Identification of candidate genes associated with mealiness and maturity date in peach [Prunus persica (L.) Batsch] using QTL analysis and deep sequencing

Núñez-Lillo, Gerardo; Cifuentes-Esquivel, Alejandra; Troggio, Michela; Micheletti, Diego; Infante, Rodrigo; Campos-Vargas, Reinaldo; Orellana, Ariel; Blanco‐Herrera, Francisca; Meneses, Claudio

doi:10.1007/s11295-015-0911-9

Cited by 68 publications

(97 citation statements)

References 74 publications

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“…To our knowledge, this is the sixth full map produced with the 'IPSC 9K peach SNP array v1' in peach, although others have been constructed with this array technology in other Prunus-derived progenies Yang et al 2013;Martínez-García et al 2013a;Frett et al 2014;Pacheco et al 2014;Romeu et al 2014;Da Silva-Linge et al 2015;Nuñez-Lillo et al 2015). The length of genetic linkage maps mostly based on SNP markers were more saturated compared with the previously published maps, with the exception of the T × E Prunus reference map (Dirlewanger et al 2006).…”

Section: Genetic Mapsmentioning

confidence: 86%

“…Moreover, Sánchez et al (2014) found that chromosomes 2, 1, and 3 were missing in a pseudo-test cross population between the cultivars 'MxR_01' and 'Granada'. The lack of polymorphic SNPs in certain chromosomes is caused by homozygosis in the peach genome and is probably due to germplasm background Sánchez et al 2014;Nuñez-Lillo et al 2015). Verde et al (2012) Table 3).…”

Section: Genetic Mapsmentioning

confidence: 99%

“…More recently, attempts have been made to map QTLs in peach using the newly developed SNP genotyping array v1 . Several QTLs that control traits such as chilling and heat requirements , blush (Frett et al 2014), maturity date Fresnedo-Ramírez et al 2015;Nuñez-Lillo et al 2015) or other pomological traits such as fruit weight, soluble solids content or pH (Fresnedo-Ramírez et al 2015) have been mapped. Moreover, the current analytical techniques are more powerful for large-scale phenotyping than older methods, and new traits related to fruit quality are being incorporated in QTL analysis.…”

Section: Introductionmentioning

confidence: 99%

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Mapping QTLs associated with fruit quality traits in peach [Prunus persica (L.) Batsch] using SNP maps

Zeballos

Abidi

Giménez

et al. 2016

Tree Genetics & Genomes

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Zeballos, JL.; Adibi, W.; Giménez Millán, R.; Monforte Gilabert, AJ.; Moreno, MA.; Gogorcena, Y. (2016). Mapping QTLs associated with fruit quality traits in peach Prunus persica (L.) Batsch using SNP maps. Tree Genetics and Genomes. 12(3):1-17. doi:10.1007/s11295-016-0996-9. AbstractFruit quality is an essential criterion used to select new cultivars in peach breeding programs and is determined based on a combination of organoleptic and nutritional traits. The aim of this study was to identify quantitative trait loci (QTLs) for fruit quality traits in an F 1 nectarine population derived from 'Venus' and 'Big Top' cultivars. The progeny were evaluated over 4 years for agronomical and biochemical characteristics, and genotyped using SSR markers and 'IPSC 9K peach SNP array v1'. Two genetic maps were constructed using 411 markers. The 'Venus' map spanned 259 cM on nine linkage groups (LGs) with 104 markers. The 'Big Top' map spanned 464 cM on ten LGs with 122 markers.Single or Multiple QTL models mapping was applied separately for each year and all years combined. A total of 54 QTLs mapped over 12LGs belonged to seven peach chromosomes. Most of the QTLs were consistent over the 4 years of study and were validated with the Multi-year analysis. QTLs for total phenolic, flavonoid, and anthocyanin contents were reported for the first time in peach.LG4 in 'Venus' and LG5 in 'Big Top' showed the highest numbers of QTLs. This work represents the first study in an F 1 nectarine family to identify peach genomic regions that control fruit quality traits using 'IPSC 9K SNP array v1' and provides useful information for marker-assisted breeding to produce peaches with better antioxidant content and healthy attributes.

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Section: Genetic Mapsmentioning

confidence: 86%

Section: Genetic Mapsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mapping QTLs associated with fruit quality traits in peach [Prunus persica (L.) Batsch] using SNP maps

Zeballos

Abidi

Giménez

et al. 2016

Tree Genetics & Genomes

View full text Add to dashboard Cite

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“…NACs constitute one of the largest plant TF families and are key regulators of developmental programmes and stress response ). In addition, more recently, Nuñez-Lillo et al (2015) have found a QTL in the same region of LG 4 of peach linked to maturity date, explaining around 80 % of the variability.…”

Section: Genetic Linkage Analysis and Qtl Identificationmentioning

confidence: 98%

Inheritance of reproductive phenology traits and related QTL identification in apricot

Salazar

Ruiz

Campoy

et al. 2016

Tree Genetics & Genomes

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Reproductive phenological traits of great agronomical interest in apricot species, including flowering date, ripening date and fruit development period, were studied during 3 years in two F 1 progenies derived from the crosses 'Bergeron' × 'Currot' (B × C) and 'Goldrich' × 'Currot' (G × C). Results showed great variability and segregation in each population, confirming the polygenic nature and quantitative inheritance of all the studied traits. Genetic linkage maps were constructed combining SSR and SNP markers, using 87 markers in the 'B × C' population and 89 markers in 'G × C'. The genetic linkage maps in both progenies show the eight linkage groups (LGs) of apricot, covering a distance of 394.9 cM in 'Bergeron' and of 414.3 cM in 'Currot'. The 'Goldrich' and 'Currot' maps were of 353.5 and 422.3 cM, respectively. The average distance obtained between markers was thus 7.59 cM in 'Bergeron' and 7.53 cM in 'Currot', whereas the 'Goldrich' and 'Currot' averages were 5.6 and 7.5 cM, respectively. According to the polygenic nature of the studied phenology traits, QTLs linked to flowering date, ripening date and the fruit development period were identified during the 3 years of the study in all LGs except for LG 8. Among the QTLs identified, major QTLs for flowering and ripening date and the fruit development period were identified in LG 4, especially important in the 'G × C' population.

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“…Another important fruit quality trait is resistance to cold storage, slow ripening (SR) is an interesting trait for selecting this resistance. Whole genome analysis allowed the identification of a deletion co-localizing with the SR trait (Nuñez-Lillo et al, 2015). Fruit acidity is a major determinant of fruit quality in peach.…”

Section: Impact Of Ngs On Breedingmentioning

confidence: 99%

Application of Genomic Technologies to the Breeding of Trees

et al. 2016

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The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species.

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Identification of candidate genes associated with mealiness and maturity date in peach [Prunus persica (L.) Batsch] using QTL analysis and deep sequencing

Cited by 68 publications

References 74 publications

Mapping QTLs associated with fruit quality traits in peach [Prunus persica (L.) Batsch] using SNP maps

Mapping QTLs associated with fruit quality traits in peach [Prunus persica (L.) Batsch] using SNP maps

Inheritance of reproductive phenology traits and related QTL identification in apricot

Application of Genomic Technologies to the Breeding of Trees

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