Chapter title |
GENCODE Pseudogenes
|
---|---|
Chapter number | 10 |
Book title |
Pseudogenes
|
Published in |
Methods in molecular biology, April 2014
|
DOI | 10.1007/978-1-4939-0835-6_10 |
Pubmed ID | |
Book ISBNs |
978-1-4939-0834-9, 978-1-4939-0835-6
|
Authors |
Adam Frankish, Jennifer Harrow, Frankish A, Harrow J, Adam Frankish Ph.D. |
Editors |
Laura Poliseno |
Abstract |
Historically pseudogenes were believed to represent nonfunctional genomic fossils; however, there is emerging evidence that many of them could be biologically active. This possibility has ignited interest in pseudogene loci and made the need for their high-quality annotation more pressing as an accurate knowledge of all pseudogenes in the human reference genome sequence facilitates confident functional analysis. GENCODE have undertaken the first genome-wide pseudogene assignment for protein-coding genes combining both large-scale manual annotation and computational pseudogene prediction pipelines. Multiple computational predictions provide an unbiased set of hints for manual annotators to investigate, both during first-pass annotation and as part of QC to identify any potential missing pseudogene loci. Where a pseudogene is identified, the extent of its homology to the parent locus is fully investigated by a manual annotator; a pseudogene model is built and assigned to one of eight pseudogene biotypes depending on the mechanism of creation and on the presence of locus-specific transcriptional or proteomic data. The high-quality, information-rich set of pseudogenes created has been integrated with ENCODE functional genomics data, specifically expression level, transcription factor and RNA polymerase II binding, and chromatin marks. In this way we have been able to identify some pseudogenes that possess conventional characteristics of functionality as well as others with interesting patterns of partial activity, which might suggest that putatively inactive loci could be gaining a novel function, for example as long noncoding RNAs. The activity data associated with every pseudogene is stored in the psiDR resource. |
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