A New Advanced Backcross Tomato Population Enables High Resolution Leaf QTL Mapping and Gene Identification.

Quantitative Trait Loci (QTL) mapping is a powerful technique for dissecting the genetic basis of traits and species differences. Established tomato mapping populations between domesticated tomato (Solanum lycopersicum) and its more distant interfertile relatives typically follow a near isogenic line (NIL) design, such as the S. pennellii Introgression Line (IL) population, with a single wild introgression per line in an otherwise domesticated genetic background. Here, we report on a new advanced backcross QTL mapping resource for tomato, derived from a cross between the M82 tomato cultivar and S. pennellii This so-called Backcrossed Inbred Line (BIL) population is comprised of a mix of BC2 and BC3 lines, with domesticated tomato as the recurrent parent. The BIL population is complementary to the existing S. pennellii IL population, with which it shares parents. Using the BILs, we mapped traits for leaf complexity, leaflet shape, and flowering time. We demonstrate the utility of the BILs for fine-mapping QTL, particularly QTL initially mapped in the ILs, by fine-mapping several QTL to single or few candidate genes. Moreover, we confirm the value of a backcrossed population with multiple introgressions per line, such as the BILs, for epistatic QTL mapping. Our work was further enabled by the development of our own statistical inference and visualization tools, namely a heterogeneous hidden Markov model for genotyping the lines, and by using state-of-the-art sparse regression techniques for QTL mapping

Quantitative trait loci analysis of seed-specialized metabolites reveals seed-specific flavonols and differential regulation of glycoalkaloid content in tomato

Given the potential health benefits (and adverse effects), of polyphenolic and steroidal glycoalkaloids in the diet there is a growing interest in fully elucidating the genetic control of their levels in foodstuffs. Here we carried out profiling of the specialized metabolites in the seeds of the Solanum pennellii introgression lines identifying 338 putative metabolite quantitative trait loci (mQTL) for flavonoids, steroidal glycoalkaloids and further specialized metabolites. Two putative mQTL for flavonols and one for steroidal glycoalkaloids were cross-validated by evaluation of the metabolite content of recombinants harboring smaller introgression in the corresponding QTL interval or by analysis of lines from an independently derived backcross inbred line population. The steroidal glycoalkaloid mQTL was localized to a chromosomal region spanning 14 genes, including a previously defined steroidal glycoalkaloid gene cluster. The flavonoid mQTL was further vali dated via the use of transient and stable overexpression of the Solyc12g098600 and Solyc12g096870 genes, which encode seed-specific uridine 50 -diphosphate-glycosyltransferases. The results are discussed in the context of our understanding of the accumulation of polyphenols and steroidal glycoalkaloids, and how this knowledge may be incorporated into breeding strategies aimed at improving nutritional aspects of plants as well as in fortifying them against abiotic stress

Canalization of Tomato Fruit Metabolism

To explore the genetic robustness (canalization) of metabolism, we examined the levels of fruit metabolites in multiple harvests of a tomato introgression line (IL) population. The IL partitions the whole genome of the wild species Solanum pennellii in the background of the cultivated tomato (Solanum lycopersicum). We identified several metabolite quantitative trait loci that reduce variability for both primary and secondary metabolites, which we named canalization metabolite quantitative trait loci (cmQTL). We validated nine cmQTL using an independent population of backcross inbred lines, derived from the same parents, which allows increased resolution in mapping the QTL previously identified in the ILs. These cmQTL showed little overlap with QTL for the metabolite levels themselves. Moreover, the intervals they mapped to harbored few metabolism-associated genes, suggesting that the canalization of metabolism is largely controlled by regulatory genes