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Comparing early transcriptomic responses of 18 soybean (Glycine max) genotypes to iron stress

dataset
posted on 2024-06-11, 06:38 authored by USDA
Iron deficiency chlorosis (IDC) is an abiotic stress that negatively affects soybean (Glycine max [L.] Merr.) production. Much of our knowledge of IDC stress responses is derived from model plant species. Gene expression, quantitative trait loci (QTL) mapping, and genome-wide association studies (GWAS) performed in soybean suggest that stress response differences exist between model and crop species. Our current understanding of the molecular response to IDC in soybeans is largely derived from gene expression studies using near-isogenic lines differing in iron efficiency. To improve iron efficiency in soybeans and other crops, we need to expand gene expression studies to include the diversity present in germplasm collections. Therefore, we collected 216 purified RNA samples (18 genotypes, two tissue types [leaves and roots], two iron treatments [sufficient and deficient], three replicates) and used RNA sequencing to examine the expression differences of 18 diverse soybean genotypes in response to iron deficiency. We found a rapid response to iron deficiency across genotypes, most responding within 60 min of stress. There was little evidence of an overlap of specific differentially expressed genes, and comparisons of gene ontology terms and transcription factor families suggest the utilization of different pathways in the stress response. These initial findings suggest an untapped genetic potential within the soybean germplasm collection that could be used for the continued improvement of iron efficiency in soybean.

History

Data contact name

BioProject Curation Staff

Publisher

National Center for Biotechnology Information

Temporal Extent Start Date

2021-03-05

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

transcriptome; gene expression

Pending citation

  • No

Public Access Level

  • Public

Accession Number

PRJNA706999

Preferred dataset citation

It is recommended to cite the accession numbers that are assigned to data submissions, e.g. the GenBank, WGS or SRA accession numbers. If individual BioProjects need to be referenced, state that "The data have been deposited with links to BioProject accession number PRJNA706999 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/)."

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