Complex genetic interactions in a quantitative trait locus.
ABSTRACT: 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.
Project description:Identification of causal quantitative trait genes (QTGs) governing obesity is challenging. We previously revealed that the lymphocyte antigen 75 (Ly75) gene with an immune function is a putative QTG for Pbwg1.5, a quantitative trait locus (QTL) for resistance to obesity found from wild mice (Mus musculus castaneus). The objective of this study was to identify a true QTG for Pbwg1.5 by a combined approach of a quantitative complementation test, qualitative phenotypic analyses and causal analysis using segregating populations. In a four-way cross population among an Ly75 knockout strain, a subcongenic strain carrying Pbwg1.5 and their background strains, the quantitative complementation test showed genetic evidence that the Ly75 locus is identical to Pbwg1.5. Qualitative phenotypic analyses in two intercross populations between knockout and background strains and between subcongenic and background strains suggested that Ly75 may have pleiotropic effects on weights of white fat pads and organs. Causal analysis in the intercross population between knockout and background strains revealed that only variation in fat pad weight is caused by the genotypic difference via the difference in liver Ly75 expression. The results showed that Ly75 is a true Pbwg1.5 QTG for resistance to obesity. The finding provides a novel insight for obesity biology.
Project description:Trauma- and stress-related disorders are clinically heterogeneous and associated with substantial genetic risk. Understanding the biological origins of heterogeneity of key intermediate phenotypes such as cognition and emotion can provide novel mechanistic insights into disorder pathogenesis. Performing quantitative genetics in animal models is a tractable strategy for examining both the genetic basis of intermediate phenotypes and functional testing of candidate quantitative traits genes (QTGs). Here, existing and newly collected data were used for collaborative genome-wide mapping of cued fear acquisition and expression in 65 mouse strains from the BXD genetic reference panel. For fear acquisition, we identified a significant locus on chromosome (Chr) 10 and eight suggestive loci on Chr 2, 4, 5, 11, 13, and 15. For fear expression, we identified one significant and another highly suggestive locus on Chr 13, as well as four suggestive loci on Chr 10, 11, and X. Across these loci, 60 putative QTGs were identified. The quantitative trait locus on distal Chr 13 contained a single, highly promising gene at the location of the peak likelihood ratio statistic score. The gene, hyperpolarization-activated cyclic nucleotide-gated channel 1 (Hcn1), regulates neuronal excitability. Validation experiments using behavioral pharmacology revealed that functional Hcn channels in the basolateral amygdala are necessary for conditioned fear acquisition and expression. Hcn1, together with the other candidate QTGs, thus provide new targets for neurobiological and treatment studies of fear learning and trauma- and stress-related disorders.There is a knowledge gap in understanding the genetic contributions to behavioral heterogeneity in typical and atypical populations. Mouse genetic reference panels (GRPs) provide one approach for identifying genetic sources of variation. Here, we identified three loci for conditioned fear acquisition and expression in a mouse GRP. Each locus contained candidate quantitative trait genes (QTGs). One locus had a single QTG, Hcn1 (hyperpolarization-activated cyclic nucleotide-gated channel 1), which has been implicated in neuronal excitability and learning. This discovery was validated using behavioral pharmacology, revealing that Hcn channels in the basolateral amygdala are required for fear acquisition and expression. The study thus identifies novel candidate QTGs that may contribute to variation in emotional learning and highlight the utility of mouse GRPs for the identification of genes underlying complex traits.
Project description:Mutations are the root source of genetic variation and underlie the process of evolution. Although the rates at which mutations occur vary considerably between species, little is known about differences within species, or the genetic and molecular basis of these differences. Here, we leveraged the power of the yeast Saccharomyces cerevisiae as a model system to uncover natural genetic variants that underlie variation in mutation rate. We developed a high-throughput fluctuation assay and used it to quantify mutation rates in seven natural yeast isolates and in 1040 segregant progeny from a cross between BY, a laboratory strain, and RM, a wine strain. We observed that mutation rate varies among yeast strains and is heritable (H 2 = 0.49). We performed linkage mapping in the segregants and identified four quantitative trait loci underlying mutation rate variation in the cross. We fine-mapped two quantitative trait loci to the underlying causal genes, RAD5 and MKT1, that contribute to mutation rate variation. These genes also underlie sensitivity to the DNA-damaging agents 4NQO and MMS, suggesting a connection between spontaneous mutation rate and mutagen sensitivity.
Project description:Yeast sporulation efficiency is a quantitative trait and is known to vary among experimental populations and natural isolates. Some studies have uncovered the genetic basis of this variation and have identified the role of sporulation genes (IME1, RME1) and sporulation-associated genes (FKH2, PMS1, RAS2, RSF1, SWS2), as well as non-sporulation pathway genes (MKT1, TAO3) in maintaining this variation. However, these studies have been done mostly in experimental populations. Sporulation is a response to nutrient deprivation. Unlike laboratory strains, natural isolates have likely undergone multiple selections for quick adaptation to varying nutrient conditions. As a result, sporulation efficiency in natural isolates may have different genetic factors contributing to phenotypic variation. Using Saccharomyces cerevisiae strains in the genetically and environmentally diverse SGRP collection, we have identified genetic loci associated with sporulation efficiency variation in a set of sporulation and sporulation-associated genes. Using two independent methods for association mapping and correcting for population structure biases, our analysis identified two linked clusters containing 4 non-synonymous mutations in genes - HOS4, MCK1, SET3, and SPO74. Five regulatory polymorphisms in five genes such as MLS1 and CDC10 were also identified as putative candidates. Our results provide candidate genes contributing to phenotypic variation in the sporulation efficiency of natural isolates of yeast.
Project description:Two Saccharomyces cerevisiae mutants, end3 and end4, defective in the internalization step of endocytosis, have previously been isolated. The END3 gene was cloned by complementation of the temperature-sensitive growth defect caused by the end3 mutation and the END3 nucleotide sequence was determined. The END3 gene product is a 40-kDa protein that has a putative EF-hand Ca(2+)-binding site, a consensus sequence for the binding of phosphotidylinositol 4,5-bisphosphate (PIP2), and a C-terminal domain containing two homologous regions of 17-19 aa. The EF-hand consensus and the putative PIP2-binding sites are seemingly not required for End3 protein function. In contrast, different portions of the End3p N-terminal domain, and at least one of the two repeated regions in its C-terminus, are required for End3p activity. Disruption of the END3 gene yielded cells with the same phenotype as the original end3 mutant. An end3ts allele was obtained and this allowed us to demonstrate that End3p is specifically involved in the internalization step of endocytosis. In addition, End3p was shown to be required for proper organization of the actin cytoskeleton and for the correct distribution of chitin at the cell surface.
Project description:PURPOSE:The human CAV1-CAV2 locus has been associated with susceptibility to primary open-angle glaucoma in four studies of Caucasian, Chinese, and Pakistani populations, although not in several other studies of non-Korean populations. In this study with Korean participants, the CAV1-CAV2 locus was investigated for associations with susceptibility to primary open-angle glaucoma accompanied by elevated intraocular pressure (IOP), namely, high-tension glaucoma (HTG), as well as with IOP elevation, which is a strong risk factor for glaucoma. METHODS:Two single nucleotide polymorphisms (SNPs) were genotyped in 1,161 Korean participants including 229 patients with HTG and 932 healthy controls and statistically examined for association with HTG susceptibility and IOP. One SNP was rs4236601 G>A, which had been reported in the original study, and the other SNP was rs17588172 T>G, which was perfectly correlated (r2=1) with another reported SNP rs1052990. Expression quantitative trait loci (eQTL) analysis was performed using GENe Expression VARiation (Genevar) data. RESULTS:Both SNPs were associated with HTG susceptibility, but the rs4236601 association disappeared when adjusted for the rs17588172 genotype and not vice versa. The minor allele G of rs17588172 was associated significantly with 1.5-fold increased susceptibility to HTG (p=0.0069) and marginally with IOP elevation (p=0.043) versus the major allele T. This minor allele was also associated with decreased CAV1 and CAV2 mRNA in skin and adipose according to the Genevar eQTL analysis. CONCLUSIONS:The minor allele G of rs17588172 in the CAV1-CAV2 locus is associated with decreased expression of CAV1 and CAV2 in some tissues, marginally with IOP elevation, and consequently with increased susceptibility to HTG.
Project description:The Mkt1-Pbp1 complex promotes mating-type switching by regulating the translation of HO mRNA in Saccharomyces cerevisiae. Here, we performed in vivo immunoprecipitation assays and mass spectrometry analyses in the human fungal pathogen Cryptococcus neoformans to show that Pbp1, a poly(A)-binding protein-binding protein, interacts with Mkt1 containing a PIN like-domain. Association of Pbp1 with Mkt1 was confirmed by co-immunoprecipitation assays. Results of spot dilution growth assays showed that unlike pbp1 deletion mutant strains, mkt1 deletion mutant strains were not resistant to heat stress compared with wild-type. However, similar to the pbp1 deletion mutant strains, the mkt1 deletion mutants exhibited both, defective dikaryotic hyphal production and reduced pheromone gene (MF?1) expression during mating. In addition, deletion of mkt1 caused attenuated virulence in a murine intranasal inhalation model. Taken together, our findings reveal that Mkt1 plays a crucial role in sexual reproduction and virulence in C. neoformans.
Project description:Acute stress responsiveness is a quantitative trait that varies in severity from one individual to another; however, the genetic component underlying the individual variation is largely unknown. Fischer 344 (F344) and Wistar Kyoto (WKY) rat strains show large differences in behavioral responsiveness to acute stress, such as freezing behavior in response to footshock during the conditioning phase of contextual fear conditioning (CFC). Quantitative trait loci (QTL) have been identified for behavioral responsiveness to acute stress in the defensive burying (DB) and open field test (OFT) from a reciprocal F2 cross of F344 and WKY rat strains. These included a significant QTL on chromosome 6 (Stresp10). Here, we hypothesized that the Stresp10 region harbors genes with sequence variation(s) that contribute to differences in multiple behavioral response phenotypes between the F344 and WKY rat strains. To test this hypothesis, first we identified differentially expressed genes within the Stresp10 QTL in the hippocampus, amygdala, and frontal cortex of F344 and WKY male rats using genome-wide microarray analyses. Genes with both expression differences and non-synonymous sequence variations in their coding regions were considered candidate quantitative trait genes (QTGs). As a proof-of-concept, the F344.WKY-Stresp10 congenic strain was generated with the Stresp10 WKY donor region into the F344 recipient strain. This congenic strain showed behavioral phenotypes similar to those of WKYs. Expression patterns of Gpatch11 (G-patch domain containing 11), Cdkl4 (Cyclin dependent kinase like 4), and Drc1 (Dynein regulatory complex subunit 1) paralleled that of WKY in the F344.WKY-Stresp10 strain matching the behavioral profiles of WKY as opposed to F344 parental strains. We propose that these genes are candidate QTGs for behavioral responsiveness to acute stress.
Project description:We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.
Project description:High ethanol tolerance is an exquisite characteristic of the yeast Saccharomyces cerevisiae, which enables this microorganism to dominate in natural and industrial fermentations. Up to now, ethanol tolerance has only been analyzed in laboratory yeast strains with moderate ethanol tolerance. The genetic basis of the much higher ethanol tolerance in natural and industrial yeast strains is unknown. We have applied pooled-segregant whole-genome sequence analysis to map all quantitative trait loci (QTL) determining high ethanol tolerance. We crossed a highly ethanol-tolerant segregant of a Brazilian bioethanol production strain with a laboratory strain with moderate ethanol tolerance. Out of 5974 segregants, we pooled 136 segregants tolerant to at least 16% ethanol and 31 segregants tolerant to at least 17%. Scoring of SNPs using whole-genome sequence analysis of DNA from the two pools and parents revealed three major loci and additional minor loci. The latter were more pronounced or only present in the 17% pool compared to the 16% pool. In the locus with the strongest linkage, we identified three closely located genes affecting ethanol tolerance: MKT1, SWS2, and APJ1, with SWS2 being a negative allele located in between two positive alleles. SWS2 and APJ1 probably contained significant polymorphisms only outside the ORF, and lower expression of APJ1 may be linked to higher ethanol tolerance. This work has identified the first causative genes involved in high ethanol tolerance of yeast. It also reveals the strong potential of pooled-segregant sequence analysis using relatively small numbers of selected segregants for identifying QTL on a genome-wide scale.