A methodology framework for weighting genetic traits that impact greenhouse gas emission intensities in selection indexes.

A methodological framework was presented for deriving weightings to be applied in selection indexes to account for the impact genetic change in traits will have on greenhouse gas emissions intensities (EIs). Although the emission component of the breeding goal was defined as the ratio of total emissions relative to a weighted combination of farm outputs, the resulting trait-weighting factors can be applied as linear weightings in a way that augments any existing breeding objective before consideration of EI. Calculus was used to define the parameters and assumptions required to link each trait change to the expected changes in EI for an animal production system. Four key components were identified. The potential impact of the trait on relative numbers of emitting animals per breeding female first has a direct effect on emission output but, second, also has a dilution effect from the extra output associated with the extra animals. Third, each genetic trait can potentially change the amount of emissions generated per animal and, finally, the potential impact of the trait on product output is accounted for. Emission intensity weightings derived from this equation require further modifications to integrate them into an existing breeding objective. These include accounting for different timing and frequency of trait expressions as well as a weighting factor to determine the degree of selection emphasis that is diverted away from improving farm profitability in order to achieve gains in EI. The methodology was demonstrated using a simple application to dairy cattle breeding in Ireland to quantify gains in EI reduction from existing genetic trends in milk production as well as in fertility and survival traits. Most gains were identified as coming through the dilution effect of genetic increases in milk protein per cow, although gains from genetic improvements in survival by reducing emissions from herd replacements were also significant. Emission intensities in the Irish dairy industry were estimated to be reduced by ~5% in the last 10 years because of genetic trends in production, fertility and survival traits, and a further 15% reduction was projected over the next 15 years because of an observed acceleration of genetic trends.

Prediction of effects of beef selection indexes on greenhouse gas emissions.

Genetic improvement in production efficiency traits can also drive reduction in greenhouse gas emissions. This study used international 'best-practice' methodology to quantify the improvements in system-wide CO2 equivalent emissions per unit of genetic progress in the Irish Maternal Replacement (MR) and Terminal (T) beef cattle indexes. Effects of each index trait on system gross emissions (GE) and system emissions intensity (EI) were modelled by estimating effects of trait changes on per-animal feed consumption and associated methane production, per-animal meat production and numbers of animals in the system. Trait responses to index selection were predicted from linear regression of individual bull estimated breeding values for each index trait on their MR or T index value, and the resulting regression coefficients were used to calculate trait-wise responses in GE and EI from index selection. Summed over all trait responses, the MR index was predicted to reduce system GE by 0.810 kg CO2e/breeding cow per year per € index and system EI by 0.009 kg CO2e/kg meat per breeding cow per year per € index. These reductions were mainly driven by improvements in cow survival, reduced mature cow maintenance feed requirements, shorter calving interval and reduced offspring mortality. The T index was predicted to reduce system EI by 0.021 kg CO2e/kg meat per breeding cow per year per € index, driven by increased meat production from improvements in carcass weight, conformation and fat. Implications for incorporating an EI reduction index to the current production indexes and long-term projections for national breeding programs are discussed.

Comparative analysis of genetic parameters and quantitative trait loci for growth traits in Fraser strain Arctic charr (Salvelinus alpinus) reared in freshwater and brackish water environments.

To determine the potential for genetic improvement in Fraser strain Arctic charr (AC, Salvelinus alpinus), we calculated genetic parameters for BW and condition factor (K) and tested if previously identified QTL for these traits were detectable across a commercial broodstock reared in both freshwater (FRW) and brackish water (BRW). Individuals from 30 full-sib families were reared up to 29 mo of age in FRW and BRW tanks at a commercial facility. Heritability for BW and K was moderate in FRW (0.29 to 0.38) but lower in BRW (0.14 to 0.17). Genetic correlations for BW across environments were positive and moderate (0.33 to 0.67); however, equivalent K correlations were very weak (0.24 to 0.37). We identified a single BW QTL with experimentwide effects on linkage group AC-8, 4 BW QTL (AC-4, -13, -14, and -19), and 3 K QTL (AC-4, -5, and -20) with chromosomewide effects across families. Notably, the QTL on AC-8 had significant effects with BW at 3 out of 4 sampling dates in FRW and had significant allelic phase disequilibrium with BW across families, suggesting a tight coupling of the marker region to the QTL in this population. Body weight QTL were identified on AC-4 in both FRW and BRW environments and AC-4 was the only linkage group with a detectable QTL for both K and BW. Modest consistency of some QTL effects as well as moderate heritability in both environments suggests that there is some potential for genetic improvement of growth in this species even though gene × environment interactions are high.

Genetic analysis of survival and fitness in turkeys with multiple-trait animal models.

Genetic parameters for production, survival, and structural fitness traits recorded in pedigreed turkey sire and dam parental lines from a nucleus breeding program were estimated with multiple-trait animal models. Survival and conformation traits were scored in binary terms of health, where 0 = died or affected, and 1 = survived or healthy. Walking ability at 20 wk was subjectively scored from 1 (poor) to 6 (excellent). Body weights and egg production displayed moderate heritability (h(2) = 0.18 to 0.35). Early survival (to 3 wk) displayed low heritability (h(2) = 0.02 and 0.04 for the dam and sire lines, respectively). Late survival (3 to 23 wk) and longevity (age at death or cull) had low to moderate heritability (h(2) = 0.12 to 0.14). Walking ability had moderate heritability (h(2) = 0.26, 0.25). Leg structure health displayed low heritability (h(2) = 0.08), as did hip structure, foot, and skin health (h(2) ≤ 0.02). Crop health displayed moderate heritability (h(2) = 0.12). Walking ability, hip and leg structures, footpad, and breast skin health had negative genetic correlations with BW (r(G) = -0.50 to -0.23). Egg production had moderate positive genetic correlation with late survival (r(G) = 0.61). Genetic correlations between early and late survival were close to zero (r(G) = 0.10 and 0.03 for the dam and sire lines, respectively). Walking ability had high positive genetic correlations with late survival, longevity, hip structure, and leg structure in both lines (r(G) = 0.51 to 0.91). These genetic parameters indicate that unchecked selection for growth could decrease survival, walking ability, and hip, leg, footpad, and skin health in turkeys. However, index selection should be effective at improving fitness, survival, and growth simultaneously in commercial turkey lines. Walking ability should be a good indicator trait for selection to improve overall late survival and hip and leg health in turkeys.

Genetic relationships of body composition and feed utilization traits in European whitefish (Coregonus lavaretus L.) and implications for selective breeding in fishmeal- and soybean meal-based diet environments.

Body composition traits have potential use in fish breeding programs as indicator traits for selective improvement of feed efficiency. Moreover, feed companies are increasingly replacing traditional fish meal (FM) based ingredients in feeds for carnivorous farmed fish with plant protein ingredients. Therefore, genetic relationships of composition and feed utilization traits need to be quantified for both current FM-based and future plant-based aquaculture feeds. Individual whole-body lipid% and protein%, daily gain (DG), ADFI, and G:F (daily gain/daily feed intake) were measured on 1,505 European whitefish (Coregonus lavaretus) from 70 half/full-sib families reared in a split-family design with either a typical FM or a novel soybean meal (SBM) based diet. Diet-specific genetic parameters were estimated with multiple-trait animal models. Lipid% was significantly greater in the FM diet group than in the SBM group, even independent of final BW or total feed intake. In both diets, lipid% showed moderate heritability (0.12 to 0.22) and had positive phenotypic and genetic correlations with DG (0.37 to 0.82) and ADFI (0.36 to 0.88). Therefore, selection against lipid% can be used to indirectly select for lower feed intake. Protein% showed low heritability (0.05 to 0.07), and generally very weak or zero correlations with DG and ADFI. In contrast to many previous studies on terrestrial livestock, lipid% showed zero or very weak phenotypic and genetic correlations with G:F. However, selection index calculations demonstrated that simultaneous selection for high DG and reduced lipid% could be used to indirectly increase G:F; this strategy increased absolute genetic response in G:F by a factor of 1.5 to 1.6 compared with selection on DG alone. Lipid% and protein% were not greatly affected by genotype-diet environment interactions, and therefore, selection strategies for improving body composition within current FM diets should also improve populations for future SBM diets.