GeneiASE: Detection of condition-dependent and static allele-specific expression from RNA-seq data without haplotype information

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.

Allele Specific Expression in Human – Genomic Makeup and Phenotypic Implications

“…Specifically, in different cell types, the relevant allele can be selected to support a desired phenotype (Schmiedel et al 2018). At the individual level, ASE expression interacts with other genetic or environmental factors that may alter the allele expression choice thus affecting the outcome for complex phenotype and diseases (Buil et al 2015;Edsgärd et al 2016;Moyerbrailean et al 2016) A special case of evolution concerns the MHC and other immune related loci (Table 1).…”

RPASE: Individual‐based allele‐specific expression detection without prior knowledge of haplotype phase

“…RPASE uses physical phasing in the model, which is another advantage over methods which ignore phasing (Edsgärd et al., ; Romanel, Lago, Prandi, Sboner, & Demichelis, ) or rely on statistical phasing (Wang et al., ) or pseudo‐phasing (Mayba et al., ). Ignoring phasing can produce incorrect test results when multiple SNPs within a transcript are not properly integrated.…”

“…RPASE uses physical phasing in the model, which is another advantage over methods which ignore phasing (Edsg€ ard et al, 2016;Romanel, Lago, Prandi, Sboner, & Demichelis, 2015) or rely on statistical phasing (Wang et al, 2017) or pseudo-phasing (Mayba et al, 2014 Menelaou & Marchini, 2013) infers phase from linkage disequilibrium using preferably hundreds of individual samples. It however fails to reliably infer rare haplotypes and has no capability to infer individual haplotypes as may arise from recent recombination events (He et al, 2010;Snyder, Adey, Kitzman, & Shendure, 2015).…”

“…Extra-Poisson and extra-binomial distributions allow for overdispersion (Edsg€ ard et al, 2016;Leon-Novelo, McIntyre, Fear, & Graze, 2014;Mayba et al, 2014;Wang, Uebbing, & Ellegren, 2017) and have been widely applied in ASE studies in many species, including humans (McCoy, Wakefield, & Akey, 2017), Drosophila (Graze et al, 2012), birds (Davidson & Balakrishnan, 2016) and plants (Steige et al, 2015). The majority of these studies have focused on F1 hybrids and/or on model organisms where sequence data from multiple replicates are used to estimate overdispersion.…”

Allele specific expression and gene regulation explain transgressive thermal tolerance in non-native hybrids of the endangered California tiger salamander (Ambystoma californiense)

“…We used the software package geneiASE to identify SNPs and genes that exhibited significant allele specific expression (Edsgärd et al, 2016). This software uses a beta-binomial distribution to compare the counts of reference and alternate SNPs at heterozygous loci against the null hypothesis that alternate allele counts (altCounts) = reference allele counts (refCounts).…”