Testis expression in Mus musculus domesticus WSB/EiJ x Mus musculus musculus PWD/PhJ F2 hybrids
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE54089 | GEO | 2014/05/01
SECONDARY ACCESSION(S): PRJNA235166
REPOSITORIES: GEO
Similar Datasets
Project description:To characterize the genetic basis of hybrid male sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven M-bM-^@M-^Xhotspots,M-bM-^@M-^Y seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL - but not cis eQTL - were substantially lower when mapping was restricted to a M-bM-^@M-^XfertileM-bM-^@M-^Y subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. Gene expression was measured in whole testis in males aged 70(M-BM-15) days. Samples include 294 WSB/EiJ x PWD/PhJ F2s, 11 PWD/PhJ x WSB/EiJ F2s, 8 WSB/EiJ, 8 PWD/PhJ, 6 PWD/PhJ x WSB/EiJ F1s and 4 WSB/EiJ x PWD/PhJ F1s.
2014-05-01 | E-GEOD-54089 | biostudies-arrayexpress
Project description:We collected whole genome testis expression data from hybrid zone mice. We integrated GWAS mapping of testis expression traits and low testis weight to gain insight into the genetic basis of hybrid male sterility. Gene expression was measured in whole testis from males aged 62-86 days. Samples include 190 first generation lab-bred male offspring of wild-caught mice from the Mus musculus musculus - M. m. domesticus hybrid zone.
2014-12-04 | E-GEOD-61417 | biostudies-arrayexpress
Project description:We collected whole genome testis expression data from hybrid zone mice. We integrated GWAS mapping of testis expression traits and low testis weight to gain insight into the genetic basis of hybrid male sterility.
2014-12-04 | GSE61417 | GEO
Project description:We used microarrays and a previously established linkage map to localize the genetic determinants of brain gene expression for a backcross family of lake whitefish species pairs (Coregonus sp.). Our goals were to elucidate the genomic distribution and sex-specificity of brain expression QTL (eQTL) and to determine the extent to which genes controlling transcriptional variation may underlie adaptive divergence in the recently evolved dwarf (limnetic) and normal (benthic) whitefish. We observed a sex-bias in transcriptional genetic architecture, with more eQTL observed in males, as well as divergence in genome location of eQTL between sexes. Hotspots of nonrandom aggregations of up to 32 eQTL in one location were observed. We identified candidate genes for species pair divergence involved with energetic metabolism, protein synthesis, and neural development based on co-localization of eQTL for these genes with eight previously identified adaptive phenotypic QTL and four previously identified outlier loci from a genome scan in natural populations. 88% of eQTL-phenotypic QTL co-localization involved growth rate and condition factor QTL, two traits central to adaptive divergence between whitefish species pairs. Hotspots co-localized with phenotypic QTL in several cases, revealing possible locations where master regulatory genes, such as a zinc finger protein in one case, control gene expression directly related to adaptive phenotypic divergence. We observed little evidence of co-localization of brain eQTL with behavioral QTL, which provides insight on the genes identified by behavioral QTL studies. These results extend to the transcriptome level previous work illustrating that selection has shaped recent parallel divergence between dwarf and normal lake whitefish species pairs and that metabolic, more than morphological differences appear to play a key role in this divergence. Keywords: eQTL mapping, gene expression, linkage mapping, adaptive radiation, Coregonus, microarrays The objective of this study was to elucidate the genomic distribution and sex-specificity of brain eQTL in dwarf and normal lake whitefish. Dissected brain tissue (250-350 mg) was sampled for 55 individuals from a hybrid x dwarf backcross mapping family. We used a loop design (YANG and SPEED 2002; CHURCHILL 2002) to maximize the number of sampled meioses. Each of 55 samples was technically replicated on two distinct slides, while performing dye swapping (Cy3 and Alexa) to estimate the dye intensity variation bias. After correcting for local background, raw intensity values were both log2 transformed and normalized using the regional LOWESS method implemented in the R/MANOVA software (KERR et al. 2000). We used a previously generated linkage map based on the same backcross individuals for which gene expression was measured. eQTL mapping was performed with QTL Cartographer.
2008-09-01 | E-GEOD-12068 | biostudies-arrayexpress
Project description:In this study, early infection by F. graminearum was characterized in a doubled-haploid population derived from the cross of the moderately FHB resistant wheat genotypes Wuhan 1 and Nyubai. Three significant QTL were identified: 1AL was associated with reduced deoxynivalenol levels, and 4BS and 5A were associated with reduced F. graminearum levels at 2 days after infection. The early resistance alleles for 1AL and 4BS were inherited from Wuhan 1, and those for the 5A QTL were inherited from Nyubai. The LOD support interval for the 5A QTL was in the same region as FHB5, a QTL previously associated with field resistance to FHB. Cis and trans eQTL were identified using RNA sequencing data from infected head samples. In total, 240 cis eQTL and 17,401 trans eQTL were identified within LOD support intervals for the three QTL. Hotspots for trans eQTL were identified within LOD support intervals for the 1AL and 4BS QTL. Differential gene expression analysis revealed twenty genes with cis eQTL within one of the 3 QTL support intervals, that had higher expression associated with FHB early resistance, and 17 genes with higher expression associated with FHB early susceptibility. Among those, genes with a cis eQTL peak coinciding with QTL peaks were enriched in functions related to signaling and protein-protein interaction, including NBS-LRR, BAH, LRR/F-box and TPR domain-containing proteins. Several genes located within one of the three QTL support intervals also had a trans eQTL with a peak at the same position as QTL peaks on other chromosomes, suggesting interactions between the QTL.
2019-11-13 | GSE123548 | GEO
Project description:The control of gene expression in Toxoplasma is not well understood. As we and others have shown, this organism does contain bipartite promoters that are sufficient to induce gene expression. This information can be used in downstream experiments to identify proteins that bind to experimentally confirmed cis elements. One of these methods, yeast one-hybrid is currently being employed to identify proteins which bind to the BAG1 and B-NTPase promoter elements. Another powerful method that can be used to identify genomic regions containing controllers of gene expression takes advantage of genetic linkage mapping provided by genetic crosses, called expression quantitative trait locus (eQTL) mapping. In the eQTL approach, one uses gene expression as quantitative traits, or phenotypes, in QTL mapping. QTL mapping is a proven method in Toxoplasma that has recently identified apicomplexan-specific virulence factors in both the Type II X III and Type I X III crosses (Saeij et al., 2006, Taylor et al., 2006, Su et al., 2002). With the recent design of the Affymetrix Toxoplasma GeneChip one can gather gene expression profiles for all predicted genes in the Toxoplasma genome in a rapid and reproducible way. Combining the power of Affymetrix gene expression technology and QTL mapping can lead to the identification of genes with differential expression in the parents and progeny of a genetic cross and then to the identification of the genomic regions that contain mechanisms that have an effect on expression. The first description of combining global gene expression profiles with QTL mapping was published by Brem et al. using the model organism Saccharomyces cerevisiae (Brem et al., 2002). Since that time, eQTL projects have been described for several other organisms including human, mouse, rat, maize, Arabidopsis, barley, eucalyptus, and wheat (Gibson & Weir, 2005). There are two mapping location types expected when using gene expression profiles as phenotypes. Mapping of gene expression profiles can lead to linkage of a locus (region) containing the gene being mapped, thus cis to the gene. Although the boundaries of the locus will contain many genes, it is presumed that for most cis QTLs sequence polymorphisms in the regulatory region(s) of the gene being mapped are the cause of the observed expression differences. The other mapping location type expected is one where the expression profile maps to a locus not containing the gene being mapped, or trans to the gene (Ronald et al., 2005). The most interesting trans loci are those that have multiple genes mapping to the same locus in trans, or to a trans hotspot. These hotspots likely contain factor(s) that regulate many genes, such as transcription factors or factors involved in upstream signal transduction pathways that can eventually lead to a number of transcriptional changes (Yvert et al., 2003). Here we describe the results of an eQTL project using the gene expression profiles for the parents and 34 informative progeny of the type I-GT1-Fudr X type III-CTGara cross for both the tachyzoite and bradyzoite stages. This is the first time global gene expression profiles have been used to determine linkage to regions presumed to be controllers of transcription using the Affymetrix Toxoplasma GeneChip. The dominant genomic associations found were those mapping cis and there were several regions, or hotspots, where multiple genes map in trans. In addition, we observed an unexpected finding suggesting there are several duplication events in the parasites of the Type I X III cross which may also have consequences on gene expression levels. The ToxoGeneChip microarray (http://ancillary.toxodb.org/docs/Array-Tutorial.html) was used to measure both tachyzoite and bradyzoite mRNA expression in the parents and progeny of the I X III cross. For each of the two developmental expression sets, genome-wide eQTL scans were run for each gene specific probeset on the microarray. The parents of the cross are CTGara and GT1-Fudr. The rest comprise the informative progeny.
2012-01-11 | E-GEOD-26558 | biostudies-arrayexpress
Project description:The control of gene expression in Toxoplasma is not well understood. As we and others have shown, this organism does contain bipartite promoters that are sufficient to induce gene expression. This information can be used in downstream experiments to identify proteins that bind to experimentally confirmed cis elements. One of these methods, yeast one-hybrid is currently being employed to identify proteins which bind to the BAG1 and B-NTPase promoter elements. Another powerful method that can be used to identify genomic regions containing controllers of gene expression takes advantage of genetic linkage mapping provided by genetic crosses, called expression quantitative trait locus (eQTL) mapping. In the eQTL approach, one uses gene expression as quantitative traits, or phenotypes, in QTL mapping. QTL mapping is a proven method in Toxoplasma that has recently identified apicomplexan-specific virulence factors in both the Type II X III and Type I X III crosses (Saeij et al., 2006, Taylor et al., 2006, Su et al., 2002). With the recent design of the Affymetrix Toxoplasma GeneChip one can gather gene expression profiles for all predicted genes in the Toxoplasma genome in a rapid and reproducible way. Combining the power of Affymetrix gene expression technology and QTL mapping can lead to the identification of genes with differential expression in the parents and progeny of a genetic cross and then to the identification of the genomic regions that contain mechanisms that have an effect on expression. The first description of combining global gene expression profiles with QTL mapping was published by Brem et al. using the model organism Saccharomyces cerevisiae (Brem et al., 2002). Since that time, eQTL projects have been described for several other organisms including human, mouse, rat, maize, Arabidopsis, barley, eucalyptus, and wheat (Gibson & Weir, 2005). There are two mapping location types expected when using gene expression profiles as phenotypes. Mapping of gene expression profiles can lead to linkage of a locus (region) containing the gene being mapped, thus cis to the gene. Although the boundaries of the locus will contain many genes, it is presumed that for most cis QTLs sequence polymorphisms in the regulatory region(s) of the gene being mapped are the cause of the observed expression differences. The other mapping location type expected is one where the expression profile maps to a locus not containing the gene being mapped, or trans to the gene (Ronald et al., 2005). The most interesting trans loci are those that have multiple genes mapping to the same locus in trans, or to a trans hotspot. These hotspots likely contain factor(s) that regulate many genes, such as transcription factors or factors involved in upstream signal transduction pathways that can eventually lead to a number of transcriptional changes (Yvert et al., 2003). Here we describe the results of an eQTL project using the gene expression profiles for the parents and 34 informative progeny of the type I-GT1-Fudr X type III-CTGara cross for both the tachyzoite and bradyzoite stages. This is the first time global gene expression profiles have been used to determine linkage to regions presumed to be controllers of transcription using the Affymetrix Toxoplasma GeneChip. The dominant genomic associations found were those mapping cis and there were several regions, or hotspots, where multiple genes map in trans. In addition, we observed an unexpected finding suggesting there are several duplication events in the parasites of the Type I X III cross which may also have consequences on gene expression levels.
2012-01-11 | GSE26558 | GEO
Project description:We used microarrays and a previously established linkage map to localize the genetic determinants of brain gene expression for a backcross family of lake whitefish species pairs (Coregonus sp.). Our goals were to elucidate the genomic distribution and sex-specificity of brain expression QTL (eQTL) and to determine the extent to which genes controlling transcriptional variation may underlie adaptive divergence in the recently evolved dwarf (limnetic) and normal (benthic) whitefish. We observed a sex-bias in transcriptional genetic architecture, with more eQTL observed in males, as well as divergence in genome location of eQTL between sexes. Hotspots of nonrandom aggregations of up to 32 eQTL in one location were observed. We identified candidate genes for species pair divergence involved with energetic metabolism, protein synthesis, and neural development based on co-localization of eQTL for these genes with eight previously identified adaptive phenotypic QTL and four previously identified outlier loci from a genome scan in natural populations. 88% of eQTL-phenotypic QTL co-localization involved growth rate and condition factor QTL, two traits central to adaptive divergence between whitefish species pairs. Hotspots co-localized with phenotypic QTL in several cases, revealing possible locations where master regulatory genes, such as a zinc finger protein in one case, control gene expression directly related to adaptive phenotypic divergence. We observed little evidence of co-localization of brain eQTL with behavioral QTL, which provides insight on the genes identified by behavioral QTL studies. These results extend to the transcriptome level previous work illustrating that selection has shaped recent parallel divergence between dwarf and normal lake whitefish species pairs and that metabolic, more than morphological differences appear to play a key role in this divergence. Keywords: eQTL mapping, gene expression, linkage mapping, adaptive radiation, Coregonus, microarrays
2008-09-01 | GSE12068 | GEO
Project description:The aim of this study was to identify eQTL in Brassica rapa grown under altered soil phosphorus (P) supply, to understand better the genetic architecture of P-use efficiency (PUE) in plants. Recombinant inbred lines (RILs) of the BraIRRI mapping population were grown at adequate and growth-limiting soil P. Variation in leaf gene expression was quantified using an Agilent Brassica 95k oligonucleotide array. Informative gene expression markers (GEMs) were used to map eQTL and PUE-related QTL. Gene expression was highly dependent on soil P supply. However, the altered expression of many genes, including known P-responsive genes, was highly heritable. Interval mapping using P supply as a covariate revealed 18,876 eQTL, representing 15,912 unique probes. Notable trans-eQTL hotspots occurred on chromosomes A06 and A01; these were enriched with protein modification and phosphorus metabolism-related (A06), as well as chloroplast and photosynthesis-related (A01) transcripts. Regulatory loci and genes associated with P-use efficiency identified through eQTL analysis are potential targets for further characterisation and may have potential for crop improvement. Availability of the annotated B. rapa genome sequence will facilitate their study, including the separation of cis- and trans- effects.
2011-06-29 | GSE27052 | GEO
Project description:SILAC based protein correlation profiling using size exclusion of protein complexes derived from Mus musculus tissues (Heart, Liver, Lung, Kidney, Skeletal Muscle, Thymus)
2021-05-05 | PXD022309 | Pride