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Functional annotation and meta-analysis of maize transcriptomes reveal genes involved in biotic and abiotic stress.
Hayford, Rita K; Haley, Olivia C; Cannon, Ethalinda K; Portwood, John L; Gardiner, Jack M; Andorf, Carson M; Woodhouse, Margaret R.
Afiliação
  • Hayford RK; Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, 50011, USA. rita.hayford@usda.gov.
  • Haley OC; Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, 50011, USA.
  • Cannon EK; Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, 50011, USA.
  • Portwood JL; Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, 50011, USA.
  • Gardiner JM; Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
  • Andorf CM; Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, 50011, USA. carson.andorf@usda.gov.
  • Woodhouse MR; Department of Computer Science, Iowa State University, Ames, IA, 50011, USA. carson.andorf@usda.gov.
BMC Genomics ; 25(1): 533, 2024 May 30.
Article em En | MEDLINE | ID: mdl-38816789
ABSTRACT

BACKGROUND:

Environmental stress factors, such as biotic and abiotic stress, are becoming more common due to climate variability, significantly affecting global maize yield. Transcriptome profiling studies provide insights into the molecular mechanisms underlying stress response in maize, though the functions of many genes are still unknown. To enhance the functional annotation of maize-specific genes, MaizeGDB has outlined a data-driven approach with an emphasis on identifying genes and traits related to biotic and abiotic stress.

RESULTS:

We mapped high-quality RNA-Seq expression reads from 24 different publicly available datasets (17 abiotic and seven biotic studies) generated from the B73 cultivar to the recent version of the reference genome B73 (B73v5) and deduced stress-related functional annotation of maize gene models. We conducted a robust meta-analysis of the transcriptome profiles from the datasets to identify maize loci responsive to stress, identifying 3,230 differentially expressed genes (DEGs) 2,555 DEGs regulated in response to abiotic stress, 408 DEGs regulated during biotic stress, and 267 common DEGs (co-DEGs) that overlap between abiotic and biotic stress. We discovered hub genes from network analyses, and among the hub genes of the co-DEGs we identified a putative NAC domain transcription factor superfamily protein (Zm00001eb369060) IDP275, which previously responded to herbivory and drought stress. IDP275 was up-regulated in our analysis in response to eight different abiotic and four different biotic stresses. A gene set enrichment and pathway analysis of hub genes of the co-DEGs revealed hormone-mediated signaling processes and phenylpropanoid biosynthesis pathways, respectively. Using phylostratigraphic analysis, we also demonstrated how abiotic and biotic stress genes differentially evolve to adapt to changing environments.

CONCLUSIONS:

These results will help facilitate the functional annotation of multiple stress response gene models and annotation in maize. Data can be accessed and downloaded at the Maize Genetics and Genomics Database (MaizeGDB).
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estresse Fisiológico / Zea mays / Anotação de Sequência Molecular / Transcriptoma Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estresse Fisiológico / Zea mays / Anotação de Sequência Molecular / Transcriptoma Idioma: En Ano de publicação: 2024 Tipo de documento: Article