Evidence map›Paper›PMID 36646724›Full record

SynthesisScientific reports2023

Integration of meta-analysis, machine learning and systems biology approach for investigating the transcriptomic response to drought stress in Populus species.

Ahmad Tahmasebi, Ali Niazi, Sahar Akrami

Erratum issuedOpen access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 3 pooled it
6.8field-weighted citation impact, top 4% of its field
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

12 citing papers in PubMed, 3 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
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  6. Core Perturbomes ofPathogens (Basel, Switzerland) · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Ahmad TahmasebiInstitute of Biotechnology, Shiraz University, Shiraz, 7144165186, Iran. atahmasebi1@gmail.com.ORCID 0000-0001-5590-1218
Ali NiaziInstitute of Biotechnology, Shiraz University, Shiraz, 7144165186, Iran. niazi@shirazu.ac.ir.ORCID 0000-0002-9902-9422
Sahar AkramiInstitute of Biotechnology, Shiraz University, Shiraz, 7144165186, Iran.
Shiraz University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Populus, drought is a major problem affecting plant growth and development which can be closely reflected by corresponding transcriptomic changes. Nevertheless, how these changes in Populus are not fully understood. Here, we first used meta-analysis and machine learning methods to identify water stress-responsive genes and then performed a systematic approach to discover important gene networks. Our analysis revealed that large transcriptional variations occur during drought stress. These changes were more associated with the response to stress, cellular catabolic process, metabolic pathways, and hormone-related genes. The differential gene coexpression analysis highlighted two acetyltransferase NATA1-like and putative cytochrome P450 genes that have a special contribution in response to drought stress. In particular, the findings showed that MYBs and MAPKs have a prominent role in the drought stress response that could be considered to improve the drought tolerance of Populus. We also suggest ARF2-like and PYL4-like genes as potential markers for use in breeding programs. This study provides a better understanding of how Populus responses to drought that could be useful for improving tolerance to stress in Populus.

Indexed as

PopulusTranscriptomeDroughtsGene Expression Regulation, PlantPlant BreedingStress, PhysiologicalSystems Biology

Identifiers

PMID36646724
PMCPMC9842770
OpenAlexW4316500152

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.