QTL Detection of Important Agronomic Traits for Sweet Cherry Breeding

Quero-Garcia, José; Fodor, Agota; Reignier, A.; Capdeville, Guy de; Joly, Jacques; Tauzin, Yves; Fouilhaux, Lydie; Dirlewanger, Elisabeth

doi:10.17660/actahortic.2014.1020.5

Cited by 20 publications

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“…Traits showing normal (MD) and bimodal (FD time) distribution were observed in this study, revealing different behavior of these traits. As reported here, normal distribution was previously observed for MD in sweet cherry 8 and apricot 5,27 . However, in most peach populations, bimodal distributions for MD were reported 10,11,25 .…”

Section: Haplotype Analysis Of Lg4supporting

confidence: 86%

“…Quantitative trait locus (QTL) analyses have been conducted in sweet cherry to investigate the genetic control of MD 7 – 9 but not FD period. Analysis of MD in a ‘Regina’ × ‘Lapins’ population during 3 years 7 , 8 identified three stable QTLs on linkage groups (LGs) 1, 4, and 5. A large percentage of variation was explained by a QTL on LG4 (20.4%), which was associated with advancing maturity 5.4 days 7 .…”

Section: Introductionmentioning

confidence: 99%

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Multiple-population QTL mapping of maturity and fruit-quality traits reveals LG4 region as a breeding target in sweet cherry (Prunus avium L.)

Calle

Wünsch

2020

Hortic Res

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Sweet cherry maturity date and fruit quality are relevant traits for its marketability, transport, and consumer acceptance. In this work, sweet cherry fruit development time, maturity date, and commercial fruit-quality traits (size, weight, firmness, soluble solid content, and titratable acidity) were investigated to improve the knowledge of their genetic control, and to identify alleles of breeding interest. Six sweet cherry populations segregating for these traits were used for QTL analyses. These populations descend from cross-and self-pollinations of local Spanish sweet cherries 'Ambrunés' and 'Cristobalina', and breed cultivars ('Brooks', 'Lambert', or 'Vic'). The six populations (n = 411), previously genotyped with RosBREED Cherry 6 K SNP array, were phenotyped for 2 years. QTL analyses were conducted using a multifamily approach implemented by FlexQTL ™. Fruit development time, soluble solid content, and titratable acidity QTLs are first reported in sweet cherry in this work. Significant QTLs were detected for all the traits. Eighteen were more stable as they were detected for 2 years. Of these, nine are first reported in this work. The major QTLs for fruit development time, maturity date, firmness, and soluble solid content were identified on the same narrow region of linkage group 4. These traits also showed significant positive correlation (long fruit development time associated with late maturity, high firmness, and high SSC). NAC transcription factor genes identified on this LG4 region may be candidate genes for the regulation of these traits in sweet cherry, as previously described in syntenic regions of other Rosaceae species. Haplotypes of breeding interest on this LG4 genomic region were identified and will be useful for sweet cherry breeding from this and related plant material.

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Section: Haplotype Analysis Of Lg4supporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Multiple-population QTL mapping of maturity and fruit-quality traits reveals LG4 region as a breeding target in sweet cherry (Prunus avium L.)

Calle

Wünsch

2020

Hortic Res

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“…This study is based on a model of individual SNP loci in linkage disequilibrium with chromosome segments containing numerous small-effect QTLs such that replication of SNP alleles across environments models the replication of causal alleles at the small-effect QTLs. However, as previous studies 10,12 have suggested the presence of large-effect QTLs contributing to genetic variation of fruit maturity timing, the model of genetic architecture used in this study might not be accurate. Incorporation of known QTL effects in the linear model should improve accuracy, as it is expected that such a model would more closely approximate the true distribution of QTL effects 77 .…”

Section: Discussionmentioning

confidence: 84%

“…Traditionally, sweet cherry cultivars are divided according to their maturity date into early (e.g., ‘Burlat’ and ‘Chelan’), mid- (e.g., ‘Bing’) and late season (e.g., ‘Sumtare’) 9 . Individual broad-sense heritability of fruit maturity timing is high (0.76–0.83) 10,11 and large-effect Quantiatative Trait Loci (QTLs) on linkage groups 1, 4, 5, and 6 have been detected within a full-sib family (‘Regina’ × ‘Lapins’), each explaining up to 20% of phenotypic variation 10,12 .…”

Section: Introductionmentioning

confidence: 99%

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array

et al. 2019

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The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G × E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA, thus sampling eight ‘environments’. The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions. Linkage disequilibrium among marker loci declined rapidly with physical distance, and ordination of the relationship matrix suggested no strong structure among germplasm. The most parsimonious G × E model allowed heterogeneous genetic variance and pairwise covariances among environments. Narrow-sense genomic heritability was very high (0.60–0.83), as was accuracy of predicted breeding values (>0.62). Average correlation of additive effects among environments was high (0.96) and breeding values were highly correlated across locations. Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments. Limited G × E for this trait indicated that phenotypes of individuals will be stable across similar environments. Equivalent analyses for other sweet cherry traits, for which multiple years of data are commonly available among breeders and cultivar testers, would be informative for predicting performance of elite selections and cultivars in new environments.

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“…Each genotype from the R×L progeny, grafted on 'Tabel Edabriz' rootstock, was planted in a large pot and placed in tunnels equipped with the overhead sprinklers. Slightly before maturity and irrigated during several hours at fixed times and for 5 d. Every day, the number of cracked fruits, out of a total of 100 fruits, was counted and removed (Quero-Garcia et al, 2009). This methodology was compared to cracking tolerance values observed in field conditions during three successive years (2008, 2009, and 2010).…”

Section: Genetics and Molecular Factors Involved In Fruit Crackingmentioning

confidence: 99%

Cracking in sweet cherries: A comprehensive review from a physiological, molecular, and genomic perspective

Balbontín¹,

Ayala²,

Bastías³

et al. 2013

Chilean J. Agric. Res.

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Rain-induced cracking in fruits of sweet cherry (Prunus avium [L.]) is a problem in most producing areas of the world and causes significant economic losses. Different orchard management practices have been employed to reduce the severity of this problem, although a complete solution is not yet available. Fruit cracking is a complex phenomenon and there are many factors that seem to be involved in its development. During the last decade, genomic and biochemical approaches have provided new insights on the different mechanisms that could be involved in the differential susceptibility shown by commercial cultivars. For instance, sweet cherry genome and transcriptome sequencing information have provided new opportunities to study the expression and structure of genes involved in cracking, which may help in the development of new tolerant cultivars. The present review summarizes, discuss, and integrate most of the recently generated information in cultural practices, physiology, biochemistry, and genetics in relation to cracking in sweet cherries.

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QTL Detection of Important Agronomic Traits for Sweet Cherry Breeding

Cited by 20 publications

References 0 publications

Multiple-population QTL mapping of maturity and fruit-quality traits reveals LG4 region as a breeding target in sweet cherry (Prunus avium L.)

Multiple-population QTL mapping of maturity and fruit-quality traits reveals LG4 region as a breeding target in sweet cherry (Prunus avium L.)

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array

Cracking in sweet cherries: A comprehensive review from a physiological, molecular, and genomic perspective

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