Transcriptome sequencing of a large human family identifies the impact of rare non-coding variants
Transcriptomics Dataset
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| Accession | GSE56961 |
| Title | Transcriptome sequencing of a large human family identifies the impact of rare non-coding variants |
| Description | We have combined high-quality genome sequencing and RNA-sequencing data within a 17-individual, three generation family. Using these data, we have contrasted cis-acting expression, allele-specific expression and splicing quantitative trait loci (collectively termed eQTLs) within the family to eQTLs discovered within a cell-type and ethnicity-matched population sample. We identified that eQTL that exhibit larger effects in the family compared to the population are enriched for rare regulatory and splicing variants and were more likely to influence essential genes. In addition, we identify several large effect-size eQTLs within the family for genes involved in complex disease. Through analysis of eQTLs in a large family we also report the utility of non-coding genome annotation to predicting the effect of rare non-coding variants. We find that a combination of distance to the transcription start site, evolutionary constraint and epigenetic annotation is considerably more informative for predicting the consequence of rare non-coding variants than for common variants. In summary, through transcriptome analyses within a large family we are able to identify the contribution of rare non-coding variants to expression phenotypes and further demonstrate the predictive potential of diverse non-coding genome annotation for interpretation of the impact of rare non-coding variants. |
| Landing Page | https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE56961 |
| Repository | Gene Expression Omnibus |
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