Mapping Quantitative Trait Loci for Resistance to Goss's Bacterial Wilt and Leaf Blight in North American Maize by Joint Linkage Analysis

Singh, Amritpal; Andersen, Aaron P.; Jackson-Ziems, T. A.; Lorenz, Aaron J.

doi:10.2135/cropsci2015.09.0543

Cited by 13 publications

(45 citation statements)

References 22 publications

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“…The heritability of GW resistance in this population was relatively high and on par with previous GW studies ( Ngong-Nassah 1992 ; Singh et al 2016 ; Cooper et al 2018 ). High heritability has been reported for the three fungal diseases for this population, namely 0.76 for SCLB, 0.75 for NCLB, and 0.59 for GLS ( Lopez-Zuniga et al 2019 ), indicating that progress can be made from inbred line evaluations in breeding for these diseases.…”

Section: Discussionsupporting

confidence: 79%

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Identification of Loci That Confer Resistance to Bacterial and Fungal Diseases of Maize

Qiu

Cooper

Kaiser

et al. 2020

G3 Genes|Genomes|Genetics

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Crops are hosts to numerous plant pathogenic microorganisms. Maize has several major disease issues; thus, breeding multiple disease resistant (MDR) varieties is critical. While the genetic basis of resistance to multiple fungal pathogens has been studied in maize, less is known about the relationship between fungal and bacterial resistance. In this study, we evaluated a disease resistance introgression line (DRIL) population for the foliar disease Goss's bacterial wilt and blight (GW) and conducted quantitative trait locus (QTL) mapping. We identified a total of ten QTL across multiple environments. We then combined our GW data with data on four additional foliar diseases (northern corn leaf blight, southern corn leaf blight, gray leaf spot, and bacterial leaf streak) and conducted multivariate analysis to identify regions conferring resistance to multiple diseases. We identified 20 chromosomal bins with putative multiple disease effects. We examined the five chromosomal regions (bin 1.05, 3.04, 4.06, 8.03, and 9.02) with the strongest statistical support. By examining how each haplotype effected each disease, we identified several regions associated with increased resistance to multiple diseases and three regions associated with opposite effects for bacterial and fungal diseases. In summary, we identified several promising candidate regions for multiple disease resistance in maize and specific DRILs to expedite interrogation.

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Section: Discussionsupporting

confidence: 79%

“…The GW QTL we identified were relatively stable across multiple environments in the single trait analysis. The QTL in bins 1.05, 2.07 and 9.02 were consistently detected and colocalized with previously identified QTL ( Cooper et al 2018 ; Singh et al 2016 ).…”

Section: Discussionsupporting

confidence: 69%

Identification of Loci That Confer Resistance to Bacterial and Fungal Diseases of Maize

Qiu

Cooper

Kaiser

et al. 2020

G3 Genes|Genomes|Genetics

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“…The three bi-parental RIL populations selected from the NAM population were B73 x Oh43, B73 x HP301, and B73 x P39. These same populations were used in an earlier study to identify QTL for Goss’s wilt through linkage mapping (Singh et al 2016). While the common parent, B73, is moderately resistant, the other three parents were found to be comparatively susceptible to Goss’s wilt in a preliminary screening.…”

Section: Methodsmentioning

confidence: 99%

“…In 2014, 174 RILs from the B73 x Oh43 population, 143 RILs from the B73 x HP301 population, and 124 RILs from the B73 x P39 population were phenotyped for Goss’s wilt. The lines were evaluated using a completely randomized field design with replicated checks as described earlier (Singh et al 2016).…”

Section: Methodsmentioning

confidence: 99%

“…The re-emergence of Goss’s wilt has increased interest in identifying sources of resistance, molecular markers that could be used for selection, and genes controlling resistance. Using three bi-parental maize populations connected by a common parent, Singh et al (2016) identified eleven QTL of small effect, half of which were population specific. Schaefer and Bernardo (2013) performed genome-wide association mapping for Goss’s wilt and identified several SNPs associated with resistance, each explaining no more than 10% of the phenotypic variation.…”

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confidence: 99%

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Genome-Wide Association and Gene Co-expression Network Analyses Reveal Complex Genetics of Resistance to Goss’s Wilt of Maize

Singh

Brohammer

et al. 2019

G3 Genes|Genomes|Genetics

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Goss’s bacterial wilt and leaf blight is a disease of maize caused by the gram positive bacterium Clavibacter michiganensis subsp. nebraskensis (Cmn). First discovered in Nebraska, Goss’s wilt has now spread to major maize growing states in the United States and three provinces in Canada. Previous studies conducted using elite maize inbred lines and their hybrids have shown that resistance to Goss’s wilt is a quantitative trait. The objective of this study was to further our understanding of the genetic basis of resistance to Goss’s wilt by using a combined approach of genome-wide association mapping and gene co-expression network analysis. Genome-wide association analysis was accomplished using a diversity panel consisting of 555 maize inbred lines and a set of 450 recombinant inbred lines (RILs) from three bi-parental mapping populations, providing the most comprehensive screening of Goss’s wilt resistance to date. Three SNPs in the diversity panel and 10 SNPs in the combined dataset, including the diversity panel and RILs, were found to be significantly associated with Goss’s wilt resistance. Each significant SNP explained 1–5% of the phenotypic variation for Goss’s wilt (total of 8–11%). To augment the results of genome-wide association mapping and help identify candidate genes, a time course RNA sequencing experiment was conducted using resistant (N551) and susceptible (B14A) maize inbred lines. Gene co-expression network analysis of this time course experiment identified one module of 141 correlated genes that showed differential regulation in response to Cmn inoculations in both resistant and susceptible lines. SNPs inside and flanking these genes explained 13.3% of the phenotypic variation. Among 1,000 random samples of genes, only 8% of samples explained more phenotypic variance for Goss’s wilt resistance than those implicated by the co-expression network analysis. While a statistically significant enrichment was not observed (P < 0.05), these results suggest a possible role for these genes in quantitative resistance at the field level and warrant more research on combining gene co-expression network analysis with quantitative genetic analyses to dissect complex disease resistance traits. The results of the GWAS and co-expression analysis both support the complex nature of resistance to this important disease of maize.

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Genetic dissection of maize disease resistance and its applications in molecular breeding

Zhu

Tong

et al. 2021

Mol Breeding

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Disease resistance is essential for reliable maize production. In a long-term tug-of-war between maize and its pathogenic microbes, naturally occurring resistance genes gradually accumulate and play a key role in protecting maize from various destructive diseases. Recently, significant progress has been made in deciphering the genetic basis of disease resistance in maize. Enhancing disease resistance can now be explored at the molecular level, from marker-assisted selection to genomic selection, transgenesis technique, and genome editing. In view of the continuing accumulation of cloned resistance genes and in-depth understanding of their resistance mechanisms, coupled with rapid progress of biotechnology, it is expected that the large-scale commercial application of molecular breeding of resistant maize varieties will soon become a reality.

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Mapping Quantitative Trait Loci for Resistance to Goss's Bacterial Wilt and Leaf Blight in North American Maize by Joint Linkage Analysis

Abstract: Supporting information for this article is available following the references.

Cited by 13 publications

References 22 publications

Identification of Loci That Confer Resistance to Bacterial and Fungal Diseases of Maize

Identification of Loci That Confer Resistance to Bacterial and Fungal Diseases of Maize

Genome-Wide Association and Gene Co-expression Network Analyses Reveal Complex Genetics of Resistance to Goss’s Wilt of Maize

Genetic dissection of maize disease resistance and its applications in molecular breeding

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