Evidence map›Paper›PMID 28061745›Full record

ArticleBMC genomics2017

Large-scale transcriptome comparison of sunflower genes responsive to Verticillium dahliae.

Shuchun Guo, Yongchun Zuo, Yanfang Zhang, Chengyan Wu, Wenxia Su, Wen Jin, Haifeng Yu, Yulin An, Qianzhong Li

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
13.2field-weighted citation impact, top 2% 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

26 citing papers in PubMed, 61 citations in OpenAlex.

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  16. A Genome-Wide Analysis ofFrontiers in genetics · 2022
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  17. Review
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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 at 2 institutions in 1 country.

Shuchun GuoLaboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China.
Yongchun ZuoLaboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China.
Yanfang ZhangInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Chengyan WuLaboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China.
Wenxia SuLaboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China.
Wen JinLaboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China.
Haifeng YuInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Yulin AnInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Qianzhong LiLaboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China. qzli@imu.edu.cn.
Inner Mongolia University · CNInner Mongolia Academy of Agricultural & Animal Husbandry Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSunflower Verticillium wilt (SVW) is a vascular disease caused by root infection with Verticillium dahliae (V. dahlia). It is a serious threat to the yield and quality of sunflower. However, chemical and agronomic measures for controlling this disease are not effective. The selection of more resistant genotypes is a desirable strategy to reduce contamination. A deeper knowledge of the molecular mechanisms and genetic basis underlying sunflower Verticillium wilt is necessary to accelerate breeding progress.

resultsAn RNA-Seq approach was used to perform global transcriptome profiling on the roots of resistant (S18) and susceptible (P77) sunflower genotypes infected with V. dahlia. Different pairwise transcriptome comparisons were examined over a time course (6, 12 and 24 h, and 2, 3, 5 and 10 d post inoculation). In RD, SD and D datasets, 1231 genes were associated with SVW resistance in a genotype-common transcriptional pattern. Moreover, 759 and 511 genes were directly related to SVW resistance in the resistant and susceptible genotypes, respectively, in a genotype-specific transcriptional pattern. Most of the genes were demonstrated to participate in plant defense responses; these genes included peroxidase (POD), glutathione peroxidase, aquaporin PIP, chitinase, L-ascorbate oxidase, and LRR receptors. For the up-regulated genotype-specific differentially expressed genes (DEGs) in the resistant genotype, higher average fold-changes were observed in the resistant genotype compared to those in the susceptible genotype. An inverse effect was observed in the down-regulated genotype-specific DEGs in the resistant genotype. KEGG analyses showed that 98, 112 and 52 genes were classified into plant hormone signal transduction, plant-pathogen interaction and flavonoid biosynthesis categories, respectively. Many of these genes, such as CNGC, RBOH, FLS2, JAZ, MYC2 NPR1 and TGA, regulate crucial points in defense-related pathway and may contribute to V. dahliae resistance in sunflower.

conclusionsThe transcriptome profiling results provided a clearer understanding of the transcripts associated with the crosstalk between sunflower and V. dahliae. The results identified several differentially expressed unigenes involved in the hyper sensitive response (HR) and the salicylic acid (SA)/jasmonic acid (JA)-mediated signal transduction pathway for resistance against V. dahliae. These results are useful for screening resistant sunflower genotypes.

Indexed as

Gene Expression ProfilingGenes, PlantGenotypeHelianthusPlant DiseasesPlant RootsTranscription, GeneticVerticilliumDefense responses genesDifferentially expressed genes (DEGs)Helianthus annuus LRNA-SeqVerticillium dahliae

Identifiers

PMID28061745
PMCPMC5219742
OpenAlexW2568867706

What OpenQuestion holds

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LicenceCC BY
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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.