TY - JOUR
T1 - Transcriptomic data-driven discovery of global regulatory features of rice seeds developing under heat stress
AU - Islam, Mohammad Mazharul
AU - Sandhu, Jaspreet
AU - Walia, Harkamal
AU - Saha, Rajib
N1 - Funding Information:
This work was supported by University of Nebraska-Lincoln Faculty Startup Grant [ 21–1106–4308 ] to RS, University of Nebraska-Lincoln Research Council Interdisciplinary Grant [ 26–1106–9001–008 ] to both RS and HW, and NSF Award [Grant numbers 1736192 , 1564621 ] to HW. If the funding sources had no involvement in the design of the study, analysis of data, or the preparation of the manuscript.
Funding Information:
This work has been completed utilizing the Holland Computing Center of the University of Nebraska, which receives support from the Nebraska Research Initiative.
Publisher Copyright:
© 2020 The Author(s)
PY - 2020
Y1 - 2020
N2 - Plants respond to abiotic stressors through a suite of strategies including differential regulation of stress-responsive genes. Hence, characterizing the influences of the relevant global regulators or on stress-related transcription factors is critical to understand plant stress response. Rice seed development is highly sensitive to elevated temperatures. To elucidate the extent and directional hierarchy of gene regulation in rice seeds under heat stress, we developed and implemented a robust multi-level optimization-based algorithm called Minimal Regulatory Network identifier (MiReN). MiReN could predict the minimal regulatory relationship between a gene and its potential regulators from our temporal transcriptomic dataset. MiReN predictions for global regulators including stress-responsive gene Slender Rice 1 (SLR1) and disease resistance gene XA21 were validated with published literature. It also predicted novel regulatory influences of other major regulators such as Kinesin-like proteins KIN12C and STD1, and WD repeat-containing protein WD40. Out of the 228 stress-responsive transcription factors identified, we predicted de novo regulatory influences on three major groups (MADS-box M-type, MYB, and bZIP) and investigated their physiological impacts during stress. Overall, MiReN results can facilitate new experimental studies to enhance our understanding of global regulatory mechanisms triggered during heat stress, which can potentially accelerate the development of stress-tolerant cultivars.
AB - Plants respond to abiotic stressors through a suite of strategies including differential regulation of stress-responsive genes. Hence, characterizing the influences of the relevant global regulators or on stress-related transcription factors is critical to understand plant stress response. Rice seed development is highly sensitive to elevated temperatures. To elucidate the extent and directional hierarchy of gene regulation in rice seeds under heat stress, we developed and implemented a robust multi-level optimization-based algorithm called Minimal Regulatory Network identifier (MiReN). MiReN could predict the minimal regulatory relationship between a gene and its potential regulators from our temporal transcriptomic dataset. MiReN predictions for global regulators including stress-responsive gene Slender Rice 1 (SLR1) and disease resistance gene XA21 were validated with published literature. It also predicted novel regulatory influences of other major regulators such as Kinesin-like proteins KIN12C and STD1, and WD repeat-containing protein WD40. Out of the 228 stress-responsive transcription factors identified, we predicted de novo regulatory influences on three major groups (MADS-box M-type, MYB, and bZIP) and investigated their physiological impacts during stress. Overall, MiReN results can facilitate new experimental studies to enhance our understanding of global regulatory mechanisms triggered during heat stress, which can potentially accelerate the development of stress-tolerant cultivars.
KW - Global regulation
KW - Heat stress
KW - Minimal regulatory network
KW - Optimization
KW - Rice seed development
KW - Transcriptomics
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U2 - 10.1016/j.csbj.2020.09.022
DO - 10.1016/j.csbj.2020.09.022
M3 - Article
C2 - 33033578
AN - SCOPUS:85091668256
SN - 2001-0370
VL - 18
SP - 2556
EP - 2567
JO - Computational and Structural Biotechnology Journal
JF - Computational and Structural Biotechnology Journal
ER -