Researchers from the Technical University of Munich have made important progress in understanding how genetic information differs between alleles, the two versions of each gene we inherit from our parents. By using advanced long-read RNA sequencing, the team was able to see how these genetic variations influence which RNA transcripts are produced.

Traditional short-read sequencing methods have been excellent for studying gene expression, but they sometimes miss the full picture of complex genes with multiple transcript isoforms. In this work, the researchers used the PacBio Iso-Seq workflow combined with a phasing tool called WhatsHap to link long RNA reads to their specific alleles in hybrid mice. This allowed them to clearly identify which transcripts came from the maternal or paternal copy of a gene.

Integrating PacBio Iso-Seq with WhatsHap for allele assignment in a polymorphic F1 mouse hybrid

The raw reads obtained from long-read sequencing are filtered using the Iso-Seq pipeline. These filtered reads are called full-length non-concatemer reads and are aligned using PacBio’s minimap2 wrapper. Using known exonic SNPs between BL6 and CAST, long reads are assigned to the corresponding allele (maternal or paternal).

The researchers confirmed known patterns of genomic imprinting, where only one parental allele is active, while the other remains silent. They focused on the Gnas locus, a region known for its complex mix of coding and non-coding RNA isoforms, and successfully confirmed findings that had been suggested by earlier, less precise studies. Interestingly, they also found evidence of genes that escape X chromosome inactivation, meaning that some genes remain active on both the maternal and paternal X chromosomes.

Overall, this work demonstrates how long-read RNA sequencing can reveal the full diversity of transcripts at allele-specific loci, deepening our understanding of how genes are regulated and expressed.

Availability – Access to the allele-specific long-read resource is provided via the Integrative Genomics Viewer at: https://github.com/AndergassenLab/Allelic_Longreads.