Abstract
Allele-specific expression (ASE) is the imbalance in transcription between maternal and paternal alleles at a locus and can be probed in single individuals using massively parallel DNA sequencing technology. Assessing ASE within a single sample provides a static picture of the ASE, but the magnitude of ASE for a given transcript may vary between different biological conditions in an individual. Such condition-dependent ASE could indicate a genetic variation with a functional role in the phenotypic difference. We investigated ASE through RNA-sequencing of primary white blood cells from eight human individuals before and after the controlled induction of an inflammatory response, and detected condition-dependent and static ASE at 211 and 13021 variants, respectively. We developed a method, GeneiASE, to detect genes exhibiting static or condition-dependent ASE in single individuals. GeneiASE performed consistently over a range of read depths and ASE effect sizes, and did not require phasing of variants to estimate haplotypes. We observed condition-dependent ASE related to the inflammatory response in 19 genes, and static ASE in 1389 genes. Allele-specific expression was confirmed by validation of variants through real-time quantitative RT-PCR, with RNA-seq and RT-PCR ASE effect-size correlations r = 0.67 and r = 0.94 for static and condition-dependent ASE, respectively.
Highlights
Gj or UTR, affecting transcript processing[11]
We investigated the impact of varying read depth on the false negative rate by using sustained effect size across individuals instead of demanding significant individual condition-dependent Allele-specific expression (ASE) (icd-ASE)
The method we proposed for assessing ASE in genes, GeneiASE, used unphased data and as such would be possible to apply on all existing RNA sequencing (RNA-seq) data sets without the need for additional experiments or haplotype estimation, instantly generating additional transcriptional details to published results
Summary
Gj or UTR, affecting transcript processing[11]. Corroborating this, a study of 60 CEU HapMap individuals showed that genes exhibiting ASE are enriched for eQTLs12, and the ENCODE project reported correlations between allele-specific epigenetic marks and allele-specific transcription[13]. Most ASE studies have been performed on cancer cell lines[6,9,12,20] with only a few exceptions[21,22] These ASE prevalence estimates pertain to the ASE that is detected between the two variants of a heterozygous allele in a single sample under a certain unchanging condition (controlled or observed). RNA-seq based identification of differential ASE in tumour samples and cancer cell lines was presented in a recent paper, which provided an ASE analysis tool[22]. The authors investigated 32 samples (7 matched tumour/ normal tissues and 18 cancer cell lines) and reported higher rates of static ASE in tumour samples (9–26%) as compared to normal tissue samples (0.5–2%), and that a variable fraction of genes with static ASE exhibited differential ASE (3–32% for normal tissues). Phasing (haplotype estimation) enables the use of certain tools to analyze ASE6,15, but requires a substantially increased sequencing and analysis effort
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