Identification of quantitative trait loci controlling resistance to gray leaf spot disease in maize

Parasites represent strong selection on host populations because they are ubiquitous and can drastically reduce host fitness. It has been hypothesized that parasite selection could explain the widespread occurrence of recombination because it is a coevolving force that favours new genetic combinations in the host. A review of deterministic models for the maintenance of recombination reveals that for recombination to be favoured, multiple genes that interact with each other must be under selection. To evaluate whether parasite selection can explain the maintenance of recombination, we review 85 studies that investigated the genetic architecture of plant disease resistance and discuss whether they conform to the requirements that emerge from theoretical models. General characteristics of disease resistance in plants and problems in evaluating resistance experimentally are also discussed. We found strong evidence that disease resistance in plants is determined by multiple loci. Furthermore, in most cases where loci were tested for interactions, epistasis between loci that affect resistance was found. However, we found weak support for the idea that specific allelic combinations determine resistance to different host genotypes and there was little data on whether epistasis between resistance genes is negative or positive. Thus, the current data indicate that it is possible that parasite selection can favour recombination, but more studies in natural populations that specifically address the nature of the interactions between resistance genes are necessary. The data summarized here suggest that disease resistance is a complex trait and that environmental effects and fitness trade-offs should be considered in future models of the coevolutionary dynamics of host and parasites.

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“…Among them, three indicated negative epistasis (Byrne et al . 1996; Maroof et al . 1996; Yencho et al .…”

Section: Interaction Between Resistance Qtlmentioning

confidence: 99%

The genetic architecture of disease resistance in plants and the maintenance of recombination by parasites

Kover

Caicedo

2001

Molecular Ecology

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“…Maroof et al. () detected three main resistance QTLs, but only one of these QTLs was detected repeatedly in multiple environments. Liu et al.…”

Section: Discussionmentioning

confidence: 99%

“…So far, based on studies of multiple locating populations built from different resistant germplasms, a series of GLS resistance QTLs from different sources have been identified. Maroof, Yue, Xiang, Stromberg, and Rufener () constructed an F 2 population from Va14 × B73 and detected three main resistance QTLs on chromosomes 1, 4, and 8 that explained 7.7%‐56% of the phenotypic variation rate. Clements, Dudley, and White () constructed populations with 061 × FR1141 and detected five QTLs for resistance to GLS and six QTLs for growth period that were associated with disease resistance.…”

Section: Introductionmentioning

confidence: 99%

QTL mapping for resistance of maize to grey leaf spot

Lin

Leng

et al. 2017

Journal of Phytopathology

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Grey leaf spot (GLS) is a global maize leaf disease that seriously endangers maize production. Discovering and utilizing genetic loci for GLS resistance would be useful for breeding new varieties with improved resistance. In this study, 233 F2:3 families (produced from the susceptible inbred line 08‐641 × the resistant inbred line 446) were used for quantitative trait locus (QTL) mapping of resistance to GLS. Five GLS resistance QTLs were detected on chromosomes 1, 2, 3, 4, and 6, which explained 6.7%‐21.3% of the phenotypic variation. The QTLs, qRgls.CH‐4, qRgls.CH‐1, qRgls.CH‐2, and qRgls.CH‐6, were stably expressed in the four environments, and all loci for GLS resistance were derived from the resistant parent, 446. The additive effects of qRgls.CH‐4, qRgls.CH‐1, and qRgls.CH‐6 were significantly greater than their single dominant effects, which may be beneficial for GLS resistance breeding. The QTL qRgls.CH‐6, located in bins 6.02–6.05, did not overlap with any previously reported resistance QTL and thus was identified here for the first time. QTL analysis of PI (leaf performance index) detected three leaf function QTLs on chromosomes 4, 8, and 9 were related to GLS resistance and explained 4.8%‐6.2% of the phenotypic variation. Among them, qPI.CH‐4 was significantly stronger expressed in several environments; this allele associated with increased leaf function came from the resistant parent, 446, and its interval overlapped with that of qRgls.CH‐4. Furthermore, both qRgls.CH‐4 and qPI.CH‐4 were located in a hotspot area for GLS resistance in bins 4.05‐4.06, indicating that GLS resistance was significantly related to leaf performance and that GLS significantly reduced leaf photosynthetic performance.

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“…Estudos de herança indicam que a resistência é governada por um grande número de genes de pequeno efeito com prevalência de efeitos aditivos (Thompson et al, 1987;de Nazareno et al, 1992;Donahue et al, 1991;Bubeck et al, 1993;Coates & White, 1994;Marrof et al, 1996). Em adição a isso, um gene conferindo resistência qualitativa e com prevalente ação dominante foi descrito em genótipos cultivados na África do Sul (Gevers et al, 1994).…”

Section: Controle Da Doençaunclassified

Cercospora zeae-maydis: esporulação, diversidade morfo-genética e reação de linhagens de milho.

Brunelli¹

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Identification of quantitative trait loci controlling resistance to gray leaf spot disease in maize

Cited by 7 publications

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The genetic architecture of disease resistance in plants and the maintenance of recombination by parasites

The genetic architecture of disease resistance in plants and the maintenance of recombination by parasites

QTL mapping for resistance of maize to grey leaf spot

Cercospora zeae-maydis: esporulação, diversidade morfo-genética e reação de linhagens de milho.

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