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Advances in Genome-Wide Studies of Complex Agronomic Traits in Crops
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Advances in Genome-Wide Studies of Complex Agronomic Traits in Crops

A Special Issue of Plants (ISSN 2223-7747) belonging to the section "Plant Genetics, Genomics and Biotechnology".

Deadline for manuscript submissions: closed (31 July 2026) | Viewed by 6502

Editors

Dr. Hantao Wang

E-Mail Website
Guest Editor
State Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455000, China
Interests: molecular mechanisms; regulatory network; QTL mapping; genome-wide association study
Special Issues, Collections and Topics in MDPI journals
Dr. Chao Shen

E-Mail Website
Guest Editor
College of Biological and Food Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China
Interests: genomics; domestication; population genetics; QTL mapping; genome-wide association study; complex traits
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Understanding the genetic basis of complex agronomic traits is essential for accelerating crop improvement in the face of climate change, food insecurity, and sustainability challenges. This Special Issue aims to highlight recent advances in genome-wide studies, including GWAS, QTL mapping, transcriptome-wide association studies (TWASs), and genomic prediction, that have unraveled the genetic architecture of yield, stress resistance, flowering time, nutrient use efficiency, and other key traits in crops. We welcome the submission of original research, reviews, and methodological advances that apply multi-omics integration, artificial intelligence (AI), machine learning (ML), or population genomics to decipher complex traits. Studies focusing on both major and underutilized crops, as well as comparative approaches across species, are encouraged. By compiling cutting-edge findings in this area, this issue aims to facilitate knowledge exchange and promote innovative strategies for crop genetic improvement.

Dr. Hantao Wang
Dr. Chao Shen
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • genome-wide association study (GWAS)
  • quantitative trait loci (QTL)
  • complex traits
  • artificial intelligence (AI)
  • machine learning
  • crop genomics
  • multi-omics integration
  • genomic prediction
  • agronomic traits
  • population genomics

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Published Papers (6 papers)

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Research

15 pages, 7127 KB  
Article
Functional Analysis of GhRNG1L Reveals Its Positive Role in Drought Tolerance Mediated by GhDREB2B in Cotton
by Mengyan Wang, Li An, Xiaokang Fu, Chao Shen, Jianhua Lu, Hongmei Wu, Yanna Gao, Nan Zhang, Guoli Song and Hantao Wang
Plants 2026, 15(17), 2636; https://doi.org/10.3390/plants15172636 - 28 Aug 2026
Viewed by 275
Abstract
Drought stress is a major abiotic factor limiting cotton yield and quality. RING-type E3 ubiquitin ligases play central regulatory roles in plant stress responses; however, the functions and regulatory networks of this gene family in cotton drought response remain largely unclear. In this [...] Read more.
Drought stress is a major abiotic factor limiting cotton yield and quality. RING-type E3 ubiquitin ligases play central regulatory roles in plant stress responses; however, the functions and regulatory networks of this gene family in cotton drought response remain largely unclear. In this study, we characterized the RING-type E3 ubiquitin ligase gene GhRNG1L from upland cotton (Gossypium hirsutum L.) and demonstrated its role in enhancing drought tolerance in cotton, and we successfully identified its upstream transcription factor GhDREB2B. Functional assays showed that overexpression of GhRNG1L significantly increased catalase (CAT) activity and reduced hydrogen peroxide (H2O2) accumulation in Arabidopsis, thereby improving plant drought tolerance, whereas silencing GhRNG1L produced the opposite phenotype. Further molecular analysis confirmed that GhDREB2B directly binds to the promoter of GhRNG1L and activates its transcription. Collectively, our findings reveal, for the first time, the positive regulatory role of the GhDREB2B-GhRNG1L module in cotton drought response, providing a clear upstream regulatory target and theoretical basis for molecular breeding of drought-tolerant cotton. Full article
(This article belongs to the Special Issue Advances in Genome-Wide Studies of Complex Agronomic Traits in Crops)
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27 pages, 11281 KB  
Article
Genetic Architecture of Grain Protein Content in Hulless Barley: Insights from Multi-Environment GWAS
by Sadaf Memon, Rizwan Ali Kumbhar, Shabana Memon, Shah Nawaz Mari Baloch, Rania Chourouk Benhafid, Kehan Yang, Zebaman, Longfei Zeng, Cile Duoji, Qiji Zhuoma, Mingxiang Wang, Mingyong, Xiaoqin Yang, Yajie Liu, Hui Zhao and Zongyun Feng
Plants 2026, 15(15), 2304; https://doi.org/10.3390/plants15152304 - 27 Jul 2026
Viewed by 424
Abstract
Hulless barley (HB) is a nutrient-rich cereal gaining renewed research interest in the Tibetan regions of China. Grain protein content (GPC) is a quality-determining trait in HB that significantly affects end-use quality and is strongly influenced by environmental factors. Identifying stable association regions [...] Read more.
Hulless barley (HB) is a nutrient-rich cereal gaining renewed research interest in the Tibetan regions of China. Grain protein content (GPC) is a quality-determining trait in HB that significantly affects end-use quality and is strongly influenced by environmental factors. Identifying stable association regions and developing breeding-applicable molecular markers are breeding objectives for high-GPC HB variety improvement. This study analyzed 266 HB accessions grown across six environments (2018–2021). Phenotypic GPC ranged from 5.02% to 18.31%, with moderate heritability (H2 = 0.473) and significant G×E interaction. A genome-wide association study (GWAS) using 168,983 GBS-derived SNPs and three models (GLM, MLM, FarmCPU) revealed no Bonferroni-significant SNPs in the BLUP meta-analysis. At the suggestive threshold (p < 1 × 10−5), 40 SNPs (18 loci) showed nominal association, with chromosome 7H harboring the most robust cross-model signal. Two SNPs on chromosome 6H and 7H exceeded Bonferroni correction in Yangma-2018 under GLM and FarmCPU. Candidate gene mining revealed seven functional genes, including 30S ribosomal protein S13 and glutamate-cysteine ligase. The lead SNP S7H_6966377 was located 165 kb from 30S ribosomal protein S13. These findings establish chromosome 7H as a regulatory hub for GPC and provide markers for marker-assisted selection. Full article
(This article belongs to the Special Issue Advances in Genome-Wide Studies of Complex Agronomic Traits in Crops)
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22 pages, 5511 KB  
Article
Genome-Wide Identification of Melon Single-Nucleotide Polymorphisms and Structural Variations Associated with Resistance to Fusarium oxysporum f. sp. melonis Race 1.2
by Abolfazl Bozorgmehr, Mohammad Sadegh Sabet, Mohammad Ali Malboobi, Stefano Pavan, Chiara Delvento and Ahmad Moieni
Plants 2026, 15(14), 2205; https://doi.org/10.3390/plants15142205 - 19 Jul 2026
Viewed by 508
Abstract
Fusarium wilt, caused by Fusarium oxysporum f. sp. melonis (FOM), is a main disease of melon (Cucumis melo L.). FOM 1.2 is the most widespread and detrimental variant of FOM, causing substantial economic losses under severe disease conditions. Current information suggests that [...] Read more.
Fusarium wilt, caused by Fusarium oxysporum f. sp. melonis (FOM), is a main disease of melon (Cucumis melo L.). FOM 1.2 is the most widespread and detrimental variant of FOM, causing substantial economic losses under severe disease conditions. Current information suggests that resistance to race 1.2 (FOM 1.2) is controlled by multiple recessive genes and is strongly influenced by the environment. Therefore, identifying genetic polymorphisms within diverse melon populations is essential to elucidate the loci and putative candidate genes associated with resistance. The objective of this investigation was to identify single-nucleotide polymorphism (SNP) and structural variant (SV) markers associated with FOM 1.2 resistance utilizing a panel of 160 genotypes through a genome-wide association study (GWAS). Phenotypic evaluation was performed two weeks after sowing, at the first-true-leaf stage, on 2400 individual plants inoculated by the root dip method with a concentration of about 106 spores/mL. Biochemical and disease-related traits, including area under disease progress curve (AUDPC), disease severity index (DSI), standardized AUDPC (SAUDPC), latent period (LP), catalase, peroxidase activity, and ascorbate peroxidase activity were measured 35 days after inoculation. PCA identified eighty-three individual melon plants with a broad range of disease-response variation. Genotyping-by-sequencing (GBS) was conducted on these plants, resulting in the identification of 737,435 SNPs and 75,133 SVs. Evaluation of the population structure outlined four genetic groups, including one associated with germplasm highly resistant to FOM 1.2. We used SNP data to describe linkage disequilibrium (LD), which was estimated to decay at 14 kb, on average. A GWAS was performed using the Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK) method, which revealed nine SNPs significantly associated with several disease indices, namely ascorbate peroxidase activity, AUDPC, catalase, peroxidase activity, rAUDPC, and SAUDPC. Also, eight SVs were associated with AUDPC and relative area under disease progress curve (rAUDPC), including translocation and deletion types. In addition, GWAS using the fixed and random model circulating probability unification (FarmCPU) method unveiled thirteen SVs associated with rAUDPC, peroxidase activity and ascorbate peroxidase activity, including translocation and inversion types. According to the performed models of GWAS, several significant SNPs and SVs, associated with putative candidate genes, including multidrug resistance-associated protein 6 (MRP6), LOB domain-containing protein 15 (LBD15), phosphomannomutase, and NADH-ubiquinone oxidoreductase B8 subunit, which may be involved in FOM 1.2 resistance. However, these findings represent a preliminary genome-wide survey and require further validation using high-coverage or long-read sequencing approaches. The results provide remarkable insights into the genetic control of FOM 1.2 resistance and valuable information for the implementation of the putative molecular markers identified in this study in melon breeding programs. Full article
(This article belongs to the Special Issue Advances in Genome-Wide Studies of Complex Agronomic Traits in Crops)
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17 pages, 2800 KB  
Article
Genetic Dissection of Frost Tolerance in Winter Durum Wheat: Three Validated KASP Markers for Marker-Assisted Selection
by Mikhail Divashuk, Aleksey Ermolaev, Viktoria Voronezhskaya, Aleksey Yanovsky, Varvara Korobkova, Ludmila Bespalova, Alexandra Mudrova, Anastasiya Voropaeva, Anastasia Lappo, Stepan Toshchakov, Mariia Samarina, Anastasia Krylova and Gennady Karlov
Plants 2026, 15(1), 19; https://doi.org/10.3390/plants15010019 - 20 Dec 2025
Viewed by 1710
Abstract
Winter durum wheat combines the benefits of autumn sowing with high grain quality but remains poorly adapted to temperate regions due to low frost tolerance. To elucidate the genetic basis of winter hardiness and support breeding for improved cold adaptation, a segregating multi-family [...] Read more.
Winter durum wheat combines the benefits of autumn sowing with high grain quality but remains poorly adapted to temperate regions due to low frost tolerance. To elucidate the genetic basis of winter hardiness and support breeding for improved cold adaptation, a segregating multi-family F2 panel (n = 270) was developed from crosses among frost-tolerant and frost-susceptible lines. GWAS identified four loci significantly associated with winter survival on chromosomes 1B, 5A, 5B, and 7B, collectively explaining 7.6–21.5% of phenotypic variance. These loci jointly improved model performance (ΔMcFadden R2 = 0.230, p-value = 4.76 × 10−17) without evidence of epistasis, indicating additive inheritance. Predicted survival increased nearly linearly with the number of favorable alleles, highlighting the potential for pyramiding through marker-assisted or genomic selection. Three significant SNPs were converted to KASP assays, providing validated molecular tools for breeding applications. Overall, the study broadens understanding of frost-tolerance genetics in winter durum wheat beyond canonical Fr regions and delivers practical markers for improving winter hardiness in breeding programs targeting continental climates. Full article
(This article belongs to the Special Issue Advances in Genome-Wide Studies of Complex Agronomic Traits in Crops)
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17 pages, 1924 KB  
Article
Comparison of the Genetic Basis of Yield Traits Between Main and Ratoon Rice in an Eight-Way MAGIC Population
by Zhongmin Han, Ahmed Sherif, Mohammed Ayaad, Yongzhong Xing and Yuncai Lu
Plants 2025, 14(22), 3527; https://doi.org/10.3390/plants14223527 - 19 Nov 2025
Cited by 2 | Viewed by 1543
Abstract
Ratoon rice plays a crucial role in sustainable rice production due to its potential for additional harvests; however, the genetic basis of its yield remains to be explored. In this study, we aimed to precisely dissect the genetic basis of yield in ratoon [...] Read more.
Ratoon rice plays a crucial role in sustainable rice production due to its potential for additional harvests; however, the genetic basis of its yield remains to be explored. In this study, we aimed to precisely dissect the genetic basis of yield in ratoon rice by selecting 302 eight-way MAGIC lines that achieved synchronized heading within a 10-day period through staggered sowing. The eight parental lines exhibited distinct yield performances across both main and ratoon crops. Significant correlations were observed between the main and ratoon crops concerning panicle length (R = 0.67) and spikelets per panicle (R = 0.36). Genome-wide association studies (GWAS) revealed a total of 17 quantitative trait loci (QTLs) associated with five yield-related traits in both main and ratoon crops. Specifically, seven QTLs were detected for yield components in the main crop, while six QTLs were identified in the ratoon crop, in addition to five QTLs associated with ratooning ability. Notably, only one QTL, qPL1, was commonly detected in both crops, exhibiting opposite effects on tiller number across crop types. Among the QTLs specifically identified in the ratoon crop, qGY10 demonstrated the largest effect on ratoon grain yield without compromising the performance of the main crop. The known gene, Ghd7.1, exhibited pleiotropic effects on both ratooning ability and ratoon grain yield. Candidate gene analysis prioritized likely causal genes and defined key haplotypes within these QTL intervals by leveraging the genomic diversity of the eight founders. These findings underscore the distinct genetic determinants for yields in main and ratoon crops, providing a genetic basis for breeding high-yielding varieties in both crop types. Full article
(This article belongs to the Special Issue Advances in Genome-Wide Studies of Complex Agronomic Traits in Crops)
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21 pages, 2330 KB  
Article
Using Structural Equation Models to Interpret Genome-Wide Association Studies for Morphological and Productive Traits in Soybean [Glycine max (L.) Merr.]
by Matheus Massariol Suela, Camila Ferreira Azevedo, Ana Carolina Campana Nascimento, Gota Morota, Felipe Lopes da Silva, Gaspar Malone, Nizio Fernando Giasson and Moysés Nascimento
Plants 2025, 14(19), 3015; https://doi.org/10.3390/plants14193015 - 29 Sep 2025
Viewed by 1320
Abstract
Understanding trait relationships is fundamental in soybean breeding because the goal is to maximize simultaneous gains. Standard multi-trait genome-wide association studies (MT-GWAS) identify variants linked to multiple traits but fail to capture phenotypic structures or interrelations. Structural Equation Models (SEM) account for covariances [...] Read more.
Understanding trait relationships is fundamental in soybean breeding because the goal is to maximize simultaneous gains. Standard multi-trait genome-wide association studies (MT-GWAS) identify variants linked to multiple traits but fail to capture phenotypic structures or interrelations. Structural Equation Models (SEM) account for covariances and recursion, enabling the decomposition of single nucleotide polymorphism (SNP) effects into direct or indirect components and identifying pleiotropic regions. We applied SEM to analyze morphology (pod thickness, PT) and yield traits (number of pods, NP; number of grains, NG; hundred-grain weight, HGW). The dataset comprised 96 soybean individuals genotyped with 4070 SNP markers. The phenotypic network was constructed using the hill-climbing algorithm, a class of score-based methods commonly applied to learn the structure of Bayesian networks, and structural coefficients were estimated with SEM. According to coefficient signs, we identified negative interrelationships between NG and HGW, and positive ones between NP and NG, and HGW and PT. NG, HGW, and PT showed indirect SNP effects. We also found loci jointly controlling traits. In total, 46 candidate genes were identified: 7 associated exclusively with NP and 4 associated with NG. An additional 15 genes were common to NP and NG, 3 were common to NP and HGW, 6 were common to NG and HGW, and 11 were common to NP, NG, and HGW. In summary, SEM-GWAS revealed novel relationships among soybean traits, including PT, supporting breeding programs. Full article
(This article belongs to the Special Issue Advances in Genome-Wide Studies of Complex Agronomic Traits in Crops)
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