Traits In Maize Research Articles

Effect of Water Stress, Nitrogen and Potassium Fertilizers on Maize Yield Productivity

Two field experiments were carried out at the Farm of Agric. Res. and Exp. Center of Fac. of Agric. Moshtohor, Benha University, Toukh Directorate, Qalyubia Governorate, Egypt, during two successive summer growing seasons of 2015 and 2016 to study the effect of three water stress, i.e. normal irrigation, skipping the second irrigation (skipping one irrigation during vegetative growth stage) and skipping the fifth irrigation (skipping one irrigation during kernels filling stage) and four nitrogen fertilizer rates, i.e. 0, 50, 100 and 150kg N/fed as well as three potassium fertilizer rates, i.e. 0, 24 and 48 kg K2O/fed on growth, yield and its components as well as some kernels chemical properties of maize (white single cross hybrid 2031 for Misr hytech Seed Int.,). Results of combined analysis of the two seasons showed that kernels filling stage was the most sensitive to water deficit stress and preventing irrigation at this stage (skipping the 5th irrigation) caused marked decrease in mean values of allmost maize yield and its components, while, full irrigation treatment appeared to be the best irrigation treatment sine it enhanced all maize traits under study. Planting maize under water stress by skipping the 2nd irrigation and skipping the 5th irrigation significantly decreased mean values of grain yield/fed (kg) by 25.49 and 41.04 % respectively, compared to mean values of grain yield/fed (kg) of maize under normal irrigation. Planting maize when received 150 kg N/fed caused significant increase in all mean values of maize traits under study such as plant height (cm), ear height (cm), No. of ears/fed, ear diameter (cm), ear length (cm), No. of rows/ear, No. of kernels/row, No. of kernels/ear, ear weight (g), kernels weight/ear (g), kernels shelling (%), 100-kernel weight (g), ear yield/fed (kg), grain yield/fed (kg), stover yield/fed (kg), biological yield/fed (kg), harvest index (%), kernels nitrogen content (%), kernels crude protein (%), nitrogen uptake/fed (kg) and protein yield/fed (kg) Meanwhile, the highest mean values of potassium use efficiency (KUE) which were recorded from growing maize when received 100 kg N/fed. Growing maize under the higher potassium rate (48 kg K2O/fed) was produced the maximum mean values of plant height (cm), No. of ears/fed, ear length (cm), No. of kernels/row, No. of kernels/ear, ear weight (g), kernels weight/ear (g), 100-kernel weight (g), kernels shelling (%), ear yield/fed (kg), grain yield/fed (kg), stover yield/fed (kg), biological yield/fed (kg), harvest index (%), kernels potassium content (%), nitrogen uptake/fed (kg) and protein yield/fed (kg) while, the highest mean values of KUE which were recorded from growing maize when received 24 kg K2O/fed. The first order interactions between (normal irrigation X 150 Kg N/fed), (normal irrigation X 48 kg K2O/fed) and (150 Kg N/fed X 48 kg K2O/fed) as well as the second order interaction between normal irrigation X 150 Kg N/fed X 48 kg K2O/fed) were significantly recorded the greatest mean values of maize yield and its components as compared with the others interactions. It could be summarized that grown maize under full irrigation and fertilization by 150 Kg N + 48 kg K2O/fed in order to maximizing its productivity.

EFFECT OF NITROGEN LEVELS AND APPLICATION SCHEDULING ON THE GROWTH AND YIELD OF MAIZE

A field trial was conducted to assess the effect of Nitrogen (N) levels and application scheduling on the growth and grain yield of maize. The results revealed that growth and grain yield traits of maize were influenced significantly (P<0.01) due to different Nitrogen (N) levels and application schedule. Crop fertilized with the highest Nitrogen (N) level of 180 kg per ha resulted from 185.07 cm plant height, 11.94 leaves per plant, 473.92 cm leaf area per plant, 1.73 cobs per plant, 347.91 grains per cob, 15650.33 kg biomass yield and 3030.28 kg grain yield per ha. The crop receiving Nitrogen (N) at the rate of 120 kg per ha gave 177.67 cm plant height, 10.91 leaves per plant, 464.44 cm leaf area per plant, 1.60 cobs per plant, 237.04 grains per cob, 14241.80 kg biomass yield and 2762.30 kg grain yield per ha; while lowest Nitrogen (N) rate of 60 kg per ha resulted from 170.26 cm plant height, 9.89 leaves per plant, 455.15 cm leaf area per plant, 1.47 cobs per plant, 307.41 grains per cob, 13672.13 kg biomass yield and 2541.32 kg grain yield per ha. The effect of the scheduling of Nitrogen (N) application suggested that Nitrogen (N) applied in four equal splits, 25% each, 14, 28 and 42 days after emergence (DAE) ranked 1st

Genetic Dissection of the General Combining Ability of Yield-Related Traits in Maize.

Maize yield components including row number, kernel number per row, kernel thickness, kernel width, kernel length, 100-kernel weight, and volume weight affect grain yield directly. Previous studies mainly focused on dissecting the genetic basis of per se performances for yield-related traits, but the genetic basis of general combining ability (GCA) for these traits is still unclear. In the present study, 328 RILs were crossed as males to two testers according to the NCII mating design, resulting in a hybrid panel composed of 656 hybrids. Both the hybrids and parental lines were evaluated in four environments in 2015 and 2016. Correlation analysis showed the performances of GCA effects were significantly correlated to the per se performances of RILs for all yield-related traits (0.17 ≤ r ≤ 0.64, P > 0.01). Only 17 of 95 QTL could be detected for both per se performances of RILs and GCA effects for eight yield-related traits. The QTL qKN7-1 and qHKW1-3, which could explain more than 10% of the variation in the GCA effects of KN and HKW, were also detected for per se performances for the traits. The pleiotropic loci qRN3-1 and qRN6, which together explained 14.92% of the observed variation in GCA effects for RN, were associated with the GCA effects of KW and HKW, but not with per se performances for these traits. In contrast, Incw1, which was related to seed weight in maize, was mapped to the region surrounding MK2567 at the qHKW5-2 locus, but no GCA effect was detected. The QTL identified in present study for per se performances and corresponding GCA effects for yield-related traits might be useful for maize hybrid breeding.

Genome wide association analysis of a stemborer egg induced \u201ccall-for-help\u201d defence trait in maize

Tritrophic interactions allow plants to recruit natural enemies for protection against herbivory. Here we investigated genetic variability in induced responses to stemborer egg-laying in maize Zea mays (L.) (Poaceae). We conducted a genome wide association study (GWAS) of 146 maize genotypes comprising of landraces, inbred lines and commercial hybrids. Plants were phenotyped in bioassays measuring parasitic wasp Cotesia sesamiae (Cameron) (Hymenoptera: Braconidae) attraction to volatiles collected from plants exposed to stemborer Chilo partellus (Swinhoe) (Lepidoptera: Crambidae) eggs. Genotyping-by-sequencing was used to generate maize germplasm SNP data for GWAS. The egg-induced parasitoid attraction trait was more common in landraces than in improved inbred lines and hybrids. GWAS identified 101 marker-trait associations (MTAs), some of which were adjacent to genes involved in the JA-defence pathway (opr7, aos1, 2, 3), terpene biosynthesis (fps3, tps2, 3, 4, 5, 7, 9, 10), benzoxazinone synthesis (bx7, 9) and known resistance genes (e.g. maize insect resistance 1, mir1). Intriguingly, there was also association with a transmembrane protein kinase that may function as a receptor for the egg elicitor and other genes implicated in early plant defence signalling. We report maize genomic regions associated with indirect defence and provide a valuable resource for future studies of tritrophic interactions in maize. The markers identified may facilitate selection of indirect defence by maize breeders.

QTL Mapping and Prediction of Haploid Male Fertility Traits in Maize (Zea mays L.).

Chromosome doubling of maize haploids is a bottleneck in the large-scale application of doubled haploid (DH) technology. Spontaneous chromosome doubling (SCD) of haploid has been taken as an important method in the production of DH lines and low haploid male fertility (HMF) is a main limiting factor for the use of SCD. To study its genetic basis, haploids of 119 DH lines derived from a cross between inbred lines Qi319 and Chang7-2 were used to map the quantitative trait locus (QTL) contributing to HMF. Three traits including anther emergence rate (AER), anther emergence score (AES) and pollen production score (PPS) of the haploid population were evaluated at two locations. The heritability of the three traits ranged from 0.70 to 0.81. The QTL contributing to AER, AES and PPS were identified on the chromosomes 1, 2, 3, 4, 5, 7, 9 and 10. Five major QTL, qAER5-1, qAER5-2, qAES3, qPPS1 and qPPS5, were found and each could explain more than 15% of the phenotypic variance at least in one environment. Two major QTL, qPPS1 and qPPS5, and two minor QTL, qAES2 and qAER3, were repeatedly detected at both locations. To increase the application efficiency of HMF in breeding programs, genomic prediction for the three traits were carried out with ridge regression best linear unbiased prediction (rrBLUP) and rrBLUP adding QTL effects (rrBLUP-QTL). The prediction accuracies of rrBLUP-QTL were significantly higher than that by rrBLUP for three traits (p < 0.001), which indirectly indicates these QTL were effective. The prediction accuracies for PPS were 0.604 (rrBLUP) and 0.703 (rrBLUP-QTL) across both locations, which were higher than that of AER and AES. Overall, this study provides important information to understand the genetic architecture of SCD of maize haploids.

Temporal covariance structure of multi-spectral phenotypes and their predictive ability for end-of-season traits in maize

Key messageHeritable variation in phenotypes extracted from multi-spectral images (MSIs) and strong genetic correlations with end-of-season traits indicates the value of MSIs for crop improvement and modeling of plant growth curve.Vegetation indices (VIs) derived from multi-spectral imaging (MSI) platforms can be used to study properties of crop canopy, providing non-destructive phenotypes that could be used to better understand growth curves throughout the growing season. To investigate the amount of variation present in several VIs and their relationship with important end-of-season traits, genetic and residual (co)variances for VIs, grain yield and moisture were estimated using data collected from maize hybrid trials. The VIs considered were Normalized Difference Vegetation Index (NDVI), Green NDVI, Red Edge NDVI, Soil-Adjusted Vegetation Index, Enhanced Vegetation Index and simple Ratio of Near Infrared to Red (Red) reflectance. Genetic correlations of VIs with grain yield and moisture were used to fit multi-trait models for prediction of end-of-season traits and evaluated using within site/year cross-validation. To explore alternatives to fitting multiple phenotypes from MSI, random regression models with linear splines were fit using data collected in 2016 and 2017. Heritability estimates ranging from (0.10 to 0.82) were observed, indicating that there exists considerable amount of genetic variation in these VIs. Furthermore, strong genetic and residual correlations of the VIs, NDVI and NDRE, with grain yield and moisture were found. Considerable increases in prediction accuracy were observed from the multi-trait model when using NDVI and NDRE as a secondary trait. Finally, random regression with a linear spline function shows potential to be used as an alternative to mixed models to fit VIs from multiple time points.

Maize domestication: Facts and proofs

Maize (Zea mays L.; 2n = 20) is a member of the world’s most successful family of agricultural crops, including wheat, rice and sugarcane. Its versatile spread across the world has its nativity to Central America. The genus Zea includes wild taxa known as teosinte (Zea mays ssp. parviglumis) and domesticated corn or maize (Z. mays ssp. mays). Maize domestication is one of the greatest events of artificial selection and evolution, wherein a weedy plant in Central Mexico was converted through human-mediated selection into the most productive crop in the world. In fact, the changes were so notable between modern maize’s and true ancestor. From its primate form to modern cultivated maize, there were several facts and proofs to show cultivated maize were originated from teosinte about 9000 years ago. The major domestication events led to odds and ends in modern maize along with some beneficial traits useful for mankind. The present review briefly explains the domestication events and breeding aspects of maize and how selection influenced on differential traits in domesticated maize?

Appraisal of genetic variability for different quantitative traits in kharif maize (Zea mays L.) genotypes

The present study was conducted at AKS University, Satna (M.P.) during kharif 2019–20. Altogether 25 maize genotypes were grown under RBD design with three replications. In this study various parameters of genetic variability, broad sense heritability and genetic advance estimated in inbreed line of maize. Analysis of variance revealed that the mean sum of square showed significant due to genotypes for all the 17 characters studied. High GCV and PCV were recorded for seed yield per plant, seed yield per cob, cob ear weight and shelling %. Traits seed yield per plant, seed yield per cob, total seeds per cob, cob year weight and shelling % were showed high heritability accompanied with high genetic advance which indicated that most likely the heritability due to additive gene effects and selection may be effective in the early generation for these traits. Whereas high to moderate heritability along with low estimates of genetic advance which indicates that non additive gene effects. The genotypes which shows non additive gene effects will not be consider for further breeding programme.

Plant architectural responses in simultaneous maize/soybean strip intercropping do not lead to a yield advantage

AbstractMaize/soybean strip intercropping is a commonly used system throughout China with high crop yields at reduced nutrient input compared to sole maize. Maize is the taller crop, and due to its dominance in light capture over soybean in the intercrop, maize is expected to outperform maize in sole cropping. Conversely, soybean is the subordinate crop and intercropped soybean plants are expected to perform worse than sole soybean. Crop plants show plastic responses in plant architecture to their growing conditions to forage for light and avoid shading. There is little knowledge on plant architectural responses to growing conditions in simultaneous (non‐relay) intercropping and their relationship to species yields. A two‐year field experiment with two simultaneous maize/soybean intercropping systems with narrow and wide strips was conducted to characterise architectural traits of maize and soybean plants grown as intercrop and sole crops. Intercropped maize plants, especially those in border rows, had substantially greater leaf area, biomass and yield than maize plants in sole crops. Intercropped soybean plants, especially those in border rows, had lower leaf area, biomass and yield than sole soybean plants. Overall intercrop performance was similar to that of sole crops, with the land equivalent ratio (LER) being only slightly greater than one (1.03–1.08). Soybean displayed typical shade avoidance responses in the intercrop, such as greater internode elongation and changes in specific leaf area, but these responses could not overcome the consequences of the competition with the taller maize plants. Therefore, in contrast to relay intercrop systems, in the studied simultaneous maize/soybean system, plastic responses did not contribute to practically relevant increases in resource capture and yield at whole system (i.e., intercrop) level.

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

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.

Genomic prediction of maize microphenotypes provides insights for optimizing selection and mining diversity.

SummaryEffective evaluation of millions of crop genetic stocks is an essential component of exploiting genetic diversity to achieve global food security. By leveraging genomics and data analytics, genomic prediction is a promising strategy to efficiently explore the potential of these gene banks by starting with phenotyping a small designed subset. Reliable genomic predictions have enhanced selection of many macroscopic phenotypes in plants and animals. However, the use of genomicprediction strategies for analysis of microscopic phenotypes is limited. Here, we exploited the power of genomic prediction for eight maize traits related to the shoot apical meristem (SAM), the microscopic stem cell niche that generates all the above‐ground organs of the plant. With 435 713 genomewide single‐nucleotide polymorphisms (SNPs), we predicted SAM morphology traits for 2687 diverse maize inbreds based on a model trained from 369 inbreds. An empirical validation experiment with 488 inbreds obtained a prediction accuracy of 0.37–0.57 across eight traits. In addition, we show that a significantly higher prediction accuracy was achieved by leveraging the U value (upper bound for reliability) that quantifies the genomic relationships of the validation set with the training set. Our findings suggest that double selection considering both prediction and reliability can be implemented in choosing selection candidates for phenotyping when exploring new diversity is desired. In this case, individuals with less extreme predicted values and moderate reliability values can be considered. Our study expands the turbocharging gene banks via genomic prediction from the macrophenotypes into the microphenotypic space.

Identification, association, and expression analysis of ZmNAC134 gene response to phosphorus deficiency tolerance traits in maize at seedling stage

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.

Investigation of combining ability and superiority percentages for yield and some related traits in yellow maize using line × tester analysis

Combining ability estimation is an important genetic attribute for maize breeders in anticipating improvement in productivity via hybridization and selection. This research was carried out to investigate the genetic structure of the 27 F1 maize hybrids established from nine lines derived from Maize Research Department and three testers, to determine general combining ability (GCA), determine crosses showing specific combining ability (SCA) and superiority percentages for crosses. Nine lines, three testers, 27 F1 hybrids and two check commercial hybrids (SC162 and SC168) were studied in randomized complete block Design (RCBD) with three replications during 2016. The results of mean squares showed that significant and highly significant for most studied traits (days to 50% tasseling, days to 50% silking, plant and ear height, ear position, ear length, no. of kernels per row, 100-kernel weight and Grain yield). Estimates of variance due to GCA and SCA and their ratio revealed predominantly non-additive gene effects for all studied traits. Lines with the best GCA effects were: P2 (line 11) and P6 (line 21) for grain yield, for testers Gm174 and Gm1021 had significant GCA effects for grain yield. The hybrids P5×Gm1021, P6×Gm1021, P7×Gm1021, P8×Gm1002, P9×Gm1002 had significant and negative SCA effects for grain yield. Crosses P1×Gm174, P2×Gm1002, P5×Gm1021, P6×Gm174, P6×Gm1021, P7×Gm1021, P8×Gm1002, P9×Gm1021 were the best combinations manifested and significant superiority percentages over than check varieties (SC162 and SC168) for most studied traits. Therefore, these hybrids may be preferred for hybrid crop development.&#x0D; Abbreviations: GCA general combining ability; SCA specific combining ability

Denser Markers and Advanced Statistical Method Identified More Genetic Loci Associated with Husk Traits in Maize

The husk—the leaf-like outer covering of maize ear—has multiple functions, including protecting the ear from diseases infection and dehydration. In previous studies, we genotyped an association panel of 508 inbred lines genotyped with a total of ~550,000 SNPs (Illumina 50 K SNP Chip and RNA-seq). Genome-Wide Association Studies (GWAS) were conducted on four husk traits: husk length (HL), husk layer number (HN), husk thickness (HT), and husk width (HW). Minimal associations were identified and none of them passed the P-value threshold after a Bonferroni multiple-test correction using a single locus test in framework of mixed linear model. In this study, we doubled the number of SNPs (~1,250,000 in total) by adding GBS and 600 K SNP Chip. GWAS, performed with the recently developed multiple loci model (BLINK), revealed six genetic loci associated with HN and HT above the Bonferroni multiple-test threshold. Five candidate genes were identified based on the linkage disequilibrium with these loci, including GRMZM2G381691 and GRMZM2G012416. These two genes were up-regulation and down-regulation in all husk related tissues, respectively. GRMZM2G381691 associated with HT encoded a CCT domain protein, which expressed higher in tropical than temperate maize. GRMZM2G012416 associated with HN encoded an Armadillo (ARM) repeat protein, which regulated GA signal pathway. These associated SNPs and candidate genes paved a path to understand the genetic architecture of husk in maize.

Dominance Effects and Functional Enrichments Improve Prediction of Agronomic Traits in Hybrid Maize.

Single-cross hybrids have been critical to the improvement of maize (Zea mays L.), but the characterization of their genetic architectures remains challenging. Previous studies of hybrid maize have shown the contribution of within-locus complementation effects (dominance) and their differential importance across functional classes of loci. However, they have generally considered panels of limited genetic diversity, and have shown little benefit from genomic prediction based on dominance or functional enrichments. This study investigates the relevance of dominance and functional classes of variants in genomic models for agronomic traits in diverse populations of hybrid maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the U.S. (1106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1640 hybrids). We investigated three agronomic traits: days to silking (DTS), plant height (PH), and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results suggest that dominance and gene annotations improve genomic prediction across diverse populations in hybrid maize.

Genome-Wide Association Study of Plant and Ear Height in Maize

Both plant height (PH) and ear height (EH) are key agronomic traits in maize that are associated with plant lodging resistance and population density. To explore the genetic basis for PH and EH in maize, we conducted a genome-wide association study (GWAS) based upon 1.49 × 106 single nucleotide polymorphisms (SNPs) identified following the sequencing of 80 backbone inbred maize lines in Jilin Province. By comparing genotypic data and these two traits of interest, we identified 27 total SNPs significantly associated with PH and EH (P < 0.000001). Of these SNPs, 12 were significantly associated with PH and were found on chromosomes 1, 3, 4, 6, 7, and 9, accounting for 25.8% of the phenotypic variability for this trait. The remaining 15 SNPs were significantly linked with EH and were located on chromosomes 1, 2, 4, 6, 7, 8, 9, and 10, accounting for 30% of the phenotypic variability for this trait. Within a mean linkage disequilibrium (LD) distance of 9.7 kb from these SNP loci, we identified 5 candidate genes associated with PH, with one of these candidate genes harboring a significant SNP. Similarly, we identified 12 candidate genes associated with EH, of which 3 harbored significant SNPs. We then isolated RNA from 8 different inbred maize lines from this GWAS study cohort and assessed the expression of these candidate genes of interest via quantitative real-time PCR (qRT-PCR). Through this analysis, we were able to verify that there were significant differences in the expression of these four SNP-harboring candidate genes in plants with a range of EH and PH phenotypes.

Genetic differentiation of Mutator insertion polymorphisms and association with agronomic traits in waxy and common maize.

As waxy maize is considered a key economic crop in Korea, an understanding of its genetic variation and differentiation is fundamental for the selective plant breeding. The maize genome is primarily composed of transposable elements, for which large and stable insertions generate variations that reflect selection during evolution. This study was to elucidate the genetic diversity based on the contribution of TEs and to investigate the effect of Mu transposition on the genetic divergence of waxy and common maize. We also performed an association analysis on these inbred lines to determine the Mu insertions associated with agronomic traits. In this study, we utilized a Mutator-based transposon display method to study the genetic diversity and population structure of 40 waxy and 40 common inbred lines of maize in the Gangwon Agricultural Research and Extension Services collection at the Maize Research Institute. We detected polymorphisms in 86.33% of 278 Mutator (Mu) anchored loci, reflecting the activity of the Mu element and its contribution to genetic variation. Common maize showed a substantial amount of genetic diversity, which was greater than that observed in waxy maize. Principal-coordinate and neighbor-joining cluster analyzes consistently supported the presence of two genetically distinct groups. However, the distribution of genetic variation within the populations was much higher than the genetic differentiation among the populations. To explore the contribution of the Mu element to phenotypic variation, we analyzed the associations with ten important agronomical traits. On the basis of the combined results from two models (QGLM and Q + KLM), we found significant associations between seven Mu loci and four different traits. These results will assist waxy maize breeders in choosing parental lines and be useful for marker-assisted selection.

Genome–Phenome Wide Association in Maize and Arabidopsis Identifies a Common Molecular and Evolutionary Signature

Linking natural genetic variation to trait variation can help determine the functional roles ofdifferent genes. Variations of one or several traits are often assessed separately. High-throughput phenotyping and data mining can capture dozens or hundreds of traits from the same individuals. Here, we test the association between markers within a gene and many traits simultaneously. This genome–phenome wide association study (GPWAS) is both a multi-marker and multi-trait test. Genes identified using GPWAS with 260 phenotypic traits in maize were enriched for genes independently linked to phenotypic variation. Traits associated with classical mutants were consistent with reported phenotypes for mutant alleles. Genes linked to phenomic variation in maize using GPWAS shared molecular, population genetic, and evolutionary features with classical mutants in maize. Genes linked to phenomic variation in Arabidopsis using GPWAS are significantly enriched in genes with known loss-of-function phenotypes. GPWAS may be an effective strategy to identify genes in which loss-of-function alleles produce mutant phenotypes. The shared signatures present in classical mutants and genes identified using GPWAS may be markers for genes with a role in specifying plant phenotypes generally or pleiotropy specifically.

A QTL atlas for grain yield and its component traits in maize (Zea mays)

AbstractGrain yield and its component traits are essential targets in maize breeding. These traits are genetically complex and controlled by a large number of quantitative trait loci (QTL). The aim of this study was to compile reported QTL and major genes for grain yield and its component traits in a QTL atlas, as a valuable resource for the maize community. To this end, 1,177 QTL related to maize yield were collected from 56 studies published between 1992 and 2018. These QTL were projected to genetic map “IBM2 2008 Neighbors”, which led to the identification of 135 meta‐QTL. Some genomic regions appear to be hotspots for yield‐related meta‐QTL, often affecting more than one of the investigated traits. Moreover, we catalogued 20 major maize loci associated with yield and identified 65 maize homologs of 21 rice yield‐related genes. Interestingly, we found that a significant proportion of them are located in meta‐QTL regions. Collectively, this study provides a reference for QTL fine‐mapping and gene cloning, as well as for molecular marker‐assisted breeding of yield‐related traits in maize.

RILs development and its characterization for MLB resistance and flowering in maize (Zea mays)

Maydis leaf blight (MLB) resistance and days to flowering are the important yield determining traits in maize. Breeding for MLB resistance and days to flowering can be accelerated by understanding their genetics and identifying genomic regions contributing for their expression. Two F2s population with 338 and 349 individuals along with their recombinants inbred lines (RILs) having 283 and 277 individuals were developed from F1 crosses HKIPC4P × CML269 and ESM113 × P72clXbrasil1117 for genetic studies of MLB resistance and flowering. The populations along with their parents were screened under artificially inoculated conditions at hot-spot sites during 2015–17. Race O inoculum was artificially inoculated in the leaf whorl of each plant at 4-6 leaf stage. The inoculation was repeated after 8-10 days of first inoculation to avoid any chance of disease escape. The partial dominance in F1s, normal distribution patterns in F2s and RILs for both the traits has indicated their polygenic nature. Correlation analysis found negative and significant association (P≤0.001) between disease scores and days to flowering across the populations. Total 250 simple sequence repeats (SSR) markers, uniformly selected from all linkage groups were used for parental polymorphism survey between parents of the populations contrasting for target traits. Of total 250 SSRs, 122 (48.8% polymorphism) were identified as polymorphic between either of the parents. Sufficient genetic variation was observed within and between different F2s and RILs mapping populations. The information on inheritance, parental polymorphism survey and genetic materials developed will be useful for fine mapping and systematic breeding of targeted traits in tropical maize germplasm.