Evidence map›Paper›PMID 35573803›Full record

Article3 Biotech2022

Identification of major candidate genes for multiple abiotic stress tolerance at seedling stage by network analysis and their validation by expression profiling in rice (

M K Ramkumar, Ekta Mulani, Vasudha Jadon, V Sureshkumar, S Gopala Krishnan, S Senthil Kumar, M Raveendran, A K Singh, Amolkumar U Solanke, N K Singh and 1 more

Open access · greenAbstract read
In one paragraph

Article in 3 Biotech, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
3.2field-weighted citation impact, top 8% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. RiceMetaSys: Drought-miR, a one-stop solution for drought responsive miRNAs-mRNA module in rice.Database : the journal of biological databases and curation · 2024
    Article
  8. Article
  9. Review
  10. Article
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

11 authors at 4 institutions in 1 country.

M K RamkumarICAR-National Institute for Plant Biotechnology, Pusa Campus, New Delhi, 110012 India.
Ekta MulaniICAR-National Institute for Plant Biotechnology, Pusa Campus, New Delhi, 110012 India.
Vasudha JadonICAR-National Institute for Plant Biotechnology, Pusa Campus, New Delhi, 110012 India.
V SureshkumarICAR-National Institute for Plant Biotechnology, Pusa Campus, New Delhi, 110012 India.
S Gopala KrishnanDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, 110012 India.
S Senthil KumarDepartment of Botany, National College, Tiruchirapalli, Tamil Nadu 620001 India.
M RaveendranTamil Nadu Agricultural University, Coimbatore, India.
A K SinghDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, 110012 India.
Amolkumar U SolankeICAR-National Institute for Plant Biotechnology, Pusa Campus, New Delhi, 110012 India.
N K SinghICAR-National Institute for Plant Biotechnology, Pusa Campus, New Delhi, 110012 India.
Amitha Mithra SevanthiICAR-National Institute for Plant Biotechnology, Pusa Campus, New Delhi, 110012 India.ORCID 0000-0002-8447-9148
National Research Centre on Plant Biotechnology · INIndian Agricultural Research Institute · INNational Institute of Technology Tiruchirappalli · INTamil Nadu Agricultural University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A wealth of microarray and RNA-seq data for studying abiotic stress tolerance in rice exists but only limited studies have been carried out on multiple stress-tolerance responses and mechanisms. In this study, we identified 6657 abiotic stress-responsive genes pertaining to drought, salinity and heat stresses from the seedling stage microarray data of 83 samples and used them to perform unweighted network analysis and to identify key hub genes or master regulators for multiple abiotic stress tolerance. Of the total 55 modules identified from the analysis, the top 10 modules with 8-61 nodes comprised 239 genes. From these 10 modules, 10 genes common to all the three stresses were selected. Further, based on the centrality properties and highly dense interactions, we identified 7 intra-modular hub genes leading to a total of 17 potential candidate genes. Out of these 17 genes, 15 were validated by expression analysis using a panel of 4 test genotypes and a pair of standard check genotypes for each abiotic stress response. Interestingly, all the 15 genes showed upregulation under all stresses and in all the genotypes, suggesting that they could be representing some of the core abiotic stress-responsive genes. More pertinently, eight of the genes were found to be co-localized with the stress-tolerance QTL regions. Thus, in conclusion, our study not only provided an effective approach for studying abiotic stress tolerance in rice, but also identified major candidate genes which could be further validated by functional genomics for abiotic stress tolerance. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03182-7.

Indexed as

Co-expression and network analysisCommon abiotic stress-tolerance mechanismsHub genesRice

Identifiers

PMID35573803
PMCPMC9098736
OpenAlexW4280515781

What OpenQuestion holds

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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.