Recent Advances in the Genetics, Genomics and Breeding of Cereal Crops

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 (30 September 2025) | Viewed by 3599

Special Issue Editors


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Guest Editor
National Wheat Improvement Centre, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Interests: breeding; genetics; marker-assisted selection; wheat
Special Issues, Collections and Topics in MDPI journals
School of Agriculture, Sun Yat-sen University, Guangzhou, China
Interests: breeding; genetics; marker-assisted selection; molecular biology; rice
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cereal crops, such as wheat, maize, rice, barley, etc., are the main foods worldwide. Cereals occupy nearly 75% of the total cultivated area and provide over half of the world’s caloric consumption. Benefiting from modern breeding technology, cereal yields have increased significantly in the past half-century; however, recent studies have shown that the global annual increase for major crops has slowed down to around 1% after entering the 21st century.

To address this challenge and ensure food security in an environmentally sustainable manner, breeding varieties with higher yields, superior quality, and resilience to both biotic and abiotic stresses is crucial. Diverse breeding methods, ranging from traditional to modern technologies, have been employed. Advances in biotechnology, molecular biology, genomics, and genome editing have significantly improved breeding efficiency. Additionally, all of the above approaches require diverse genetic resources and germplasms; however, an urgent issue for modern cultivars is the narrowing of genetic diversity due to domestication and selection. Therefore, marker-assisted selection (MAS) based on quantitative trait loci (QTL) or genes identified through forward and reverse genetics holds significant promise for crop breeding. This Special Issue aims to highlight recent advances in genetics, genomics, and breeding techniques for cereal crops. We invite original research and review articles that focus on, but are not limited to, the following topics:

  1. Genetic analyses to uncover complex quantitative traits (particularly yield, quality, and resistance to biotic and abiotic stresses).
  2. Genomic selection/prediction and molecular design methods for cereal crops.
  3. Novel insights from traditional agronomic breeding methods.
  4. Genomic analyses (re-sequence, BSA, or others) for cereal crops.
  5. Domestication and selection signatures for cereal crops.
  6. Identifying the desired haplotypes and MAS breeding for cereal crops.

Dr. Jindong Liu
Dr. Yamei Wang
Guest Editors

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Keywords

  • agronomic
  • breeding
  • cereal crops
  • genetics
  • genomics
  • marker-assisted selection

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Published Papers (4 papers)

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Research

16 pages, 2514 KB  
Article
QTL Mapping for Leaf Rust Resistance in a Common Wheat Recombinant Inbred Line Population of Doumai/Shi4185
by Yamei Wang, Wenjing Li, Rui Wang, Nannan Zhao, Xinye Zhang, Shu Zhu and Jindong Liu
Plants 2025, 14(19), 3113; https://doi.org/10.3390/plants14193113 - 9 Oct 2025
Viewed by 433
Abstract
Leaf rust, a devastating fungal disease caused by Puccinia triticina (Pt), severely impacts wheat quality and yield. Identifying genetic loci for wheat leaf rust resistance, developing molecular markers, and breeding resistant varieties is the most environmentally friendly and economical strategy for disease control. [...] Read more.
Leaf rust, a devastating fungal disease caused by Puccinia triticina (Pt), severely impacts wheat quality and yield. Identifying genetic loci for wheat leaf rust resistance, developing molecular markers, and breeding resistant varieties is the most environmentally friendly and economical strategy for disease control. This study utilized a recombinant inbred line (RIL) population of Doumai and Shi4185, combined with the wheat 90 K single nucleotide polymorphisms (SNPs) chip data and maximum disease severity (MDS) of leaf rust from four environments, to identify adult plant resistance (APR) loci through linkage mapping. Additionally, kompetitive allele-specific PCR (KASP) markers suitable for breeding were developed, and genetic effects were validated in a natural population. In this study, 5 quantitative trait loci (QTL) on chromosomes 1B (2), 2A and 7B (2) were identified through inclusive composite interval mapping, and named as QLr.lfnu-1BL1, QLr.lfnu-1BL2, QLr.lfnu-2AL, QLr.lfnu-7BL1 and QLr.lfnu-7BL2, respectively, explaining 4.54–8.91% of the phenotypic variances. The resistance alleles of QLr.lfnu-1BL1 and QLr.lfnu-1BL2 originated from Doumai, while the resistance alleles of QLr.lfnu-2AL, QLr.lfnu-7BL1 and QLr.lfnu-7BL2 came from Shi4185. Among these, QLr.lfnu-1BL2, QLr.lfnu-7BL1 and QLr.lfnu-7BL2 overlapped with previously reported loci, whereas QLr.lfnu-1BL1 and QLr.lfnu-2AL are likely to be novel. Two KASP markers, QLr.lfnu-2AL and QLr.lfnu-7BL, were significantly associated with leaf rust resistance in a diverse panel of 150 wheat varieties mainly from China. Totally, 34 potential candidate genes encoded the NLR proteins, receptor-like kinases, signaling kinases and transcription factors were selected as candidate genes for the resistance loci. These findings will provide stable QTL, available breeding KASP markers and candidate genes, and will accelerate the progresses of wheat leaf rust resistance improvement through marker-assisted selection breeding. Full article
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16 pages, 3432 KB  
Article
Genetic Architecture and Meta-QTL Identification of Yield Traits in Maize (Zea mays L.)
by Xin Li, Xiaoqiang Zhao, Siqi Sun, Meiyue He, Jing Wang, Xinxin Xiang and Yining Niu
Plants 2025, 14(19), 3067; https://doi.org/10.3390/plants14193067 - 4 Oct 2025
Viewed by 537
Abstract
Yield components are the most important breeding objectives, directly determining maize high-yield breeding. It is well known that these traits are controlled by a large number of quantitative trait loci (QTL). Therefore, deeply understanding the genetic basis of yield components and identifying key [...] Read more.
Yield components are the most important breeding objectives, directly determining maize high-yield breeding. It is well known that these traits are controlled by a large number of quantitative trait loci (QTL). Therefore, deeply understanding the genetic basis of yield components and identifying key regulatory candidate genes can lay the foundation for maize marker-assisted selection (MAS) breeding. In this study, our aim was to identify the key genomic regions that regulate maize yield component formation through bioinformatic methods. Herein, 554 original QTLs related to 11 yield components, including ear length (EL), hundred-kernel weight (HKW), ear weight (EW), cob weight (CW), ear diameter (ED), cob diameter (CD), kernel row number (KRN), kernel number per row (KNR), kernel length (KL), grain weight per plant (GW), and kernel width (KW) in maize, were collected from the MaizeGDB, national center for biotechnology information (NCBI), and China national knowledge infrastructure (CNKI) databases. The consensus map was then constructed with a total length of 7154.30 cM. Approximately 80.32% of original QTLs were successfully projected on the consensus map, and they were unevenly distributed on the 10 chromosomes (Chr.). Moreover, 44 meta-QTLs (MQTLs) were identified by the meta-analysis. Among them, 39 MQTLs controlled two or more yield components, except for the MQTL4 in Chr. 1, which was associated with HKW; MQTL11 in Chr. 2, which was responsible for EL; MQTL19 in Chr. 3, which was related to KRN; MQTL26 in Chr. 5, which was involved in HKW; and MQTL36 in Chr. 7, which regulated EL. These findings were consistent with the Pearson correlation results, indicating that these traits exhibited co-linked heredity phenomena. Meanwhile, 159 candidate genes were found in all of the above MQTLs intervals, of which, 29 genes encoded E3 ubiquitin protein ligase, which was related with kernel size and weight. Other genes were involved in multiple metabolic processes, including plant hormones signaling transduction, plant growth and development, sucrose–starch synthesis and metabolism, and reproductive growth. Overall, the results will provide reliable genetic resources for high-yield molecular breeding in maize. Full article
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12 pages, 1906 KB  
Article
Combined Analysis of BSA-Seq and RNA-Seq Reveals Candidate Genes for qGS1 Related to Sorghum Grain Size
by Qi Shen, Kai Wang, Lu Hu, Lei Li, Lihua Wang, Yongfei Wang, Yi-Hong Wang and Jieqin Li
Plants 2025, 14(12), 1791; https://doi.org/10.3390/plants14121791 - 11 Jun 2025
Viewed by 845
Abstract
Grain size is a crucial agronomic trait that significantly impacts yield potential in sorghum (Sorghum bicolor), making it a key focus for genetic improvement. In this study, we investigated the genetic basis of grain size variation using two contrasting sorghum accessions, [...] Read more.
Grain size is a crucial agronomic trait that significantly impacts yield potential in sorghum (Sorghum bicolor), making it a key focus for genetic improvement. In this study, we investigated the genetic basis of grain size variation using two contrasting sorghum accessions, PI302232 (small grain, Sg) and PI563512 (large grain, Lg). The 1000-grain weight, grain length, and grain width of Lg were 3.63-fold, 1.22-fold, and 1.65-fold higher than Sg, respectively. The 1000-grain weight in the F2 segregating population derived from the cross Sg and Lg parents exhibited the highest phenotypic variation and followed a normal distribution in the three traits. Using bulked segregant analysis sequencing (BSA-seq) with small- and large-grain bulks from the F2 population, two major quantitative trait loci (QTLs) for grain size were identified on chromosomes 1 and 3. Fine mapping with SSR markers narrowed the qGS1 locus to a 1.03 Mb region on chromosome 1 (Chr01: 22,001,448–23,035,593), containing 49 candidate genes. To narrow down potential candidate genes, transcriptome analysis of spike tissues from Sg and Lg at 0 and 14 days after heading revealed 3719 differentially expressed genes (DEGs), primarily enriched in “starch and sucrose metabolism” and “phenylpropanoid biosynthesis” pathways. Integrating fine mapping intervals and RNA-seq data, 6 DEGs were identified within the qGS1 region. Quantitative real-time PCR confirmed that 6 genes exhibited different expression at two stages. The expression and bioinformatics analysis showed Sobic.001G230700 was the most likely candidate gene for the qGS1 locus. This study provides new insights into the genetic regulation of grain size and a new target to improve grain size in sorghum. Full article
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16 pages, 2088 KB  
Article
Genetic Basis of Seedling Root Traits in Common Wheat (Triticum aestivum L.) Identified by Genome-Wide Linkage Mapping
by Xiaole Ma, Juncheng Wang, Hong Zhang, Lirong Yao, Erjing Si, Baochun Li, Yaxiong Meng and Huajun Wang
Plants 2025, 14(3), 490; https://doi.org/10.3390/plants14030490 - 6 Feb 2025
Cited by 1 | Viewed by 1235
Abstract
Common wheat production is significantly influenced by abiotic stresses. Identifying the genetic loci for seedling root traits and developing the available molecular markers are crucial for breeding high yielding and stable varieties. In this study, five wheat seedling root traits, including root length [...] Read more.
Common wheat production is significantly influenced by abiotic stresses. Identifying the genetic loci for seedling root traits and developing the available molecular markers are crucial for breeding high yielding and stable varieties. In this study, five wheat seedling root traits, including root length (RL), root surface area (RA), root volume (RV), number of root tips (RT), and root dry weight (RW), were measured in the Wp-072/Wp-119 recombinant inbred line (RIL) population. Genotyping was conducted for the RIL population and their parents using the wheat 90K single-nucleotide polymorphism (SNP) chip. In total, three quantitative trait loci (QTLs) for RL (QRL.gau-1DS, QRL.gau-1DL and QRL.gau-4AL), two QTLs for RA (QRA.gau-1D and QRA.gau-2DL), one locus for RV (QRV.gau-6AS), two loci for RW (QRW.gau-2DL and QRW.gau-2AS), and two loci for RT (QRT.gau-3AS and QRT.gau-6DL) were identified, with each explaining 4.5–8.4% of the phenotypic variances, respectively. Among these, QRT.gau-3AS, QRL.gau-4AL, and QRV.gau-6AS overlapped with the previous reports, whereas the other seven QTLs were novel. The favorable alleles of QRL.gau-1DS, QRL.gau-1DL, QRL.gau-4AL, QRA.gau-1D, QRW.gau-2AS, QRV.gau-6AS, QRT.gau-3AS, and QRT.gau-6DL were contributed by Wp-072, whereas the other two loci originated from Wp-119. Additionally, five kompetitive allele-specific PCR (KASP) markers, KASP-RL-1DL for RL, KASP-RA-1D and KASP-RA-2DL for RA, KASP-RW-2AS and KASP-RW-2DL for RW, were developed and validated successfully in 149 wheat accessions. Furthermore, seven candidate genes mainly for plant hormones were selected and validated by quantitative real-time PCR (qRT-PCR). This study provides new loci, new candidate genes, available KASP markers, and varieties for optimizing wheat root system architecture. Full article
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