Improvement of genomic prediction in advanced wheat breeding lines by including additive-by-additive epistasis

Key message Including additive and additive-by-additive epistasis in a NOIA parametrization did not yield orthogonal partitioning of genetic variances, nevertheless, it improved predictive ability in a leave-one-out cross-validation for wheat grain yield. Abstract Additive-by-additive epistasis is the principal non-additive genetic effect in inbred wheat lines and is potentially useful for developing cultivars based on total genetic merit; nevertheless, its practical benefits have been highly debated. In this article, we aimed to (i) evaluate the performance of models including additive and additive-by-additive epistatic effects for variance components (VC) estimation of grain yield in a wheat-breeding population, and (ii) to investigate whether including additive-by-additive epistasis in genomic prediction enhance wheat grain yield predictive ability (PA). In total, 2060 sixth-generation (F6) lines from Nordic Seed A/S breeding company were phenotyped in 21 year-location combinations in Denmark, and genotyped using a 15 K-Illumina-BeadChip. Three models were used to estimate VC and heritability at plot level: (i) “I-model” (baseline), (ii) “I + GA-model”, extending I-model with an additive genomic effect, and (iii) “I + GA + GAA-model”, extending I + GA-model with an additive-by-additive genomic effects. The I + GA-model and I + GA + GAA-model were based on the Natural and Orthogonal Interactions Approach (NOIA) parametrization. The I + GA + GAA-model failed to achieve orthogonal partition of genetic variances, as revealed by a change in estimated additive variance of I + GA-model when epistasis was included in the I + GA + GAA-model. The PA was studied using leave-one-line-out and leave-one-breeding-cycle-out cross-validations. The I + GA + GAA-model increased PA significantly (16.5%) compared to the I + GA-model in leave-one-line-out cross-validation. However, the improvement due to including epistasis was not observed in leave-one-breeding-cycle-out cross-validation. We conclude that epistatic models can be useful to enhance predictions of total genetic merit. However, even though we used the NOIA parameterization, the variance partition into orthogonal genetic effects was not possible.

Genetic Parameters for Growth, Ultrasound and Carcass Traits in New Zealand Beef Cattle and Their Correlations with Maternal Performance

Research has shown that enhancing finishing performance in beef cows is feasible; however, any adverse impact of selection strategies for finishing performance on the performance of the maternal herd should be taken into account. The aim of this research was to examine the inheritance of growth, ultrasound and carcass traits in finishing beef cattle and to evaluate their correlations with maternal performance traits. Data were collected from a nationwide progeny test on commercial New Zealand hill country farms comprising a total of 4473 beef cows and their progeny. Most finishing traits were moderately to highly heritable (0.28–0.58) with the exception of meat or fat colour and ossification (0.00–0.12). Ultrasound scan traits had high genetic correlations with corresponding traits measured at slaughter (rg = 0.53–0.95) and may be used as a selection tool for improved genetic merit of the beef carcass. Fat content determined via ultrasound scanning in the live animal or at slaughter in finishing cattle is positively genetically correlated with rebreeding performance (rg = 0.22–0.39) in female herd replacements and negatively correlated with mature cow live weight (rg = −0.40 to −0.19). Low-magnitude associations were observed between the genetic merit for carcass fat traits with body condition in mature cows.

Performance of lactating suckler cows of diverse genetic merit and genotype under a seasonal pasture-based system

The objective of this study was to investigate the effect of genetic merit of the national Irish maternal index and genotype (i.e. beef vs. beef × dairy [BDX]) of beef cows and subsequent performance of their progeny. With the exception that high genetic merit cows produced 0.57 kg more milk and tended to have 0.04 of a lower body condition score (BCS), no significant differences were observed between cows of diverse genetic merit. Differences between contrasting cow genotype were apparent. Beef cows were 50 kg heavier and had a BCS 0.27 greater than BDX cows. The BDX cows produced 1.67 kg more milk and had a greater 24-d submission rate than beef cows. Calves generated from BDX cows were 19 kg heavier at weaning and were worth €51 more than progeny generated from beef cows. Beef cow progeny, however, had 0.77 of a greater conformation score at slaughter than BDX. While differences were observed across cows of different replacement strategies, results from the current study showed that genetic selection for national maternal index had no effect on the overall performance of suckler cows in a pasture-based spring-calving system.

Dairy Producers Who Market Their Surplus Progeny as Calves Use Germplasm With Slightly Lighter and Less-Conformed Carcasses Than Producers Who Rear Their Surplus Progeny Beyond Weaning

Understanding dairy producer mindset in service sire selection can provide useful information for different junctures along the commercial and extension animal breeding chain. It can aid the targeted marketing of bulls based on farm production systems but also provide useful information for delivering bespoke extension services. The objective of the present study was to examine if differences exist among dairy producers in their choice of dairy and beef service sires depending on the life stage at which the surplus progeny generated from such matings exit the dairy farm. This was predominantly based on evaluating the breed of beef sires used but also their genetic merit for calving difficulty and carcass traits, namely, carcass weight, conformation, and fat score; differences in genetic merit among dairy sires as well as among the dairy cows themselves were also considered. The objective was accomplished through the cross-sectional analyses of progeny fate data from 1,092,403 progeny born in 4,117 Irish dairy herds. Herd-years were categorized into one of four systems based on when the surplus progeny exited the dairy farm: (1) calves sold <70 days of age, (2) cattle sold as yearlings between 250 and 450 days of age, (3) prime cattle sold for finishing (slaughtered between 8 and 120 days of exiting the dairy farm), or (4) prime cattle sold for immediate slaughter (i.e., slaughtered within 7 days of exiting the dairy farm). The mean genetic merit of both the cows and service sires used across the four different systems was estimated using linear mixed models. Of the beef service sires used in herds that sold their surplus progeny as calves, their mean predicted transmitting ability for carcass weight and carcass conformation score was just 2.00 kg and 0.11 scores [scale of 1 (poor) to 15 (excellent)] inferior to the beef service sires used in herds that sold their surplus progeny as prime cattle for immediate slaughter. Similar trends, albeit of smaller magnitude, were evident when comparing the genetic merit of the dairy service sires used in those systems. Cows in herds that sold their surplus progeny as calves were genetically less likely to incur dystocia as well as to have lighter, less-conformed, and leaner carcasses than cows in herds that sold their surplus progeny post-weaning. Hence, results from the present study suggest that diversity in herd strategy regarding when surplus progeny exit the herd influences service sire selection choices in respect of genetic merit for dystocia and carcass attributes. That said, the biological difference based on the current pool of available service sires is small relative to the dairy producers that sell their surplus progeny as young calves; when expressed on a per standard deviation in genetic merit of the beef service sires used across all herds, the difference between extreme systems was, nonetheless, approximately half a standard deviation for carcass weight and conformation.

26 Are Subjectively Scored Linear Type Traits Suitable Predictors of Genetic Merit for Feed Intake in Grazing Holstein-friesian Dairy Cows?

Measuring dry matter intake (DMI) in grazing dairy cows using currently available techniques is invasive, time consuming, and expensive. An alternative to directly measuring DMI for use in genetic evaluations is to identify a set of readily available data sources that can be used in a multi-trait genetic evaluation with DMI. The objectives of the present study were to estimate the genetic correlations between readily available body-related linear type trait information and DMI in grazing, lactating Irish dairy cows and to estimate the partial genetic correlations between linear traits and DMI, after adjusting for differences in genetic merit for body weight. After edits, a total of 8,055 test-day records of DMI, body weight, and milk yield from 1,331 multiparous dairy cows were available, as were chest width, body depth, and stature scores for 47,141 first lactation dairy cows. In addition to considering the routinely recorded linear type traits individually, novel traits were defined as the product of two or three linear type traits as an approximation of rumen volume. The genetic variance of DMI, body weight, milk yield, and linear type traits were estimated using univariate animal linear mixed models. Sire linear mixed models were used to calculate genetic and phenotypic covariances. All linear type traits were moderately heritable (0.27 to 0.49) and genetically correlated (0.29 to 0.63) with DMI. The genetic correlations between the individual linear type traits and DMI, when the latter was adjusted for differences in the genetic merit for body weight, varied from 0.00 to 0.39. If the (partial) genetic correlations were validated with genetic evaluations, routinely available linear type trait records and live weight data could facilitate the selection of DMI in dairy cows, removing the need to capture large amounts of cost prohibitive feed intake phenotypes.