Refining RNA-Seq Transcriptome Profiles with Transcript-Specific Minimal-Shared Regions

A minimal-sharing k-mer strategy identifies transcript-specific minimal-shared regions across heterologous genes, reducing RNA-seq mapping ambiguity and improving isoform quantification accuracy.

• Why it matters: Shared sequences among transcripts can cause ambiguous read assignment, leading to false positives and false negatives in transcript detection, especially when shared regions extend beyond homologous isoforms.
• What they did: The method partitions transcripts into unique k-mer sets and evaluates overlap across all transcripts to isolate minimal-shared regions for each isoform, tested in silico and on empirical sequencing data.
• The result: Across simulations and real datasets, it outperforms traditional probabilistic model-based quantification, improving isoform abundance estimates, gene ontology annotations, and resolving distinct isoforms in a Huntington’s disease mouse model.

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