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Updated: Jan 16, 2026

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
Applications of the Soybean Expression Atlas in Genomics and Transcriptomics Research
Gabriel Quintanilha-Peixoto1, Dayana Kelly Turquetti-Moraes1, Ana Luiza Martins Karl1,2
1Laboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil.
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Genomics, the study of an organism's full set of genes, is often enhanced by gene expression data from RNA analysis, reflecting the correlation between gene function and expression profiles. This is particularly important for understanding complex traits regulated by multiple genes. RNA sequencing (RNA-Seq) has become a standard technique for studying gene expression, especially in crops like soybean (Glycine max), which is valued for its high protein and oil content. Despite the availability of soybean genomic data, processing raw RNA-Seq data into usable formats remains a resource-intensive task, often requiring expensive hardware and bioinformatics expertise. The Soybean Expression Atlas (SEA) simplifies this process by providing access to transcript- and gene-level abundance data from 5481 RNA-Seq samples through a user-friendly interface. SEA's features include tools like the Global Expression Viewer for visualizing gene expression profiles and the Search Gene List for generating lists across selected tissues. Users can also download gene expression matrices by BioProject and explore gene metadata, including tissue-specific indices and protein domain filters. SEA has facilitated studies of key metabolic pathways in soybean, such as oil biosynthesis, nodulation, and responses to environmental factors. It has also supported the development of additional tools in G. max and inspired similar initiatives in other plant species. This chapter demonstrates SEA's application in pathogen research, using examples of the fungal species Colletotrichum truncatum and the soybean cyst nematode Heterodera glycines, showcasing SEA's utility for narrowing down genes of interest for specific traits.
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