The Antisense Transcriptome and the Human Brain

被引:0
作者
James D. Mills
Bei Jun Chen
Uwe Ueberham
Thomas Arendt
Michael Janitz
机构
[1] University of New South Wales,School of Biotechnology and Biomolecular Sciences
[2] University of Leipzig,Paul
来源
Journal of Molecular Neuroscience | 2016年 / 58卷
关键词
Human brain; Antisense transcripts; Transcriptome; RNA-Seq;
D O I
暂无
中图分类号
学科分类号
摘要
The transcriptome of a cell is made up of a varied array of RNA species, including protein-coding RNAs, long non-coding RNAs, short non-coding RNAs, and circular RNAs. The cellular transcriptome is dynamic and can change depending on environmental factors, disease state and cellular context. The human brain has perhaps the most diverse transcriptome profile that is enriched for many species of RNA, including antisense transcripts. Antisense transcripts are produced when both the plus and minus strand of the DNA helix are transcribed at a particular locus. This results in an RNA transcript that has a partial or complete overlap with an intronic or exonic region of the sense transcript. While antisense transcription is known to occur at some level in most organisms, this review focuses specifically on antisense transcription in the brain and how regulation of genes by antisense transcripts can contribute to functional aspects of the healthy and diseased brain. First, we discuss different techniques that can be used in the identification and quantification of antisense transcripts. This is followed by examples of antisense transcription and modes of regulatory function that have been identified in the brain.
引用
收藏
页码:1 / 15
页数:14
相关论文
共 1108 条
[1]  
Abou-Sleiman PM(2006)Expanding insights of mitochondrial dysfunction in Parkinson’s disease Nat Rev Neurosci 7 207-219
[2]  
Muqit MM(2007)Mouse and rat BDNF gene structure and expression revisited J Neurosci Res 85 525-535
[3]  
Wood NW(1999)Mutational spectra of PTEN/MMAC1 gene: a tumor suppressor with lipid phosphatase activity J Natl Cancer Inst 91 1922-1932
[4]  
Aid T(2010)Differential expression analysis for sequence count data Genome Biol 11 R106-169
[5]  
Kazantseva A(2015)HTSeq—a Python framework to work with high-throughput sequencing data Bioinformatics 31 166-403
[6]  
Piirsoo M(1993)The relationship between trinucleotide (CAG) repeat length and clinical features of Huntington’s disease Nat Genet 4 398-11
[7]  
Palm K(1993)Pre- and postmortem influences on brain RNA J Neurochem 61 1-769
[8]  
Timmusk T(2008)A natural antisense transcript regulates Zeb2/Sip1 gene expression during Snail1-induced epithelial-mesenchymal transition Genes Dev 22 756-626
[9]  
Ali IU(2008)A cryptic unstable transcript mediates transcriptional trans-silencing of the Ty1 retrotransposon in S. cerevisiae Genes Dev 22 615-131
[10]  
Schriml LM(2004)Brain-derived neurotrophic factor Growth Factors 22 123-47