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Use of network analysis to capture key traits affecting tomato organoleptic quality.

ABSTRACT: The long-term objective of tomato breeders is to identify metabolites that contribute to defining the target flavour and to design strategies to enhance it. This paper reports the results of network analysis, based on metabolic phenotypic and sensory data, to highlight important relationships among such traits. This tool allowed a reduction in data set complexity, building a network consisting of 35 nodes and 74 links corresponding to the 74 significant (positive or negative) correlations among the variables studied. A number of links among traits contributing to fruit organoleptic quality and to the perception of sensory attributes were identified. Modular partitioning of the characteristics involved in fruit organoleptic perception captured the essential fruit parameters that regulate interactions among different class traits. The main feature of the network was the presence of three nodes interconnected among themselves (dry matter, pH, and degrees Brix) and with other traits, and nodes with widely different linkage degrees. Identification of strong associations between some metabolic and sensory traits, such as citric acid with tomato smell, glycine with tomato smell, and granulosity with dry matter, suggests a basis for more targeted investigations in the future.

SUBMITTER: Carli P

PROVIDER: S-EPMC2724691 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Use of network analysis to capture key traits affecting tomato organoleptic quality.

Carli Paola P Arima Serena S Fogliano Vincenzo V Tardella Luca L Frusciante Luigi L Ercolano Maria R MR

Journal of experimental botany 20090610 12

The long-term objective of tomato breeders is to identify metabolites that contribute to defining the target flavour and to design strategies to enhance it. This paper reports the results of network analysis, based on metabolic phenotypic and sensory data, to highlight important relationships among such traits. This tool allowed a reduction in data set complexity, building a network consisting of 35 nodes and 74 links corresponding to the 74 significant (positive or negative) correlations among ...[more]

PMID: 19516072

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Project description:Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits.

Project description:Identification of tomato varieties able to exhibit higher accumulation of primary and secondary metabolites in their fruits is currently a main objective in tomato breeding. One tool to improve fruit quality is to cultivate the plants under salt stress, although improvement of fruit quality is generally accompanied by productivity losses. However, it is very interesting to implement strategies aiming at enhancing fruit quality of tomato by means of growing plants in moderate salt stress that allows for a sustainable fruit yield. The traditional tomato varieties adapted to the Mediterranean environmental constraints may be very attractive plant materials to achieve this goal, given the wide range of fruit quality traits because of their genetic diversity. Here, agronomic responses and fruit quality traits, including primary and secondary metabolites, were analyzed in fruits of two Mediterranean traditional tomato varieties named "Tomate Pimiento" ("TP") and "Muchamiel Aperado" ("MA") because of the pepper and pear shape of their fruits, using as reference the commercial cultivar "Moneymaker" ("MM"). Plants were grown without salt (control) and with moderate salt stress (50 mM NaCl), which did not affect fruit yield in any variety. "TP" is of great interest because of its high soluble solids content (SSC) in control, which is even higher in salt, whereas "MA" is very attractive because of its high Brix yield index (SSC × fruit yield), used as overall fruit quality measure. Similitude between both traditional varieties were found for primary metabolism, as they significantly increased sucrose contents compared with "MM" in red ripe fruits from plants in control and, especially, salt stress conditions. The most remarkable difference was the high constitutive levels of total amino acids in "TP" fruits, including the three major free amino acids found in tomato fruit, GABA, glutamate, and glutamine, which even increased under salinity. Regarding secondary metabolites, the most interesting change induced by salinity was the increase in α-tocopherol found in red ripe fruits of both "TP" and "MA." These results reveal the interest of traditional varieties as sources of genetic variation in breeding because of their improvement of tomato fruit quality without production losses under moderate salt stress.

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Use of network analysis to capture key traits affecting tomato organoleptic quality.

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Use of network analysis to capture key traits affecting tomato organoleptic quality.

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