Abstract
BackgroundAlignment analysis of the Vv-miRNAs identified from various grapevine cultivars indicates that over 30% orthologous Vv-miRNAs exhibit a 1–3 nucleotide discrepancy only at their ends, suggesting that this sequence discrepancy is not a random event, but might mainly derive from divergence of cultivars. With advantages of miR-RACE technology in determining precise sequences of potential miRNAs from bioinformatics prediction, the precise sequences of vv-miRNAs predicted computationally can be verified with miR-RACE in a different grapevine cultivar. This presents itself as a new approach for large scale discovery of precise miRNAs in different grapevine varieties.Methodology/Principal FindingsAmong 88 unique sequences of Vv-miRNAs from bioinformatics prediction, 83 (96.3%) were successfully validated with MiR-RACE in grapevine cv. ‘Summer Black’. All the validated sequences were identical to their corresponding ones obtained from deep sequencing of the small RNA library of ‘Summer Black’. Quantitative RT-PCR analysis of the expressions levels of 10 Vv-miRNA/target gene pairs in grapevine tissues showed some negative correlation trends. Finally, comparison of Vv-miRNA sequences with their orthologs in Arabidopsis and study on the influence of divergent bases of the orthologous miRNAs on their targeting patterns in grapevine were also done.ConclusionThe validation of precise sequences of potential Vv-miRNAs from computational prediction in a different grapevine cultivar can be a new way to identify the orthologous Vv-miRNAs. Nucleotide discrepancy of orthologous Vv-miRNAs from different grapevine cultivars normally does not change their target genes. However, sequence variations of some orthologous miRNAs in grapevine and Arabidopsis can change their targeting patterns. These precise Vv-miRNAs sequences validated in our study could benefit some further study on grapevine functional genomics.
Highlights
MicroRNAs are a newly identified class of endogenous tiny, non-protein-coding RNA molecules that play very important roles in post transcriptional gene regulation through degradation of target mRNAs or by repression of targeted gene translation in organisms [1,2,3,4,5]
‘Summer Black’ and the VvmiRNAs predicted computationally were our preferable choices to be researched on, since the former is one of the most popular and important grapevine cultivars grown for a table grape in China and the later is the largest group of candidate Vv-miRNAs released publicly
In the last group of 26 Vv-miRNAs, 14 were identical in both reports while another 12 exhibited some different nucleotides in the end sequences from the two studies. These 162 predicted Vv-miRNAs can be used as baits in the discovery of their corresponding orthologs in other grapevine cultivars (e.g ‘‘Summer Black’’ in our study) by validating the termini nucleotides based on the phenomenon that the nucleotide variations only happen at either ends of the corresponding VvmiRNAs in different grapevine cultivars
Summary
MicroRNAs (miRNAs) are a newly identified class of endogenous tiny, non-protein-coding RNA molecules that play very important roles in post transcriptional gene regulation through degradation of target mRNAs or by repression of targeted gene translation in organisms [1,2,3,4,5]. With advantages of miR-RACE technology in determining precise sequences of potential miRNAs from bioinformatics prediction, the precise sequences of vv-miRNAs predicted computationally can be verified with miR-RACE in a different grapevine cultivar. This presents itself as a new approach for large scale discovery of precise miRNAs in different grapevine varieties
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
