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Molecular Genetics and Plant Breeding, 5th Edition

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 4184

Special Issue Editor

Special Issue Information

Dear Colleagues,

This Special Issue is a continuation of our previous Special Issue “Molecular Genetics and Plant Breeding 4.0”(https://www.mdpi.com/journal/ijms/special_issues/ZAM60GJ3Q7).

Plant breeding is a historical academic discipline which laid the foundations of modern agriculture. The principles of classical breeding are still the nucleus of modern breeding science and industry. On the other hand, recent methodological advancements in genomics, biotechnology, molecular biology, and bioinformatics have revolutionized the area of plant breeding and its linkages with related disciplines. These developments have opened new interdisciplinary areas of plant breeding with quantitative genetics, genomics, agro-biotechnology, and bioinformatics.

This Special Issue will focus on innovative research on the exploration and utilization of crop biodiversity for improving essential breeding traits using molecular techniques and to replenish the genetic potential of the cultivated gene pool for yield and sustainability.

Prof. Dr. Hai Du
Guest Editor

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Keywords

  • crop biodiversity
  • wild accessions
  • molecular breeding
  • QTL and gene mapping
  • comparative genomics
  • drought stress adaptation
  • disease resistance
  • yield and sustainability
  • GWAS mapping
  • predictive breeding
  • genomic prediction

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Published Papers (5 papers)

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Research

15 pages, 3332 KiB  
Article
The Pentatricopeptide Repeat Protein OsPPR674 Regulates Rice Growth and Drought Sensitivity by Modulating RNA Editing of the Mitochondrial Transcript ccmC
by Jinglei Li, Longhui Zhang, Chenyang Li, Weijun Chen, Tiankang Wang, Lvni Tan, Yingxin Qiu, Shufeng Song, Bin Li and Li Li
Int. J. Mol. Sci. 2025, 26(6), 2646; https://doi.org/10.3390/ijms26062646 - 14 Mar 2025
Viewed by 417
Abstract
The P-type pentatricopeptide repeat (PPR) proteins are crucial for RNA editing and post-transcriptional regulation in plant organelles, particularly mitochondria. This study investigates the role of OsPPR674 in rice, focusing on its function in mitochondrial RNA editing. Using CRISPR/Cas9 technology, we generated ppr674 mutant [...] Read more.
The P-type pentatricopeptide repeat (PPR) proteins are crucial for RNA editing and post-transcriptional regulation in plant organelles, particularly mitochondria. This study investigates the role of OsPPR674 in rice, focusing on its function in mitochondrial RNA editing. Using CRISPR/Cas9 technology, we generated ppr674 mutant and examined its phenotypic and molecular characteristics. The results indicate that ppr674 exhibits reduced plant height, decreased seed-setting rate, and poor drought tolerance. Further analysis revealed that in the ppr674 mutant, RNA editing at the 299th nucleotide position of the mitochondrial ccmC gene (C-to-U conversion) was abolished. REMSAs showed that GST-PPR674 specifically binds to RNA probes targeting this ccmC-299 site, confirming its role in this editing process. In summary, these results suggest that OsPPR674 plays a pivotal role in mitochondrial RNA editing, emphasizing the significance of PPR proteins in organelle function and plant development. Full article
(This article belongs to the Special Issue Molecular Genetics and Plant Breeding, 5th Edition)
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19 pages, 2872 KiB  
Article
Identification of Quantitative Trait Loci for Node Number, Pod Number, and Seed Number in Soybean
by Chunlei Zhang, Bire Zha, Rongqiang Yuan, Kezhen Zhao, Jianqiang Sun, Xiulin Liu, Xueyang Wang, Fengyi Zhang, Bixian Zhang, Sobhi F. Lamlom, Honglei Ren and Lijuan Qiu
Int. J. Mol. Sci. 2025, 26(5), 2300; https://doi.org/10.3390/ijms26052300 - 5 Mar 2025
Viewed by 509
Abstract
Optimizing soybean yield remains a crucial challenge in meeting global food security demands. In this study, we report a comprehensive genetic analysis of yield-related traits in soybeans using a recombinant inbred line (RIL) population derived from crosses between ‘Qihuang 34’ (GH34) and ‘Dongsheng [...] Read more.
Optimizing soybean yield remains a crucial challenge in meeting global food security demands. In this study, we report a comprehensive genetic analysis of yield-related traits in soybeans using a recombinant inbred line (RIL) population derived from crosses between ‘Qihuang 34’ (GH34) and ‘Dongsheng 16′ (DS16). Phenotypic analysis across two years (2023–2024) revealed significant variations between parental lines. Through high-density genetic mapping with 6297 SLAF markers spanning 2945.26 cM across 20 chromosomes, we constructed a genetic map with an average marker distance of 0.47 cM and 99.17% of gaps under 5 cM. QTL analysis identified ten significant loci across both years: in 2023, we detected six QTLs, including a major main stem node number (MSNN) QTL on chromosome 19 (LOD = 22.59, PVE = 24.57%), two seed number (SN) QTLs on chromosomes 14 and 18 (LOD = 2.52–2.85, PVE = 7.35% combined), and one pod number (PN) QTL on chromosome 20 (LOD = 4.68, PVE = 5.85%). The 2024 analysis revealed four major QTLs, notably a cluster on chromosome 19 harboring significant loci for MSNN (LOD = 37.92, PVE = 43.59%), PN (LOD = 18.16, PVE = 23.02%), and SN (LOD = 15.24, PVE = 19.59%). Within the stable chromosome 19 region, we identified seventeen candidate genes involved in crucial developmental processes. Gene expression analysis revealed distinct temporal patterns between parental lines during vegetative and reproductive stages, with GH34 showing dramatically higher expression of key reproductive genes Glyma.19G201300 and Glyma.19G201400 during the R1 stage. Our findings provide new insights into the genetic architecture of soybean stem node development and yield components, offering multiple promising targets for molecular breeding programs aimed at crop improvement. Full article
(This article belongs to the Special Issue Molecular Genetics and Plant Breeding, 5th Edition)
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25 pages, 7090 KiB  
Article
Combined Bulked Segregant Analysis-Sequencing and Transcriptome Analysis to Identify Candidate Genes Associated with Cold Stress in Brassica napus L
by Jiayi Jiang, Rihui Li, Kaixuan Wang, Yifeng Xu, Hejun Lu and Dongqing Zhang
Int. J. Mol. Sci. 2025, 26(3), 1148; https://doi.org/10.3390/ijms26031148 - 28 Jan 2025
Viewed by 794
Abstract
Cold tolerance in rapeseed is closely related to its growth, yield, and geographical distribution. However, the mechanisms underlying cold resistance in rapeseed remain unclear. This study aimed to explore cold resistance genes and provide new insights into the molecular mechanisms of cold resistance [...] Read more.
Cold tolerance in rapeseed is closely related to its growth, yield, and geographical distribution. However, the mechanisms underlying cold resistance in rapeseed remain unclear. This study aimed to explore cold resistance genes and provide new insights into the molecular mechanisms of cold resistance in rapeseed. Rapeseed M98 (cold-sensitive line) and D1 (cold-tolerant line) were used as parental lines. In their F2 population, 30 seedlings with the lowest cold damage levels and 30 with the highest cold damage levels were selected to construct cold-tolerant and cold-sensitive pools, respectively. The two pools and parental lines were analyzed using bulk segregant sequencing (BSA-seq). The G’-value analysis indicated a single peak on Chromosome C09 as the candidate interval, which had a 2.59 Mb segment with 69 candidate genes. Combined time-course and weighted gene co-expression network analyses were performed at seven time points to reveal the genetic basis of the two-parent response to low temperatures. Twelve differentially expressed genes primarily involved in plant cold resistance were identified. Combined BSA-seq and transcriptome analysis revealed BnaC09G0354200ZS, BnaC09G0353200ZS, and BnaC09G0356600ZS as the candidate genes. Quantitative real-time PCR validation of the candidate genes was consistent with RNA-seq. This study facilitates the exploration of cold tolerance mechanisms in rapeseed. Full article
(This article belongs to the Special Issue Molecular Genetics and Plant Breeding, 5th Edition)
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18 pages, 8509 KiB  
Article
The Potassium Utilization Gene Network in Brassica napus and Functional Validation of BnaZSHAK5.2 Gene in Response to Potassium Deficiency
by Xingzhi Qian, Hanrong Liu, Jie Zhou, Wenyu Zhu, Liping Hu, Xiaoya Yang, Xiwen Yang, Huiyan Zhao, Huafang Wan, Nengwen Yin, Jiana Li, Cunmin Qu and Hai Du
Int. J. Mol. Sci. 2025, 26(2), 794; https://doi.org/10.3390/ijms26020794 - 18 Jan 2025
Viewed by 656
Abstract
Potassium, an essential inorganic cation, is crucial for the growth of oil crops like Brassica napus L. Given the scarcity of potassium in soil, enhancing rapeseed’s potassium utilization efficiency is of significant importance. This study identified 376 potassium utilization genes in the genome [...] Read more.
Potassium, an essential inorganic cation, is crucial for the growth of oil crops like Brassica napus L. Given the scarcity of potassium in soil, enhancing rapeseed’s potassium utilization efficiency is of significant importance. This study identified 376 potassium utilization genes in the genome of B. napus ZS11 through homologous retrieval, encompassing 7 functional and 12 regulatory gene families. These genes are unevenly distributed across 19 chromosomes, and the proteins encoded by these genes are mainly localized in the cell membrane, vacuoles, and nucleus. Microsynteny analysis highlighted the role of small-scale replication events and allopolyploidization in the expansion of potassium utilization genes, identifying 77 distinct types of cis-acting elements within their promoter regions. The regulatory mechanisms of potassium utilization genes were provided by analyses of transcription factors, miRNA, and protein interaction networks. Under low potassium stress, the potassium utilization genes, particularly those belonging to the KUP and CBL families, demonstrate pronounced co-expression. RNA-seq and RT-qPCR analysis identified the BnaZSHAK5.2 gene, which is a high-affinity potassium ion transporter, playing a crucial role in the stress response to potassium deficiency in B. napus, as its expression is strongly induced by low potassium stress. A functional complementation study demonstrates that the BnaZSHAK5.2 gene could rescue the primary root growth of the Athak5 mutant under low potassium conditions, confirming its role in response to low potassium stress by sustaining root development. Full article
(This article belongs to the Special Issue Molecular Genetics and Plant Breeding, 5th Edition)
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16 pages, 2564 KiB  
Article
Genome-Wide Association and Genomic Prediction of Alfalfa (Medicago sativa L.) Biomass Yield Under Drought Stress
by Cesar A. Medina, Julie Hansen, Jamie Crawford, Donald Viands, Manoj Sapkota, Zhanyou Xu, Michael D. Peel and Long-Xi Yu
Int. J. Mol. Sci. 2025, 26(2), 608; https://doi.org/10.3390/ijms26020608 - 13 Jan 2025
Cited by 1 | Viewed by 1240
Abstract
Developing drought-resistant alfalfa (Medicago sativa L.) that maintains high biomass yield is a key breeding goal to enhance productivity in water-limited areas. In this study, 424 alfalfa breeding families were analyzed to identify molecular markers associated with biomass yield under drought stress [...] Read more.
Developing drought-resistant alfalfa (Medicago sativa L.) that maintains high biomass yield is a key breeding goal to enhance productivity in water-limited areas. In this study, 424 alfalfa breeding families were analyzed to identify molecular markers associated with biomass yield under drought stress and to predict high-merit plants. Biomass yield was measured from 18 harvests from 2020 to 2023 in a field trial with deficit irrigation. A total of 131 significant markers were associated with biomass yield, with 80 markers specifically linked to yield under drought stress; among these, 19 markers were associated with multiple harvests. Finally, genomic best linear unbiased prediction (GBLUP) was employed to obtain predictive accuracies (PAs) and genomic estimated breeding values (GEBVs). Removing low-informative SNPs [SNPs with p-values > 0.05 from the additive Genome-Wide Association (GWAS) model] for GBLUP increased PA by 47.3%. The high number of markers associated with yield under drought stress and the highest PA (0.9) represent a significant achievement in improving yield under drought stress in alfalfa. Full article
(This article belongs to the Special Issue Molecular Genetics and Plant Breeding, 5th Edition)
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