Micro-dissection and integration of long and short reads for identifying isoforms at microscopic structure-level

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 physiological functions and thus presumably their isoform expression also differs. University of Michigan researchers have developed an experimental and computational pipeline for identifying isoforms at microscopic structure-level. The researchers microdissected glomerular and tubulo-interstitial compartments from healthy human kidney tissues from two cohorts. The two compartments were separately sequenced with the PacBio RS II platform. These transcripts were then validated using transcripts of the same samples by the traditional Illumina RNA-Seq protocol, distinct Illumina RNA-Seq short reads from European Renal cDNA Bank (ERCB) samples, and annotated GENCODE transcript list, thus identifying novel transcripts. The researchers identified 14,739 and 14,259 annotated transcripts, and 17,268 and 13,118 potentially novel transcripts in the glomerular and tubulo-interstitial compartments, respectively. Of note, relying solely on either short or long reads would have resulted in many erroneous identifications. They identified distinct pathways involved in glomerular and tubulo-interstitial compartments at the isoform level, creating an important experimental and computational resource for the kidney research community.

Overall study design

The features of every multi-exon Consensus Full-Length transcripts (CFL’s) found in PacBio reads were validated through Illumina short reads from two different RNA-seq datasets. Whole CFLs were then validated at every splice junction before comparison to GENCODE annotation.

Li H, Eksi R, Yi D, Godfrey B, Mathew LR, O’Connor CL, et al. (2022) Micro-dissection and integration of long and short reads to create a robust catalog of kidney compartment-specific isoforms. PLoS Comput Biol 18(4): e1010040. [article]

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