The effects of genotype-by-environment interactions on body condition score across three winter supplemental feed environments in a composite beef cattle breed in Montana.

Cattle operations in the Northern Great Plains region of the United States face extreme cold weather conditions and require nutritional supplementation over the winter season in order for animals to maintain body condition. In cow-calf operations, body condition scores (BCS) measured at calving and breeding have been shown to be associated with several economically important health and fertility traits, so maintenance of BCS is both an animal welfare and economic concern. A low-to-medium heritability has been found for BCS when measured across various production stages, indicating a large environmental influence but sufficient genetic basis for selection. The present study evaluated BCS measured prior to calving (late winter) and breeding (early summer) under three winter supplementation environments in a multitrait linear mixed model. Traits were discretized by winter supplementation and genetic correlations between environments were considered a reflection of evidence for genotype-by-environment interactions between BCS and diet. Winter supplementation treatments were fed October through April and varied by range access and protein content: 1) feedlot environment with approximately 15% crude protein (CP) corn/silage diet, 2) native rangeland access with 1.8 kg of an 18% CP pellet supplement, and 3) native rangeland access with a self-fed 50% CP and mineral supplement. A total of 2,988 and 2,353 records were collected across multiple parities on 1,010 and 800 individuals for prebreeding and precalving BCS, respectively. Heifers and cows came from a composite beef cattle breed developed and maintained by the USDA Fort Keogh Livestock and Range Research Laboratory near Miles City, Montana. Genetic correlations between treatments 1 and 2, 1 and 3, and 2 and 3 were 0.98, 0.78, and 0.65 and 1.00, 0.98, and 0.99 for precalving and prebreeding BCS, respectively. This provides moderate evidence of genotype-by-environment interactions for precalving BCS under treatment 3 relative to treatments 1 and 2, but no evidence for genotype-by-environment interactions for prebreeding BCS. Treatment 3 differed substantially in CP content relative to treatments 1 and 2, indicating that some animals differ in their ability to maintain BCS up to spring calving across a protein gradient. These results indicate the potential for selection of animals with increased resilience under cold weather conditions and high protein, restricted energy diets to maintain BCS.

Multienvironment genomic prediction in tetraploid potato.

Multienvironment genomic prediction was applied to tetraploid potato using 147 potato varieties, tested for 2 years, in 3 locations representative of 3 distinct regions in Europe. Different prediction scenarios were investigated to help breeders predict genotypic performance in the regions from one year to the next, for genotypes that were tested this year (scenario 1), as well as new genotypes (scenario 3). In scenario 2, we predicted new genotypes for any one of the 6 trials, using all the information that is available. The choice of prediction model required assessment of the variance-covariance matrix in a mixed model that takes into account heterogeneity of genetic variances and correlations. This was done for each analyzed trait (tuber weight, tuber length, and dry matter) where examples of both limited and higher degrees of heterogeneity was observed. This explains why dry matter did not need complex multienvironment modeling to combine environments and increase prediction ability, while prediction in tuber weight, improved only when models were flexible enough to capture the heterogeneous variances and covariances between environments. We also found that the prediction abilities in a target trial condition decreased, if trials with a low genetic correlation to the target were included when training the model. Genomic prediction in tetraploid potato can work once there is clarity about the prediction scenario, a suitable training set is created, and a multienvironment prediction model is chosen based on the patterns of G×E indicated by the genetic variances and covariances.

Evaluation of the Influence of Genetic and Environmental Factors on the Ephedrine Alkaloids Content of Ephedra sinica.

Ephedra herb, a dried terrestrial stem of Ephedra sinica, is used in traditional Japanese medicine (Kampo) and Chinese medicine to treat the common cold, headaches, bronchial asthma, and nasal inflammation. E. sinica predominantly contains two ephedrine alkaloids-(-)-ephedrine and (+)-pseudoephedrine-which are crucial for its medicinal effects. This study aimed to reveal the influence of genetic and environmental factors on ephedrine alkaloids content using statistical genetic analyses. To evaluate the influence of genetic factors on ephedrine alkaloids content, 25 clonal lines were cultivated in Ibaraki and the broad-sense heritability of the traits was estimated. The heritabilities of (-)-ephedrine, (+)-pseudoephedrine, and "total alkaloids" (TA) content were 0.871, 0.969, and 0.865, respectively. The heritabilities of ephedrine alkaloids content were high. To evaluate the influence of environmental factors on ephedrine alkaloids content, four clonal lines which have different genotypes were cultivated in three locations (Ibaraki, Shizuoka, and Yamanashi prefectures). The effects of genotype (G), location (L), and genotype by environment (G × E) interactions on ephedrine alkaloids content were found to be significant (p < 0.05) by two-way ANOVA, and, in particular, the genotypic effects were found to be the largest. Our results indicate that the ephedrine alkaloids content in E. sinica is under relatively strong genetic control and remains stable under various environments. These findings suggest that E. sinica with a higher and stable ephedrine alkaloids content could be cultivated in different locations through selective breeding.

Genomic selection for genotype performance and environmental stability in Coffea canephora.

Coffee is one of the most important beverages and trade products in the world. Among the multiple research initiatives focused on coffee sustainability, plant breeding provides the best means to increase phenotypic performance and release cultivars that could meet market demands. Since coffee is well adapted to a diversity of tropical environments, an important question for those confronting the problem of evaluating phenotypic performance is the relevance of genotype-by-environment interaction. As a perennial crop with a long juvenile phase, coffee is subjected to significant temporal and spatial variations. Such facts not only hinder the selection of promising materials but also cause a majority of complaints among growers. In this study, we hypothesized that trait stability in coffee is genetically controlled and therefore is predictable using molecular information. To test it, we used genome-based methods to predict stability metrics computed with the primary goal of selecting coffee genotypes that combine high phenotypic performance and stability for target environments. Using 2 populations of Coffea canephora, evaluated across multiple years and locations, our contribution is 3-fold: (1) first, we demonstrated that the number of harvest evaluations may be reduced leading to accelerated implementation of molecular breeding; (2) we showed that stability metrics are predictable; and finally, (3) both stable and high-performance genotypes can be simultaneously predicted and selected. While this research was carried out on representative environments for coffee production with substantial crossover in genotypic ranking, we anticipate that genomic prediction can be an efficient tool to select coffee genotypes that combine high performance and stability across years and the target locations here evaluated.

Genetic Dissection of Phosphorus Use Efficiency and Genotype-by-Environment Interaction in Maize.

Genotype-by-environment interaction (G-by-E) is a common but potentially problematic phenomenon in plant breeding. In this study, we investigated the genotypic performance and two measures of plasticity on a phenotypic and genetic level by assessing 234 maize doubled haploid lines from six populations for 15 traits in seven macro-environments with a focus on varying soil phosphorus levels. It was found intergenic regions contributed the most to the variation of phenotypic linear plasticity. For 15 traits, 124 and 31 quantitative trait loci (QTL) were identified for genotypic performance and phenotypic plasticity, respectively. Further, some genes associated with phosphorus use efficiency, such as Zm00001eb117170, Zm00001eb258520, and Zm00001eb265410, encode small ubiquitin-like modifier E3 ligase were identified. By significantly testing the main effect and G-by-E effect, 38 main QTL and 17 interaction QTL were identified, respectively, in which MQTL38 contained the gene Zm00001eb374120, and its effect was related to phosphorus concentration in the soil, the lower the concentration, the greater the effect. Differences in the size and sign of the QTL effect in multiple environments could account for G-by-E. At last, the superiority of G-by-E in genomic selection was observed. In summary, our findings will provide theoretical guidance for breeding P-efficient and broadly adaptable varieties.

Characterization of polyphenols in Australian sweet lupin (Lupinus angustifolius) seed coat by HPLC-DAD-ESI-MS/MS.

Seeds of the legume lupin (Lupinus spp.) are becoming increasingly important as human food. The seed coat, at ~25% of the whole seed of Lupinus angustifolius (Australian sweet lupin, ASL), is the main by-product of lupin kernel flour production. The primary market for lupin seed coat is low value feed with very limited use in foods. In this study, seed coats of six ASL commercial varieties from two growing sites were sampled for identification and quantification of polyphenols using a high-performance liquid chromatography (HPLC) with diode array detector (DAD) and coupled with a triple quadrupole mass spectrometer which equipped with electrospray ionization source (ESI-MS/MS). Three flavones (apigenin-7-O-ß-apiofuranosyl-6,8-di-C-ß-glucopyranoside, vicenin 2, and apigenin-7-O-ß-glucopyranoside), one isoflavone (genistein) and one dihydroflavonol derivative (aromadendrin-6-C-ß-d-glucopyranosyl-7-O-[ß-D-apiofuranosyl-(1 → 2)]-O-ß-D-glucopyranoside), and several hydroxybenzoic and hydroxycinnamic acid derivatives were identified. Considerable variations in levels of individual polyphenols were found but apigenin-7-O-ß-apiofuranosyl-6,8-di-C-ß-glucopyranoside was the predominant polyphenol in all samples accounting for 73.08-82.89% of the total free polyphenols. These results suggest that ASL seed coat could be valuable dietary source of polyphenols.