Small
            <scp>RNA</scp>
            diversity and roles in model legumes

Proust, Hélène; Moreau, J F; Crespi, Martín; Hartmann, Caroline; Lelandais‐Brière, Christine

doi:10.1002/9781119409144.ch123

Cited by 2 publications

(1 citation statement)

References 166 publications

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“…To explore the biological significance of soybean MTRMs, we collected related soybean miRNAs, which revealed five types of abiotic stresses, involving (1) drought, (2) salt, (3) cold, (4) Pi, (5) phosphorus deficiency based on publications ( Subramanian et al, 2008 ; Kulcheski et al, 2011 ; Li et al, 2011 ; Sha et al, 2012 ; Subramanian, 2012 ; Sunkar et al, 2012 ; Dong et al, 2013 ; Zhang et al, 2014 , 2018 ; Balyan et al, 2015 ; Xu et al, 2016 ; Zheng et al, 2016 ; Chen et al, 2018 ; Gupta et al, 2019 ; Proust et al, 2019 ; Yu J.-Y. et al, 2019 ; Wang et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

A Multi-Level Iterative Bi-Clustering Method for Discovering miRNA Co-regulation Network of Abiotic Stress Tolerance in Soybeans

Chang

Zhang

et al. 2022

Front. Plant Sci.

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Although growing evidence shows that microRNA (miRNA) regulates plant growth and development, miRNA regulatory networks in plants are not well understood. Current experimental studies cannot characterize miRNA regulatory networks on a large scale. This information gap provides an excellent opportunity to employ computational methods for global analysis and generate valuable models and hypotheses. To address this opportunity, we collected miRNA–target interactions (MTIs) and used MTIs from Arabidopsis thaliana and Medicago truncatula to predict homologous MTIs in soybeans, resulting in 80,235 soybean MTIs in total. A multi-level iterative bi-clustering method was developed to identify 483 soybean miRNA–target regulatory modules (MTRMs). Furthermore, we collected soybean miRNA expression data and corresponding gene expression data in response to abiotic stresses. By clustering these data, 37 MTRMs related to abiotic stresses were identified, including stress-specific MTRMs and shared MTRMs. These MTRMs have gene ontology (GO) enrichment in resistance response, iron transport, positive growth regulation, etc. Our study predicts soybean MTRMs and miRNA-GO networks under different stresses, and provides miRNA targeting hypotheses for experimental analyses. The method can be applied to other biological processes and other plants to elucidate miRNA co-regulation mechanisms.

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