Gene regulatory networks associated with lateral root and nodule development in soybean

Abstract

24Legume plants such as soybean produce two major types of root lateral organs, lateral roots and 25 root nodules. A robust computational framework was developed to predict potential gene 26 regulatory networks (GRNs) associated with root lateral organ development in soybean. A 27 genome-scale expression dataset was obtained from soybean root nodules and lateral roots and 28 subjected to biclustering using QUBIC. Biclusters (BCs) and transcription factor (TF) genes with 29 enriched expression in lateral root tissues were converged using different network inference 30 algorithms to predict high confident regulatory modules that are repeatedly retrieved in different 31 methods. The ranked combination of results from all different network inference algorithms into 32 one ensemble solution identified 21 GRN modules of 182 co-regulated genes networks 33 potentially involved in root lateral organ development stages in soybean. The pipeline correctly 34 predicted previously known nodule-and LR-associated TFs including the expected hierarchical 35 relationships. The results revealed high scorer AP2, GRF5, and C3H co-regulated GRN modules 36 during early nodule development; and GRAS, LBD41, and ARR18 co-regulated GRN modules 37 late during nodule maturation. Knowledge from this work supported by experimental validation 38 in the future is expected to help determine key gene targets for biotechnological strategies to 39 optimize nodule formation and enhance nitrogen fixation. 40 41