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Improvement and Genetic Analysis of Germplasm Resources in Major Crops—2nd...
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Improvement and Genetic Analysis of Germplasm Resources in Major Crops—2nd Edition

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Genetics, Genomics and Biotechnology".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 1709

Special Issue Editors

Dr. Kun Li

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Guest Editor
Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Interests: genetics, germplasm, maize breeding
Special Issues, Collections and Topics in MDPI journals
Dr. Shutu Xu

E-Mail Website
Guest Editor
College of Agronomy, Northwest A&F University, Yangling 712100, China
Interests: germplasm improvement; molecular genetics; maize breeding
Special Issues, Collections and Topics in MDPI journals
Dr. Zhanying Zhang

E-Mail Website
Guest Editor
Department of Crop Genetics and Breeding,China Agricultural University, Beijing 100193, China
Interests: rice grain yield; lodging resistance
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Tingting Guo

E-Mail Website
Guest Editor
Department of Plant Genetics and Breeding, Huazhong Agricultural University, Wuhan 430070, China
Interests: quantitative genetics, genomics, enviromics, maize breeding
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Germplasm resources of major crops have become increasingly important in terms of food security, not only being the core during crop breeding but also a key factor for crop genetics and biology, which can be used to dissect the genetic mechanism of important traits and feedback to germplasm improvement. However, the genetic background of commercial varieties is restricted; many newer varieties are developed from restricted elite inbred lines or their derived materials. Thus, it is necessary to expand genetic diversity in major crops.

Along with the development of technology, including next-generation sequencing and genomics, high-throughput phenotypes, and the modified analytical method, significant advancements have enabled us to understand the regulation mechanism of the important traits, such as agronomic traits, biotic and abiotic stress, seed quality and metabolism. Some effective molecular markers have been explored and applied with the aim of achieving germplasm improvement. The application of genome-wide selection technology has accelerated progress towards this goal as well as breeding.

Thus, Plants has organized a Special Issue on “Improvement and Genetic Analysis of Germplasm Resources in Major Crops” to provide an excellent platform for advancements in germplasm improvement and genetics of important traits in the breeding process.

Dr. Kun Li
Dr. Shutu Xu
Dr. Zhanying Zhang
Prof. Dr. Tingting Guo
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. Plants is an international peer-reviewed open access semimonthly 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

  • germplasm improvement
  • genetics mechanism
  • genome-wide selection
  • major crops

Published Papers (2 papers)

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Research

13 pages, 1097 KiB  
Article
Evaluating and Predicting the Performance of Sorghum Lines in an Elite by Exotic Backcross-Nested Association Mapping Population
by Daniel Crozier, Noah D. Winans, Leo Hoffmann, Jr., Nikhil Y. Patil, Patricia E. Klein, Robert R. Klein and William L. Rooney
Plants 2024, 13(6), 879; https://doi.org/10.3390/plants13060879 - 19 Mar 2024
Viewed by 736
Abstract
Maintaining or introducing genetic diversity into plant breeding programs is necessary for continual genetic gain; however, diversity at the cost of reduced performance is not something sought by breeders. To this end, backcross-nested association mapping (BC-NAM) populations, in which the recurrent parent is [...] Read more.
Maintaining or introducing genetic diversity into plant breeding programs is necessary for continual genetic gain; however, diversity at the cost of reduced performance is not something sought by breeders. To this end, backcross-nested association mapping (BC-NAM) populations, in which the recurrent parent is an elite line, can be employed as a strategy to introgress diversity from unadapted accessions while maintaining agronomic performance. This study evaluates (i) the hybrid performance of sorghum lines from 18 BC1-NAM families and (ii) the potential of genomic prediction to screen lines from BC1-NAM families for hybrid performance prior to phenotypic evaluation. Despite the diverse geographical origins and agronomic performance of the unadapted parents for BC1-NAM families, many BC1-derived lines performed significantly better in the hybrid trials than the elite recurrent parent, R.Tx436. The genomic prediction accuracies for grain yield, plant height, and days to mid-anthesis were acceptable, but the prediction accuracies for plant height were lower than expected. While the prediction accuracies increased when including more individuals in the training set, improvements tended to plateau between two and five lines per family, with larger training sets being required for more complex traits such as grain yield. Therefore, genomic prediction models can be optimized in a large BC1-NAM population with a relatively low fraction of individuals needing to be evaluated. These results suggest that genomic prediction is an effective method of pre-screening lines within BC1-NAM families prior to evaluation in extensive hybrid field trials. Full article
(This article belongs to the Special Issue Improvement and Genetic Analysis of Germplasm Resources in Major Crops—2nd Edition)
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10 pages, 477 KiB  
Article
Identification of Quantitative Trait Loci (QTL) for Sucrose and Protein Content in Soybean Seed
by Daniel R. Jamison, Pengyin Chen, Navam S. Hettiarachchy, David M. Miller and Ehsan Shakiba
Plants 2024, 13(5), 650; https://doi.org/10.3390/plants13050650 - 27 Feb 2024
Viewed by 678
Abstract
Protein and sugar content are important seed quality traits in soybean because they improve the value and sustainability of soy food and feed products. Thus, identifying Quantitative Trait Loci (QTL) for soybean seed protein and sugar content can benefit plant breeders and the [...] Read more.
Protein and sugar content are important seed quality traits in soybean because they improve the value and sustainability of soy food and feed products. Thus, identifying Quantitative Trait Loci (QTL) for soybean seed protein and sugar content can benefit plant breeders and the soybean market by accelerating the breeding process via marker-assisted selection. For this study, a population of recombinant inbred lines (RILs) was developed from a cross between R08-3221 (high protein and low sucrose) and R07-2000 (high sucrose and low protein). Phenotypic data for protein content were taken from the F2:4 and F2:5 generations. The DA7250 NIR analyzer and HPLC instruments were used to analyze total seed protein and sucrose content. Genotypic data were generated using analysis via the SoySNP6k chip. A total of four QTLs were identified in this study. Two QTLs for protein content were located on chromosomes 11 and 20, and two QTLs associated with sucrose content were located on chromosomes 14 and. 11, the latter of which co-localized with detected QTLs for protein, explaining 10% of the phenotypic variation for protein and sucrose content in soybean seed within the study population. Soybean breeding programs can use the results to improve soybean seed quality. Full article
(This article belongs to the Special Issue Improvement and Genetic Analysis of Germplasm Resources in Major Crops—2nd Edition)
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