Analysis of Spatio-Temporal Transcriptome Profiles of Soybean (Glycine max) Tissues during Early Seed Development.
Int J Mol Sci
; 21(20)2020 Oct 14.
Article
em En
| MEDLINE
| ID: mdl-33066688
ABSTRACT
Soybean (Glycine max) is an important crop providing oil and protein for both human and animal consumption. Knowing which biological processes take place in specific tissues in a temporal manner will enable directed breeding or synthetic approaches to improve seed quantity and quality. We analyzed a genome-wide transcriptome dataset from embryo, endosperm, endothelium, epidermis, hilum, outer and inner integument and suspensor at the global, heart and cotyledon stages of soybean seed development. The tissue specificity of gene expression was greater than stage specificity, and only three genes were differentially expressed in all seed tissues. Tissues had both unique and shared enriched functional categories of tissue-specifically expressed genes associated with them. Strong spatio-temporal correlation in gene expression was identified using weighted gene co-expression network analysis, with the most co-expression occurring in one seed tissue. Transcription factors with distinct spatiotemporal gene expression programs in each seed tissue were identified as candidate regulators of expression within those tissues. Gene ontology (GO) enrichment of orthogroup clusters revealed the conserved functions and unique roles of orthogroups with similar and contrasting expression patterns in transcript abundance between soybean and Arabidopsis during embryo proper and endosperm development. Key regulators in each seed tissue and hub genes connecting those networks were characterized by constructing gene regulatory networks. Our findings provide an important resource for describing the structure and function of individual soybean seed compartments during early seed development.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Sementes
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Glycine max
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Redes Reguladoras de Genes
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Transcriptoma
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article