Genomic-regions associated with cold stress tolerance in Asia-adapted tropical maize germplasm.

Maize is gaining impetus in non-traditional and non-conventional seasons such as off-season, primarily due to higher demand and economic returns. Maize varieties directed for growing in the winter season of South Asia must have cold resilience as an important trait due to the low prevailing temperatures and frequent cold snaps observed during this season in most parts of the lowland tropics of Asia. The current study involved screening of a panel of advanced tropically adapted maize lines to cold stress during vegetative and flowering stage under field conditions. A suite of significant genomic loci (28) associated with grain yield along and agronomic traits such as flowering (15) and plant height (6) under cold stress environments. The haplotype regression revealed 6 significant haplotype blocks for grain yield under cold stress across the test environments. Haplotype blocks particularly on chromosomes 5 (bin5.07), 6 (bin6.02), and 9 (9.03) co-located to regions/bins that have been identified to contain candidate genes involved in membrane transport system that would provide essential tolerance to the plant. The regions on chromosome 1 (bin1.04), 2 (bin 2.07), 3 (bin 3.05-3.06), 5 (bin5.03), 8 (bin8.05-8.06) also harboured significant SNPs for the other agronomic traits. In addition, the study also looked at the plausibility of identifying tropically adapted maize lines from the working germplasm with cold resilience across growth stages and identified four lines that could be used as breeding starts in the tropical maize breeding pipelines.

Low-Density Reference Fingerprinting SNP Dataset of CIMMYT Maize Lines for Quality Control and Genetic Diversity Analyses.

CIMMYT maize lines (CMLs), which represent the tropical maize germplasm, are freely available worldwide. All currently released 615 CMLs and fourteen temperate maize inbred lines were genotyped with 180 kompetitive allele-specific PCR single nucleotide polymorphisms to develop a reference fingerprinting SNP dataset that can be used to perform quality control (QC) and genetic diversity analyses. The QC analysis identified 25 CMLs with purity, identity, or mislabeling issues. Further field observation, purification, and re-genotyping of these CMLs are required. The reference fingerprinting SNP dataset was developed for all of the currently released CMLs with 152 high-quality SNPs. The results of principal component analysis and average genetic distances between subgroups showed a clear genetic divergence between temperate and tropical maize, whereas the three tropical subgroups partially overlapped with one another. More than 99% of the pairs of CMLs had genetic distances greater than 0.30, showing their high genetic diversity, and most CMLs are distantly related. The heterotic patterns, estimated with the molecular markers, are consistent with those estimated using pedigree information in two major maize breeding programs at CIMMYT. These research findings are helpful for ensuring the regeneration and distribution of the true CMLs, via QC analysis, and for facilitating the effective utilization of the CMLs, globally.

Identification and validation of a key genomic region on chromosome 6 for resistance to Fusarium stalk rot in tropical maize.

KEY MESSAGE: A key genomic region was identified for resistance to FSR at 168 Mb on chromosome 6 in GWAS and haplotype regression analysis, which was validated by QTL mapping in two populations. Fusarium stalk rot (FSR) of maize is an economically important post-flowering stalk rot (PFSR) disease caused by Fusarium verticillioides. The pathogen invades the plant individually, or in combination with other stalk rot pathogens or secondary colonizers, thereby making it difficult to make accurate selection for resistance. For identification and validation of genomic regions associated with FSR resistance, a genome-wide association study (GWAS) was conducted with 342 maize lines. The panel was screened for FSR in three environments using standard artificial inoculation methodology. GWAS using the mixed linear model corrected for population structure and kinship was done, in which 290,626 SNPs from genotyping-by-sequencing were used. A total of 7 SNPs, five on chromosome 6 showing strong LD at 168 Mb, were identified to be associated with FSR. Haplotype regression analysis identified 32 haplotypes with a significant effect on the trait. In a QTL mapping experiment in two populations for validating the identified variants, QTLs were identified with confidence intervals having overlapped physical coordinates in both the populations on chromosome 6, which was closely located to the GWAS-identified variants on chromosome 6. It makes this genomic region a crucial one to further investigate the possibility of developing trait markers for deployment in breeding pipelines. It was noted that previously reported QTLs for other stalk rots in maize mapped within the same physical intervals of several haplotypes identified for FSR resistance in this study. The possibility of QTLs controlling broad-spectrum resistance for PFSR in general requires further investigation.

GBS-Based SNP Map Pinpoints the QTL Associated With Sorghum Downy Mildew Resistance in Maize (Zea mays L.).

Sorghum downy mildew (SDM), caused by the biotrophic fungi Peronosclerospora sorghi , threatens maize production worldwide, including India. To identify quantitative trait loci (QTL) associated with resistance to SDM, we used a recombinant inbred line (RIL) population derived from a cross between resistant inbred line UMI936 (w) and susceptible inbred line UMI79. The RIL population was phenotyped for SDM resistance in three environments [E1-field (Coimbatore), E2-greenhouse (Coimbatore), and E3-field (Mandya)] and also utilized to construct the genetic linkage map by genotyping by sequencing (GBS) approach. The map comprises 1516 SNP markers in 10 linkage groups (LGs) with a total length of 6924.7 cM and an average marker distance of 4.57 cM. The QTL analysis with the phenotype and marker data detected nine QTL on chromosome 1, 2, 3, 5, 6, and 7 across three environments. Of these, QTL namely qDMR1.2, qDMR3.1, qDMR5.1, and qDMR6.1 were notable due to their high phenotypic variance. qDMR3.1 from chromosome 3 was detected in more than one environment (E1 and E2), explaining the 10.3% and 13.1% phenotypic variance. Three QTL, qDMR1.2, qDMR5.1, and qDMR6.1 from chromosomes 1, 5, and 6 were identified in either E1 or E3, explaining 15.2%-18% phenotypic variance. Moreover, genome mining on three QTL (qDMR3.1, qDMR5.1, and qDMR6.1) reveals the putative candidate genes related to SDM resistance. The information generated in this study will be helpful for map-based cloning and marker-assisted selection in maize breeding programs.

Identification and Validation of Genomic Regions Associated With Charcoal Rot Resistance in Tropical Maize by Genome-Wide Association and Linkage Mapping.

Charcoal rot is a post-flowering stalk rot (PFSR) disease of maize caused by the fungal pathogen, Macrophomina phaseolina. It is a serious concern for smallholder maize cultivation, due to significant yield loss and plant lodging at harvest, and this disease is expected to surge with climate change effects like drought and high soil temperature. For identification and validation of genomic variants associated with charcoal rot resistance, a genome-wide association study (GWAS) was conducted on CIMMYT Asia association mapping panel comprising 396 tropical-adapted lines, especially to Asian environments. The panel was phenotyped for disease severity across two locations with high disease prevalence in India. A subset of 296,497 high-quality SNPs filtered from genotyping by sequencing was correcting for population structure and kinship matrices for single locus mixed linear model (MLM) of GWAS analysis. A total of 19 SNPs were identified to be associated with charcoal rot resistance with P-value ranging from 5.88 × 10-06 to 4.80 × 10-05. Haplotype regression analysis identified 21 significant haplotypes for the trait with Bonferroni corrected P ≤ 0.05. For validating the associated variants and identifying novel QTLs, QTL mapping was conducted using two F2:3 populations. Two QTLs with overlapping physical intervals, qMSR6 and qFMSR6 on chromosome 6, identified from two different mapping populations and contributed by two different resistant parents, were co-located with the SNPs and haplotypes identified at 103.51 Mb on chromosome 6. Similarly, several SNPs/haplotypes identified on chromosomes 3, 6 and 8 were also found to be physically co-located within QTL intervals detected in one of the two mapping populations. The study also noted that several SNPs/haplotypes for resistance to charcoal rot were located within physical intervals of previously reported QTLs for Gibberella stalk rot resistance, which opens up a new possibility for common disease resistance mechanisms for multiple stalk rots.

Genomic regions associated with heat stress tolerance in tropical maize (Zea mays L.).

With progressive climate change and the associated increase in mean temperature, heat stress tolerance has emerged as one of the key traits in the product profile of the maize breeding pipeline for lowland tropics. The present study aims to identify the genomic regions associated with heat stress tolerance in tropical maize. An association mapping panel, called the heat tolerant association mapping (HTAM) panel, was constituted by involving a total of 543 tropical maize inbred lines from diverse genetic backgrounds, test-crossed and phenotyped across nine locations in South Asia under natural heat stress. The panel was genotyped using a genotyping-by-sequencing (GBS) platform. Considering the large variations in vapor pressure deficit (VPD) at high temperature (Tmax) across different phenotyping locations, genome-wide association study (GWAS) was conducted separately for each location. The individual location GWAS identified a total of 269 novel significant single nucleotide polymorphisms (SNPs) for grain yield under heat stress at a p value of < 10-5. A total of 175 SNPs were found in 140 unique gene models implicated in various biological pathway responses to different abiotic stresses. Haplotype trend regression (HTR) analysis of the significant SNPs identified 26 haplotype blocks and 96 single SNP variants significant across one to five locations. The genomic regions identified based on GWAS and HTR analysis considering genomic region x environment interactions are useful for breeding efforts aimed at developing heat stress resilient maize cultivars for current and future climatic conditions through marker-assisted introgression into elite genetic backgrounds and/or genome-wide selection.

Genome wide association mapping for heat tolerance in sub-tropical maize.

BACKGROUND: Heat tolerance is becoming increasingly important where maize is grown under spring season in India which coincide with grain filling stage of crop resulting in tassel blast, reduced pollen viability, pollination failure and barren ears that causes devastating yield losses. So, there is need to identify the genomic regions associated with heat tolerance component traits which could be further employed in maize breeding program. RESULTS: An association mapping panel, consisting of 662 doubled haploid (DH) lines, was evaluated for yield contributing traits under normal and natural heat stress conditions. Genome wide association studies (GWAS) carried out using 187,000 SNPs and 130 SNPs significantly associated for grain yield (GY), days to 50% anthesis (AD), days to 50% silking (SD), anthesis-silking interval (ASI), plant height (PH), ear height (EH) and ear position (EPO) were identified under normal conditions. A total of 46 SNPs strongly associated with GY, ASI, EH and EPO were detected under heat stress conditions. Fifteen of the SNPs was found to have common association with more than one trait such as two SNPs viz. S10_1,905,273 and S10_1,905,274 showed colocalization with GY, PH and EH whereas S10_7,132,845 SNP associated with GY, AD and SD under normal conditions. No such colocalization of SNP markers with multiple traits was observed under heat stress conditions. Haplotypes trend regression analysis revealed 122 and 85 haplotype blocks, out of which, 20 and 6 haplotype blocks were associated with more than one trait under normal and heat stress conditions, respectively. Based on SNP association and haplotype mapping, nine and seven candidate genes were identified respectively, which belongs to different gene models having different biological functions in stress biology. CONCLUSIONS: The present study identified significant SNPs and haplotype blocks associated with yield contributing traits that help in selection of donor lines with favorable alleles for multiple traits. These results provided insights of genetics of heat stress tolerance. The genomic regions detected in the present study need further validation before being applied in the breeding pipelines.

Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments.

KEY MESSAGE: Intensive public sector breeding efforts and public-private partnerships have led to the increase in genetic gains, and deployment of elite climate-resilient maize cultivars for the stress-prone environments in the tropics. Maize (Zea mays L.) plays a critical role in ensuring food and nutritional security, and livelihoods of millions of resource-constrained smallholders. However, maize yields in the tropical rainfed environments are now increasingly vulnerable to various climate-induced stresses, especially drought, heat, waterlogging, salinity, cold, diseases, and insect pests, which often come in combinations to severely impact maize crops. The International Maize and Wheat Improvement Center (CIMMYT), in partnership with several public and private sector institutions, has been intensively engaged over the last four decades in breeding elite tropical maize germplasm with tolerance to key abiotic and biotic stresses, using an extensive managed stress screening network and on-farm testing system. This has led to the successful development and deployment of an array of elite stress-tolerant maize cultivars across sub-Saharan Africa, Asia, and Latin America. Further increasing genetic gains in the tropical maize breeding programs demands judicious integration of doubled haploidy, high-throughput and precise phenotyping, genomics-assisted breeding, breeding data management, and more effective decision support tools. Multi-institutional efforts, especially public-private alliances, are key to ensure that the improved maize varieties effectively reach the climate-vulnerable farming communities in the tropics, including accelerated replacement of old/obsolete varieties.

Genome wide association study and genomic prediction for stover quality traits in tropical maize (Zea mays L.).

Maize is rapidly replacing traditionally cultivated dual purpose crops of South Asia, primarily due to the better economic remuneration. This has created an impetus for improving maize for both grain productivity and stover traits. Molecular techniques can largely assist breeders in determining approaches for effectively integrating stover trait improvement in their existing breeding pipeline. In the current study we identified a suite of potential genomic regions associated to the two major stover quality traits-in-vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) through genome wide association study. However, considering the fact that the loci identified for these complex traits all had smaller effects and accounted only a small portion of phenotypic variation, the effectiveness of following a genomic selection approach for these traits was evaluated. The testing set consists of breeding lines recently developed within the program and the training set consists of a panel of lines from the working germplasm comprising the founder lines of the newly developed breeding lines and also an unrelated diversity set. The prediction accuracy as determined by the Pearson's correlation coefficient between observed and predicted values of these breeding lines were high even at lower marker density (200 random SNPs), when the training and testing set were related. However, the accuracies were dismal, when there was no relationship between the training and the testing set.

Genome-wide association studies in tropical maize germplasm reveal novel and known genomic regions for resistance to Northern corn leaf blight.

Northern Corn Leaf Blight (NCLB) caused by Setosphaeria turcica, is one of the most important diseases of maize world-wide, and one of the major reasons behind yield losses in maize crop in Asia. In the present investigation, a high-resolution genome wide association study (GWAS) was conducted for NCLB resistance in three association mapping panels, predominantly consisting of tropical lines adapted to different agro-ecologies. These panels were phenotyped for disease severity across three locations with high disease prevalence in India. High density SNPs from Genotyping-by-sequencing were used in GWAS, after controlling for population structure and kinship matrices, based on single locus mixed linear model (MLM). Twenty-two SNPs were identified, that revealed a significant association with NCLB in the three mapping panels. Haplotype regression analysis revealed association of 17 significant haplotypes at FDR ≤ 0.05, with two common haplotypes across three maize panels. Several of the significantly associated SNPs/haplotypes were found to be co-located in chromosomal bins previously reported for major genes like Ht2, Ht3 and Htn1 and QTL for NCLB resistance and multiple foliar disease resistance. Phenotypic variance explained by these significant SNPs/haplotypes ranged from low to moderate, suggesting a breeding strategy of combining multiple resistance alleles towards resistance for NCLB.

Genetic Dissection of Resistance to Gray Leaf Spot by Combining Genome-Wide Association, Linkage Mapping, and Genomic Prediction in Tropical Maize Germplasm.

Gray leaf spot (GLS) is one of the major maize foliar diseases in sub-Saharan Africa. Resistance to GLS is controlled by multiple genes with additive effect and is influenced by both genotype and environment. The objectives of the study were to dissect the genetic architecture of GLS resistance through linkage mapping and genome-wide association study (GWAS) and assessing the potential of genomic prediction (GP). We used both biparental populations and an association mapping panel of 410 diverse tropical/subtropical inbred lines that were genotyped using genotype by sequencing. Phenotypic evaluation in two to four environments revealed significant genotypic variation and moderate to high heritability estimates ranging from 0.43 to 0.69. GLS was negatively and significantly correlated with grain yield, anthesis date, and plant height. Linkage mapping in five populations revealed 22 quantitative trait loci (QTLs) for GLS resistance. A QTL on chromosome 7 (qGLS7-105) is a major-effect QTL that explained 28.2% of phenotypic variance. Together, all the detected QTLs explained 10.50, 49.70, 23.67, 18.05, and 28.71% of phenotypic variance in doubled haploid (DH) populations 1, 2, 3, and F3 populations 4 and 5, respectively. Joint linkage association mapping across three DH populations detected 14 QTLs that individually explained 0.10-15.7% of phenotypic variance. GWAS revealed 10 significantly (p < 9.5 × 10-6) associated SNPs distributed on chromosomes 1, 2, 6, 7, and 8, which individually explained 6-8% of phenotypic variance. A set of nine candidate genes co-located or in physical proximity to the significant SNPs with roles in plant defense against pathogens were identified. GP revealed low to moderate prediction correlations of 0.39, 0.37, 0.56, 0.30, 0.29, and 0.38 for within IMAS association panel, DH pop1, DH pop2, DH pop3, F3 pop4, and F3 po5, respectively, and accuracy was increased substantially to 0.84 for prediction across three DH populations. When the diversity panel was used as training set to predict the accuracy of GLS resistance in biparental population, there was 20-50% reduction compared to prediction within populations. Overall, the study revealed that resistance to GLS is quantitative in nature and is controlled by many loci with a few major and many minor effects. The SNPs/QTLs identified by GWAS and linkage mapping can be potential targets in improving GLS resistance in breeding programs, while GP further consolidates the development of high GLS-resistant lines by incorporating most of the major- and minor-effect genes.

Applications of genotyping-by-sequencing (GBS) in maize genetics and breeding.

Genotyping-by-Sequencing (GBS) is a low-cost, high-throughput genotyping method that relies on restriction enzymes to reduce genome complexity. GBS is being widely used for various genetic and breeding applications. In the present study, 2240 individuals from eight maize populations, including two association populations (AM), backcross first generation (BC1), BC1F2, F2, double haploid (DH), intermated B73 × Mo17 (IBM), and a recombinant inbred line (RIL) population, were genotyped using GBS. A total of 955,120 of raw data for SNPs was obtained for each individual, with an average genotyping error of 0.70%. The rate of missing genotypic data for these SNPs was related to the level of multiplex sequencing: ~ 25% missing data for 96-plex and ~ 55% for 384-plex. Imputation can greatly reduce the rate of missing genotypes to 12.65% and 3.72% for AM populations and bi-parental populations, respectively, although it increases total genotyping error. For analysis of genetic diversity and linkage mapping, unimputed data with a low rate of genotyping error is beneficial, whereas, for association mapping, imputed data would result in higher marker density and would improve map resolution. Because imputation does not influence the prediction accuracy, both unimputed and imputed data can be used for genomic prediction. In summary, GBS is a versatile and efficient SNP discovery approach for homozygous materials and can be effectively applied for various purposes in maize genetics and breeding.

Combination of Linkage Mapping, GWAS, and GP to Dissect the Genetic Basis of Common Rust Resistance in Tropical Maize Germplasm.

Common rust (CR) caused by Puccina sorghi is one of the destructive fungal foliar diseases of maize and has been reported to cause moderate to high yield losses. Providing CR resistant germplasm has the potential to increase yields. To dissect the genetic architecture of CR resistance in maize, association mapping, in conjunction with linkage mapping, joint linkage association mapping (JLAM), and genomic prediction (GP) was conducted on an association-mapping panel and five F3 biparental populations using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). Analysis of variance for the biparental populations and the association panel showed significant genotypic and genotype x environment (GXE) interaction variances except for GXE of Pop4. Heritability (h2) estimates were moderate with 0.37-0.45 for the individual F3 populations, 0.45 across five populations and 0.65 for the association panel. Genome-wide association study (GWAS) analyses revealed 14 significant marker-trait associations which individually explained 6-10% of the total phenotypic variances. Individual population-based linkage analysis revealed 26 QTLs associated with CR resistance and together explained 14-40% of the total phenotypic variances. Linkage mapping revealed seven QTLs in pop1, nine QTL in pop2, four QTL in pop3, five QTL in pop4, and one QTL in pop5, distributed on all chromosomes except chromosome 10. JLAM for the 921 F3 families from five populations detected 18 QTLs distributed in all chromosomes except on chromosome 8. These QTLs individually explained 0.3 to 3.1% and together explained 45% of the total phenotypic variance. Among the 18 QTL detected through JLAM, six QTLs, qCR1-78, qCR1-227, qCR3-172, qCR3-186, qCR4-171, and qCR7-137 were also detected in linkage mapping. GP within population revealed low to moderate correlations with a range from 0.19 to 0.51. Prediction correlation was high with r = 0.78 for combined analysis of the five F3 populations. Prediction of biparental populations by using association panel as training set reveals positive correlations ranging from 0.05 to 0.22, which encourages to develop an independent but related population as a training set which can be used to predict diverse but related populations. The findings of this study provide valuable information on understanding the genetic basis of CR resistance and the obtained information can be used for developing functional molecular markers for marker-assisted selection and for implementing GP to improve CR resistance in tropical maize.

Genome-wide association study to identify genomic regions influencing spontaneous fertility in maize haploids.

Efficient production and use of doubled haploid lines can greatly accelerate genetic gains in maize breeding programs. One of the critical steps in standard doubled haploid line production is doubling the haploid genome using toxic and costly mitosis-inhibiting chemicals to achieve fertility in haploids. Alternatively, fertility may be spontaneously restored by natural chromosomal doubling, although generally at a rate too low for practical applications in most germplasm. This is the first large-scale genome-wise association study to analyze spontaneous chromosome doubling in haploids derived from tropical maize inbred lines. Induction crosses between tropicalized haploid inducers and 400 inbred lines were made, and the resulting haploid plants were assessed for haploid male fertility which refers to pollen production and haploid fertility which refers to seed production upon self-fertilization. A small number of genotypes were highly fertile and these fertility traits were highly heritable. Agronomic traits like plant height, ear height and tassel branch number were positively correlated with fertility traits. In contrast, haploid induction rate of the source germplasm and plant aspect were not correlated to fertility traits. Several genomic regions and candidate genes were identified that may control spontaneous fertility restoration. Overall, the study revealed the presence of large variation for both haploid male fertility and haploid fertility which can be potentially exploited for improving the efficiency of doubled haploid derivation in tropical maize germplasm.

Molecular Breeding for Nutritionally Enriched Maize: Status and Prospects.

Maize is a major source of food security and economic development in sub-Saharan Africa (SSA), Latin America, and the Caribbean, and is among the top three cereal crops in Asia. Yet, maize is deficient in certain essential amino acids, vitamins, and minerals. Biofortified maize cultivars enriched with essential minerals and vitamins could be particularly impactful in rural areas with limited access to diversified diet, dietary supplements, and fortified foods. Significant progress has been made in developing, testing, and deploying maize cultivars biofortified with quality protein maize (QPM), provitamin A, and kernel zinc. In this review, we outline the status and prospects of developing nutritionally enriched maize by successfully harnessing conventional and molecular marker-assisted breeding, highlighting the need for intensification of efforts to create greater impacts on malnutrition in maize-consuming populations, especially in the low- and middle-income countries. Molecular marker-assisted selection methods are particularly useful for improving nutritional traits since conventional breeding methods are relatively constrained by the cost and throughput of nutritional trait phenotyping.

Marker-Assisted Breeding of Improved Maternal Haploid Inducers in Maize for the Tropical/Subtropical Regions.

For efficient production of doubled haploid (DH) lines in maize, maternal haploid inducer lines with high haploid induction rate (HIR) and good adaptation to the target environments is an important requirement. In this study, we present second-generation Tropically Adapted Inducer Lines (2GTAILs), developed using marker assisted selection (MAS) for qhir1, a QTL with a significant positive effect on HIR from the crosses between elite tropical maize inbreds and first generation Tropically Adapted Inducers Lines (TAILs). Evaluation of 2GTAILs for HIR and agronomic performance in the tropical and subtropical environments indicated superior performance of 2GTAILs over the TAILs for both HIR and agronomic performance, including plant vigor, delayed flowering, grain yield, and resistance to ear rots. One of the new inducers 2GTAIL006 showed an average HIR of 13.1% which is 48.9% higher than the average HIR of the TAILs. Several other 2GTAILs also showed higher HIR compared to the TAILs. While employing MAS for qhir1 QTL, we observed significant influence of the non-inducer parent on the positive effect of qhir1 QTL on HIR. The non-inducer parents that resulted in highest mean HIR in the early generation qhir1+ families also gave rise to highest numbers of candidate inducers, some of which showed transgressive segregation for HIR. The mean HIR of early generation qhir1+ families involving different non-inducer parents can potentially indicate recipient non-inducer parents that can result in progenies with high HIR. Our study also indicated that the HIR associated traits (endosperm abortion rate, embryo abortion rate, and proportion of haploid plants among the inducer plants) can be used to differentiate inducers vs. non-inducers but are not suitable for differentiating inducers with varying levels of haploid induction rates. We propose here an efficient methodology for developing haploid inducer lines combining MAS for qhir1 with HIR associated traits.

Identification and validation of genomic regions influencing kernel zinc and iron in maize.

KEY MESSAGE: Genome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize. Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world's poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (P ≤ 5.03 × 10-05) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (P ≤ 1 × 10-03) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (P ≤ 0.01, R2 ≥ 0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.

Genome-wide association study in Asia-adapted tropical maize reveals novel and explored genomic regions for sorghum downy mildew resistance.

Globally, downy mildews are among the important foliar diseases of maize that cause significant yield losses. We conducted a genome-wide association study for sorghum downy mildew (SDM; Peronosclerospora sorghi) resistance in a panel of 368 inbred lines adapted to the Asian tropics. High density SNPs from Genotyping-by-sequencing were used in GWAS after controlling for population structure and kinship in the panel using a single locus mixed model. The study identified a set of 26 SNPs that were significantly associated with SDM resistance, with Bonferroni corrected P values ≤ 0.05. Among all the identified SNPs, the minor alleles were found to be favorable to SDM resistance in the mapping panel. Trend regression analysis with 16 independent genetic variants including 12 SNPs and four haplotype blocks identified SNP S2_6154311 on chromosome 2 with P value 2.61E-24 and contributing 26.7% of the phenotypic variation. Six of the SNPs/haplotypes were within the same chromosomal bins as the QTLs for SDM resistance mapped in previous studies. Apart from this, eight novel genomic regions for SDM resistance were identified in this study; they need further validation before being applied in the breeding pipeline. Ten SNPs identified in this study were co-located in reported mildew resistance genes.

Dissection of a major QTL qhir1 conferring maternal haploid induction ability in maize.

KEY MESSAGE: Among the qhir11 and qhir12 sub-regions of a major QTL qhir1, only qhir11 has significant effect on maternal haploid induction, segregation distortion and kernel abortion. In vivo haploid induction in maize can be triggered in high frequencies by pollination with special genetic stocks called haploid inducers. Several genetic studies with segregating populations from non-inducer x inducer crosses identified a major QTL, qhir1, on chromosome 1.04 contributing to in vivo haploid induction. A recent Genome Wide Association Study using 51 inducers and 1482 non-inducers also identified two sub-regions within the qhir1 QTL region, named qhir11 and qhir12; qhir12 was proposed to be mandatory for haploid induction because the haplotype of qhir11 was also present in some non-inducers and putative candidate genes coding for DNA and amino acid binding proteins were identified in the qhir12 region. To characterize the effects of each sub-region of qhir1 on haploid induction rate, F2 recombinants segregating for one of the sub-regions and fixed for the other were identified in a cross between CML269 (non-inducer) and a tropicalized haploid inducer TAIL8. To quantify the haploid induction effects of qhir11 and qhir12, selfed progenies of recombinants between these sub-regions were genotyped. F3 plants homozygous for qhir11 and/or qhir12 were identified, and crossed to a ligueless tester to determine their haploid induction rates. The study revealed that only the qhir11 sub-region has a significant effect on haploid induction ability, besides causing significant segregation distortion and kernel abortion, traits that are strongly associated with maternal haploid induction. The results presented in this study can guide fine mapping efforts of qhir1 and in developing new inducers efficiently using marker assisted selection.

The Genetic Basis of Haploid Induction in Maize Identified with a Novel Genome-Wide Association Method.

In vivo haploid induction (HI) triggered by pollination with special intraspecific genotypes, called inducers, is unique to Zea maysL. within the plant kingdom and has revolutionized maize breeding during the last decade. However, the molecular mechanisms underlying HI in maize are still unclear. To investigate the genetic basis of HI, we developed a new approach for genome-wide association studies (GWAS), termed conditional haplotype extension (CHE) test that allows detection of selective sweeps even under almost perfect confounding of population structure and trait expression. Here, we applied this test to identify genomic regions required for HI expression and dissected the combined support interval (50.34 Mb) of the QTL qhir1, detected in a previous study, into two closely linked genomic segments relevant for HI expression. The first, termed qhir11(0.54 Mb), comprises an already fine-mapped region but was not diagnostic for differentiating inducers and noninducers. The second segment, termed qhir12(3.97 Mb), had a haplotype allele common to all 53 inducer lines but not found in any of the 1482 noninducers. By comparing resequencing data of one inducer with 14 noninducers, we detected in the qhir12 region three candidate genes involved in DNA or amino acid binding, however, none for qhir11 We propose that the CHE test can be utilized in introgression breeding and different fields of genetics to detect selective sweeps in heterogeneous genetic backgrounds.