Combination of multi-locus genome-wide association study and QTL mapping reveals genetic basis of tassel architecture in maize

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Deploying QTL-seq rapid identification and separation of the major QTLs of tassel branch number for fine-mapping in advanced maize populations

The tassel competes with the ear for nutrients and shields the upper leaves, thereby reducing the yield of grain. The tassel branch number (TBN) is a pivotal determinant of tassel size, wherein the reduced TBN has the potential to enhance the transmission of light and reduce the consumption of nutrients, which should ultimately result in increased yield. Consequently, the TBN has emerged as a vital target trait in contemporary breeding programs that focus on compact maize varieties. In this study, QTL-seq technology and advanced population mapping were used to rapidly identify and dissect the major effects of the TBN on QTL. Advanced mapping populations (BC4F2 and BC4F3) were derived from the inbred lines 18-599 (8-11 TBN) and 3237 (0-1 TBN) through phenotypic recurrent selection. First, 13 genomic regions associated with the TBN were detected using quantitative trait locus (QTL)-seq and were located on chromosomes 2 and 5. Subsequently, validated loci within these regions were identified by QTL-seq. Three QTLs for TBN were identified in the BC4F2 populations by traditional QTL mapping, with each QTL explaining the phenotypic variation of 6.13-18.17%. In addition, for the major QTL (qTBN2-2 and qTBN5-1), residual heterozygous lines (RHLs) were developed from the BC4F2 population. These two major QTLs were verified in the RHLs by QTL mapping, with the phenotypic variation explained (PVE) of 21.57% and 30.75%, respectively. Near-isogenic lines (NILs) of qTBN2-2 and qTBN5-1 were constructed. There were significant differences between the NILs in TBN. These results will enhance our understanding of the genetic basis of TBN and provide a solid foundation for the fine-mapping of TBN.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01431-y.

Identification of QTLs and their candidate genes for the number of maize tassel branches in F2 from two higher generation sister lines using QTL mapping and RNA-seq analysis

Tassel branch number is an important agronomic trait that is closely associated with maize kernels and yield. The regulation of genes associated with tassel branch development can provide a theoretical basis for analyzing tassel branch growth and improving maize yield. In this study. we used two high-generation sister maize lines, PCU (unbranched) and PCM (multiple-branched), to construct an F2 population comprising 190 individuals, which were genotyped and mapped using the Maize6H-60K single-nucleotide polymorphism array. Candidate genes associated with tassel development were subsequently identified by analyzing samples collected at three stages of tassel growth via RNA-seq. A total of 13 quantitative trait loci (QTLs) and 22 quantitative trait nucleotides (QTNs) associated with tassel branch number (TBN) were identified, among which, two major QTLs, qTBN6.06-1 and qTBN6.06-2, on chromosome 6 were identified in two progeny populations, accounting for 15.07% to 37.64% of the phenotypic variation. Moreover, we identified 613 genes that were differentially expressed between PCU and PCM, which, according to Kyoto Encyclopedia of Genes and Genomes enrichment analysis, were enriched in amino acid metabolism and plant signal transduction pathways. Additionally, we established that the phytohormone content of Stage I tassels and the levels of indole-3-acetic acid (IAA) and IAA-glucose were higher in PCU than in PCM plants, whereas contrastingly, the levels of 5-deoxymonopolyl alcohol in PCM were higher than those in PCU. On the basis of these findings, we speculate that differences in TBN may be related to hormone content. Collectively, by combining QTL mapping and RNA-seq analysis, we identified five candidate genes associated with TBN. This study provides theoretical insights into the mechanism of tassel branch development in maize.

Genetic dissection of protein and starch during wheat grain development using QTL mapping and GWAS

Protein, starch, and their components are important for wheat grain yield and end-products, which are affected by wheat grain development. Therefore, QTL mapping and a genome-wide association study (GWAS) of grain protein content (GPC), glutenin macropolymer content (GMP), amylopectin content (GApC), and amylose content (GAsC) were performed on wheat grain development at 7, 14, 21, and 28 days after anthesis (DAA) in two environments using a recombinant inbred line (RIL) population of 256 stable lines and a panel of 205 wheat accessions. A total of 29 unconditional QTLs, 13 conditional QTLs, 99 unconditional marker-trait associations (MTAs), and 14 conditional MTAs significantly associated (p < 10^-4) with four quality traits were found to be distributed on 15 chromosomes, with the phenotypic variation explained (PVE) ranging from 5.35% to 39.86%. Among these genomic variations, three major QTLs [QGPC3B, QGPC2A, and QGPC(S3|S2)3B] and SNP clusters on the 3A and 6B chromosomes were detected for GPC, and the SNP TA005876-0602 was stably expressed during the three periods in the natural population. The QGMP3B locus was detected five times in three developmental stages in two environments with 5.89%-33.62% PVE, and SNP clusters for GMP content were found on the 3A and 3B chromosomes. For GApC, the QGApC3B.1 locus had the highest PVE of 25.69%, and SNP clusters were found on chromosomes 4A, 4B, 5B, 6B, and 7B. Four major QTLs of GAsC were detected at 21 and 28 DAA. Most interestingly, both QTL mapping and GWAS analysis indicated that four chromosomes (3B, 4A, 6B, and 7A) were mainly involved in the development of protein, GMP, amylopectin, and amylose synthesis. Of these, the wPt-5870-wPt-3620 marker interval on chromosome 3B seemed to be most important because it played an important role in the synthesis of GMP and amylopectin before 7 DAA, in the synthesis of protein and GMP from 14 to 21 DAA, and in the development of GApC and GAsC from 21 to 28 DAA. Using the annotation information of IWGSC Chinese Spring RefSeq v1.1 genome assembly, we predicted 28 and 69 candidate genes for major loci from QTL mapping and GWAS, respectively. Most of them have multiple effects on protein and starch synthesis during grain development. These results provide new insights and information for the potential regulatory network between grain protein and starch synthesis.

Genome-Wide Association Study and Genomic Prediction on Plant Architecture Traits in Sweet Corn and Waxy Corn

Sweet corn and waxy corn has a better taste and higher accumulated nutritional value than regular maize, and is widely planted and popularly consumed throughout the world. Plant height (PH), ear height (EH), and tassel branch number (TBN) are key plant architecture traits, which play an important role in improving grain yield in maize. In this study, a genome-wide association study (GWAS) and genomic prediction analysis were conducted on plant architecture traits of PH, EH, and TBN in a fresh edible maize population consisting of 190 sweet corn inbred lines and 287 waxy corn inbred lines. Phenotypic data from two locations showed high heritability for all three traits, with significant differences observed between sweet corn and waxy corn for both PH and EH. The differences between the three subgroups of sweet corn were not obvious for all three traits. Population structure and PCA analysis results divided the whole population into three subgroups, i.e., sweet corn, waxy corn, and the subgroup mixed with sweet and waxy corn. Analysis of GWAS was conducted with 278,592 SNPs obtained from resequencing data; 184, 45, and 68 significantly associated SNPs were detected for PH, EH, and TBN, respectively. The phenotypic variance explained (PVE) values of these significant SNPs ranged from 3.50% to 7.0%. The results of this study lay the foundation for further understanding the genetic basis of plant architecture traits in sweet corn and waxy corn. Genomic selection (GS) is a new approach for improving quantitative traits in large plant breeding populations that uses whole-genome molecular markers. The marker number and marker quality are essential for the application of GS in maize breeding. GWAS can choose the most related markers with the traits, so it can be used to improve the predictive accuracy of GS.

Combining datasets for maize root seedling traits increases the power of GWAS and genomic prediction accuracies

The identification of genomic regions associated with root traits and the genomic prediction of untested genotypes can increase the rate of genetic gain in maize breeding programs targeting roots traits. Here, we combined two maize association panels with different genetic backgrounds to identify single nucleotide polymorphisms (SNPs) associated with root traits, and used a genome-wide association study (GWAS) and to assess the potential of genomic prediction for these traits in maize. For this, we evaluated 377 lines from the Ames panel and 302 from the Backcrossed Germplasm Enhancement of Maize (BGEM) panel in a combined panel of 679 lines. The lines were genotyped with 232 460 SNPs, and four root traits were collected from 14-day-old seedlings. We identified 30 SNPs significantly associated with root traits in the combined panel, whereas only two and six SNPs were detected in the Ames and BGEM panels, respectively. Those 38 SNPs were in linkage disequilibrium with 35 candidate genes. In addition, we found higher prediction accuracy in the combined panel than in the Ames or BGEM panel. We conclude that combining association panels appears to be a useful strategy to identify candidate genes associated with root traits in maize and improve the efficiency of genomic prediction.

Genetic Structure and Molecular Mechanisms Underlying the Formation of Tassel, Anther, and Pollen in the Male Inflorescence of Maize (Zea mays L.)

Maize tassel is the male reproductive organ which is located at the plant's apex; both its morphological structure and fertility have a profound impact on maize grain yield. More than 40 functional genes regulating the complex tassel traits have been cloned up to now. However, the detailed molecular mechanisms underlying the whole process, from male inflorescence meristem initiation to tassel morphogenesis, are seldom discussed. Here, we summarize the male inflorescence developmental genes and construct a molecular regulatory network to further reveal the molecular mechanisms underlying tassel-trait formation in maize. Meanwhile, as one of the most frequently studied quantitative traits, hundreds of quantitative trait loci (QTLs) and thousands of quantitative trait nucleotides (QTNs) related to tassel morphology have been identified so far. To reveal the genetic structure of tassel traits, we constructed a consensus physical map for tassel traits by summarizing the genetic studies conducted over the past 20 years, and identified 97 hotspot intervals (HSIs) that can be repeatedly mapped in different labs, which will be helpful for marker-assisted selection (MAS) in improving maize yield as well as for providing theoretical guidance in the subsequent identification of the functional genes modulating tassel morphology. In addition, maize is one of the most successful crops in utilizing heterosis; mining of the genic male sterility (GMS) genes is crucial in developing biotechnology-based male-sterility (BMS) systems for seed production and hybrid breeding. In maize, more than 30 GMS genes have been isolated and characterized, and at least 15 GMS genes have been promptly validated by CRISPR/Cas9 mutagenesis within the past two years. We thus summarize the maize GMS genes and further update the molecular regulatory networks underlying male fertility in maize. Taken together, the identified HSIs, genes and molecular mechanisms underlying tassel morphological structure and male fertility are useful for guiding the subsequent cloning of functional genes and for molecular design breeding in maize. Finally, the strategies concerning efficient and rapid isolation of genes controlling tassel morphological structure and male fertility and their application in maize molecular breeding are also discussed.

Genetic Variation in ZmPAT7 Contributes to Tassel Branch Number in Maize

Tassel branch number (TBN) is one of the important agronomic traits that contribute to the efficiency of seed production and has been selected strongly during the modern maize breeding process. However, the genetic mechanisms of TBN in maize are not entirely clear. In this study, we used a B73 × CML247 recombination inbred lines (RILs) population to detect quantitative trait loci (QTLs) for TBN. A total of four QTLs (qTBN2a, qTBN2b, qTBN4, and qTBN6) and six candidate genes were identified through expression analysis. Further, one of the candidates (GRMZM2G010011, ZmPAT7) encoding an S-acyltransferase was selected to validate its function by CRISPR-Cas9 technology, and its loss-of-function lines showed a significant increase in TBN. A key SNP(-101) variation in the promoter of ZmPAT7 was significantly associated with TBN. A total of 17 distant eQTLs associated with the expression of ZmPAT7 were identified in expression quantitative trait loci (eQTL) analysis, and ZmNAC3 may be a major factor involved in regulating ZmPAT7. These findings of the present study promote our understanding of the genetic basis of tassel architecture and provide new gene resources for maize breeding improvement.

GWAS with a PCA uncovers candidate genes for accumulations of microelements in maize seedlings

Microelements are necessary for plant growth and development, they control key processes of physiological metabolism. Herein, we evaluated three accumulation-related performances for each of the four microelements (Fe, Zn, Cu, and Mn) among 305 inbred maize lines. Quantification of these microelements in maize roots and shoots revealed abundant phenotypic variations in the association panel, with the variation coefficients ranging from 0.31 to 0.76. Principal component analysis (PCA) of the three related traits (concentration in root, concentration in shoot, and transport coefficient) showed that PC1 and PC2 explained >95% of phenotypic variations for each element. The scores of PC1 and PC2 were thereby used for a genome-wide association study by combining 44,134 SNPs of this panel. A total of 27, 1, 5, and 3 SNPs were significantly (P < .05) associated with Zn-PC1, Zn-PC2, Cu-PC1, and Mn-PC2, respectively, with 11 genes closely linked (r²  > 0.8) to these SNPs. Of them, GRMZM2G142870, GRMZM2G045531, and GRMZM2G143512 were individually annotated as ABC transporter C family member 14, zinc transporter 3, and heavy metal ATPase10. A candidate gene association analysis further verified that GRMZM2G142870 and GRMZM2G045531 affect Zn and Mn accumulations, respectively. Evaluation of contrasting allele ratios in elite lines indicated that the majority of the alleles correlating with higher Zn or Cu had not been utilized in maize breeding. Integration of more "higher-accumulation" alleles in the elite lines will be practical for improving Zn and Cu accumulations in maize. Our findings contribute to genetic revelation and molecular marker-assisted selection of microelement accumulations in maize.

QDtbn1 , an F-box gene affecting maize tassel branch number by a dominant model

Tassel branch number (TBN) is one of the important agronomic traits that directly contribute to grain yield in maize (Zea mays L.), and identification of genes precisely regulating TBN in the parental lines is important for maize hybrid breeding. In this study, a quantitative trait nucleotide (QTN), Q^Dtbn1 , related to tassel branch number was identified using a testcrossing association mapping population through association mapping with the Indels/SNPs in the 5'-UTR (untranslated region) of Zm00001d053358, which encodes a Kelch repeat-containing F-box protein. Q^Dtbn1 was further confirmed to be associated with TBN by a dominant model using an F₂ population, and over-expressing of the candidate gene resulted in a decreasing of TBN, implying that Q^Dtbn1 was governed by the candidate gene with a negative model. This makes Q^Dtbn1 very useful in maize hybrid breeding. Q^Dtbn1 could interact with a maize Skp1-like protein and a SnRK1 protein, and the SnRK1 could also interact with a SnRK2.8 protein. In addition, quantitative real-time PCR assay showed that five substrates of SnRK2 were down-regulated in the over-expressed plants. These imply that the SCF (Skp1/Cul1/F-box protein/Roc1) complex and ABA signal pathway might be involved in the modulation of TBN in maize.

Genetic analyses of lodging resistance and yield provide insights into post-Green-Revolution breeding in rice

Lodging reduces grain yield in cereal crops. Understanding the genetic basis of lodging resistance (LR) benefits LR breeding. In the study, 524 accessions from a rice germplasm collection and 193 recombinant inbred lines were phenotyped for 17 LR-related traits. Height and culm strength (the magnitude of applied force necessary to break the culm) were two major factors affecting LR. We conducted genome-wide association study (GWAS) and identified 127 LR-associated loci. Significant phenotypic correlations between culm-strength traits and yield-related traits were observed. To reveal the genetic relationship between them, we conducted GWAS of culm-strength traits with adding yield-related trait as a covariate and detected 63 loci linking culm strength and yield. As a proof, a near-isogenic line for an association locus on chromosome 7 showed enhanced LR and yield. Strikingly, 58 additional loci were identified in the covariate-added GWAS. Several LR-associated loci had undergone divergent selection. Linkage analysis supported the GWAS results. We propose that introgression of alleles beneficial for both culm strength and panicle weight without negative effects on panicle number or pyramiding high-yielding alleles and lodging-resistant alleles without effects on yield can be employed for the post-Green-Revolution breeding.