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Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A maize ( Zea mays L.) association mapping panel including 527 inbred lines with tropical, subtropical and temperate backgrounds, representing the global maize diversity, was genotyped using 1,536 single nucleotide polymorphisms (SNPs). In total, 926 SNPs with minor allele frequencies of ≥0.1 were used to estimate the pattern of genetic diversity and relatedness among individuals. The analysis revealed broad phenotypic diversity and complex genetic relatedness in the maize panel. Two different Bayesian approaches identified three specific subpopulations, which were then reconfirmed by principal component analysis (PCA) and tree-based analyses. Marker-trait associations were performed to assess the suitability of different models for false-positive correction by population structure (Q matrix/PCA) and familial kinship (K matrix) alone or in combination in this panel. The K, Q + K and PCA + K models could reduce the false positives, and the Q + K model performed slightly better for flowering time, ear height and ear diameter. Our findings suggest that this maize panel is suitable for association mapping in order to understand the relationship between genotypic and phenotypic variations for agriculturally complex quantitative traits using optimal statistical methods. [ABSTRACT FROM AUTHOR]

Leaf collection from the field, labeling and tracking back to the source plants after genotyping are rate limiting steps in leaf DNA-based genotyping. In this study, an optimized genotyping method using endosperm DNA sampled from single maize seeds was developed, which can be used to replace leaf DNA-based genotyping for both genetic studies and breeding applications. A similar approach is likely to be suitable for all plants with relatively large seeds. Part of the endosperm was excised from imbibed maize seeds and DNA extracted in 96-tube plates using individuals from eight F2 populations and seven inbreds. The quality of the resultant DNA was functionally comparable to DNA extracted from leaf tissue. Extraction from 30 mg of endosperm yields 3–10 μg DNA, which is sufficient for analysis of 200–400 agarose-gel PCR-based markers, with the potential for several million chip-based SNP marker analyses. By comparing endosperm DNA and leaf DNA for individuals from an F2 population, genotyping errors caused by pericarp contamination and hetero-fertilization were found to average 3.8 and 0.6%, respectively. Endosperm sampling did not affect germination rates under controlled conditions, although under normal field conditions the germination rate, seedling establishment, and growth vigor were significantly lower than that of non-sampled controls for some genotypes. However, careful field management can compensate for these effects. Seed DNA-based genotyping lowered costs by 24.6% compared to leaf DNA-based genotyping due to reduced field plantings and labor costs. A substantial advantage of this approach is that it can be used to select desirable genotypes before planting. As such it provides an opportunity for dramatic improvements in the efficiency and selective gain of breeding systems based on optimum combinations of marker-assisted selection and phenotypic selection within and between generations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The discovery and characterization of the opaque endosperm gene provide ideas and resources for the production and application of maize. We found an o213 mutant whose phenotype was opaque and shrunken endosperm with semi-dwarf plant height. The protein, lipid, and starch contents in the o213 endosperm were significantly decreased, while the free amino acid content in the o213 endosperm significantly increased. The aspartic acid, asparagine, and lysine contents were raised in the o213 endosperm by 6.5-, 8.5-, and 1.7-fold, respectively. Genetic analysis showed that this o213 mutant is a recessive single-gene mutation. The position mapping indicated that o213 is located in a 468-kb region that contains 11 protein-encoding genes on the long arm of chromosome 5. The coding sequence analysis of candidate genes between the WT and o213 showed that ZmYSL2 had only a single-base substitution (A–G) in the fifth exon, which caused methionine substitution to valine. Sequence analysis and the allelic test showed that o213 is a new mutant allele of ZmYSL2. The qRT-PCR results indicated that o213 is highly expressed in the stalks and anthers. Subcellular localization studies showed that o213 is a membrane transporter. In the variation analysis of o213, the amplification of 65 inbred lines in GWAS showed that this 3-bp deletion of the first exon of o213 was found only in temperate inbred lines, implying that the gene was artificially affected in the selection process. Our results suggest that o213 is an important endosperm development gene and may serve as a genetic resource. [ABSTRACT FROM AUTHOR]

Key message: Two read depth methods were jointly used in next-generation sequencing data to identify deletions in maize population. GWAS by deletions were analyzed for gene expression pattern and classical traits, respectively. Many studies have confirmed that structural variation (SV) is pervasive throughout the maize genome. Deletion is one type of SV that may impact gene expression and cause phenotypic changes in quantitative traits. In this study, two read count approaches were used to analyze the deletions in the whole-genome sequencing data of 270 maize inbred lines. A total of 19,754 deletion windows overlapped 12,751 genes, which were unevenly distributed across the genome. The deletions explained population structure well and correlated with genomic features. The deletion proportion of genes was determined to be negatively correlated with its expression. The detection of gene expression quantitative trait loci (eQTL) indicated that local eQTL were fewer but had larger effects than distant ones. The common associated genes were related to basic metabolic processes, whereas unique associated genes with eQTL played a role in the stress or stimulus responses in multiple tissues. Compared with the eQTL detected by SNPs derived from the same sequencing data, 89.4% of the associated genes could be detected by both markers. The effect of top eQTL detected by SNPs was usually larger than that detected by deletions for the same gene. A genome-wide association study (GWAS) on flowering time and plant height illustrated that only a few loci could be consistently captured by SNPs, suggesting that combining deletion and SNP for GWAS was an excellent strategy to dissect trait architecture. Our findings will provide insights into characteristic and biological function of genome-wide deletions in maize. [ABSTRACT FROM AUTHOR]

Vitamin A deficiency (VAD) compromises immune function and is the leading cause of preventable blindness in children in many developing countries. Biofortification, or breeding staple food crops that are rich in micronutrients, provides a sustainable way to fight VAD and other micronutrient malnutrition problems. Polymorphisms, with associated molecular markers, have recently been identified for two loci, LcyE (lycopene epsilon cyclase) and CrtRB1 (β-carotene hydroxylase 1) that govern critical steps in the carotenoid biosynthetic pathway in maize endosperm, thereby enabling the opportunity to integrate marker-assisted selection (MAS) into carotenoid breeding programs. We validated the effects of 3 polymorphisms (LcyE5′TE, LcyE3′Indel and CrtRB1-3′TE) in 26 diverse tropical genetic backgrounds. CrtRB1-3′TE had a two-ten fold effect on enhancing beta-carotene (BC) and total provitamin A (proA) content. Reduced-function, favorable polymorphisms within LcyE resulted in 0-30 % reduction in the ratio of alpha- to beta-branch carotenoids, and increase in proA content (sometimes statistically significant). CrtRB1-3′TE had large, significant effect on enhancing BC and total ProA content, irrespective of genetic constitution for LcyE5′TE. Genotypes with homozygous favorable CrtRB1-3′TE alleles had much less zeaxanthin and an average of 25 % less total carotenoid than other genotypes, suggesting that feedback inhibition may be reducing the total flux into the carotenoid pathway. Because this feedback inhibition was most pronounced in the homozygous favorable LcyE (reduced-function) genotypes, and because maximum total proA concentrations were achieved in genotypes with homozygous unfavorable or heterozygous LcyE, we recommend not selecting for both reduced-function genes in breeding programs. LcyE exhibited significant segregation distortion (SD) in all the eight, while CrtRB1 in five of eight digenic populations studied, with favorable alleles of both the genes frequently under-represented. MAS using markers reported herein can efficiently increase proA carotenoid concentration in maize. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Phosphorus deficiency is one of the major factors limiting plant growth and grain yield. Improving plant tolerance to Pi deficiency through genetic mechanism is an important source to increase grain yield. In this study, bioinformatics analysis, expression, and natural variation in ZmNAC134 gene with low Pi tolerant traits were analyzed under low Pi conditions. A total of 177 diverse heterotic groups of maize inbreds were used to identify the nucleotide diversity and alleles of ZmNAC134, which plays a vital role in the regulation of root architecture in response to Pi deficiency evolutionary results showed that ZmNAC134 has 3 homologous genes and these genes have one exon and conserved domain. The phenotypic traits showed significant difference for each of the 22 traits under deficient and sufficient Pi conditions. A total of 27 SNPs were identified in the coding region of ZmNAC134 and no InDels among 177 inbred lines. Among 27 SNPs, a total of 8 sites were highly significantly associated with multiple traits of low Pi tolerant trait index at − log10 P = 3.43. Although, 7 sites under Pi normal and 9 sites under Pi deficient conditions, of which four synonymous sites (position S24, S82, S164, and S1037) were associated with diverse number of traits in low Pi and normal Pi conditions and LD was not tight among these sites. Furthermore, the expression pattern was compared between Pi tolerant 178 and Pi sensitive 9782 inbred lines. ZmNAC134 was highly up-regulated in the roots and leaves of Pi tolerant 178 inbred line at 3 days, 7 days, and 9 days in roots and 7 days and 12 days in leaves while down-regulated in roots and leaves of Pi sensitive 9782 inbred line. In addition, protein encoded by ZmNAC134 was located in both nucleus and cytoplasm. Our findings provide the new insight of ZmNAC134 gene involved in low Pi stress and responsible against low Pi condition and the significant association of polymorphic loci with traits could be helpful to find out the molecular marker for genetic resources for further molecular maize breeding program. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Large phenotypic variations in the lead (Pb) concentration were observed in grains and leaves of maize plants. A further understanding of inheritance of Pb accumulation may facilitate improvement of low-Pb-accumulating cultivars in maize. A genome-wide association study was conducted in a population of 269 maize accessions with 43,737 single-nucleotide polymorphisms (SNPs). The Pb concentrations in leaves and kernels of 269 accessions were collected in pot-culture and field experiments in years of 2015 and 2016. Significant differences in Pb accumulation were found among individuals under different environments. Using the structure and kinship model, a total of 21 SNPs significantly associated with the Pb accumulation were identified with P < 2.28 × 10−5 and FDR < 0.05 in the pot-culture and field experiments across 2 years. Three SNPs on chromosome 4 had significant associations simultaneously with the Pb concentrations of kernels and leaves and were co-localized with the previously detected quantitative trait loci. Through ridge regression best linear unbiased prediction Pb accumulation in the association population, the prediction accuracies by cross validation were 0.18-0.59 and 0.17-0.64, depending on the k-fold and the size of the training population. The results are helpful for genetic improvement and genomic prediction of Pb accumulation in maize. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is the most important macronutrient for plant growth and development. Hence, understanding genetic architectures and functional genes involved in the response to N deficiency can greatly facilitate the development of low-N-tolerant cultivars. In this study, we collected 212 quantitative trait loci (QTL) of agronomically important traits under low-N stress conditions in maize. We then identified 21 consensus QTL (cQTL) strongly induced for low-N tolerance after excluding overlapping cQTL containing QTL simultaneously identified in meta-analyses of studies performed under other environmental conditions. Among the 21 cQTL, 30 candidate maize genes were identified from maize large-scale differential expression data derived from analyses of low-N stress, and the 12 most important maize orthologs were identified using homologous BLAST analyses of genes with known functions in N use efficiency in model plants. Furthermore, maize orthologs associated with low-N tolerance and metabolism were also predicted using large-scale expression data from other model plants. The present genetic loci and candidate genes indicate the molecular mechanisms of low-N tolerance in maize and may provide information for QTL fine mapping and molecular marker-assisted selection. [ABSTRACT FROM AUTHOR]

Molecular breeding for complex traits in crop plants requires understanding and manipulation of many factors influencing plant growth, development and responses to an array of biotic and abiotic stresses. Molecular marker-assisted breeding procedures can be facilitated and revolutionized through whole-genome strategies, which utilize full genome sequencing and genome-wide molecular markers to effectively address various genomic and environmental factors through a representative or complete set of genetic resources and breeding materials. These strategies are now increasingly based on understanding of specific genomic regions, genes/alleles, haplotypes, linkage disequilibrium (LD) block(s), gene networks and their contribution to specific phenotypes. Large-scale and high-density genotyping and genome-wide selection are two important components of these strategies. As components of whole-genome strategies, molecular breeding platforms and methodologies should be backed up by high throughput and precision phenotyping and e-typing (environmental assay) with strong support systems such as breeding informatics and decision support tools. Some basic strategies are discussed in this article, including (1) seed DNA-based genotyping for simplifying marker-assisted selection (MAS), reducing breeding cost and increasing scale and efficiency, (2) selective genotyping and phenotyping, combined with pooled DNA analysis, for capturing the most important contributing factors, (3) flexible genotyping systems, such as genotyping by sequencing and arraying, refined for different selection methods including MAS, marker-assisted recurrent selection and genomic selection (GS), (4) marker-trait association analysis using joint linkage and LD mapping, and (5) sequence-based strategies for marker development, allele mining, gene discovery and molecular breeding. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is required for numerous developmental processes, such as flowering and reproduction, in maize (Zea mays L.). It is also an essential nutrient in fertilizers to sustain high yields in farmlands with insufficient available phosphate, particularly in acid soils in China. Flowering time is a key factor influencing the adaptation of maize to the local environment and is associated with high yields. However, few studies have focused on the genetic characteristics of flowering time under low phosphate conditions. In this study, a recombinant inbred line (RIL) population derived from a cross between X178 and 9782 was evaluated for three flowering time traits under two phosphates (Pi) levels at four locations. We found that low phosphate significantly delayed the flowering stage of maize and proposed the hypothesis of "Phosphorus Accumulation Effect". Mixed-model-based composite interval mapping was used to dissect the genetic basis of the flowering time traits. A total of 41 quantitative trait loci (QTL) was identified for the three flowering time traits through four procedures. Among these 41 QTL, 38 focused on four hot regions, including bin 2.02, bin 2.03, bin 5.04, and bin 6.01. These regions and linked markers should be the targets for fine mapping, map-based cloning, and marker-assisted selection of flowering time and phosphate utilization efficiency. [ABSTRACT FROM AUTHOR]

A correction to the article "Mining for Low-Nitrogen Tolerance Genes by Integrating Meta-Analysis and Large-Scale Gene Expression Data From Maize" by Bowen Luo et al. that was published in a 2015 issue is presented.