Study of the effect of genotype–environment interaction on age at first calving and production traits in Nellore cattle using multi‐trait reaction norms and Bayesian inference

This study investigated the effects of genotype–environment interaction on yearling weight, age at first calving and post‐weaning weight gain in Nellore cattle using multi‐trait reaction norm models. The environmental gradient was defined as a function of the mean yearling weight of the contemporary groups. A first‐order random regression sire model with four classes of residual variance was used in the analyses and Bayesian methods were applied to estimate the (co)variance components. The heritability estimates ranged from 0.284 to 0.547, 0.222 to 0.316 and 0.256 to 0.522 for yearling weight, age at first calving and post‐weaning weight gain, respectively. The lowest genetic correlations between environment groups for each trait were 0.38, 0.02 and 0.04 for yearling weight, age at first calving and post‐weaning weight gain, respectively. Differences in the correlation estimates were observed between traits in the same environments, with the magnitude of the estimates tending toward zero as the environment improved. The results highlight the importance of including genotype–environment interactions in genetic evaluation programs considering the differences observed between environmental groups not only in terms of heritability, but also of genetic correlations.     

Identification of genomic regions related to age at first calving and first calving interval in water buffalo using single-step GBLUP

In Brazil, water buffaloes have been used to produce milk for mozzarella cheese production. Consequently, the main selection criterion applied for the buffalo genetic improvement is the estimated mozzarella yield as a function of milk, fat and protein production. However, given the importance of reproductive traits in production systems, this study aimed to use techniques for identifying genomic regions that affect the age at first calving (AFC) and first calving interval (FCI) in buffalo cows and to select candidate genes for the identification of QTL and gene expression studies. The single-step GBLUP method was used for the identification of genomic regions. Windows of 1 Mb containing single-nucleotide polymorphisms were constructed and the 10 windows that explained the greatest proportion of genetic variance were considered candidate regions for each trait. Genes present into the selected windows were identified using the UOA_WB_1 assembly as the reference, and their ontology was defined with the Panther tool. Candidate regions for both traits were identified on BBU 3, 12, 21 and 22; for AFC, candidates were detected on BBU 6, 7, 8, 9 and 15 and for first calving interval on BBU 4, 14 and 19. This study identified regions with great contribution to the additive genetic variance of age at first calving and first calving interval in the population of buffalo cows studied. The ROCK2, PMVK, ADCY2, MAP2K6, BMP10 and GFPT1 genes are main candidates for reproductive traits in water dairy buffaloes, and these results may have future applications in animal breeding programs or in gene expression studies of the species.     

An analysis of age and body weight at first calving for Holsteins in the United States

In a national survey of US dairy producers, only 2.7 ± 0.5% of Holstein dairy operations reported achieving recommended target ranges of age ≤ 24 months and body weight (BW) ≥ 550 kg at first calving. Allowing for wider target ranges, still only 14.6 ± 1.3% of Holstein dairy operations reported achieving age ≤ 25 months and BW ≥ 544.3 kg at first calving. Ages of individual first-calf heifers observed at calving were heavily skewed toward older individuals. Dairy producers reported an average age at first calving that was 1.3 months lower than the mean and 1.0 months lower than median age of first-calf heifers' observed calving on the operations. Stepwise logistic regression was used to identify the herd characteristics associated with producers reporting first calvings within the wider age and BW target ranges for Holsteins. Rolling herd average milk production ≥ 7711 kg/yr, using a computer for recordkeeping, and not tying preweaned heifers in a barn with cows, were associated with achieving the target BW and age at first calving.     

Genomic prediction of growth traits for pigs in the presence of genotype by environment interactions using single-step genomic reaction norm model

Economically important traits are usually complex traits influenced by genes, environment and genotype-by-environment (G × E) interactions. Ignoring G × E interaction could lead to bias in the estimation of breeding values and selection decisions. A total of 1,778 pigs were genotyped using the PorcineSNP80 BeadChip. The existence of G × E interactions was investigated using a single-step reaction norm model for growth traits of days to 100 kg (AGE) and backfat thickness adjusted to 100 kg (BFT), based on a pedigree-based relationship matrix (A) or a genomic–pedigree joint relationship matrix (H). In the reaction norm model, the herd-year-season effect was measured as the environmental variable (EV). Our results showed no G × E interactions for AGE, but for BFT. For both AGE and BFT, the genomic reaction norm model (H) produced more accurate predictions than the conventional reaction norm model (A). For BFT, the accuracies were greater based on the reaction norm model than those based on the reduced model without exploiting G × E interaction, with EV ranging from 0.5 to 1, and accuracy increasing by 3.9% and 4.6% in the reaction norm model based on A and H matrices, respectively, while reaction norm model yielded approximately 8.4% and 7.9% lower accuracy for EVs ranging from 0 to 0.4, based on A and H matrices, respectively. In addition, for BFT, the highest accuracy was obtained in the BJLM6 farm for realizing directional selection. This study will help to apply G × E interactions to practical genomic selection.     

Genetic associations between age at first calving and heifer body weight and scrotal circumference in Nelore cattle

Age at first calving (AFC) measures the entry of heifers into the beef cattle production system. This trait can be used as a selection criterion for earlier reproductive performance. Using data from Nelore cattle participating in the 'Program for Genetic Improvement of the Nelore Breed' (PMGRN-Nelore Brazil), bi-trait analyses were performed using the restricted maximum likelihood method, based on an AFC animal model and the following traits: female body weight adjusted to 365 (BW365) and 450 (BW450) days of age, and male scrotal circumference adjusted to 365 (SC365), 450 (SC450), 550 (SC550) and 730 (SC730) days of age. The heritability estimates for AFC ranged from 0.02 ± 0.02 to 0.04 ± 0.02. The estimates of additive direct heritabilities (with standard error) for BW365, BW450, SC365, SC450, SC550 and SC730 were 0.36 ± 0.07, 0.38 ± 0.07, 0.48 ± 0.07, 0.65 ± 0.07, 0.64 ± 0.07 and 0.42 ± 0.07, respectively, and the genetic correlations with AFC were −0.38, −0.33, 0.10, −0.13, −0.13 and 0.06, respectively. In the herds studied, selection for SC365, SC450, SC550 or SC730 should not cause genetic changes in AFC. Selection based on BW365 or BW450 would favor smaller AFC breeding values. However, the low magnitude of direct heritability estimates for AFC in these farms indicates that changes in phenotypical expression depend mostly on non-genetic factors.     

Effects of sex and age on genotype x environment interaction for beef cattle body weight studied using reaction norm models

The interest in the effect of genotype × environment interaction is increasing because animal breeding programs have become geographically broader. Climate changes in the next decades are also expected to challenge the present breeding goals, increasing the importance of environmental sensitivity. The aim of this work was to analyze genotype × environment interaction effect on cattle BW using the environmental sensitivity predicted by random regression reaction norm models, including sex and age effects as additional dimensions in the study. Genetic parameters were estimated for adjusted BW of Brazilian Nelore cattle at different ages (120, 210, 365, and 450 d), using linear polynomials for random regression analysis. The analyses with sex as a fixed effect (total analyses) were compared with those with sex-separated progenies (male and female progeny analyses, respectively). (Co)variance components were estimated and breeding values calculated EPD. The results showed important differences in reaction norm model genetic parameter estimates according to different age and sex analyses. The results confirmed the presence of an important genotype × environment × sex × age interaction for Nelore cattle BW. The patterns in these results lead to a revision of the importance of sexual and developmental factors on plasticity and adaptation concepts.     

Genetic parameters and genetic trends for age at first calving and calving interval in an Angus-Blanco Orejinegro-Zebu multibreed cattle population in Colombia

Genetic parameters and genetic trends for age at first calving (AFC), interval between first and second calving (CI1), and interval between second and third calving (CI2) were estimated in a Colombian beef cattle population composed of Angus, Blanco Orejinegro, and Zebu straightbred and crossbred animals. Data were analyzed using a multiple trait mixed model procedures. Estimates of variance components and genetic parameters were obtained by Restricted Maximum Likelihood. The 3-trait model included the fixed effects of contemporary group (year-season of calving-sex of calf; sex of calf for CI1 and CI2 only), age at calving (CI1 and CI2 only), breed genetic effects (as a function of breed fractions of cows), and individual heterosis (as a function of cow heterozygosity). Random effects for AFC, CI1, and CI2 were cow and residual. Program AIREMLF90 was used to perform computations. Estimates of heritabilities for additive genetic effects were 0.15 ± 0.13 for AFC, 0.11 ± 0.06 for CI1, and 0.18 ± 0.11 for CI2. Low heritabilities suggested that nutrition and reproductive management should be improved to allow fuller expressions of these traits. The correlations between additive genetic effects for AFC and CI1 (0.33 ± 0.41) and for AFC and CI2 (0.40 ± 0.36) were moderate and favorable, suggesting that selection of heifers for AFC would also improve calving interval. Trends were negative for predicted cow yearly means for AFC, CI1, and CI2 from 1989 to 2004. The steepest negative trend was for cow AFC means likely due to the introduction of Angus and Blanco Orejinegro cattle into this population.     

Genetic parameters for birth weight,weaning weight and age at first calving in Brown Swiss cattle in Mexico

Heritabilities and genetic correlations between birth weight (n = 13,741), adjusted 240-day weaning weight (WW, n = 8,806) and age at first calving (AFC, n = 3,955) of Brown Swiss cattle in Mexico were estimated. Data from 91 herds located in 19 of 32 states of Mexico from 1982 to 2006 were provided by the Mexican Brown cattle Breeder Association. Components of (co)variance, direct and maternal heritabilities were estimated for birth weight, WW and AFC using bivariate animal models. Direct and maternal heritabilities were 0.21 and 0.05 for birth weight, 0.40 and 0.05 for WW, whereas direct heritability for AFC was 0.08. The correlations between direct and maternal effects for birth weight and WW were −0.49 and −0.64, respectively. The genetic correlations between birth weight–WW and WW–AFC were 0.36 and −0.02, respectively. Under the conditions of this study, selection for increasing birth weight would increase WW, but increasing WW will not change AFC.     

Milk yield, age at first calving, and the risk of BSE: an analysis at the farm level in France

The epidemic of bovine spongiform encephalopathy (BSE) in France, as in the UK, has affected dairy cattle much more than beef cattle. However, the intensification of dairy herd management as a risk factor for BSE has not to date been analyzed. For this purpose, two databases were merged: the French Milk Records database, and the French BSE database, which can be considered as being devoid of notification bias since July 2001, when systematic tests were implemented. Only pure Holstein herds were considered, which represent the vast majority of total and BSE-affected dairy herds in France. A case-control study was designed so that 20 control herds were matched to each case herd according to the location of the farm and the year of birth of the index case. Three thousand and forty five farms were included, among which 145 with a BSE case notified between July 2001 and July 2003, and 2900 controls. With respect to the risk of BSE, odds ratios for each class of milk yield and age at first calving were estimated by using conditional logistic regression models with appropriate adjustments to herd size. The two main results were the following: firstly, whereas most Holstein herds, with average production between 7000 and 10,000kg, had nearly the same BSE risk, a small category of very intensive herds, with annual milk yields above 10,000kg, were significantly more at risk than the other herds. Secondly, a very early first calving (under 26 months of age) was found to be at risk for BSE as compared to other categories, independently of the milk yield. These results are discussed in the light of the known age-dependent susceptibility to BSE.     

Genetic parameters and relationships of heifer pregnancy and age at first calving with weight gain, yearling and mature weight in Nelore cattle

The objectives of the current study were to investigate the additive genetic associations between heifer pregnancy at 16 months of age (HP16) and age at first calving (AFC) with weight gain from birth to weaning (WG), yearling weight (YW) and mature weight (MW), in order to verify the possibility of using the traits measured directly in females as selection criteria for the genetic improvement of sexual precocity in Nelore cattle. (Co)variance components were estimated by Bayesian inference using a linear animal model for AFC, WG, YW and MW and a nonlinear (threshold) animal model for HP16. The posterior means of direct heritability estimates were: 0.45 ± 0.02; 0.10 ± 0.01; 0.23 ± 0.02; 0.36 ± 0.01 and 0.39 ± 0.04, for HP16, AFC, WG, YW and MW, respectively. Maternal heritability estimate for WG was 0.07 ± 0.01. Genetic correlations estimated between HP16 and WG, YW and MW were 0.19 ± 0.04; 0.25 ± 0.06 and 0.14 ± 0.05, respectively. The genetic correlations of AFC with WG, YW and MW were low to moderate and negative, with values of − 0.18 ± 0.06; − 0.22 ± 0.05 and − 0.12 ± 0.05, respectively. The high heritability estimated for HP16 suggests that this trait seem to be a better selection criterion for females sexual precocity than AFC. Long-term selection for animals that are heavier at young ages tends to improve the heifers sexual precocity evaluated by HP16 or AFC. Predicted breeding values for HP16 can be used to select bulls and it can lead to an improvement in sexual precocity. The inclusion of HP16 in a selection index will result in small or no response for females mature weight.     

Genetic and phenotypic parameters of milk yield, milk composition and age at first kidding in Saanen goats from Mexico

A total of 4007 lactation records from 1520 Saanen goats kidding from 1999 to 2006 and obtained from 10 herds in Guanajuato, Mexico, were analyzed to estimate the heritabilities, repeatabilities, as well as genetic, environmental and phenotypic correlations for milk yield (MILK), fat yield (FAT), protein yield (PROT), fat content (%FAT), protein content (%PROT) and age at fist kidding (AFK). A five-trait repeatability model was used to estimate (co)variances for milk traits, and a four-trait animal model for first lactation records was used to estimate (co)variances involving AFK. For MILK, FAT, PROT, %FAT, %PROT and AFK, heritability estimates were 0.17 ± 0.04, 0.19 ± 0.05, 0.17 ± 0.04, 0.32 ± 0.06, 0.38 ± 0.07 and 0.31 ± 0.09, respectively. Repeatabilities for MILK, FAT, PROT, %FAT and %PROT were 0.43 ± 0.02, 0.42 ± 0.02, 0.42 ±0.02, 0.64 ± 0.02, and 0.63 ± 0.02, respectively. The genetic correlations between MILK and FAT, and between MILK and PROT, were high and positive (0.72 ± 0.08 and 0.87 ± 0.04, respectively). Genetic correlations between MILK and %FAT, between MILK and %PROT and between MILK and AFK, were − 0.24 ± 0.16, − 0.30 ± 0.15 and − 0.18 ± 0.23, respectively. Genetic correlations between AFK and FAT and between AFK and PROT were − 0.09 ± 0.24 and − 0.17 ± 0.25, respectively; and genetic correlations between AFK and %FAT and between AFK and %PROT were 0.29 ± 0.35 and 0.14 ± 0.27, respectively. Selection for milk traits is possible using a repeatability animal model. Selection for milk production traits would probably not increase AFK, but more precise estimates of the genetic correlations are required. Selection to lower AFK is possible. These (co)variance estimates would make it possible to predict the selection responses from different economic indices in order to maximize the economic responses for the local markets.     

Linear–threshold animal model for birth weight, gestation length and calving ease in United Kingdom Limousin beef cattle data

Breeding value evaluation for UK Limousin beef cattle data was carried out by multiple-trait linear–threshold animal model with variance components assumed to be known. Polychotomous calving ease with five categories was analysed with two continuous traits: birth weight and gestation length. Field data consisted of 220,799 animals with observations with every possible combination of traits, and 270,035 animals in the pedigree. The threshold model was solved either with Newton Raphson or Expectation Maximisation algorithm, and solutions were compared to evaluation by a linear model with original and normalised scores. There were insignificant differences in solutions between the two algorithms for threshold model analyses. Furthermore, solutions of the continuous traits were similar by the threshold and linear models. For the categorical trait, correlations for random effects from the threshold and linear models were high. In case of normalised scores (original scores case in brackets) correlations with solutions from the threshold and linear model were 0.97 (0.94) and 0.97 (0.93) for direct and maternal genetic effects and 0.95 (0.89) for permanent maternal effects. Even so, at least one third of the top 1% ranking of bulls differed between the linear and the threshold models. Predictive abilities as correlations between estimated breeding values and pedigree indices were almost equal between the linear and threshold models for both continuous and categorical traits. In conclusion, despite the higher computational demand, the linear–threshold animal model can be seen worthwhile in the genetic evaluation of the national UK beef cattle data set.     

Prevalence of porcine reproductive and respiratory syndrome virus detection in aborted fetuses,mummified fetuses and stillborn piglets using quantitative polymerase chain reaction

The objective of the present study was to investigate the prevalence of porcinereproductive and respiratory syndrome (PRRS) virus detection in aborted fetuses (n=32),mummified fetuses (n=30) and stillborn piglets (n=27) from 10 swine herds in Thailandusing quantitative polymerase chain reaction (qPCR). Pooled organs and umbilical cord fromeach fetus/piglet were homogenized and subjected to RNA extraction and cDNA synthesis. TheqPCR was carried out on the ORF7 of the PRRS viral genome using fluorogenic probes foramplified product detection. The results revealed that 67.4% (60/89) of the specimenscontained PRRS virus. The virus was found in 65.6% (21/32) of aborted fetuses, 63.3%(19/30) of mummified fetuses and 74.1% (20/27) of stillborn piglets(P=0.664). Genotype 1, genotype 2 and mixed genotypes of PRRS virus weredetected in 19.1% (17/89), 25.8% (23/89) and 22.5% (20/89) of the specimens, respectively(P=0.316). PRRS virus antigen was retrieved from bothnon-PRRS-vaccinated herds (68.2%, 45/66) and PRRS-vaccinated herds (65.2%, 15/23)(P=0.794). These findings indicated that these specimens are importantsources of the PRRS viral load and the viral shedding within the herd. Thus, intensivecare on the routine management of dead fetuses and stillborn piglets in PRRSvirus-positive herds should be emphasized.     

Genetic parameters for litter size,piglet growth and sow's early growth and body composition in the Chinese–European line Tai Zumu

Genetics of piglet growth in association with sow's early growth and body composition were estimated in the Tai Zumu line. Piglet and sow's litter growth traits were calculated from individual weights collected at birth and at 3 weeks of age. Sow's litter traits included the number of piglets born alive (NBA), the mean piglet weight (MW) and the standard deviation of weights within the litter (SDW). Sow's early growth was measured by the age at 100 kg (A₁₀₀), and body composition included backfat thickness (BF₁₀₀). A main objective of this study was to estimate separately the direct genetic effect (d) and the maternal genetic effect (m) on piglet weight and daily weight gain during lactation. Variance components were estimated using the restricted maximum likelihood methodology based on animal models. The heritability estimates were 0.19 for NBA, 0.15 and 0.26 for SDW and MW at 3 weeks and 0.42 and 0.70 for A₁₀₀ and BF₁₀₀. The NBA was almost independent from SDW. Conversely, the A₁₀₀ and BF₁₀₀ were correlated unfavourably with SDW (r_g<−0.24, SE<0.12). A stronger selection for litter size should have little effect on litter homogeneity in weights. Selection for lean growth rate tends to favour heterogeneity in weights. The direct effect on piglet weight at birth and daily weight gain accounted for 12% (h² (d) = 0.02) and 50% (h² (d) = 0.11) of the genetic variance, respectively. The association between d and m for piglet weight was not different from zero at birth (r_g = 0.19, SE = 0.27), but a strong antagonism between d and m for daily weight gain from birth to 3 weeks was found (r_g = −0.41, SE = 0.17). Substantial direct and maternal genetic effects influenced piglet growth until weaning in opposite way.     

Estimation of direct and maternal genetic parameters for growth and carcass traits in a herd of Japanese Black cattle in Miyagi prefecture, using a multitrait animal model

Data from 1170 records of fattening calves were collected on growth and carcass traits from a Japanese Black cattle herd located in Miyagi prefecture, Japan. The objective was to determine direct and maternal heritabilities, direct and maternal genetic correlations and phenotypic correlations between bodyweight at the beginning of the fattening period (BWS), bodyweight at the end of the fattening period (BWF), carcass weight (CW), average daily gain during the fattening period (ADG), rib eye area (REA), rib thickness, subcutaneous backfat thickness (SFT), yield estimate (YE) and beef marbling score (BMS). Direct heritability estimates of 0.16 (SFT) and 0.07 (BMS) were low, whereas estimates of the other traits were medium to high and ranged between 0.44 (REA) and 0.78 (CW). Direct genetic correlations were all positive, except those that were between BWS and SFT, and between BWS and YE (?0.49 and ?0.14, respectively). The lowest positive genetic correlation was between BWS and BMS (0.04) and the highest was between BWF and CW (0.99). The phenotypic correlation coefficients ranged between ?0.41 (between SFT and YE) and 0.96 (between BWF and CW). Maternal heritability estimates were generally low and ranged between 0.00 for BMS and 0.08 for BWS, CW and ADG. Selection programs comprising information on growth and carcass traits of calves and maternal traits of dams were suggested.     

Sensitivity of breeding values for carcass traits of meat‐type quail to changes in dietary (methionine + cystine):lysine ratio using reaction norm models

Our objective was to evaluate changes in breeding values for carcass traits of two meat‐type quail (Coturnix coturnix) strains (LF1 and LF2) to changes in the dietary (methionine + cystine):lysine ([Met + Cys]:Lys) ratio due to genotype by environment (G × E) interaction via reaction norm. A total of 7000 records of carcass weight and yield were used for analyses. During the initial phase (from hatching to day 21), five diets with increasing (Met + Cys):Lys ratios (0.61, 0.66, 0.71, 0.76 and 0.81), containing 26.1% crude protein and 2900 kcal ME/kg, were evaluated. Analyses were performed using random regression models that included linear functions of sex (fixed effect) and breeding value (random effect) for carcass weight and yield, without and with heterogeneous residual variance adjustment. Both fixed and random effects were modelled using Legendre polynomials of second order. Genetic variance and heritability estimates were affected by both (Met + Cys):Lys ratio and strain. We observed that a G × E interaction was present, with changes in the breeding value ranking. Therefore, genetic evaluation for carcass traits should be performed under the same (Met + Cys):Lys ratio in which quails are raised.     

Uterine serpin (SERPINA 14) correlates negatively with cytokine production at the foetal–maternal interface but not in the corpus luteum in pregnant dairy heifers experimentally infected with Neospora caninum

This study examines gene expression patterns in dairy heifers experimentally infected with N. caninum during on Day 110 of pregnancy with live foetuses at euthanasia, 42 days later. The study population was constituted of four non‐infected controls and three infected dams. Gene expression was determined on gamma interferon (IFNγ), (Th1 pro‐inflammatory cytokine), interleukin‐4 (IL4) (Th2 pro‐gestation cytokine) or interleukin‐10 (IL10) (T regulatory cytokine) and the serine peptidase inhibitor SERPINA14 in intercaruncular, placental, uterine lymph node (UTLN) and luteal tissue samples. Intercaruncular SERPINA14 expression was negatively correlated with IFNγ expression in cotyledon samples and with IL4 expression in UTLN. No relationships were detected between cytokine gene expression at the foetal–maternal interface and SERPINA14 expression in the luteal samples. Our findings suggest that gene expression of the uterine serpin SERPINA14 correlates negatively with the expression of Th1 and Th2 cytokines at the foetal–maternal interface but not in the corpus luteum.