Bayesian estimation of genetic variance and response to selection on linear or ratio traits of feed efficiency in dairy cattle.

This study aimed to estimate genetic parameters of the linear trait genetic residual feed intake (RFI) and the ratio traits feed conversion ratio (FCR) and feed conversion efficiency (FCE) along with dry matter intake (DMI) and energy sink traits such as energy-corrected milk (ECM), body weight (BW), body condition score (BCS), and BW change (BWC) across different weeks in the first lactation of Danish Holstein cows. A second objective was to conduct a Bayesian analysis of direct and correlated superiority of the selected group when selecting on genetic RFI, FCR, or FCE. Feed intake and energy sink traits were recorded during wk 1 to 44 of lactation on 847 primiparous Danish Holstein cows. A Bayesian multivariate random regression animal model was used to analyze DMI, ECM, BW, and BCS in different weeks of lactation. Genetic RFI was obtained by conditioning DMI on ECM, BW, BCS, and BWC using genetic partial regression coefficients. The posterior distribution of the breeding values for FCR and FCE was derived from the posterior distribution of functions of "fixed" environmental effects and random additive genetic effects on DMI and ECM. Genetic superiority of the selected group was defined as the difference in additive genetic mean of the selected top individuals expected to be potential parents, and the total population after integrating genetic trends out of the posterior distribution of selection responses. Posterior means of heritability of genetic RFI ranged from 0.10 to 0.15, genetic variance of FCR and FCE ranged from 2.13 × 10-3 to 3.2 × 10-3 (kg2 DMI/kg2 ECM) and 6.11 × 10-3 to 2.4 × 10-2 (kg2 ECM/kg2 DMI), respectively. Selection against RFI showed a direct response of -1.01 to -2.23 kg/d RFI and correlated responses of -0.031 to -0.056 kg/kg for FCR, 0.104 to 0.160 kg/kg for FCE, and -0.316 to -1.057 kg/d for DMI in different weeks of lactation. Selection against RFI had no significant effect on production traits but selection for ratio traits reduced BW and BCS. Posterior means of genetic correlation between DMI and ratio traits were low. In conclusion, the Bayesian procedure allowed us to estimate genetic RFI without the need for separate multiple regression analysis and considered the non-normal posterior distribution of ratio traits. Selection against genetic RFI might be an effective means to improve feed efficiency compared with ratio traits for feed efficiency in dairy cattle.

Combined analysis of group recorded feed intake and individually recorded body weight and litter size in mink.

In the mink industry, feed costs are the largest variable expense and breeding for feed efficient animals is warranted. Implementation of selection for feed efficiency must consider the relationships between feed efficiency and the current selection traits BW and litter size. Often, feed intake (FI) is recorded on a cage with a male and a female and there is sexual dimorphism that needs to be accounted for. Study aims were to (1) model group recorded FI accounting for sexual dimorphism, (2) derive genetic residual feed intake (RFI) as a measure of feed efficiency, (3) examine the relationship between feed efficiency and BW in males (BWM) and females (BWF) and litter size at day 21 after whelping (LS21) in Danish brown mink and (4) investigate direct and correlated response to selection on each trait of interest. Feed intake records from 9574 cages, BW records on 16 782 males and 16 875 females and LS21 records on 6446 yearling females were used for analysis. Genetic parameters for FI, BWM, BWF and LS21 were obtained using a multivariate animal model, yielding sex-specific additive genetic variances for FI and BW to account for sexual dimorphism. The analysis was performed in a Bayesian setting using Gibbs sampling, and genetic RFI was obtained from the conditional distribution of FI given BW using genetic regression coefficients. Responses to single trait selection were defined as the posterior distribution of genetic superiority of the top 10% of animals after conditioning on the genetic trends. The heritabilities ranged from 0.13 for RFI in females and LS21 to 0.59 for BWF. Genetic correlations between BW in both sexes and LS21 and FI in both sexes were unfavorable, and single trait selection on BW in either sex showed increased FI in both sexes and reduced litter size. Due to the definition of RFI and high genetic correlation between BWM and BWF, selection on RFI did not significantly alter BW. In addition, selection on RFI in either sex did not affect LS21. Genetic correlation between sexes for FI and BW was high but significantly lower than unity. The high correlations across sex allowed for selection on standardized averages of animals' breeding values (BVs) for RFI, FI and BW, which yielded selection responses approximately equal to the responses obtained using the sex-specific BVs. The results illustrate the possibility of selecting against RFI in mink with no negative effects on BW and litter size.

Genome-wide pleiotropy and shared biological pathways for resistance to bovine pathogens.

Host genetic architecture is a major factor in resistance to pathogens and parasites. The collection and analysis of sufficient data on both disease resistance and host genetics has, however, been a major obstacle to dissection the genetics of resistance to single or multiple pathogens. A severe challenge in the estimation of heritabilities and genetic correlations from pedigree-based studies has been the confounding effects of the common environment shared among relatives which are difficult to model in pedigree analyses, especially for health traits with low incidence rates. To circumvent this problem we used genome-wide single-nucleotide polymorphism data and implemented the Genomic-Restricted Maximum Likelihood (G-REML) method to estimate the heritabilities and genetic correlations for resistance to 23 different infectious pathogens in calves and cows in populations undergoing natural pathogen challenge. Furthermore, we conducted gene-based analysis and generalized gene-set analysis to understand the biological background of resistance to infectious diseases. The results showed relatively higher heritabilities of resistance in calves than in cows and significant pleiotropy (both positive and negative) among some calf and cow resistance traits. We also found significant pleiotropy between resistance and performance in both calves and cows. Finally, we confirmed the role of the B-lymphocyte pathway as one of the most important biological pathways associated with resistance to all pathogens. These results both illustrate the potential power of these approaches to illuminate the genetics of pathogen resistance in cattle and provide foundational information for future genomic selection aimed at improving the overall production fitness of cattle.

Joint analysis of longitudinal feed intake and single recorded production traits in pigs using a novel Horizontal model.

A novel Horizontal model is presented for multitrait analysis of longitudinal traits through random regression analysis combined with single recorded traits. Weekly ADFI on test for Danish Duroc, Landrace, and Yorkshire boars were available from the national test station and were collected from 30 to 100 kg BW. Single recorded production traits of ADG from birth to 30 kg BW (ADG30), ADG from 30 to 100 kg BW (ADG100), and lean meat percentage (LMP) were available from breeding herds or the national test station. The Horizontal model combined random regression analysis of feed intake (FI) with single recorded traits of ADG100, LMP, and ADG30. In the Horizontal model, the FI data were horizontally structured with FI on each week as a "trait." The additive genetic and litter effects were modeled to be common across different FI records by reducing the rank of the covariance matrices using second- and first-order Legendre polynomials of age on test, respectively. The fixed effect and random residual variance were estimated for each weekly FI trait. Residual feed intake (RFI) was derived from the conditional distribution of FI given the breeding values of ADG100 and LMP. The heritability of FI varied by week on test in Duroc (0.12 to 0.19), Landrace (0.13 to 0.22), and Yorkshire (0.21 to 0.23). The heritability of RFI was lowest and highest in wk 6 (0.03) and 10 (0.10), respectively, in Duroc and wk 7 (0.04 and 0.02) and 1 (0.09 and 0.20), respectively, in Landrace and Yorkshire. The proportion of FI genetic variance explained by RFI ranged from 20 to 75% in Duroc, from 19 to 75% in Landrace, and from 11 to 91% in Yorkshire. Average daily gain from 30 to 100 kg BW and ADG30 heritabilities were moderate in Duroc (0.24 and 0.22, respectively), Landrace (0.34 and 0.25, respectively), and Yorkshire (0.34 and 0.22, respectively). Lean meat percentage heritability was moderate in Duroc (0.37) and large in Landrace (0.62) and Yorkshire (0.60). The genetic correlation of FI with ADG100 increased by week on test followed by a 32% decrease from wk 7 in Duroc and a 7% decrease in dam line breeds. Defining RFI as genetically independent of production traits leads to consistent and easy interpretable breeding values. The genetic parameters of traits in the feed efficiency complex and their dynamics over the test period showed breed differences that could be related to the fatness and growth potential of the breeds. The Horizontal model can be used to simultaneously analyze repeated and single recorded traits through proper modeling of the environmental variances and covariances.

Regional heritability mapping method helps explain missing heritability of blood lipid traits in isolated populations.

Single single-nucleotide polymorphism (SNP) genome-wide association studies (SSGWAS) may fail to identify loci with modest effects on a trait. The recently developed regional heritability mapping (RHM) method can potentially identify such loci. In this study, RHM was compared with the SSGWAS for blood lipid traits (high-density lipoprotein (HDL), low-density lipoprotein (LDL), plasma concentrations of total cholesterol (TC) and triglycerides (TG)). Data comprised 2246 adults from isolated populations genotyped using ∼300 000 SNP arrays. The results were compared with large meta-analyses of these traits for validation. Using RHM, two significant regions affecting HDL on chromosomes 15 and 16 and one affecting LDL on chromosome 19 were identified. These regions covered the most significant SNPs associated with HDL and LDL from the meta-analysis. The chromosome 19 region was identified in our data despite the fact that the most significant SNP in the meta-analysis (or any SNP tagging it) was not genotyped in our SNP array. The SSGWAS identified one SNP associated with HDL on chromosome 16 (the top meta-analysis SNP) and one on chromosome 10 (not reported by RHM or in the meta-analysis and hence possibly a false positive association). The results further confirm that RHM can have better power than SSGWAS in detecting causal regions including regions containing crucial ungenotyped variants. This study suggests that RHM can be a useful tool to explain some of the 'missing heritability' of complex trait variation.

Longitudinal analysis of residual feed intake and BW in mink using random regression with heterogeneous residual variance.

The aim of this study was to determine the genetic background of longitudinal residual feed intake (RFI) and BW gain in farmed mink using random regression methods considering heterogeneous residual variances. The individual BW was measured every 3 weeks from 63 to 210 days of age for 2139 male+female pairs of juvenile mink during the growing-furring period. Cumulative feed intake was calculated six times with 3-week intervals based on daily feed consumption between weighing's from 105 to 210 days of age. Genetic parameters for RFI and BW gain in males and females were obtained using univariate random regression with Legendre polynomials containing an animal genetic effect and permanent environmental effect of litter along with heterogeneous residual variances. Heritability estimates for RFI increased with age from 0.18 (0.03, posterior standard deviation (PSD)) at 105 days of age to 0.49 (0.03, PSD) and 0.46 (0.03, PSD) at 210 days of age in male and female mink, respectively. The heritability estimates for BW gain increased with age and had moderate to high range for males (0.33 (0.02, PSD) to 0.84 (0.02, PSD)) and females (0.35 (0.03, PSD) to 0.85 (0.02, PSD)). RFI estimates during the growing period (105 to 126 days of age) showed high positive genetic correlations with the pelting RFI (210 days of age) in male (0.86 to 0.97) and female (0.92 to 0.98). However, phenotypic correlations were lower from 0.47 to 0.76 in males and 0.61 to 0.75 in females. Furthermore, BW records in the growing period (63 to 126 days of age) had moderate (male: 0.39, female: 0.53) to high (male: 0.87, female: 0.94) genetic correlations with pelting BW (210 days of age). The result of current study showed that RFI and BW in mink are highly heritable, especially at the late furring period, suggesting potential for large genetic gains for these traits. The genetic correlations suggested that substantial genetic gain can be obtained by only considering the RFI estimate and BW at pelting, however, lower genetic correlations than unity indicate that extra genetic gain can be obtained by including estimates of these traits during the growing period. This study suggests random regression methods are suitable for analysing feed efficiency and BW gain; and genetic selection for RFI in mink is promising.

Nitrogen excretion at different stages of growth and its association with production traits in growing pigs.

The objectives of this study were to determine nitrogen loss at different stages of growth and during the entire growing period and to investigate the associations between nitrogen excretion and production traits in growing pigs. Data from 315 pigs of an F(2) population which originated from crossing Pietrain sires with a commercial dam line were used. Nitrogen retention was derived from protein retention as measured using the deuterium dilution technique during different stages of growth (60 to 90 kg, 90 to 120 kg, and 120 to 140 kg). Pigs were fed ad libitum with 2 pelleted diets containing 17% (60 to 90 kg) and 16.5% (90 to 120 and 120 to 140 kg) CP. Average daily nitrogen excretion (ADNE) within each stage of growth was calculated on the basis of the accumulated difference between average daily nitrogen intake (ADNI) and average daily nitrogen retention (ADNR). Least ADNE, nitrogen excretion per BW gain (NEWG) and total nitrogen excretion (TNE) were observed during growth from 60 to 90 kg. In contrast, the greatest ADNE, NEWG, and TNE were found during growth from 120 to 140 kg. Statistical analyses indicated that gender, housing type, the ryanodine receptor 1 (RYR1) gene, and batch influenced nitrogen excretion (P < 0.05), but the degree and direction of influences differed between growth stages. Gender differences showed that gilts excreted less nitrogen than barrows (P < 0.05), which was associated with decreased feed conversion ratio (FCR; feed:gain) and lipid:protein gain ratio. Single-housed pigs showed reduced nitrogen excretion compared with group-housed pigs (P < 0.05). In comparison to other genotypes, pigs carrying genotype NN (homozygous normal) at the RYR1 locus had the least nitrogen excretion (P < 0.05) at all stages of growth except from 60 to 90 kg. The residual correlations indicated that NEWG and TNE have large positive correlations with FCR (r = 0.99 and 0.91, respectively) and moderate negative correlations with ADG (r = -0.53 and -0.48, respectively), for the entire growing period. Improvement in FCR, increase in ADG and reduction in lipid:protein gain ratio by 1 phenotypic SD reduced TNE per pig by 709 g, 307 g, and 211 g, respectively, over the entire growing period. The results indicate that nitrogen excretion changes substantially during growth, and it can be reduced most effectively by improvement of feed efficiency and to a lesser extent through the improvement of BW gain or body composition or both.