Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14093800_1.fastq.gz | Fastqsanger.gz | |||
| SRR14093800_2.fastq.gz | Fastqsanger.gz | |||
| SRR14093900_1.fastq.gz | Fastqsanger.gz | |||
| SRR14093900_2.fastq.gz | Fastqsanger.gz | |||
| SRR14094000_1.fastq.gz | Fastqsanger.gz |
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Project description:Transcriptome-wide association studies (TWAS) to pinpoint enhanced expression of genes involved in DNA repair attributed to viral resistance of atxr5 atxr6.
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Project description:To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five new histotype-specific EOC risk regions (P-value < 5 x 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (P-value < 10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue data sets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (FDR < 0.05). Finally, by integrating genome-wide HiChIP interactome analysis with TWAS, variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8 and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by GWAS.
2024-03-27 | GSE255142 | GEO
Project description:TWAS uncovers lncRNAs controlling seed weight in soybean (PRJCA031929)
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Project description:Osteoporosis, characterized by low bone mineral density (BMD), is the most common complex disease affecting bone and constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 associations influencing BMD. It has been shown that perturbations to long non-coding RNAs (lncRNAs) influence BMD and the activities of bone cells; however, the extent to which lncRNAs are involved in the genetic regulation of BMD is unknown. Here, we combined the analysis of allelic imbalance (AI) in human acetabular bone fragments with a transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) colocalization analysis using data from the Genotype-Tissue Expression (GTEx) project to identify lncRNAs potentially responsible for GWAS associations. We identified 27 lncRNAs in bone that are located in proximity to a BMD GWAS association and harbor SNPs demonstrating AI. Using GTEx data we identified an additional 31 lncRNAs whose expression was associated (FDR correction<0.05) with BMD through TWAS and had a colocalizing eQTL (regional colocalization probability (RCP)>0.1). The 58 lncRNAs are located in 43 BMD associations. To further support a causal role for the identified lncRNAs, we show that 23 of the 58 lncRNAs are differentially expressed as a function of osteoblast differentiation. Our approach identifies lncRNAs that are potentially responsible for BMD GWAS associations and suggest that lncRNAs play a role in the genetics of osteoporosis.
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Project description:Osteoporosis, characterized by low bone mineral density (BMD), is the most common complex disease affecting bone and constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 associations influencing BMD. It has been shown that perturbations to long non-coding RNAs (lncRNAs) influence BMD and the activities of bone cells; however, the extent to which lncRNAs are involved in the genetic regulation of BMD is unknown. Here, we combined the analysis of allelic imbalance (AI) in human acetabular bone fragments with a transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) colocalization analysis using data from the Genotype-Tissue Expression (GTEx) project to identify lncRNAs potentially responsible for GWAS associations. We identified 27 lncRNAs in bone that are located in proximity to a BMD GWAS association and harbor SNPs demonstrating AI. Using GTEx data we identified an additional 31 lncRNAs whose expression was associated (FDR correction<0.05) with BMD through TWAS and had a colocalizing eQTL (regional colocalization probability (RCP)>0.1). The 58 lncRNAs are located in 43 BMD associations. To further support a causal role for the identified lncRNAs, we show that 23 of the 58 lncRNAs are differentially expressed as a function of osteoblast differentiation. Our approach identifies lncRNAs that are potentially responsible for BMD GWAS associations and suggest that lncRNAs play a role in the genetics of osteoporosis.
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Project description:Reliably generating rice varieties with low glycemic index (GI) is an important nutritional intervention given the high rates of Type II diabetes incidences in Asia where rice is staple diet. We integrated a genome-wide association study (GWAS) with a transcriptome-wide association study (TWAS) to determine the genetic basis of the GI in rice. GWAS utilized 305 re-sequenced diverse indica panel comprising ~2.4 million single nucleotide polymorphisms (SNPs) enriched in genic regions. A novel association signal was detected at a synonymous SNP in exon 2 of LOC_Os05g03600 for intermediate-to-high GI phenotypic variation. Another major hotspot region was predicted for contributing intermediate-to-high GI variation, involves 26 genes on chromosome 6 (GI6.1). These set of genes included GBSSI, two hydrolase genes, genes involved in signalling and chromatin modification. The TWAS and methylome sequencing data revealed cis-acting functionally relevant genetic variants with differential methylation patterns in the hot spot GI6.1 region, narrowing the target to 13 genes. Conversely, the promoter region of GBSSI and its alternative splicing allele (G allele of Wxa) explained the intermediate-to-high GI variation. A SNP (C>T) at exon-10 was also highlighted in the preceding analyses to influence final viscosity (FV), which is independent of amylose content/GI. The low GI line with GC haplotype confirmed soft texture, while other two low GI lines with GT haplotype were characterized as hard and cohesive. The low GI lines were further confirmed through clinical in vivo studies. Gene regulatory network analysis highlighted the role of the non‑starch polysaccharide pathway in lowering GI.
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Project description:Statin-induced myotoxicity (SIM) is one of the principal reasons for atorvastatin (AT) non-adherence and/or discontinuation, contributing to adverse cardiovascular outcomes. To date, the genetic mechanism of SIM is far from well-illustrated. Published data in vitro and in vivo indicated that atorvastatin lactone (ATL) is the key metabolite to induce myotoxicity. We therefore hypothesis that genetic variants increasing the formation of ATL can increase the risk to statin-induced myotoxicity. And a transcriptome-wide association study (TWAS) integrating genome wide variants and gene expression data will applied to identify expression quantitative trait loci (eQTL) associated with the formation of ATL and different bioinformatic tools will then be applied to reveal the potential causal impact of eQTLs on the formation of ATL.
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Project description:Camelina sativa is an important polyploid oilseed crop with multiple favorable agronomic traits. Capturing the leaf transcriptome of 48 accessions of C. sativa suggests allelic variation for gene expression levels and notably sub-genome dominance, both of which could provide opportunities for crop improvement. Flowering time (FT) is a crucial factor affecting the overall yield of crops. However, our understanding of the molecular mechanisms underlying FT regulation in C. sativa are still limited, partly due to its complex allohexaploid genome. In this study, weighted gene co-expression network analysis (WGCNA), expression quantitative trait loci (eQTL) analysis and transcriptome-wide association study (TWAS) were employed to explore the FT diversity among 48 C. sativa accessions and dissect the underlying molecular basis. Our results revealed a FT-related co-expressed gene module highly enriched with SOC1s and SOC1-like genes, and identified 10 significant FT-associated single nucleotide polymorphisms (SNPs), thus providing a molecular basis for future genetic improvements in C. sativa breeding
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