Yucebilgili, Kuaybe and Kantar, Melda and Budak, Hikmet (2014) New wheat microRNA using whole-genome sequence. Functional and Integrative Genomics, 14 (2). pp. 363-379. ISSN 1438-793X (Print) 1438-7948 (Online)
Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.1007/s10142-013-0357-9
Abstract
MicroRNAs are post-transcriptional regulators of gene expression, taking roles in a variety of fundamental biological processes. Hence, their identification, annotation and characterization are of great significance, especially in bread wheat, one of the main food sources for humans. The recent availability of 5x coverage Triticum aestivum L. whole-genome sequence provided us with the opportunity to perform a systematic prediction of a complete catalogue of wheat microRNAs. Using an in silico homology-based approach, stem-loop coding regions were derived from two assemblies, constructed from wheat 454 reads. To avoid the presence of pseudo-microRNAs in the final data set, transposable element related stem-loops were eliminated by repeat analysis. Overall, 52 putative wheat microRNAs were predicted, including seven, which have not been previously published. Moreover, with distinct analysis of the two different assemblies, both variety and representation of putative microRNA-coding stem-loops were found to be predominant in the intergenic regions. By searching available expressed sequences and small RNA library databases, expression evidence for 39 (out of 52) putative wheat microRNAs was provided. Expression of three of the predicted microRNAs (miR166, miR396 and miR528) was also comparatively quantified with real-time quantitative reverse transcription PCR. This is the first report on in silico prediction of a whole repertoire of bread wheat microRNAs, supported by the wet-lab validation.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Triticum aestivum; MicroRNA; MicroRNA prediction; Next-generation sequencing; Real-time quantitative reverse transcription PCR |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Biological Sciences & Bio Eng. Faculty of Engineering and Natural Sciences |
Depositing User: | Hikmet Budak |
Date Deposited: | 19 Dec 2014 16:37 |
Last Modified: | 02 Aug 2019 14:38 |
URI: | https://research.sabanciuniv.edu/id/eprint/25542 |