Evidence map›Paper›PMID 32267863›Full record

ArticlePloS one2020

Comparative analysis of sugarcane root transcriptome in response to the plant growth-promoting Burkholderia anthina MYSP113.

Mukesh Kumar Malviya, Chang-Ning Li, Manoj Kumar Solanki, Rajesh Kumar Singh, Reemon Htun, Pratiksha Singh, Krishan K Verma, Li-Tao Yang, Yang-Rui Li

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
–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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Characterization of the Pyrroloquinoline Quinone ProducingInternational journal of molecular sciences · 2023
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  11. Co-Inoculation of EndophytesPlants (Basel, Switzerland) · 2023
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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

9 authors.

Mukesh Kumar MalviyaKey Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China.
Chang-Ning LiKey Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China.
Manoj Kumar SolankiDepartment of Food Quality & Safety, Institute for Post-Harvest and Food Sciences, The Volcani Center, Agricultural Research Organization, Rishon LeZion, Israel.
Rajesh Kumar SinghKey Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China.
Reemon HtunDepartment of Biotechnology, Mandalay Technological University, Mandalay, Myanmar.
Pratiksha SinghKey Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China.
Krishan K VermaKey Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China.
Li-Tao YangCollege of Agriculture, Guangxi University, Nanning, Guangxi, China.
Yang-Rui LiKey Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The diazotrophic Burkholderia anthina MYSP113 is a vital plant growth-promoting bacteria and sugarcane root association. The present study based on a detailed analysis of sugarcane root transcriptome by using the HiSeq-Illumina platform in response to the strain MYSP113. The bacterium was initially isolated from the rhizosphere of sugarcane. To better understand biological, cellular, and molecular mechanisms, a de novo transcriptomic assembly of sugarcane root was performed. HiSeq-Illumina platformwas employed for the sequencing of an overall of 16 libraries at a 2×100 bp configuration. Differentially expressed genes (DEGs) analysis identified altered gene expression in 370 genes (total of 199 up-regulated genes and 171 down-regulated genes). Deciphering the huge datasets, concerning the functioning and production of biological systems, a high throughput genome sequencing analysis was attempted with Gene ontology functional analyses and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The report revealed a total of 148930 unigenes. 70414 (47.28%) of them were annotated successfully to Gene Ontology (GO) terms. 774 at 45 days, 4985 of 30 days and 15 days of 6846 terms were significantly regulated. GO analysis revealed that many genes involved in the metabolic, oxidation-reduction process and biological regulatory processes in response to strain MYSP113 and significantly enriched as compare to the control. Moreover, KEGG enriched results show that differentially expressed genes were classified into different pathway categories involved in various processes, such as nitrogen metabolism, plant hormone signal transduction, etc. The sample correlation analyses could help examine the similarity at the gene expression level. The reliability of the observed differential gene expression patterns was validated with quantitative real-time PCR (qRT-PCR). Additionally, plant enzymes activities such as peroxidase and superoxide dismutase were significantly increased in plant roots after the inoculation of strain MYSP113. The results of the research may help in understanding the plant growth-promoting rhizobacteria and plant interaction.

Indexed as

TranscriptomeAntioxidantsBurkholderiaCluster AnalysisGene Expression Regulation, PlantGenes, PlantMetabolic Networks and PathwaysPlant RootsReal-Time Polymerase Chain ReactionRNA, PlantSaccharumSequence Analysis, RNAAntioxidantsRNA, Plant

Identifiers

PMID32267863
PMCPMC7141665

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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.