The Soybean Expression Atlas v2: a comprehensive database of over 5000 RNA-seq samples

Abstract

Soybean is a crucial crop worldwide, used as a source of food, feed, and industrial products due to its high protein and oil content. Previously, the rapid accumulation of soybean RNA-seq data in public databases and the computational challenges of processing raw RNA-seq data motivated us to develop the Soybean Expression Atlas, a gene expression database of over a thousand RNA-seq samples. Over the past few years, our database has allowed researchers to explore the expression profiles of important gene families, discover genes associated with agronomic traits, and understand the transcriptional dynamic of cellular processes. Here, we present the Soybean Expression Atlas v2, an updated version of our database with a 4-fold increase in the number of samples, featuring transcript- and gene-level transcript abundance matrices for 5481 publicly available RNA-seq samples. New features in our database include the availability of transcript-level abundance estimates and equivalence classes to explore differential transcript usage, abundance estimates in bias-corrected counts to increase the accuracy of differential gene expression analyses, a new web interface with improved data visualization and user experience, and a reproducible and scalable pipeline available as an R package. The Soybean Expression Atlas v2 is available at https://soyatlas.venanciogroup.uenf.br/, and it will accelerate soybean research, empowering researchers with high-quality and easily accessible gene expression data. Keywords: transcriptomics, bioinformatics, gene expression, integrative biology.

Novel genetic resources associated with sucrose and stachyose content through genome-wide association study in soybean (Glycine max (L.) Merr.)

“…Highly expressed candidate genes were determined based on at least two gene expression levels of more than 10 RPKM in developing seed tissues (https://www.ebi.ac.uk/). Another large set of RNA-Seq databases of gene-level transcript abundances (https:// soyatlas.venanciogroup.uenf.br/) was used for additional exploration in the differential gene expression across 19 parts of the soybean plant, including cotyledon, embryo, endosperm, epicotyl, flower, hypocotyl, leaf, nodule, petiole, pod, radicle, root, seed, seed coat, seedling, shoot, suspensor, unknown, and whole plant (Almeida-Silva et al, 2023). The raw gene expression counts were normalized using a Transcripts Per Million (TPM) method.…”