Evidence map›Paper›PMID 38117849›Full record

ArticlePLoS computational biology2023

High CO2 adaptation mechanisms revealed in the miR156-regulated flowering time pathway.

Kun Zhang, Erkang Wang, Qiong Alison Liu, Jin Wang

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 17% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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

4 authors at 2 institutions in 2 countries.

Kun ZhangSchool of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei, Anhui, P. R. China.ORCID 0000-0002-5986-4511
Erkang WangSchool of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei, Anhui, P. R. China.
Qiong Alison LiuIvyGen LLC, Wilmington, Delaware, United States of America.ORCID 0000-0002-4636-0920
Jin WangDepartment of Chemistry and of Physics, Stony Brook University, Stony Brook, New York, United States of America.ORCID 0000-0002-2841-4913
University of Science and Technology of China · CNStony Brook University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Elevated CO2 concentrations have been observed to accelerate flowering time in Arabidopsis through the action of a highly conserved regulatory network controlled by miR156 and miR172. However, the network's robustness to the impact of increasing CO2 concentrations on flowering time remains poorly understood. In this study, we investigate this question by conducting a comprehensive analysis of the global landscape of network dynamics, including quantifying the probabilities associated with juvenile and flowering states and assessing the speed of the transition between them. Our findings reveal that a CO2 concentration range of 400-800ppm only mildly advances flowering time, contrasting with the dramatic changes from 200 to 300ppm. Notably, the feedback regulation of miR156 by squamosal promoter binding protein-like proteins (SPLs) plays a substantial role in mitigating the effects of increasing CO2 on flowering time. Intriguingly, we consistently observe a correlation between delayed flowering time and increased variance in flowering time, and vice versa, suggesting that this might be an intrinsic adaptation mechanism embedded within the network. To gain a deeper understanding of this network's dynamics, we identified the sensitive features within the feedback loops of miR156 SPLs and miR172-APETALA2 family proteins (AP2s), with the latter proving to be the most sensitive. Strikingly, our study underscores the indispensability of all feedback regulations in maintaining both juvenile and adult states as well as the transition time between them. Together, our research provides the first physical basis in plant species, aiding in the elucidation of novel regulatory mechanisms and the robustness of the miRNAs-regulated network in response to increasing CO2, therefore influencing the control of flowering time. Moreover, this study provides a promising strategy for engineering plant flowering time to enhance their adaptation and resilience.

Indexed as

ArabidopsisArabidopsis ProteinsMicroRNAsCarbon DioxideFlowersGene Expression Regulation, PlantTranscription FactorsArabidopsis ProteinsCarbon DioxideMicroRNAsMirn156 microRNA, ArabidopsisTranscription Factors

Identifiers

PMID38117849
PMCPMC10775972
OpenAlexW4390036917

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.