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Biology
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Genetic Improvement and Breeding of Wheat
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Genetic Improvement and Breeding of Wheat

A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Plant Science".

Deadline for manuscript submissions: closed (2 July 2021) | Viewed by 12622

Special Issue Editors

Dr. Laura Pascual

E-Mail Website
Guest Editor
Unit of Genetics, Department of Biotechnology—Plant Biology, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Interests: wheat genetics and genomics; plant breeding; wheat quality; QTLs; GWAs; MAS
Dr. Rosa Mérida-García

E-Mail Website
Guest Editor
Institute for Sustainable Agriculture (IAS-CSIC), Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, 14004 Córdoba, Spain
Interests: wheat genomics and transcriptomics; plant breeding; GWAs; genomic selection
Dr. Eugene Metakovsky

E-Mail
Guest Editor
Unit of Genetics, Department of Biotechnology—Plant Biology, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Interests: wheat genetic; wheat evolution; proteins polymorphism; prolamines; APAGE; gliadins

Special Issue Information

Wheat occupies a central place in human nutrition, providing 20% of the daily protein and food calories consumed by the human population. In order to meet the increasing requirements of a growing population and tackle the challenges of global climate change, the genetic improvement of this crop is of utmost importance. The recently published durum and bread wheat reference genomes provide high-quality data that facilitate the identification of key genes and provide tools that will be of high value for wheat breeding programs.

The Special Issue will be focused on studies related to the identification and analysis of key genomic regions related to breeding and evolution, and the development of new genetic marker-based strategies to conduct breeding in wheat.

Dear Colleagues,

Wheat occupies a central place in human nutrition, providing 20% of the daily protein and food calories consumed by the human population. In order to meet the increasing requirements of a growing population and tackle the challenges of global climate change, the genetic improvement of this crop is of utmost importance.

Nowadays, most wheat breeding programs mainly rely on conventional replicated, time-consuming field trials. In order to accelerate this process, it is important to uncover the genetic basis of key traits, and to develop genome-based breeding strategies. The recently published durum and bread wheat reference genomes provide high-quality data that facilitate the identification of key genes by GWA or QTL analysis. This knowledge, coupled with strategies such as marker-assisted selection (MAS) and genomic selection, which facilitates the selection with or without pre-knowledge of the trait targets, provides modern tools that will increase genetic gain during wheat improvement.

Therefore, this Special Issue aims to promote genomics-enabled wheat improvement by collecting original research and review manuscripts focusing on the development of new genetic marker-based strategies to conduct breeding in wheat, the identification of new genomic regions that may play an important role on breeding, but also the analysis of genetic diversity and evolution of already known key genomic regions, helping us to define wheat breeding in the 21st century.

Dr. Laura Pascual
Dr. Rosa Mérida-García
Dr. Eugene Metakovsky
Guest Editors

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. Biology 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 2700 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

  • wheat breeding
  • wheat genetics and genomics
  • QTLs
  • GWAs
  • marker-assisted selection
  • genomic selection
  • wheat

Published Papers (4 papers)

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Research

25 pages, 5789 KiB  
Article
The Emergence of New Aggressive Leaf Rust Races with the Potential to Supplant the Resistance of Wheat Cultivars
by Reda Ibrahim Omara, Yasser Nehela, Ola Ibrahim Mabrouk and Mohsen Mohamed Elsharkawy
Biology 2021, 10(9), 925; https://0-doi-org.brum.beds.ac.uk/10.3390/biology10090925 - 16 Sep 2021
Cited by 12 | Viewed by 2080
Abstract
Characterization of the genetic structure and the physiological races of Puccinia triticina is a growing necessity to apply host genetic resistance against wheat leaf rust as a successful control strategy. Herein, we collected and identified about 130 isolates of P. triticina from 16 [...] Read more.
Characterization of the genetic structure and the physiological races of Puccinia triticina is a growing necessity to apply host genetic resistance against wheat leaf rust as a successful control strategy. Herein, we collected and identified about 130 isolates of P. triticina from 16 Egyptian commercial wheat cultivars grown at different locations, over two seasons (2019/2020 and 2020/2021). The 130 isolates of P. triticina were segregated into 17 different physiological races. TTTST and TTTKS were the most common virulent races, whereas TTTST and MTTGT were the most frequent races. The races were classified into three groups, based on their distinct DNA band sizes (150 bp, 200 bp, and 300 bp) after RAPD analysis. The new wheat cultivars (Sakha-94, Sakha-95, and Shandweel-1) infected with the most virulent race (TTTST), Gemmeiza-12, and Misr-3 were resistant to all physiological races. The resistance of these cultivars was mostly due to the presence of Lr19- and Lr28-resistant genes. Our results serve as a warning about emerging aggressive races capable of supplanting resistance to leaf rust, and help in the understanding of the pathotype–cultivar–location association and its role in the susceptibility/resistance of new wheat cultivars to P. triticina. Full article
(This article belongs to the Special Issue Genetic Improvement and Breeding of Wheat)
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10 pages, 577 KiB  
Article
Powdery Mildew Resistance Phenotypes of Wheat Gene Bank Accessions
by Antonín Dreiseitl
Biology 2021, 10(9), 846; https://0-doi-org.brum.beds.ac.uk/10.3390/biology10090846 - 30 Aug 2021
Cited by 6 | Viewed by 2122
Abstract
Powdery mildew (Blumeria graminis f. sp. tritici) is a common pathogen of bread wheat (Triticum aestivum L.), and genetic resistance is an effective and environmentally friendly method to reduce its adverse impact. The introgression of novel genes from wheat progenitors [...] Read more.
Powdery mildew (Blumeria graminis f. sp. tritici) is a common pathogen of bread wheat (Triticum aestivum L.), and genetic resistance is an effective and environmentally friendly method to reduce its adverse impact. The introgression of novel genes from wheat progenitors and related species can increase the diversity of disease resistance and accumulation of minor genes to improve the crop’s resistance durability. To accomplish these two actions, host genotypes without major resistances should be preferably used. Therefore, the main aim of this study was to carry out seedling tests to detect such resistances in a set of wheat accessions from the Czech gene bank and to group the cultivars according to their phenotype. Ear progenies of 448 selected cultivars originating from 33 countries were inoculated with three isolates of the pathogen. Twenty-eight cultivars were heterogeneous, and 110 cultivars showed resistance to at least one isolate. Fifty-nine cultivars, mostly from Northwest Europe, were resistant to all three isolates were more than three times more frequently recorded in spring than in winter cultivars. Results will facilitate a rational and practical approach preferably using the set of cultivars without major resistances for both mentioned methods of breeding wheat cultivars resistant to powdery mildew. Full article
(This article belongs to the Special Issue Genetic Improvement and Breeding of Wheat)
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19 pages, 3445 KiB  
Article
Genomic Selection for End-Use Quality and Processing Traits in Soft White Winter Wheat Breeding Program with Machine and Deep Learning Models
by Karansher Singh Sandhu, Meriem Aoun, Craig F. Morris and Arron H. Carter
Biology 2021, 10(7), 689; https://0-doi-org.brum.beds.ac.uk/10.3390/biology10070689 - 20 Jul 2021
Cited by 29 | Viewed by 5319
Abstract
Breeding for grain yield, biotic and abiotic stress resistance, and end-use quality are important goals of wheat breeding programs. Screening for end-use quality traits is usually secondary to grain yield due to high labor needs, cost of testing, and large seed requirements for [...] Read more.
Breeding for grain yield, biotic and abiotic stress resistance, and end-use quality are important goals of wheat breeding programs. Screening for end-use quality traits is usually secondary to grain yield due to high labor needs, cost of testing, and large seed requirements for phenotyping. Genomic selection provides an alternative to predict performance using genome-wide markers under forward and across location predictions, where a previous year’s dataset can be used to build the models. Due to large datasets in breeding programs, we explored the potential of the machine and deep learning models to predict fourteen end-use quality traits in a winter wheat breeding program. The population used consisted of 666 wheat genotypes screened for five years (2015–19) at two locations (Pullman and Lind, WA, USA). Nine different models, including two machine learning (random forest and support vector machine) and two deep learning models (convolutional neural network and multilayer perceptron) were explored for cross-validation, forward, and across locations predictions. The prediction accuracies for different traits varied from 0.45–0.81, 0.29–0.55, and 0.27–0.50 under cross-validation, forward, and across location predictions. In general, forward prediction accuracies kept increasing over time due to increments in training data size and was more evident for machine and deep learning models. Deep learning models were superior over the traditional ridge regression best linear unbiased prediction (RRBLUP) and Bayesian models under all prediction scenarios. The high accuracy observed for end-use quality traits in this study support predicting them in early generations, leading to the advancement of superior genotypes to more extensive grain yield trails. Furthermore, the superior performance of machine and deep learning models strengthens the idea to include them in large scale breeding programs for predicting complex traits. Full article
(This article belongs to the Special Issue Genetic Improvement and Breeding of Wheat)
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19 pages, 2562 KiB  
Article
Labelling Selective Sweeps Used in Durum Wheat Breeding from a Diverse and Structured Panel of Landraces and Cultivars
by Jose Miguel Soriano, Carolina Sansaloni, Karim Ammar and Conxita Royo
Biology 2021, 10(4), 258; https://0-doi-org.brum.beds.ac.uk/10.3390/biology10040258 - 24 Mar 2021
Cited by 6 | Viewed by 2335
Abstract
A panel of 387 durum wheat genotypes including Mediterranean landraces and modern cultivars was characterized with 46,161 diversity arrays technology (DArTseq) markers. Analysis of population structure uncovered the existence of five subpopulations (SP) related to the pattern of migration of durum wheat from [...] Read more.
A panel of 387 durum wheat genotypes including Mediterranean landraces and modern cultivars was characterized with 46,161 diversity arrays technology (DArTseq) markers. Analysis of population structure uncovered the existence of five subpopulations (SP) related to the pattern of migration of durum wheat from the domestication area to the west of the Mediterranean basin (SPs 1, 2, and 3) and further improved germplasm (SPs 4 and 5). The total genetic diversity (HT) was 0.40 with a genetic differentiation (GST) of 0.08 and a mean gene flow among SPs of 6.02. The lowest gene flow was detected between SP 1 (presumably the ancient genetic pool of the panel) and SPs 4 and 5. However, gene flow from SP 2 to modern cultivars was much higher. The highest gene flow was detected between SP 3 (western Mediterranean germplasm) and SP 5 (North American and European cultivars). A genome wide association study (GWAS) approach using the top ten eigenvectors as phenotypic data revealed the presence of 89 selective sweeps, represented as quantitative trait loci (QTL) hotspots, widely distributed across the durum wheat genome. A principal component analysis (PCoA) using 147 markers with −log10p > 5 identified three regions located on chromosomes 2A, 2B and 3A as the main drivers for differentiation of Mediterranean landraces. Gene flow between SPs offers clues regarding the putative use of Mediterranean old durum germplasm by the breeding programs represented in the structure analysis. EigenGWAS identified selective sweeps among landraces and modern cultivars. The analysis of the corresponding genomic regions in the ‘Zavitan’, ‘Svevo’ and ‘Chinese Spring’ genomes discovered the presence of important functional genes including Ppd, Vrn, Rht, and gene models involved in important biological processes including LRR-RLK, MADS-box, NAC, and F-box. Full article
(This article belongs to the Special Issue Genetic Improvement and Breeding of Wheat)
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