Genetic relationships among traits related to reproduction and growth of Nelore females

The objective of the study presented here was to analyze the genetic relationships among heifer pregnancy (HP), age at first calving (AFC), stayability (STAY), average annual productivity of the cow, in kilograms of weaned calf per cow per year (PRODAM), postweaning weight gain (PWG), and hip height (HH) of Nelore females from 12 Brazilian herds. (Co)variance components were obtained by six-trait animal model using Gibbs sampling. The posterior mean of the heritability estimates were 0.37, 0.18, 0.19, 0.16, 0.21, and 0.37 for HP, AFC, STAY, PRODAM, PWG, and HH, respectively. In general, the genetic correlations were strong between traits related to reproduction, for example, −0.85 between HP and AFC, and 0.94 between STAY and PRODAM. Weak genetic correlations were obtained between reproductive and growth traits (absolute values ranging from 0.02 to 0.30). Although weak, the genetic correlations between PWG and reproductive traits were favorable, whereas the genetic correlations between HH and reproductive traits were close to zero and slightly unfavorable for HP, AFC, and STAY. An increase of HH is therefore expected to have little or no negative effect on the reproductive performance of females. The posterior mean of genetic correlation between PWG and HH was moderate (0.50). On the basis of the heritability, genetic correlation estimates, and time to obtain data, HP and PRODAM seems to show the best potential as selection criteria to improve the productive and reproductive performance of Nelore females. In principle, it is possible to select for increased PWG without compromising the reproduction of Nelore females. However, selection for PWG may result in an increase of female HH as a correlated response, a fact that could increase management costs in advanced generations of selection. In the light of the results, all traits studied here can be used as selection criteria and there is no strong evidence of genetic antagonism among traits related to reproduction and growth of Nelore females.     

Two-trait random regression model to estimate the genetic association of scrotal circumference with female reproductive performance in Nelore cattle

In an attempt to determine when scrotal circumference (SC) could be a reasonable indicator of female reproductive performance, a series of two-trait random regression model (regression for SC on age at measurement) using Gibbs sampling was applied to field data of Nelore cattle raised in a tropical environment. The female traits evaluated were age at first calving (AFC), first calving interval (FCI), heifer pregnancy (HP), and stayability (STAY). The posterior means of heritability of female traits ranged from 0.15 for AFC to 0.46 for HP and were about 0.50 for SC. The posterior means of genetic correlations between SC and AFC, FCI, HP, STAY were up to −0.70, −0.25, 0.48, and 0.29, respectively. Genetically, SC could be a reasonable indicator of female puberty (e.g., HP) as long as it is measured at a young age (400–440 days). However, for female reproductive traits measured at an older age (e.g., STAY), SC is merely a modest or even poor indicator. The use of sire expected progeny differences for female reproductive traits will be more effective than the use of expected progeny differences for SC to improve the reproductive performance of female cattle.     

Genetic relationship among reproductive traits in Nellore cattle

In order to achieve improvements in production efficiency in livestock, herds of high sexual precocity and good fertility are needed. These traits increase the availability of animals in herd, either for sale or selection, allowing both greater selective intensity and greater genetic progress. This study aimed at estimating genetic parameters for reproductive traits measured directly in females in order to verify whether they could be used as selection criteria for genetic improvement in Nellore cows, as well as estimating the genetic relationship among these traits and scrotal circumference (SC), the traditional selection criterion for sexual precocity in cattle. In addition to SC, stayability (STAY), number of calvings at 53 months (NC53) and heifers rebreeding (HR) were studied. The (co)variances and genetic parameters were estimated using Bayesian inference. STAY, NC53 and HR were analyzed assuming a threshold model, whereas SC was analyzed with a linear model. Heritability estimated for NC53 was 0.22, and this trait was strongly and positively correlated with STAY, meaning selection for NC53 would improve productive longevity of Nellore cows. Correlations estimated between HR and STAY (≈0.97) and between HR and NC53 (≈0.99) allow an improvement on HR rates if selection was applied to traits related to longevity. Genetic correlations among SC and female reproductive traits were positive but weak, suggesting the need to use reproductive traits directly measured in females in order to obtain greater improvements in sexual precocity and longevity.     

Genetic correlation between heifer pregnancy and scrotal circumference measured at 15 and 18 months of age in Nellore cattle

Data of pregnancy diagnosis from 24,945 Nellore heifers, raised under tropical conditions in Brazil and exposed to breeding at about 14 months of age, were analyzed simultaneously with 13,742 (analysis 1), 36,091 (analysis 2), 8,405 (analysis 3), and 8,405 (analysis 4) scrotal circumference (SC) records of contemporary young bulls in order to estimate heritability (h(2)) for yearling heifer pregnancy (HP) and for SC measured at around 15 (SC15) and 18 (SC18) months of age and to estimate genetic correlation between HP and SC15 (SC18). Heifer pregnancy was considered as a categorical trait, with the value 1 (success) assigned to heifers that were detected as pregnant by rectal palpation approximately 60 days after the end of a 90-day breeding season and the value 0 (failure) otherwise. In analyses 1 and 3, SC was measured at around 15 months of age and in analysis 2 and 4 it was measured at around 18 months of age. Only 8,848 animals from datasets 1 and 2 were common in both files, which means the same animals measured at different ages. Datasets used in analyses 3 and 4 included the same animals, measured at 15 and at 18 months of age, respectively. Heritability estimates for HP were similar in all analyses, with values ranging from 0.66 +/- 0.08 to 0.67 +/- 0.008. For SC15, the estimates were 0.57 +/- 0.05 in analysis 1 and 0.60 +/- 0.07 in analysis 3. For SC18, the estimates were 0.53 +/- 0.03 in analysis 2 and 0.64 +/- 0.06 in analysis 4. The estimates of genetic correlation between HP and SC15 were 0.15 +/- 0.10 in analysis 1 and 0.11 +/- 0.11 in analysis 3. For the correlation between HP and SC18, the values were 0.27 +/- 0.10 in analysis 2 and 0.16 +/- 0.11 in analysis 4. Based on standard errors and confidence intervals, the best heritability and genetic correlation estimates were obtained from analysis 2, which included more data and a better pedigree structure. Pearson correlation between HP and SC breeding values was similar to the genetic correlation estimates obtained from two-trait models, when all animals in the pedigree file were considered for its calculation. If only sires were considered for the calculation, Pearson correlation was higher but the pattern was the same as from two-trait analyses. The high heritability estimates obtained in the present study confirm that expected progeny difference (EPD) for HP can be used to select bulls for the production of precocious daughters and that the low genetic correlation between SC and HP indicates a greater efficacy of selection based on heifer pregnancy EPD than of selection based on scrotal circumference EPD. The results of the present study, although not conclusive, indicate that SC measured at around SC18 would have a higher genetic correlation with HP than would SC measured at around SC15.     

Genetic parameters and environmental effects on temperament score and reproductive traits of Nellore cattle

Animal temperament is a trait of economic relevance and its use as a selection criterion requires the identification of environmental factors that influence this trait, as well as the estimation of its genetic variability and interrelationship with other traits. The objectives of this study were to evaluate the effect of the covariates dam age at calving (ADC), long yearling age (YA) and long yearling weight (YW) on temperament score (T) and to estimate genetic parameters for T, scrotal circumference (SC) at long YA and age at first calving (AFC) in Nellore cattle participating in a selection program. The traits were analyzed by the restricted maximum likelihood method under a multiple-trait animal model. For all traits, contemporary group was included as a fixed effect and additive genetic and residual as random effects. In addition to these effects, YA, YW and ADC were considered for analyzing T. In the case of SC and AFC, the effect of long YW was included as a covariate. Genetic parameters were estimated for and between traits. The three covariates significantly influenced T. The heritability estimates for T, SC and AFC were 0.18 ± 0.02, 0.53 ± 0.04 and 0.23 ± 0.08, respectively. The genetic correlations between T and SC, and T and AFC were -0.07 ± 0.17 and -0.06 ± 0.19, respectively. The genetic correlation estimated between SC and AFC was -0.57 ± 0.16. In conclusion, a response to selection for T, SC and AFC is expected and selection for T does not imply correlated responses with the other traits.     

Genome‐enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods

This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregnancy (EP) and stayability (STAY). The numbers of genotyped animals and SNP markers available were 2342 and 321 419 (AFC), 4671 and 309 486 (SC), 2681 and 319 619 (STAY) and 3356 and 319 108 (EP). Predictive ability of support vector regression (SVR), Bayesian regularized artificial neural network (BRANN) and random forest (RF) were compared with results obtained using parametric models (genomic best linear unbiased predictor, GBLUP, and Bayesian least absolute shrinkage and selection operator, BLASSO). A 5‐fold cross‐validation strategy was performed and the average prediction accuracy (ACC) and mean squared errors (MSE) were computed. The ACC was defined as the linear correlation between predicted and observed breeding values for categorical traits (EP and STAY) and as the correlation between predicted and observed adjusted phenotypes divided by the square root of the estimated heritability for continuous traits (AFC and SC). The average ACC varied from low to moderate depending on the trait and model under consideration, ranging between 0.56 and 0.63 (AFC), 0.27 and 0.36 (SC), 0.57 and 0.67 (EP), and 0.52 and 0.62 (STAY). SVR provided slightly better accuracies than the parametric models for all traits, increasing the prediction accuracy for AFC to around 6.3 and 4.8% compared with GBLUP and BLASSO respectively. Likewise, there was an increase of 8.3% for SC, 4.5% for EP and 4.8% for STAY, comparing SVR with both GBLUP and BLASSO. In contrast, the RF and BRANN did not present competitive predictive ability compared with the parametric models. The results indicate that SVR is a suitable method for genome‐enabled prediction of reproductive traits in Nellore cattle. Further, the optimal kernel bandwidth parameter in the SVR model was trait‐dependent, thus, a fine‐tuning for this hyper‐parameter in the training phase is crucial.     

Heritability estimates and genetic correlations for body weight and scrotal circumference adjusted to 12 and 18 months of age for male Nellore cattle

Heritability estimates and genetic correlations were obtained for body weight and scrotal circumference, adjusted, respectively, to 12 (BW12 and SC12) and 18 (BW18 and SC18) months of age, for 10 742 male Nellore cattle. The adjustments to SC12 and SC18 were made using a nonlinear logistic function, while BW12 and BW18 were obtained by linear adjustment. The contemporary groups (CGs) were defined from animals born on the same farm, in the same year and birth season. The mean heritability estimates obtained using the restricted maximum likelihood method in bi-trait analysis were 0.25, 0.25, 0.29 and 0.42 for BW12, BW18, SC12 and SC18, respectively. The genetic correlations were 0.30 ± 0.11, 0.21 ± 0.13, 0.21 ± 0.11, -0.08 ± 0.15, 0.16 ± 0.12 and 0.89 ± 0.04 between the traits BW12 and BW18; BW12 and SC12; BW12 and SC18; BW18 and SC12; BW18 and SC18; and SC12 and SC18. The heritability for SC18 was considerably greater than for SC12, suggesting that this should be included as a selection criterion. The genetic correlation between BW18 and SC12 was close to zero, indicating that these traits did not influence each other. The contrary occurred between SC12 and SC18, indicating that selection using one of these could alter the other. Because of the mean magnitudes of heritabilities in the various measurements of weight and scrotal perimeter, it is suggested that the practice of individual selection for these traits is possible.     

Genetics of crossbred sow longevity

The aim of this study was to estimate genetic parameters for longevity from Swedish crossbred sows to investigate the possibilities of selecting for this trait. Data were collected from 16 commercial piglet-producing herds, on crossbred (Landrace × Yorkshire) sows farrowing in the period 1 January 2001 to 31 December 2004. The data set with records on 10 373 sows was split into two sets according to the breed of the sire, i.e. Landrace sires (LS) or Yorkshire sires (YS). Removal hazard during productive life (PL) was analysed with survival analysis, using a sire model. Stayability from first to second litter (STAY12), stayability from first to third litter (STAY13), length of productive life (LPL) and lifetime production (LTP) were analysed with linear models, using an animal model. Females after the worst sire had 1.7 times higher (progeny of LS) and 2.4 times higher (progeny of YS) risk of removal than females after the best sire. Heritability for PL was estimated at 0.06 (LS) and 0.12 (YS). The heritabilities for the linear longevity traits ranged from 0.03 to 0.08. Genetic correlations between the four linear longevity traits were all high and positive (0.6 to 1.0), as were the phenotypic correlations (0.5 to 0.8). The correlations (Spearman rank) between the sire's estimated breeding values for all the five longevity traits were all significant (P < 0.001) and moderate to strong in both data sets. Estimated breeding value (EBV) correlations between the five longevity traits and traits included in the present Swedish breeding evaluation (Quality Genetics (QG)) were significant in a few cases. Significant and favourable EBV correlations were found between age at first farrowing and both STAY12 and STAY13 (-0.20 and -0.31), as well as between litter weight at 3 weeks and LPL and LTP (0.13 to 0.20). Significant and unfavourable EBV correlations were found between age at 100 kg and STAY12 (0.32), as well as between the exterior conformation score from testing station and PL (-0.20). The level of the estimated heritabilities for longevity indicates that genetic improvement of sow longevity would be possible. However, overall, there was no strong indirect selection for sow longevity with the current Swedish breeding evaluation (QG).     

Genetic parameters and relationships between growth traits and scrotal circumference measured at different ages in Nellore cattle

Records from 106,212 Nellore animals, born between 1998 and 2006, were used to estimate (co)variance components and genetic parameters for birth weight (BW), average weight gains from birth to weaning (GBW), average weight gains from weaning to after yearling (GWAY), weaning hip height (WHH), postweaning hip height (PHH) and scrotal circumferences at 9 (SC9), 12 (SC12) and 15 (SC15) months of age. (Co)variance components were estimated by an animal model using multi-trait analysis. Heritability estimates for BW, GBW, GWAY, WHH, PHH, SC9, SC12 and SC15 were 0.31 ± 0.01; 0.25 ± 0.02; 0.30 ± 0.04; 0.51 ± 0.04; 0.54 ± 0.04; 0.39 ± 0.01; 0.41 ± 0.01 and 0.44 ± 0.02, respectively. Genetic correlations between growth traits ranged from 0.09 ± 0.01 to 0.88 ± 0.01, thereby implying that, at any age, selection to increase average weight gains will also increase stature. Genetic correlations between BW and average weight gains with scrotal circumferences were all positive and moderate (0.15 ± 0.03 to 0.38 ± 0.01). On the other hand, positive and low genetic associations were estimated between hip height and scrotal circumference at different ages (0.09 ± 0.01 to 0.17 ± 0.02). The results of this study pointed out that selection to larger scrotal circumferences in males will promote changes in average weight gains. In order to obtain Nellore cattle with the stature and size suitable for the production system, both weight gain and hip height should be included in a selection index.     

Genetic correlations between mature cow weight and productive and reproductive traits in Nellore cattle

We investigated genetic associations between mature cow weight (MW) and weaning weight (WW), yearling weight (YW), weight gain from birth to weaning (GBW), weight gain from weaning to yearling (GWY), weaning hip height (WHH), yearling hip height (YHH), scrotal circumference (SC), and age at first calving (AFC). Data from 127,104 Nellore animals born between 1993 and 2006, belonging to Agropecuária Jacarezinho Ltda., were analyzed. (Co)variance components were obtained by the restricted maximum likelihood method, applying an animal model in a multi-traits analysis. The model included direct genetic and residual effects as random effects, the fixed effects of contemporary group, and the linear and quadratic effects of animal age at recording (except for AFC, GBW, and GWY) and age of cow at calving as covariates (except for MW). The numbers of days from birth to weaning and from weaning to yearling were included as covariates for GBW and GWY, respectively. Estimated direct heritabilities were 0.43 ± 0.02 (MW), 0.33 ± 0.01 (WW), 0.36 ± 0.01 (YW), 0.28 ± 0.02 (GBW), 0.31 ± 0.01 (GWY), 0.44 ± 0.02 (WHH), 0.48 ± 0.02 (YHH), 0.44 ± 0.01 (SC), and 0.16 ± 0.03 (AFC). Genetic correlations between MW and productive traits were positive and of medium to high magnitude (ranging from 0.47 ± 0.03 to 0.71 ± 0.01). A positive and low genetic correlation was observed between MW and SC (0.24 ± 0.04). A negative genetic correlation (-0.19 ± 0.03) was estimated between MW and AFC. Selection to increase weight or weight gains at any age, as well as hip height, will change MW in the same direction. Selection for higher SC may lead to a long-term increase in MW. The AFC can be included in selection indices to improve the reproductive performance of beef cattle without significant changes in MW.     

Comparison among three approaches for evaluation of sexual precocity in Nellore cattle

Restricted breeding seasons used in beef cattle produce censored data for reproduction traits measured in regard to these seasons. To analyze these data, adequate methods must be used. The objective of this paper was to compare three approaches aiming to evaluate sexual precocity in Nellore cattle. The final data set contained 6699 records of age at first conception (AFC14) (in days) and of heifer pregnancy (HP14) (binary) obtained from females exposed to the bulls for the first time at about 14 months of age. Records of females that did not calve in the following year after being exposed to a sire were considered censored (77.5% of total). The models used to obtain genetic parameters and expected progeny differences (EPDs) were a Weibull mixed and a censored linear model for AFC14 and threshold model for HP14. The mean heritabilities obtained were 0.76 and 0.44, respectively, for survival and censored linear models (for AFC14), and 0.58 for HP14. Ranking and Pearson correlations varied (in absolute values) from 0.54 to 0.99 (considering different percentages of sires selected), indicating moderate changes in the classification. Considering survival analysis as the best selection criterion (that would result in the best response to selection), it was observed that selection for HP14 would lead to a more significant decrease in selection response if compared with selection for AFC14 analysed by censored linear model, from which results were very similar to the survival analysis.     

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer’s early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal’s sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme—dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme—low EC (−3.0 and −1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28–0.56 for SC and 0.26–0.49 for HP, using RNM_H, and 0.26–0.52 for SC and 0.22–0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (−3.0) and favorable (3.0) EC levels were 0.30 for HP and −0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals’ genetic merit and re-ranking of animals on different environmental conditions. SNP marker–environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.     

Responses of prolactin and hair growth to selection for age at puberty in Angus cattle

A trial was carried out over a 7-year period (1999 to 2005 calf crops) to compare indicators of seasonality in Angus cattle, which were part of a long-term genetic selection experiment. Divergent selection was applied for early ('AGE-') or late ('AGE+') age at puberty (AP) in heifers, and selection lines differed over the 7-year period by 62 days (15% of the mean). The primary measures of seasonality studied in 629 heifer progeny (59 sire groups) were serum concentration of prolactin (PRL), and winter and summer hair growth. Serial samples were obtained for PRL from 11 to 18 months of age, and data were analysed with adjustment for cortisol concentration. Using restricted maximum likelihood procedures with an animal model, heritability estimates were: AP, 0.26 ± 0.03; log(e)PRL concentration, 0.23 ± 0.07; log(e)cortisol concentration, 0.22 ± 0.07; hair weight, 0.21 ± 0.04; and hair length, 0.09 ± 0.05. Corresponding repeatability estimates for the last four traits were 0.49 ± 0.03, 0.38 ± 0.03, 0.21 ± 0.04, and 0.64 ± 0.02, respectively. The genetic correlation between AP and log(e)PRL concentration was estimated at -0.29 ± 0.13 (P < 0.05). PRL concentration in the AGE- line after passing through puberty was 11 ± 5% lower than in the AGE+ line (P < 0.05). Line effects were not significant for hair weight or hair length. It was concluded that divergent selection for AP changed PRL concentration, which may partly reflect sensitivity to changing day length.     

Estimates of (co)variance components and genetic parameters for body weights and first greasy fleece weight in Bharat Merino sheep

(Co)variance components and genetic parameters of weight at birth (BWT), weaning (3WT), 6, 9 and 12 months of age (6WT, 9WT and 12WT, respectively) and first greasy fleece weight (GFW) of Bharat Merino sheep, maintained at Central Sheep and Wool Research Institute, Avikanagar, Rajasthan, India, were estimated by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. Data were collected over a period of 10 years (1998 to 2007). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for BWT, 3WT, 6WT, 9WT and 12WT and first GFW were 0.05 ± 0.03, 0.04 ± 0.02, 0.00, 0.03 ± 0.03, 0.09 ± 0.05 and 0.05 ± 0.03, respectively. There was no evidence for the maternal genetic effect on the traits under study. Maternal permanent environmental effect contributed 19% for BWT and 6% to 11% from 3WT to 9WT and 11% for first GFW. Maternal permanent environmental effect on the post-3WT was a carryover effect of maternal influences during pre-weaning age. A low rate of genetic progress seems possible in the flock through selection. Direct genetic correlations between body weight traits were positive and ranged from 0.36 between BWT and 6WT to 0.94 between 3WT and 6WT and between 6WT and 12WT. Genetic correlations of 3WT with 6WT, 9WT and 12WT were high and positive (0.94, 0.93 and 0.93, respectively), suggesting that genetic gain in post-3WT will be maintained if selection age is reduced to 3 months. The genetic correlations of GFW with live weights were 0.01, 0.16, 0.18, 0.40 and 0.32 for BWT, 3WT, 6WT, 9WT and 12WT, respectively. Correlations of permanent environmental effects of the dam across different traits were high and positive for all the traits (0.45 to 0.98).     

Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference

Background

An important goal of Zebu breeding programs is to improve reproductive performance. A major problem faced with the genetic improvement of reproductive traits is that recording the time for an animal to reach sexual maturity is costly. Another issue is that accurate estimates of breeding values are obtained only a long time after the young bulls have gone through selection. An alternative to overcome these problems is to use traits that are indicators of the reproductive efficiency of the herd and are easier to measure, such as age at first calving. Another problem is that heifers that have conceived once may fail to conceive in the next breeding season, which increases production costs. Thus, increasing heifer’s rebreeding rates should improve the economic efficiency of the herd. Response to selection for these traits tends to be slow, since they have a low heritability and phenotypic information is provided only later in the life of the animal. Genome-wide association studies (GWAS) are useful to investigate the genetic mechanisms that underlie these traits by identifying the genes and metabolic pathways involved.

Results

Data from 1853 females belonging to the Agricultural Jacarezinho LTDA were used. Genotyping was performed using the BovineHD BeadChip (777 962 single nucleotide polymorphisms (SNPs)) according to the protocol of Illumina - Infinium Assay II ® Multi-Sample HiScan with the unit SQ ™ System. After quality control, 305 348 SNPs were used for GWAS. Forty-two and 19 SNPs had a Bayes factor greater than 150 for heifer rebreeding and age at first calving, respectively. All significant SNPs for age at first calving were significant for heifer rebreeding. These 42 SNPs were next or within 35 genes that were distributed over 18 chromosomes and comprised 27 protein-encoding genes, six pseudogenes and two miscellaneous noncoding RNAs.

Conclusions

The use of Bayes factor to determine the significance of SNPs allowed us to identify two sets of 42 and 19 significant SNPs for heifer rebreeding and age at first calving, respectively, which explain 11.35 % and 6.42 % of their phenotypic variance, respectively. These SNPs provide relevant information to help elucidate which genes affect these traits.     

Genetic associations between weight at maturity and maturation rate with ages and weights at first and second calving in Canchim beef cattle

Genetic parameters for weight at maturity (WM), maturation rate (MR), age and weight at first calving (AFC and WFC) and second calving (ASC and WSC) were estimated for females of the Canchim breed. The number of records per trait ranged from 1440 to 1923. The restricted maximum likelihood method was used and the statistical model included the fixed effect of contemporary group and the additive genetic and residual as random effects. The mean heritability estimate and respective standard errors were 0.34±0.05 (WM), 0.13±0.04 (MR), 0.14±0.04 (AFC), 0.44±0.06 (WFC), 0.16±0.06 (ASC) and 0.39±0.06 (WSC). The heritability estimate for WM and MR suggested that it would be possible to achieve changes in the animals' growth curve through selection, but the genetic correlation between these two traits suggested that there would be antagonism between them. Selection for WM would result in animals with later growth and would also affect individuals' sexual precocity. This was also seen from the genetic correlations between WM and the other traits, which ranged from 0.37 to 0.98; and between MR and the other traits, which ranged from -0.83 to -0.25. Selection to modify WM would be expected to result in correlated responses in AFC, WFC and WSC and a moderate response in ASC. Although the heritability estimate for MR was low, selection aimed for its increase might cause a large decrease in AFC, ASC and WFC and a moderate change in WSC, and this could be an alternative for improving the progeny's overall performance.     

Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping

The objective of this study was to estimate genetic and phenotypic correlations of body weight at 6 weeks of age (BW6), as well as final carcass yield, and moisture, protein, fat and ash contents, using data from 3,422 F2 chickens originated from reciprocal cross between a broiler and a layer line. Variance components were estimated by the REML method, using animal models for evaluating random additive genetic and fixed contemporary group (sex, hatch and genetic group) effects. The heritability estimates (h(2)) for BW6, carcass yield and percentage of carcass moisture were 0.31 ± 0.07, 0.20 ± 0.05 and 0.33 ± 0.07, respectively. The h(2) for the percentages of protein, fat and ash on a dry matter basis were 0.48 ± 0.09, 0.55 ± 0.10 and 0.36 ± 0.08, respectively. BW6 had a positive genetic correlation with fat percentage in the carcass, but a negative one with protein and ash contents. Carcass yield, thus, appears to have only low genetic association with carcass composition traits. The genetic correlations observed between traits, measured on a dry matter basis, indicated that selection for carcass protein content may favor higher ash content and a lower percentage of carcass fat.     

Correlated responses of growth traits to selection for high and low plasma alkaline phosphatase in mice

Summary The effectiveness of two way selection for plasma alkaline phosphatase (ALP) was investigated in order to determine its influences on growth traits through thirteen generations. The responses of the two lines selected for high (HP) and low (LP) ALP at 45 days of age were compared to that of the mice selected for large (L) and small (SM) body size. The selection responses of plasma ALP were very effective for both HP and LP lines, with average responses per generation calculated from linear regressions of 0.227±0.037 and –0.088±0.022 respectively. The final levels of ALP in HP and LP were 5.54±0.71 and 1.27±0.20 in the thirtheenth generation, while the SM, L and base population had levels of 3.49±0.08, 0.86±0.55 and 2.77±0.56 respectively. The body weight at 45 days of age in LP (31.4±1.4 g) as a correlated response was significantly higher than HP (23.4±1.8 g) at generation 10. The correlated response of milk yield, measured by weight gain up to 12 days of age, was significantly greater in the LP line than in HP, but the correlated response of gains after weaning was not so different as the response of milk yield. The response of litter size and weight in LP showed significant higher levels than that of HP, but pups' birth weight did not differ between LP and HP. It is suggested that the correlated response of milk yield contributed more to the divergence of body size between HP and LP than the gain after weaning.Realized heritabilities of ALP were 0.335±0.059 (HP) and 0.279±0.051 (LP). Realized genetic correlations between ALP and 45 days' body weight were –0.27±0.13 (HP with SM) and –0.52±0.19 (LP with L). Realized genetic correlations between ALP and milk yield were –0.95±0.03 (HP) and –0.37±0.29 (LP). Correlations between ALP and postweaning gains were fairly low.     

Genetic parameters for five traits in Africanized honeybees using Bayesian inference

Heritability and genetic correlations for honey (HP) and propolis production (PP), hygienic behavior (HB), syrup-collection rate (SCR) and percentage of mites on adult bees (PMAB) of a population of Africanized honeybees were estimated. Data from 110 queen bees over three generations were evaluated. Single and multi-trait models were analyzed by Bayesian Inference using MTGSAM. The localization of the hive was significant for SCR and HB and highly significant for PP. Season-year was highly significant only for SCR. The number of frames with bees was significant for HP and PP, including SCR. The heritability estimates were 0.16 for HP, 0.23 for SCR, 0.52 for HB, 0.66 for PP, and 0.13 for PMAB. The genetic correlations were positive among productive traits (PP, HP and SCR) and negative between productive traits and HB, except between PP and HB. Genetic correlations between PMAB and other traits, in general, were negative, except with PP. The study permitted to identify honeybees for improved propolis and honey production. Hygienic behavior may be improved as a consequence of selecting for improved propolis production. The rate of syrup consumption and propolis production may be included in a selection index to enhance honeybee traits.