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Dani Zamir

Researcher at Hebrew University of Jerusalem

Publications -  158
Citations -  30225

Dani Zamir is an academic researcher from Hebrew University of Jerusalem. The author has contributed to research in topics: Quantitative trait locus & Lycopersicon. The author has an hindex of 76, co-authored 154 publications receiving 27712 citations. Previous affiliations of Dani Zamir include Weizmann Institute of Science & Cornell University.

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Less-than-additive epistatic interactions of quantitative trait loci in tomato.

TL;DR: It is proposed that the diminishing additivity of QTL effects is amplified when more loci are involved; this mode of epistasis may be an important factor in phenotype canalization and in breeding.
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The tomato genome sequence provides insights into fleshy fruit evolution

Shusei Sato, +323 more
- 31 May 2012 - 
TL;DR: A high-quality genome sequence of domesticated tomato is presented, a draft sequence of its closest wild relative, Solanum pimpinellifolium, is compared, and the two tomato genomes are compared to each other and to the potato genome.
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An introgression line population of Lycopersicon pennellii in the cultivated tomato enables the identification and fine mapping of yield-associated QTL

TL;DR: A novel population consisting of 50 introgression lines originating from a cross between the green-fruited species Lycopersicon pennellii and the cultivated tomato (cv M82) is presented, which provides complete coverage of the genome and a set of lines nearly isogenic to M82.
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Mendelian factors underlying quantitative traits in tomato: comparison across species, generations, and environments.

TL;DR: The results suggested that, for a trait with low heritability (soluble solids), the phenotype of F3 progeny could be predicted more accurately from the genotype of the F2 parent at QTLs than from the phenotypic variation of theF2 individual.
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Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement

TL;DR: 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 is generated.