Differential expression levels of aroma-related genes during ripening of apricot (Prunus armeniaca L.)

González-Agüero, Mauricio; Troncoso, Sebastian Peña; Gudenschwager, Orianne; Campos-Vargas, Reinaldo; Moya-León, Marı́a Alejandra; Defilippi, Bruno G.

doi:10.1016/j.plaphy.2009.01.002

Cited by 73 publications

(62 citation statements)

References 32 publications

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“…In apricot, candidate genes have been assayed in the study of Plum pox virus (PPV) resistance including resistance gene analogs (RGA) (Dondini et al, 2004;Decroocq et al 2005;Lalli et al 2005), nucleotide binding site-leucine-rich repeat (NBS-LRR) (Soriano et al 2005), eukaryotic translation initiation factor (eIF4E), RNA helicase SDE3 (Cd93) and Argonaut AGO1 protein (Marandel et al 2009). In addition, several works have made possible the identification of candidate gene coding for enzymes involved in apricot ripening, such as ACC oxidase (Mbé-guié et al 1999); polyphenol oxidase (Chevalier et al 1999); enzymes involved in the softening process (Mbé-guié et al 2002); cell wall, sugar, lipid, organic acid, and protein metabolism (Geuna et al (2005) and enzymes involved in apricot aroma (González-Agüero et al 2009). …”

Section: Early Transcriptome Analysis Inmentioning

confidence: 99%

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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Section: Early Transcriptome Analysis Inmentioning

confidence: 99%

New approaches to Prunus transcriptome analysis

et al. 2011

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“…A lack of ethylene due to 1-MCP treatment (1-methylcyclopropen) was shown to result in a decrease in alcohols and esters (Fan et al 2000;Botondi et al 2003). A reduction in aldehyde and alcohol production in late-harvested fruit compared to early-harvested fruit was also reported by (Botondi et al 2003;González-Agüero et al 2009). Terpene levels are highest for medium late cultivars (Orangered, Velkopavlovická, Pincot, Silvercot and Leskora), where limonene, α-terpineol and β-ionone predominate.…”

Section: Differentiation Of Cultivars Using Aromatic Compoundsmentioning

confidence: 84%

“…The degree of ripeness affects the production of volatiles from a diverse range of chemical groups such as alcohols, aldehydes, esters, terpenes and lactones (Guillot et al 2006;Greger, Schieberle 2007;Gokbulut, Karabulut 2012). Variation in the production of aroma compounds was previously reported to vary with the choice of cultivars (Gurrieri et al 2001;Solís-Solís et al 2007;Lo Bianco et al 2010 ) and the stage of maturity (Aubert, Chanforan 2007;González-Agüero et al 2009;Aubert et al 2010). Important differences were found in the concentrations of lactones and terpenic alcohols (Goméz, Ledbetter 1997;Botondi et al 2003).…”

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confidence: 98%

Physico-chemical changes and volatile constituents observed in 10 apricot cultivars during post-harvest ripening

Goliáš

Létal²,

Dokoupil

et al. 2013

Hort. Sci. (Prague)

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Physico-chemical changes included a significant decrease in firmness during post-harvest ripening, whereas the levels of total soluble solids were found to be very similar. Ethylene as a parameter of ripening contributed to the resolution of cultivars in the over-ripe phase. On the other hand, fruit softening was not a useful parameter for distinguishing cultivars. 59 of volatiles were determined by the static headspace SPME gas chromatography with mass spectrometry and included 18 alcohols, 12 aldehydes, 10 esters, 11 terpenes, 5 lactones and 3 miscellaneous. Actually, the production of alcohols at ripe stage had almost been completed, since at the over-ripe stage they increased only slightly. Terpene levels were highest for the medium-late cultivars (Orangered, Velkopavlovická, Pinco, Silvercot and Leskora); they were predominantly limonene, α-terpineol and β-Ionone. The decrease in the concentration of terpenes in over-ripe fruit was statistically significant. There are six compounds (2-methylbutan-1-ol, 2-methylbutanal, n-hexylbutanoate, 3-methyl-3-methylbutyric acid, γ-caprolactone and γ-octalactone) which taken together can be used to distinguish the two different stages of maturity, ripe and over-ripe. The most abundant of these are γ-caprolactone and γ-octalactone, followed by 2-methylbutan-1-ol. If the volatiles from the cultivars used in this investigation are compared using cv. Bergeron as a standard, then only 10 are required to separate each variety at the over-ripe phase. Principal component analysis clearly separated the cvs Velkopavlovická and Bergeron from all the others, which probably reflects major differences in the production of volatiles and ethylene.Keywords: volatile compounds; ethylene; respiration rate; firmness; HP-SPME-GC-MS Optimum fruit quality depends upon a number of factors, including the fruit developmental stage at the point of harvest and the subsequent changes during the period of post-harvest maturation. Ripening to achieve optimum quality means that there must be good aroma development (Botondi et al.

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“…The results suggest that C4_PC3 identified 'kiwifruit fruit ripeness', which is probably a measure of the balance between different components of flavours and odours. The presence of this component may also suggest that AAT enzymes with ethanol may play a key role in the biosynthesis of ethyl esters (Ke et al 1994), and that alcohol dehydrogenase (ADH) and lipoxygenase (LOX) enzymes could play specific roles in the regulation of odour biosynthesis (Zhang et al 2009;González-Agüero et al 2009). Sequence analysis of acyltransferases (ATs) from the Actinidia EST database showed that two clades contained enzymes involved in the synthesis of flavour-related esters (Crowhurst et al 2008).…”

Section: 'Flavour Impact' Volatiles Of a Chinensis Fruitmentioning

confidence: 99%

“…López et al (1998) found that odour components varied in class and quantity in two apple cultivars and were associated with sensory properties characteristic of each cultivar. During fruit ripening, a number of different biosynthetic pathways are involved in volatile synthesis (Dixon and Hewett 2000;González-Agüero et al 2009;Zhang et al 2009). These have not been fully described, but appear to be common to different fruits (Dixon and Hewett 2000).…”

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confidence: 99%

Identifying volatile compounds associated with sensory and fruit attributes in diploid Actinidia chinensis (kiwifruit) using multivariate analysis

et al. 2011

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While the roles of sugars and acids in fruit flavour are well known and described, the roles of volatile compounds that contribute to flavour and odour are more difficult to define. The determination of volatiles that make a significant contribution to the flavour of kiwifruit (Actinidia chinensis) is essential for efficient and cost effective flavour breeding. The aims of this study were to explore associations between volatile compounds, sensory and fruit attributes of A. chinensis fruit and to identify potential key flavour impact volatiles, superior parents and selection methods, using multivariate analysis. We investigated the volatiles produced by ripe fruit of 24 genotypes selected by principal component analysis (PCA) to represent the diversity of taste and fruit characteristics in a breeding population. Seventy-two volatiles were detected. Extended use of multivariate analysis proved powerful for gaining maximum information from the limited plant material. The volatiles were successfully grouped into four clusters, using hierarchical clustering of variables based on phenotypic correlations between volatiles to avoid a singular correlation matrix in PCA. Based on these clusters, associations between volatiles, sensory and fruit attributes were explored using PCA and multiple linear regressions. Principal components provided a measure of the balance of complex volatiles that is likely to affect consumer responses. Thirteen potential key impact volatiles that made a substantial contribution to the flavour of A. chinensis fruit were identified. Five esters were strongly associated with the flavours and odours characteristic of 'Hort16A'. Volatiles associated with 'sour taste', 'fruit ripeness', 'atypical 'Hort16A'-like odour' and 'atypical kiwifruit flavour' were also recognized. Parents with potentially desirable volatile profiles and a possible selection method for flavour breeding were identified.

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Differential expression levels of aroma-related genes during ripening of apricot (Prunus armeniaca L.)

Cited by 73 publications

References 32 publications

New approaches to Prunus transcriptome analysis

New approaches to Prunus transcriptome analysis

Physico-chemical changes and volatile constituents observed in 10 apricot cultivars during post-harvest ripening

Identifying volatile compounds associated with sensory and fruit attributes in diploid Actinidia chinensis (kiwifruit) using multivariate analysis

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