Abstract
Recent analyses show that transcriptome sequencing can be utilized as a diagnostic tool for rare Mendelian diseases. The third generation sequencing de novo detects long reads of thousands of base pairs, thus greatly expanding the isoform discovery and identification of novel long noncoding RNAs. In this study, we developed TGStools, a bioinformatics suite to facilitate routine tasks such as characterizing full-length transcripts, detecting shifted types of alternative splicing, and long noncoding RNAs (lncRNAs) identification in transcriptome analysis. It also prioritizes the transcripts with a visualization framework that automatically integrates rich annotation with known genomic features. TGStools is a Python package freely available at Github.
Highlights
Gene-panel and whole-exome sequencing revolutionized mutation detection of the rare Mendelian disease during the past decade
Compared to canonical second generation sequencing (i.e., RNA-seq), third generation sequencing (TGS) provides a great potential in isoform discovery and characterization of novel long noncoding RNAs
Several large cohort studies revealed that the impacts of splicing pattern, altered expression, as well as non-coding variants contribute to the identification of causal genes, especially for genetically unresolved cases of rare diseases [1,2,3]
Summary
Gene-panel and whole-exome sequencing revolutionized mutation detection of the rare Mendelian disease during the past decade. Accumulated analyses demonstrated that transcriptome analysis significantly improves diagnostic yield in genetically unresolved cases of rare diseases [1,2,3]. Compared to canonical second generation sequencing (i.e., RNA-seq), TGS provides a great potential in isoform discovery and characterization of novel long noncoding RNAs. Compared to canonical second generation sequencing (i.e., RNA-seq), TGS provides a great potential in isoform discovery and characterization of novel long noncoding RNAs Both are essential aspects of rare disease diagnostics [6,7]. The main drawback of TGS is its higher sequencing error rate, which may produce spurious transcripts [8]
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