Gene regulatory networks associated with lateral root and nodule development in soybean. Issue 1 (28th February 2020)

• Record Type: Journal Article
• Authors: Smita, Shuchi; Kiehne, Jason; Adhikari, Sajag; Zeng, Erliang; Ma, Qin; Subramanian, Senthil
• Is Part Of: In silico plants. Volume 2:Issue 1(2020)
• Publication Date: 2020-02-28
• Subjects: Plant physiology -- Periodicals; Botany -- Periodicals; Botany -- Mathematical models -- Periodicals; Crop science -- Periodicals; 580
• DOI: 10.1093/insilicoplants/diaa002
• Languages: English
• ISSNs: 2517-5025

Abstract

Abstract: Legume plants such as soybean produce two major types of root lateral organs, lateral roots and root nodules. A robust computational framework was developed to predict potential gene regulatory networks (GRNs) associated with root lateral organ development in soybean. A genome-scale expression dataset was obtained from soybean root nodules and lateral roots and subjected to biclustering using QUBIC (QU alitative BIC lustering algorithm). Biclusters and transcription factor (TF) genes with enriched expression in lateral root tissues were converged using different network inference algorithms to predict high confident regulatory modules that were repeatedly retrieved in different methods. The ranked combination of results from all different network inference algorithms into one ensemble solution identified 21 GRN modules of 182 co-regulated genes networks, potentially involved in root lateral organ development stages in soybean. The workflow correctly predicted previously known nodule- and lateral root associated TFs including the expected hierarchical relationships. The results revealed distinct high-confidence GRN modules associated with early nodule development involving AP2, GRF5, and C3H family TFs, and those associated with nodule maturation involving GRAS, LBD41, and ARR18 family TFs. Knowledge from this work supported by experimental validation in the future is expected to help determine key gene targets for biotechnological strategies to optimize nodule formation and enhance nitrogen fixation.