Unifying Genetic Canalization,Genetic Constraint,and Genotype-by-Environment Interaction: QTL by Genomic Background by Environment Interaction of Flowering Time in Boechera stricta

Natural populations exhibit substantial variation in quantitative traits. A quantitative trait is typically defined by its mean and variance, and to date most genetic mapping studies focus on loci altering trait means but not (co)variances. For single traits, the control of trait variance across genetic backgrounds is referred to as genetic canalization. With multiple traits, the genetic covariance among different traits in the same environment indicates the magnitude of potential genetic constraint, while genotype-by-environment interaction (GxE) concerns the same trait across different environments. While some have suggested that these three attributes of quantitative traits are different views of similar concepts, it is not yet clear, however, whether they have the same underlying genetic mechanism. Here, we detect quantitative trait loci (QTL) influencing the (co)variance of phenological traits in six distinct environments in Boechera stricta, a close relative of Arabidopsis. We identified nFT as the QTL altering the magnitude of phenological trait canalization, genetic constraint, and GxE. Both the magnitude and direction of nFT''s canalization effects depend on the environment, and to our knowledge, this reversibility of canalization across environments has not been reported previously. nFT''s effects on trait covariance structure (genetic constraint and GxE) likely result from the variable and reversible canalization effects across different traits and environments, which can be explained by the interaction among nFT, genomic backgrounds, and environmental stimuli. This view is supported by experiments demonstrating significant nFT by genomic background epistatic interactions affecting phenological traits and expression of the candidate gene, FT. In contrast to the well-known canalization gene Hsp90, the case of nFT may exemplify an alternative mechanism: Our results suggest that (at least in traits with major signal integrators such as flowering time) genetic canalization, genetic constraint, and GxE may have related genetic mechanisms resulting from interactions among major QTL, genomic backgrounds, and environments.     

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 variation for lettuce seed thermoinhibition is associated with temperature-sensitive expression of abscisic Acid, gibberellin, and ethylene biosynthesis, metabolism, and response genes

Lettuce (Lactuca sativa ‘Salinas’) seeds fail to germinate when imbibed at temperatures above 25°C to 30°C (termed thermoinhibition). However, seeds of an accession of Lactuca serriola (UC96US23) do not exhibit thermoinhibition up to 37°C in the light. Comparative genetics, physiology, and gene expression were analyzed in these genotypes to determine the mechanisms governing the regulation of seed germination by temperature. Germination of the two genotypes was differentially sensitive to abscisic acid (ABA) and gibberellin (GA) at elevated temperatures. Quantitative trait loci associated with these phenotypes colocated with a major quantitative trait locus (Htg6.1) from UC96US23 conferring germination thermotolerance. ABA contents were elevated in Salinas seeds that exhibited thermoinhibition, consistent with the ability of fluridone (an ABA biosynthesis inhibitor) to improve germination at high temperatures. Expression of many genes involved in ABA, GA, and ethylene biosynthesis, metabolism, and response was differentially affected by high temperature and light in the two genotypes. In general, ABA-related genes were more highly expressed when germination was inhibited, and GA- and ethylene-related genes were more highly expressed when germination was permitted. In particular, LsNCED4, a gene encoding an enzyme in the ABA biosynthetic pathway, was up-regulated by high temperature only in Salinas seeds and also colocated with Htg6.1. The temperature sensitivity of expression of LsNCED4 may determine the upper temperature limit for lettuce seed germination and may indirectly influence other regulatory pathways via interconnected effects of increased ABA biosynthesis.     

Joint effects of genes underlying a temperature specialization tradeoff in yeast

A central goal of evolutionary genetics is to understand, at the molecular level, how organisms adapt to their environments. For a given trait, the answer often involves the acquisition of variants at unlinked sites across the genome. Genomic methods have achieved landmark successes in pinpointing these adaptive loci. To figure out how a suite of adaptive alleles work together, and to what extent they can reconstitute the phenotype of interest, requires their transfer into an exogenous background. We studied the joint effect of adaptive, gain-of-function thermotolerance alleles at eight unlinked genes from Saccharomyces cerevisiae, when introduced into a thermosensitive sister species, S. paradoxus. Although the loci damped each other’s beneficial impact (that is, they were subject to negative epistasis), most boosted high-temperature growth alone and in combination, and none was deleterious. The complete set of eight genes was sufficient to confer ~15% of the S. cerevisiae thermotolerance phenotype in the S. paradoxus background. The same loci also contributed to a heretofore unknown advantage in cold growth by S. paradoxus. Together, our data establish temperature resistance in yeasts as a model case of a genetically complex evolutionary tradeoff, which can be partly reconstituted from the sequential assembly of unlinked underlying loci.     

Genetic Variation for Life History Sensitivity to Seasonal Warming in Arabidopsis thaliana

Climate change has altered life history events in many plant species; however, little is known about genetic variation underlying seasonal thermal response. In this study, we simulated current and three future warming climates and measured flowering time across a globally diverse set of Arabidopsis thaliana accessions. We found that increased diurnal and seasonal temperature (1°–3°) decreased flowering time in two fall cohorts. The early fall cohort was unique in that both rapid cycling and overwintering life history strategies were revealed; the proportion of rapid cycling plants increased by 3–7% for each 1° temperature increase. We performed genome-wide association studies (GWAS) to identify the underlying genetic basis of thermal sensitivity. GWAS identified five main-effect quantitative trait loci (QTL) controlling flowering time and another five QTL with thermal sensitivity. Candidate genes include known flowering loci; a cochaperone that interacts with heat-shock protein 90; and a flowering hormone, gibberellic acid, a biosynthetic enzyme. The identified genetic architecture allowed accurate prediction of flowering phenotypes (R² > 0.95) that has application for genomic selection of adaptive genotypes for future environments. This work may serve as a reference for breeding and conservation genetic studies under changing environments.     

Receptor Polymorphism and Genomic Structure Interact to Shape Bitter Taste Perception

The ability to taste bitterness evolved to safeguard most animals, including humans, against potentially toxic substances, thereby leading to food rejection. Nonetheless, bitter perception is subject to individual variations due to the presence of genetic functional polymorphisms in bitter taste receptor (TAS2R) genes, such as the long-known association between genetic polymorphisms in TAS2R38 and bitter taste perception of phenylthiocarbamide. Yet, due to overlaps in specificities across receptors, such associations with a single TAS2R locus are uncommon. Therefore, to investigate more complex associations, we examined taste responses to six structurally diverse compounds (absinthin, amarogentin, cascarillin, grosheimin, quassin, and quinine) in a sample of the Caucasian population. By sequencing all bitter receptor loci, inferring long-range haplotypes, mapping their effects on phenotype variation, and characterizing functionally causal allelic variants, we deciphered at the molecular level how a subjects’ genotype for the whole-family of TAS2R genes shapes variation in bitter taste perception. Within each haplotype block implicated in phenotypic variation, we provided evidence for at least one locus harboring functional polymorphic alleles, e.g. one locus for sensitivity to amarogentin, one of the most bitter natural compounds known, and two loci for sensitivity to grosheimin, one of the bitter compounds of artichoke. Our analyses revealed also, besides simple associations, complex associations of bitterness sensitivity across TAS2R loci. Indeed, even if several putative loci harbored both high- and low-sensitivity alleles, phenotypic variation depended on linkage between these alleles. When sensitive alleles for bitter compounds were maintained in the same linkage phase, genetically driven perceptual differences were obvious, e.g. for grosheimin. On the contrary, when sensitive alleles were in opposite phase, only weak genotype-phenotype associations were seen, e.g. for absinthin, the bitter principle of the beverage absinth. These findings illustrate the extent to which genetic influences on taste are complex, yet arise from both receptor activation patterns and linkage structure among receptor genes.     

Simultaneous improvement and genetic dissection of grain yield and its related traits in a backbone parent of hybrid rice (Oryza sativa L.) using selective introgression

Three populations with a total of 125 BC2F3:4 introgression lines (ILs) selected for high yields from three BC2F2 populations were used for genetic dissection of rice yield and its related traits. The progeny testing in replicated phenotyping across two environments and genotyping with 140 polymorphic simple sequence repeat markers allowed the identification of 21 promising ILs that had significantly higher yields than the recurrent parent Shuhui527 (SH527). A total of 94 quantitative trait loci (QTL) were identified using the selective introgression method based on Chi-squared (χ ²) and multi-locus probability tests and the RSTEP-LRT method based on stepwise regression. These QTL were mostly mapped to 12 clusters on seven rice chromosomes. Several important properties of the QTL affecting grain yield (GY) and its related traits were revealed. The first one was the presence of strong and frequent non-random associations between or among QTL that affect low-heritability traits (GY and spikelet number per panicle, SN) in the ILs with high trait values. Second, beneficial alleles at 88.9 % GY and 75 % SN QTL for increased productivity were from the donors, suggesting that direct phenotypic selection for high yield in our introgression breeding program was a powerful way to transfer beneficial alleles at many loci from the donors into SH527. Third, most QTL were in clusters with large effects on multiple traits, which should be the focal points in further investigations and marker-assisted selection in rice. The majority of the QTL identified were expressed only in one of the environments, suggesting that differential expression of QTL in different environments is the primary genetic basis of genotype × environment interaction. Finally, a large variation in both the direction and magnitude of QTL effects was detected for different donor alleles at seven QTL in the same genetic background and environments. This finding suggests the possible presence of functional diversity among the donor alleles at these loci. The promising ILs and QTL identified provide valuable materials and genetic information for further improving the yield potential of SH527, which is a backbone restorer of hybrid rice in China.     

Negative frequency-dependent selection and asymmetrical transformation stabilise multi-strain bacterial population structures

Streptococcus pneumoniae can be divided into many strains, each a distinct set of isolates sharing similar core and accessory genomes, which co-circulate within the same hosts. Previous analyses suggested the short-term vaccine-associated dynamics of S. pneumoniae strains may be mediated through multi-locus negative frequency-dependent selection (NFDS), which maintains accessory loci at equilibrium frequencies. Long-term simulations demonstrated NFDS stabilised clonally-evolving multi-strain populations through preventing the loss of variation through drift, based on polymorphism frequencies, pairwise genetic distances and phylogenies. However, allowing symmetrical recombination between isolates evolving under multi-locus NFDS generated unstructured populations of diverse genotypes. Replication of the observed data improved when multi-locus NFDS was combined with recombination that was instead asymmetrical, favouring deletion of accessory loci over insertion. This combination separated populations into strains through outbreeding depression, resulting from recombinants with reduced accessory genomes having lower fitness than their parental genotypes. Although simplistic modelling of recombination likely limited these simulations’ ability to maintain some properties of genomic data as accurately as those lacking recombination, the combination of asymmetrical recombination and multi-locus NFDS could restore multi-strain population structures from randomised initial populations. As many bacteria inhibit insertions into their chromosomes, this combination may commonly underlie the co-existence of strains within a niche.Subject terms: Population genetics, Microbial ecology, Microbial genetics, Bacterial genetics, Phylogenetics     

Genetic framework for flowering-time regulation by ambient temperature-responsive miRNAs in Arabidopsis

Flowering is the primary trait affected by ambient temperature changes. Plant microRNAs (miRNAs) are small non-coding RNAs playing an important regulatory role in plant development. In this study, to elucidate the mechanism of flowering-time regulation by small RNAs, we identified six ambient temperature-responsive miRNAs (miR156, miR163, miR169, miR172, miR398 and miR399) in Arabidopsis via miRNA microarray and northern hybridization analyses. We also determined the expression profile of 120 unique miRNA loci in response to ambient temperature changes by miRNA northern hybridization analysis. The expression of the ambient temperature-responsive miRNAs and their target genes was largely anticorrelated at two different temperatures (16 and 23°C). Interestingly, a lesion in short vegetative phase (SVP), a key regulator within the thermosensory pathway, caused alteration in the expression of miR172 and a subset of its target genes, providing a link between a thermosensory pathway gene and miR172. The miR172-overexpressing plants showed a temperature-independent early flowering phenotype, suggesting that modulation of miR172 expression leads to temperature insensitivity. Taken together, our results suggest a genetic framework for flowering-time regulation by ambient temperature-responsive miRNAs under non-stress temperature conditions.     

Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

Grain length is an important quantitative trait in rice (Oryza sativa L.) that influences both grain yield and exterior quality. Although many quantitative trait loci (QTLs) for grain length have been identified, it is still unclear how different alleles from different QTLs regulate grain length coordinately. To explore the mechanisms of QTL combination in the determination of grain length, five mapping populations, including two F₂ populations, an F₃ population, an F₇ recombinant inbred line (RIL) population, and an F₈ RIL population, were developed from the cross between the U.S. tropical japonica variety ‘Lemont’ and the Chinese indica variety ‘Yangdao 4’ and grown under different environmental conditions. Four QTLs (qGL-3-1, qGL-3-2, qGL-4, and qGL-7) for grain length were detected using both composite interval mapping and multiple interval mapping methods in the mapping populations. In each locus, there was an allele from one parent that increased grain length and another allele from another parent that decreased it. The eight alleles in the four QTLs were analyzed to determine whether these alleles act additively across loci, and lead to a linear relationship between the predicted breeding value of QTLs and phenotype. Linear regression analysis suggested that the combination of eight alleles determined grain length. Plants carrying more grain length-increasing alleles had longer grain length than those carrying more grain length-decreasing alleles. This trend was consistent in all five mapping populations and demonstrated the regulation of grain length by the four QTLs. Thus, these QTLs are ideal resources for modifying grain length in rice.     

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.     

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.     

Genome-wide interaction of genotype by erythrocyte n-3 fatty acids contributes to phenotypic variance of diabetes-related traits

Background

Little is known about the interplay between n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level. The present study aimed to examine variance contributions of genotype by environment (GxE) interactions for different erythrocyte n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level in a non-Hispanic white population living in the U.S.A. (n = 820). A tool for Genome-wide Complex Trait Analysis (GCTA) was used to estimate the genome-wide GxE variance contribution of four diabetes-related traits: HOMA-Insulin Resistance (HOMA-IR), fasting plasma insulin, glucose and adiponectin. A GxE genome-wide association study (GWAS) was conducted to further elucidate the GCTA results. Replication was conducted in the participants of the Boston Puerto Rican Health Study (BPRHS) without diabetes (n = 716).

Results

In GOLDN, docosapentaenoic acid (DPA) contributed the most significant GxE variance to the total phenotypic variance of both HOMA-IR (26.5%, P-nominal = 0.034) and fasting insulin (24.3%, P-nominal = 0.042). The ratio of arachidonic acid to eicosapentaenoic acid + docosahexaenoic acid contributed the most significant GxE variance to the total variance of fasting glucose (27.0%, P-nominal = 0.023). GxE variance of the arachidonic acid/eicosapentaenoic acid ratio showed a marginally significant contribution to the adiponectin variance (16.0%, P-nominal = 0.058). None of the GCTA results were significant after Bonferroni correction (P < 0.001). For each trait, the GxE GWAS identified a far larger number of significant single-nucleotide polymorphisms (P-interaction ≤ 10E-5) for the significant E factor (significant GxE variance contributor) than a control E factor (non-significant GxE variance contributor). In the BPRHS, DPA contributed a marginally significant GxE variance to the phenotypic variance of HOMA-IR (12.9%, P-nominal = 0.068) and fasting insulin (18.0%, P-nominal = 0.033).

Conclusion

Erythrocyte n-3 fatty acids contributed a significant GxE variance to diabetes-related traits at the genome-wide level.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-781) contains supplementary material, which is available to authorized users.     

Genome-Wide Contribution of Genotype by Environment Interaction to Variation of Diabetes-Related Traits

While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P-nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P-nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P-nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits.     

Additive genetic variation,but not temperature,influences warning signal expression in Amata nigriceps moths (Lepidoptera: Arctiinae)

Many aposematic species show variation in their color patterns even though selection by predators is expected to stabilize warning signals toward a common phenotype. Warning signal variability can be explained by trade‐offs with other functions of coloration, such as thermoregulation, that may constrain warning signal expression by favoring darker individuals. Here, we investigated the effect of temperature on warning signal expression in aposematic Amata nigriceps moths that vary in their black and orange wing patterns. We sampled moths from two flight seasons that differed in the environmental temperatures and also reared different families under controlled conditions at three different temperatures. Against our prediction that lower developmental temperatures would reduce the warning signal size of the adult moths, we found no effect of temperature on warning signal expression in either wild or laboratory‐reared moths. Instead, we found sex‐ and population‐level differences in wing patterns. Our rearing experiment indicated that ~70% of the variability in the trait is genetic but understanding what signaling and non‐signaling functions of wing coloration maintain the genetic variation requires further work. Our results emphasize the importance of considering both genetic and plastic components of warning signal expression when studying intraspecific variation in aposematic species.     

Variance Heterogeneity in Saccharomyces cerevisiae Expression Data: Trans-Regulation and Epistasis

Here, we describe the results from the first variance heterogeneity Genome Wide Association Study (VGWAS) on yeast expression data. Using this forward genetics approach, we show that the genetic regulation of gene-expression in the budding yeast, Saccharomyces cerevisiae, includes mechanisms that can lead to variance heterogeneity in the expression between genotypes. Additionally, we performed a mean effect association study (GWAS). Comparing the mean and variance heterogeneity analyses, we find that the mean expression level is under genetic regulation from a larger absolute number of loci but that a higher proportion of the variance controlling loci were trans-regulated. Both mean and variance regulating loci cluster in regulatory hotspots that affect a large number of phenotypes; a single variance-controlling locus, mapping close to DIA2, was found to be involved in more than 10% of the significant associations. It has been suggested in the literature that variance-heterogeneity between the genotypes might be due to genetic interactions. We therefore screened the multi-locus genotype-phenotype maps for several traits where multiple associations were found, for indications of epistasis. Several examples of two and three locus genetic interactions were found to involve variance-controlling loci, with reports from the literature corroborating the functional connections between the loci. By using a new analytical approach to re-analyze a powerful existing dataset, we are thus able to both provide novel insights to the genetic mechanisms involved in the regulation of gene-expression in budding yeast and experimentally validate epistasis as an important mechanism underlying genetic variance-heterogeneity between genotypes.