Office of Technology Transfer – University of Michigan

The Landscape of Antisense Gene Expression in Human Cancers

Technology #6287

The human genome is widely transcribed, containing protein-coding and non-coding regions. Double-stranded DNA is transcribed to sense transcripts that are eventually translated to form proteins. Some DNA is transcribed into natural antisense RNA (NAT), which are endogenous transcripts that are complementary to sense transcripts. NATs are widespread in eukaryotes with complementary to sense transcripts of diverse biological function, and are thought to play a role in antisense-mediated gene regulation. Functional NATs have recently been identified as being involved in human disorders such as Alzheimer’s disease, Parkinson’s disease, and Fragile X syndrome. It is thought that 50-70% of sense transcripts have antisense partners, and an accurate and thorough characterization of NATs is needed to understand their role in homeostasis and disease progression. Future utilization of NATs to modify the expression of their cognate sense genes is a promising technology for disease therapeutics.

OncoNAT identifies cancer-related genes with significant antisense transcription

An extensive catalogue of NATs in cancer-related genes has been established from a cohort of 376 cancer patients covering 9 major tissue types. This landscape of antisense expression, termed OncoNAT, is based on strand-specific paired-end RNA sequencing (ssRNASeq) to provide accurate characterization of the exact boundaries of antisense transcripts and their expression. OncoNAT provides new candidate cis-NAT pairs that merit further investigation for potential therapeutic intervention.


  • Catalog of antisense expression across the human transcriptome that allows users to investigate sense/antisense regulation and its role in cancer.


  • Largest ssRNASeq study characterizing the landscape of antisense gene expression in cancer.
  • First characterization of NATs in a disease state.
  • ssRNASeq allows for accurate characterization of NAT expression level and location.