Evidence map›Paper›PMID 36859112›Full record

ArticleBMC plant biology2023

Transcriptome sequencing leads to an improved understanding of the infection mechanism of Alternaria solani in potato.

Jia Jiang, Xuhao Guo, Huanhuan Tan, Mingya Ding, Fangming Liu, Zhihui Yang, Jiehua Zhu

Open access · goldAbstract read
In one paragraph

Article in BMC plant biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 16% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Mechanisms of action and biocontrol potential ofFrontiers in fungal biology · 2026
    Review
  2. Alternaria diseases on potato and tomato.Molecular plant pathology · 2024
    Review
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 2 institutions in 1 country.

Jia JiangCollege of Plant Protection, Hebei Agricultural University, Baoding, 071001, China.
Xuhao GuoDepartment of Plant Protection, College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang, 471023, China.
Huanhuan TanDepartment of Plant Protection, College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang, 471023, China.
Mingya DingPotato Research Institute of Weichang Manchu and Mongolian Autonomous County, Chengde, 068450, China.
Fangming LiuPotato Research Institute of Weichang Manchu and Mongolian Autonomous County, Chengde, 068450, China.
Zhihui YangCollege of Plant Protection, Hebei Agricultural University, Baoding, 071001, China.
Jiehua ZhuCollege of Plant Protection, Hebei Agricultural University, Baoding, 071001, China. zhujiehua356@126.com.
Hebei Agricultural University · CNHenan University of Science and Technology · CN

Funding

China Agriculture Research System of MOF and MARA CARS-09-P18Hebei key Research and Development Program 21326515D
6 · The paper itself

Abstract

backgroundAlternaria solani (A. solani), the main pathogen of potato early blight, causes serious yield reductions every year. The application of fungicides is the most common and effective method of controlling Alternaria-caused diseases. The differentially expressed transcripts of A. solani infecting potato were identified, revealing a group of valuable candidate genes for a systematic analysis to increase the understanding of the molecular pathogenesis of A. solani, and providing scientific data for formulating additional measures to prevent and control potato early blight. In this study, a deep RNA-sequencing approach was applied to gain insights into A. solani pathogenesis. At 3, 4, and 5 days post inoculation (dpi), RNA samples from the susceptible potato cultivar Favorita infected with A. solani strain HWC-168, were sequenced and utilized for transcriptome analysis, and compared to the transcriptome obtained 0 dpi.

resultsA total of 4430 (2167 upregulated, 2263 downregulated), 4736 (2312 upregulated, 2424 downregulated), and 5043 (2411 upregulated, 2632 downregulated) genes were differentially expressed 3, 4 and 5 dpi, respectively, compared with genes analysed at 0 dpi. KEGG enrichment analysis showed that genes involved in the pathways of amino acid metabolism, glucose metabolism, and enzyme activity were significantly differentially expressed at the late infection stage. Correspondingly, symptoms developed rapidly during the late stage of A. solani infection. In addition, a short time-series expression miner (STEM) assay was performed to analyse the gene expression patterns of A. solani and Profile 17 and 19 showed significant change trends 3, 4 and 5 dpi. Both profiles, but especially Profile 17, included enzymes, including transferases, oxidoreductases, hydrolases and carbohydrate-active enzymes (CAZYmes), which may play important roles in late fungal infection. Furthermore, possible candidate effectors were identified through the adopted pipelines, with 137 differentially expressed small secreted proteins identified, including some enzymes and proteins with unknown functions.

conclusionsCollectively, the data presented in this study show that amino acid metabolism, and glucose metabolism pathways, and specific pathway-related enzymes may be key putative pathogenic factors, and play important roles in late stage A. solani infection. These results contribute to a broader base of knowledge of A. solani pathogenesis in potato, as indicated by the transcriptional level analysis, and provide clues for determining the effectors of A. solani infection.

Indexed as

Solanum tuberosumAlternariaAmino AcidsGlucoseTranscriptomeAmino AcidsGlucoseAlternaria solaniEarly blightRNA-sequencingTranscriptomic analysis

Identifiers

PMID36859112
PMCPMC9976505
OpenAlexW4322741409

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.