Evidence map›Paper›PMID 41288984›Full record

ArticleBriefings in functional genomics2025

Computational inference of Rhizobium phaseoli transcriptional regulatory network predicts Transcription Factors involved in nodulation.

Ericka M Hernandez-Benitez, Esperanza Martínez-Romero, José Luis Aguirre-Noyola, Jose Arcadio Farias-Rico, Daniela Ledezma-Tejeida

Abstract read
In one paragraph

Article in Briefings in functional genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ericka M Hernandez-BenitezPrograma de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Av. Universidad s/n, Col. Chamilpa, Cuernavaca, Morelos, 62210  Mexico.
Esperanza Martínez-RomeroPrograma de Ecología Genómica, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Av. Universidad s/n, Col. Chamilpa, Cuernavaca, Morelos 62210, Mexico.
José Luis Aguirre-NoyolaPrograma de Ecología Genómica, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Av. Universidad s/n, Col. Chamilpa, Cuernavaca, Morelos 62210, Mexico.
Jose Arcadio Farias-RicoPrograma de Biología Sintética, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Av. Universidad s/n, Col. Chamilpa, Cuernavaca, Morelos 62210, Mexico.
Daniela Ledezma-TejeidaPrograma de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Av. Universidad s/n, Col. Chamilpa, Cuernavaca, Morelos, 62210  Mexico.ORCID 0000-0002-2055-417X

Funding

Programa de Maestría en Ciencias Bioquímicas, Universidad Nacional Autónoma de México 2057038Secretaría de Ciencia, Humanidades, Tecnología e InnovaciónUniversidad Nacional Autónoma de México, Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica IA204925
6 · The paper itself

Abstract

Growth of the common bean plant Phaseolus vulgaris is tightly linked to its symbiotic relationship with diverse rhizobial species, particularly Rhizobium phaseoli, an alphaproteobacterium that forms root nodules and provides high levels of nitrogen to the plant. Molecular cross-talk is known to happen through plant-derived metabolites, but only flavonoids have been identified as nodulation signals, which act through the activation of the NodD Transcription Factor (TF). The identification of signals that mediate nodulation via TFs can aid in the rational design of biofertilizers that promote plant-bacteria symbiosis. Here, we identified 57 TFs in the R. phaseoli genome through sequence conservation from Escherichia coli, and predicted a transcriptional regulatory network comprising 16 TFs, and 1,371 target genes. We identified the regulatory interactions relevant to nodulation via transcriptome analysis, and hypothesize that PuuR is a TF involved in nodulation, potentially acting via its known binding metabolite putrescine. Sequence and structural evidence predict a model where putrescine acts as a signaling metabolite in nodulation via the TF PuuR, and the regulation of the nodI gene.

Indexed as

Computational BiologyGene Regulatory NetworksPhaseolusPlant Root NodulationRhizobiumTranscription FactorsBacterial ProteinsSymbiosisBacterial ProteinsTranscription Factorsbioinformaticscomparative genomicsnodulationsymbiosistranscriptional regulatory networktranscription factors

Identifiers

PMID41288984
PMCPMC12645834

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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.