Presence Of Population Structure Research Articles

Estimation of Direct and Indirect Polygenic Effects and Gene-Environment Interactions using Polygenic Scores in Case-Parent Trio Studies.

Family-based studies provide a unique opportunity to characterize genetic risks of diseases in the presence of population structure, assortative mating, and indirect genetic effects. We propose a novel framework, PGS-TRI, for the analysis of polygenic scores (PGS) in case-parent trio studies for estimation of the risk of an index condition associated with direct effects of inherited PGS, indirect effects of parental PGS, and gene-environment interactions. Extensive simulation studies demonstrate the robustness of PGS-TRI in the presence of complex population structure and assortative mating compared to alternative methods. We apply PGS-TRI to multi-ancestry trio studies of autism spectrum disorders (N trio = 1,517) and orofacial clefts (N trio = 1,904) to establish the first transmission-based estimates of risk associated with pre-defined PGS for these conditions and other related traits. For both conditions, we further explored offspring risk associated with polygenic gene-environment interactions, and direct and indirect effects of genetically predicted levels of gene expression and metabolite traits.

Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies

Large-scale, multi-ethnic whole-genome sequencing (WGS) studies, such as the National Human Genome Research Institute Genome Sequencing Program's Centers for Common Disease Genomics (CCDG), play an important role in increasing diversity for genetic research. Before performing association analyses, assessing Hardy-Weinberg equilibrium (HWE) is a crucial step in quality control procedures to remove low quality variants and ensure valid downstream analyses. Diverse WGS studies contain ancestrally heterogeneous samples; however, commonly used HWE methods assume that the samples are homogeneous. Therefore, directly applying these to the whole dataset can yield statistically invalid results. To account for this heterogeneity, HWE can be tested on subsets of samples that have genetically homogeneous ancestries and the results aggregated at each variant. To facilitate valid HWE subset testing, we developed a semi-supervised learning approach that predicts homogeneous ancestries based on the genotype. This method provides a convenient tool for estimating HWE in the presence of population structure and missing self-reported race and ethnicities in diverse WGS studies. In addition, assessing HWE within the homogeneous ancestries provides reliable HWE estimates that will directly benefit downstream analyses, including association analyses in WGS studies. We applied our proposed method on the CCDG dataset, predicting homogeneous genetic ancestry groups for 60,545 multi-ethnic WGS samples to assess HWE within each group.

Interpreting SNP heritability in admixed populations.

SNP heritability is defined as the proportion of phenotypic variance explained by genotyped SNPs and is believed to be a lower bound of heritability ( ), being equal to it if all causal variants are known. Despite the simple intuition behind , its interpretation and equivalence to is unclear, particularly in the presence of population structure and assortative mating. It is well known that population structure can lead to inflation in estimates because of confounding due to linkage disequilibrium (LD) or shared environment. Here we use analytical theory and simulations to demonstrate that estimates can be biased in admixed populations, even in the absence of confounding and even if all causal variants are known. This is because admixture generates LD, which contributes to the genetic variance, and therefore to heritability. Genome-wide restricted maximum likelihood (GREML) does not capture this contribution leading to under- or over-estimates of relative to , depending on the genetic architecture. In contrast, Haseman-Elston (HE) regression exaggerates the LD contribution leading to biases in the opposite direction. For the same reason, GREML and HE estimates of local ancestry heritability are also biased. We describe this bias in and as a function of admixture history and the genetic architecture of the trait and show that it can be recovered under some conditions. We clarify the interpretation of in admixed populations and discuss its implication for genome-wide association studies and polygenic prediction.

Genetic diversity and population structure of a rare flowering tree endemic to Appalachia, Stewartia ovata.

Stewartia ovata (cav.) Weatherby, commonly known as mountain stewartia, is an understory tree native to the southeastern United States (U.S.). This relatively rare species occurs in isolated populations in Virginia, Kentucky, Tennessee, North Carolina, South Carolina, Georgia, Alabama, and Mississippi. As a species, S. ovata has largely been overlooked, and limited information is available regarding its ecology, which presents obstacles to conservation efforts. Stewartia ovata has vibrant, large white flowers that bloom in summer with a variety of filament colors, suggesting potential horticultural traits prized by ornamental industry. However, S. ovata is relatively slow growing and, due to long seed dormancy, propagation is challenging with limited success rates. This has created a need to assess the present genetic diversity in S. ovata populations to inform potential conservation and restoration of the species. Here, we employ a genotyping-by-sequencing (GBS) approach to characterize the spatial distribution and genetic diversity of S. ovata in the southern Appalachia region of the eastern United States. A total of 4475 single nucleotide polymorphisms (SNPs) were identified across 147 individuals from 11 collection sites. Our results indicate low genetic diversity (He = 0.216), the presence of population structure (K = 2), limited differentiation (F ST = 0.039), and high gene flow (Nm = 6.16) between our subpopulations. Principal component analysis corroborated the findings of STRUCTURE, confirming the presence of two distinct S. ovata subpopulations. One subpopulation mainly contains genotypes from the Cumberland Plateau, Tennessee, while the other consists of genotypes present in the Great Smoky Mountain ranges in Tennessee, North Carolina, and portions of Nantahala, Chattahoochee-Oconee national forests in Georgia, highlighting that elevation likely plays a major role in its distribution. Our results further suggested low inbreeding coefficient (F IS = 0.070), which is expected with an outcrossing tree species. This research further provides necessary insight into extant subpopulations and has generated valuable resources needed for conservation efforts of S. ovata.

SSR Marker–Based Genetic Diversity and Relationship Analyses of Stephania tetrandra S. Moore

AbstractStephania tetrandra S. Moore (family: Menispermaceae), a dioecious herbaceous vine and the only species in the subgenus Botryodiscia of the genus Stephania of the family Menispermaceae, is mainly distributed in hilly areas south of the Huaihe River in China and found in many provinces of China, showing a high genetic diversity. This paper aimed to study genetic diversity of and genetic relationship among individuals of S. tetrandra within China to provide a basis for evaluation, exploitation, and utilization of S. tetrandra by using simple sequence repeat (SSR) molecular markers. Our results show that effective products were amplified from the 26 screened SSR gene loci, a total of 183 alleles amplified (2–16 alleles amplified by each pair of primers). Among the 26 loci, 16 had a PIC value higher than 0.5, indicating a high level of polymorphism. For most of the loci, the number of effective alleles was lower than that of the observed alleles, and the observed heterozygosity was lower than the expected heterozygosity. The genetic differentiation coefficient (0.021–0.547) was lower than 0.05 (low level of genetic differentiation) for 7 loci and higher than 0.25 (very high level of genetic differentiation) for 2 loci, and had a value representing a medium level of genetic differentiation for the remaining 17 loci. The intra-population inbreeding coefficient had a positive value for 21 loci, suggesting the presence of inbreeding and homozygous excess. The gene flow value was bigger than 1, indicating that genetic drift and natural selection played an unimportant role in population genetic differentiation of S. tetrandra. Based on discriminant analysis of principal components and Bayesian Information Criterion, K-means clustering was performed on 620 samples. These samples were divided into 9 genetic clusters, whose similarity coefficients and genetic distances were 0.755–0.918 and 0.067–0.280, respectively, indicating that these clusters were highly similar and short-distanced. The Bayesian clustering analysis was implemented in the STRUCTURE software to analyze the genetic structure of S. tetrandra and it was found that the 620 samples could be clustered into 5 ancestor groups; the 9 clusters and 40 natural populations inherited genes from the 5 groups to varying degrees, but the proportion of genes inherited from the 5 groups by each cluster and natural population differed. S. tetrandra was characterized by the presence of population structure and pronounced genetic subdivision, which, together with the presence of gene flow, may indicate a relatively stable recent state of these populations.

Genomic variation in baboons from central Mozambique unveils complex evolutionary relationships with other Papio species

BackgroundGorongosa National Park in Mozambique hosts a large population of baboons, numbering over 200 troops. Gorongosa baboons have been tentatively identified as part of Papio ursinus on the basis of previous limited morphological analysis and a handful of mitochondrial DNA sequences. However, a recent morphological and morphometric analysis of Gorongosa baboons pinpointed the occurrence of several traits intermediate between P. ursinus and P. cynocephalus, leaving open the possibility of past and/or ongoing gene flow in the baboon population of Gorongosa National Park. In order to investigate the evolutionary history of baboons in Gorongosa, we generated high and low coverage whole genome sequence data of Gorongosa baboons and compared it to available Papio genomes.ResultsWe confirmed that P. ursinus is the species closest to Gorongosa baboons. However, the Gorongosa baboon genomes share more derived alleles with P. cynocephalus than P. ursinus does, but no recent gene flow between P. ursinus and P. cynocephalus was detected when available Papio genomes were analyzed. Our results, based on the analysis of autosomal, mitochondrial and Y chromosome data, suggest complex, possibly male-biased, gene flow between Gorongosa baboons and P. cynocephalus, hinting to direct or indirect contributions from baboons belonging to the “northern” Papio clade, and signal the presence of population structure within P. ursinus.ConclusionsThe analysis of genome data generated from baboon samples collected in central Mozambique highlighted a complex set of evolutionary relationships with other baboons. Our results provided new insights in the population dynamics that have shaped baboon diversity.

Coalescence times, life history traits and conservation concerns: An example from four coastal shark species from the Indo-Pacific.

Dispersal abilities play a crucial role in shaping the extent of population genetic structure, with more mobile species being panmictic over large geographical ranges and less mobile ones organized in metapopulations exchanging migrants to different degrees. In turn, population structure directly influences the coalescence pattern of the sampled lineages, but the consequences on the estimated variation of the effective population size (Ne ) over time obtained by means of unstructured demographic models remain poorly understood. However, this knowledge is crucial for biologically interpreting the observed Ne trajectory and further devising conservation strategies in endangered species. Here we investigated the demographic history of four shark species (Carharhinus melanopterus, Carharhinus limbatus, Carharhinus amblyrhynchos, Galeocerdo cuvier) with different degrees of endangered status and life history traits related to dispersal distributed in the Indo-Pacific and sampled off New Caledonia. We compared several evolutionary scenarios representing both structured (metapopulation) and unstructured models and then inferred the Ne variation through time. By performing extensive coalescent simulations, we provided a general framework relating the underlying population structure and the observed Ne dynamics. On this basis, we concluded that the recent decline observed in three out of the four considered species when assuming unstructured demographic models can be explained by the presence of population structure. Furthermore, we also demonstrated the limits of the inferences based on the sole site frequency spectrum and warn that statistics based on linkage disequilibrium will be needed to exclude recent demographic events affecting meta-populations.

"Jumping Jack": Genomic Microsatellites Underscore the Distinctiveness of Closely Related Pseudoperonospora cubensis and Pseudoperonospora humuli and Provide New Insights Into Their Evolutionary Past.

Downy mildews caused by obligate biotrophic oomycetes result in severe crop losses worldwide. Among these pathogens, Pseudoperonospora cubensis and P. humuli, two closely related oomycetes, adversely affect cucurbits and hop, respectively. Discordant hypotheses concerning their taxonomic relationships have been proposed based on host–pathogen interactions and specificity evidence and gene sequences of a few individuals, but population genetics evidence supporting these scenarios is missing. Furthermore, nuclear and mitochondrial regions of both pathogens have been analyzed using microsatellites and phylogenetically informative molecular markers, but extensive comparative population genetics research has not been done. Here, we genotyped 138 current and historical herbarium specimens of those two taxa using microsatellites (SSRs). Our goals were to assess genetic diversity and spatial distribution, to infer the evolutionary history of P. cubensis and P. humuli, and to visualize genome-scale organizational relationship between both pathogens. High genetic diversity, modest gene flow, and presence of population structure, particularly in P. cubensis, were observed. When tested for cross-amplification, 20 out of 27 P. cubensis-derived gSSRs cross-amplified DNA of P. humuli individuals, but few amplified DNA of downy mildew pathogens from related genera. Collectively, our analyses provided a definite argument for the hypothesis that both pathogens are distinct species, and suggested further speciation in the P. cubensis complex.

Microsatellite Loci Reveal Genetic Diversity of Asian Callery Pear (Pyrus calleryana) in the Species Native Range and in the North American Cultivars.

Pyrus calleryana Decne. (Callery pear) includes cultivars that in the United States are popular ornamentals in commercial and residential landscapes. Last few decades, this species has increasingly naturalized across portions of the eastern and southern US. However, the mechanisms behind this plant’s spread are not well understood. The genetic relationship of present-day P. calleryana trees with their Asian P. calleryana forebears (native trees from China, Japan, and Korea) and the original specimens of US cultivars are unknown. We developed and used 18 microsatellite markers to analyze 147 Pyrus source samples and to articulate the status of genetic diversity within Asian P. calleryana and US cultivars. We hypothesized that Asian P. calleryana specimens and US cultivars would be genetically diverse and would show genetic relatedness. Our data revealed high genetic diversity, high gene flow, and presence of population structure in P. calleryana, potentially relating to the highly invasive capability of this species. Strong evidence for genetic relatedness between Asian P. calleryana specimens and US cultivars was also demonstrated. Our data suggest the source for P. calleryana that have become naturalized in US was China. These results will help understand the genetic complexity of invasive P. calleryana when developing management for escaped populations: In follow-up studies, we use the gSSRs developed here to analyze P. calleryana escape populations from across US.

Detecting inversions with PCA in the presence of population structure.

Chromosomal inversions can lead to reproductive isolation and adaptation in insects such as Drosophila melanogaster and the non-model malaria vector Anopheles gambiae. Inversions can be detected and characterized using principal component analysis (PCA) of single nucleotide polymorphisms (SNPs). To aid in developing such methods, we formed a new benchmark derived from three publicly-available insect data. We then used this benchmark to perform an extended validation of our software for inversion analysis (Asaph). Through that process, we identified and characterized several problematic test cases liable to misinterpretation that can help guide PCA-based inversion detection. Lastly, we re-analyzed the 2R chromosome arm of 150 An. gambiae and coluzzii samples and observed two inversions (2Rc and 2Rd) that were previously known but not annotated in these particular individuals. The resulting benchmark data set and methods will be useful for future inversion detection based solely on SNP data.

Habitat fragmentation influences genetic diversity and differentiation: Fine-scale population structure of Cercis canadensis (eastern redbud).

Forest fragmentation may negatively affect plants through reduced genetic diversity and increased population structure due to habitat isolation, decreased population size, and disturbance of pollen‐seed dispersal mechanisms. However, in the case of tree species, effective pollen‐seed dispersal, mating system, and ecological dynamics may help the species overcome the negative effect of forest fragmentation. A fine‐scale population genetics study can shed light on the postfragmentation genetic diversity and structure of a species. Here, we present the genetic diversity and population structure of Cercis canadensis L. (eastern redbud) wild populations on a fine scale within fragmented areas centered around the borders of Georgia–Tennessee, USA. We hypothesized high genetic diversity among the collections of C. canadensis distributed across smaller geographical ranges. Fifteen microsatellite loci were used to genotype 172 individuals from 18 unmanaged and naturally occurring collection sites. Our results indicated presence of population structure, overall high genetic diversity (H E = 0.63, H O = 0.34), and moderate genetic differentiation (F ST = 0.14) among the collection sites. Two major genetic clusters within the smaller geographical distribution were revealed by STRUCTURE. Our data suggest that native C. canadensis populations in the fragmented area around the Georgia–Tennessee border were able to maintain high levels of genetic diversity, despite the presence of considerable spatial genetic structure. As habitat isolation may negatively affect gene flow of outcrossing species across time, consequences of habitat fragmentation should be regularly monitored for this and other forest species. This study also has important implications for habitat management efforts and future breeding programs.

In the presence of population structure: From genomics to candidate genes underlying local adaptation.

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis‐regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low‐frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis‐regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic‐acid pathway to local adaptation.

Extending Tests of Hardy-Weinberg Equilibrium to Structured Populations.

Testing for Hardy-Weinberg equilibrium (HWE) is an important component in almost all analyses of population genetic data. Genetic markers that violate HWE are often treated as special cases; for example, they may be flagged as possible genotyping errors, or they may be investigated more closely for evolutionary signatures of interest. The presence of population structure is one reason why genetic markers may fail a test of HWE. This is problematic because almost all natural populations studied in the modern setting show some degree of structure. Therefore, it is important to be able to detect deviations from HWE for reasons other than structure. To this end, we extend statistical tests of HWE to allow for population structure, which we call a test of "structural HWE." Additionally, our new test allows one to automatically choose tuning parameters and identify accurate models of structure. We demonstrate our approach on several important studies, provide theoretical justification for the test, and present empirical evidence for its utility. We anticipate the proposed test will be useful in a broad range of analyses of genome-wide population genetic data.

Genetic population structure of a highly migratory Hilsa Shad, Tenualosa ilisha, in three river systems, inferred from four mitochondrial genes analysis

This is the first study to clearly demonstrate genetic divergence in the highly migratory Hilsa shad, Tenualosa ilisha and the presence of population structure, as well as speculated migratory routes among the natural hilsa populations of Hoogli, Brahmaputra and Padma (in India) river systems, compared with that of marine samples from Kakdwip and Digha, collected during 2013–16. Sequence data of four mitochondrial regions, Cytochrome b (CytB), ATPase6&8 (ATPase), 12 s and 16 s rRNA (rRNA) were used for the study. It was found that ATPase6&8 and rRNA were under selection pressure and out of 45 population pairs analyzed, highest significant pairs (16) were observed with ATPase, followed equally (12) by rRNA and CytB datasets. Comparison of these samples with those collected in 1999–2000 revealed temporal stability of sampled populations, with low genetic differentiation between temporal samples from same locality, except for Brahmaputra samples. Among the samples collected (2013–16), between samples from Brahmaputra and Padma, several shared haplotypes indicated genetic homogeneity and significant level of migration was also observed. The FST values showed that samples collected from both moonsoon and winter runs, at brackish water location in Hoogly River, Godakhali, were found to be two separate distinct genetic stocks. Migratory patterns from the sea to these freshwater river systems have also been speculated from mitochondrial DNA data, which needs confirmation from tagging studies. These results have strong implications for the conservation and sustainable management of hilsa fishery, as a consequence to its over-exploitation, which directly influences the overall species diversity.

Determinants of QTL Mapping Power in the Realized Collaborative Cross.

The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses from extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments.

Genome-wide Significance Thresholds for Admixture Mapping Studies

Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1× 10-5 and 4.5× 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.

Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies

With advances in whole-genome sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and sequence kernel association test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-set mixed model association tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program. SMMATs share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be fit only once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMATs correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

English

Frafra potato (Solenostemon rotundifolius) is an important food crop indigenous to Western Africa and a member of the Labiaceae (mint) family. It is nutrient-rich and drought tolerant; however, despite its potential as a food security crop, it has not received the research support needed to promote its widespread adoption and safeguard its diversity. As a result, Frafra potato is becoming extinct and restricted to indigenous communities where it holds traditional importance. It is imperative that conservation methods are explored, but before then, the genetic diversity of the species should be assessed. The objectives of this study were to develop simple sequence repeats (SSRs) for Frafra potato from de novo sequencing of the genome, and to provide a preliminary assessment of genetic diversity of Frafra potato in Ghana. To this end, 57 accessions of Frafra potato obtained from three geographic regions of Ghana were characterized using 15 discovered microsatellites. Forty-six multilocus genotypes (MLGs) were identified among the 57 accessions. The genetic diversity among the MLGs was moderate-to-high. Preliminary evaluation of accessions from the three collection zones indicated the presence of population structure among Frafra potato individuals collected in Ghana, Africa. Key words: Food security, Frafra potato, genetic diversity, microsatellites, simple sequence repeats, Solenostemon rotundifolius.

A rapid epistatic mixed-model association analysis by linear retransformations of genomic estimated values.

MotivationEpistasis provides a feasible way for probing potential genetic mechanism of complex traits. However, time-consuming computation challenges successful detection of interaction in practice, especially when linear mixed model (LMM) is used to control type I error in the presence of population structure and cryptic relatedness.ResultsA rapid epistatic mixed-model association analysis (REMMA) method was developed to overcome computational limitation. This method first estimates individuals’ epistatic effects by an extended genomic best linear unbiased prediction (EG-BLUP) model with additive and epistatic kinship matrix, then pairwise interaction effects are obtained by linear retransformations of individuals’ epistatic effects. Simulation studies showed that REMMA could control type I error and increase statistical power in detecting epistatic QTNs in comparison with existing LMM-based FaST-LMM. We applied REMMA to two real datasets, a mouse dataset and the Wellcome Trust Case Control Consortium (WTCCC) data. Application to the mouse data further confirmed the performance of REMMA in controlling type I error. For the WTCCC data, we found most epistatic QTNs for type 1 diabetes (T1D) located in a major histocompatibility complex (MHC) region, from which a large interacting network with 12 hub genes (interacting with ten or more genes) was established.Availability and implementationOur REMMA method can be freely accessed at https://github.com/chaoning/REMMA.Supplementary information Supplementary data are available at Bioinformatics online.

Molecular variance and population structure of lentil (Lens culinarisMedik.) landraces from Mediterranean countries as revealed by simple sequence repeat DNA markers: implications for conservation and use

AbstractThe Mediterranean region has a rich history of domestication and cultivation of lentil (Lens culinarisMedik.). Landraces have been grown and repeatedly selected by local farmers under different agro-environments. Characterization of molecular variation and genetic differentiation helps to ensure enhanced valorization, conservation and use of these genetic resources. Nineteen Simple Sequence Repeat DNA markers were used for molecular variance analysis (AMOVA) and population structure assessment underlying 74 lentil landraces from four Mediterranean countries: Morocco, Italy, Greece and Turkey. Based on AMOVA, presence of population structure and genetic differentiation at different levels were evidenced. Genetic diversity among Turkish landraces was higher than that of other countries. These landraces were more homogeneous as shown by low genetic differentiation among individuals within each landrace. Whereas Moroccan landraces followed by Italian and Greek provenances showed higher diversity and differentiation among individuals within landraces. The wide genetic variability of these landraces could help to better adaptation to biotic and abiotic stresses. Moreover, they could provide useful alleles related to adaptive traits for breeding purposes. Based on structure analysis, we obtained indications of possible presence of two major gene pools: a northern gene pool composed of Turkish, Italian and Greek landraces, and a southern gene pool composed of Moroccan landraces. Our results could be of interest when designing future diversity studies, collection missions, conservation and core collection construction strategies on Mediterranean lentil landraces.