Special Issue "Applications of Genomics or Transcriptomics Approaches in Phytopathology"

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: 20 March 2024 | Viewed by 1011

Special Issue Editor

Institute of Plant Breeding and Genetic Resources, Hellenic Agricultural Organization–Demeter, Thermi, Thessaloniki, Greece
Interests: fungal genomics; plant–microbe interactions; plant pathogens; breeding for disease resistance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As plants are constantly plagued by a wide variety of pathogens, ongoing pathogens genomics revolution has highly contributed to disease management applications in phytopathology. The advent of such genomics-based resources coupled with next-generation sequencing (NGS) technologies has improved disease resistance in various crops. Coping with this challenge, these applications are effective and can be routinely adopted for crop protection by unraveling the molecular mechanisms underpinning pathogenesis and resistance, gaining insights into the genetics of pathogen populations on a large scale. Furthermore, transcriptome profiling plays a pivotal role for unraveling the molecular mechanisms during compatible or incompatible plant–pathogen interactions. Thus, RNA-seq technology can effectively decipher the differential expression patterns and the transcriptional immune responses when it comes to resistant and sensitive plant hosts challenged by pathogens.

The aim and scope of this Special Issue are the integration and contribution of genomics or transcriptomics data that would undoubtedly facilitate a comprehensive approach for deciphering various plant–microbe interactions. In the context of this Special Issue, we aim to exchange knowledge on the implementation of pathogens’ genomic approaches, such as pathogen genome-wide association studies and population genomics, or transcriptomic approaches employing RNA-seq differential expression analyses.

In this respect, we are soliciting the submission of any type of research article covering the applications of specific genomics or transcriptomics approaches towards enhancing our understanding of plant–microbe interactions and control of diseases caused by plant pathogens.

Dr. Antonios G. Zambounis
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • pathogens
  • genomics
  • transcriptomics
  • plant–microbe interactions
  • genetics
  • next-generation
  • sequencing
  • diseases
  • breeding for disease resistance

Published Papers (1 paper)

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Research

15 pages, 5621 KiB  
Article
Transcriptome Analysis of Nitrogen-Deficiency-Responsive Genes in Two Potato Cultivars
Agronomy 2023, 13(8), 2164; https://doi.org/10.3390/agronomy13082164 - 18 Aug 2023
Viewed by 663
Abstract
The potato is the third largest food crop, and nitrogen fertilizer is important for increasing potato yields; however, the shallow root system of potatoes causes the nitrogen fertilizer utilization rate to be low, which results in waste and environmental pollution, meaning that high [...] Read more.
The potato is the third largest food crop, and nitrogen fertilizer is important for increasing potato yields; however, the shallow root system of potatoes causes the nitrogen fertilizer utilization rate to be low, which results in waste and environmental pollution, meaning that high nitrogen efficiency breeding is highly significant for potatoes. In the high nitrogen efficiency breeding of potatoes, genes with a nitrogen-deficient response should first be identified, and RNA-seq is an efficient method for identifying nitrogen-deficiency-response genes. In this study, two potato cultivars, Dongnong 322 (DN322) and Dongnong 314 (DN314), were utilized, and two nitrogen fertilizer application rates (N0 and N1) were set for both cultivars. Through the determination of physiological indicators, we identified that DN314 is more sensitive to nitrogen fertilizer, while DN322 is relatively insensitive to nitrogen fertilizer. Samples were taken at the seedling and tuber formation stage. At the seedling stage, DN322 and DN314 had 573 and 150 differentially expressed genes (DEGs), while at the tuber formation stage, they had 59 and 1905 DEGs, respectively. A total of three genes related to a low-nitrogen response were obtained via the combined analysis of differentially expressed genes (DEGs) and weighted correlation network analysis (WGCNA), of which two genes were obtained at the tuber formation stage and one gene in the seedling stage, providing theoretical guidance for the high nitrogen efficiency breeding of potatoes. Full article
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