In silico discovery of human natural antisense transcripts

Area of Science:

• Genomics
• Transcriptomics
• Bioinformatics

Background:

• Previous research on natural antisense transcripts (NATs) primarily focused on cis-NATs.
• A comprehensive in silico analysis of human transcripts is needed to broaden the understanding of NATs.

Purpose of the Study:

• To conduct a thorough in silico analysis of human transcripts to identify and characterize natural antisense transcripts (NATs).
• To expand the knowledge of NATs, particularly focusing on trans-NATs and their potential regulatory functions.

Main Methods:

• In silico analysis of human RefSeq RNA sequences.
• Classification of NATs based on pairing regions.
• Analysis of alternative splicing and UTR involvement.
• Microarray data analysis for expression patterns.

Main Results:

• Identified 568 human NATs (hNATs), with 403 reported for the first time, including at least 157 novel trans-NATs.
• Classified hNATs into 6 types, with ~87% involving 5' or 3' UTRs, suggesting a regulatory role for UTRs.
• Found a significant relationship between alternative splicing and antisense-directed regulation, with 77.4% of splice variant-related NAT pairs affected by alternative splicing.
• Observed significant inverse expression patterns in two hNAT pairs post-insulin injection using microarray data.

Conclusions:

• Human NATs exhibit more extensive and complex functions than previously recognized.
• NATs, alongside endogenous microRNAs, form a distinct class of transcripts involved in intricate gene regulatory networks.