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Plants
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Crop Genetic Mechanisms and Breeding Improvement
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Crop Genetic Mechanisms and Breeding Improvement

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

Deadline for manuscript submissions: closed (20 March 2025) | Viewed by 3990

Special Issue Editors

Dr. Hua Zhong

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Guest Editor
Population Sciences in the Pacific Program, University of Hawaiʻi at Mānoa, Honolulu, HI 96813, USA
Interests: population genetics; genomics; bioinformatics; post-GWAS
Special Issues, Collections and Topics in MDPI journals
Dr. Weilong Kong

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Guest Editor
Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
Interests: crop; genome; QTL-mapping; GWAS
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The exploration of crop genetics and breeding holds the potential to revolutionize agricultural practices by creating improved crop varieties that exhibit higher yields, better nutritional profiles, and enhanced tolerance to environmental challenges. As the history of agriculture progressed, selective breeding was introduced for the purpose of combining beneficial loci in germplasm. Identifying specific genetic determinants of stress adaptation and precisely introducing them into elite varieties is an effective new paradigm. The combination of contemporary genomics and genetic techniques, along with advancements in accurate phenotyping and breeding methods, is anticipated to enhance the understanding of the genes and metabolic pathways responsible for conferring abiotic stress resistance in crops.

This special issue gathers cutting-edge research on deciphering the intricate genetic pathways and mechanisms underlying crop traits, which are crucial for sustainable food production in the face of global challenges such as climate change and growing populations. Contributions to this issue shed light on the interplay between crop genomes, diverse omics technologies, and advanced breeding methodologies to develop crops that thrive in changing environmental conditions.

Dr. Hua Zhong
Dr. Weilong Kong
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

  • crop breeding
  • population genetics
  • genome
  • multi-omics
  • Genome Wide Association Study (GWAS)
  • Quantitative trait loci (QTL)-mapping
  • abiotic stress

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Published Papers (3 papers)

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Research

30 pages, 20660 KB  
Article
Comprehensive Identification of Key Genes Responsible for Leaf Senescence of Rice (Oryza sativa L.) by WGCNA Using Two Independent Aging Datasets
by Xiaoya Zhou, Hua Zhong, Chuntian Yu and Zhaohai Wang
Plants 2025, 14(17), 2704; https://doi.org/10.3390/plants14172704 - 30 Aug 2025
Viewed by 667
Abstract
Leaf senescence is the final stage of plant leaf development, closely related to the yield and quality of cereal crops. However, the molecular regulatory mechanism of rice (Oryza sativa L.) leaf senescence is not yet very clear. This study conducted weighted gene [...] Read more.
Leaf senescence is the final stage of plant leaf development, closely related to the yield and quality of cereal crops. However, the molecular regulatory mechanism of rice (Oryza sativa L.) leaf senescence is not yet very clear. This study conducted weighted gene co-expression network analysis (WGCNA) using two independent senescence-related transcriptome datasets of rice. Modules positively/negatively correlated with leaf senescence were obtained for each dataset. The additional intersection analysis screened out 180 and 248 common genes highly and positively/negatively correlated with leaf senescence. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that these identified common genes were mainly enriched in senescence-related biological processes and pathways, such as reactive oxygen metabolism, hormone pathway, cell death regulation, stimulus–response, amino acid metabolism, photosynthetic metabolism, etc. Transcription factors and studied genes were identified from these common genes, finding that transcription regulation, hormone regulation, reactive oxygen species metabolism, and photosynthesis pathways play an essential role in rice leaf senescence. Protein–protein interaction (PPI) network analysis identified 28 key genes probably involved in leaf senescence. Hub network analysis identified 68 hub genes probably participating in leaf senescence. Twelve genes from the PPI network and the hub gene network were selected for RT-qPCR validation of their expression patterns during leaf senescence. The functions of the senescence-correlated genes identified in this study are discussed in detail. These results provide valuable insights into the regulatory mechanisms of leaf senescence in rice and lay a foundation for functional research on candidate senescence genes. Full article
(This article belongs to the Special Issue Crop Genetic Mechanisms and Breeding Improvement)
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13 pages, 3258 KB  
Article
Characterization of a Major Quantitative Trait Locus for the Whiteness of Rice Grain Using Chromosome Segment Substitution Lines
by Lulu Chen, Yujia Leng, Caiyun Zhang, Xixu Li, Zhihui Ye, Yan Lu, Lichun Huang, Qing Liu, Jiping Gao, Changquan Zhang and Qiaoquan Liu
Plants 2024, 13(24), 3588; https://doi.org/10.3390/plants13243588 - 23 Dec 2024
Cited by 1 | Viewed by 906
Abstract
The whiteness of rice grains (WRG) is a key indicator of appearance quality, directly impacting its commercial value. The trait is quantitative, influenced by multiple factors, and no specific genes have been cloned to date. In this study, we first examined the correlation [...] Read more.
The whiteness of rice grains (WRG) is a key indicator of appearance quality, directly impacting its commercial value. The trait is quantitative, influenced by multiple factors, and no specific genes have been cloned to date. In this study, we first examined the correlation between the whiteness of polished rice, cooked rice, and rice flour, finding that the whiteness of rice flour significantly correlated with both polished and cooked rice. Thus, the whiteness of rice flour was chosen as the indicator of WRG in our QTL analysis. Using a set of chromosome segment substitution lines (CSSL) with japonica rice Koshihikari as the recipient and indica rice Nona Bokra as the donor, we analyzed QTLs for WRG across two growth environments and identified six WRG QTLs. Notably, qWRG9 on chromosome 9 displayed stable genetic effects in both environments. Through chromosomal segment overlapping mapping, qWRG9 was narrowed to a 1.2 Mb region. Additionally, a BC4F2 segregating population confirmed that low WRG was a dominant trait governed by the major QTL qWRG9, with a segregation ratio of low to high WRG approximating 3:1, consistent with Mendelian inheritance. Further grain quality analysis on the BC4F2 population revealed that rice grains carrying the Indica-type qWRG9 allele not only exhibited lower WRG but also had significantly higher protein content. These findings support the fine mapping of the candidate gene and provide an important QTL for improving rice grain quality through genetic improvement. Full article
(This article belongs to the Special Issue Crop Genetic Mechanisms and Breeding Improvement)
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18 pages, 1882 KB  
Article
Genome-Wide Association Study for Resistance to Phytophthora sojae in Soybean [Glycine max (L.) Merr.]
by Hee Jin You, Ruihua Zhao, Yu-Mi Choi, In-Jeong Kang and Sungwoo Lee
Plants 2024, 13(24), 3501; https://doi.org/10.3390/plants13243501 - 15 Dec 2024
Cited by 1 | Viewed by 1450
Abstract
Phytophthora sojae (Kauffman and Gerdemann) is an oomycete pathogen that threatens soybean (Glycine max L.) production worldwide. The development of soybean cultivars with resistance to this pathogen is of paramount importance for the sustainable management of the disease. The objective of this [...] Read more.
Phytophthora sojae (Kauffman and Gerdemann) is an oomycete pathogen that threatens soybean (Glycine max L.) production worldwide. The development of soybean cultivars with resistance to this pathogen is of paramount importance for the sustainable management of the disease. The objective of this study was to identify genomic regions associated with resistance to P. sojae isolate 40468 through genome-wide association analyses of 983 soybean germplasms. To elucidate the genetic basis of resistance, three statistical models were employed: the compressed mixed linear model (CMLM), Bayesian-information and linkage disequilibrium iteratively nested keyway (BLINK), and fixed and random model circulating probability unification (FarmCPU). The three models consistently identified a genomic region (3.8–5.3 Mbp) on chromosome 3, which has been previously identified as an Rps cluster. A total of 18 single nucleotide polymorphisms demonstrated high statistical significance across all three models, which were distributed in eight linkage disequilibrium (LD) blocks within the aforementioned interval. Of the eight, LD3-2 exhibited the discernible segregation of phenotypic reactions by haplotype. Specifically, over 93% of accessions with haplotypes LD3-2-F or LD3-2-G displayed resistance, whereas over 91% with LD3-2-A, LD3-2-C, or LD3-2-D exhibited susceptibility. Furthermore, the BLINK and FarmCPU models identified new genomic variations significantly associated with the resistance on several other chromosomes, indicating that the resistance observed in this panel was due to the presence of different alleles of multiple Rps genes. These findings underscore the necessity for robust statistical models to accurately detect true marker–trait associations and provide valuable insights into soybean genetics and breeding. Full article
(This article belongs to the Special Issue Crop Genetic Mechanisms and Breeding Improvement)
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