Gene Editing and Molecular Markers for Crops Genetics and Breeding

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Genotype Evaluation and Breeding".

Deadline for manuscript submissions: closed (20 May 2024) | Viewed by 1103

Special Issue Editors


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Guest Editor
Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou 225009, China
Interests: rice; quantitative trait loci (QTL); gene cloning; molecular breeding; gene editing

E-Mail Website
Guest Editor
College of Agriculture, Shandong Agricultural University, Taian 271018, China
Interests: maize; quantitative trait loci (QTL); functional genomics; comparative genomics; bioinfomatics

Special Issue Information

Dear Colleagues,

Improving crop production is facing great challenges due to global population explosion and climate change, and the yield of major crops including rice, wheat, maize and soybean will need to double to satisfy the diet demands by 2050. The advent of new breeding techniques provides an opportunity to develop crops with higher production. Molecular markers are well-known tools for breeding selection, and developing advanced markers is important for both foreground and background selection, such as functional markers directly recognizing the causative sequence variations and non-labor intensive markers with higher genotyping efficiency. Gene editing is becoming the most popular technique to create mutants for both genetic study and crop breeding, and trait improvement of a specific variety can be achieved quickly in a short time period. Therefore, combinational use of marker selection and gene editing will be the best way to break through the ceiling of crop production.

This Special Issue focuses on various dimensions about efficient use of molecular markers or gene editing for crop genetics and breeding research. Submissions of molecular marker research could cover the development of functional markers targeting important genes and middle- or high-throughput marker packages suitable for population discrimination, gene mapping and breeding selection. Gene editing research could include the creation of beneficial alleles of known genes or function validation of unknown genes and clarifying the phenotypic effect of different mutations. We also welcome case studies of efficient crop breeding using either of the techniques described above. We accept both research and review papers matching with the topic.

Prof. Dr. Lin Zhang
Dr. Guobin Zhang
Guest Editors

Manuscript Submission Information

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Keywords

  • crops
  • molecular makers
  • gene editing
  • functional markers
  • association mapping
  • QTL analysis
  • marker-assisted selection (MAS) breeding
  • CRISPR/Cas9
  • base editing

Published Papers (1 paper)

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Research

14 pages, 2297 KiB  
Article
Fine-Tuning Quantitative Trait Loci Identified in Immortalized F2 Population Are Essential for Genomic Prediction of Hybrid Performance in Maize
by Pingxi Wang, Xingye Ma, Xining Jin, Xiangyuan Wu, Xiaoxiang Zhang, Huaisheng Zhang, Hui Wang, Hongwei Zhang, Junjie Fu, Yuxin Xie and Shilin Chen
Agriculture 2024, 14(3), 340; https://doi.org/10.3390/agriculture14030340 - 21 Feb 2024
Viewed by 772
Abstract
Maize breeding is greatly affected by hybrid vigor, a phenomenon that hybrids exhibit superior performance than parental lines. The immortalized F2 population (IMF2) is ideal for the genetic dissection and prediction of hybrid performance. Here, in this study, we conducted [...] Read more.
Maize breeding is greatly affected by hybrid vigor, a phenomenon that hybrids exhibit superior performance than parental lines. The immortalized F2 population (IMF2) is ideal for the genetic dissection and prediction of hybrid performance. Here, in this study, we conducted the QTL mapping and genomic prediction of six traits related to plant architecture using an IMF2 population. Broad-sense heritability of these traits ranged from 0.85 to 0.94. Analysis of genetic effects showed that additive variance was the main contributor to phenotypic variations. The mapping of quantitative trait loci (QTLs) revealed 10 to 16 QTLs (including pleiotropic loci and epistatic QTLs) for the six traits. Additionally, we identified 15 fine-tuning QTLs for plant height (PH). For genomic prediction (GP), the model of additive and dominance (AD) exhibited higher prediction accuracy than those fitting general combining ability (GCA) and its combination with special combining ability (SCA) effects for all tested traits. And adding the epistasis (E) effect into the AD model did not significantly increase its prediction accuracy. Moreover, the identified 15 fine-tuning QTLs of PH, which exerted large genomic prediction effects, were verified by the marker effect of GP. Our results not only provide an approach for the fine-mapping of fine-tuning QTLs but also serve as references for GP breeding in crops. Full article
(This article belongs to the Special Issue Gene Editing and Molecular Markers for Crops Genetics and Breeding)
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