Gene-based mapping of trehalose biosynthetic pathway genes reveals association with source- and sink-related yield traits in a spring wheat panel

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 enrichment 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 specifically built to capture the diversity across the 75,000 CIMMYT wheat cultivar collection. Twelve phenotypes were correlated to variation in TPS and TPP genes including plant height and biomass (source), spikelets per spike, spike growth and grain filling traits (sink) which showed indications of both positive and negative gene selection. Individual genes explained proportions of heritability for biomass and grain‐related traits. Three TPS1 homologues were particularly significant for trait variation. Epistatic interactions were found within and between the TPS and TPP gene families for both plant height and grain‐related traits. Gene‐based prediction improved predictive ability for grain weight when gene effects were combined with the whole‐genome markers. Our study has generated a wealth of information on natural variation of TPS and TPP genes related to yield potential which confirms the role for T6P in resource allocation and in affecting traits such as grain number and size confirming other studies which now opens up the possibility of harnessing natural genetic variation more widely to better understand the contribution of native genes to yield traits for incorporation into breeding programmes.

Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform

Genetic studies increasingly rely on high-throughput phenotyping, but the resulting longitudinal data pose analytical challenges. We used canopy height data from an automated field phenotyping platform to compare several approaches to scanning for quantitative trait loci (QTLs) and performing genomic prediction in a wheat recombinant inbred line mapping population based on up to 26 sampled time points (TPs). We detected four persistent QTLs (i.e. expressed for most of the growing season), with both empirical and simulation analyses demonstrating superior statistical power of detecting such QTLs through functional mapping approaches compared with conventional individual TP analyses. In contrast, even very simple individual TP approaches (e.g. interval mapping) had superior detection power for transient QTLs (i.e. expressed during very short periods). Using spline-smoothed phenotypic data resulted in improved genomic predictive abilities (5-8% higher than individual TP prediction), while the effect of including significant QTLs in prediction models was relatively minor (<1-4% improvement). Finally, although QTL detection power and predictive ability generally increased with the number of TPs analysed, gains beyond five or 10 TPs chosen based on phenological information had little practical significance. These results will inform the development of an integrated, semi-automated analytical pipeline, which will be more broadly applicable to similar data sets in wheat and other crops.

Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform

Genetic studies increasingly rely on high-throughput phenotyping, but the resulting longitudinal data pose analytical challenges. We used canopy height data from an automated field phenotyping platform to compare several approaches to scanning for quantitative trait loci (QTLs) and performing genomic prediction in a wheat recombinant inbred line mapping population based on up to 26 sampled time points (TPs). We detected four persistent QTLs (i.e. expressed for most of the growing season), with both empirical and simulation analyses demonstrating superior statistical power of detecting such QTLs through functional mapping approaches compared with conventional individual TP analyses. In contrast, even very simple individual TP approaches (e.g. interval mapping) had superior detection power for transient QTLs (i.e. expressed during very short periods). Using spline-smoothed phenotypic data resulted in improved genomic predictive abilities (5-8% higher than individual TP prediction), while the effect of including significant QTLs in prediction models was relatively minor (<1-4% improvement). Finally, although QTL detection power and predictive ability generally increased with the number of TPs analysed, gains beyond five or 10 TPs chosen based on phenological information had little practical significance. These results will inform the development of an integrated, semi-automated analytical pipeline, which will be more broadly applicable to similar data sets in wheat and other crops.

Combining abilities for agronomic traits and marker-assisted selection for Potato virus X and Potato virus Y resistance

Disease-resistant potato cultivars with good tuber appearance and desirable agronomic traits are essential for meeting the demands of producers and the market. Attaining these cultivars is the focus of potato breeding programs whose aim is to benefit the productive chain. The purpose of this study was to estimate combining abilities and evaluate potato clones based on tuber appearance, yield, and resistance to the PVY and PVX viruses. Crosses between four commercial cultivars of potato with good tuber appearance were performed, using eight clones with proven resistance to PVY and PVX from the breeding program of UFLA. The clones obtained were evaluated for agronomic traits, tuber appearance, and the presence of both Ry_adg and Rx1 alleles, which confer extreme resistance to the PVY and PVX viruses, respectively. The independent culling level method was used to select genotypes of commercial interest, as well as to estimate the combining abilities of the parents. We identified clones carrying the Ry_adg and Rx1 alleles with agronomic traits suitable for the fresh market and for processing. The BRS Ana cultivar and CMA-399 and CMA-385 clones showed positive effects on general combining ability (GCA) for tuber yield, while the Monalisa cultivar showed positive effects on GCA for general tuber appearance.

Genetic diversity and selection gain in the physic nut (Jatropha curcas)

The use of efficient breeding methods depends on knowledge of genetic control of traits to be improved. We estimated genetic parameters, selection gain, and genetic diversity in physic nut half-sib families, in order to provide information for breeding programs of this important biofuel species. The progeny test included 20 half-sib families in 4 blocks and 10 plants per plot. The mean progeny heritability values were: 50% for number of bunches, 47% for number of fruits, 35% for number of seeds, 6% for stem diameter, 26% for number of primary branches, 14% for number of secondary branches, 66% for plant height, and 25% for survival of the plants, demonstrating good potential for early selection in plant height, number of branches, and number of fruits per plant. In the analysis of genetic diversity, genotypes were divided into 4 groups. Genotypes 18, 19, 20, and 8 clustered together and presented the highest means for the vegetative and production. Lower means were observed in the 17, 12, 13, and 9 genotypes from the same group. We detected genetic variability in this population, with high heritability estimates and accuracy, demonstrating the possibility of obtaining genetic gains for vegetative characters and production at 24 months after planting.