Exploring The Genetic Basis Of Northern Leaf Blight Via Genome Wide Association Mapping In Maize

Gigantic efforts are required from the scientific community to find out genuine sources of resistance and overcome the most abstruse phenomenon of disease resistance. Maize being the third largest staple in the world is affected by more than100pathogens. With the advent of molecular markers especially the single nucleotide polymorphism (SNP), the process of full genome screening has become easier and the scientists are trying to unleash the hidden truth of disease resistance. We performed meta-analysis for northern leaf blight (NLB), southern leaf blight (SLB), and gray leaf spot (GLS), with the aim to find out the total number of QTL and depict some real QTL for molecular breeding and marker assisted selection (MAS). Our analysis revealed that disease resistance QTL was randomly distributed in maize genome.63QTL were controlling more than one disease revealing the presence of multiple disease resistance (MDR).44real-QTL were observed based on4QTL as a standard in specific region of genome during this analysis. Minimum confidence interval (CI) was observed for a QTL on chromosome three, while on chromosome8two nucleotide binding site (NBS) genes in one QTL were observed. We also confirmed the Htl and Ht2genes within the region of real QTL. On chromosome3, we observed several cluster and maximum MDR QTL indicating that the apparent clustering could be due to genes exhibiting pleiotropic effect. The biggest cluster was found on chromosome5and significant relationship was observed between the number of disease QTL and total genes per chromosome based on the reference genome B73. Therefore, we concluded that disease resistance genes are abundant in maize genome and these results can unleash the phenomenon of MDR.We evaluated the most diverse maize population including999individuals for quantitative resistance under the epiphytotic of Exserohilum turcicum across several environments using SNP markers. High-resolution genome-wide association analysis was conducted using56110SNP markers, which were evenly distributed throughout the genome. We observed that these markers controlled42.2,47.4, and53.8%of the total genetic variance for area under disease progress curve (AUDPC), mean rating and maximum rating, respectively. SNP based genome wide association mapping revealed a total of49significant loci for these traits, among which4genes were common for all the three traits. Haplotype based association mapping revealed six and seven alleles for AUDPC and maximum rating, while five alleles were detected for mean rating. Among these, four alleles were common for the three traits, which were located on chromosomes7,8and10. The results for Anderson-Darling (A-D) test revealed more than100candidate loci in sub-group A while sub-group C and B harbored few or even no genes for different traits explaining the differences in the genetic background of the germplasm in each sub-group. The possible candidate genes are GRMZM2G171605, GRMZM2G100107, GRMZM2G158141and GRMZM2G020254. Among these genes the GRMZM2G100107was confirmed for all the three traits using SNP and haplotype based association mapping and confirmed by A-D test as well. The other gene (GRMZM2G020254) was detected for two traits in SNP based analysis while significant for three traits in haplotype based analysis. Some of the genes were adjacent to already known possible candidate genes that allow more investigation as putative causal genes underlying quantitative disease-resistance QTL.Another study was conducted to confirm some loci in maize genome for SLB using linkage mapping in a RIL population (Yu87-1/Zong3). The analysis of variance showed highly significant differences in the germplasm and high broad-sense heritability (0.76) was observed for SLB resistance. An integrated genetic linkage map was constructed using137S9SNP markers, spanning a total of2710cM of the maize genome with an average interval of0.2cM. Three QTL for resistance to SLB were identified by CIM, which reside on chromosome3,5, and7, together accounting for7.27to14.40%of the phenotypic variation for this trait. Two of these QTL were contributed by the resistant parent87-1(Chr3and5) and overall the additive QTL explained30.29%of the total phenotypic variation. Therefore, we concluded that NLB and SLB are very complex traits no single major gene is responsible for resistance while several minor genes control these disease with relative low effects.