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.

Combined correlation-based network and mQTL analyses efficiently identified loci for branched-chain amino acid, serine to threonine, and proline metabolism in tomato seeds.

Correlation-based network analysis (CNA) of the metabolic profiles of seeds of a tomato introgression line mapping population revealed a clique of proteinogenic amino acids: Gly, Ile, Pro, Ser, Thr, and Val. Correlations between profiles of these amino acids exhibited a statistically significant average correlation coefficient of 0.84 as compared with an average correlation coefficient of 0.39 over the 16 119 other metabolite cliques containing six metabolites. In silico removal of cliques was used to quantify their importance in determining seminal network properties, highlighting the strong effects of the amino acid clique. Quantitative trait locus analysis revealed co-localization for the six amino acids on chromosome 2, 4 and 10. Sequence analysis identified a unique set of 10 genes on chromosome 2 only, which were associated with amino acid metabolism and specifically the metabolism of Ser-Gly and their conversion into branched-chain amino acids. Metabolite profiling of a set of sublines, with introgressions on chromosome 2, identified a significant change in the abundance of the six amino acids in comparison with M82. Expression analysis of candidate genes affecting Ser metabolism matched the observation from the metabolite data, suggesting a coordinated behavior of the level of these amino acids at the genetic level. Analysis of transcription factor binding sites in the promoter regions of the identified genes suggested combinatorial response to light and the circadian clock.