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Integrating Genetics and Molecular Biology for Soybean Researchers

Enter a gene model name or a list of gene model names for the expression profiles of each gene.

Data Type


NOTE: The RNA-seq reads have been mapped only to the initial genome assembly, i.e. Wm82.a1.v1. Gene models that were uniquely identified in the later Wm82.a1.v1.1 or Wm82.a2.v1 assemblies are not represented in this expression atlas. This tool can be used to translate gene model names between all working versions.

RNA-Seq Atlas of Glycine max: A guide to the soybean transcriptome

This RNA-Seq atlas extends upon the analyses of previous gene expression atlases performed using Affymetrix GeneChip technology and describes new methods that compensate for the increase in transcriptome data obtained from next generation sequencing.

The RNA Seq-Atlas presented here provides high-resolution gene expression in a diverse set of fourteen tissues. Mining of these data suggests three clades of tissue (aerial, underground and seed) exhibiting transcriptionally similar profiles. For example, the analysis of the gene expression profiles of over 2,000 genes with preferential gene expression in seed suggests there are more than 177 genes with functional roles that complement or aid in the economically important seed filling process.

We provide a means for examine genes with differential gene expression between any two tissues. The list of genes with a significant increase in gene expression between the tissues can be found here. One application of this table is to explore the differential gene expression between two developmental time points in a tissue of interest to gain insight into the gene functions and thereby the biological processes that occur during particular stages of development.

Additionally, we find that tissue specific gene expression of both the highest expressed genes and the genes specific to legumes is found in seed development and nodule tissues. Heatmaps effectively display gene expression profiles to easily identify genes with specific gene expression.

Finally We also investigate the relationship between gene structure and gene expression and find a correlation between gene length and gene expression. These tables along with figures, supplementary material and raw data are available for download.

We are always interested in collaborations and welcome next-generation sequencing data to be deposited in SoyBase.

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