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Zhai R, Huang A, Mo R, Zou C, Wei X, Yang M, Tan H, Huang K, Qin J. SNP-based bulk segregant analysis revealed disease resistance QTLs associated with northern corn leaf blight in maize. Front Genet 2022; 13:1038948. [PMID: 36506330 PMCID: PMC9732028 DOI: 10.3389/fgene.2022.1038948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 10/31/2022] [Indexed: 11/27/2022] Open
Abstract
Maize (Zea mays L.) is the most important food security crop worldwide. Northern corn leaf blight (NCLB), caused by Exserohilum turcicum, severely reduces production causing millions of dollars in losses worldwide. Therefore, this study aimed to identify significant QTLs associated with NCLB by utilizing next-generation sequencing-based bulked-segregant analysis (BSA). Parental lines GML71 (resistant) and Gui A10341 (susceptible) were used to develop segregating population F2. Two bulks with 30 plants each were further selected from the segregating population for sequencing along with the parental lines. High throughput sequencing data was used for BSA. We identified 10 QTLs on Chr 1, Chr 2, Chr 3, and Chr 5 with 265 non-synonymous SNPs. Moreover, based on annotation information, we identified 27 candidate genes in the QTL regions. The candidate genes associated with disease resistance include AATP1, At4g24790, STICHEL-like 2, BI O 3-BIO1, ZAR1, SECA2, ABCG25, LECRK54, MKK7, MKK9, RLK902, and DEAD-box ATP-dependent RNA helicase. The annotation information suggested their involvement in disease resistance-related pathways, including protein phosphorylation, cytoplasmic vesicle, protein serine/threonine kinase activity, and ATP binding pathways. Our study provides a substantial addition to the available information regarding QTLs associated with NCLB, and further functional verification of identified candidate genes can broaden the scope of understanding the NCLB resistance mechanism in maize.
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Affiliation(s)
- Ruining Zhai
- Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China
| | - Aihua Huang
- Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China
| | - Runxiu Mo
- Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China
| | - Chenglin Zou
- Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China
| | - Xinxing Wei
- Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China
| | - Meng Yang
- Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China
| | - Hua Tan
- Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China
| | - Kaijian Huang
- Maize Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China,*Correspondence: Kaijian Huang, ; Jie Qin,
| | - Jie Qin
- Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China,*Correspondence: Kaijian Huang, ; Jie Qin,
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Population Structure Analysis and Association Mapping for Turcicum Leaf Blight Resistance in Tropical Maize Using SSR Markers. Genes (Basel) 2022; 13:genes13040618. [PMID: 35456424 PMCID: PMC9030036 DOI: 10.3390/genes13040618] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 03/26/2022] [Accepted: 03/28/2022] [Indexed: 12/04/2022] Open
Abstract
Maize is an important cereal crop in the world for feed, food, fodder, and raw materials of industries. Turcicum leaf blight (TLB) is a major foliar disease that can cause more than 50% yield losses in maize. Considering this, the molecular diversity, population structure, and genome-wide association study (GWAS) for TLB resistance were studied in 288 diverse inbred lines genotyped using 89 polymorphic simple sequence repeats (SSR) markers. These lines werescreened for TLB disease at two hot-spot locations under artificially inoculated conditions. The average percent disease incidence (PDI) calculated for each genotype ranged from 17 (UMI 1201) to 78% (IML 12-22) with an overall mean of 40%. The numbers of alleles detected at a locus ranged from twoto nine, with a total of 388 alleles. The polymorphic information content (PIC) of each marker ranged between 0.04 and 0.86. Out of 89 markers, 47 markers were highly polymorphic (PIC ≥ 0.60). This indicated that the SSR markers used were very informative and suitable for genetic diversity, population structure, and marker-trait association studies.The overall observed homozygosity for highly polymorphic markers was 0.98, which indicated that lines used were genetically pure. Neighbor-joining clustering, factorial analysis, and population structure studies clustered the 288 lines into 3–5 groups. The patterns of grouping were in agreement with the origin and pedigree records of the genotypesto a greater extent.A total of 94.10% lines were successfully assigned to one or another group at a membership probability of ≥0.60. An analysis of molecular variance (AMOVA) revealed highly significant differences among populations and within individuals. Linkage disequilibrium for r2 and D′ between loci ranged from 0 to 0.77 and 0 to 1, respectively. A marker trait association analysis carried out using a general linear model (GLM) and mixed linear model (MLM), identified 15 SSRs markers significantly associated with TLB resistance.These 15 markers were located on almost all chromosomes (Chr) except 7, 8, and 9. The phenotypic variation explained by these loci ranged from 6% (umc1367) to 26% (nc130, phi085). Maximum 7 associated markers were located together on Chr 2 and 5. The selected regions identified on Chr 2 and 5 corroborated the previous studies carried out in the Indian maize germplasm. Further, 11 candidate genes were identified to be associated with significant markers. The identified sources for TLB resistance and associated markers may be utilized in molecular breeding for the development of suitable genotypes.
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Sunitha NC, Gangappa E, Gowda RPV, Ramesh S, Biradar S, Swamy D, Hemareddy HB. Discovery of genomic regions associated with resistance to late wilt disease caused by Harpophora maydis (Samra, Sabet and Hing) in maize (Zea mays L.). J Appl Genet 2021; 63:185-197. [PMID: 34841470 DOI: 10.1007/s13353-021-00672-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 11/17/2021] [Accepted: 11/23/2021] [Indexed: 11/24/2022]
Abstract
Late wilt disease (LWD) caused by Harpophora maydis (Samra, Sabet and Hing) is emerging as major production constraint in maize across the world. As a prelude to develop maize hybrid resistance to LWD, genetic basis of resistance was investigated. Two F2:3 mapping populations (derived from CV156670 × 414-33 (P-1) and CV156670 × CV143587 (P-2)) were challenged with LWD at two locations (Kallinayakanahalli and Muppadighatta) during 2017 post-rainy season. A wider range of LWD scores was observed at both locations in both the populations. LWD response was influenced by significant genotype × location interaction. Six and 56 F2:3 progeny families showed resistance level better than resistant parent. A total of 150 and 199 polymorphic single nucleotide polymorphism markers were used to genotype P-1 and P-2, respectively. Inclusive composite interval mapping was performed to detect significant Quantitative Trait Loci (QTL), QTL × QTL, QTL × location interaction effects. Three major and four minor QTL controlling LWD resistance were detected on chromosome-1. The position and effect of the QTL varied with the location. Significant di-QTL interactions involving QTL (with significant and/or non-significant effects) located within and between all the ten chromosomes were detected. Five of the seven detected QTL showed significant QTL × location interaction. Though two major QTL (q-lw-1.5 and q-lw-1.6) with lower Q×L interaction effects could be considered as stable, their phenotypic variance is not large enough to deploy them in Marker Assisted Selection (MAS). However, these QTL are of paramount importance in accumulating positive alleles for LWD resistance breeding.
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Affiliation(s)
- N C Sunitha
- Department of Genetics and Plant Breeding, College of Agriculture, University of Agricultural Sciences, Gandhi Krishi Vignana Kendra, Bengaluru, 560065, India
| | - E Gangappa
- Department of Genetics and Plant Breeding, College of Agriculture, University of Agricultural Sciences, Gandhi Krishi Vignana Kendra, Bengaluru, 560065, India
| | | | - S Ramesh
- Department of Genetics and Plant Breeding, College of Agriculture, University of Agricultural Sciences, Gandhi Krishi Vignana Kendra, Bengaluru, 560065, India.
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Ranganatha HM, Lohithaswa HC, Pandravada A. Mapping and Validation of Major Quantitative Trait Loci for Resistance to Northern Corn Leaf Blight Along With the Determination of the Relationship Between Resistances to Multiple Foliar Pathogens of Maize ( Zea mays L.). Front Genet 2021; 11:548407. [PMID: 33584784 PMCID: PMC7878677 DOI: 10.3389/fgene.2020.548407] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 12/14/2020] [Indexed: 11/13/2022] Open
Abstract
Among various foliar diseases affecting maize yields worldwide, northern corn leaf blight (NCLB) is economically important. The genetics of resistance was worked out to be quantitative in nature thereby suggesting the need for the detection of quantitative trait loci (QTL) to initiate effective marker-aided breeding strategies. From the cross CML153 (susceptible) × SKV50 (resistant), 344 F2 : 3 progenies were derived and screened for their reaction to NCLB during the rainy season of 2013 and 2014. The identification of QTL affecting resistance to NCLB was carried out using the genetic linkage map constructed with 194 polymorphic SNPs and the disease data recorded on F2 : 3 progeny families. Three QTL for NCLB resistance were detected on chromosomes 2, 5, and 8 with the QTL qNCLB-8-2 explaining the highest phenotypic variation of 16.34% followed by qNCLB-5 with 10.24%. QTL for resistance to sorghum downy mildew (SDM) and southern corn rust (SCR) were also identified from one season phenotypic data, and the co-location of QTL for resistance to three foliar diseases was investigated. QTL present in chromosome bins 8.03, 5.03, 5.04, and 3.04 for resistance to NCLB, SDM, and SCR were co-localized, indicating their usefulness for the pyramiding of quantitative resistance to multiple foliar pathogens. Marker-assisted selection was practiced in the crosses CM212 × SKV50, HKI162 × SKV50, and CML153 × SKV50 employing markers linked to major QTL on chromosomes 8, 2, and 10 for NCLB, SDM, and SCR resistance, respectively. The populations were advanced to F6 stage to derive multiple disease-resistant inbred lines. Out of the 125 lines developed, 77 lines were tested for their combining ability and 39 inbred lines exhibited high general combining ability with an acceptable level of resistance to major diseases.
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Affiliation(s)
- Hosahally Muddrangappa Ranganatha
- Department of Genetics and Plant Breeding, College of Agriculture - Mandya, University of Agricultural Sciences, Bengaluru, Bengaluru, India
| | - Hirenallur Chandappa Lohithaswa
- Department of Genetics and Plant Breeding, College of Agriculture - Mandya, University of Agricultural Sciences, Bengaluru, Bengaluru, India
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