Assessing the complex architecture of polygenic traits in diverged yeast populations

Phenotypic variation arising from populations adapting to different niches has a complex underlying genetic architecture. A major challenge in modern biology is to identify the causative variants driving phenotypic variation. Recently, the baker's yeast, Saccharomyces cerevisiae has emerged as a powerful model for dissecting complex traits. However, past studies using a laboratory strain were unable to reveal the complete architecture of polygenic traits. Here, we present a linkage study using 576 recombinant strains obtained from crosses of isolates representative of the major lineages. The meiotic recombinational landscape appears largely conserved between populations; however, strain-specific hotspots were also detected. Quantitative measurements of growth in 23 distinct ecologically relevant environments show that our recombinant population recapitulates most of the standing phenotypic variation described in the species. Linkage analysis detected an average of 6.3 distinct QTLs for each condition tested in all crosses, explaining on average 39% of the phenotypic variation. The QTLs detected are not constrained to a small number of loci, and the majority are specific to a single cross-combination and to a specific environment. Moreover, crosses between strains of similar phenotypes generate greater variation in the offspring, suggesting the presence of many antagonistic alleles and epistatic interactions. We found that subtelomeric regions play a key role in defining individual quantitative variation, emphasizing the importance of the adaptive nature of these regions in natural populations. This set of recombinant strains is a powerful tool for investigating the complex architecture of polygenic traits.     

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.     

QTL Analysis of High Thermotolerance with Superior and Downgraded Parental Yeast Strains Reveals New Minor QTLs and Converges on Novel Causative Alleles Involved in RNA Processing

Revealing QTLs with a minor effect in complex traits remains difficult. Initial strategies had limited success because of interference by major QTLs and epistasis. New strategies focused on eliminating major QTLs in subsequent mapping experiments. Since genetic analysis of superior segregants from natural diploid strains usually also reveals QTLs linked to the inferior parent, we have extended this strategy for minor QTL identification by eliminating QTLs in both parent strains and repeating the QTL mapping with pooled-segregant whole-genome sequence analysis. We first mapped multiple QTLs responsible for high thermotolerance in a natural yeast strain, MUCL28177, compared to the laboratory strain, BY4742. Using single and bulk reciprocal hemizygosity analysis we identified MKT1 and PRP42 as causative genes in QTLs linked to the superior and inferior parent, respectively. We subsequently downgraded both parents by replacing their superior allele with the inferior allele of the other parent. QTL mapping using pooled-segregant whole-genome sequence analysis with the segregants from the cross of the downgraded parents, revealed several new QTLs. We validated the two most-strongly linked new QTLs by identifying NCS2 and SMD2 as causative genes linked to the superior downgraded parent and we found an allele-specific epistatic interaction between PRP42 and SMD2. Interestingly, the related function of PRP42 and SMD2 suggests an important role for RNA processing in high thermotolerance and underscores the relevance of analyzing minor QTLs. Our results show that identification of minor QTLs involved in complex traits can be successfully accomplished by crossing parent strains that have both been downgraded for a single QTL. This novel approach has the advantage of maintaining all relevant genetic diversity as well as enough phenotypic difference between the parent strains for the trait-of-interest and thus maximizes the chances of successfully identifying additional minor QTLs that are relevant for the phenotypic difference between the original parents.     

On the Prospects of Whole-Genome Association Mapping in Saccharomyces cerevisiae

Advances in sequencing technology have enabled whole-genome sequences to be obtained from multiple individuals within species, particularly in model organisms with compact genomes. For example, 36 genome sequences of Saccharomyces cerevisiae are now publicly available, and SNP data are available for even larger collections of strains. One potential use of these resources is mapping the genetic basis of phenotypic variation through genome-wide association (GWA) studies, with the benefit that associated variants can be studied experimentally with greater ease than in outbred populations such as humans. Here, we evaluate the prospects of GWA studies in S. cerevisiae strains through extensive simulations and a GWA study of mitochondrial copy number. We demonstrate that the complex and heterogeneous patterns of population structure present in yeast populations can lead to a high type I error rate in GWA studies of quantitative traits, and that methods typically used to control for population stratification do not provide adequate control of the type I error rate. Moreover, we show that while GWA studies of quantitative traits in S. cerevisiae may be difficult depending on the particular set of strains studied, association studies to map cis-acting quantitative trait loci (QTL) and Mendelian phenotypes are more feasible. We also discuss sampling strategies that could enable GWA studies in yeast and illustrate the utility of this approach in Saccharomyces paradoxus. Thus, our results provide important practical insights into the design and interpretation of GWA studies in yeast, and other model organisms that possess complex patterns of population structure.     

Genetic dissection of ethanol tolerance in the budding yeast Saccharomyces cerevisiae

Uncovering genetic control of variation in ethanol tolerance in natural populations of yeast Saccharomyces cerevisiae is essential for understanding the evolution of fermentation, the dominant lifestyle of the species, and for improving efficiency of selection for strains with high ethanol tolerance, a character of great economic value for the brewing and biofuel industries. To date, as many as 251 genes have been predicted to be involved in influencing this character. Candidacy of these genes was determined from a tested phenotypic effect following gene knockout, from an induced change in gene function under an ethanol stress condition, or by mutagenesis. This article represents the first genomics approach for dissecting genetic variation in ethanol tolerance between two yeast strains with a highly divergent trait phenotype. We developed a simple but reliable experimental protocol for scoring the phenotype and a set of STR/SNP markers evenly covering the whole genome. We created a mapping population comprising 319 segregants from crossing the parental strains. On the basis of the data sets, we find that the tolerance trait has a high heritability and that additive genetic variance dominates genetic variation of the trait. Segregation at five QTL detected has explained approximately 50% of phenotypic variation; in particular, the major QTL mapped on yeast chromosome 9 has accounted for a quarter of the phenotypic variation. We integrated the QTL analysis with the predicted candidacy of ethanol resistance genes and found that only a few of these candidates fall in the QTL regions.     

Mapping Quantitative Trait Loci Affecting Variation in Drosophila Triacylglycerol Storage

Objective: Recent genetic studies indicate that Drosophila melanogaster could be a powerful model to identify genes involved in mammalian adipocyte differentiation and fat storage. The objective of our study was to identify quantitative trait loci (QTLs) that contribute to variation in triacylglycerol (TAG) storage in two D. melanogaster laboratory strains. Research Methods and Procedures: We used two genetic mapping procedures to identify loci with main and epistatic effects on TAG storage. First, using 68 recombinant inbred lines derived from the unrelated Oregon R and Russian 2b strains, we mapped the location of QTLs affecting TAG storage using both composite interval mapping and Bayesian epistatic methods. Second, we used the quantitative deficiency mapping procedure to identify candidate genes affecting this trait within one of the QTLs identified on the second chromosome. For both mapping experiments, flies were cultured in standard conditions. TAG content of 4‐ to 5‐day‐old flies, adjusted for live body mass and total proteins, was used as the phenotypic measure. Results: Multiple QTLs associated with variation in TAG storage were identified by the genome‐wide recombination mapping method, and some of them were sex‐specific. The QTLs had main effects, but a male‐specific epistatic interaction between two QTLs was also found. Finally, two closely linked QTLs were detected by deficiency mapping at 57E1‐57E3 and 57E4‐57F1 on chromosome 2, the first of which causes female‐specific variation in TAG between the Oregon R and 2b strains. Discussion: Our results suggest that variation in TAG storage in D. melanogaster is controlled by different genetic mechanisms and different sets of QTLs in male and female flies.     

High-throughput sequence identification of gene coding variants within alcohol-related QTLs

Low initial response to alcohol has been shown to be among the best predictors of development of alcoholism. A similar phenotypic measure, difference in initial sensitivity to ethanol, has been used for the genetic selection of two mouse strains, the Inbred Long-Sleep (ILS) and Inbred Short-Sleep (ISS) mice, and for the subsequent identification of four quantitative trait loci (QTLs) for alcohol sensitivity. We now report the application of high throughput comparative gene sequencing in the search for genes underlying these four QTLs. To carry out this search, over 1.7 million bases of comparative DNA sequence were generated from 68 candidate genes within the QTL intervals, corresponding to a survey of over 36,000 amino acids. Eight central nervous system genes, located within these QTLs, were identified that contain a total of 36 changes in protein coding sequence. Some of these coding variants are likely to contribute to the phenotypic variation between ILS/ISS animals, including sensitivity to alcohol, providing specific new genetic targets potentially important to the neuronal actions of alcohol.     

From genotype to phenotype: buffering mechanisms and the storage of genetic information

DNA sequence variation is abundant in wild populations. While molecular biologists use genetically homogeneous strains of model organisms to avoid this variation, evolutionary biologists embrace genetic variation as the material of evolution since heritable differences in fitness drive evolutionary change. Yet, the relationship between the phenotypic variation affecting fitness and the genotypic variation producing it is complex. Genetic buffering mechanisms modify this relationship by concealing the effects of genetic and environmental variation on phenotype. Genetic buffering allows the build-up and storage of genetic variation in phenotypically normal populations. When buffering breaks down, thresholds governing the expression of previously silent variation are crossed. At these thresholds, phenotypic differences suddenly appear and are available for selection. Thus, buffering mechanisms modulate evolution and regulate a balance between evolutionary stasis and change. Recent work provides a glimpse of the molecular details governing some types of genetic buffering.     

Evolution of pleiotropy: epistatic interaction pattern supports a mechanistic model underlying variation in genotype-phenotype map

The genotype-phenotype (GP) map consists of developmental and physiological mechanisms mapping genetic onto phenotypic variation. It determines the distribution of heritable phenotypic variance on which selection can act. Comparative studies of morphology as well as of gene regulatory networks show that the GP map itself evolves, yet little is known about the actual evolutionary mechanisms involved. The study of such mechanisms requires exploring the variation in GP maps at the population level, which presently is easier to quantify by statistical genetic methods rather than by regulatory network structures. We focus on the evolution of pleiotropy, a major structural aspect of the GP map. Pleiotropic genes affect multiple traits and underlie genetic covariance between traits, often causing evolutionary constraints. Previous quantitative genetic studies have demonstrated population-level variation in pleiotropy in the form of loci, at which genotypes differ in the genetic covariation between traits. This variation can potentially fuel evolution of the GP map under selection and/or drift. Here, we propose a developmental mechanism underlying population genetic variation in covariance and test its predictions. Specifically, the mechanism predicts that the loci identified as responsible for genetic variation in pleiotropy are involved in trait-specific epistatic interactions. We test this prediction for loci affecting allometric relationships between traits in an advanced intercross between inbred mouse strains. The results consistently support the prediction. We further find a high degree of sign epistasis in these interactions, which we interpret as an indication of adaptive gene complexes within the diverged parental lines.     

solQTL: a tool for QTL analysis,visualization and linking to genomes at SGN database

Background  

A common approach to understanding the genetic basis of complex traits is through identification of associated quantitative trait loci (QTL). Fine mapping QTLs requires several generations of backcrosses and analysis of large populations, which is time-consuming and costly effort. Furthermore, as entire genomes are being sequenced and an increasing amount of genetic and expression data are being generated, a challenge remains: linking phenotypic variation to the underlying genomic variation. To identify candidate genes and understand the molecular basis underlying the phenotypic variation of traits, bioinformatic approaches are needed to exploit information such as genetic map, expression and whole genome sequence data of organisms in biological databases.     

Analysis of the Mesotelencephalic Dopamine System by Quantitative-Trait Locus Introgression

One of the significant factors that affect brain dopamine function is the activity of tyrosine hydroxylase (TH), the first and rate-limiting enzyme in catecholamine biosynthesis. For the analysis of the genetically determined role of dopamine function and TH in behavior and in the regulatory mechanisms of the mesotelencephalic dopamine system we devised a novel genetic strategy (Vadasz; Mouse Genome 88:16–18; 1990). We hypothesized that phenotypic introgression and recombinant fixation could ensure the transfer of Quantitative Trait Loci (QTL) from one strain onto the genetic background of another strain, and new, genetically very similar quasi-congenic strains could be created that would carry individual QTLs, or QTLs in various combinations. Here we summarize the construction of the first set of QTL Introgression strains, and present evidence that QTLs that are responsible for the continuous variation of mesencephalic tyrosine hydroxylase activity (TH/MES), have been transferred onto the C57BL/6By (B6) strain background from BALB/cJ (C) and CXBI (I) donor strains with high and low TH/MES, respectively. The QTL transfer was carried out in two directions by repeated backcross-intercross cycles with concomitant selection for the extreme high and low expressions of TH/MES in replicates, resulting in four QTL Introgression lines. Analysis of regional brain TH activities in the course of the QTL introgression indicated that (a) TH activity in B6.I lines showed quite limited heritability, (b) TH/MES was not highly correlated with striatal TH, and (c) the control of hypothalamic and olfactory tubercle TH activities was largely independent from that of TH/MES. Examination of the open-field (OF) behavior data demonstrated that TH activity did not correlate significantly with OF behavior. After 5 backcross-intercross cycles, TH/MES in each replicate line was still significantly different from that of the B6 background strain. A genomewide scanning of microsatellite markers in the QTL introgression lines demonstrated that about 96% of the markers were of background (B6) type. These results indicate the successful transfer of TH/MES QTLs. After the QTL transfer phase of the experiment altogether more than 100 new RQI strains were initiated in the QTL Introgression lines by strict brother × sister mating. After fixing the introgressed QTLs, ten of the inbred RQI strains were tested for TH/MES. The results showed that in one of the new RQI strains TH/MES was restored to a level that is characteristic to the C donor strain, while TH/MES values in some other strains were between those of the background and donor strains, confirming our hypothesis that phenotypic introgression and recombinant fixation can ensure a virtually complete transfer of QTLs. We conclude from this study that complex, continuously distributed neural traits can successfully be subjected to QTL introgression, and the results raise the possibility that the RQI method can be efficiently applied for gene mapping of complex neural and behavioral traits even if their phenotypic expression is sensitive to confounding developmental and environmental variations, genetic interactions, and genotype-environment interactions.     

Playing Dr Jekyll and Mr Hyde: combined mechanisms of phase variation in bacteria

Phase variation is the adaptive process by which bacteria undergo frequent and reversible phenotypic changes resulting from genetic alterations in specific loci of their genomes. This process is crucial for the survival of pathogens and commensals in hostile and ever-changing host environments. Despite important differences in the molecular mechanisms that mediate and regulate phase variation, related strategies have evolved to generate high levels of genetic diversity through complex and combinatorial reshuffling of genetic information. Recent studies, supported by the emergence of global genomic approaches, have revealed that bacterial pathogens often use a combination of different mechanisms to vary the expression of a variety of biological functions, providing new insights into bacterial adaptation and virulence mechanisms. Recent advances in the understanding of the molecular mechanisms of phase variation are reviewed, and differences in these mechanisms outlined.     

Genetic analysis for drought resistance of rice at reproductive stage in field with different types of soil

Drought resistance of rice is a complex trait and is mainly determined by mechanisms of drought avoidance and drought tolerance. The present study was conducted to characterize the genetic basis of drought resistance at reproductive stage in field by analyzing the QTLs for drought response index (DRI, normalized by potential yield and flowering time), relative yield, relative spikelet fertility, and four traits of plant water status and their relationships with root traits using a recombinant inbred population derived from a cross between an indica rice and upland rice. A total of 39 QTLs for these traits were detected with individual QTL explained 5.1–32.1% of phenotypic variation. Only two QTLs for plant water status were commonly detected in two environments, suggesting different mechanisms might exist in two types of soil conditions. DRI has no correlation with potential yield and flowering time under control, suggesting that it can be used as a good drought resistance index in field conditions. The co-location of QTLs for canopy temperature and delaying in flowering time suggested a usefulness of these two traits as indexes in drought resistance screening. Correlation and QTL congruence between root traits and putative drought tolerance traits revealed that drought avoidance (via thick and deep root traits) was the main genetic basis of drought resistance in sandy soil condition, while drought tolerance may play more role in the genetic basis of drought resistance in paddy soil condition. Therefore, both drought mechanisms and soil textures must be considered in the improvement of drought resistance at reproductive stage in rice.     

Data integration uncovers the metabolic bases of phenotypic variation in yeast

The relationship between different levels of integration is a key feature for understanding the genotype-phenotype map. Here, we describe a novel method of integrated data analysis that incorporates protein abundance data into constraint-based modeling to elucidate the biological mechanisms underlying phenotypic variation. Specifically, we studied yeast genetic diversity at three levels of phenotypic complexity in a population of yeast obtained by pairwise crosses of eleven strains belonging to two species, Saccharomyces cerevisiae and S. uvarum. The data included protein abundances, integrated traits (life-history/fermentation) and computational estimates of metabolic fluxes. Results highlighted that the negative correlation between production traits such as population carrying capacity (K) and traits associated with growth and fermentation rates (J_max) is explained by a differential usage of energy production pathways: a high K was associated with high TCA fluxes, while a high J_max was associated with high glycolytic fluxes. Enrichment analysis of protein sets confirmed our results.This powerful approach allowed us to identify the molecular and metabolic bases of integrated trait variation, and therefore has a broad applicability domain.     

Heritability, correlations and in silico mapping of locomotor behavior and neurochemistry in inbred strains of mice

The midbrain dopamine system mediates normal and pathologic behaviors related to motor activity, attention, motivation/reward and cognition. These are complex, quantitative traits whose variation among individuals is modulated by genetic, epigenetic and environmental factors. Conventional genetic methods have identified several genes important to this system, but the majority of factors contributing to the variation remain unknown. To understand these genetic and environmental factors, we initiated a study measuring 21 behavioral and neurochemical traits in 15 common inbred mouse strains. We report trait data, heritabilities and genetic and non-genetic correlations between pheno-types. In general, the behavioral traits were more heritable than neurochemical traits, and both genetic and non-genetic correlations within these trait sets were high. Surprisingly, there were few significant correlations between the behavioral and the individual neurochemical traits. However, striatal serotonin and one measure of dopamine turnover (DOPAC/DA) were highly correlated with most behavioral measures. The variable accounting for the most variation in behavior was mouse strain and not a specific neurochemical measure, suggesting that additional genetic factors remain to be determined to account for these behavioral differences. We also report the prospective use of the in silico method of quantitative trait loci (QTL) analysis and demonstrate difficulties in the use of this method, which failed to detect significant QTLs for the majority of these traits. These data serve as a framework for further studies of correlations between different midbrain dopamine traits and as a guide for experimental cross designs to identify QTLs and genes that contribute to these traits.     

Genetic Influences on Translation in Yeast

Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosome profiling to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes. Allele specific measurements in the diploid hybrid between the two strains revealed roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, most effects on translation were of small magnitude, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. There was a tendency for translation to cause larger footprint differences than expected given the respective mRNA differences. This is in contrast to translational differences between yeast species that have been reported to more often oppose than reinforce mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains and also found several instances where erroneous reference gene annotations lead to apparent nonsense mutations that in fact reside outside of the translated gene body. Overall, genetic influences on translation subtly modulate gene expression differences, and translation does not create strong discrepancies between genetic influences on mRNA and protein levels.     

Ecological and evolutionary genomics of Saccharomyces cerevisiae

Saccharomyces cerevisiae, the budding yeast, is the most thoroughly studied eukaryote at the cellular, molecular, and genetic levels. Yet, until recently, we knew very little about its ecology or population and evolutionary genetics. In recent years, it has been recognized that S. cerevisiae occupies numerous habitats and that populations harbour important genetic variation. There is therefore an increasing interest in understanding the evolutionary forces acting on the yeast genome. Several researchers have used the tools of functional genomics to study natural isolates of this unicellular fungus. Here, we review some of these studies, and show not only that budding yeast is a prime model system to address fundamental molecular and cellular biology questions, but also that it is becoming a powerful model species for ecological and evolutionary genomics studies as well.     

Identification of QTLs related to cocoa resistance to three species of<Emphasis Type="Italic"> Phytophthora</Emphasis>

This study aimed to compare the genetic control of cacao resistance to three species of Phytophthora: Phytophthora palmivora, Phytophthora megakarya and Phytophthora capsici. The study was conducted on 151 hybrid progenies created in Côte d'Ivoire and grown in a green-house in Montpellier. Phytophthora resistance was screened by leaf-test inoculation with two different strains per species. Selection of the best individuals for resistance to P. palmivora at a 10% selection rate, would lead to a genetic progress of 47% in the disease evaluation for this species and a genetic progress of 42% and 21% for the two other species. A genetic map with a total length of 682 cM was built with 213 markers, 190 AFLPs and 23 microsatellites. QTLs were identified using composite interval mapping. QTLs were found located in six genomic regions. One of these was detected with five strains belonging to the three Phytophthora species. Two other regions were detected with two or three strains of two different species. Three additional QTLs were detected for only one species of Phytophthora. Each QTL explained between 8 to 12% of the phenotypic variation. For each strain, between 11.5% to 27.5% of the total phenotypic variation could be explained by the QTLs identified. The identification of multiple QTLs involved in resistance to Phytophthora offers the possibility to improve durability of resistance in cocoa by a possible cumulation of many different resistance genes located in different chromosome regions using marker-aided selection.Communicated by H.F. Linskens