular ecology and evolutionary biology. The direction of adaptive differentiation of species in regions lacking strong selection pressure is usually diverse. However, the driving mechanism of the diverse adaptive differentiation for regional species is still undetermined to date. In this study, we used landscape genomics modelling to infer the adaptive evolution of Cotinus coggygria in China’s warm-temperate zone.

Results

Using fifteen natural populations and nine start codon targeted (SCoT) markers, a total of 1131 unambiguous loci were yielded. Our results showed two genetic groups existed in the fifteen natural populations of C. coggygria, which is due to the divergent selection driven by six environmental factors. Environmental association analyses revealed the environmental variables related to precipitation were associated with high numbers of environment-associated loci.

Conclusions

Our results indicated that the ecological characters of C. coggygria, i.e. avoiding wetness and tolerating drought, determine its adaptive evolution. This study provides a reference that ecological character determines the adaptive evolution of species in regions lacking strong selection pressure.

Electronic supplementary material

The online version of this article (10.1186/s12862-017-1055-3) contains supplementary material, which is available to authorized users.