Illuminating the dark side of the human transcriptome with long read transcript sequencing.

ABSTRACT:

Background

The human transcriptome annotation is regarded as one of the most complete of any eukaryotic species. However, limitations in sequencing technologies have biased the annotation toward multi-exonic protein coding genes. Accurate high-throughput long read transcript sequencing can now provide additional evidence for rare transcripts and genes such as mono-exonic and non-coding genes that were previously either undetectable or impossible to differentiate from sequencing noise.

Results

We developed the Transcriptome Annotation by Modular Algorithms (TAMA) software to leverage the power of long read transcript sequencing and address the issues with current data processing pipelines. TAMA achieved high sensitivity and precision for gene and transcript model predictions

SUBMITTER: Kuo RI 

PROVIDER: S-EPMC7596999 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature