Evidence map›Paper›PMID 30248119›Full record

ArticlePloS one2018

Elucidation and analyses of the regulatory networks of upland and lowland ecotypes of switchgrass in response to drought and salt stresses.

Chunman Zuo, Yuhong Tang, Hao Fu, Yiming Liu, Xunzhong Zhang, Bingyu Zhao, Ying Xu

Open access · goldAbstract readComparative Study
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

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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

7 authors at 3 institutions in 2 countries.

Chunman ZuoCollege of Computer Science and Technology, Jilin University, Changchun, China.
Yuhong TangNoble Research Institute, LLC., Ardmore, OK, United States of America.
Hao FuNorth Automatic Control Technology Institute, Taiyuan, China.
Yiming LiuDepartment of Crop and Soil Environmental Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.
Xunzhong ZhangDepartment of Crop and Soil Environmental Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.
Bingyu ZhaoDepartment of Horticulture, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.
Ying XuCollege of Computer Science and Technology, Jilin University, Changchun, China.ORCID 0000-0001-5887-2926
Virginia Tech · USUniversity of Georgia · USNoble Research Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Switchgrass is an important bioenergy crop typically grown in marginal lands, where the plants must often deal with abiotic stresses such as drought and salt. Alamo is known to be more tolerant to both stress types than Dacotah, two ecotypes of switchgrass. Understanding of their stress response and adaptation programs can have important implications to engineering more stress tolerant plants. We present here a computational study by analyzing time-course transcriptomic data of the two ecotypes to elucidate and compare their regulatory systems in response to drought and salt stresses. A total of 1,693 genes (target genes or TGs) are found to be differentially expressed and possibly regulated by 143 transcription factors (TFs) in response to drought stress together in the two ecotypes. Similarly, 1,535 TGs regulated by 110 TFs are identified to be involved in response to salt stress. Two regulatory networks are constructed to predict their regulatory relationships. In addition, a time-dependent hidden Markov model is derived for each ecotype responding to each stress type, to provide a dynamic view of how each regulatory network changes its behavior over time. A few new insights about the response mechanisms are predicted from the regulatory networks and the time-dependent models. Comparative analyses between the network models of the two ecotypes reveal key commonalities and main differences between the two regulatory systems. Overall, our results provide new information about the complex regulatory mechanisms of switchgrass responding to drought and salt stresses.

Indexed as

DroughtsGene Expression Regulation, PlantAlternative SplicingComputer SimulationEcotypeMarkov ChainsPanicumSalt StressSpecies SpecificityTranscriptome

Identifiers

PMID30248119
PMCPMC6152977
OpenAlexW2892952620

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.