Naturally occurring genetic variation in the universal florigen flowering pathway has produced major advancements in crop domestication. However, variants that can maximize crop yields may not exist in natural populations. Here we show that tomato productivity can be fine-tuned and optimized by exploiting combinations of selected mutations in multiple florigen pathway components. By screening for chemically induced mutations that suppress the bushy, determinate growth habit of field tomatoes, we isolated a new weak allele of the florigen gene SINGLE FLOWER TRUSS (SFT) and two mutations affecting a bZIP transcription factor component of the 'florigen activation complex' (ref. 11). By combining heterozygous mutations, we pinpointed an optimal balance of flowering signals, resulting in a new partially determinate architecture that translated to maximum yields. We propose that harnessing mutations in the florigen pathway to customize plant architecture and flower production offers a broad toolkit to boost crop productivity.

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 populations and via agroinfiltration-based overexpression in order to exemplify the fidelity of this method in identifying the genes that drive tomato metabolic phenotypes.