Disrupted gene networks in subfertile hybrid mice
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ABSTRACT:
PROVIDER: PRJNA563924 | ENA |
REPOSITORIES: ENA
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Project description:The Dobzhansky-Muller model provides a widely accepted mechanism for the evolution of reproductive isolation: incompatible substitutions disrupt interactions between genes. To date, few candidate incompatibility genes have been identified, leaving the genes driving speciation mostly uncharacterized. The importance of interactions in the Dobzhansky-Muller model suggests that gene coexpression networks provide a powerful framework to understand disrupted pathways associated with postzygotic isolation. Here, we perform Weighted Gene Coexpression Network Analysis (WGCNA) to infer gene interactions in hybrids of two recently diverged European house mouse subspecies, Mus mus domesticus and M. m. musculus, which commonly show hybrid male sterility or subfertility. We use genome-wide testis expression data from 467 hybrid mice from two mapping populations: F2s from a laboratory cross between wild-derived pure subspecies strains and offspring of natural hybrids captured in the Central Europe hybrid zone. This large data set enabled us to build a robust consensus network using hybrid males with fertile phenotypes. We identify several expression modules, or groups of coexpressed genes, that are disrupted in subfertile hybrids, including modules functionally enriched for spermatogenesis, cilium and sperm flagellum organization, chromosome organization and DNA repair, and including genes expressed in spermatogonia, spermatocytes and spermatids. Our network-based approach enabled us to hone in on specific hub genes likely to be influencing module-wide gene expression and hence potentially driving Dobzhansky-Muller incompatibilities. A total of 67 (24.4%) of these genes lie in sterility loci identified previously in these mapping populations, and represent promising candidate barrier genes and targets for future functional analysis.
2019-09-05 | GSE136886 | GEO
Project description:The Dobzhansky-Muller (DM) model provides a widely accepted mechanism for the evolution of reproductive isolation: incompatible substitutions disrupt interactions between genes. To date, few candidate incompatibility genes have been identified, leaving the genes driving speciation mostly uncharacterized. The importance of interactions in the DM model suggests that gene coexpression networks provide a powerful framework to understand disrupted pathways associated with postzygotic isolation. Here, we perform weighted gene coexpression network analysis to infer gene interactions in hybrids of two recently diverged European house mouse subspecies, Mus mus domesticus and M. m. musculus, which commonly show hybrid male sterility or subfertility. We use genome-wide testis expression data from 467 hybrid mice from two mapping populations: F2s from a laboratory cross between wild-derived pure subspecies strains and offspring of natural hybrids captured in the Central Europe hybrid zone. This large data set enabled us to build a robust consensus network using hybrid males with fertile phenotypes. We identify several expression modules, or groups of coexpressed genes, that are disrupted in subfertile hybrids, including modules functionally enriched for spermatogenesis, cilium and sperm flagellum organization, chromosome organization, and DNA repair, and including genes expressed in spermatogonia, spermatocytes, and spermatids. Our network-based approach enabled us to hone in on specific hub genes likely to be influencing module-wide gene expression and hence potentially driving large-effect DM incompatibilities. A disproportionate number of hub genes lie within sterility loci identified previously in the hybrid zone mapping population and represent promising candidate barrier genes and targets for future functional analysis.
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Project description:In order to clarify the cause of reproductive failure, we conducted global endometrial gene expression analysis in fertile and subfertile cows. Hierarchical cluster analysis with the expression levels of mitochondrial DNA encoded genes was divided these cows into two clusters. One cluster was composed of fertile cows, the other cluster contained subfertile cows, and the expressions of mitochondrial DNA encoded genes in subfertile cows were higher than those in fertile cows
2018-01-11 | GSE107741 | GEO
Project description:The miRNA profiles were measured using small-RNA sequencing in beef heifers sampled at weaning that was retrospectively classified as fertile or subfertile following the breeding protocol. To accomplish this, the miRNA profiles were generated from the blood samples (10 mL) collected from crossbred heifers (Angus-Simmental) at the time of weaning (~238 days after birth). Peripheral white blood cells (PWBC) were extracted from the blood samples and stored at -80°C until further processing. During the breeding season, all the heifers followed the same breeding protocol, estrus synchronization, and fixed-time artificial insemination (AI). Fourteen days following the fixed-time AI, the non-pregnant heifers were exposed to fertile bulls for 60 days. Depending on the presence or absence of conceptus at 75 days following AI, heifers were classified as fertile for those who were pregnant through artificial insemination, pregnant to natural breeding (P-NB), or subfertile for those who were not pregnant. Heifers from fertile (n = 7) and subfertile (n = 7) groups were considered for the study. Total RNA was extracted from the PWBC of 14 samples and was subjected to small RNA library preparation and sequencing. After quality control, adapter trimming, and alignment, mature miRNAs were used for differential expression analysis. The read counts were transformed to counts per million (CPM), and raw counts with CPM < 1 in 50% of the samples were filtered out. The filtered raw counts were analyzed using DESeq2 v 1.26.0 to identify differentially expressed miRNAs (DEMIs). The DEMIs identified with a p-value < 0.05 and absolute (log2 fold change) > 0.5 were considered significant. With the subfertile heifers as the reference group, we identified 16 DEMIs between fertile and subfertile groups. To determine the genes targeting the DEMIs, we downloaded the target genes for each DEMI and retained only those genes expressed in the PWBCs. For the miRNA-gene correlation, we used the partial correlation and information theory (PCIT) approach to identify the significant gene-miRNA correlated pairs. The significant genes correlated with the miRNAs identified pathways including MAPK, ErbB, HIF-1, FoxO, p53, mTOR, T-cell receptor, insulin and GnRH signaling, apoptosis, and pathways regulating pluripotency of stem cells in the fertile group while cell cycle, p53 signaling pathway and apoptosis pathways in the subfertile group.
2023-07-17 | GSE225854 | GEO
Project description:Obesity-disrupted H3K4me3 in hematopoietic stem progentior cells in mice
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Project description:Endometrial gene expression in fertile and subfertile cows
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Project description:43 biopsies were obtained from subfertile/infertile patients undergoing testicular sperm extraction (TESE) as part of their treatment. Labelled cDNAs were compared to a reference normal testis RNA (Ambion).
2007-03-15 | E-MEXP-1019 | 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:To uncover genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. We mapped 27 behavioral quantitative trait loci with a false discovery rate of 5%. We also identified two gene co-expression networks correlated with context-dependent immobility. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. We surveyed the architecture of brain transcript regulation and showed preservation of gene co-expression modules in hippocampus and striatum while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance associated strongly with fear phenotypes. Total mRNA islolated from hippocampus and striatum of strains from Hybrid Mouse Diversity Panel and gene expression quantified using Illumina MouseRef-8 v2.0 microarrays. Submission includes gene expression data from 100 strains of HMDP for hippocampus (n=1 for each strain) and 98 strains of HMDP for striatum (n=1 for each strain).
2011-03-15 | E-GEOD-26500 | biostudies-arrayexpress