Combining genome-wide association study and linkage mapping in the genetic dissection of amylose content in maize (Zea mays L.).

KEY MESSAGE: Integrated linkage and association analysis revealed genetic basis across multiple environments. The genes Zm00001d003102 and Zm00001d015905 were further verified to influence amylose content using gene-based association study. Maize kernel amylose is an important source of human food and industrial raw material. However, the genetic basis underlying maize amylose content is still obscure. Herein, we used an intermated B73 × Mo17 (IBM) Syn10 doubled haploid population composed of 222 lines and a germplasm set including 305 inbred lines to uncover the genetic control for amylose content under four environments. Linkage mapping detected 16 unique QTL, among which four were individually repeatedly identified across multiple environments. Genome-wide association study revealed 17 significant (P = 2.24E-06) single-nucleotide polymorphisms, of which two (SYN19568 and PZE-105090500) were located in the intervals of the mapped QTL (qAC2 and qAC5-3), respectively. According to the two population co-localized loci, 20 genes were confirmed as the candidate genes for amylose content. Gene-based association analysis indicated that the variants in Zm00001d003102 (Beta-16-galactosyltransferase GALT29A) and Zm00001d015905 (Sugar transporter 4a) affected amylose content across multi-environment. Tissue expression analysis showed that the two genes were specifically highly expressed in the ear and stem, respectively, suggesting that they might participate in sugar transport from source to sink organs. Our study provides valuable genetic information for breeding maize varieties with high amylose.

A combination of QTL mapping and genome-wide association study revealed the key gene for husk number in maize.

KEY MESSAGE: Two key genes Zm00001d021232 and Zm00001d048138 were identified by QTL mapping and GWAS. Additionally, they were verified to be significantly associated with maize husk number (HN) using gene-based association study. As a by-product of maize production, maize husk is an important industrial raw material. Husk layer number (HN) is an important trait that affects the yield of maize husk. However, the genetic mechanism underlying HN remains unclear. Herein, a total of 13 quantitative trait loci (QTL) controlling HN were identified in an IBM Syn 10 DH population across different locations. Among these, three QTL were individually repeatedly detected in at least two environments. Meanwhile, 26 unique single nucleotide polymorphisms (SNPs) were detected to be significantly (p < 2.15 × 10-6) associated with HN in an association pool. Of these SNPs, three were simultaneously detected across multiple environments or environments and best linear unbiased prediction (BLUP). We focused on these environment-stable and population-common genetic loci for excavating the candidate genes responsible for maize HN. Finally, 173 initial candidate genes were identified, of which 22 were involved in both multicellular organism development and single-multicellular organism process and thus confirmed as the candidate genes for HN. Gene-based association analyses revealed that the variants in four genes were significantly (p < 0.01/N) correlated with HN, of which Zm00001d021232 and Zm00001d048138 were highly expressed in husks and early developing ears among different maize tissues. Our study contributes to the understanding of genetic and molecular mechanisms of maize husk yield and industrial development in the future.

A genome-wide co-expression network analysis revealed ZmNRAMP6-mediated regulatory pathway involved in maize tolerance to lead stress.

KEY MESSAGE: A metal transporter ZmNRAMP6 was identified by using a trait-associated co-expression network analysis at a genome-wide level. ZmNRAMP6 confers maize sensitivity to Pb by accumulating it to maize shoots. ZmNRAMP6 knockout detains Pb in roots, activates antioxidant enzymes, and improves Pb tolerance. Lead (Pb) is one of the most toxic heavy metal pollutants, which can penetrate plant cells via root absorption and thus cause irreversible damages to the human body through the food chain. To identify the key gene responsible for Pb tolerance in maize, we performed a trait-associated co-expression network analysis at a genome-wide level, using two maize lines with contrasting Pb tolerances. Finally, ZmNRAMP6 that encodes a metal transporter was identified as the key gene among the Pb tolerance-associated co-expression module. Heterologous expression of ZmNRAMP6 in yeast verified its role in Pb transport. Combined Arabidopsis overexpression and maize mutant analysis suggested that ZmNRAMP6 conferred plant sensitivity to Pb stress by mediating Pb distribution across the roots and shoots. Knockout of ZmNRAMP6 caused Pb retention in the roots and activation of the antioxidant enzyme system, resulting in an increased Pb tolerance in maize. ZmNRAMP6 was likely to transport Pb from the roots to shoots and environment. An integration of yeast one-hybrid and dual-luciferase reporter assay uncovered that ZmNRAMP6 was negatively regulated by a known Pb tolerance-related transcript factor ZmbZIP54. Collectively, knockout of ZmNRAMP6 will aid in the bioremediation of contaminated soil and food safety guarantee of forage and grain corn.

GWAS across multiple environments and WGCNA suggest the involvement of ZmARF23 in embryonic callus induction from immature maize embryos.

KEY MESSAGE: Combined GWAS, WGCNA, and gene-based association studies identified the co-expression network and hub genes for maize EC induction. ZmARF23 bound to ZmSAUR15 promoter and regulated its expression, affecting EC induction. Embryonic callus (EC) induction in immature maize embryos shows high genotype dependence, which limits the application of genetic transformation in transgenic breeding and gene function elucidation in maize. Herein, we conducted a genome-wide association mapping (GWAS) for four EC induction-related traits, namely rate of embryonic callus induction (REC), increased callus diameter (ICD), ratio of shoot formation (RSF), and length of shoot (LS) across different environments. A total of 77 SNPs were significantly associated these traits under three environments and using the averages (across environments). Among these significant SNPs, five were simultaneously detected under multiple environments and 11 had respective phenotypic variation explained > 10%. A total of 257 genes were located in the linkage disequilibrium decay of these REC- and ICD-associated SNPs, of which 178 were responsive to EC induction. According to the expression values of the 178 genes, we performed a weighted gene co-expression network analysis (WGCNA) and revealed an EC induction-associated module and five hub genes. Hub gene-based association studies uncovered that the intragenic variations in GRMZM2G105473 and ZmARF23 influenced EC induction efficiency among different maize lines. Dual-luciferase reporter assay indicated that ZmARF23 bound to the promoter of a known causal gene (ZmSAUR15) for EC induction and positively regulated its expression on the transcription level. Our study will deepen the understanding of genetic and molecular mechanisms underlying EC induction and contribute to the use of genetic transformation in maize.

Combined linkage mapping and association analysis uncovers candidate genes for 25 leaf-related traits across three environments in maize.

KEY MESSAGE: Combined linkage and association analysis revealed five co-localized genetic loci across multiple environments. The key gene Zm00001d026491 was further verified to influence leaf length by candidate gene association analysis. Leaf morphology and number determine the canopy structure and thus affect crop yield. Herein, the genetic basis and key genes for 25 leaf-related traits, including leaf lengths (LL), leaf widths (LW), and leaf areas (LA) of eight continuous leaves under the tassel, and the number of leaves above the primary ear (LAE), were dissected by using an association panel and a biparental population. Using an intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, 290 quantitative trait loci (QTL) controlling these traits were detected across different locations, among which 115 QTL were individually repeatedly identified in at least two environments. Using the association panel, 165 unique significant single-nucleotide polymorphisms (SNPs) were associated with target traits (P < 2.15E-06), of which 35 were separately detected across multiple environments. In total, 42 pleiotropic QTL/SNPs (pQTL/SNPs) were responsible for at least two of the LL, LW, LA, and LAE traits across multiple environments. Combining the QTL mapping and association study, five unique SNPs were located within the confidence intervals of seven QTL, and 77 genes were identified based on the linkage disequilibrium regions of co-localized SNP loci. Gene-based association studies verified that the intragenic variants in the candidate gene Zm00001d026491 influenced LL of the third leaf counted from the top node. These findings will provide vital information to understanding the genetic basis of leaf-related traits and help to cultivate maize varieties with ideal plant architecture.

Genome-Wide Association Study Discovers Novel Germplasm Resources and Genetic Loci with Resistance to Gibberella Ear Rot Caused by Fusarium graminearum.

Gibberella ear rot (GER) in maize caused by Fusarium graminearum is one of the most devastating maize diseases reducing grain yield and quality worldwide. The genetic bases of maize GER resistance remain largely unknown. Using artificial inoculation across multiple environments, the GER severity of an association panel consisting of 316 diverse inbred lines was observed with wide phenotypic variation. In the association panel, a genome-wide association study using a general linear model identified 69 single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance at the threshold of 2.04 × 10-5, and the average phenotypic variation explained (PVE) of these SNPs was 5.09%. We also conducted a genome-wide association study analysis using a mixed linear model at a threshold of 1.0 × 10-4, and 16 significantly associated SNPs with an average PVE of 4.73% were detected. A combined general linear model and mixed linear model method obtained 10 co-localized significantly associated SNPs linked to GER resistance, including the most significant SNP (PZE-105079915) with the greatest PVE value, 9.07%, at bin 5.05 following 10 candidate genes. These findings are significant for the exploration of the complicated genetic variations in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the elite germplasm resources that can be used for breeding GER resistance in maize.

A Combination of QTL Mapping and GradedPool-Seq to Dissect Genetic Complexity for Gibberella Ear Rot Resistance in Maize Using an IBM Syn10 DH Population.

Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most devastating maize diseases that reduces grain yield and quality worldwide. Utilization of host genetic resistance has become one of the most suitable strategies to control GER. In this study, a set of 246 diverse inbred lines derived from the intermated B 73 × Mo 17 doubled haploid population (IBM Syn10 DH) were used to detect quantitative trait loci (QTL) associated with resistance to GER. Meanwhile, a GradedPool-Seq (GPS) approach was performed to identify genomic variations involved in GER resistance. Using artificial inoculation across multiple environments, GER severity of the population was observed with wide phenotypic variation. Based on the linkage mapping, a total of 14 resistant QTLs were detected, accounting for 5.11 to 14.87% of the phenotypic variation, respectively. In GPS analysis, five significant single nucleotide polymorphisms (SNPs) associated with GER resistance were identified. Combining QTL mapping and GPS analysis, a peak-value SNP on chromosome 4 from GPS was overlapped with the QTL qGER4.2, suggesting that the colocalized region could be the most possible target location conferring resistance to GER. Subsequently, seven candidate genes were identified within the peak SNP, linking them to GER resistance. These findings are useful for exploring the complicated genetic variations in maize GER resistance. The genomic regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the combined strategy that can be used for quantitative traits in plant species.

Integrated analysis of long non-coding RNAs and mRNAs reveals the regulatory network of maize seedling root responding to salt stress.

BACKGROUND: Long non-coding RNAs (lncRNAs) play important roles in response to abiotic stresses in plants, by acting as cis- or trans-acting regulators of protein-coding genes. As a widely cultivated crop worldwide, maize is sensitive to salt stress particularly at the seedling stage. However, it is unclear how the expressions of protein-coding genes are affected by non-coding RNAs in maize responding to salt tolerance. RESULTS: The whole transcriptome sequencing was employed to investigate the differential lncRNAs and target transcripts responding to salt stress between two maize inbred lines with contrasting salt tolerance. We developed a flexible, user-friendly, and modular RNA analysis workflow, which facilitated the identification of lncRNAs and novel mRNAs from whole transcriptome data. Using the workflow, 12,817 lncRNAs and 8,320 novel mRNAs in maize seedling roots were identified and characterized. A total of 742 lncRNAs and 7,835 mRNAs were identified as salt stress-responsive transcripts. Moreover, we obtained 41 cis- and 81 trans-target mRNA for 88 of the lncRNAs. Among these target transcripts, 11 belonged to 7 transcription factor (TF) families including bHLH, C2H2, Hap3/NF-YB, HAS, MYB, WD40, and WRKY. The above 8,577 salt stress-responsive transcripts were further classified into 28 modules by weighted gene co-expression network analysis. In the salt-tolerant module, we constructed an interaction network containing 79 nodes and 3081 edges, which included 5 lncRNAs, 18 TFs and 56 functional transcripts (FTs). As a trans-acting regulator, the lncRNA MSTRG.8888.1 affected the expressions of some salt tolerance-relative FTs, including protein-serine/threonine phosphatase 2C and galactinol synthase 1, by regulating the expression of the bHLH TF. CONCLUSIONS: The contrasting genetic backgrounds of the two inbred lines generated considerable variations in the expression abundance of lncRNAs and protein-coding transcripts. In the co-expression networks responding to salt stress, some TFs were targeted by the lncRNAs, which further regulated the salt tolerance-related functional transcripts. We constructed a regulatory pathway of maize seedlings to salt stress, which was mediated by the hub lncRNA MSTRG.8888.1 and participated by the bHLH TF and its downstream target transcripts. Future work will be focused on the functional revelation of the regulatory pathway.

GWAS and transcriptome analysis reveal MADS26 involved in seed germination ability in maize.

KEY MESSAGE: MADS26 affecting maize seed germination was identified by GWAS and transcriptomics. Gene-based association analyses revealed three variations within MADS26 regulating seed germination traits. Overexpressed MADS26 in Arabidopsis improved seed germination. Seed germination ability is extremely important for maize production. Exploring the genetic control of seed germination ability is useful for improving maize yield. In this study, a genome-wide association study (GWAS) was conducted to excavate the significant SNPs involved in seed germination ability based on an association panel consisting of 300 lines. A total of 11 SNPs and 75 candidate genes were significantly associated with the seed germination traits. In addition, we constructed 24 transcriptome libraries from maize seeds at four germination stages using two inbred lines with contrasting germination rates. In total, 15,865 differentially expressed genes were induced during seed germination. Integrating the results of GWAS and transcriptome analysis uncovered four prioritized genes underlying maize seed germination. The variations located in the promoter of Zm00001d017932, a MADS-transcription factor 26 (MADS26), were verified to affect the seed germination, and the haplotype TAT was determined as a favorable haplotype for high-germination capability. MADS26 was induced to express by ethylene during seed germination in maize and overexpressing MADS26 increased the seed germination ability in Arabidopsis. These findings will contribute to understanding of the genetic and molecular mechanisms on seed germination and the genetic modification of seed germination ability in maize.

Joint GWAS and WGCNA uncover the genetic control of calcium accumulation under salt treatment in maize seedlings.

Soil salinization is an important factor threatening the yield and quality of maize. Ca2+ plays a considerable role in regulating plant growth under salt stress. Herein, we examined the shoot Ca2+ concentrations, root Ca2+ concentrations, and transport coefficients of seedlings in an association panel composed of 305 maize inbred lines under normal and salt conditions. A genome-wide association study was conducted by using the investigated phenotypes and 46,408 single-nucleotide polymorphisms of the panel. As a result, 53 significant SNPs were specifically detected under salt treatment, and 544 genes were identified in the linkage disequilibrium regions of these SNPs. According to the expression data of the 544 genes, we carried out a weighted coexpression network analysis. Combining the enrichment analyses and functional annotations, four hub genes (GRMZM2G051032, GRMZM2G004314, GRMZM2G421669, and GRMZM2G123314) were finally determined, which were then used to evaluate the genetic variation effects by gene-based association analysis. Only GRMZM2G123314, which encodes a pentatricopeptide repeat protein, was significantly associated with Ca2+ transport and the haplotype G-CT was identified as the superior haplotype. Our study brings novel insights into the genetic and molecular mechanisms of salt stress response and contributes to the development of salt-tolerant varieties in maize.

A Combination of a Genome-Wide Association Study and a Transcriptome Analysis Reveals circRNAs as New Regulators Involved in the Response to Salt Stress in Maize.

Salinization seriously threatens the normal growth of maize, especially at the seedling stage. Recent studies have demonstrated that circular RNAs (circRNAs) play vital roles in the regulation of plant stress resistance. Here, we performed a genome-wide association study (GWAS) on the survival rate of 300 maize accessions under a salt stress treatment. A total of 5 trait-associated SNPs and 86 candidate genes were obtained by the GWAS. We performed RNA sequencing for 28 transcriptome libraries derived from 2 maize lines with contrasting salt tolerance under normal and salt treatment conditions. A total of 1217 highly expressed circRNAs were identified, of which 371 were responsive to a salt treatment. Using PCR and Sanger sequencing, we verified the reliability of these differentially expressed circRNAs. An integration of the GWAS and RNA-Seq analyses uncovered two differentially expressed hub genes (Zm00001eb013650 and Zm00001eb198930), which were regulated by four circRNAs. Based on these results, we constructed a regulation model of circRNA/miRNA/mRNA that mediated salt stress tolerance in maize. By conducting hub gene-based association analyses, we detected a favorable haplotype in Zm00001eb198930, which was responsible for high salt tolerance. These results help to clarify the regulatory relationship between circRNAs and their target genes as well as to develop salt-tolerant lines for maize breeding.

An Integration of Linkage Mapping and GWAS Reveals the Key Genes for Ear Shank Length in Maize.

Ear shank length (ESL) has significant effects on grain yield and kernel dehydration rate in maize. Herein, linkage mapping and genome-wide association study were combined to reveal the genetic architecture of maize ESL. Sixteen quantitative trait loci (QTL) were identified in the segregation population, among which five were repeatedly detected across multiple environments. Meanwhile, 23 single nucleotide polymorphisms were associated with the ESL in the association panel, of which four were located in the QTL identified by linkage mapping and were designated as the population-common loci. A total of 42 genes residing in the linkage disequilibrium regions of these common variants and 12 of them were responsive to ear shank elongation. Of the 12 genes, five encode leucine-rich repeat receptor-like protein kinases, proline-rich proteins, and cyclin11, respectively, which were previously shown to regulate cell division, expansion, and elongation. Gene-based association analyses revealed that the variant located in Cyclin11 promoter affected the ESL among different lines. Cyclin11 showed the highest expression in the ear shank 15 days after silking among diverse tissues of maize, suggesting its role in modulating ESL. Our study contributes to the understanding of the genetic mechanism underlying maize ESL and genetic modification of maize dehydration rate and kernel yield.

Combined QTL Mapping across Multiple Environments and Co-Expression Network Analysis Identified Key Genes for Embryogenic Callus Induction from Immature Maize Embryos.

The ability of immature embryos to induce embryogenic callus (EC) is crucial for genetic transformation in maize, which is highly genotype-dependent. To dissect the genetic basis of maize EC induction, we conducted QTL mapping for four EC induction-related traits, the rate of embryogenic callus induction (REC), rate of shoot formation (RSF), length of shoot (LS), and diameter of callus (DC) under three environments by using an IBM Syn10 DH population derived from a cross of B73 and Mo17. These EC induction traits showed high broad-sense heritability (>80%), and significantly negative correlations were observed between REC and each of the other traits across multiple environments. A total of 41 QTLs for EC induction were identified, among which 13, 12, 10, and 6 QTLs were responsible for DC, RSF, LS, and REC, respectively. Among them, three major QTLs accounted for >10% of the phenotypic variation, including qLS1-1 (11.54%), qLS1-3 (10.68%), and qREC4-1 (11.45%). Based on the expression data of the 215 candidate genes located in these QTL intervals, we performed a weighted gene co-expression network analysis (WGCNA). A combined use of KEGG pathway enrichment and eigengene-based connectivity (KME) values identified the EC induction-associated module and four hub genes (Zm00001d028477, Zm00001d047896, Zm00001d034388, and Zm00001d022542). Gene-based association analyses validated that the variations in Zm00001d028477 and Zm00001d034388, which were involved in tryptophan biosynthesis and metabolism, respectively, significantly affected EC induction ability among different inbred lines. Our study brings novel insights into the genetic and molecular mechanisms of EC induction and helps to promote marker-assisted selection of high-REC varieties in maize.

Genetic dissection of maize seedling traits in an IBM Syn10 DH population under the combined stress of lead and cadmium.

The heavy metals lead and cadmium have become important pollutants in the environment, which exert negative effects on plant morphology, growth and photosynthesis. It is particularly significant to uncover the genetic loci and the causal genes for lead and cadmium tolerance in plants. This study used an IBM Syn10 DH population to identify the quantitative trait loci (QTL) controlling maize seedling tolerance to lead and cadmium by linkage mapping. The broad-sense heritability of these seedling traits ranged from 65.8-97.3% and 32.0-98.8% under control (CK) and treatment (T) conditions, respectively. A total of 53 and 64 QTL were detected under CK and T conditions, respectively. Moreover, 42 QTL were identified using lead and cadmium tolerance coefficient (LCTC). Among these QTL, five and two major QTL that explained > 10% of phenotypic variation were identified under T condition and using LCTC, respectively. Furthermore, eight QTL were simultaneously identified by T and LCTC, explaining 5.23% to 9.21% of the phenotypic variations. Within these major and common QTL responsible for the combined heavy metal tolerance, four candidate genes (Zm00001d048759, Zm00001d004689, Zm00001d004843, Zm00001d033527) were previously reported to correlate with heavy metal transport and tolerance. These findings will contribute to functional gene identification and molecular marker-assisted breeding for improving heavy metal tolerance in maize.

GWAS and WGCNA uncover hub genes controlling salt tolerance in maize (Zea mays L.) seedlings.

KEYMESSAGE: Two hub genes GRMZM2G075104 and GRMZM2G333183 involved in salt tolerance were identified by GWAS and WGCNA. Furthermore, they were verified to affect salt tolerance by candidate gene association analysis. Salt stress influences maize growth and development. To decode the genetic basis and hub genes controlling salt tolerance is a meaningful exploration for cultivating salt-tolerant maize varieties. Herein, we used an association panel consisting of 305 lines to identify the genetic loci responsible for Na+- and K+-related traits in maize seedlings. Under the salt stress, seven significant single nucleotide polymorphisms were identified using a genome-wide association study, and 120 genes were obtained by scanning the linkage disequilibrium regions of these loci. According to the transcriptome data of the above 120 genes under salinity treatment, we conducted a weighted gene co-expression network analysis. Combined the gene annotations, two SNaC/SKC (shoot Na+ content/shoot K+ content)-associated genes GRMZM2G075104 and GRMZM2G333183 were finally identified as the hub genes involved in salt tolerance. Subsequently, these two genes were verified to affect salt tolerance of maize seedlings by candidate gene association analysis. Haplotypes TTGTCCG-CT and CTT were determined as favorable/salt-tolerance haplotypes for GRMZM2G075104 and GRMZM2G333183, respectively. These findings provide novel insights into genetic architectures underlying maize salt tolerance and contribute to the cultivation of salt-tolerant varieties in maize.

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.

Identification and fine mapping of a recessive gene controlling zebra leaf phenotype in maize.

Leaf color mutant is an important resource for studying chlorophyll biosynthesis and chloroplast development in maize. Here, a novel mutant zebra crossband 9 (zb9) with transverse green-/yellow-striped leaves appeared from ten-leaf stage until senescence was identified from mutant population derived from the maize inbred line RP125. The yellow section of the zb9 mutant displays a reduction of chlorophyll and carotenoid contents, as well as impaired chloroplast structure. Genetic analysis showed that the zb9 mutant phenotype was caused by a single recessive gene. Map-based cloning demonstrated that the zb9 locus was delimited into a 648 kb region on chromosome 1 covering thirteen open reading frames (ORFs). Among them, a point mutation (G to A) in exon 2 of the gene Zm00001d029151, named Zmzb9, was identified based on sequencing analysis. The causal gene Zmzb9 encodes UDP-glucose-4-epimerase 4 (UGE4), a key enzyme involved in chloroplast development and was considered as the only candidate gene controlling the mutant phenotype. Expression patterns indicated that the causal gene was abundantly expressed in the leaves and sheaths, as well as significantly downregulated in the mutant compared to that in the wild type. Subcellular localization showed that ZmZB9 was localized in chloroplasts and implied the putative gene involved in chloroplast development. Taken together, we propose that the causal gene Zmzb9 tightly associated with the zebra leaf phenotype, and the obtained gene here will help to uncover the regulatory mechanism of pigment biosynthesis and chloroplast development in maize. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01202-7.

Combined GWAS and QTL analysis for dissecting the genetic architecture of kernel test weight in maize.

Kernel weight in a unit volume is referred to as kernel test weight (KTW) that directly reflects maize (Zea mays L.) grain quality. In this study, an inter-mated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population and an association panel were used to identify loci responsible for KTW of maize across multiple environments. A total of 18 significant KTW-related single-nucleotide polymorphisms (SNPs) were identified using genome-wide association study (GWAS); they were closely linked to 12 candidate genes. In the IBM Syn10 DH population, linkage analysis detected 19 common quantitative trait loci (QTL), five of which were repeatedly detected among multiple environments. Several verified genes that regulate maize seed development were found in the confidence intervals of the mapped QTL and the LD regions of GWAS, such as ZmYUC1, BAP2, ZmTCRR-1, dek36 and ZmSWEET4c. Combined QTL mapping and GWAS identified one significant SNP that was co-identified in the both populations. Based on the co-localized SNP across the both populations, 17 candidate genes were identified. Of them, Zm00001d044075, Zm00001d044086, and Zm00001d044081 were further identified by candidate gene association study for KTW. Zm00001d044081 encodes homeobox-leucine zipper protein ATHB-4, which has been demonstrated to control apical embryo development in Arabidopsis. Our findings provided insights into the mechanism underlying maize KTW and contributed to the application of molecular-assisted selection of high KTW breeding in maize.

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping.

Kernel size-related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10-6 ) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10-3 ) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable-effect SNPs and the co-localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co-localized SNPs, of which zma-miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma-miR164e resulted in the down-regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker-assisted selection (MAS) for high-yield breeding in maize.

A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments.

KEY MESSAGE: Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which control yield-related traits in maize. The candidate gene GRMZM2G098557 was further validated to regulate ear row number by using a segregation population. Understanding the genetic basis of yield-related traits contributes to the improvement of grain yield in maize. This study used an inter-mated B73 × Mo17 (IBM) Syn10 doubled-haploid (DH) population and an association panel to identify the genetic loci responsible for nine yield-related traits in maize. Using quantitative trait loci (QTL) mapping, 100 QTL influencing these traits were detected across different environments in the IBM Syn10 DH population, with 25 co-detected in multiple environments. Using a genome-wide association study (GWAS), 138 single-nucleotide polymorphisms (SNPs) were identified as correlated with these traits (P < 2.04E-06) in the association panel. Twenty-one pleiotropic QTL/SNPs were identified to control different traits in both populations. A combination of QTL mapping and GWAS uncovered eight significant SNPs (PZE-101097575, PZE-103169263, ZM011204-0763, PZE-104044017, PZE-104123110, SYN8062, PZE-108060911, and PZE-102043341) that were co-located within seven QTL confidence intervals. According to the eight co-localized SNPs by the two populations, 52 candidate genes were identified, among which the ear row number (ERN)-associated SNP SYN8062 was closely linked to SBP-transcription factor 7 (GRMZM2G098557). Several SBP-transcription factors were previously demonstrated to modulate maize ERN. We then validated the phenotypic effects of SYN8062 in the IBM Syn10 DH population, indicating that the ERN of the lines with the A-allele in SYN8062 was significantly (P < 0.05) larger than that of the lines with the G-allele in SYN8062 in each environment. These findings provide valuable information for understanding the genetic mechanisms of maize grain yield formation and for improving molecular marker-assisted selection for the high-yield breeding of maize.