Evidence map›Paper›PMID 41028381›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Applications of the Soybean Expression Atlas in Genomics and Transcriptomics Research.

Gabriel Quintanilha-Peixoto, Dayana Kelly Turquetti-Moraes, Ana Luiza Martins Karl, Fabrício Almeida-Silva, Thiago M Venancio

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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gabriel Quintanilha-PeixotoLaboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil.
Dayana Kelly Turquetti-MoraesLaboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil.
Ana Luiza Martins KarlLaboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil.
Fabrício Almeida-SilvaDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium. fabricio.almeidasilva@psb.ugent.be.
Thiago M VenancioLaboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil. tmvenancio@uenf.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Gene Expression ProfilingGene Expression Regulation, PlantGenomicsGlycine maxTranscriptomeComputational BiologyDatabases, GeneticSoftwareAgricultureBioinformaticsDifferential expressionGlycine maxRNA-SeqTranscriptomics

Identifiers

PMID41028381

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.