Recent studies have identified a large number of natural antisense transcripts that are transcribed from the genomic loci of well annotated genes, but from the opposite DNA strands. It is still unclear whether the majority of antisense transcripts are functional or merely transcriptional noise. We hypothesized that if antisense transcripts are related to certain physiological functions, they will exhibit variable levels of expression in different types of tissues and the pattern would tend to be evolutionarily conserved. By adapting commercial high-density oligonucleotide microarrays, we developed a cost-efficient approach that can monitor antisense expression across all exonic loci in mammalian genomes. Based on this approach, we will perform systematic profiling of antisense expression in various normal tissues in human, mouse and rat. Coupled with expression analysis of sense transcripts in the same samples, this will define a """"""""double stranded"""""""" expression profile at the exon level. The data will be used for comparative analyses to determine if there are conserved patterns of tissue-dependent antisense expression. We will compare the correlations of expression patterns in orthologous pairs of antisense transcripts with the correlation of the expression pattern of permutated pairs. We will also determine whether highly expressed pairs of orthologous antisense transcripts have smaller DNA sequence divergence and whether orthologous pairs of antisense transcripts with smaller DNA sequence divergence tend to have (1) higher correlation in their expression profiles across various tissues, (2) smaller changes in expression level between species, and (3) smaller change in breadth of expression, similar to what have been observed in protein-coding genes. This could either provide substantial evidence for a selective purifying pressure on antisense transcription or favor a """"""""neutral drift"""""""" model. The comprehensive datasets will also be used to identify novel antisense transcripts and tissue-specific antisense transcripts for further investigation. Such large-scale analysis of antisense expression will critically evaluate whether antisense transcription is a highly regulated process.

Public Health Relevance

The present proposal represents an attempt to obtain comprehensive data on the expression of a certain type of novel genes that could interfere with ordinary protein- coding genes. We will study their expression patterns in various normal tissues of human, mouse and rat so that we could gain insight into their potential physiological function.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
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Genomics, Computational Biology and Technology Study Section (GCAT)
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Bender, Michael T
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South Dakota State University
Biostatistics & Other Math Sci
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United States
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Ge, Steven Xijin (2017) Exploratory bioinformatics investigation reveals importance of ""junk"" DNA in early embryo development. BMC Genomics 18:200
Lai, Liming; Ge, Steven X (2014) Meta-analysis of gene expression signatures reveals hidden links among diverse biological processes in Arabidopsis. PLoS One 9:e108567
Hennessey, Jason; Ge, Steven (2013) A cross disciplinary study of link decay and the effectiveness of mitigation techniques. BMC Bioinformatics 14 Suppl 14:S5
Ling, Maurice Ht; Rabara, Roel C; Tripathi, Prateek et al. (2013) Extending MapMan Ontology to Tobacco for Visualization of Gene Expression. Dataset Pap Biol 2013:
Ling, Maurice H T; Ban, Yuguang; Wen, Hongxiu et al. (2013) Conserved expression of natural antisense transcripts in mammals. BMC Genomics 14:243
Lai, Liming; Liberzon, Arthur; Hennessey, Jason et al. (2012) AraPath: a knowledgebase for pathway analysis in Arabidopsis. Bioinformatics 28:2291-2
Wilson, Tyler J; Lai, Liming; Ban, Yuguang et al. (2012) Identification of metagenes and their interactions through large-scale analysis of Arabidopsis gene expression data. BMC Genomics 13:237
Graham, Kelly; Ge, Xijin; de Las Morenas, Antonio et al. (2011) Gene expression profiles of estrogen receptor-positive and estrogen receptor-negative breast cancers are detectable in histologically normal breast epithelium. Clin Cancer Res 17:236-46
Ge, Steven X (2011) Large-scale analysis of expression signatures reveals hidden links among diverse cellular processes. BMC Syst Biol 5:87
Wang, Chinling; Chou, Chung-Hsi; Tseng, Charles et al. (2011) Early gene response of human brain microvascular endothelial cells to Listeria monocytogenes infection. Can J Microbiol 57:441-6

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