Evidence map›Paper›PMID 42576043›Full record

ArticlePlanta2026

Integrative RNA sequencing uncovers the miRNA-mRNA landscape of water-deficit response in Setaria italica.

Juliana M Rodrigues, Vitor G B Theodoro, Gabriel G Carvalho, Igor Cesarino, Leandro F de Oliveira, Nathalia de Setta

Abstract read
In one paragraph

Article in Planta, 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
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

6 authors.

Juliana M RodriguesCentro de Ciências Naturais E Humanas (CCNH), Universidade Federal Do ABC (UFABC), São Bernardo Do Campo, SP, Brazil.ORCID http://orcid.org/0000-0002-8123-5324
Vitor G B TheodoroCentro de Ciências Naturais E Humanas (CCNH), Universidade Federal Do ABC (UFABC), São Bernardo Do Campo, SP, Brazil.ORCID http://orcid.org/0009-0001-6072-0662
Gabriel G CarvalhoLigninLab, Department of Botany, Institute of Biosciences, University of São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0009-0007-5848-7148
Igor CesarinoLigninLab, Department of Botany, Institute of Biosciences, University of São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0000-0002-6789-2432
Leandro F de OliveiraLigninLab, Department of Botany, Institute of Biosciences, University of São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0000-0002-5318-2771
Nathalia de SettaCentro de Ciências Naturais E Humanas (CCNH), Universidade Federal Do ABC (UFABC), São Bernardo Do Campo, SP, Brazil. nathalia.setta@ufabc.edu.br.ORCID http://orcid.org/0000-0002-4807-5410

Funding

Agência Nacional do Petróleo, Gás Natural e Biocombustíveis 2024/11571-3)Agência Nacional do Petróleo, Gás Natural e Biocombustíveis D&I of Resolution ANP No. 50/2015 (Grant No. 2025/18201-0Agência Nacional do Petróleo, Gás Natural e Biocombustíveis PRH-ANP UFABC supported with resources from the investment of oil companies qualified in the Clause of PCoordenação de Aperfeiçoamento de Pessoal de Nível Superior ScholarshipFundação de Amparo à Pesquisa do Estado de São Paulo 2021/06142-8Fundação de Amparo à Pesquisa do Estado de São Paulo 2023/02414-9Fundação de Amparo à Pesquisa do Estado de São Paulo 2024/01685-1Fundação de Amparo à Pesquisa do Estado de São Paulo 2024/10125-0Fundação de Amparo à Pesquisa do Estado de São Paulo 2024/12357-
6 · The paper itself

Abstract

MAIN

conclusionIn miRNA-mRNA regulatory modules of Setaria italica, the candidate novel miRNAs Sit-miR74-N/APX7 and Sit-miR132-N/PEPC involved in key pathways underlying water-deficit response have been detected. In the first module, APX7 expression was directly associated with water-deficit intensity, whereas in the second module, PEPC activation occurred under moderate water deficit. Drought severely constrains plant growth and productivity, yet the underlying regulatory mechanisms remain incompletely understood. Here, we determined the miRNA-mediated post-transcriptional landscape during water deficit in the panicoid grass Setaria italica. Two independent water-deficit experiments combined with small RNA and degradome sequencing identified 159 miRNAs, including 135 candidate novel sequences, of which 20 were differentially expressed under contrasting watering regimes. In silico analysis predicted 1,612 miRNA-mRNA regulatory modules, representing a broad landscape of potential post-transcriptional regulation. Complementarily, degradome sequencing identified 19 miRNA-mRNA modules, several of which exhibited inverse expression patterns, particularly under severe water-deficit conditions. Functional annotation of target mRNAs uncovered multiple functional processes, including transcriptional regulation, photosynthesis, redox homeostasis, and solute transport. Additionally, transient expression assays validated selected miRNA-mRNA modules, confirming the interaction between candidate novel miRNAs and water deficit-related mRNA targets. These modules are involved in key water deficit-responsive pathways, including oxidative stress regulation (Sit-miR74-N/APX7), photosynthetic carbon metabolism (Sit-miR132-N/PEPC), and flavonoid biosynthetic pathways (Sit-miR39-N/OMT). Together, these findings reveal a complex regulatory network in which miRNAs contribute to the coordination of water-deficit responses in S. italica, with post-transcriptional regulation underlying plant responses to abiotic stress.

Indexed as

MicroRNAsRNA, MessengerSetaria PlantWaterDroughtsGene Expression Regulation, PlantRNA, PlantSequence Analysis, RNAMicroRNAsRNA, MessengerRNA, PlantWaterAbiotic stressDegradome sequencingGene expressionMonocotyledonsPost-transcriptional regulationTranscriptome

Identifiers

PMID42576043
PMCPMC13457271

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Registered trials

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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.