Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement

Nicolas Schauer; Yaniv Semel; Ute Roessner; Amit Gur; Ilse Balbo; Fernando Carrari; Tzili Pleban; Alicia Perez-Melis; Claudia Bruedigam; Joachim Kopka; Lothar Willmitzer; Dani Zamir; Alisdair R. Fernie

doi:10.1038/nbt1192

Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement

Nicolas Schauer, Yaniv Semel, Ute Roessner, Amit Gur, Ilse Balbo, Fernando Carrari, Tzili Pleban, Alicia Perez-Melis, Claudia Bruedigam, Joachim Kopka, Lothar Willmitzer, Dani Zamir, Alisdair R. Fernie^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

643 Citations (Scopus)

Abstract

Tomato represents an important source of fiber and nutrients in the human diet and is a central model for the study of fruit biology. To identify components of fruit metabolic composition, here we have phenotyped tomato introgression lines (ILs) containing chromosome segments of a wild species in the genetic background of a cultivated variety. Using this high-diversity population, we identify 889 quantitative fruit metabolic loci and 326 loci that modify yield-associated traits. The mapping analysis indicates that at least 50% of the metabolic loci are associated with quantitative trait loci (QTLs) that modify whole-plant yield-associated traits. We generate a cartographic network based on correlation analysis that reveals whole-plant phenotype associated and independent metabolic associations, including links with metabolites of nutritional and organoleptic importance. The results of our genomic survey illustrate the power of genome-wide metabolic profiling and detailed morphological analysis for uncovering traits with potential for crop breeding.

Original language	English
Pages (from-to)	447-454
Number of pages	8
Journal	Nature Biotechnology
Volume	24
Issue number	4
DOIs	https://doi.org/10.1038/nbt1192
Publication status	Published - Apr 2006
Externally published	Yes

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title = "Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement",

abstract = "Tomato represents an important source of fiber and nutrients in the human diet and is a central model for the study of fruit biology. To identify components of fruit metabolic composition, here we have phenotyped tomato introgression lines (ILs) containing chromosome segments of a wild species in the genetic background of a cultivated variety. Using this high-diversity population, we identify 889 quantitative fruit metabolic loci and 326 loci that modify yield-associated traits. The mapping analysis indicates that at least 50% of the metabolic loci are associated with quantitative trait loci (QTLs) that modify whole-plant yield-associated traits. We generate a cartographic network based on correlation analysis that reveals whole-plant phenotype associated and independent metabolic associations, including links with metabolites of nutritional and organoleptic importance. The results of our genomic survey illustrate the power of genome-wide metabolic profiling and detailed morphological analysis for uncovering traits with potential for crop breeding.",

author = "Nicolas Schauer and Yaniv Semel and Ute Roessner and Amit Gur and Ilse Balbo and Fernando Carrari and Tzili Pleban and Alicia Perez-Melis and Claudia Bruedigam and Joachim Kopka and Lothar Willmitzer and Dani Zamir and Fernie, {Alisdair R.}",

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T1 - Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement

AU - Schauer, Nicolas

AU - Semel, Yaniv

AU - Roessner, Ute

AU - Gur, Amit

AU - Balbo, Ilse

AU - Carrari, Fernando

AU - Pleban, Tzili

AU - Perez-Melis, Alicia

AU - Bruedigam, Claudia

AU - Kopka, Joachim

AU - Willmitzer, Lothar

AU - Zamir, Dani

AU - Fernie, Alisdair R.

PY - 2006/4

Y1 - 2006/4

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AB - Tomato represents an important source of fiber and nutrients in the human diet and is a central model for the study of fruit biology. To identify components of fruit metabolic composition, here we have phenotyped tomato introgression lines (ILs) containing chromosome segments of a wild species in the genetic background of a cultivated variety. Using this high-diversity population, we identify 889 quantitative fruit metabolic loci and 326 loci that modify yield-associated traits. The mapping analysis indicates that at least 50% of the metabolic loci are associated with quantitative trait loci (QTLs) that modify whole-plant yield-associated traits. We generate a cartographic network based on correlation analysis that reveals whole-plant phenotype associated and independent metabolic associations, including links with metabolites of nutritional and organoleptic importance. The results of our genomic survey illustrate the power of genome-wide metabolic profiling and detailed morphological analysis for uncovering traits with potential for crop breeding.

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Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement

Abstract

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