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Updated: Jun 16, 2026

Tomato Analyzer: A Useful Software Application to Collect Accurate and Detailed Morphological and Colorimetric Data from Two-dimensional Objects
Published on: March 16, 2010
Genomic analysis of wild tomato introgressions determining metabolism- and yield-associated traits
Laura Kamenetzky1, Ramón Asís, Sebastián Bassi
1Instituto de Biotecnología, Instituto Nacional de Tecnología Agropecuaría, and Consejo Nacional de Investigaciones Científicas y Técnicas, B1712WAA Castelar, Argentina.
Abstract:
With the aim of determining the genetic basis of metabolic regulation in tomato fruit, we constructed a detailed physical map of genomic regions spanning previously described metabolic quantitative trait loci of a Solanum pennellii introgression line population. Two genomic libraries from S. pennellii were screened with 104 colocated markers from five selected genomic regions, and a total of 614 bacterial artificial chromosome (BAC)/cosmids were identified as seed clones. Integration of sequence data with the genetic and physical maps of Solanum lycopersicum facilitated the anchoring of 374 of these BAC/cosmid clones. The analysis of this information resulted in a genome-wide map of a nondomesticated plant species and covers 10% of the physical distance of the selected regions corresponding to approximately 1% of the wild tomato genome. Comparative analyses revealed that S. pennellii and domesticated tomato genomes can be considered as largely colinear. A total of 1,238,705 bp from both BAC/cosmid ends and nine large insert clones were sequenced, annotated, and functionally categorized. The sequence data allowed the evaluation of the level of polymorphism between the wild and cultivated tomato species. An exhaustive microsynteny analysis allowed us to estimate the divergence date of S. pennellii and S. lycopersicum at 2.7 million years ago. The combined results serve as a reference for comparative studies both at the macrosyntenic and microsyntenic levels. They also provide a valuable tool for fine-mapping of quantitative trait loci in tomato. Furthermore, they will contribute to a deeper understanding of the regulatory factors underpinning metabolism and hence defining crop chemical composition.
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