Genomics Approaches to Crop Improvement in the Rosaceae

Peace, Cameron; Norelli, J.L.

doi:10.1007/978-0-387-77491-6_2

Cited by 44 publications

(36 citation statements)

References 104 publications

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“…Clingstone non-melting flesh (CNMF) fruit lack a functional Melting flesh endoPG gene (Peace and Norelli 2009). This type of fruit remains firm and juicy following cold storage and ripening, although they become leathery if general ripening is disabled.…”

Section: Inheritance Of CI Symptomsmentioning

confidence: 99%

“…Both of our populations segregated into fruit types of FMF (F-allelic combinations) and CNMF. Although clingstone non-softening flesh (CNSF, f2f2) can be phenotypically and genotypically distinguished from CNMF (f1f1 and f1f2) (Peace and Norelli 2009), for our purposes of evaluating chilling injury incidence, allelic combinations of f1f1 ('Dr. Davis'), f1f2 (CNMF Pop-G seedlings), and f2f2 (CNSF Pop-G seedlings) were grouped as ''CNMF''.…”

Section: Relationships Among Traitsmentioning

confidence: 99%

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Influence of year and genetic factors on chilling injury susceptibility in peach (Prunus persica (L.) Batsch)

et al. 2011

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Chilling injury (CI) is a major physiological problem limiting consumption and export of peach and nectarine (Prunus persica (L.) Batsch). To clarify the genetic basis for chilling injury, inheritance of the major CI symptoms mealiness, flesh browning, flesh bleeding, and flesh leatheriness were examined over three years in two related peach progenies. In addition, genetic relationships among traits and the year-to-year variation in trait performance in these progenies were tracked. Both populations also segregated for Freestone-Melting flesh (F-M) and yellow flesh. There were significant differences in CI symptoms among years. The major gene endoPG, which controls the F-M locus, provides resistance to mealiness in nonmelting flesh fruit. Only fruit with melting flesh can develop mealiness if the tree possesses other genetic susceptibility factors and/or experiences inducing conditions. The F-M locus also greatly influences susceptibility to flesh bleeding, although the physiological mechanism for this disorder is unclear and may be controlled by a different gene closely linked to endoPG. Unlike mealiness, flesh bleeding occurred primarily in non-melting flesh fruit, particularly when the fruit is white-fleshed. Flesh browning incidence was greater in mealy fruit and was not associated with flesh bleeding. Breeding for CI resistance is thus a viable long-term strategy to reduce losses in the fresh and processed peach and nectarine industries. This study is an important first step to understanding genetic control of CI symptoms in peach.

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Section: Inheritance Of CI Symptomsmentioning

confidence: 99%

Section: Relationships Among Traitsmentioning

confidence: 99%

Influence of year and genetic factors on chilling injury susceptibility in peach (Prunus persica (L.) Batsch)

et al. 2011

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“…1) have been more scarce (Dirlewanger et al 2004(Dirlewanger et al , 2009aShulaev et al 2008;Peace and Norelli 2009). These molecular studies have been performed mainly in peach Pozzi and Vecchietti 2009), considered the model species; followed by almond (Martínez-Gómez et al 2007;Arús et al 2009), a very close species to peach; apricot (Folta and Gardiner 2009); cherry (Dirlewanger et al 2009b); and plum (Esmenjaud and Dirlewanger 2007).…”

Section: Introductionmentioning

confidence: 97%

New approaches to Prunus transcriptome analysis

et al. 2011

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The recent sequencing of the complete genome of the peach offers new opportunities for further transcriptomic studies in Prunus species in the called post-genomics era. First works on transcriptome analysis in Prunus species started in the early 2000s with the development of ESTs (expressed sequence tags) and the analysis of several candidate genes. Later, new strategies of massive analysis (high throughput) of transcriptomes have been applied, producing larger amounts of data in terms of expression of a large number of genes in a single experiment. One of these systems is massive transcriptome analysis using cDNA biochips (microarrays) to analyze thousands of genes by hybridization of mRNA labelled with fluorescence. However, the recent emergence of a massive sequencing methodology ("deep-sequencing") of the transcriptome (RNA-Seq), based on lowering the costs of DNA (in this cases complementary, cDNA) sequencing, could be more suitable than the application of microarrays. Recent papers have described the tremendous power of this technology, both in terms of profiling coverage and quantitative accuracy in transcriptomic studies. Now this technology is being applied to plant species, including Prunus. In this work, we analyze the potential in using this RNA-Seq technology in the study of Prunus transcriptomes and the development of genomic tools. In addition, the strengths and limitations of RNA-Seq relative to microarray profiling have been discussed.

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“…Determining the genetic basis of these traits is necessary to understand their genetic control and will provide necessary information to develop specific approaches to enhance breeding programs (Peace and Norelli 2009).…”

Section: Introductionmentioning

confidence: 99%

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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Genomics Approaches to Crop Improvement in the Rosaceae

Cited by 44 publications

References 104 publications

Influence of year and genetic factors on chilling injury susceptibility in peach (Prunus persica (L.) Batsch)

Influence of year and genetic factors on chilling injury susceptibility in peach (Prunus persica (L.) Batsch)

New approaches to Prunus transcriptome analysis

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

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