Computational analysis reveals 43% antisense transcription in 1182 transcripts in mouse muscle

Abstract

It is increasingly evident that there is a widespread antisense transcription in the human and other eukaryotic genomes. However, the concept of general antisense expression is rarely investigated. We retrieved and correlated the expression of sense and antisense sequences of 1182 mouse transcripts to assess the prevalence of antisense transcription. We contrasted 20 Affymetrix MGU74A version 1 mouse genome chips to 12 MGU74A version 2 chips. For these 1182 transcripts, the version 1 chips contained the antisense sequences of the transcripts presented on the version 2 chips. The original data was taken from the GEO database. As the Affymetrix data is semi quantitative, the relative levels of antisense partners were analysed. We detected antisense transcription with an overall magnitude of 43% relative to sense transcription in the investigated transcripts. The average MGU74A version 1 expression is shifted towards smaller expression values (MGU74A version 1: 525.1; version 2: 1219.1; t-test: p < 0.001). A direct correlation between sense and antisense expression values could not be observed. Genes with high inverse expression values may be correlated to the investigated condition: genes where sense/control and control/antisense ratios were above two may be included in the pathogenetic pathways associated with dystrophin deficiency. The ratio of sense to antisense transcription varied between different chromosomes. We conclude that antisense transcription is a common phenomenon in the mouse genome and may have indirect regulatory functions.

• Antisense expression
• complementary transcripts
• mouse genome
• dystrophin deficiency

Acknowledgements

We thank Stephen Borovsky MD for his help in the preparation of the manuscript. This work was supported by the National Office for Research and Technology, Hungary.

Notes

* http://www.R-project.org; R Development Core Team (2004). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

^† http://www.ncbi.nlm.nih.gov/projects/geo/; Expression values for the corresponding complementary datasets were retrieved from the Gene Expression Omnibus web depository.

^‡ http://www.bioconductor.org/; Source of metadata packages for the Affymetrix MGU74A version 1 and version 2 chips and home of the Matchprobes package for matching sequence probes on arrays.

^¶ http://www.affymetrix.com/support/technical/byproduct.affx?product = mgu74; The murine genome U74v2 set supporting materials, including alignment, annotation and sequence data.