QTL analysis for ascochyta blight resistance in an intraspecific population of chickpea (Cicer arietinum L.)

Flandez-Galvez, H.; Ades, Peter K.; Ford, Rebecca; Pang, E. C. K.; Taylor, P. W. J.

doi:10.1007/s00122-003-1371-4

Cited by 112 publications

(84 citation statements)

References 49 publications

(47 reference statements)

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“…This marker explained between 59 and 69% of the variations for resistance using different isolates under controlled environments. Furthermore, loci TS12b and STMS28 on LG 1, TS45 and TA3b on LG 2, were significantly associated with the disease reaction under controlled environments [88,89]. Bian et al [90] compared three chickpea LGs, harbouring six QTLs conditioning resistance against A. rabiei with the most comprehensive chickpea map (W-Ca-LG) and found that QTL1 (LG 3) was located in the subcentromere region of the chickpea W-Ca-LG3 (chromosome C).…”

Section: Inheritance and Marker Assisted Breeding For Ab Resistancementioning

confidence: 99%

An Update on Genetic Resistance of Chickpea to Ascochyta Blight

Sharma

Ghosh

2016

Agronomy

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Ascochyta blight (AB) caused by Ascochyta rabiei (Pass.) Labr. is an important and widespread disease of chickpea (Cicer arietinum L.) worldwide. The disease is particularly severe under cool and humid weather conditions. Breeding for host resistance is an efficient means to combat this disease. In this paper, attempts have been made to summarize the progress made in identifying resistance sources, genetics and breeding for resistance, and genetic variation among the pathogen population. The search for resistance to AB in chickpea germplasm, breeding lines and land races using various screening methods has been updated. Importance of the genotypeˆenvironment (GE) interaction in elucidating the aggressiveness among isolates from different locations and the identification of pathotypes and stable sources of resistance have also been discussed. Current and modern breeding programs for AB resistance based on crossing resistant/multiple resistant and high-yielding cultivars, stability of the breeding lines through multi-location testing and molecular marker-assisted selection method have been discussed. Gene pyramiding and the use of resistant genes present in wild relatives can be useful methods in the future. Identification of additional sources of resistance genes, good characterization of the host-pathogen system, and identification of molecular markers linked to resistance genes are suggested as the key areas for future study.

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Section: Inheritance and Marker Assisted Breeding For Ab Resistancementioning

confidence: 99%

An Update on Genetic Resistance of Chickpea to Ascochyta Blight

Sharma

Ghosh

2016

Agronomy

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“…The map was used to map genes for important morphological traits along with the double podded character. An intraspecific chickpea genome map consisting of 51 STMS, 3 inter-simple sequence repeats (ISSRs) and 12 resistance gene analogs (RGA) mapped to eight linkage groups was developed using an F 2 population of chickpea [67]. Another map developed based on a "Kabuli × Desi" cross included a total of 134 molecular markers (3 ISSR, 13 STMSs AND 118 RAPDs) mapped to 10 linkage groups [68].…”

Section: Linkage Mappingmentioning

confidence: 99%

“…It integrated 555 marker loci including, RAPDs (251), STMSs (149), AFLPs (47), 33 cross-genome markers, 28 gene-specific markers, 10 isozyme markers, 10 inter-simple sequence repeats (ISSRs) and 7 RGA loci. Several other linkage maps were developed using different mapping populations with different morphological and molecular markers [66,67,[72][73][74]. More recently, a comprehensive genetic map spanning 845.56 cM was developed using RILs from C. arietinum (ICC 4958) × C. reticulatum (PI 489777) [55].…”

Section: Linkage Mappingmentioning

confidence: 99%

Impact of Genomic Technologies on Chickpea Breeding Strategies

2012

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Abstract:The major abiotic and biotic stresses that adversely affect yield of chickpea (Cicer arietinum L.) include drought, heat, fusarium wilt, ascochyta blight and pod borer. Excellent progress has been made in developing short-duration varieties with high resistance to fusarium wilt. The early maturity helps in escaping terminal drought and heat stresses and the adaptation of chickpea to short-season environments. Ascochyta blight continues to be a major challenge to chickpea productivity in areas where chickpea is exposed to cool and wet conditions. Limited variability for pod borer resistance has been a major bottleneck in the development of pod borer resistant cultivars. The use of genomics technologies in chickpea breeding programs has been limited, since available genomic resources were not adequate and limited polymorphism was observed in the cultivated chickpea for the available molecular markers. Remarkable progress has been made in the development of genetic and genomic resources in recent years and integration of genomic technologies in chickpea breeding has now started. Marker-assisted breeding is currently being used for improving drought tolerance and combining resistance to diseases. The integration of genomic technologies is expected to improve the precision and efficiency of chickpea breeding in the development of improved cultivars with enhanced resistance to abiotic and biotic stresses, better adaptation to existing and evolving agro-ecologies and traits preferred by farmers, industries and consumers.

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“…Replicated phenotypic measurements or the use of clones (via cuttings) can be used to improve the accuracy of QTL mapping by reducing background ‗noise' (Danesh et al, 1994;Haley and Andersson, 1997). Some thorough studies include those where phenotypic evaluations have been conducted in both field and glasshouse trials, for ascochyta blight resistance in chickpea (Flandez-Galvez et al, 2003a), bacterial brown spot in common bean (Jung et al, 2003), and downy mildew resistance in pearl millet (Jones et al, 2002).…”

Section: Factors Influencing the Detection Of Qtlsmentioning

confidence: 99%

Recent Advances in QTL Mapping and Quantitative Disease Resistance Approach

Sheikh¹

2017

Int.J.Curr.Microbiol.App.Sci

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Quantitative trait locus (QTL) mapping is a highly effective approach for studying genetically complex forms of plant disease resistance. With QTL mapping, the roles of specific resistance loci can be described, race-specificity of partial resistance genes can be assessed and interactions between resistance genes, plant development and the environment can be analysed (Young, 1996). DNA markers tightly linked to quantitative resistance loci (QRLs) controlling QDR can be used for marker-assisted selection (MAS) to incorporate these valuable traits. QDR confers a reduction, rather than lack, of disease and has diverse biological and molecular bases as revealed by cloning of QRLs and identification of the candidate gene(s) underlying QRLs (Dina St. Clair, 2010). Outstanding examples include: quantitative resistance to the rice blast fungus, late blight of potato, bacterial wilt of tomato, and the soybean cyst nematode. These studies provide insights into the number of quantitative resistance loci involved in complex disease resistance, epistasis and environmental interactions, race-specificity of partial resistance loci, interactions between pathogen biology, plant development. A thorough understanding of quantitative disease resistance (QDR) would contribute to the design and deployment of durably resistant crop cultivars. However, the molecular mechanisms that control QDR remain poorly understood, largely due to the incomplete and inconsistent nature of the resistance phenotype, which is usually conditioned by many loci of small effect (Jesse Poland et al., 2008). QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms and breeding methods. Thus QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits (Fred van Eeuwijk et al., 2010). DNA marker technology, QTL theory and statistical methodology for QTL analysis have undergone rapid developments in the past two decades. These concepts and the jargon used by molecular biologists may not be clearly understood by plant breeders and other plant scientists (Collard et al., 2005). Host pattern recognition receptor (HPRR) genes, and defenseresponsive or defense-related genes are important resources for quantitative broad spectrum resistance and durable resistance (Yanjun Kou and Shiping Wang, 2010). Adaptation to the hypersensitive R-genes by fungal and bacterial specialists is quite different from the adaptations to polygenic quantitative resistance. In first case a loss mutation in the avirulence gene results in restoring the pathogenicity. In the latter, exemplified by the cereals/take-all pathosystem, the mutation is due to a gain mutation. Adaptation by a loss mutation is expected to be much easier than adaptation through a gain mutation. This is the main reason for the large difference in durability (Jan Parlevliet).QRLs for which the phenotypic effects on QDR have been verified and for...

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QTL analysis for ascochyta blight resistance in an intraspecific population of chickpea (Cicer arietinum L.)

Cited by 112 publications

References 49 publications

An Update on Genetic Resistance of Chickpea to Ascochyta Blight

An Update on Genetic Resistance of Chickpea to Ascochyta Blight

Impact of Genomic Technologies on Chickpea Breeding Strategies

Recent Advances in QTL Mapping and Quantitative Disease Resistance Approach

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