De novo derivation of proteomes from transcriptomes for transcript and protein identification.

De novo derivation of proteomes from transcriptomes for transcript and protein identification.
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DOI:
10.1038/nmeth.2227
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发表时间:
2012-12
期刊:
影响因子:
48
通讯作者:
Matthews, David A.
Matthews, David A.
中科院分区:
生物学1区
文献类型:
--
作者:
Evans, Vanessa C.;Barker, Gary;Heesom, Kate J.;Fan, Jun;Bessant, Conrad;Matthews, David A.

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Identification of proteins by tandem mass spectrometry requires a database of the proteins that could be in the sample. This is available for model species (e.g. humans) but not for non-model species. Ideally, for a non-model species the sequencing of expressed mRNA would generate a protein database for mass spectrometry based identification, allowing detection of genes and proteins using high throughput sequencing and protein identification technologies. Here we use human cells infected with human adenovirus as a complex and dynamic model to demonstrate this approach is robust. Our Proteomics Informed by Transcriptomics technique identifies >99% of over 3700 distinct proteins identified using traditional analysis reliant on comprehensive human and adenovirus protein lists. This facilitates high throughput acquisition of direct evidence for transcripts and proteins in non-model species. Critically, we show this approach can also be used to highlight genes and proteins undergoing dynamic changes in post transcriptional protein stability.
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