Journal article
Gene regulatory networks associated with lateral root and nodule development in soybean
in silico Plants, Vol.2(1), diaa002
01/01/2020
DOI: 10.1093/insilicoplants/diaa002
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 data set was obtained from soybean root nodules and lateral roots and subjected to biclustering using QUBIC (QUalitative BIClustering algorithm). Biclusters and transcription factor (TF) genes with enriched expression in lateral root tissues were converged using different network inference algorithms to predict high-confidence 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.
Details
- Title: Subtitle
- Gene regulatory networks associated with lateral root and nodule development in soybean
- Creators
- Shuchi Smita - Department of Agronomy, Horticulture and Plant Science and Department of Biology and Microbiology, South Dakota State University, Brookings, SD, USAJason Kiehne - Simpson College, Indianola, IA, USASajag Adhikari - Department of Agronomy, Horticulture and Plant Science and Department of Biology and Microbiology, South Dakota State University, Brookings, SD, USAErliang Zeng - Department of Biology and Department of Computer Science, University of South Dakota, Vermillion, SD, USAQin Ma - Department of Agronomy, Horticulture and Plant Science and Department of Biology and Microbiology, South Dakota State University, Brookings, SD, USASenthil Subramanian - Department of Agronomy, Horticulture and Plant Science and Department of Biology and Microbiology, South Dakota State University, Brookings, SD, USA
- Resource Type
- Journal article
- Publication Details
- in silico Plants, Vol.2(1), diaa002
- DOI
- 10.1093/insilicoplants/diaa002
- ISSN
- 2517-5025
- eISSN
- 2517-5025
- Grant note
- name: National Science Foundation/EPSCoR Cooperative Agreements, award: IIA-1355423, 1849206; name: National Science Foundation’s Plant Genome Research Program, award: IOS-1350189; name: United States Department of Agriculture National Institute of Food and Agriculture, award: 2016-67014-24589; DOI: 10.13039/100012372, name: SD Agricultural Experiment Station, award: SD00H543-15, OAC-1559978
- Language
- English
- Date published
- 01/01/2020
- Academic Unit
- Preventive and Community Dentistry; Roy J. Carver Department of Biomedical Engineering; Iowa Neuroscience Institute; Biostatistics; Dental Research
- Record Identifier
- 9984070349002771
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