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Advanced backcross QTL analysis in tomato. I. Identification of QTLs for traits of agronomic importance from Lycopersicon hirsutum

Authors :
D. Bernacchi
Dani Zamir
T. Beck-Bunn
J. Lopez
Yuval Eshed
Vincent Petiard
J. Uhlig
Steve Tanksley
Source :
Theoretical and Applied Genetics. 97:381-397
Publication Year :
1998
Publisher :
Springer Science and Business Media LLC, 1998.

Abstract

Advanced backcross QTL (AB-QTL) analysis is a new strategy for studying the effect of unadapted alleles on the agronomic performance of elite cultivated lines. In this paper we report results from the application of the AB-QTL strategy to cultivated tomato using the wild species Lycopersicon hirsutum LA1777 as the donor parent. RFLP genomic fingerprints were determined for 315 BC2 plants and phenotypic data were collected for 19 agronomic traits from approximately 200 derived BC3 lines which were grown in replicated field trials in three locations worldwide. Between 1 and 12 significant QTLs were identified for each of the 19 traits evaluated, with a total of 121 QTLs identified for all traits. For 25 of the QTLs (20%) corresponding to 12 traits (60%), the L. hirsutum allele was associated with an improvement of the trait from a horticultural perspective, despite the fact that L. hirsutum is overall phenotypically inferior to the elite parent. For example, L. hirsutum has fruit that remains green when ripe (lack of red pigment) yet alleles were found in this species that significantly increase red color when transferred into cultivated tomatoes. Wild alleles were also associated with increases in total yield and soluble solids (up to 15%) and brix×red yield (up to 41%). These results support the idea that one cannot predict the genetic potential of exotic germplasm based on phenotype alone and that marker-based methods, such as the AB-QTL strategy, should be applied to fully exploit exotic germplasm.

Details

ISSN :
14322242 and 00405752
Volume :
97
Database :
OpenAIRE
Journal :
Theoretical and Applied Genetics
Accession number :
edsair.doi...........3f365bcbb11c00f00837053677685087
Full Text :
https://doi.org/10.1007/s001220050908