A vast resource of allelic expression data spanning human tissues

Abstract

Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

Cell type–specific genetic regulation of gene expression across human tissues

“…Because few external replication datasets exist, we used allele-specific expression (ASE) data of eQTL heterozygotes (29,30) to correlate individuallevel quantifications of the eQTL effect size [measured as allelic fold-change (aFC)] with individual-level cell type enrichments. If the eQTL is active in the cell type of interest, we expect to see low aFC in individuals with low cell type abundance and higher aFC in individuals with high cell type abundance ( fig.…”

Transcriptome variation in human tissues revealed by long-read sequencing

“…Comparing the long-read ASE events to the ones reported for short-read GTEx v8 data 35 , we observed moderate concordance when looking at the p-values in short-read data using the long-read significant ASE events (π1 = 0.23) and vice-versa (π1 = 0.41) ( Suppl. Figure 11A ).…”

“…To perform allele-specific expression (ASE) and allele-specific transcript structure (ASTS) analysis, we developed a new software package, LORALS (Long-Read Allelic analysis). In addition to adopting mappability and genotyping error filters previously developed for short-read data 35 , we introduced flags addressing the higher error rate of long-read data ( Suppl. Figure 8 ).…”

Genomic Context and Mechanisms of the ACVR1 Mutation in Fibrodysplasia Ossificans Progressiva

“…This can be done through the analysis of RNA-seq reads that include heterozygous SNPs, allowing one to assign the read to an allele. Allelic imbalance occurs when the two alleles of a gene are differentially expressed and the magnitude of the imbalance can be quantified by allelic fold change (aFC) [ 40 ]. Although it is too simplistic to attribute an expression imbalance to a single variant, rather than to a cumulative effect of more variants on each allele, we cannot exclude that one or some of the variants within a haplotype have a stronger effect on ASE.…”