TIF-Seq2 disentangles overlapping isoforms in complex human transcriptomes.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Eukaryotic transcriptomes are highly complex, featuring numerous overlapping transcripts.
• This complexity hinders the identification of regulatory regions and can lead to misinterpretation of gene expression data.
• Existing methods struggle with accurately characterizing lowly expressed or overlapping transcripts.

Purpose of the Study:

• To develop and optimize a method for simultaneously sequencing the 5' and 3' ends of individual RNA molecules.
• To improve the understanding of complex, overlapping eukaryotic transcriptomes.
• To enhance gene annotation and identify novel transcript isoforms and regulatory elements.

Main Methods:

• Development of TIF-Seq2 (Transcript Isoform Sequencing 2), an optimized method for paired 5' and 3' end sequencing of RNA molecules at single-nucleotide resolution.
• Application of TIF-Seq2 to a human K562 cell line transcriptome.
• Validation using targeted long-read sequencing and standard RNA-Sequencing on chronic myeloid leukemia patient samples.

Main Results:

• Identification of thousands of previously unannotated transcript isoforms in the human K562 cell line.
• Accurate definition of boundaries for lowly expressed, unannotated, and read-through transcripts, including putatively fused genes.
• Characterization of transcription regulation and crosstalk among overlapping transcript units, showing upstream transcripts utilize downstream poly(A) sites.

Conclusions:

• TIF-Seq2 significantly improves the annotation of complex genomes by precisely defining RNA molecule ends.
• The method facilitates accurate assignment of promoters to genes and enables straightforward identification of transcriptionally fused genes.
• This approach enhances the study of transcription regulation in intricate transcriptome architectures.