Network-based feature selection reveals substructures of gene modules responding to salt stress in rice

Qian Du, Malachy Campbell, Huihui Yu, Kan Liu, Harkamal Walia, Qi Zhang, Chi Zhang

Research output: Contribution to journalArticle

Abstract

Rice, an important food resource, is highly sensitive to salt stress, which is directly related to food security. Although many studies have identified physiological mechanisms that confer tolerance to the osmotic effects of salinity, the link between rice genotype and salt tolerance is not very clear yet. Association of gene co-expression network and rice phenotypic data under stress has penitential to identify stress-responsive genes, but there is no standard method to associate stress phenotype with gene co-expression network. A novel method for integration of gene co-expression network and stress phenotype data was developed to conduct a system analysis to link genotype to phenotype. We applied a LASSO-based method to the gene co-expression network of rice with salt stress to discover key genes and their interactions for salt tolerance-related phenotypes. Submodules in gene modules identified from the co-expression network were selected by the LASSO regression, which establishes a linear relationship between gene expression profiles and physiological responses, that is, sodium/potassium condenses under salt stress. Genes in these submodules have functions related to ion transport, osmotic adjustment, and oxidative tolerance. We argued that these genes in submodules are biologically meaningful and useful for studies on rice salt tolerance. This method can be applied to other studies to efficiently and reliably integrate co-expression network and phenotypic data.

Original languageEnglish (US)
Article numbere00154
JournalPlant Direct
Volume3
Issue number8
DOIs
StatePublished - Jan 1 2019

Fingerprint

Gene Regulatory Networks
salt stress
Feature extraction
Salt-Tolerance
rice
Salts
Genes
salt
gene
Phenotype
Gene Expression
tolerance
genes
phenotype
salt tolerance
Genotype
Food Supply
Ion Transport
Salinity
Systems Analysis

Keywords

  • LASSO regression
  • co-expression network
  • data integration
  • gene modules
  • linkage between genome to phenotype

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Plant Science

Cite this

Network-based feature selection reveals substructures of gene modules responding to salt stress in rice. / Du, Qian; Campbell, Malachy; Yu, Huihui; Liu, Kan; Walia, Harkamal; Zhang, Qi; Zhang, Chi.

In: Plant Direct, Vol. 3, No. 8, e00154, 01.01.2019.

Research output: Contribution to journalArticle

Du, Qian ; Campbell, Malachy ; Yu, Huihui ; Liu, Kan ; Walia, Harkamal ; Zhang, Qi ; Zhang, Chi. / Network-based feature selection reveals substructures of gene modules responding to salt stress in rice. In: Plant Direct. 2019 ; Vol. 3, No. 8.
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