Complex genetic interactions in a quantitative trait locus

Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs), characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg) QTGs (MKT1, END3, and RHO2). We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3′UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.     

Four linked genes participate in controlling sporulation efficiency in budding yeast

Quantitative traits are conditioned by several genetic determinants. Since such genes influence many important complex traits in various organisms, the identification of quantitative trait loci (QTLs) is of major interest, but still encounters serious difficulties. We detected four linked genes within one QTL, which participate in controlling sporulation efficiency in Saccharomyces cerevisiae. Following the identification of single nucleotide polymorphisms by comparing the sequences of 145 genes between the parental strains SK1 and S288c, we analyzed the segregating progeny of the cross between them. Through reciprocal hemizygosity analysis, four genes, RAS2, PMS1, SWS2, and FKH2, located in a region of 60 kilobases on Chromosome 14, were found to be associated with sporulation efficiency. Three of the four “high” sporulation alleles are derived from the “low” sporulating strain. Two of these sporulation-related genes were verified through allele replacements. For RAS2, the causative variation was suggested to be a single nucleotide difference in the upstream region of the gene. This quantitative trait nucleotide accounts for sporulation variability among a set of ten closely related winery yeast strains. Our results provide a detailed view of genetic complexity in one “QTL region” that controls a quantitative trait and reports a single nucleotide polymorphism-trait association in wild strains. Moreover, these findings have implications on QTL identification in higher eukaryotes.     

Isolation of a major genetic interaction associated with an extreme phenotype using assorted F2 populations in rice

Detection of quantitative trait loci (QTLs) is dependent on the materials used in the analysis, as different combinations of parental materials may lead to different outcomes in QTLs for the same trait. On the other hand, an extreme phenotype associated with a given trait implies the potential involvement of a particular allele in various allelic interactions. A genetic factor associated with such an extreme phenotype may frequently be identified from various genetic populations consisting of different parental combinations. In this study, we attempted to uncover the genetic factor associated with extremely early heading date in rice, using various F2 populations. Heading date in rice has been characterized by at least 19 QTLs, from which 12 genes have been identified. A58, a rice strain with an extremely early heading date, is adapted to Hokkaido, the northernmost limit of rice cultivation. Six F2 populations derived from crosses of A58 with six other strains displayed a range of heading dates. Genotyping using 19 QTL markers indicated that the A58 allele of the Ghd7 locus was present in most F2 individuals exhibiting extremely early heading dates. This analysis also demonstrated that when the wild-type Ehd1 allele was present, the Ghd7 allele from A58 accelerated floral induction. The results of this study demonstrate that assorted F2 populations are valuable materials for comprehensive genotyping to explore major genetic factors for extreme phenotypes, and that this methodology is broadly applicable to other unknown traits.     

Pleiotropy of FRIGIDA enhances the potential for multivariate adaptation

An evolutionary response to selection requires genetic variation; however, even if it exists, then the genetic details of the variation can constrain adaptation. In the simplest case, unlinked loci and uncorrelated phenotypes respond directly to multivariate selection and permit unrestricted paths to adaptive peaks. By contrast, ‘antagonistic’ pleiotropic loci may constrain adaptation by affecting variation of many traits and limiting the direction of trait correlations to vectors that are not favoured by selection. However, certain pleiotropic configurations may improve the conditions for adaptive evolution. Here, we present evidence that the Arabidopsis thaliana gene FRI (FRIGIDA) exhibits ‘adaptive’ pleiotropy, producing trait correlations along an axis that results in two adaptive strategies. Derived, low expression FRI alleles confer a ‘drought escape’ strategy owing to fast growth, low water use efficiency and early flowering. By contrast, a dehydration avoidance strategy is conferred by the ancestral phenotype of late flowering, slow growth and efficient water use during photosynthesis. The dehydration avoidant phenotype was recovered when genotypes with null FRI alleles were transformed with functional alleles. Our findings indicate that the well-documented effects of FRI on phenology result from differences in physiology, not only a simple developmental switch.     

Genetic association with boldness and maternal performance in a free-ranging population of grey seals (Halichoerus grypus)

Individual variation in quantitative traits clearly influence many ecological and evolutionary processes. Moderate to high heritability estimates of personality and life-history traits suggest some level of genetic control over these traits. Yet, we know very little of the underlying genetic architecture of phenotypic variation in the wild. In this study, we used a candidate gene approach to investigate the association of genetic variants with repeated measures of boldness and maternal performance traits (weaning mass and lactation duration) collected over an 11- and 28-year period, respectively, in a free-ranging population of grey seals on Sable Island National Park Reserve, Canada. We isolated and re-sequenced five genes: dopamine receptor D4 (DRD4), serotonin transporter (SERT), oxytocin receptor (OXTR), and melanocortin receptors 1 (MC1R) and 5 (MC5R). We discovered single nucleotide polymorphisms (SNPs) in each gene; and, after accounting for loci in linkage disequilibrium and filtering due to missing data, we were able to test for genotype-phenotype relationships at seven loci in three genes (DRD4, SERT, and MC1R). We tested for association between these loci and traits of 180 females having extreme shy-bold phenotypes using mixed-effects models. One locus within SERT was significantly associated with boldness (effect size = 0.189) and a second locus within DRD4 with weaning mass (effect size = 0.232). Altogether, genotypes explained 6.52–13.66% of total trait variation. Our study substantiates SERT and DRD4 as important determinants of behaviour, and provides unique insight into the molecular mechanisms underlying maternal performance variation in a marine predator.Subject terms: Behavioural ecology, Evolutionary genetics, Behavioural genetics, Genetic association study, Quantitative trait     

The Genetic Basis of Natural Variation in Oenological Traits in Saccharomyces cerevisiae

Saccharomyces cerevisiae is the main microorganism responsible for wine alcoholic fermentation. The oenological phenotypes resulting from fermentation, such as the production of acetic acid, glycerol, and residual sugar concentration are regulated by multiple genes and vary quantitatively between different strain backgrounds. With the aim of identifying the quantitative trait loci (QTLs) that regulate oenological phenotypes, we performed linkage analysis using three crosses between highly diverged S. cerevisiae strains. Segregants from each cross were used as starter cultures for 20-day fermentations, in synthetic wine must, to simulate actual winemaking conditions. Linkage analysis on phenotypes of primary industrial importance resulted in the mapping of 18 QTLs. We tested 18 candidate genes, by reciprocal hemizygosity, for their contribution to the observed phenotypic variation, and validated five genes and the chromosome II right subtelomeric region. We observed that genes involved in mitochondrial metabolism, sugar transport, nitrogen metabolism, and the uncharacterized ORF YJR030W explained most of the phenotypic variation in oenological traits. Furthermore, we experimentally validated an exceptionally strong epistatic interaction resulting in high level of succinic acid between the Sake FLX1 allele and the Wine/European MDH2 allele. Overall, our work demonstrates the complex genetic basis underlying wine traits, including natural allelic variation, antagonistic linked QTLs and complex epistatic interactions between alleles from strains with different evolutionary histories.     

The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance

Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.     

Genetic Linkage Map Construction and QTL Mapping of Salt Tolerance Traits in Zoysiagrass (Zoysia japonica)

Zoysiagrass (Zoysia Willd.) is an important warm season turfgrass that is grown in many parts of the world. Salt tolerance is an important trait in zoysiagrass breeding programs. In this study, a genetic linkage map was constructed using sequence-related amplified polymorphism markers and random amplified polymorphic DNA markers based on an F₁ population comprising 120 progeny derived from a cross between Zoysia japonica Z105 (salt-tolerant accession) and Z061 (salt-sensitive accession). The linkage map covered 1211 cM with an average marker distance of 5.0 cM and contained 24 linkage groups with 242 marker loci (217 sequence-related amplified polymorphism markers and 25 random amplified polymorphic DNA markers). Quantitative trait loci affecting the salt tolerance of zoysiagrass were identified using the constructed genetic linkage map. Two significant quantitative trait loci (qLF-1 and qLF-2) for leaf firing percentage were detected; qLF-1 at 36.3 cM on linkage group LG4 with a logarithm of odds value of 3.27, which explained 13.1% of the total variation of leaf firing and qLF-2 at 42.3 cM on LG5 with a logarithm of odds value of 2.88, which explained 29.7% of the total variation of leaf firing. A significant quantitative trait locus (qSCW-1) for reduced percentage of dry shoot clipping weight was detected at 44.1 cM on LG5 with a logarithm of odds value of 4.0, which explained 65.6% of the total variation. This study provides important information for further functional analysis of salt-tolerance genes in zoysiagrass. Molecular markers linked with quantitative trait loci for salt tolerance will be useful in zoysiagrass breeding programs using marker-assisted selection.     

High-Resolution Mapping of Complex Traits with a Four-Parent Advanced Intercross Yeast Population

A large fraction of human complex trait heritability is due to a high number of variants with small marginal effects and their interactions with genotype and environment. Such alleles are more easily studied in model organisms, where environment, genetic makeup, and allele frequencies can be controlled. Here, we examine the effect of natural genetic variation on heritable traits in a very large pool of baker’s yeast from a multiparent 12th generation intercross. We selected four representative founder strains to produce the Saccharomyces Genome Resequencing Project (SGRP)-4X mapping population and sequenced 192 segregants to generate an accurate genetic map. Using these individuals, we mapped 25 loci linked to growth traits under heat stress, arsenite, and paraquat, the majority of which were best explained by a diverging phenotype caused by a single allele in one condition. By sequencing pooled DNA from millions of segregants grown under heat stress, we further identified 34 and 39 regions selected in haploid and diploid pools, respectively, with most of the selection against a single allele. While the most parsimonious model for the majority of loci mapped using either approach was the effect of an allele private to one founder, we could validate examples of pleiotropic effects and complex allelic series at a locus. SGRP-4X is a deeply characterized resource that provides a framework for powerful and high-resolution genetic analysis of yeast phenotypes and serves as a test bed for testing avenues to attack human complex traits.     

Mapping determinants of gene expression plasticity by genetical genomics in C. elegans

Recent genetical genomics studies have provided intimate views on gene regulatory networks. Gene expression variations between genetically different individuals have been mapped to the causal regulatory regions, termed expression quantitative trait loci. Whether the environment-induced plastic response of gene expression also shows heritable difference has not yet been studied. Here we show that differential expression induced by temperatures of 16 °C and 24 °C has a strong genetic component in Caenorhabditis elegans recombinant inbred strains derived from a cross between strains CB4856 (Hawaii) and N2 (Bristol). No less than 59% of 308 trans-acting genes showed a significant eQTL-by-environment interaction, here termed plasticity quantitative trait loci. In contrast, only 8% of an estimated 188 cis-acting genes showed such interaction. This indicates that heritable differences in plastic responses of gene expression are largely regulated in trans. This regulation is spread over many different regulators. However, for one group of trans-genes we found prominent evidence for a common master regulator: a transband of 66 coregulated genes appeared at 24 °C. Our results suggest widespread genetic variation of differential expression responses to environmental impacts and demonstrate the potential of genetical genomics for mapping the molecular determinants of phenotypic plasticity.     

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.     

A Major Genetic Locus in Trypanosoma brucei Is a Determinant of Host Pathology

The progression and variation of pathology during infections can be due to components from both host or pathogen, and/or the interaction between them. The influence of host genetic variation on disease pathology during infections with trypanosomes has been well studied in recent years, but the role of parasite genetic variation has not been extensively studied. We have shown that there is parasite strain-specific variation in the level of splenomegaly and hepatomegaly in infected mice and used a forward genetic approach to identify the parasite loci that determine this variation. This approach allowed us to dissect and identify the parasite loci that determine the complex phenotypes induced by infection. Using the available trypanosome genetic map, a major quantitative trait locus (QTL) was identified on T. brucei chromosome 3 (LOD = 7.2) that accounted for approximately two thirds of the variance observed in each of two correlated phenotypes, splenomegaly and hepatomegaly, in the infected mice (named TbOrg1). In addition, a second locus was identified that contributed to splenomegaly, hepatomegaly and reticulocytosis (TbOrg2). This is the first use of quantitative trait locus mapping in a diploid protozoan and shows that there are trypanosome genes that directly contribute to the progression of pathology during infections and, therefore, that parasite genetic variation can be a critical factor in disease outcome. The identification of parasite loci is a first step towards identifying the genes that are responsible for these important traits and shows the power of genetic analysis as a tool for dissecting complex quantitative phenotypic traits.     

Identification of Shared Genes and Pathways: A Comparative Study of Multiple Sclerosis Susceptibility,Severity and Response to Interferon Beta Treatment

Recent genome-wide association studies (GWAS) have successfully identified several gene loci associated with multiple sclerosis (MS) susceptibility, severity or interferon-beta (IFN-ß) response. However, due to the nature of these studies, the functional relevance of these loci is not yet fully understood. We have utilized a systems biology based approach to explore the genetic interactomes of these MS related traits. We hypothesised that genes and pathways associated with the 3 MS related phenotypes might interact collectively to influence the heterogeneity and unpredictable clinical outcomes observed. Individual genetic interactomes for each trait were constructed and compared, followed by prioritization of common interactors based on their frequencies. Pathway enrichment analyses were performed to highlight shared functional pathways. Biologically relevant genes ABL1, GRB2, INPP5D, KIF1B, PIK3R1, PLCG1, PRKCD, SRC, TUBA1A and TUBA4A were identified as common to all 3 MS phenotypes. We observed that the highest number of first degree interactors were shared between MS susceptibility and MS severity (p = 1.34×10⁻⁷⁹) with UBC as the most prominent first degree interactor for this phenotype pair from the prioritisation analysis. As expected, pairwise comparisons showed that MS susceptibility and severity interactomes shared the highest number of pathways. Pathways from signalling molecules and interaction, and signal transduction categories were found to be highest shared pathways between 3 phenotypes. Finally, FYN was the most common first degree interactor in the MS drugs-gene network. By applying the systems biology based approach, additional significant information can be extracted from GWAS. Results of our interactome analyses are complementary to what is already known in the literature and also highlight some novel interactions which await further experimental validation. Overall, this study illustrates the potential of using a systems biology based approach in an attempt to unravel the biological significance of gene loci identified in large GWAS.     

Genome Wide Association Identifies Novel Loci Involved in Fungal Communication

Understanding how genomes encode complex cellular and organismal behaviors has become the outstanding challenge of modern genetics. Unlike classical screening methods, analysis of genetic variation that occurs naturally in wild populations can enable rapid, genome-scale mapping of genotype to phenotype with a medium-throughput experimental design. Here we describe the results of the first genome-wide association study (GWAS) used to identify novel loci underlying trait variation in a microbial eukaryote, harnessing wild isolates of the filamentous fungus Neurospora crassa. We genotyped each of a population of wild Louisiana strains at 1 million genetic loci genome-wide, and we used these genotypes to map genetic determinants of microbial communication. In N. crassa, germinated asexual spores (germlings) sense the presence of other germlings, grow toward them in a coordinated fashion, and fuse. We evaluated germlings of each strain for their ability to chemically sense, chemotropically seek, and undergo cell fusion, and we subjected these trait measurements to GWAS. This analysis identified one gene, NCU04379 (cse-1, encoding a homolog of a neuronal calcium sensor), at which inheritance was strongly associated with the efficiency of germling communication. Deletion of cse-1 significantly impaired germling communication and fusion, and two genes encoding predicted interaction partners of CSE1 were also required for the communication trait. Additionally, mining our association results for signaling and secretion genes with a potential role in germling communication, we validated six more previously unknown molecular players, including a secreted protease and two other genes whose deletion conferred a novel phenotype of increased communication and multi-germling fusion. Our results establish protein secretion as a linchpin of germling communication in N. crassa and shed light on the regulation of communication molecules in this fungus. Our study demonstrates the power of population-genetic analyses for the rapid identification of genes contributing to complex traits in microbial species.     

Interactions Among Flower-Size QTL of Mimulus guttatus Are Abundant but Highly Variable in Nature

The frequency and character of interactions among genes influencing complex traits remain unknown. Our ignorance is most acute for segregating variation within natural populations, the epistasis most relevant for quantitative trait evolution. Here, we report a comprehensive survey of interactions among a defined set of flower-size QTL: loci polymorphic within a single natural population of yellow monkeyflower (Mimulus guttatus). We find that epistasis is typical. Observed phenotypes routinely differ from those predicted on the basis of direct allelic affects in the isogenic background, although the direction of deviations is highly variable. Across QTL pairs, there are significantly positive and negative interactions for every trait. Across traits, specific locus pairs routinely exhibit both positive and negative interactions. There was a tendency for negative epistasis to accompany positive direct effects and vice versa for the trait of corolla width, which may be due, at least in part, to the fact that QTL were identified from their direct effects on this trait.EPISTASIS contributes significantly to intrapopulation variation in floral morphology, development time, and male fitness components of Mimulus guttatus (Kelly 2005). The aggregate effect of interactions among QTL substantially alters the resemblance of relatives and phenotypic response to inbreeding. However, previous experiments did not identify the specific character of interactions between QTL. For example, it is not clear whether interactions change the rank order of QTL genotypes. If the direction of allelic effect changes with genetic background, so-called “sign epistasis” (Weinreich et al. 2005), the same selection pressure may favor different alleles in different genomic contexts, e.g., different subpopulations of a species (De Brito et al. 2005). When the trait is fitness, these kinds of interactions naturally generate peaks and valleys in genotypic fitness landscapes (Wright 1932; Burch and Chao 2000).Sign epistasis can involve a reversal of allelic effect at one or both loci of an interacting pair. Poelwijk et al. (2007) define the double reversal as “reciprocal sign epistasis” and contrast sign epistasis generally to “magnitude epistasis” where the magnitude but not the direction of allelic effects changes with genetic background. Magnitude epistasis includes synergistic interactions (alleles have greater effect in combination than individually) and less-than-additive or diminishing returns interactions (alleles have lesser effect in combination) (see Crow and Kimura 1970). Alternatively, one can classify interactions as positive or negative (Phillips et al. 2000)—positive if the observed phenotype of an allelic combination exceeds that predicted from direct effects at each locus, and negative if the phenotype of the combination is less than the additive prediction. Unfortunately, there is no simple logical mapping from the magnitude/sign epistasis classification to the positive/negative classification, nor to epistasis in the classical sense (Bateson 1909), wherein one locus masks the effect of another. The taxonomy of epistasis is further complicated by dominance (Routman and Cheverud 1997), higher-order interactions (Templeton 2000), and environmental dependencies (Brock et al. 2010).Molecular genetic studies provide clear examples of sign epistasis. Here, the interacting polymorphisms are often within the same gene. For example, the stability of RNA secondary structures requires matching of nucleotides at different positions. Whether a particular nucleotide change increases or reduces stability depends entirely on the identity of the nucleotide at its paired site (Chen et al. 1999). With “compensatory evolution” (Moore et al. 2000), a mutation that is neutral or detrimental in the original genetic background becomes advantageous by compensating for some other mutation that has recently fixed or at least become prevalent within the population. Mutations conferring antibiotic resistance often have deleterious side effects that reduce bacterial fitness in the absence of the drug. These side effects are attenuated by secondary mutations that are often detrimental in the original genotype (Levin et al. 1997; Schrag et al. 1997).Despite the progress in research on microbes (Weinreich et al. 2005; Elena et al. 2010), we currently know little about the prevalence or nature of epistasis for quantitative traits (Carlborg and Haley 2004) and particularly its impact on standing (segregating) variation within natural populations. Eshed and Zamir (1996) found extensive epistasis among QTL in Lycopersicon (tomato), but interactions primarily influenced the magnitude of single-locus effects and not their direction. In contrast, Kroymann and Mitchell-Olds (2005) documented a case of QTL effect reversal in Arabidopsis thaliana. The high allele for biomass accumulation in the Ler-0 accession becomes the low allele when introgressed into another line (the Col-0 accession). Patterns of gene sequence variation suggest that this polymorphism is maintained by balancing selection. In Avena barbata, two loci with negligible average effects exhibit sign epistasis for fitness in a cross between mesic and xeric genotypes (Latta et al. 2010).Even with these examples, it is difficult to evaluate the quantitative frequency of epistasis or regularities in its nature from the current literature. In part, this is because discovery of QTL×QTL interactions is typically idiosyncratic. In a segregating mapping population such as F₂’s or recombinant inbred lines, there is limited replication of particular multi-locus genotypes. As a consequence, it is difficult to accurately estimate the mean phenotype of any particular multi-locus genotype. Also, there are an enormous number of pairwise tests in a full simultaneous scan, which leads to very stringent significance levels (see box 2 of Carlborg and Haley 2004). Thus, while genomic scans have successfully identified interactions (e.g., Li et al. 1997; Cheverud 2000; Montooth et al. 2003), it is hard to know if the many nonsignificant interactions are due to absence of effect or absence of power.Our intention in this study was to conduct a comprehensive survey of interactions among a specific set of monkeyflower QTL. These loci are polymorphic within a single contiguous natural population. We first mapped flower-size QTL within nearly isogenic lines (NILs). Measurements on the NILs isolate the “direct effect” of each QTL, i.e., how the polymorphism affects phenotype in a single uniform genetic background. We then intercrossed the various single-QTL NILs in all combinations to generate the four double homozygotes for each pair of QTL: aabb, AAbb, aaBB, and AABB. This design allows high replication of each multi-locus genotype and hence reasonable power to detect even moderate epistasis (e.g., Moyle and Nakazato 2009). Applying this methodology, we find that epistasis is more the rule than the exception, although the form of interaction is highly variable among QTL pairs.     

QTL analysis of flowering time inArabidopsis thaliana

Quantitative trait loci (QTL) analyses based on restriction fragment length polymorphism maps have been used to resolve the genetic control of flowering time in a cross between twoArabidopsis thaliana ecotypes H51 and Landsbergerecta, differing widely in flowering time. Five quantitative trait loci affecting flowering time were identified in this cross (RLN1-5), four of which are located in regions containing mutations or loci previously identified as conferring a late-flowering phenotype. One of these loci is coincident with theFRI locus identified as the major determinant for late flowering and vernalization responsiveness in theArabidopsis ecotype Stockholm.RLN5, which maps to the lower half of chromosome five (between markers mi69 and m233), only affected flowering time significantly under short day conditions following a vernalization period. The late-flowering phenotype of H51 compared to Landsbergerecta was due to alleles conferring late flowering at only two of the five loci. At the three other loci, H51 possessed alleles conferring early flowering in comparison to those of Landsbergerecta. Combinations of alleles conferring early and late flowering from both parents accounted for the transgressive segregation of flowering time observed within the F₂ population. Three QTL,RLN1,RLN2 andRLN3 displayed significant genotype-by-environment interactions for flowering time. A significant interaction between alleles atRLN3 andRLN4 was detected.