The landscape of long noncoding RNAs in the human transcriptome

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Long noncoding RNAs (lncRNAs) are increasingly recognized for their roles in cellular functions and diseases, particularly cancer.
• Understanding the full spectrum of lncRNA expression is crucial for deciphering their biological significance.

Purpose of the Study:

• To comprehensively map the human transcriptome, focusing on genome-wide long noncoding RNA (lncRNA) expression.
• To identify novel lncRNAs and characterize their potential association with disease, especially cancer.
• To prioritize lineage- and cancer-specific lncRNA candidates for further investigation and biomarker development.

Main Methods:

• Curated and analyzed a large dataset of 7,256 RNA sequencing (RNA-seq) libraries from various human samples.
• Applied *ab initio* assembly to generate a consensus human transcriptome.
• Utilized non-parametric differential expression testing to identify lineage- or cancer-associated lncRNAs.

Main Results:

• Assembled a human transcriptome comprising 91,013 expressed genes.
• Identified 58,648 long noncoding RNAs (lncRNAs), with 79% being previously unannotated.
• Found that 1% of lncRNAs contained ultraconserved elements and 7% overlapped with disease-associated SNPs.
• Nominated 7,942 lineage- or cancer-associated lncRNA genes.

Conclusions:

• The characterized lncRNA landscape provides a valuable resource for understanding normal biological processes and cancer pathogenesis.
• A significant portion of the identified lncRNAs are novel, highlighting the vastness of the unannotated transcriptome.
• These findings may facilitate the development of novel biomarkers for cancer diagnosis and prognosis.