Year: 2020
Type: article
Abstract: A challenge of next generation sequencing is read contamination. We use Genotype-Tissue Expression (GTEx) datasets and technical metadata along with RNA-seq datasets from other studies to understand factors that contribute to contamination. Here we report, of 48 analyzed tissues in GTEx, 26 have variant co-expression clusters of four highly expressed and pancreas-enriched genes (PRSS1, PNLIP, CLPS, and/or CELA3A). Fourteen additional highly expressed genes from other tissues also indicate contamination. Sample contamination is strongly associated with a sample being sequenced on the same day as a tissue that natively expresses those genes. Discrepant SNPs across four contaminating genes validate the contamination. Low-level contamination affects ~40% of samples and leads to numerous eQTL assignments in inappropriate tissues among these 18 genes. This type of contamination occurs widely, impacting bulk and single cell (scRNA-seq) data set analysis. In conclusion, highly expressed, tissue-enriched genes basally contaminate GTEx and other datasets impacting analyses.
Source: Nature Communications
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,380
Funders: American Heart Association, University of Rochester, Georgia Clinical and Translational Science Alliance, National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute, National Institute of General Medical Sciences, National Institute of Environmental Health Sciences, National Center for Advancing Translational Sciences
Awards: G1165598027, G276595759, G2802014078, G4411448324, xMD-miRNA-Seq estimates cell-specific miRNA expression, G5258278944, G5633899073, G625544220, Profiling Intercalated Disc Components in Arrhythmogenic Cardiomyopathy, G9000001345, G9000041231, G9000049607, G9000134567, G9000208853, Environmental Agents as Modulators of Disease Processes
OpenAlex ID: W3018638530