Mapping epistatic quantitative trait loci

Assessing the opportunity for selection to impact morphological traits in crosses between two Solanum species

Within biology, there have been long-standing goals to understand how traits impact fitness, determine the degree of adaptation, and predict responses to selection. One key step in answering these questions is to study the mode of gene action or genetic architecture of traits. The genetic architecture underlying a trait will ultimately determine whether selection can lead to a change in the phenotype. Theoretical and empirical research have shown that additive architectures are most responsive to selection. The genus Solanum offers a unique system to quantify the genetic architecture of traits. Crosses between Solanum pennellii and S. lycopersicum, which have evolved unique adaptive traits for very different environments, offer an opportunity to investigate the genetic architecture of a variety of morphological traits that often are not variable within species. We generated cohorts between strains of these two Solanum species and collected phenotypic data for eight morphological traits. The genetic architectures underlying these traits were estimated using an information-theoretic approach to line cross analysis. By estimating the genetic architectures of these traits, we were able to show a key role for maternal and epistatic effects and infer the accessibility of these traits to selection.

Searching for gene-gene interactions through variance quantitative trait loci of 29 continuous Taiwan Biobank phenotypes

Introduction: After the era of genome-wide association studies (GWAS), thousands of genetic variants have been identified to exhibit main effects on human phenotypes. The next critical issue would be to explore the interplay between genes, the so-called "gene-gene interactions" (GxG) or epistasis. An exhaustive search for all single-nucleotide polymorphism (SNP) pairs is not recommended because this will induce a harsh penalty of multiple testing. Limiting the search of epistasis on SNPs reported by previous GWAS may miss essential interactions between SNPs without significant marginal effects. Moreover, most methods are computationally intensive and can be challenging to implement genome-wide. Methods: I here searched for GxG through variance quantitative trait loci (vQTLs) of 29 continuous Taiwan Biobank (TWB) phenotypes. A discovery cohort of 86,536 and a replication cohort of 25,460 TWB individuals were analyzed, respectively. Results: A total of 18 nearly independent vQTLs with linkage disequilibrium measure r 2 < 0.01 were identified and replicated from nine phenotypes. 15 significant GxG were found with p-values <1.1E-5 (in the discovery cohort) and false discovery rates <2% (in the replication cohort). Among these 15 GxG, 11 were detected for blood traits including red blood cells, hemoglobin, and hematocrit; 2 for total bilirubin; 1 for fasting glucose; and 1 for total cholesterol (TCHO). All GxG were observed for gene pairs on the same chromosome, except for the APOA5 (chromosome 11)-TOMM40 (chromosome 19) interaction for TCHO. Discussion: This study provided a computationally feasible way to search for GxG genome-wide and applied this approach to 29 phenotypes.

Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis

PURPOSE

Epistasis, the interaction between two or more genes, is integral to the study of genetics and is present throughout nature. Yet, it is seldom fully explored as most approaches primarily focus on single-locus effects, partly because analyzing all pairwise and higher-order interactions requires significant computational resources. Furthermore, existing methods for epistasis detection only consider a Cartesian (multiplicative) model for interaction terms. This is likely limiting as epistatic interactions can evolve to produce varied relationships between genetic loci, some complex and not linearly separable.

METHODS

We present new algorithms for the interaction coefficients for standard regression models for epistasis that permit many varied models for the interaction terms for loci and efficient memory usage. The algorithms are given for two-way and three-way epistasis and may be generalized to higher order epistasis. Statistical tests for the interaction coefficients are also provided. We also present an efficient matrix based algorithm for permutation testing for two-way epistasis. We offer a proof and experimental evidence that methods that look for epistasis only at loci that have main effects may not be justified. Given the computational efficiency of the algorithm, we applied the method to a rat data set and mouse data set, with at least 10,000 loci and 1,000 samples each, using the standard Cartesian model and the XOR model to explore body mass index.

RESULTS

This study reveals that although many of the loci found to exhibit significant statistical epistasis overlap between models in rats, the pairs are mostly distinct. Further, the XOR model found greater evidence for statistical epistasis in many more pairs of loci in both data sets with almost all significant epistasis in mice identified using XOR. In the rat data set, loci involved in epistasis under the XOR model are enriched for biologically relevant pathways.

CONCLUSION

Our results in both species show that many biologically relevant epistatic relationships would have been undetected if only one interaction model was applied, providing evidence that varied interaction models should be implemented to explore epistatic interactions that occur in living systems.

Susceptibility of Toxoplasma gondii to autophagy in human cells relies on multiple interacting parasite loci

IMPORTANCE

Autophagy is a process used by cells to recycle organelles and macromolecules and to eliminate intracellular pathogens. Previous studies have shown that some stains of Toxoplasma gondii are resistant to autophagy-dependent growth restriction, while others are highly susceptible. Although it is known that autophagy-mediated control requires activation by interferon gamma, the basis for why parasite strains differ in their susceptibility is unknown. Our findings indicate that susceptibility involves at least five unlinked parasite genes on different chromosomes, including several secretory proteins targeted to the parasite-containing vacuole and exposed to the host cell cytosol. Our findings reveal that susceptibility to autophagy-mediated growth restriction relies on differential recognition of parasite proteins exposed at the host-pathogen interface, thus identifying a new mechanism for cell-autonomous control of intracellular pathogens.

Integration of eQTL and GWAS analysis uncovers a genetic regulation of natural ionomic variation in Arabidopsis

KEY MESSAGE

This study provided important insights into the genetic architecture of variations in A. thaliana leaf ionome in a cell-type-specific manner. The functional interpretation of traits associated variants by expression quantitative trait loci (eQTL) analysis is usually performed in bulk tissue samples. While the regulation of gene expression is context-dependent, such as cell-type-specific manner. In this study, we estimated cell-type abundances from 728 bulk tissue samples using single-cell RNA-sequencing dataset, and performed cis-eQTL mapping to identify cell-type-interaction eQTL (cis-eQTLs(ci)) in A. thaliana. Also, we performed Genome-wide association studies (GWAS) analyses for 999 accessions to identify the genetic basis of variations in A. thaliana leaf ionome. As a result, a total of 5,664 unique eQTL genes and 15,038 unique cis-eQTLs(ci) were significant. The majority (62.83%) of cis-eQTLs(ci) were cell-type-specific eQTLs. Using colocalization, we uncovered one interested gene AT2G25590 in Phloem cell, encoding a kind of plant Tudor-like protein with possible chromatin-associated functions, which colocalized with the most significant cis-eQTL(ci) of a Mo-related locus (Chr2:10,908,806:A:C; P = 3.27 × 10-27). Furthermore, we prioritized eight target genes associated with AT2G25590, which were previously reported in regulating the concentration of Mo element in A. thaliana. This study revealed the genetic regulation of ionomic variations and provided a foundation for further studies on molecular mechanisms of genetic variants controlling the A. thaliana ionome.

Efficiency of mapping epistatic quantitative trait loci

Most theoretical studies on epistatic QTL mapping have shown that this procedure is powerful, efficient to control the false positive rate (FPR), and precise to localize QTLs. The objective of this simulation-based study was to show that mapping epistatic QTLs is not an almost-perfect process. We simulated 50 samples of 400 F2 plants/recombinant inbred lines, genotyped for 975 SNPs distributed in 10 chromosomes of 100 cM. The plants were phenotyped for grain yield, assuming 10 epistatic QTLs and 90 minor genes. Adopting basic procedures of r/qtl package, we maximized the power of detection for QTLs (56-74%, on average) but associated with a very high FPR (65%) and a low detection power for the epistatic pairs (7%). Increasing the average detection power for epistatic pairs (14%) highly increased the related FPR. Adopting a procedure to find the best balance between power and FPR, there was a significant decrease in the power of QTL detection (17-31%, on average), associated with a low average detection power for epistatic pairs (8%) and an average FPR of 31% for QTLs and 16% for epistatic pairs. The main reasons for these negative results are a simplified specification of the coefficients of epistatic effects, as theoretically proved, and the effects of minor genes since 2/3 of the FPR for QTLs were due to them. We hope that this study, including the partial derivation of the coefficients of epistatic effects, motivates investigations on how to increase the power of detection for epistatic pairs, effectively controlling the FPR.

Bayesian Modeling for Epistasis Analysis Using Data-Driven Reversible Jump

We propose a procedure for modeling a phenotype using QTLs which estimate the additive and dominance effects of genotypes and epistasis. The estimation of the model is implemented through a Bayesian approach which uses the data-driven reversible jump (DDRJ) for multiple QTL mapping and model selection. We compare the DDRJ's performance with the usual reversible jump (RJ), QTLBim, multiple interval mapping (MIM) and LASSO using real and simulated data sets. The DDRJ outperforms the available methods to estimate the number of QTLs in epistatic models and it identifies their locations in the genome, without increasing the number of false-positive QTLs in the considered data. Since QTL mapping is a regression model involving complex non-observable variables and their interactions, the model selection procedure proposed here is also useful in other areas of research. The application for identifying main and epistatic relevant QTLs to systolic blood pressure after salt intervention is our main motivation.

Genetic, morphometric, and molecular analyses of interspecies differences in head shape and hybrid developmental defects in the wasp genus Nasonia

Males in the parasitoid wasp genus Nasonia have distinct, species-specific, head shapes. The availability of fertile hybrids among the species, along with obligate haploidy of males, facilitates analysis of complex gene interactions in development and evolution. Previous analyses showed that both the divergence in head shape between Nasonia vitripennis and Nasonia giraulti, and the head-specific developmental defects of F2 haploid hybrid males, are governed by multiple changes in networks of interacting genes. Here, we extend our understanding of the gene interactions that affect morphogenesis in male heads. Use of artificial diploid male hybrids shows that alleles mediating developmental defects are recessive, while there are diverse dominance relationships among other head shape traits. At the molecular level, the sex determination locus doublesex plays a major role in male head shape differences, but it is not the only important factor. Introgression of a giraulti region on chromsome 2 reveals a recessive locus that causes completely penetrant head clefting in both males and females in a vitripennis background. Finally, a third species (N. longicornis) was used to investigate the timing of genetic changes related to head morphology, revealing that most changes causing defects arose after the divergence of N. vitripennis from the other species, but prior to the divergence of N. giraulti and N. longicornis from each other. Our results demonstrate that developmental gene networks can be dissected using interspecies crosses in Nasonia, and set the stage for future fine-scale genetic dissection of both head shape and hybrid developmental defects.

RIL-StEp: epistasis analysis of rice recombinant inbred lines reveals candidate interacting genes that control seed hull color and leaf chlorophyll content

Characterizing epistatic gene interactions is fundamental for understanding the genetic architecture of complex traits. However, due to the large number of potential gene combinations, detecting epistatic gene interactions is computationally demanding. A simple, easy-to-perform method for sensitive detection of epistasis is required. Due to their homozygous nature, use of recombinant inbred lines excludes the dominance effect of alleles and interactions involving heterozygous genotypes, thereby allowing detection of epistasis in a simple and interpretable model. Here, we present an approach called RIL-StEp (recombinant inbred lines stepwise epistasis detection) to detect epistasis using single-nucleotide polymorphisms in the genome. We applied the method to reveal epistasis affecting rice (Oryza sativa) seed hull color and leaf chlorophyll content and successfully identified pairs of genomic regions that presumably control these phenotypes. This method has the potential to improve our understanding of the genetic architecture of various traits of crops and other organisms.

Rapid generation of ecologically relevant behavioral novelty in experimental cichlid hybrids

The East African cichlid radiations are characterized by repeated and rapid diversification into many distinct species with different ecological specializations and by a history of hybridization events between nonsister species. Such hybridization might provide important fuel for adaptive radiation. Interspecific hybrids can have extreme trait values or novel trait combinations and such transgressive phenotypes may allow some hybrids to explore ecological niches neither of the parental species could tap into. Here, we investigate the potential of second-generation (F2) hybrids between two generalist cichlid species from Lake Malawi to exploit a resource neither parental species is specialized on: feeding by sifting sand. Some of the F2 hybrids phenotypically resembled fish of species that are specialized on sand sifting. We combined experimental behavioral and morphometric approaches to test whether the F2 hybrids are transgressive in both morphology and behavior related to sand sifting. We then performed a quantitative trait loci (QTL) analysis using RADseq markers to investigate the genetic architecture of morphological and behavioral traits. We show that transgression is present in several morphological traits, that novel trait combinations occur, and we observe transgressive trait values in sand sifting behavior in some of the F2 hybrids. Moreover, we find QTLs for morphology and for sand sifting behavior, suggesting the existence of some loci with moderate to large effects. We demonstrate that hybridization has the potential to rapidly generate novel and ecologically relevant phenotypes that may be suited to a niche neither of the parental species occupies. Interspecific hybridization may thereby contribute to the rapid generation of ecological diversity in cichlid radiations.

Multiple QTL Mapping in Autopolyploids: A Random-Effect Model Approach with Application in a Hexaploid Sweetpotato Full-Sib Population

In developing countries, the sweetpotato, Ipomoea batatas (L.) Lam. [Formula: see text], is an important autopolyploid species, both socially and economically. However, quantitative trait loci (QTL) mapping has remained limited due to its genetic complexity. Current fixed-effect models can fit only a single QTL and are generally hard to interpret. Here, we report the use of a random-effect model approach to map multiple QTL based on score statistics in a sweetpotato biparental population ('Beauregard' × 'Tanzania') with 315 full-sibs. Phenotypic data were collected for eight yield component traits in six environments in Peru, and jointly adjusted means were obtained using mixed-effect models. An integrated linkage map consisting of 30,684 markers distributed along 15 linkage groups (LGs) was used to obtain the genotype conditional probabilities of putative QTL at every centiMorgan position. Multiple interval mapping was performed using our R package QTLpoly and detected a total of 13 QTL, ranging from none to four QTL per trait, which explained up to 55% of the total variance. Some regions, such as those on LGs 3 and 15, were consistently detected among root number and yield traits, and provided a basis for candidate gene search. In addition, some QTL were found to affect commercial and noncommercial root traits distinctly. Further best linear unbiased predictions were decomposed into additive allele effects and were used to compute multiple QTL-based breeding values for selection. Together with quantitative genotyping and its appropriate usage in linkage analyses, this QTL mapping methodology will facilitate the use of genomic tools in sweetpotato breeding as well as in other autopolyploids.

High Density Mapping of Quantitative Trait Loci Conferring Gluten Strength in Canadian Durum Wheat

Gluten strength is one of the factors that determine the end-use quality of durum wheat and is an important breeding target for this crop. To characterize the quantitative trait loci (QTL) controlling gluten strength in Canadian durum wheat cultivars, a population of 162 doubled haploid (DH) lines segregating for gluten strength and derived from cv. Pelissier × cv. Strongfield was used in this study. The DH lines, parents, and controls were grown in 3 years and two seeding dates in each year and gluten strength of grain samples was measured by sodium dodecyl sulfate (SDS)-sedimentation volume (SV). With a genetic map created by genotyping the DH lines using the Illumina Infinium iSelect Wheat 90K SNP (single nucleotide polymorphism) chip, QTL contributing to gluten strength were detected on chromosome 1A, 1B, 2B, and 3A. Two major and stable QTL detected on chromosome 1A (QGlu.spa-1A) and 1B (QGlu.spa-1B.1) explaining 13.7-18.7% and 25.4-40.1% of the gluten strength variability respectively were consistently detected over 3 years, with the trait increasing alleles derived from Strongfield. Putative candidate genes underlying the major QTL were identified. Two novel minor QTL (QGlu.spa-3A.1 and QGlu.spa-3A.2) with the trait increasing allele derived from Pelissier were mapped on chromosome 3A explaining up to 8.9% of the phenotypic variance; another three minor QTL (QGlu.spa-2B.1, QGlu.spa-2B.2, and QGlu.spa-2B.3) located on chromosome 2B explained up to 8.7% of the phenotypic variance with the trait increasing allele derived from Pelissier. QGlu.spa-2B.1 is a new QTL and has not been reported in the literature. Multi-environment analysis revealed genetic (QTL) × environment interaction due to the difference of effect in magnitude rather than the direction of the QTL. Eleven pairs of digenic epistatic QTL were identified, with an epistatic effect between the two major QTL of QGlu.spa-1A and QGlu.spa-1B.1 detected in four out of six environments. The peak SNPs and SNPs flanking the QTL interval of QGlu.spa-1A and QGlu.spa-1B.1 were converted to Kompetitive Allele Specific PCR (KASP) markers, which can be deployed in marker-assisted breeding to increase the efficiency and accuracy of phenotypic selection for gluten strength in durum wheat. The QTL that were expressed consistently across environments are of great importance to maintain the gluten strength of Canadian durum wheat to current market standards during the genetic improvement.

Characterization of Two Growth Period QTLs Reveals Modification of PRR3 Genes During Soybean Domestication

Soybean yield is largely dependent on growth period. We characterized two growth period quantitative trait loci, Gp11 and Gp12, from a recombinant inbred population generated from a cross of wild (W05) and cultivated (C08) soybean. Lines carrying Gp11C08 and Gp12C08 tend to have a shorter growth period and higher expression of GmFT2a and GmFT5a. Furthermore, multiple interval mapping suggests that Gp11 and Gp12 may be genetically interacting with the E2 locus. This is consistent with the observation that GmFT2a and GmFT5a are activated by Gp11C08 and Gp12C08 at ZT4 in the recessive e2 but not the dominant E2 background. Gp11 and Gp12 are duplicated genomic regions each containing a copy of the soybean ortholog of PSEUDO RESPONSE REGULATOR 3 (GmPRR3A and GmPRR3B). GmPRR3A and GmPRR3B from C08 carry mutations that delete the CCT domain in the encoded proteins. These mutations were selected during soybean improvement and they alter the subcellular localization of GmPRR3A and GmPRR3B. Furthermore, GmPRR3A and GmPRR3B can interact with TOPLESS-related transcription factors, suggesting that they function in a transcription repressor complex. This study addresses previously unexplored components of the genetic network that probably controls the growth period of soybean and puts these loci into context with the well-characterized growth period-regulating E loci.

Collective interaction effects associated with mammalian behavioral traits reveal genetic factors connecting fear and hemostasis

BACKGROUND

Investigation of the genetic architectures that influence the behavioral traits of animals can provide important insights into human neuropsychiatric phenotypes. These traits, however, are often highly polygenic, with individual loci contributing only small effects to the overall association. The polygenicity makes it challenging to explain, for example, the widely observed comorbidity between stress and cardiac disease.

METHODS

We present an algorithm for inferring the collective association of a large number of interacting gene variants with a quantitative trait. Using simulated data, we demonstrate that by taking into account the non-uniform distribution of genotypes within a cohort, we can achieve greater power than regression-based methods for high-dimensional inference.

RESULTS

We analyzed genome-wide data sets of outbred mice and pet dogs, and found neurobiological pathways whose associations with behavioral traits arose primarily from interaction effects: γ-carboxylated coagulation factors and downstream neuronal signaling were highly associated with conditioned fear, consistent with our previous finding in human post-traumatic stress disorder (PTSD) data. Prepulse inhibition in mice was associated with serotonin transporter and platelet homeostasis, and noise-induced fear in dogs with hemostasis.

CONCLUSIONS

Our findings suggest a novel explanation for the observed comorbidity between PTSD/anxiety and cardiovascular diseases: key coagulation factors modulating hemostasis also regulate synaptic plasticity affecting the learning and extinction of fear.

Diabetes and Kidney Disease in American Indians: Potential Role of Sugar-Sweetened Beverages

Since the early 20th century, a marked increase in obesity, diabetes, and chronic kidney disease has occurred in the American Indian population, especially the Pima Indians of the Southwest. Here, we review the current epidemic and attempt to identify remediable causes. A search was performed using PubMed and the search terms American Indian and obesity, American Indian and diabetes, American Indian and chronic kidney disease, and American Indian and sugar or fructose, Native American, Alaska Native, First Nations, Aboriginal, Amerind, and Amerindian for American Indian for articles linking American Indians with diabetes, obesity, chronic kidney disease, and sugar; additional references were identified in these publications traced to 1900 and articles were reviewed if they were directly discussing these topics. Multiple factors are involved in the increased risk for diabetes and kidney disease in the American Indian population, including poverty, overnutrition, poor health care, high intake of sugar, and genetic mechanisms. Genetic factors may be especially important in the Pima, as historical records suggest that this group was predisposed to obesity before exposure to Western culture and diet. Exposure to sugar-sweetened beverages may also be involved in the increased risk for chronic kidney disease. In these small populations in severe health crisis, we recommend further studies to investigate the role of excess added sugar, especially sugar-sweetened beverages, as a potentially remediable risk factor.