快速型黄羽肉鸡饲料利用效率性状的基因组选择研究

旨在探究快速型黄羽肉鸡饲料利用效率性状的遗传参数,评估不同方法所得估计育种值的准确性。本研究以自主培育的快速型黄羽肉鸡E系1 923个个体（其中公鸡1 199只,母鸡724只）为研究素材,采用"京芯一号"鸡55K SNP芯片进行基因分型。分别利用传统最佳线性无偏预测（BLUP）、基因组最佳线性无偏预测（GBLUP）和一步法（SSGBLUP）3种方法,基于加性效应模型进行遗传参数估计,通过10倍交叉验证比较3种方法所得估计育种值的准确性。研究性状包括4个生长性状和4个饲料利用效率性状：42日龄体重（BW42D）、56日龄体重（BW56D）、日均增重（ADG）、日均采食量（ADFI）和饲料转化率（FCR）、剩余采食量（RFI）、剩余增长体重（RG）、剩余采食和增长体重（RIG）。结果显示,4个饲料利用效率性状均为低遗传力（0.08~0.20）,其他生长性状为中等偏低遗传力（0.11~0.35）;4个饲料利用效率性状间均为高度遗传相关,RFI、RIG与ADFI间为中度遗传相关,RFI与ADG间无显著相关性,RIG与ADG间为低度遗传相关。本研究在获得SSGBLUP方法的最佳基因型和系谱矩阵权重比基础上,比较8个性状的估计育种值准确性,SSGBLUP方法获得的准确性分别比传统BLUP和GBLUP方法提高3.85%~14.43%和5.21%~17.89%。综上,以RIG为选择指标能够在降低日均采食量的同时保持日均增重,比RFI更适合快速型黄羽肉鸡的选育目标;采用最佳权重比进行SSGBLUP分析,对目标性状估计育种值的预测性能最优,建议作为快速型黄羽肉鸡基因组选择方法。     

Genetic parameters for body weight, hip height, and the ratio of weight to hip height from random regression analyses of Brahman feedlot cattle

The objective of this research was to assess the genetic control of BW, hip height, and the ratio of BW to hip height (n = 5,055) in Brahman cattle through 170 d on feed using covariance function-random regression models. A progeny test of Brahman sires (n = 27) generated records of Brahman steers and heifers (n = 724) over 7 yr. Each year after weaning, calves were assigned to feedlot pens, where they were fed a high-concentrate grain diet. Body weights and hip heights were recorded every 28 d until cattle reached a targeted fatness level. All calves had records through 170 d on feed; subsequent records were excluded. Models included contemporary group (sex-pen-year combinations, n = 63) and age at the beginning of the feeding period as a covariate. The residual error structure was modeled as a random effect, with 2 levels corresponding to two 85-d periods on feed. Information criterion values indicated that linear, random regression coefficients on Legendre polynomials of days on feed were most appropriate to model additive genetic effects for all 3 traits. Cubic (hip height and BW:hip height ratio) or quartic (BW) polynomials best modeled permanent environmental effects. Estimates of heritability across the 170-d feeding period ranged from 0.31 to 0.53 for BW, from 0.37 to 0.53 for hip height, and from 0.23 to 0.6 for BW:hip height ratio. Estimates of the permanent environmental proportion of phenotypic variance ranged from 0.44 to 0.58 for BW, 0.07 to 0.26 for hip height, and 0.30 to 0.48 for BW:hip height ratio. Within-trait estimates of genetic correlation on pairs of days on feed (at 28-d intervals) indicated lower associations of BW:hip height ratio EBV early and late in the feeding period but large positive associations for BW or hip height EBV throughout. Estimates of genetic correlations among the 3 traits indicated almost no association of BW:hip height ratio and hip height EBV. The ratio of BW to hip height in cattle has previously been used as an objective measure of BCS in cows or calves; it may offer a unique assessment of body dimension. Results indicated that there is substantial additive genetic variation for this trait, and it may be possible to use EBV to increase BW without increasing frame score in Brahman cattle.     

提高猪饲料效率的测定与选择

为提高猪饲料效率的选择,本试验测定一些与猪饲料效率相关的生产性状并进行遗传评估。方法：测定60头军牧1号白猪后备公猪的采食量、体增重、背膘厚等生产性状,用猪剩余采食量（RFI）和饲料转化率（FCR）作为评价饲料效率的两个指标,并对其遗传参数进行评估。结果：测定期内军牧1号公猪群体FCR均值为2．61,RFI的标准差为77．52。RFI与FCR的遗传力分别是0．35、0．33,RFI与ADFI（日采食量）、ADG（日增重）、BF（背膘厚）的遗传相关分别是0．89、0．12、-0．05,FCR与ADFI、ADG、BF的遗传相关分别是0．55、-0．65、-0．11。结论：军牧1号白猪品种内饲料效率存在较大的遗传差异,由于RFI与ADG遗传相关很低,因此用RFI作为选择性状可有效提高猪的饲料效率。     

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.     

Selection response and genetic parameters for residual feed intake in Yorkshire swine

Residual feed intake (RFI) is a measure of feed efficiency defined as the difference between the observed feed intake and that predicted from the average requirements for growth and maintenance. The objective of this study was to evaluate the response in a selection experiment consisting of a line selected for low RFI and a random control line and to estimate the genetic parameters for RFI and related production and carcass traits. Beginning with random allocation of purebred Yorkshire littermates, in each generation, electronically measured ADFI, ADG, and ultrasound backfat (BF) were evaluated during a approximately 40- to approximately 115-kg of BW test period on approximately 90 boars from first parity and approximately 90 gilts from second parity sows of the low RFI line. After evaluation of first parity boars, approximately 12 boars and approximately 70 gilts from the low RFI line were selected to produce approximately 50 litters for the next generation. Approximately 30 control line litters were produced by random selection and mating. Selection was on EBV for RFI from an animal model analysis of ADFI, with on-test group and sex (fixed), pen within group and litter (random), and covariates for interactions of on- and off-test BW, on-test age, ADG, and BF with generations. The RFI explained 34% of phenotypic variation in ADFI. After 4 generations of selection, estimates of heritability for RFI, ADFI, ADG, feed efficiency (FE, which is the reciprocal of the feed conversion ratio and equals ADG/ ADFI), and ultrasound-predicted BF, LM area (LMA), and intramuscular fat (IMF) were 0.29, 0.51, 0.42, 0.17, 0.68, 0.57, and 0.28, respectively; predicted responses based on average EBV in the low RFI line were -114, -202, and -39 g/d for RFI (= 0.9 phenotypic SD), ADFI (0.9 SD), and ADG (0.4 SD), respectively, and 1.56% for FE (0.5 SD), -0.37 mm for BF (0.1 SD), 0.35 cm(2) for LMA (0.1 SD), and -0.10% for IMF (0.3 SD). Direct phenotypic comparison of the low RFI and control lines based on 92 low RFI and 76 control gilts from the second parity of generation 4 showed that selection had significantly decreased RFI by 96 g/d (P = 0.002) and ADFI by 165 g/d (P < 0.0001). The low RFI line also had 33 g/d lower ADG (P = 0.022), 1.36% greater FE (P = 0.09), and 1.99 mm less BF (P = 0.013). There was not a significant difference in LMA and other carcass traits, including subjective marbling score, despite a large observed difference in ultrasound-predicted IMF (-1.05% with P < 0.0001). In conclusion, RFI is a heritable trait, and selection for low RFI has significantly decreased the feed required for a given rate of growth and backfat.     

Genetic analysis of longitudinal measurements of performance traits in selection lines for residual feed intake in Yorkshire swine

A 5-generation selection experiment in Yorkshire pigs for feed efficiency consists of a line selected for low residual feed intake (LRFI) and a random control line (CTRL). The objectives of this study were to use random regression models to estimate genetic parameters for daily feed intake (DFI), BW, backfat (BF), and loin muscle area (LMA) along the growth trajectory and to evaluate the effect of LRFI selection on genetic curves for DFI and BW. An additional objective was to compare random regression models using polynomials (RRP) and spline functions (RRS). Data from approximately 3 to 8 mo of age on 586 boars and 495 gilts across 5 generations were used. The average number of measurements was 85, 14, 5, and 5 for DFI, BW, BF, and LMA. The RRP models for these 4 traits were fitted with pen × on-test group as a fixed effect, second-order Legendre polynomials of age as fixed curves for each generation, and random curves for additive genetic and permanent environmental effects. Different residual variances were used for the first and second halves of the test period. The RRS models were fitted with the same fixed effects and residual variance structure as the RRP models and included genetic and permanent environmental random effects for both splines and linear Legendre polynomials of age. The RRP model was used for further analysis because the RRS model had erratic estimates of phenotypic variance and heritability, despite having a smaller Bayesian information criterion than the RRP model. From 91 to 210 d of age, estimates of heritability from the RRP model ranged from 0.10 to 0.37 for boars and 0.14 to 0.26 for gilts for DFI, from 0.39 to 0.58 for boars and 0.55 to 0.61 for gilts for BW, from 0.48 to 0.61 for boars and 0.61 to 0.79 for gilts for BF, and from 0.46 to 0.55 for boars and 0.63 to 0.81 for gilts for LMA. In generation 5, LRFI pigs had lower average genetic curves than CTRL pigs for DFI and BW, especially toward the end of the test period; estimated line differences (CTRL-LRFI) for DFI were 0.04 kg/d for boars and 0.12 kg/d for gilts at 105 d and 0.20 kg/d for boars and 0.24 kg/d for gilts at 195 d. Line differences for BW were 0.17 kg for boars and 0.69 kg for gilts at 105 d and 3.49 kg for boars and 8.96 kg for gilts at 195 d. In conclusion, selection for LRFI has resulted in a lower feed intake curve and a lower BW curve toward maturity.     

Genetic associations between feed efficiency measured in a performance test station and performance of growing cattle in commercial beef herds

Interest in selection for improved feed efficiency is increasing, but before any steps are taken toward selecting for feed efficiency, correlations with other economically important traits must first be quantified. The objective of this study was to quantify the genetic associations between feed efficiency measured during performance testing and linear type traits, BW, live animal value, and carcass traits recorded in commercial herds. Feed efficiency data were available on 2,605 bulls from 1 performance test station. There were between 10,384 and 93,442 performance records on type traits, BW, animal value, or carcass traits from 17,225 commercial herds. (Co)variance components were estimated using linear mixed animal models. Genetic correlations between the muscular type traits in commercial animals and feed conversion ratio (-0.33 to -0.25), residual feed intake (RFI; -0.33 to -0.22), and residual BW gain (RG; 0.24 to 0.27) suggest that selection for improved feed efficiency should increase muscling. This is further evidenced by the genetic correlations between carcass conformation of commercial animals and feed conversion ratio (-0.46), RFI (-0.37), and residual BW gain (0.35) measured in performance-tested animals. Furthermore, the genetic correlations between RFI and both ultrasonic fat depth and carcass fat score (0.39 and 0.33, respectively) indicated that selection for improved RFI will result in leaner animals. It can be concluded from the genetic correlations estimated in this study that selection for feed efficiency will have no unfavorable effects on the performance traits measured in this study and will actually lead to an improvement in performance for some traits, such as muscularity, animal price, and carcass conformation. Conversely, this suggests that genetic selection for traits such as carcass quality, muscling traits, and animal value might also be indirectly selecting for more efficient animals.     

Genetic parameters for feed efficiency and body weight traits in Japanese quail

1. The objectives of the present study were to estimate heritability and genetic correlations for feed efficiency and body weight (BW) in Japanese quail.

2. Recorded traits during different weeks of the growing period were BW from hatch to 35 d, feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI) from hatch to 28 d of age.

3. Genetic parameters were estimated by restricted maximum likelihood method using ASREML software. The results showed that heritability estimates for BW ranged from 0.11 to 0.22, and maternal permanent environmental effect was the highest at hatch (0.45). FCR, RFI and FI showed moderate heritabilities ranging from 0.13 to 0.40.

4.Genetic correlations of BW₂₈ with FI_0–28 (0.88) and RFI_0–28 (0.1) and genetic correlation of FI_0–28 with FCR_0–28 (0.13) and RFI_0–28 (0.52) were positive. A negative genetic correlation was found between BW₂₈ and FCR_0–28 (?0.49). There was a high positive genetic correlation (0.67) between RFI_0–28 and FCR_0–28.

5. In conclusion, selection for increased BW and reduced FI in a selection index could be recommended to improve feed efficiency traits including FCR and RFI in Japanese quail.     

Association of single nucleotide polymorphisms in the leptin gene with body weight and backfat growth curve parameters for beef cattle

Previous research has identified differences in carcass characteristics across SNP in the bovine leptin gene at slaughter, but before feedlot operators implement selection and sorting strategies, more information is needed to determine how carcass characteristics change over time. The objective of this study was to investigate the effect of 2 leptin SNP on growth curve parameters for BW and backfat. Two SNP (UASMS2 and R25C) were genotyped on 1,653 cross-bred steers and heifers in a commercial feedlot. Up to 4 serial measures of BW and ultrasound estimates of backfat thickness were taken for each animal from the time of placement on feed to slaughter. The measures were used to estimate growth models that describe changes in BW and backfat thickness as a function of days on feed. Data analysis was carried out by estimating nonlinear mixed models to determine the individual and joint effect of each SNP on growth curve parameters. Brody growth curves were fit to the BW data. Variations in the R25C SNP did not significantly affect growth parameters individually or in combination with the UASMS2 SNP. Variations in the UASMS2 SNP were significant in Brody growth curve parameters for BW growth (P < 0.001). The genotype UASMS2-CC was the heaviest at the beginning of the feeding period and exhibited the largest asymptotic mature BW, but UASMS2-TT cattle exhibited the fastest rate of BW growth. A modified power function was fit to the serial ultrasound backfat measures. Models that included the combined effect of the R25C and UASMS2 SNP provided the best fit to the data. Genotypes differed significantly in power function parameters for backfat growth (P < 0.001). The R25C-CC/UASMS2-TT cattle had the smallest backfat thickness at placement. The genotype R25C-CC/UASMS2-TT exhibited the fastest backfat growth rate, whereas backfat in R25C-CC/UASMS2-CC cattle grew at the slowest rate. The association between leptin genotype and growth in BW and backfat presents opportunities to identify genetically distinct cattle and to differentially optimize feeding times accordingly.     

Estimation of genetic parameters for growth and feed utilization traits in Japanese Black cattle

Performance test results of 3250 sire candidates were used to estimate the genetic parameters of growth and feed utilization traits in Japanese Black cattle. Growth traits analyzed were six body measurements at the end of the performance test and daily gain (DG) during the test. Feed utilization traits were intakes and conversions of concentrate, roughage, digestible crude protein and total digestible nutrient (TDN). Genetic (co)variance components were estimated by the restricted maximum likelihood procedure using an expectation maximization algorithm under the two‐trait animal model. Heritabilities for growth traits ranged from 0.40 to 0.70 and for feed utilization traits from 0.21 to 0.74. Genetic correlations of DG were positive with feed intake (0.15–0.77) and negative with feed conversions (?0.63 to ?0.30). These relationships indicate that the selection based on DG improves feed efficiency but it simultaneously increases feed intake. Feed conversions showed genetic correlations ranging from ?0.09 to 0.03 with total available energy consumption, TDN intake. Thus the results suggested that feed conversions were not efficient selection criteria to decrease TDN intake and to improve comprehensive feed utilization ability.     

Investigating maternal effects on production traits in Duroc pigs using animal and sire models

Variance components for production traits were estimated using different models to evaluate maternal effects. Data analysed were records from the South African pig performance testing scheme on 22 224 pigs from 18 herds, tested between 1990 and 2008. The traits analysed were backfat thickness (BFAT), test period weight gain (TPG), lifetime weight gain (LTG), test period feed conversion ratio (FCR) and age at slaughter (AGES). Data analyses were performed by REML procedures in ASREML, where random effects were successively fitted into animal and sire models to produce different models. The first animal model had one random effect, the direct genetic effects, while the additional random effects were maternal genetic and maternal permanent environmental effects. In the sire model, the random effects fitted were sire and maternal grand sire effects. The best model considered the covariance between direct and maternal genetic effects or between sire and maternal grand sire effects. Fitting maternal genetic effects into the animal model reduced total additive variance, while the total additive variance increased when maternal grand sire effects were fitted into the sire model. The correlations between direct and maternal genetic effects were all negative, indicating antagonism between these effects, hence the need to consider both effects in selection programmes. Direct genetic correlations were higher than other correlations, except for maternal genetic correlations of FCR with TPG, LTG and AGES. There has been direct genetic improvement and almost constant maternal ability in production traits as shown by trends for estimated (EBVs) and maternal breeding values (MBVs), while phenotypic trends were similar to those for EBVs. These results suggest that maternal genetic effects should be included in selection programmes for these production traits. Therefore, the animal–maternal model may be the most appropriate model to use when estimating genetic parameters for production traits in this population.     

Selection for feed efficiency does not change the selection for growth and carcass traits in Nellore cattle

The objectives were to conduct a genetic evaluation of residual feed intake (RFI) and residual feed intake adjusted for fat (RFIFat) and to analyse the effect of selection for these traits on growth, carcass and reproductive traits. Data from 945 Nellore bulls in seven feed efficiency tests in a feedlot were analysed. Genetic evaluation was performed using an animal model in which the feed efficiency test and age of the animal at the beginning of the test were considered as a systematic effect. Direct additive genetic and residual effects were considered as random effects. Correlations and genetic gains were estimated by two‐trait analysis between feed efficiency measures (RFI and RFIFat) and other traits. Feed conversion showed low heritability (0.06), but dry matter intake (DMI), average daily gain, RFI, RFIFat, metabolic body weight and scrotal circumference measured at 450 days of age (SC450) showed moderate to high heritability (0.49, 0.28, 0.33, 0.36, 0.38 and 0.80, respectively). Similarly, ribeye area, backfat thickness, rump cap fat thickness, marbling score and subcutaneous fat thickness also had high heritability values (0.46, 0.37, 0.57, 0.51 and 0.47, respectively). Genetic correlations between RFI and SC450 were null, and between RFIFat and SC450 were strongly positive. Genetic and phenotypic correlations of RFI and RFIFat with carcass traits were not different from zero, as correlated responses for carcass traits were also not different from zero. The Nellore selection for feed efficiency by RFI or RFIFat allows the recognition of feed efficient animals, with DMI reduction and without significant changes in growth and carcass traits. However, because of the observed results between RFIFat and SC450, selection of animals should be analysed with caution and a preselection for reproductive traits is necessary to avoid reproductive impairments in the herd.     

Simultaneous Bayesian estimation of genetic parameters for curves of weight,feed intake,and residual feed intake in beef cattle

Rates of gain and feed efficiency are important traits in most breeding programs for growing farm animals. The rate of gain (GAIN) is usually expressed over a certain age period and feed efficiency is often expressed as residual feed intake (RFI), defined as observed feed intake (FI) minus expected feed intake based on live weight (WGT) and GAIN. However, the basic traits recorded are always WGT and FI and other traits are derived from these basic records. The aim of this study was to develop a procedure for simultaneous analysis of the basic records and then derive linear traits related to feed efficiency without retorting to any approximation. A bivariate longitudinal random regression model was employed on 13,791 individual longitudinal records of WGT and FI from 2,827 bulls of six different beef breeds tested for their own performance in the period from 7 to 13 mo of age. Genetic and permanent environmental covariance functions for curves of WGT and FI were estimated using Gibbs sampling. Genetic and permanent covariance functions for curves of GAIN were estimated from the first derivative of the function for WGT and finally the covariance functions were extended to curves for RFI, based on the conditional distribution of FI given WGT and GAIN. Furthermore, the covariance functions were extended to include GAIN and RFI defined over different periods of the performance test. These periods included the whole test period as normally used when predicting breeding values for GAIN and RFI for beef bulls. Based on the presented method, breeding values and genetic parameters for derived traits such as GAIN and RFI defined longitudinally or integrated over (parts of) of the test period can be obtained from a joint analysis of the basic records. The resulting covariance functions for WGT, FI, GAIN, and RFI are usually singular but the method presented here does not suffer from the estimation problems associated with defining these traits individually before the genetic analysis. All the results are thus estimated simultaneously, and the set of parameters is consistent.     

Genetic parameters for residual energy intake and energy conversion efficiency in Nordic Red dairy cattle

Abstract

Our aim was to estimate the genetic parameters of residual energy intake (REI) and energy conversion efficiency (ECE), and their relationships with milk, feed intake and body weight (BW) and condition in Nordic Red dairy cattle with data from 400 animals. These data were analysed with repeatability and random regression models. The highest heritabilities for energy efficiency traits were obtained in the beginning and the end of the 30 week lactation period (0.21–0.40). The results suggest that the energy efficiencies in early- and mid-lactation periods are partially different traits. The genetic correlations of REI were moderate to high and positive with the other studied traits, and high and positive for ECE with milk, but moderate to low and negative with dry matter intake, BW and body condition score. Further improvements are still needed in modelling the energy efficiency traits of cows during lactation.     

Effect of competition on gain in feedlot bulls from Hereford selection lines

This study examined competition effects on ADG in the feedlot of 1,882 Hereford bulls representing 8 birth years from a selection experiment. Each year, 8 feedlot pens were used to feed bulls in groups, with 2 pens nested within each of the 4 selection lines. Gains were recorded for up to 8 periods of 28 d. Models for analyses included pen effects (fixed or random), fixed effects such as year and line, and random direct genetic, competition genetic (and in some analyses competition environmental), and environmental effects. Each pen mate as a competitor affected the records of all others in the pen. All lines traced to common foundation animals, so the numerator relationships among and within pens were the bases for separating direct and competition genetic effects and pen effects. For this population and pen conditions (average of 30 bulls per pen), the major results were 1) competition genetic effects seemed present for the first 28-d period but not for the following 7 periods; 2) models with pens considered as fixed effects could not separate variances and covariance due to direct and competition genetic effects; 3) models without competition effects had large estimates of the variance component due to pen effects for gain through 8 periods; and 4) models with genetic and environmental competition effects accounted for nearly all of the variance traditionally attributed to pen effects (even though estimates of the competition variance component were small, the estimates of pen variance were near zero).     

Genetic relationships between feed efficiency in growing males and beef cow performance

Most studies on feed efficiency in beef cattle have focused on performance in young animals despite the contribution of the cow herd to overall profitability of beef production systems. The objective of this study was to quantify, using a large data set, the genetic covariances between feed efficiency in growing animals measured in a performance-test station, and beef cow performance including fertility, survival, calving traits, BW, maternal weaning weight, cow price, and cull cow carcass characteristics in commercial herds. Feed efficiency data were available on 2,605 purebred bulls from 1 test station. Records on cow performance were available on up to 94,936 crossbred beef cows. Genetic covariances were estimated using animal and animal-dam linear mixed models. Results showed that selection for feed efficiency, defined as feed conversion ratio (FCR) or residual BW gain (RG), improved maternal weaning weight as evidenced by the respective genetic correlations of -0.61 and 0.57. Despite residual feed intake (RFI) being phenotypically independent of BW, a negative genetic correlation existed between RFI and cow BW (-0.23; although the SE of 0.31 was large). None of the feed efficiency traits were correlated with fertility, calving difficulty, or perinatal mortality. However, genetic correlations estimated between age at first calving and FCR (-0.55 ± 0.14), Kleiber ratio (0.33 ± 0.15), RFI (-0.29 ± 0.14), residual BW gain (0.36 ± 0.15), and relative growth rate (0.37 ± 0.15) all suggest that selection for improved efficiency may delay the age at first calving, and we speculate, using information from other studies, that this may be due to a delay in the onset of puberty. Results from this study, based on the estimated genetic correlations, suggest that selection for improved feed efficiency will have no deleterious effect on cow performance traits with the exception of delaying the age at first calving.     

基于系谱和基因组信息估计荷斯坦青年母牛体重性状遗传参数

旨在设计利用不同信息来源的模型估计荷斯坦后备牛不同月龄体重性状的遗传参数。本研究于2014—2020年测定并收集了7 122头荷斯坦牛32 338条0～12月龄体重数据,分别利用系谱信息(linear mixed model with pedigree relationship matrix, LM＿A)和系谱-基因组信息构建亲缘关系矩阵(linear mixed model with genotype-pedigree joint relationship matrix, LM＿H),基于母体效应动物模型估计初生重,基于是否考虑初生重作为协变量的单性状动物模型估计2～12月龄各月龄体重遗传力,并利用双性状动物模型估计初生重与其它月龄体重的遗传相关。结果显示,对于初生重,根据赤池信息量准则(Akaike information criterion, AIC),LM＿H方法的拟合程度显著优于LM＿A方法,但两种方法估计的遗传参数相差不大：直接遗传力分别为0.30和0.32,母体遗传力分别为0.08和0.09,个体直接遗传效应和母体遗传效应遗传相关系数分别为-0.65和-0.64;对于2～...     

Genetic variability in the feeding behavior of crossbred growing cattle and associations with performance and feed efficiency

The objectives of the present study were to estimate genetic parameters for several feeding behavior traits in growing cattle, as well as the genetic associations among and between feeding behavior and both performance and feed efficiency traits. An additional objective was to investigate the use of feeding behavior traits as predictors of genetic merit for feed intake. Feed intake and live-weight data on 6,088 growing cattle were used of which 4,672 had ultrasound data and 1,548 had feeding behavior data. Feeding behavior traits were defined based on individual feed events or meal events (where individual feed events were grouped into meals). Univariate and bivariate animal linear mixed models were used to estimate (co)variance components. Heritability estimates (± SE) for the feeding behavior traits ranged from 0.19 ± 0.08 for meals per day to 0.61 ± 0.10 for feeding time per day. The coefficient of genetic variation per trait varied from 5% for meals per day to 22% for the duration of each feed event. Genetically heavier cattle, those with a higher daily energy intake (MEI), or those that grew faster had a faster feeding rate, as well as a greater energy intake per feed event and per meal. Better daily feed efficiency (i.e., lower residual energy intake) was genetically associated with both a shorter feeding time per day and shorter meal time per day. In a validation population of 321 steers and heifers, the ability of estimated breeding values (EBV) for MEI to predict (adjusted) phenotypic MEI was demonstrated; EBVs for MEI were estimated using multi-trait models with different sets of predictor traits such as liveweight and/or feeding behaviors. The correlation (± SE) between phenotypic MEI and EBV for MEI marginally improved (P < 0.001) from 0.64 ± 0.03 to 0.68 ± 0.03 when feeding behavior phenotypes from the validation population were included in a genetic evaluation that already included phenotypic mid-test metabolic live-weight from the validation population. This is one of the largest studies demonstrating that significant exploitable genetic variation exists in the feeding behavior of young crossbred growing cattle; such feeding behavior traits are also genetically correlated with several performance and feed efficiency metrics. Nonetheless, there was only a marginal benefit to the inclusion of time-related feeding behavior phenotypes in a genetic evaluation for MEI to improve the precision of the EBVs for this trait.     

Individually measured feed intake characteristics and growth performance of group-housed weanling pigs: effects of sex, initial body weight, and body weight distribution within groups

Feed intake characteristics of 192, 27-d-old weanling pigs housed in groups and given ad libitum access to feed and water were measured individually with the use of computerized feeding stations. The groups were either homogeneous or heterogeneous as to BW distribution; pigs of three defined initial BW classes were used (mean BW of 6.7, 7.9, or 9.3 kg). The effects of BW distribution, BW class, and sex were studied with regard to average performance traits, latency time (interval between weaning and first feed intake), initial feed intake (intake during the first 24 h following first feed intake), and daily increase in feed intake during the interval between first feed intake and the day on which energy intake met or exceeded 1.5 times the maintenance requirement. Homogeneous and heterogeneous groups had similar latency times, initial feed intakes, and daily increases in feed intake. For the period 0 to 34 d after weaning, ADFI and ADG were also similar for homogeneous and heterogeneous groups, but gain:feed ratio was greater (P < 0.05) in the homogeneous groups. Gilts had higher (P < 0.05) initial feed intakes than barrows and also had greater (P < 0.05) ADFI and ADG during the period 0 to 13 d after weaning. Pigs with average BW of 6.7 kg had higher (P < 0.05) initial feed intakes than their counterparts with average BW of 7.9 kg and 9.3 kg, but the daily increase in feed intake was similar for the three groups. The lighter pigs had more daily visits and a lower feed intake per visit and tended to have a shorter postweaning latency to the onset of feeding than the heavier pigs. This study indicates that the high variability in early feeding behavior among group-housed weanling pigs may be related to BW and sex.     

Estimation of genetic parameters of feed intake and daily gain in Durocs using data from electronic swine feeders

Genetic parameters for daily feed intake (DFI, g/day) and daily gain (DG, g/day) were estimated using records of 1916 Duroc boars from electronic feeder stations. Management was limited and resulted in varied ranges of age and weight on test. Boars were housed in 102 pens, each equipped with one feeder, and allowed ad libitum feeding. Weekly averages of DFI and DG were used due to large variation in daily records. Six traits were defined as DFI and DG during 85–106 (period 1), 107–128 (period 2) and 129–150 days of age (period 3). A six‐trait model included age as a linear and a quadratic covariate for DFI and a linear covariate for DG with a fixed effect of year–week–pen and random effects of litter, additive genetic animal and permanent environmental animal. Variance components were estimated by a Bayesian approach using Gibbs sampling algorithm. Estimates of heritability for respective periods were 18%, 12% and 10% for DFI and 21%, 11% and 10% for DG. Genetic correlations between DFI and DG in the same period were 0.70, 0.73 and 0.32 for the respective periods. DFI and DG obtained from automatic feeders can be analysed to reveal variation across testing periods by using weekly averages when many monthly averages are incomplete.