Splicing and Junction Mapping

As a fundamental aspect of normal cell signaling and disease states, there is great interest in determining alternative splicing (AS) changes in physiologic, pathologic, and pharmacologic settings. High throughput...

Even for essential splice-site variants that are almost guaranteed to alter mRNA splicing, no current method can reliably predict whether exon-skipping, cryptic activation or multiple events will result, greatly complicating clinical interpretation of pathogenicity...

Long-read RNA sequencing (RNA-seq) holds great potential for characterizing transcriptome variation and full-length transcript isoforms, but the relatively high error rate of current long-read sequencing...

Alternative splicing is an important source of heterogeneity underlying gene expression between individual cells but remains an understudied area due to the paucity of computational tools to analyze...

Gene fusions are prevalent in a wide array of cancer types with different frequencies. Long-read transcriptome sequencing technologies, such as PacBio, Iso-Seq, and Nanopore direct RNA sequencing...

Studying isoform expression at the microscopic level has always been a challenging task. A classical example is kidney, where glomerular and tubulo-interstitial compartments carry out drastically different...

Visualisation of the transcriptome relative to a reference genome is fraught with sparsity. This is due to RNA sequencing (RNA-Seq) reads being predominantly mapped to exons that account for...

RNA editing leads to post-transcriptional variation in protein sequences and has important biological implications. Researchers from the St. Jude Children’s Research Hospital sought to elucidate the...

Alternative RNA isoforms are defined by promoter choice, alternative splicing, and polyA site selection. Although differential isoform expression is known to play a large regulatory role in eukaryotes, it has proved challenging to study with standard short-read RNA-seq because of ...

A simplistic understanding of the central dogma falls short in correlating the number of genes in the genome to the number of proteins in the proteome.