Computational Identification of MicroRNAs and Their Transcript Target(s) in Field Mustard (Brassica rapa L.).
Iran J Biotechnol
; 15(1): 22-32, 2017 Mar.
Article
em En
| MEDLINE
| ID: mdl-28959349
ABSTRACT
BACKGROUND:
Micro RNAs (miRNAs) are a pivotal part of non-protein-coding endogenous small RNA molecules that regulate the genes involved in plant growth and development, and respond to biotic and abiotic environmental stresses posttranscriptionally.OBJECTIVE:
In the present study, we report the results of a systemic search for identification of new miRNAs in B. rapa using homology-based ESTs (Expressed Sequence Tags) analysis and considering a series of fi ltration criteria. MATERIALS ANDMETHODS:
Plant mature miRNA sequences were searched in non-protein coding ESTs registered in NCBI EST database. Zuker RNA folding algorithm was used to generate the secondary structures of the ESTs. Potential sequences were candidate as miRNA genes and characterized evolutionarily only and if only they fi t some described criteria. Also, the web tool psRNATarget was applied to predict candidate B. rapa miRNA targets.RESULTS:
In this study, 10 novel miRNAs from B. rapa belonging to 6 miRNA families were identified using EST-based homology analysis by considering a series of fi ltration criteria. All potent miRNAs appropriate fold back structure. Several potential targets with known/unknown functions for these novel miRNAs were identified. The target genes mainly encode transcription factors, enzymes, DNA binding proteins, disease resistance proteins, carrier proteins and other biological processes.CONCLUSIONS:
MicroRNA having diverse functions in plant species growth, development and evolution by posttranscriptionally regulating the levels of specific transcriptome so by effecting on their translation products. Research in miRNA led to the identification of many miRNAs and their regulating genes from diverse plant species.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
Iran J Biotechnol
Ano de publicação:
2017
Tipo de documento:
Article