High-Throughput Assessment of Gene Structure Changes in Resequencing Data, Using ACE

The accurate interpretation of genetic variants is critical for characterizing genotype-phenotype associations. Because the effects of genetic variants depend on their local genomic context, accurate genome annotations are essential. Furthermore, as some variants have the potential to disrupt or alter gene structure, variant interpretation efforts stand to gain from the use of individualized annotations that account for differences in gene structure between individuals or strains. We describe a suite of haplotype-aware software tools for predicting functional changes in gene structure that may result from sequence variants. ACE (“Assessing Changes to Exons”) converts phased genotype calls to a collection of explicit haplotype sequences, maps transcript annotations onto them, detects gene-structure changes and their possible repercussions including several classes of possible loss of function. Using publicly-available RNA-seq data, we demonstrate that novel transcripts predicted by ACE are commonly supported by spliced RNA-seq. We also show that ACE predictions confirm earlier results regarding the quantitative effects of nonsense-mediated decay, and that predicted loss-of-function events are highly concordant with patterns of intolerance to mutations across the human population. ACE can be readily applied to diverse species including animals and plants, making it a broadly useful tool for use in eukaryotic population-based resequencing projects, particularly for assessing the joint impact of variants at a locus. Future enhancements currently under development include a novel probabilistic model to predict the effects of genetic variants that alter splicing enhancers or that create pseudo-exons, and quantitative prediction of changes in stoichiometric isoform ratios.