Population Genetic Tools Research Articles

Prevalence and population genetic analyses of parasites in invasive Vespa velutina and native Hymenoptera

Invasive species pose a threat to the ecological balance of the ecosystems they invade by altering local host-pathogen dynamics. To investigate these relationships and their potential consequences, we examined the prevalence and genetic diversity patterns of Trypanosomatidae, Lipotrophidae, and Nosematidae in a collection of sympatric isolates of the invasive hornet Vespa velutina and local Hymenoptera from two recently colonized areas: Europe and South Korea. Data were gathered through PCR amplification and massive parallel sequencing, and analyses were conducted using population genetics tools. Parasite prevalences showed substantial variation depending on (i) the parasite family (Trypanosomatidae and Nosematidae were the most and less prevalent, respectively), (ii) location (e.g. Galicia displayed the highest pooled values), (iii) the season (highest in spring for Trypanosomatidae and Lipotrophidae), and (iv) the host. V. velutina exhibited significantly lower parasite occurrence than native Hymenoptera across all parasite families (consistent with the enemy release hypothesis), although this difference was less pronounced during the periods of heightened predatory activity, suggestive of trophic transmission. Parasite species displayed significant genetic differentiation between European and South Korean isolates, yet no differentiation was observed across hosts, suggesting that all Hymenoptera are exposed to a common local pathogen population. There was no indication that V. velutina acted as a carrier of foreign parasites to the invaded territories.

Big jaw, small genome: first description of the mitochondrial genome of Odontomachus (Formicidae, Ponerinae): evolutionary implications for Ponerinae ants

Mitochondrial DNA is a valuable tool for population genetics and evolutionary studies in a wide range of organisms. With advancements in sequencing techniques, it’s now possible to gain deeper insights into this molecule. By understanding how many genes there are, how they’re organized within the molecule, identifying the presence of spacers, and analyzing the composition of the D-Loop, we can better grasp the rearrangements that play a crucial role in the evolutionary dynamics of mitochondrial DNA. Additionally, phylogenetic analyses benefit significantly from having access to a larger pool of mtDNA genes. This wealth of genetic information allows for the establishment of evolutionary relationships with greater accuracy than ever before, providing a more robust framework than analyses based on a limited number of genes. Studies on mitogenomes belonging to the family Formicidae have proven promising, enabling the identification of gene rearrangements and enhancing our understanding of the internal relationships within the group. Despite this, the number of mitogenomes available for the subfamily Ponerinae is still limited, and here we present for the first time the complete mitogenome of Odontomachus. Our data reveal a gene duplication event in Formicidae, the first involving trnV, and new gene arrangements involving the trnM–trnI–trnQ and trnW–trnC–trnY clusters, suggesting a possible synapomorphy for the genus. Our phylogenetic analysis using the PCGs available for Formicidae supports the monophyly of the subfamily Ponerinae and sheds light on the relationship between Odontomachus and Pachycondyla.

Smart Breeding Platform: A web-based tool for high-throughput population genetics, phenomics, and genomic selection

Smart Breeding Platform: A web-based tool for high-throughput population genetics, phenomics, and genomic selection

Metabolic control of puberty: 60 years in the footsteps of Kennedy and Mitra's seminal work.

An individual's nutritional status has a powerful effect on sexual maturation. Puberty onset is delayed in response to chronic energy insufficiency and is advanced under energy abundance. The consequences of altered pubertal timing for human health are profound. Late puberty increases the chances of cardiometabolic, musculoskeletal and neurocognitive disorders, whereas early puberty is associated with increased risks of adult obesity, type 2 diabetes mellitus, cardiovascular diseases and various cancers, such as breast, endometrial and prostate cancer. Kennedy and Mitra's trailblazing studies, published in 1963 and using experimental models, were the first to demonstrate that nutrition is a key factor in puberty onset. Building on this work, the field has advanced substantially in the past decade, which is largely due to the impressive development of molecular tools for experimentation and population genetics. In this Review, we discuss the latest advances in basic and translational sciences underlying the nutritional and metabolic control of pubertal development, with a focus on perspectives and future directions.

Phylogeographical patterns are governed by geography in endemic polymorphic snail Indrella ampulla (Gastropoda: Ariophantidae)

Abstract Genetic diversity within a species can be shaped by abiotic factors, such as climate and geography. We aimed to ascertain the relative importance of these two abiotic factors to Indrella ampulla, a monotypic snail species from the Western Ghats, India, that has three colour morphs with some overlapping distributions. We also wanted to investigate whether these colour morphs represent divergent lineages or incipient species. We sequenced one nuclear and two mitochondrial genes from 32 individuals of I. ampulla. We used phylogenetic, population genetic, and niche modelling tools to address these questions. The results suggested that the colour morphs were not reciprocally monophyletic and exhibited considerable niche overlap, suggesting that they cannot be considered as incipient species. Furthermore, the results showed that the impact of palaeoclimatic oscillations in shaping the genetic diversity of this species cannot be determined conclusively. The Palghat Gap seems to have shaped the genetic diversity in this group to a certain degree. The colour morph distributed south of the Palghat Gap did not show admixture and exhibited the least amount of niche overlap with the other morphs. The geography of the landscape seems to have played a prominent role in shaping genetic diversity in this species.

The novel developed microsatellite markers revealed potential hybridization among Cymbidium species and the interspecies sub-division of C. goeringii and C. ensifolium

BackgroundOrchids (Cymbidium spp.) exhibit significant variations in floral morphology, pollinator relations, and ecological habitats. Due to their exceptional economic and ornamental value, Cymbidium spp. have been commercially cultivated for centuries. SSR markers are extensively used genetic tools for biology identification and population genetics analysis.ResultIn this study, nine polymorphic EST-SSR loci were isolated from Cymbidium goeringii using RNA-Seq technology. All nine SSR loci showed transferability in seven other congeneric species, including 51 cultivars. The novel SSR markers detected inter-species gene flow among the Cymbidium species and intra-species sub-division of C. goeringii and C. ensifolium, as revealed by neighborhood-joining and Structure clustering analyses.ConclusionIn this study, we developed nine microsatellites using RNA-Seq technology. These SSR markers aided in detecting potential gene flow among Cymbidium species and identified the intra-species sub-division of C. goeringii and C. ensifolium.

Identification of sex-linked SNP markers in wild populations of monomorphic birds.

Single-nucleotide polymorphism (SNP) analysis is a powerful tool for population genetics, pedigree reconstruction and phenotypic trait mapping. However, the untapped potential of SNP markers to discriminate the sex of individuals in species with reduced sexual dimorphism or of individuals during immature stages remains a largely unexplored avenue. Here, we developed a novel protocol for molecular sexing of birds based on the detection of unique Z- and W-linked SNP markers. Our method is based on the identification of two unique loci, one in each sexual chromosome. Individuals are considered males when they show no calls for the W-linked SNP and are heterozygous or homozygous for the Z-linked SNP, while females exhibit both Z- and W-linked SNP calls. We validated the method in the Jackdaw (Corvus monedula). The reduced sexual dimorphism in this species makes it difficult to identify the sex of individuals in the wild. We assessed the reliability of the method using 36 individuals of known sex and found that their sex was correctly assigned in 100% of cases. The sex-linked markers also proved to be widely applicable for discriminating males and females from a sample of 927 genotyped individuals at different maturity stages, with an accuracy of 99.5%. Since SNP markers are increasingly used in quantitative genetic analyses of wild populations, the approach we propose has great potential to be integrated into broader genetic research programmes without the need for additional sexing techniques.

Social network structure and the spread of complex contagions from a population genetics perspective.

Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a nonlinear function of the fraction of the individuals' affected neighbors, such a spreading process becomes a "complex contagion." This nonlinearity does not typically appear with physically spreading infections, but instead can emerge when the concept that is spreading is subject to game theoretical considerations (e.g., for choices of strategy or behavior) or psychological effects such as social reinforcement and other forms of peer influence (e.g., for ideas, preferences, or opinions). Here we study how the stochastic dynamics of such complex contagions are affected by the underlying network structure. Motivated by simulations of complex contagions on real social networks, we present a framework for analyzing the statistics of contagions with arbitrary nonlinear adoption probabilities based on the mathematical tools of population genetics. The central idea is to use an effective lower-dimensional diffusion process to approximate the statistics of the contagion. This leads to a tradeoff between the effects of "selection" (microscopic tendencies for an idea to spread or die out), random drift, and network structure. Our framework illustrates intuitively several key properties of complex contagions: stronger community structure and network sparsity can significantly enhance the spread, while broad degree distributions dampen the effect of selection compared to random drift. Finally, we show that some structural features can exhibit critical values that demarcate regimes where global contagions become possible for networks of arbitrary size. Our results draw parallels between the competition of genes in a population and memes in a world of minds and ideas. Our tools provide insight into the spread of information, behaviors, and ideas via social influence, and highlight the role of macroscopic network structure in determining their fate.

Refining the Global Phylogeny of Mitochondrial N1a, X, and HV2 Haplogroups Based on Rare Mitogenomes from Croatian Isolates.

Mitochondrial DNA (mtDNA) has been used for decades as a predominant tool in population genetics and as a valuable addition to forensic genetic research, owing to its unique maternal inheritance pattern that enables the tracing of individuals along the maternal lineage across numerous generations. The dynamic interplay between evolutionary forces, primarily genetic drift, bottlenecks, and the founder effect, can exert significant influence on genetic profiles. Consequently, the Adriatic islands have accumulated a subset of lineages that exhibits remarkable absence or rarity within other European populations. This distinctive genetic composition underscores the islands' potential as a significant resource in phylogenetic research, with implications reaching beyond regional boundaries to contribute to a global understanding. In the initial attempt to expand the mitochondrial forensic database of the Croatian population with haplotypes from small isolated communities, we sequenced mitogenomes of rare haplogroups from different Croatian island and mainland populations using next-generation sequencing (NGS). In the next step and based on the obtained results, we refined the global phylogeny of haplogroup N1a, HV2, and X by analyzing rare haplotypes, which are absent from the current phylogenetic tree. The trees were based on 16 novel and 52 previously published samples, revealing completely novel branches in the X and HV2 haplogroups and a new European cluster in the ancestral N1a variant, previously believed to be an exclusively African-Asian haplogroup. The research emphasizes the importance of investigating geographically isolated populations and their unique characteristics within a global context.

Human Gm, Km, and Am Allotypes: WHO/IMGT Nomenclature and IMGT Unique Numbering for Immunoinformatics and Therapeutical Antibodies

Human immunoglobulin allotypes are allelic antigenic determinants (or “markers”) determined serologically, classically by hemagglutination inhibition, on the human immunoglobulin (IG) or antibody heavy and light chains. The allotypes have been identified on the gamma1, gamma2, gamma3, and alpha2 heavy chains (designated as G1m, G2m, G3m, and A2m allotypes, respectively) and on the kappa light chain (Km allotypes). Gm and Am allotypes have been one of the most powerful tools in population genetics, as they are inherited in fixed combinations, or Gm–Am haplotypes, owing to the linkage of the human IGHC genes in the IGH locus on chromosome 14. They have been very instrumental in molecular characterization of the human IGHC genes (gene polymorphisms or alleles, and IG heavy-chain structure in domains) and of the IGH locus (IGHC gene order, gene conversion, and copy number variation (CNV)). They represent a major system for understanding immunogenicity of the polymorphic IG chains in relation to amino acid and conformational changes. The WHO/IMGT allotype nomenclature and the IMGT unique numbering for constant (C) domain bridge Gm–Am and Km alleles to IGHC and IGKC gene alleles and structures and, by definition, to IG chain immunogenicity, opening the way for immunoinformatics of personalized therapeutic antibodies and engineered variants.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations.

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Dispersive currents explain patterns of population connectivity in an ecologically and economically important fish.

How to identify the drivers of population connectivity remains a fundamental question in ecology and evolution. Answering this question can be challenging in aquatic environments where dynamic lake and ocean currents coupled with high levels of dispersal and gene flow can decrease the utility of modern population genetic tools. To address this challenge, we used RAD-Seq to genotype 959 yellow perch (Perca flavescens), a species with an ~40-day pelagic larval duration (PLD), collected from 20 sites circumscribing Lake Michigan. We also developed a novel, integrative approach that couples detailed biophysical models with eco-genetic agent-based models to generate "predictive" values of genetic differentiation. By comparing predictive and empirical values of genetic differentiation, we estimated the relative contributions for known drivers of population connectivity (e.g., currents, behavior, PLD). For the main basin populations (i.e., the largest contiguous portion of the lake), we found that high gene flow led to low overall levels of genetic differentiation among populations (F ST = 0.003). By far the best predictors of genetic differentiation were connectivity matrices that were derived from periods of time when there were strong and highly dispersive currents. Thus, these highly dispersive currents are driving the patterns of population connectivity in the main basin. We also found that populations from the northern and southern main basin are slightly divergent from one another, while those from Green Bay and the main basin are highly divergent (F ST = 0.11). By integrating biophysical and eco-genetic models with genome-wide data, we illustrate that the drivers of population connectivity can be identified in high gene flow systems.

Fitting stochastic epidemic models to gene genealogies using linear noise approximation.

Phylodynamics is a set of population genetics tools that aim at reconstructing demographic history of a population based on molecular sequences of individuals sampled from the population of interest. One important task in phylodynamics is to estimate changes in (effective) population size. When applied to infectious disease sequences such estimation of population size trajectories can provide information about changes in the number of infections. To model changes in the number of infected individuals, current phylodynamic methods use non-parametric approaches (e.g., Bayesian curve-fitting based on change-point models or Gaussian process priors), parametric approaches (e.g., based on differential equations), and stochastic modeling in conjunction with likelihood-free Bayesian methods. The first class of methods yields results that are hard to interpret epidemiologically. The second class of methods provides estimates of important epidemiological parameters, such as infection and removal/recovery rates, but ignores variation in the dynamics of infectious disease spread. The third class of methods is the most advantageous statistically, but relies on computationally intensive particle filtering techniques that limits its applications. We propose a Bayesian model that combines phylodynamic inference and stochastic epidemic models, and achieves computational tractability by using a linear noise approximation (LNA) - a technique that allows us to approximate probability densities of stochastic epidemic model trajectories. LNA opens the door for using modern Markov chain Monte Carlo tools to approximate the joint posterior distribution of the disease transmission parameters and of high dimensional vectors describing unobserved changes in the stochastic epidemic model compartment sizes (e.g., numbers of infectious and susceptible individuals). In a simulation study, we show that our method can successfully recover parameters of stochastic epidemic models. We apply our estimation technique to Ebola genealogies estimated using viral genetic data from the 2014 epidemic in Sierra Leone and Liberia.

Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals.

Individuals infected with the SARS-CoV-2 virus present with a wide variety of symptoms ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe response to COVID-19. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the genetic predisposition to severe COVID-19 outcomes. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform a locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify four introgressed alleles that are strong functional candidates for driving the association between this locus and severe COVID-19. Using reporter assays in the presence/absence of SARS-CoV-2, we find evidence that these variants respond to viral infection. These variants likely drive the locus' impact on severity by modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.

Role of paleoclimatic and paleohydrological processes in lineage divergence in freshwater organisms: A snippet from lentic genus Pila

The Indian subcontinent is extremely diverse in terms of its flora and fauna. However, only a handful of studies have aimed to understand the diversity of freshwater invertebrates using multiple lines of evidence in recent times. Here we aimed to estimate the cryptic diversity of two widespread freshwater snail species within the genus Pila (Röding, 1798) and uncover the processes behind lineage diversification in these species. We sequenced mitochondrial and nuclear markers from a comprehensive sampling of specimens from different river basins in India. We implemented an integrative taxonomy approach to delimit the lineages in these groups, employing phylogenetic, geometric morphometric and niche modelling-based methods. Then, we investigated the drivers of lineage divergence in these species using population genetic tools in conjunction with divergence time estimation. We found that both species consist of several genetically and ecologically distinct lineages. The genetic data showed that several of these lineages are restricted to a single or a few river basins. The divergence time estimation analyses indicated that the time frame of divergence within the species coincided with paleohydrological and paleoclimatic events in the Miocene. The diversification was primarily driven by allopatric isolation into different river basins. To conclude, the study sheds light on the complex interaction between the habitat preference of the species and the environment in shaping the diversification patterns in this group.

Unveiling Utricularia amethystina’s true colours: a taxonomic revision of one of the largest species complexes (U. sect. Foliosa, Lentibulariaceae)

The genus Utricularia (Lentibulariaceae) is the most diverse and cosmopolitan among carnivorous plants. Utricularia sect. Foliosa sensu Taylor (1989) is composed of three South American species, U. amethystina, U. tricolor and U. tridentata, the first species being recognized as highly diverse. In his taxonomic revision of the genus Utricularia, Taylor (1989) circumscribed the polymorphic U. amethystina comprising 27 synonyms involving a wide variation in corolla size and colour, morphology of corolla parts, indumentum, and overall plant size. The original publications of the synonyms provide limited information disencouraging a revision study and therefore inflating U. amethystina as new variations were discovered. In order to shed light onto the problem, a taxonomic revision, a morphometric and a molecular study showed evidence of a larger complex than previously thought, and U. amethystina s.str. sister to U. tricolor. A previously published molecular phylogeny provided strong support for all sampled U. amethystina synonyms and potential new taxa found to be nested outside the U. amethystina s.str. and U. tricolor clade. Here, we incorporate these new relationships and describe and comment on the species that comprise U. sect. Foliosa, including the restablishment of six synonyms, the description of three new species and lectotypification of five names. The current study disentangles U. amethystina complex so that further studies can approach it in a more realistic way, especially studies using population genetics tools. Our study shows that more needs to be done and here U. hirtella is presented as a new complex.

Beta-PSMC: uncovering more detailed population history using beta distribution

BackgroundInferring the demographic history of a population is essential in population genetic studies. Though the inference methods based on the sequentially Markov coalescent can present the population history in detail, these methods assume that the population size remains unchanged in each time interval during discretizing the hidden state in the hidden Markov model. Therefore, these methods fail to uncover the detailed population history in each time interval.ResultsWe present a new method called Beta-PSMC, which introduces the probability density function of a beta distribution with a broad variety of shapes into the Pairwise Sequentially Markovian Coalescent (PSMC) model to refine the population history in each discretized time interval in place of the assumption that the population size is unchanged. Using simulation, we demonstrate that Beta-PSMC can uncover more detailed population history, and improve the accuracy and resolution of the recent population history inference. We also apply Beta-PSMC to infer the population history of Adélie penguin and find that the fluctuation in population size is contrary to the temperature change 15–27 thousand years ago.ConclusionsBeta-PSMC extends PSMC by allowing more detailed fluctuation of population size in each discretized time interval with the probability density function of beta distribution and will serve as a useful tool for population genetics.

Genetic divergence at species boundaries of the dolphinfish (Coryphaena hippurus) in the Tropical Eastern Pacific.

Marine species constitute commercially important resources, and knowledge about mechanisms that shape phylogeographic patterns and genetic structure provides valuable information for conservation. The dolphinfish, Coryphaena hippurus, is one of the most important species caught in the Tropical Eastern Pacific (TEP). However, the lack of consensus about the existence of genetically differentiated populations in the area has hindered the adoption of management strategies to ensure its viability. We assessed genetic variation and phylogeographic structure using two mitochondrial genes and 14 nuclear DNA microsatellite loci. Population genetic tools were used to characterize the spatial distribution of genetic variation of C. hippurus in the TEP, evaluate the extent of connectivity between dolphinfish populations, infer potential barriers to gene flow, and test for signals of contemporary and historical demographic expansions. Mitochondrial DNA sequences showed genetic homogeneity across locations in the TEP, as well as a strong signal of population expansion dated to the late Pleistocene. In contrast, nuclear microsatellite markers resolved four genetically distinct groups with a remarked genetic differentiation between the most distant locations, at the northern and southern boundaries of the species' range. High mean genetic diversity was found at all localities (Hs = 0.66-0.81). Notwithstanding, positive F IS and low effective population size (Ne = 77.9-496.4) were also recorded. The distribution of genetic variation could be related to expansion-contraction cycles following seasonal temperature changes at transitional areas, promoting population subdivisions. However, we cannot rule out the effect of oceanographic dynamics to the observed patterns. Although this marine species remains highly abundant despite commercial exploitation, the low Ne values are of conservation concern and must be considered in fishery management plans.

Animal-SNPAtlas: a comprehensive SNP database for multiple animals.

Single-nucleotide polymorphisms (SNPs) as the most important type of genetic variation are widely used in describing population characteristics and play vital roles in animal genetics and breeding. Large amounts of population genetic variation resources and tools have been developed in human, which provided solid support for human genetic studies. However, compared with human, the development of animal genetic variation databases was relatively slow, which limits the genetic researches in these animals. To fill this gap, we systematically identified ∼ 499 million high-quality SNPs from 4784 samples of 20 types of animals. On that basis, we annotated the functions of SNPs, constructed high-density reference panels and calculated genome-wide linkage disequilibrium (LD) matrixes. We further developed Animal-SNPAtlas, a user-friendly database (http://gong_lab.hzau.edu.cn/Animal_SNPAtlas/) which includes high-quality SNP datasets and several support tools for multiple animals. In Animal-SNPAtlas, users can search the functional annotation of SNPs, perform online genotype imputation, explore and visualize LD information, browse variant information using the genome browser and download SNP datasets for each species. With the massive SNP datasets and useful tools, Animal-SNPAtlas will be an important fundamental resource for the animal genomics, genetics and breeding community.