Amy Watson

Summary: Trehalose 6-phosphate (T6P) signalling regulates carbon use and allocation and is a target to improve crop yields. However, the specific contributions of trehalose phosphate synthase (TPS) and trehalose phosphate phosphatase (TPP) genes to source- and sink-related traits remain largely unknown. We used exome-capture sequencing on TPS and TPP genes to estimate and partition the genetic variation of yield-related traits in a spring wheat ( Triticum aestivum ) breeding panel with diverse genetic heritage. Twelve phenotypes were directly correlated to TPS and TPP genes including final biomass (source) and spikes and grain numbers and grain filling traits (sink) showing indications of both positive and negative gene selection. Additionally, individual genes explained a substantial proportion of heritability (e.g. 3, 12, and 18% of the variance in gene homeologues most closely related to Arabidopsis TPS1 for final biomass), indicating a considerable contribution of this regulatory pathway to the phenotypic variation. Most importantly, two significant missense point mutations in the exon 6 of the TPS1 gene on chromosome 1D substantially increased plant height and peduncle length which was inversely related to grains per m ² . Gene-based prediction resulted in significant gains of predictive ability (6% improvement) for grain weight when gene effects were combined with the whole genome markers, potentially helping breeding programs in designing strategic crosses. Three TPS1 homeologues were particularly significant in trait variation. Our study has generated a wealth of information on the role of natural variation of TPS and TPP genes related to yield potential.

Genomic selection (GS) can be effective in breeding for quantitative traits, such as yield, by reducing the selection cycle duration. Speed breeding (SB) uses extended photoperiod and temperature control to enable rapid generation advancement. Together, GS and SB can synergistically reduce the breeding cycle by quickly producing recombinant inbred lines (RILs) and enabling indirect phenotypic selection to improve for key traits, such as height and flowering time, prior to field trials. In addition, traits measured under SB (SB traits) correlated with field‐based yield could improve yield prediction in multivariate GS. A 193‐line spring wheat (Triticum aestivum L.) training population (TP), tested for grain yield in the field in multiple environments, was used to predict grain yield of a 350‐line selection candidate (SC) population, across multiple environments. Four SB traits measured on the TP and SC populations were used to derive principal components, which were incorporated into multivariate GS models. Predictive ability was significantly increased by multivariate GS, in some cases being twice as high as univariate GS. Based on these results, an efficient breeding strategy is proposed combining SB and multivariate GS using yield‐correlated SB traits for yield prediction. The potential for early indirect SB phenotypic selection for targeted population improvement prior to trials was also investigated. Plant height and flowering time showed strong relative predicted efficiency to indirect selection, in some cases as high as direct field selection. The higher selection intensity and rate of generation turnover under SB may enable a greater rate of genetic gain than direct field phenotyping.