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Agronomy
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Insights from Genetic Bioinformatics of Crops
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Insights from Genetic Bioinformatics of Crops

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

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 14687

Special Issue Editor

Dr. Juan J. Gutierrez-Gonzalez

E-Mail Website
Guest Editor
Department of Molecular Biology, University of Leon, Leon, Spain
Interests: genomics; bioinformatics; genetics; plant breeding; biotechnology; gene expression; legumes; plant diseases

Special Issue Information

Dear Colleagues,

We all are aware of the revolution that the irruption of bioinformatics has brought to plant research in general and crop breeding in particular. As an example, in the last decade and a half, we have passed from just using a handful of markers to thousands of them, thus being able to target whole genomes at an affordable cost. Bioinformatic tools have emerged at a similar rate to process the huge amount of data generated.

At the same time, the rapid increase in the world population coupled with the ongoing climate change problem has created the need for crop varieties adapted to the changing situation. Emphasis is now given to traits such as increasing yield, drought tolerance, and resistance to a newer and broader set of pests. Research on these and other topics is boosted by bioinformatics.

Knowing how important bioinformatics has become and will continue to be for crop and plant research, the aim of the Special Issue is to provide an opportunity for researchers to bring forth ideas to solve the current and future problems regarding crops. Papers should focus on bioinformatics applied to crop genetics and genomics, both for plants and soil microorganisms, along with newly described bioinformatic tools and their applications. Original research articles, communications, and concepts for review articles to address major issues are welcome.

Dr. Juan J. Gutierrez-Gonzalez
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

  • crop bioinformatics
  • plant breeding and genetics
  • genomics-assisted breeding
  • transcriptomics
  • crop biotechnology
  • genetic bioinformatics

Published Papers (6 papers)

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Research

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18 pages, 2805 KiB  
Article
Multi-Species Transcriptome Assemblies of Cultivated and Wild Lentils (Lens sp.) Provide a First Glimpse at the Lentil Pangenome
by Juan J. Gutierrez-Gonzalez, Pedro García, Carlos Polanco, Ana Isabel González, Francisca Vaquero, Francisco Javier Vences, Marcelino Pérez de la Vega and Luis E. Sáenz de Miera
Agronomy 2022, 12(7), 1619; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071619 - 05 Jul 2022
Cited by 4 | Viewed by 1956
Abstract
Lentils (Lens sp.) are one of the main sources of protein for humans in many regions, in part because their rusticity allows them to withstand semi-dry climates and tolerate a wide spectrum of pests. Both are also highly sought-after attributes to face [...] Read more.
Lentils (Lens sp.) are one of the main sources of protein for humans in many regions, in part because their rusticity allows them to withstand semi-dry climates and tolerate a wide spectrum of pests. Both are also highly sought-after attributes to face climate change. Wild accessions, rather than cultivated varieties, are typically the holders of most influential alleles for rusticity traits. However, most genomic and transcriptomic research conducted in lentils has been carried out on commercial accessions (L. culinaris), while wild relatives have been largely neglected. Herein, we assembled, annotated, and evaluated the transcriptomes of eight lentil accessions, including the cultivated Lens culinaris and the wild relatives: L. orientalis, L. tomentosus, L. ervoides, L. lamottei, L. nigricans, and two L. odemensis. The assemblies allowed, for the first time, a comparison among different lentil taxa at the coding sequence level, providing further insights into the evolutionary relationships between cultivated and wild germplasm and suggesting a grouping of the seven accessions into at least three conceivable gene pools. Moreover, orthologous clustering allowed a first estimation of the lentil pan-transcriptome. It is composed of 15,910 core genes, encoded in all accessions, and 24,226 accessory genes. The different pan-transcriptome clusters were also screened for Pfam-domain enrichment. The present study has a high novelty, as it is the first pan-transcriptome analysis using six wild species in addition to cultivated species. Because of the amount of transcript sequences provided, our findings will greatly boost lentil research and assist breeding efforts. Full article
(This article belongs to the Special Issue Insights from Genetic Bioinformatics of Crops)
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18 pages, 4674 KiB  
Article
Cation/Proton Antiporter Genes in Tomato: Genomic Characterization, Expression Profiling, and Co-Localization with Salt Stress-Related QTLs
by Zahid Hussain, Habiba Khan, Muhammad Imran, Muhmmad Kashif Naeem, Sabir Hussain Shah, Arshad Iqbal, Syed Shujait Ali, Muhammad Rizwan, Shahid Ali, Muhammad Atif Muneer, Emilie Widemann and Sarfraz Shafiq
Agronomy 2022, 12(2), 245; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020245 - 19 Jan 2022
Cited by 6 | Viewed by 2140
Abstract
The cation/proton antiporter (CPA) family represents a class of transmembrane transporter proteins that play a crucial role in plants during high salinity stress by maintaining the cell’s ionic balance and pH homeostasis. So far, the CPA genes have not been systematically characterized in [...] Read more.
The cation/proton antiporter (CPA) family represents a class of transmembrane transporter proteins that play a crucial role in plants during high salinity stress by maintaining the cell’s ionic balance and pH homeostasis. So far, the CPA genes have not been systematically characterized in tomato (Solanum lycopersicum). In this study, we identified and analyzed 33 putative CPA genes in tomato. Phylogenetic analysis showed that tomato CPAs could be classified into three subgroups, i.e., CHX (18 genes), KEA (8 genes), and NHX (7 genes). CPA genes within each subgroup shared similar motifs, conserved catalytic domains and gene structure. Further analysis revealed that the CPA genes were unevenly distributed on the chromosomes and segmental duplication events played a major role in the expansion of the CPA gene family in tomato. Gene expression analysis exhibited that CPA genes were differentially expressed in different tissues, various stages of fruit development, and differentially regulated in response to abiotic stresses, especially salt stress. Further, co-localization of tomato CPA genes with quantitative trait loci (QTL) of salt stress-related phenotypes revealed their broader functions in salt stress tolerance. Finally, predicted protein–protein interactions of tomato CPAs, gene ontology analysis, and the presence of putative cis-elements in the promoter further support the diverse role of tomato CPAs in plant development and plant stress tolerance. In brief, this study highlights the potential role of tomato CPAs in plant development and abiotic stress tolerance, especially in salt stress, and provides comprehensive information to explore new candidate genes for salt tolerance in tomato. Full article
(This article belongs to the Special Issue Insights from Genetic Bioinformatics of Crops)
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7 pages, 2073 KiB  
Communication
Daisychain: Search and Interactive Visualisation of Homologs in Genome Assemblies
by Oliver Schliebs, Chon-Kit Kenneth Chan, Philipp E. Bayer, Jakob Petereit, Ajit Singh, Keywan Hassani-Pak, Jacqueline Batley and David Edwards
Agronomy 2021, 11(12), 2587; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11122587 - 19 Dec 2021
Viewed by 1984
Abstract
Daisychain is an interactive graph visualisation and search tool for custom-built gene homology databases. The main goal of Daisychain is to allow researchers working with specific genes to identify homologs in other annotation releases. The gene-centric representation includes local gene neighborhood to distinguish [...] Read more.
Daisychain is an interactive graph visualisation and search tool for custom-built gene homology databases. The main goal of Daisychain is to allow researchers working with specific genes to identify homologs in other annotation releases. The gene-centric representation includes local gene neighborhood to distinguish orthologs and paralogs by local synteny. The software supports genome sequences in FASTA format and GFF3 formatted annotation files, and the process of building the homology database requires a minimum amount of user interaction. Daisychain includes an integrated web viewer that can be used for both data analysis and data publishing. The web interface extends KnetMaps.js and is based on JavaScript. Full article
(This article belongs to the Special Issue Insights from Genetic Bioinformatics of Crops)
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19 pages, 13440 KiB  
Article
SNPs, InDels, and Microsatellites within and Near to Rice NBS-LRR Resistance Gene Candidates
by Mark J. Quinton-Tulloch and Katherine A. Steele
Agronomy 2021, 11(11), 2297; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11112297 - 13 Nov 2021
Cited by 1 | Viewed by 1644
Abstract
Plant resistance genes (R-genes) drive the immune responses of crops against specific pathotypes of disease-causing organisms. Over time, genetic diversity in R-genes and R-pseudogenes has arisen among different rice varieties. This bioinformatics study was carried out to (i) predict the full sets of [...] Read more.
Plant resistance genes (R-genes) drive the immune responses of crops against specific pathotypes of disease-causing organisms. Over time, genetic diversity in R-genes and R-pseudogenes has arisen among different rice varieties. This bioinformatics study was carried out to (i) predict the full sets of candidate nucleotide-binding site leucine-rich repeat (NLR) R-genes present in six rice genomes; (ii) detect variation within candidate R-genes; (iii) identify potential selectable markers within and near to LRR genes among 75 diverse indica rice genomes. Four high quality indica genomes, plus the standard japonica and indica reference genomes, were analysed with widely available bioinformatic tools to identify candidate R-genes and R-pseudogenes. They were detected in clusters, consistent with previous studies. BLAST analysis of cloned protein sequences of 31 R-gene loci gave confidence in this approach for detection of cloned NLR R-genes. Approximately 10% of candidate R-genes were located within 1 kb of a microsatellite (SSR) marker. Sequence comparisons among indica rice genomes detected SNPs or InDels in 334 candidate rice R-genes. There were significantly more SNPs and InDels within the identified NLR R-gene candidates than in other types of gene. The genome-wide locations of candidate R-genes and their associated markers are presented here for the potential future development of improved disease-resistant varieties. Limitations of in silico approaches used for R-gene discovery are discussed. Full article
(This article belongs to the Special Issue Insights from Genetic Bioinformatics of Crops)
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13 pages, 3036 KiB  
Article
Identification and Characterization of SPL Transcription Factor Family Reveals Organization and Chilling-Responsive Patterns in Cabbage (Brassica oleracea var. capitata L.)
by Xi Shan, Wei Zhang, Jianxin Huang, Fangwei Yu, Wenbin Qin, Jianbin Li, Shenyun Wang and Zhongliang Dai
Agronomy 2021, 11(7), 1445; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11071445 - 20 Jul 2021
Cited by 2 | Viewed by 2370
Abstract
Squamosa promoter-binding protein-like (SPL) is a major family of plant-specific transcription factor, which is involved in multiple biological processes, such as plant growth and development, hormone response, light response and stress response. Therefore, it has been profoundly significant to systematically analyze the SPL [...] Read more.
Squamosa promoter-binding protein-like (SPL) is a major family of plant-specific transcription factor, which is involved in multiple biological processes, such as plant growth and development, hormone response, light response and stress response. Therefore, it has been profoundly significant to systematically analyze the SPL Transcription Factors family in Brassica oleracea. In this study, a total of 33 BoSPLs were identified in the B. oleracea genome, and they were further divided into six subgroups based on the phylogenetic tree constructed from the SPL proteins of B. oleracea, B. rapa and Arabidopsis thaliana. The expression profile of BoSPLs in different organs/tissues showed that a large number of BoSPLs were expressed in the callus, root, stem, leaf, bud, flower and silique. In addition, the expression levels of two BoSPLs (BoSPL9b and BoSPL10b) were up-regulated in chilling tolerance cabbage ‘CT-923’ at 6 h after chilling stress when compared with normal treatment (mock), while two BoSPLs (BoSPL9b and BoSPL15a) in chilling sensitive cabbage ‘CS-D9’, five BoSPLs (BoSPL1, -9a, -9b, -10b, -11b) in ‘CT-923’ and two BoSPLs (BoSPL9b and BoSPL16a) in ‘CS-D9’ were up-regulated after 24 h chilling stress, indicated that these genes may play an important role in the chilling-tolerance of cabbage. We analyzed the characteristics of BoSPLs and provided the basis for further functional research. Full article
(This article belongs to the Special Issue Insights from Genetic Bioinformatics of Crops)
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Review

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16 pages, 807 KiB  
Review
Bioinformatic-Based Approaches for Disease-Resistance Gene Discovery in Plants
by Andrea Fernandez-Gutierrez and Juan J. Gutierrez-Gonzalez
Agronomy 2021, 11(11), 2259; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11112259 - 09 Nov 2021
Cited by 3 | Viewed by 3619
Abstract
Pathogens are among the most limiting factors for crop success and expansion. Thus, finding the underlying genetic cause of pathogen resistance is the main goal for plant geneticists. The activation of a plant’s immune system is mediated by the presence of specific receptors [...] Read more.
Pathogens are among the most limiting factors for crop success and expansion. Thus, finding the underlying genetic cause of pathogen resistance is the main goal for plant geneticists. The activation of a plant’s immune system is mediated by the presence of specific receptors known as disease-resistance genes (R genes). Typical R genes encode functional immune receptors with nucleotide-binding sites (NBS) and leucine-rich repeat (LRR) domains, making the NBS-LRRs the largest family of plant resistance genes. Establishing host resistance is crucial for plant growth and crop yield but also for reducing pesticide use. In this regard, pyramiding R genes is thought to be the most ecologically friendly way to enhance the durability of resistance. To accomplish this, researchers must first identify the related genes, or linked markers, within the genomes. However, the duplicated nature, with the presence of frequent paralogues, and clustered characteristic of NLRs make them difficult to predict with the classic automatic gene annotation pipelines. In the last several years, efforts have been made to develop new methods leading to a proliferation of reports on cloned genes. Herein, we review the bioinformatic tools to assist the discovery of R genes in plants, focusing on well-established pipelines with an important computer-based component. Full article
(This article belongs to the Special Issue Insights from Genetic Bioinformatics of Crops)
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