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A Solanum neorickii introgression population providing a powerful complement to the extensively characterized Solanum pennellii population | Plant Sciences and Genetics in Agriculture

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A Solanum neorickii introgression population providing a powerful complement to the extensively characterized Solanum pennellii population

Citation:

Brog, Y. M. ; Osorio, S. ; Yichie, Y. ; Alseekh, S. ; Bensal, E. ; Kochevenko, A. ; Zamir, D. ; Fernie, A. R. . A Solanum Neorickii Introgression Population Providing A Powerful Complement To The Extensively Characterized Solanum Pennellii Population. Plant Journal 2019, 97, 391-403.

Abstract:

We present a complementary resource for trait fine-mapping in tomato to those based on the intra-specific cross between cultivated tomato and the wild tomato species Solanum pennellii, which have been extensively used for quantitative genetics in tomato over the last 20 years. The current population of backcross inbred lines (BILs) is composed of 107 lines derived after three backcrosses of progeny of the wild species Solanum neorickii (LA2133) and cultivated tomato (cultivar TA209) and is freely available to the scientific community. These S. neorickii BILs were genotyped using the 10K SolCAP single nucleotide polymorphism chip, and 3111 polymorphic markers were used to map recombination break points relative to the physical map of Solanum lycopersicum. The BILs harbor on average 4.3 introgressions per line, with a mean introgression length of 34.7 Mbp, allowing partitioning of the genome into 340 bins and thereby facilitating rapid trait mapping. We demonstrate the power of using this resource in comparison with archival data from the S. pennellii resources by carrying out metabolic quantitative trait locus analysis following gas chromatography–mass spectrometry on fruits harvested from the S. neorickii BILs. The metabolic candidate genes phenylalanine ammonia-lyase and cystathionine gamma-lyase were then tested and validated in F 2 populations and via agroinfiltration-based overexpression in order to exemplify the fidelity of this method in identifying the genes that drive tomato metabolic phenotypes. © 2018 The Authors. The Plant Journal © 2018 John Wiley & Sons Ltd and Society for Experimental Biology.

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