Genome wide in-silico miRNA and target network prediction from stress responsive Horsegram (Macrotyloma uniflorum) accessions.
Sci Rep
; 10(1): 17203, 2020 10 14.
Article
em En
| MEDLINE
| ID: mdl-33057204
ABSTRACT
Horsegram (Macrotyloma uniflorum (Lam.) Verdc.) is a drought hardy food and fodder legume of Indo-African continents with diverse germplasm sources demonstrating alternating mechanisms depicting contrasting adaptations to different climatic zones. Tissue specific expression of genes contributes substantially to location specific adaptations. Regulatory networks of such adaptive genes are elucidated for downstream translational research. MicroRNAs are small endogenous regulatory RNAs which alters the gene expression profiles at a particular time and type of tissue. Identification of such small regulatory RNAs in low moisture stress hardy crops can help in cross species transfer and validation confirming stress tolerance ability. This study outlined prediction of conserved miRNAs from transcriptome shotgun assembled sequences and EST sequences of horsegram. We could validate eight out of 15 of the identified miRNAs to demonstrate their role in deficit moisture stress tolerance mechanism of horsegram variety Paiyur1 with their target networks. The putative mumiRs were related to other food legumes indicating the presence of gene regulatory networks. Differential miRNA expression among drought specific tissues indicted the probable energy conservation mechanism. Targets were identified for functional characterization and regulatory network was constructed to find out the probable pathways of post-transcriptional regulation. The functional network revealed mechanism of biotic and abiotic stress tolerance, energy conservation and photoperiod responsiveness.
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
1_ASSA2030
Base de dados:
MEDLINE
Assunto principal:
Adaptação Fisiológica
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MicroRNAs
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Redes Reguladoras de Genes
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Fabaceae
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2020
Tipo de documento:
Article