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Transposable element-driven transcript diversification and its relevance to genetic disorders.

Gene | 2015

The human genome project and subsequent gene annotation projects have shown that the human genome contains 22,000-25,000 functional genes. Therefore, it is believed that the diversity of protein repertoire is achieved by the alternative splicing (AS) mechanism. Transposable elements (TEs) are mobile in nature and can therefore alter their position in the genome. The insertion of TEs into a new gene region can result in AS of a particular transcript through various mechanisms, including intron retention, and alternative donor or acceptor splice sites. TE-derived AS is thought to have played a part in primate evolution and in hominid radiation. However, TE-derived AS or genetic instability may sometimes result in genetic disorders. For the past two decades, numerous studies have been performed on TEs and their role in genomes. Accumulating evidence shows that the term 'junk DNA', previously used for TEs is a misnomer. Recent research has indicated that TEs may have clinical potential. However, to explore the feasibility of using TEs in clinical practice, additional studies are required. This review summarizes the available literature on TE-derived AS, alternative promoter, and alternative polyadenylation. The review covers the effects of TEs on coding genes and their clinical implications, and provides our perspectives and directions for future research.

Pubmed ID: 25617522 RIS Download

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Gene Expression Omnibus (GEO) (tool)

RRID:SCR_005012

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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