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Genes
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Applying Genome Sequencing Technologies to Crop Breeding
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Applying Genome Sequencing Technologies to Crop Breeding

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Plant Genetics and Genomics".

Deadline for manuscript submissions: closed (20 February 2022) | Viewed by 9418

Special Issue Editors

Dr. Sukhjiwan Kaur

E-Mail Website
Guest Editor
Biosciences Research, Agriculture Victoria, AgriBio, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
Interests: plant genetics and genomics; next-generation sequencing; high-throughput genotyping and phenotyping; molecular breeding; genomic selection
Special Issues, Collections and Topics in MDPI journals
Dr. Boas Pucker

E-Mail Website
Guest Editor
Plant Biotechnology and Bioinformatics, Faculty of Life Sciences, Technische Universität Braunschweig, 38106 Braunschweig, Germany
Interests: genome research; transcriptomics/RNA-Seq; evolution; plant species
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Genomics assisted crop breeding is one of the key contributors to increased crop productivity in order to meet the ever-growing food demand. Development of efficient breeding strategies that incorporate genomic technologies and high-throughput phenotyping to better utilize genetic variation and perform informed breeding selections paves the way to an increased rate of genetic gain. Advancements in next generation sequencing (NGS) technologies over the last decade have opened up unprecedented opportunities to explore the relationship between genotype and phenotype with greater precision. As the cost of sequencing has decreased, breeders have started to utilize NGS to sequence large populations of plants, increasing the resolution of gene and quantitative trait locus (QTL) discovery and providing the basis for modelling complex genotype–phenotype relationships at the whole-genome level.

The focus of this Special Issue is on applications of next generation sequencing technologies to assist crop breeding. Submissions from research groups working on orphan crops are welcome. This Special Issue also covers the latest developments in bioinformatics with a connection to crop genomics and breeding projects. Submissions on (but not limited to) the following topics are invited: (1) application of genomic technologies to identify novel alleles; (2) genomic selection for enhanced genetic gain and crop productivity; (3) integration of useful alleles from unadapted germplasm into elite background using molecular tools; (4) population genetics studies for crop adaptation and domestication; and (5) cost effective genotyping tools for breeding.

Dr. Sukhjiwan Kaur
Dr. Boas Pucker
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. Genes 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

  • genome assembly
  • short and long read sequencing
  • next generation sequencing
  • genotyping-by-sequencing (GBS)
  • genomic selection
  • predictive breeding
  • high-throughput genotyping

Published Papers (3 papers)

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Research

12 pages, 11516 KiB  
Article
Identification of Quantitative Trait Loci Associated with Seed Protein Concentration in a Pea Recombinant Inbred Line Population
by Junsheng Zhou, Krishna Kishore Gali, Ambuj Bhushan Jha, Bunyamin Tar’an and Thomas D. Warkentin
Genes 2022, 13(9), 1531; https://doi.org/10.3390/genes13091531 - 26 Aug 2022
Cited by 3 | Viewed by 1688
Abstract
This research aimed to identify quantitative trait loci (QTLs) associated with seed protein concentration in a recombinant inbred line (RIL) population of pea and aimed to validate the identified QTLs using chromosome segment-introgressed lines developed by recurrent backcrossing. PR-25, an RIL population consisting [...] Read more.
This research aimed to identify quantitative trait loci (QTLs) associated with seed protein concentration in a recombinant inbred line (RIL) population of pea and aimed to validate the identified QTLs using chromosome segment-introgressed lines developed by recurrent backcrossing. PR-25, an RIL population consisting of 108 F7 bulked lines derived from a cross between CDC Amarillo (yellow cotyledon) and CDC Limerick (green cotyledon), was used in this research. The RIL population was genotyped using an Axiom 90K SNP array. A total of 10,553 polymorphic markers were used for linkage map construction, after filtering for segregation distortion and missing values. The linkage map represents 901 unique loci on 11 linkage groups which covered a map distance of 855.3 Centimorgans. Protein concentration was assessed using near-infrared (NIR) spectroscopy of seeds harvested from field trials in seven station-years in Saskatchewan, Canada, during the 2019–2021 field seasons. Three QTLs located on chromosomes 2, 3 and 5 were identified to be associated with seed protein concentration. These QTLs explained 22%, 11% and 17% of the variation for protein concentration, respectively. The identified QTLs were validated by introgression lines, developed by marker-assisted selection of backcross lines for introgression of corresponding chromosome segments (~1/4 chromosome) harboring the QTL regions. Introgression line PR-28-7, not carrying any protein-related QTLs identified in this study, was 4.7% lower in protein concentration than CDC Amarillo, the lower protein parent of PR-25 which carried one identified protein-related QTL. The SNP markers located at the peak of the three identified QTLs will be converted into breeder-friendly KASP assays, which will be used for the selection of high-protein lines from segregating populations. Full article
(This article belongs to the Special Issue Applying Genome Sequencing Technologies to Crop Breeding)
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19 pages, 3150 KiB  
Article
Different Shades of Kale—Approaches to Analyze Kale Variety Interrelations
by Christoph Hahn, Nicholas P. Howard and Dirk C. Albach
Genes 2022, 13(2), 232; https://doi.org/10.3390/genes13020232 - 26 Jan 2022
Cited by 6 | Viewed by 3242
Abstract
Brassica oleracea is a vegetable crop with an amazing morphological diversity. Among the various crops derived from B. oleracea, kale has been in the spotlight globally due to its various health-benefitting compounds and many different varieties. Knowledge of the existing genetic diversity [...] Read more.
Brassica oleracea is a vegetable crop with an amazing morphological diversity. Among the various crops derived from B. oleracea, kale has been in the spotlight globally due to its various health-benefitting compounds and many different varieties. Knowledge of the existing genetic diversity is essential for the improved breeding of kale. Here, we analyze the interrelationships, population structures, and genetic diversity of 72 kale and cabbage varieties by extending our previous diversity analysis and evaluating the use of summed potential lengths of shared haplotypes (SPLoSH) as a new method for such analyses. To this end, we made use of the high-density Brassica 60K SNP array, analyzed SNPs included in an available Brassica genetic map, and used these resources to generate and evaluate the information from SPLoSH data. With our results we could consistently differentiate four groups of kale across all analyses: the curly kale varieties, Italian, American, and Russian varieties, as well as wild and cultivated types. The best results were achieved by using SPLoSH information, thus validating the use of this information in improving analyses of interrelations in kale. In conclusion, our definition of kale includes the curly varieties as the kales in a strict sense, regardless of their origin. These results contribute to a better understanding of the huge diversity of kale and its interrelations. Full article
(This article belongs to the Special Issue Applying Genome Sequencing Technologies to Crop Breeding)
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20 pages, 3824 KiB  
Article
Genome-Wide Association Mapping of Crown and Brown Rust Resistance in Perennial Ryegrass
by Mattia Fois, Andrea Bellucci, Marta Malinowska, Morten Greve, Anja Karine Ruud and Torben Asp
Genes 2022, 13(1), 20; https://doi.org/10.3390/genes13010020 - 22 Dec 2021
Cited by 1 | Viewed by 3493
Abstract
A population of 239 perennial ryegrass (Lolium perenne L.) genotypes was analyzed to identify marker-trait associations for crown rust (Puccinia coronata f. sp. lolii) and brown rust (Puccinia graminis f. sp. loliina) resistance. Phenotypic data from field trials [...] Read more.
A population of 239 perennial ryegrass (Lolium perenne L.) genotypes was analyzed to identify marker-trait associations for crown rust (Puccinia coronata f. sp. lolii) and brown rust (Puccinia graminis f. sp. loliina) resistance. Phenotypic data from field trials showed a low correlation (r = 0.17) between the two traits. Genotypes were resequenced, and a total of 14,538,978 SNPs were used to analyze population structure, linkage disequilibrium (LD), and for genome-wide association study. The SNP heritability (h2SNP) was 0.4 and 0.8 for crown and brown rust resistance, respectively. The high-density SNP dataset allowed us to estimate LD decay with the highest possible precision to date for perennial ryegrass. Results showed a low LD extension with a rapid decay of r2 value below 0.2 after 520 bp on average. Additionally, QTL regions for both traits were detected, as well as candidate genes by applying Genome Complex Trait Analysis and Multi-marker Analysis of GenoMic Annotation. Moreover, two significant genes, LpPc6 and LpPl6, were identified for crown and brown rust resistance, respectively, when SNPs were aggregated to the gene level. The two candidate genes encode proteins with phosphatase activity, which putatively can be induced by the host to perceive, amplify and transfer signals to downstream components, thus activating a plant defense response. Full article
(This article belongs to the Special Issue Applying Genome Sequencing Technologies to Crop Breeding)
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