Detection of single nucleotide variations in expressed exons of the human genome using RNA-Seq

Whole genome re-sequencing is still a costly method to detect genetic mutations that lead to altered forms of proteins and may be associated with disease development. Since the majority of disease-related single nucleotide variations (SNVs) are found in protein-coding regions, we propose to identify SNVs in expressed exons of the human genome using the recently developed RNA-Seq technique. We identify 12,176 and 10,621 SNVs, respectively, in Jurkat T cells and CD4+ T cells from a healthy donor. Interestingly, our data show that one copy of the TAL-1 protooncogene has a point mutation in 3' UTR and only the mutant allele is expressed in Jurkat cells. We provide a comprehensive dataset for further understanding the cancer biology of Jurkat cells. Our results indicate that this is a cost-effective and efficient strategy to systematically identify SNVs in the expressed regions of the human genome. Overall design: RNA-Seq experiments for two samples: CD4+ T cells from a healthy donor and Jurkat T cells. There are 8 lanes of data for each sample.