CDC Milestone lentil

Vandenberg, Albert; Kiehn, F. A.; Vera, C.; Gaudiel, R.; Buchwaldt, L.; Kirkland, K. J.; Morrall, R. A. A.; Wahab, J.; Slinkard, A. E.

doi:10.4141/p00-043

Cited by 17 publications

(6 citation statements)

References 1 publication

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“…The third population, LR-11, included 120 RILs developed from a cross between 'CDC Milestone' and 'ILL 8006-BM4'. 'CDC Milestone' is a high yielding, yellow cotyledon lentil cultivar developed at the CDC (Vandenberg et al 2001). 'ILL 8006-BM4' was derived from 'Barimasur-4', a highyielding, disease-resistant, red cotyledon cultivar from Bangladesh (Sarker et al 1999).…”

Section: Plant Materials and Phenotypingmentioning

confidence: 99%

Genomic selection for lentil breeding: empirical evidence

Haile

Heidecker

Wright

et al. 2019

Preprint

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Genomic selection (GS) is a type of marker-based selection which was initially suggested for livestock breeding and is being encouraged for crop breeding. Several statistical models and approaches have been developed to implement GS; however, none of these methods have been tested for use in lentil breeding. This study was conducted to evaluate different GS models and prediction scenarios based on empirical data and to make recommendations for designing genomic selection strategies for lentil breeding. We evaluated nine single-trait models, two multiple-trait models, and models that account for population structure and genotype-byenvironment interaction (GEI) using a lentil diversity panel and two recombinant inbred lines (RIL) populations that were genotyped using a custom exome capture assay. Within-population, across-population and across-environment predictions were made for five phenology traits.Prediction accuracy varied among the evaluated models, populations, prediction scenarios, traits, and statistical models. Single-trait models showed similar accuracy for each trait in the absence of large effect QTL but BayesB outperformed all models when there were QTL with relatively large effects. Models that accounted for GEI and multiple-trait (MT) models increased prediction accuracy for a low heritability trait by up to 66% and 14% but accuracy did not improve for traits of high heritability. Moderate to high accuracies were obtained for within-population and acrossenvironment predictions but across-population prediction accuracy was very low. This suggests that GS can be implemented in lentil to make predictions within populations and across environments, but across-population prediction should not be considered when the population size is small.

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Section: Plant Materials and Phenotypingmentioning

confidence: 99%

Genomic selection for lentil breeding: empirical evidence

Haile

Heidecker

Wright

et al. 2019

Preprint

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“…The most environmentally acceptable and economically profitable method of control is to develop varieties with high levels of durable resistance. A few major ascochyta blight R-genes have been characterized in different lentil genotypes (Tay and Slinkard, 1989; Andrahennadi, 1994, 1997; Ahmad et al, 1997; Ford et al, 1999; Ye et al, 2000; Nguyen et al, 2001), and varieties partially resistant to ascochyta blight have been released (Ali, 1995; Vandenberg et al, 2001, 2002). …”

Section: Introductionmentioning

confidence: 99%

Genotype-Dependent Interaction of Lentil Lines with Ascochyta lentis

et al. 2017

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Ascochyta blight of lentil is a prevalent disease in many lentil producing regions and can cause major yield and grain quality losses. The most environmentally acceptable and economically profitable method of control is to develop varieties with high levels of durable resistance. Genetic studies to date suggest that ascochyta blight resistance genes (R-gene) in lentil lines CDC Robin, ILL 7537, 964a-46, and ILL 1704 are non-allelic. To understand how different R-genes manifest resistance in these genotypes and an accession of Lens ervoides, L-01-827A, with high level of resistance to ascochyta blight, cellular and molecular defense responses were compared after inoculation with the causal pathogen Ascochyta lentis. Pathogenicity testing of the resistant lines to A. lentis inoculation revealed significantly lower disease severity on CDC Robin and ILL 7537 compared to ILL 1704 and 964a-46, and no symptoms of disease were observed on L-01-827A. Histological examinations indicated that cell death triggered by the pathogen might be disrupted as a mechanism of resistance in CDC Robin. In contrast, limiting colonization of epidermal cells by A. lentis is a suggested mechanism of resistance in 964a-46. A time-series comparison of the expressions of hallmark genes in salicylic acid (SA) and jasmonic acid (JA) signal transduction pathways between CDC Robin and 964a-46 was conducted. These partially resistant genotypes differed in the timing and the magnitude of SA and JA signaling pathway activation. The SA signaling pathway was only triggered in 964a-46, whereas the JA pathway was triggered in both partially resistant genotypes CDC Robin and 964a-46. The expression of JA-associated genes was lower in 964a-46 than CDC Robin. These observations corroborate the existence of diverse ascochyta blight resistance mechanisms in lentil genotypes carrying different R-genes.

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“…Crosses were made to introduce the resistance genes into lentil varieties with desirable agronomical traits (Buchwaldt et al, 1995). Genetic studies suggested that a single recessive gene conferred resistance in Indianhead, while that in PI 345629 and PI 320937 was based on single dominant resistance genes (Buchwaldt et al, 2001). The putative genes were designated lct-1 (Indianhead), LCT-2 (PI 320937) and LCT-3 (PI 345629).…”

Section: Sources Of Resistancementioning

confidence: 99%

Screening techniques and sources of resistance to foliar diseases caused by major necrotrophic fungi in grain legumes

Tivoli¹,

Baranger²,

Ávila

et al. 2006

Euphytica

150

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Necrotrophic pathogens of the cool season food legumes (pea, lentil, chickpea, faba bean and lupin) cause wide spread disease and severe crop losses throughout the world. Environmental conditions play an important role in the development and spread of these diseases. Form of inoculum, inoculum concentration and physiological plant growth stage all affect the degree of infection and the amount of crop loss. Measures to control these diseases have relied on identification of resistant germplasm and development of resistant varieties through screening in the field and in controlled environments. Procedures for screening and scoring germplasm and breeding lines for resistance have lacked uniformity among the various programs worldwide. However, this review highlights the most consistent screening and scoring procedures that are simple to use and provide reliable results. Sources of resistance to the major necrotrophic fungi are summarized for each of the cool season food legumes. Marker-assisted selection is underway for Ascochyta blight of pea, lentil and chickpea, and Phomopsis blight of lupin. Other measures such as fungicidal control and cultural control are also reviewed. The emerging genomic information on the model legume, Medicago truncatula, which has various degrees of genetic synteny with the cool season food legumes, has promise for identification of closely linked markers for resistance genes and possibly for eventual map-based cloning of resistance genes. Durable resistance to the necrotrophic pathogens is a common goal of cool season food legume breeders.

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CDC Milestone lentil

Cited by 17 publications

References 1 publication

Genomic selection for lentil breeding: empirical evidence

Genomic selection for lentil breeding: empirical evidence

Genotype-Dependent Interaction of Lentil Lines with Ascochyta lentis

Screening techniques and sources of resistance to foliar diseases caused by major necrotrophic fungi in grain legumes

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