Evidence map›Paper›PMID 23196693›Full record

ArticleMolecular genetics and genomics : MGG2013

Digital gene expression analysis of early root infection resistance to Sporisorium reilianum f. sp. zeae in maize.

Shaopeng Zhang, Yannong Xiao, Jiuran Zhao, Fengge Wang, Yonglian Zheng

Erratum issuedAbstract read
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In one paragraph

Article in Molecular genetics and genomics : MGG, 2013. 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 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 20% 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, 16 citations in OpenAlex.

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4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Shaopeng ZhangNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, People's Republic of China. zsp0106@gmail.com
Yannong Xiao
Jiuran Zhao
Fengge Wang
Yonglian Zheng
Huazhong Agricultural University · CNBeijing Academy of Agricultural and Forestry Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The maize smut fungus, Sporisorium reilianum f. sp. zeae, which is an important biotrophic pathogen responsible for extensive crop losses, can infect maize by invading the root during the early seedling stage. In order to investigate disease-resistance mechanisms at this early seedling stage, digital gene expression analysis, which applies a dual-enzyme approach, was used to identify the transcriptional changes in the roots of Huangzao4 (susceptible) and Mo17 (resistant) after root inoculation with S. reilianum. During the infection in the roots, the expression pattern of pathogenesis-related genes in Huangzao4 and Mo17 were significantly differentially regulated at different infection stages. The glutathione S-transferase enzyme activity and reactive oxygen species levels also showed changes before and after inoculation. The total lignin contents and the pattern of lignin depositions in the roots differed during root colonization of Huangzao4 and Mo17. These results suggest that the interplay between S. reilianum and maize during the early infection stage involves many important transcriptional and physiological changes, which offer several novel insights to understanding the mechanisms of resistance to the infection of biotrophic fungal pathogens.

Indexed as

Gene Expression ProfilingChromosome MappingGene Expression Regulation, PlantGene Regulatory NetworksGlutathione TransferaseHost-Pathogen InteractionsLigninMolecular Sequence AnnotationPlant DiseasesPlant RootsReactive Oxygen SpeciesTranscription, GeneticUstilaginalesZea maysGlutathione TransferaseLigninReactive Oxygen Species

Identifiers

PMID23196693
OpenAlexW1971621493

What OpenQuestion holds

Textmetadata
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.