Identification of transcribed protein coding sequence remnants within lincRNAs

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Long intergenic non-coding RNAs (lincRNAs) are crucial gene regulators but their evolutionary origins remain largely unknown.
• Poor cross-species conservation of lincRNAs complicates tracing their biogenesis.
• Pseudogenes have been proposed as potential precursors for lincRNA evolution.

Purpose of the Study:

• To develop a computational method for investigating the evolutionary origins of lincRNAs.
• To identify potential links between lincRNAs and protein-coding genes or transposons.
• To explore functional relationships between lincRNAs and their putative ancestral genes.

Main Methods:

• Developed a novel computational approach to detect protein-coding sequence remnants within lincRNA transcripts.
• Applied the method to human lincRNA genes to identify evolutionary relationships.
• Utilized sequence divergence visualization to trace lincRNA biogenesis.
• Analyzed expression correlations between lincRNAs and identified parental protein-coding genes using RNA-seq data.

Main Results:

• Identified 203 human lincRNA genes containing regions significantly similar to protein-coding sequences.
• Developed a visualization tool for tracing lincRNA evolutionary pathways relative to protein-coding genes.
• Found significant expression correlations between lincRNAs and their identified parental protein-coding genes.
• Provided evidence supporting the hypothesis that lincRNAs can arise from protein-coding genes or transposon insertions.

Conclusions:

• The developed computational methodology offers a novel way to study non-coding RNA evolution.
• The findings suggest protein-coding gene remnants contribute to lincRNA biogenesis.
• Expression correlations hint at new regulatory interactions between lincRNAs and protein-coding genes.
• This approach can uncover the evolutionary history and function of lincRNAs.