Identification of quantitative trait loci for kernel-related traits and the heterosis for these traits in maize (Zea mays L.)

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

In this study, hotspot regions, QTL clusters, and candidate genes for eight ear-related traits of maize (ear length, ear diameter, kernel row number, kernel number per row, kernel length, kernel width, kernel thickness, and 100-kernel weight) were summarized and analyzed over the past three decades. This review aims to (1) comprehensively summarize and analyze previous studies on QTLs associated with these eight ear-related traits and identify hotspot bin regions located on maize chromosomes and key candidate genes associated with the ear-related traits and (2) compile major and stable QTLs and QTL clusters from various mapping populations and mapping methods and techniques providing valuable insights for fine mapping, gene cloning, and breeding for high-yield and high-quality maize. Previous research has demonstrated that QTLs for ear-related traits are distributed across all ten chromosomes in maize, and the phenotypic variation explained by a single QTL ranged from 0.40% to 36.76%. In total, 23 QTL hotspot bins for ear-related traits were identified across all ten chromosomes. The most prominent hotspot region is bin 4.08 on chromosome 4 with 15 QTLs related to eight ear-related traits. Additionally, this study identified 48 candidate genes associated with ear-related traits. Out of these, five have been cloned and validated, while twenty-eight candidate genes located in the QTL hotspots were defined by this study. This review offers a deeper understanding of the advancements in QTL mapping and the identification of key candidates associated with eight ear-related traits. These insights will undoubtedly assist maize breeders in formulating strategies to develop higher-yield maize varieties, contributing to global food security.

Genetic dissection of embryo size and weight related traits for enhancement of kernel oil in maize

Embryo is a key determinant of kernel-oil in maize. Higher calorific value of maize kernel is attributed to increment in kernel-oil and it stores in specialised structure called embryo. Understanding the genetic behaviour of embryo size and weight related-traits is inevitable task for genetic improvement of kernel-oil. Here, the six-basic generations (P₁, P₂, F₁, F₂, BC₁P₁ and BC₁P₂) of three crosses (CRPBIO-962 × EC932601, CRPBIO-973 × CRPBIO-966 and CRPBIO-966 × CRPBIO-979) between contrasting embryo-sized maize inbreds were field evaluated at three locations to decipher the genetics of twenty embryo, kernel and embryo-to-kernel related-traits through generation-mean-analysis (GMA). Combined ANOVA revealed the significance of all the traits among generations; however, location and generation × location were found to be non-significant (P > 0.05) for most of the traits. Significance (P < 0.05) of scaling and joint-scaling tests revealed the presence of non-allelic interactions. Elucidation of six-parameters disclosed the predominance of dominance main-effect (h) and dominance × dominance interaction-effect (l) for most of traits. The signs of (h) and (l) indicated the prevalence of duplicate-epistasis type across crosses and locations. Thus, the population improvement approaches along with heterosis breeding method could be effective for improvement of these traits. Quantitative inheritance pattern was observed for all the traits with high broad-sense heritability and better-stability across locations. The study also predicted one to three major-gene blocks/QTLs for embryo-traits and up to 11 major-gene blocks/QTLs for embryo-to-kernel traits. These findings could provide deep insights to strategize extensive breeding methods to improve embryo traits for enhancing kernel-oil in sustainable manner.

QTL mapping of maize (Zea mays L.) kernel traits under low-phosphorus stress

Low-phosphorus stress significantly impacts the development of maize kernels. In this study, the phosphor efficient maize genotype 082 and phosphor deficient maize genotype Ye107, were used to construct an F2:3 population. QTL mapping was then employed to determine the genetic basis of differences in the maize kernel traits of the two parents in a low-phosphorus environment. This analysis revealed several major QTL that control environmental impacts on kernel length, width, thickness, and weight. These QTL were detected in all three environments and were distributed on five genome segments of chromosomes 3, 5, 6, and 9, and some new kernel-trait QTL were also detected (eg: Qkwid6, Qkthi3, Qkwei9, and Qklen3-1). These environmentally insensitive QTL can be stably expressed in low phosphorus environments, indicating that they can lay a foundation for the breeding of high phosphorus utilization efficiency germplasm.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-023-01300-0.

Development of the maize 5.5K loci panel for genomic prediction through genotyping by target sequencing

Genotyping platforms are important for genetic research and molecular breeding. In this study, a low-density genotyping platform containing 5.5K SNP markers was successfully developed in maize using genotyping by target sequencing (GBTS) technology with capture-in-solution. Two maize populations (Pop1 and Pop2) were used to validate the GBTS panel for genetic and molecular breeding studies. Pop1 comprised 942 hybrids derived from 250 inbred lines and four testers, and Pop2 contained 540 hybrids which were generated from 123 new-developed inbred lines and eight testers. The genetic analyses showed that the average polymorphic information content and genetic diversity values ranged from 0.27 to 0.38 in both populations using all filtered genotyping data. The mean missing rate was 1.23% across populations. The Structure and UPGMA tree analyses revealed similar genetic divergences (76-89%) in both populations. Genomic prediction analyses showed that the prediction accuracy of reproducing kernel Hilbert space (RKHS) was slightly lower than that of genomic best linear unbiased prediction (GBLUP) and three Bayesian methods for general combining ability of grain yield per plant and three yield-related traits in both populations, whereas RKHS with additive effects showed superior advantages over the other four methods in Pop1. In Pop1, the GBLUP and three Bayesian methods with additive-dominance model improved the prediction accuracies by 4.89-134.52% for the four traits in comparison to the additive model. In Pop2, the inclusion of dominance did not improve the accuracy in most cases. In general, low accuracies (0.33-0.43) were achieved for general combing ability of the four traits in Pop1, whereas moderate-to-high accuracies (0.52-0.65) were observed in Pop2. For hybrid performance prediction, the accuracies were moderate to high (0.51-0.75) for the four traits in both populations using the additive-dominance model. This study suggests a reliable genotyping platform that can be implemented in genomic selection-assisted breeding to accelerate maize new cultivar development and improvement.

Genome-Wide Association Analysis for Candidate Genes Contributing to Kernel-Related Traits in Maize

Maize grain size is the main factor determining grain yield. Dissecting the genetic basis of maize grain size may help reveal the regulatory mechanism of maize seed development and yield formation. In this study, two associated populations were used for genome-wide association analysis of kernel length, kernel width, kernel thickness, and hundred-kernel weight from multiple locations in AM122 and AM180, respectively. Then, genome-wide association mapping was performed based on the maize 6H90K SNP chip. A total of 139 loci were identified as associated with the four traits with p < 1 × 10^-4 using two models (FarmCPU and MLM). The transcriptome data showed that 15 of them were expressed differentially in two maize-inbred lines KB182 (small kernel) and KB020 (big kernel) during kernel development. These candidate genes were enriched in regulating peroxidase activity, oxidoreductase, and leaf senescence. The molecular function was major in binding and catalytic activity. This study provided important reference information for exploring maize kernel development mechanisms and applying molecular markers in high-yield breeding.

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize

Grain size, grain number per panicle, and grain weight are crucial determinants of yield-related traits in cereals. Understanding the genetic basis of grain yield-related traits has been the main research object and nodal in crop science. Sorghum and maize, as very close C4 crops with high photosynthetic rates, stress tolerance and large biomass characteristics, are extensively used to produce food, feed, and biofuels worldwide. In this review, we comprehensively summarize a large number of quantitative trait loci (QTLs) associated with grain yield in sorghum and maize. We placed great emphasis on discussing 22 fine-mapped QTLs and 30 functionally characterized genes, which greatly hinders our deep understanding at the molecular mechanism level. This review provides a general overview of the comprehensive findings on grain yield QTLs and discusses the emerging trend in molecular marker-assisted breeding with these QTLs.

Advances in Research on the Mechanism of Heterosis in Plants

Heterosis is a common biological phenomenon in nature. It substantially contributes to the biomass yield and grain yield of plants. Moreover, this phenomenon results in high economic returns in agricultural production. However, the utilization of heterosis far exceeds the level of theoretical research on this phenomenon. In this review, the recent progress in research on heterosis in plants was reviewed from the aspects of classical genetics, parental genetic distance, quantitative trait loci, transcriptomes, proteomes, epigenetics (DNA methylation, histone modification, and small RNA), and hormone regulation. A regulatory network of various heterosis-related genes under the action of different regulatory factors was summarized. This review lays a foundation for the in-depth study of the molecular and physiological aspects of this phenomenon to promote its effects on increasing the yield of agricultural production.

Genetic diversity and selection signatures in maize landraces compared across 50 years of in situ and ex situ conservation

Genomics-based, longitudinal comparisons between ex situ and in situ agrobiodiversity conservation strategies can contribute to a better understanding of their underlying effects. However, landrace designations, ambiguous common names, and gaps in sampling information complicate the identification of matching ex situ and in situ seed lots. Here we report a 50-year longitudinal comparison of the genetic diversity of a set of 13 accessions from the state of Morelos, Mexico, conserved ex situ since 1967 and retrieved in situ from the same donor families in 2017. We interviewed farmer families who donated in situ landraces to understand their germplasm selection criteria. Samples were genotyped by sequencing, producing 74,739 SNPs. Comparing the two sample groups, we show that ex situ and in situ genome-wide diversity was similar. In situ samples had 3.1% fewer SNPs and lower pairwise genetic distances (F_st 0.008-0.113) than ex situ samples (F_st 0.031-0.128), but displayed the same heterozygosity. Despite genome-wide similarities across samples, we could identify several loci under selection when comparing in situ and ex situ seed lots, suggesting ongoing evolution in farmer fields. Eight loci in chromosomes 3, 5, 6, and 10 showed evidence of selection in situ that could be related with farmers' selection criteria surveyed with focus groups and interviews at the sampling site in 2017, including wider kernels and larger ear size. Our results have implications for ex situ collection resampling strategies and the in situ conservation of threatened landraces.

Molecular basis of heterosis and related breeding strategies reveal its importance in vegetable breeding

Heterosis has historically been exploited in plants; however, its underlying genetic mechanisms and molecular basis remain elusive. In recent years, due to advances in molecular biotechnology at the genome, transcriptome, proteome, and epigenome levels, the study of heterosis in vegetables has made significant progress. Here, we present an extensive literature review on the genetic and epigenetic regulation of heterosis in vegetables. We summarize six hypotheses to explain the mechanism by which genes regulate heterosis, improve upon a possible model of heterosis that is triggered by epigenetics, and analyze previous studies on quantitative trait locus effects and gene actions related to heterosis based on analyses of differential gene expression in vegetables. We also discuss the contributions of yield-related traits, including flower, fruit, and plant architecture traits, during heterosis development in vegetables (e.g., cabbage, cucumber, and tomato). More importantly, we propose a comprehensive breeding strategy based on heterosis studies in vegetables and crop plants. The description of the strategy details how to obtain F1 hybrids that exhibit heterosis based on heterosis prediction, how to obtain elite lines based on molecular biotechnology, and how to maintain heterosis by diploid seed breeding and the selection of hybrid simulation lines that are suitable for heterosis research and utilization in vegetables. Finally, we briefly provide suggestions and perspectives on the role of heterosis in the future of vegetable breeding.

Association Mapping and Transcriptome Analysis Reveal the Genetic Architecture of Maize Kernel Size

Kernel length, kernel width, and kernel thickness are important traits affecting grain yield and product quality. Here, the genetic architecture of the three kernel size traits was dissected in an association panel of 309 maize inbred lines using four statistical methods. Forty-two significant single nucleotide polymorphisms (SNPs; p < 1.72E-05) and 70 genes for the three traits were identified under five environments. One and eight SNPs were co-detected in two environments and by at least two methods, respectively, and they explained 5.87-9.59% of the phenotypic variation. Comparing the transcriptomes of two inbred lines with contrasting seed size, three and eight genes identified in the association panel showed significantly differential expression between the two genotypes at 15 and 39 days after pollination, respectively. Ten and 17 genes identified by a genome-wide association study were significantly differentially expressed between the two development stages in the two genotypes. Combining environment-/method-stable SNPs and differential expression analysis, ribosomal protein L7, jasmonate-regulated gene 21, serine/threonine-protein kinase RUNKEL, AP2-EREBP-transcription factor 16, and Zm00001d035222 (cell wall protein IFF6-like) were important candidate genes for maize kernel size and development.