Sequencing of RNA provides the possibility to study an individual's transcriptome landscape and determine allelic expression ratios. Single-molecule protocols generate multi-kilobase reads longer than most transcripts, allowing sequencing of complete haplotype isoforms. This allows partitioning the reads into two parental haplotypes. While the read length of the single-molecule protocols is long, the relatively high error rate limits the ability to accurately detect the genetic variants and assemble them into the haplotype-specific isoforms. In this paper, we present Haplotype-specific Isoform reconstruction (HapIso), a method able to tolerate the relatively high error rate of the single-molecule platform and partition the isoform reads into the parental alleles. Phasing the reads according to the allele of origin allows our method to efficiently distinguish between the read errors and the true biological mutations. HapIso uses a k-means clustering algorithm aiming to group the reads into two meaningful clusters maximizing the similarity of the reads within the cluster and minimizing the similarity of the reads from different clusters. Each cluster corresponds to a parental haplotype. We used the family pedigree information to evaluate our approach. Experimental validation suggests that HapIso is able to tolerate the relatively high error rate and accurately partition the reads into the parental alleles of the isoform transcripts. We also applied HapIso to novel clinical single-molecule RNA-Seq data to estimate allele-specific expression of genes of interest. Our method was able to correct reads and determine Glu1883Lys point mutation of clinical significance validated by GeneDx HCM panel. Furthermore, our method is the first method able to reconstruct the haplotype-specific isoforms from long single-molecule reads.
- Genetic Expression
ASJC Scopus subject areas
- Medicine (miscellaneous)
- Biomedical Engineering
- Pharmaceutical Science
- Computer Science Applications
- Electrical and Electronic Engineering