Dataset Information

Mapping QTL conferring resistance in maize to gray leaf spot disease caused by Cercospora zeina.

ABSTRACT: BACKGROUND: Gray leaf spot (GLS) is a globally important foliar disease of maize. Cercospora zeina, one of the two fungal species that cause the disease, is prevalent in southern Africa, China, Brazil and the eastern corn belt of the USA. Identification of QTL for GLS resistance in subtropical germplasm is important to support breeding programmes in developing countries where C.?zeina limits production of this staple food crop. RESULTS: A maize RIL population (F7:S6) from a cross between CML444 and SC Malawi was field-tested under GLS disease pressure at five field sites over three seasons in KwaZulu-Natal, South Africa. Thirty QTL identified from eleven field trials (environments) were consolidated to seven QTL for GLS resistance based on their expression in at least two environments and location in the same core maize bins. Four GLS resistance alleles were derived from the more resistant parent CML444 (bin 1.10, 4.08, 9.04/9.05, 10.06/10.07), whereas the remainder were from SC Malawi (bin 6.06/6.07, 7.02/7.03, 9.06). QTLs in bin 4.08 and bin 6.06/6.07 were also detected as joint QTLs, each explained more than 11% of the phenotypic variation, and were identified in four and seven environments, respectively. Common markers were used to allocate GLS QTL from eleven previous studies to bins on the IBM2005 map, and GLS QTL "hotspots" were noted. Bin 4.08 and 7.02/7.03 GLS QTL from this study overlapped with hotspots, whereas the bin 6.06/6.07 and bin 9.06 QTLs appeared to be unique. QTL for flowering time (bin 1.07, 4.09) in this population did not correspond to QTL for GLS resistance. CONCLUSIONS: QTL mapping of a RIL population from the subtropical maize parents CML444 and SC Malawi identified seven QTL for resistance to gray leaf spot disease caused by C.?zeina. These QTL together with QTL from eleven studies were allocated to bins on the IBM2005 map to provide a basis for comparison. Hotspots of GLS QTL were identified on chromosomes one, two, four, five and seven, with QTL in the current study overlapping with two of these. Two QTL from this study did not overlap with previously reported QTL.

SUBMITTER: Berger DK

PROVIDER: S-EPMC4059882 | biostudies-other | 2014

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Mapping QTL conferring resistance in maize to gray leaf spot disease caused by Cercospora zeina.

Berger Dave K DK Carstens Maryke M Korsman Jeanne N JN Middleton Felix F Kloppers Frederik J FJ Tongoona Pangirayi P Myburg Alexander A AA

BMC genetics 20140522

<h4>Background</h4>Gray leaf spot (GLS) is a globally important foliar disease of maize. Cercospora zeina, one of the two fungal species that cause the disease, is prevalent in southern Africa, China, Brazil and the eastern corn belt of the USA. Identification of QTL for GLS resistance in subtropical germplasm is important to support breeding programmes in developing countries where C. zeina limits production of this staple food crop.<h4>Results</h4>A maize RIL population (F7:S6) from a cross be ...[more]

PMID: 24885661

Similar Datasets

Project description:Among the diseases threatening maize production in Africa are gray leaf spot (GLS) caused by Cercospora zeina and northern corn leaf blight (NCLB) caused by Exserohilum turcicum. The two pathogens, which have high genetic diversity, reduce the photosynthesizing ability of susceptible genotypes and, hence, reduce the grain yield. To identify population-based quantitative trait loci (QTLs) for GLS and NCLB resistance, a biparental population of 230 lines derived from the tropical maize parents CML511 and CML546 and an association mapping panel of 239 tropical and sub-tropical inbred lines were phenotyped across multi-environments in western Kenya. Based on 1,264 high-quality polymorphic single-nucleotide polymorphisms (SNPs) in the biparental population, we identified 10 and 18 QTLs, which explained 64.2% and 64.9% of the total phenotypic variance for GLS and NCLB resistance, respectively. A major QTL for GLS, qGLS1_186 accounted for 15.2% of the phenotypic variance, while qNCLB3_50 explained the most phenotypic variance at 8.8% for NCLB resistance. Association mapping with 230,743 markers revealed 11 and 16 SNPs significantly associated with GLS and NCLB resistance, respectively. Several of the SNPs detected in the association panel were co-localized with QTLs identified in the biparental population, suggesting some consistent genomic regions across genetic backgrounds. These would be more relevant to use in field breeding to improve resistance to both diseases. Genomic prediction models trained on the biparental population data yielded average prediction accuracies of 0.66-0.75 for the disease traits when validated in the same population. Applying these prediction models to the association panel produced accuracies of 0.49 and 0.75 for GLS and NCLB, respectively. This research conducted in maize fields relevant to farmers in western Kenya has combined linkage and association mapping to identify new QTLs and confirm previous QTLs for GLS and NCLB resistance. Overall, our findings imply that genetic gain can be improved in maize breeding for resistance to multiple diseases including GLS and NCLB by using genomic selection.

Project description:Gray leaf spot (GLS), caused by Cercospora zeae-maydis and Cercospora zeina, is one of the most important diseases of maize worldwide. The pathogen has a necrotrophic lifestyle and no major genes are known for GLS. Quantitative resistance, although poorly understood, is important for GLS management. We used genetic mapping to refine understanding of the genetic architecture of GLS resistance and to develop hypotheses regarding the mechanisms underlying quantitative disease resistance (QDR) loci. Nested association mapping (NAM) was used to identify 16 quantitative trait loci (QTL) for QDR to GLS, including seven novel QTL, each of which demonstrated allelic series with significant effects above and below the magnitude of the B73 reference allele. Alleles at three QTL, qGLS1.04, qGLS2.09, and qGLS4.05, conferred disease reductions of greater than 10%. Interactions between loci were detected for three pairs of loci, including an interaction between iqGLS4.05 and qGLS7.03. Near-isogenic lines (NILs) were developed to confirm and fine-map three of the 16 QTL, and to develop hypotheses regarding mechanisms of resistance. qGLS1.04 was fine-mapped from an interval of 27.0 Mb to two intervals of 6.5 Mb and 5.2 Mb, consistent with the hypothesis that multiple genes underlie highly significant QTL identified by NAM. qGLS2.09, which was also associated with maturity (days to anthesis) and with resistance to southern leaf blight, was narrowed to a 4-Mb interval. The distance between major leaf veins was strongly associated with resistance to GLS at qGLS4.05. NILs for qGLS1.04 were treated with the C. zeae-maydis toxin cercosporin to test the role of host-specific toxin in QDR. Cercosporin exposure increased expression of a putative flavin-monooxygenase (FMO) gene, a candidate detoxification-related gene underlying qGLS1.04. This integrated approach to confirming QTL and characterizing the potential underlying mechanisms advances the understanding of QDR and will facilitate the development of resistant varieties.

Project description: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.

Dataset Information

Mapping QTL conferring resistance in maize to gray leaf spot disease caused by Cercospora zeina.

Publications

Mapping QTL conferring resistance in maize to gray leaf spot disease caused by Cercospora zeina.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets