Progeny testing of Pinus sylvestris L. of seed orchard in different environmental conditions

Evaluation of the progeny test of plus trees of Scots pine - a necessary condition for determining the prospects the use of improved seeds in different environmental conditions. The paper presents the results of the study of the progeny test of groups of clones of plus trees of Scots pine selected according to certain characteristics in Northern Steppe and South Forest-Steppe of Ukraine. Analysis of results showed: a significant improvement in the growth rates of the all testing progenies of seed orchard in the better climatic and soil conditions of South Forest-Steppe between the ages of 3 and 10 years. At the same time 4 out of 5 studied progenies worsened their growth indicators relative to local control at the age of 3 to 26 years in less optimal climatic and soil conditions of Northern Steppe. The leader in the steppe conditions was the progeny of a fraction of three clones, which had the highest seed productivity. The selection of the fastest growing clones and the rejection of the slowest growing ones had a positive effect on the growth of progenies of seed orchards at both test points.

Integrative QTL Identification, Fine Mapping and Candidate Gene Analysis of a Major Locus qLTG3a for Seed Low-Temperature Germinability in Rice

Low-temperature germinability (LTG) is an important agronomic trait that can affect the planting time, planting area, and grain yield of staple crops, such as rice. However, the genetic mechanism of LTG is still unclear. In this study, a multi-parental permanent population with 208 single segment substitution lines (SSSLs) was used to conduct a genetic dissection for LTG across four cropping seasons. LTG was a typical quantitative trait with a high combined broad-sense heritability of 0.71. By comparison with the recipient parent, Huajingxian74, 24 SSSLs were identified as carrying LTG QTLs, which were further merged into integrated QTLs with shorter genetic distances by substitution mapping. Finally, 14 LTG QTLs were mapped on ten chromosomes, including seven positive-effect and seven negative-effect QTLs, with additive effect contributions ranging from 19.2 to 39.9%. qLTG3a, a main-effect and novel QTL, was confirmed by bulk segregant analysis using an F2 segregating population, and five key recombinants were selected to develop F3 populations for progeny testing. Marker-trait association analysis fine mapped qLTG3a to a 332.7-kb physical region between markers M6026 and M6341. Within this interval, 40 annotated genes were revealed, and three genes (Os03g0213300, Os03g0214400, and Os03g0214600) were considered as pivotal candidate genes for qLTG3a based on their sequence variations and expression patterns. Besides low temperature, qLTG3a can also enhance seed germination under standard temperature and osmotic stress. In summary, this study identified some genetic factors regulating LTG and opened a new window for breeding elite direct-seeded rice varieties. It will help reduce the climate risk in the production process of rice, which is of great significance to ensuring food security.

284 Genetic Selection Through Ecofeed Index Reduces Carbon Footprint in Heifers

Efficient feed conversion by ruminants has a direct impact on the animal’s carbon footprint. The objective of this study was to determine the effect of using the EcoFeed® index by STgenetics® to reduce methane production. The EcoFeed® index is an integrated approach to genetic selection based on progeny testing of females for residual feed intake to identify animals who consume less feed while maintaining production compared to their herd mates to increase profitability and global sustainability. EcoFeed® is moderately heritable and uncorrelated with traits currently selected for in dairy cows. A dataset containing phenotypic and genomic information on 5,441 heifers was used for the analysis. Heifers were divided into low, medium and high EcoFeed® classes based on ±0.5 SD from the mean. To estimate methane emissions, 17 mathematical models were collated from the literature. All models were subjected to evaluation of performance using an independent dataset containing 458 individual-animal methane production measurements. The model recommended by Intergovernmental Panel for Climate Change had the lowest root mean square prediction error with 1% mean bias and 3.37% slope bias. This model was used to calculate emissions from low and high EcoFeed® heifers. In addition, an average of all model results was computed and used to compare different classes of heifers. Based on dietary information and feed intake, low and high EcoFeed® heifers were estimated to produce 194 and 164 g methane/d, respectively, using the selected model. Using model averages, the estimated methane production was 186 and 162 g methane/d, for low and high EcoFeed® heifers, respectively. The reduction in emission between low and high EcoFeed® classes was 12.6 to 15.4%. If savings from crop production were to be considered, there will be further reductions in the carbon footprint. Therefore, genomic selection is a powerful tool to reduce carbon footprint in ruminants.

Estimated Breeding Values of Beef Sires Can Predict Performance of Beef-Cross-Dairy Progeny

On average, half of the animal’s estimated breeding value (EBV) is passed on to their progeny. However, it is not known how the performance of beef-cross-dairy cattle relates to the EBV of their beef sire. Such information is required to determine the genetic potential of beef sires selected based on existing EBV to be used on dairy cows in New Zealand. This study evaluated the relationship between the EBV of 30 Angus and 34 Hereford sires and the performance of their progeny for birth, growth, and carcass traits, via progeny testing of 975 beef-cross-dairy offspring born to dairy cows and grown on hill country pasture. Overall, BREEDPLAN EBV did predict progeny performance of the beef-cross-dairy cattle from this study. Gestation length and birthweight increased with increasing sire EBV (mean 0.37–0.62days and 0.52–0.64kg, respectively, p<0.05). Age at weaning decreased with increasing sire EBV for liveweight at 200days (0.17–0.21days per extra kilo of sire EBV, p<0.05) but sire EBV for liveweight at 200days had no effect on the liveweight of the progeny at 200days for either breed (p>0.05). Liveweight increased with sire EBV for liveweight at 400, 600, and 800days, by a similar amount for both breeds (between 0.23 and 0.42kg increase in progeny liveweight per extra kilo of sire EBV, p<0.05). The relationships were more inconsistent for carcass traits. For Hereford, carcass weight and eye muscle area increased with increasing sire EBV (0.27kg and 0.70cm2, respectively, p<0.05). For Angus, marble score increased by 0.10 with 1% extra in sire EBV for intramuscular fat (p<0.05). Rib fat depth tended to increase with sire EBV for both breeds (p<0.1). EBV derived from beef-breed data work in dairy-beef systems but maybe slightly less than the expected 0.5units of performance per unit of EBV. New Zealand farmers should consider BREEDPLAN EBV when selecting sires to mate dairy cows or when buying beef-cross-dairy calves for beef production, to ensure the resulting calves are born safely and on time and then grow well to produce carcasses of suitable meat and fat composition.

Pedigree Reconstruction and Spatial Analysis for Genetic Testing and Selection In A Larix Kaempferi (Lamb.) Carrière Plantation

Background: Larix kaempferi is one of the major timber species in Northeast Asia. Demand for the reforestation of the species is rising in South Korea due to an increase in large timber production and utilization. However, progeny trials for the species have not been explored, making it challenging to foster advanced generations of tree improvement. In the present study, genetic testing and selection for diameter growth were conducted using pedigree reconstruction and phenotypic spatial distribution analysis in a plantation of L. kaempferi. The aim of the present study was to select the superior larch individuals using the pedigree reconstruction and phenotypic spatial distribution to substitute progeny trials. The plantation of seed orchard crops was established in 1990 and one-hundred and eighty-eight trees were selected as the study material. Genetic variation was investigated first to validate its adequacy as breeding material. Genetic testing was carried out using a model considering pedigree information and spatial autoregression of the phenotypes. The major environmental effects on growth were assessed to understand the site characteristics where the breeding materials were located.Results: The expected heterozygosity of the mother trees and offspring were 0.672 and 0.681 presenting the corresponding level of genetic variation between two groups. The pedigree reconstruction using maternity analysis assigned one to six progenies to ninety-two candidate mothers. The accuracy of genetic testing was exceedingly increased with the animal model considering AR1⊗AR1 structure compared to the animal model only. The estimated genetic variance of the former was 9.086 whereas that of the latter was 4.9E-5. The predicted breeding values of the offspring were ranged from -5.937 to 5.655 and the estimated heritability of diameter growth was 0.344. Shifts in the effects of the factors were detected using geographically weighted regression analysis, which provided information on the post-sectioning of the plantation. Conclusions: The genetic testing approach based on pedigree reconstruction and phenotypic spatial distribution analysis was considered a useful analytical scheme that could replace or supplement progeny trials. Subdivision of the plantation as blocks of the progeny testing was accomplished a posteriori based on the changes of the environmental effects.

Impact of early genomiC prediction for recurrent selection in AN upland rice synthetic population

Population breeding through recurrent selection is based on the repetition of evaluation and recombination among best-selected individuals. In this type of breeding strategy, early evaluation of selection candidates combined with genomic prediction could substantially shorten the breeding cycle length, thus increasing the rate of genetic gain. The objective of the present study was to optimize early genomic prediction in an upland rice (Oryza sativa L.) synthetic population improved through recurrent selection via shuttle breeding in two sites. To this end, we used genomic prediction on 334 S0 genotypes evaluated with early generation progeny testing (S0:2 and S0:3) across two sites. Four traits were measured (plant height, days to flowering, grain yield and grain zinc concentration) and the predictive ability was assessed for the target site. For days to flowering and plant height, which correlate well among sites (0.51–0.62), an increase of up to 0.4 in predictive ability was observed when the model was trained using the two sites. For grain zinc concentration, adding the phenotype of the predicted lines in the non-target site to the model improved the predictive ability (0.51 with two-site and 0.31 with single-site model), while for grain yield the gain was less (0.42 with two-site and 0.35 with single-site calibration). Through these results, we found a good opportunity to optimize the genomic recurrent selection scheme and maximize the use of resources by performing early progeny testing in two sites for traits with best expression and/or relevance in each specific environment.

Effect of Clonal Testing on the Efficiency of Genomic Evaluation in Forest Tree Breeding

Through stochastic simulations, accuracies of breeding values and response to selection were assessed under traditional pedigree- (BLUP) and genomic-based evaluation methods (GBLUP) in forest tree breeding. The latter provides a methodological foundation for genomic selection. We evaluated the impact of clonal replication in progeny testing on the response to selection realized in seed orchards under variable marker density and target effective population sizes. We found that clonal replication in progeny trials boosted selection accuracy, thus provided additional genetic gains under BLUP. While a similar trend was observed for GBLUP, however, the added gains did not surpass those under BLUP. Therefore, breeding programs deploying extensive progeny testing with clonal propagation might not benefit from the deployment of genomic information. These findings could be helpful in the context of operational breeding programs.

Genetic analysis and molecular mapping of Rp, a mutant gene encoding red pericarp in rice (Oryza sativa L.)

Coloured rice has pigments deposited in the grain pericarp; red rice is the most common type of coloured rice. Red rice is rich in essential nutrients and has been grown and consumed in China for a long time. In this study, we report the genetic characterisation and preliminary molecular mapping of a mutant gene encoding red pericarp in rice (Oryza sativa L.). To analyse the genetic basis of the red pericarp mutant, a reciprocal cross between GER-3 (red pericarp, indica cv.) and 898 (white pericarp, indica cv.) was made. The genetic analysis results confirmed that there was only one dominant gene, temporarily designated Rp (Red pericarp) controlling the segregation of the red pericarp in the F₂ population. For the molecular mapping of Rp, an F₂ population derived from an inter-subspecific cross between Gene Engineering Rice-3 (GER-3) and C418 (japonica cv., white pericarp) was constructed. The genotype of the pericarp colour of the F₂ individuals in the mapping population was validated by progeny testing of the F_2:3 families. Simple sequence repeat (SSR) markers and the bulked segregation analysis (BSA) method were used; Rp was mapped to the short arm of chromosome 7 between the SSR markers RM21182 and RM21268, with a genetic distance of 3.5 and 12.0 cM, respectively. In this paper, the potential origin of the red pericarp mutant gene Rp was also discussed.