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Large-scale expression analysis of natural antisense transcripts

Large-scale expression analysis of natural antisense transcripts
天然反义转录本的大规模表达分析
批准号:
8054875
负责人:
Xijin Ge
金额:
$21.69万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-04-01 至 2013-03-31

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英文摘要
DESCRIPTION (provided by applicant): 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.
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