RNA sequencing differential gene expression analysis of isolated perfused bovine udders experimentally inoculated with Streptococcus agalactiae.

The aim of this study was to elucidate the differential gene expression in the RNA sequencing transcriptome of isolated perfused udders collected from 4 slaughtered Holstein × Zebu crossbred dairy cows experimentally inoculated with Streptococcus agalactiae. We studied 3 different statistical tools (edgeR, baySeq, and Cuffdiff 2). In summary, 2 quarters of each udder were experimentally inoculated with Strep. agalactiae and the other 2 were used as a control. Mammary tissue biopsies were collected at times 0 and 3 h after infection. The total RNA was extracted and sequenced on an Illumina HiSeq 2000 (Illumina Inc., San Diego, CA). Transcripts were assembled from the reads aligned to the bovine UMD 3.1 reference genome, and the statistical analyses were performed using the previously mentioned tools (edgeR, baySeq, and Cuffdiff 2). Finally, the identified genes were submitted to pathway enrichment analysis. A total of 1,756, 1,161, and 3,389 genes with differential gene expression were identified when using edgeR, baySeq, and Cuffdiff 2, respectively. A total of 122 genes were identified by the overlapping of the 3 methods; however, only the platelet activation presented a significantly enriched pathway. From the results, we suggest the FCER1G, GNAI2, ORAI1, and VASP genes shared among the 3 methods in this pathway for posterior biological validation.

Runs of homozygosity: current knowledge and applications in livestock.

This review presents a broader approach to the implementation and study of runs of homozygosity (ROH) in animal populations, focusing on identifying and characterizing ROH and their practical implications. ROH are continuous homozygous segments that are common in individuals and populations. The ability of these homozygous segments to give insight into a population's genetic events makes them a useful tool that can provide information about the demographic evolution of a population over time. Furthermore, ROH provide useful information about the genetic relatedness among individuals, helping to minimize the inbreeding rate and also helping to expose deleterious variants in the genome. The frequency, size and distribution of ROH in the genome are influenced by factors such as natural and artificial selection, recombination, linkage disequilibrium, population structure, mutation rate and inbreeding level. Calculating the inbreeding coefficient from molecular information from ROH (FROH ) is more accurate for estimating autozygosity and for detecting both past and more recent inbreeding effects than are estimates from pedigree data (FPED ). The better results of FROH suggest that FROH can be used to infer information about the history and inbreeding levels of a population in the absence of genealogical information. The selection of superior animals has produced large phenotypic changes and has reshaped the ROH patterns in various regions of the genome. Additionally, selection increases homozygosity around the target locus, and deleterious variants are seen to occur more frequently in ROH regions. Studies involving ROH are increasingly common and provide valuable information about how the genome's architecture can disclose a population's genetic background. By revealing the molecular changes in populations over time, genome-wide information is crucial to understanding antecedent genome architecture and, therefore, to maintaining diversity and fitness in endangered livestock breeds.

Association of RUNX2 and TNFSF11 genes with production traits in a paternal broiler line.

Intense selection for production traits has improved the genetic gain of important economic traits. However, selection for performance and carcass traits has led to the onset of locomotors problems and decreasing bone strength in broilers. Thus, genes associated with bone integrity traits have become candidates for genetic studies in order to reduce the impact of bone disorders in broilers. This study investigated the association of the RUNX2 and TNFSF11 genes with 79 traits related to performance, carcass composition, organs, and bone integrity in a paternal broiler line. Analyses of genetic association between single-nucleotide polymorphisms (SNPs) and traits were carried out using the maximum likelihood procedures for mixed models. Genetic associations (P < 0.05) were found between SNP g.124,883A>G in the RUNX2 gene and chilled femur weight (additive plus dominance deviation effects within sex) and with performance traits (additive within sex and additive effects). The SNP g.14,862T>C in the TNFSF11 gene presented genetic associations (P < 0.05) with additive plus dominance deviation effects within sex for performance traits. Suggestive genetic associations (P < 0.10) were found with abdominal fat and its yield. Selection based on SNPs g.14,862T>C in TNFSF11 and g.124,883A>G in RUNX2 could be used to improve performance and carcass quality traits in the population studied, although SNP g.14,862T>C was not in Hardy-Weinberg equilibrium because it was not undergoing a selection process. Furthermore, it is important to validate these markers in an unrelated population for use in the selection process.

Genetic parameters and mapping quantitative trait loci associated with tibia traits in broilers.

Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 ± 0.18 (between tibia length and BW42) to 0.89 ± 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

Association between ACTA1 candidate gene and performance, organs and carcass traits in broilers.

This study investigates the genetic association of the SNP present in the ACTA1 gene with performance traits, organs and carcass of broilers to help marker-assisted selection of a paternal broiler line (TT) from EMBRAPA Swine and Poultry, Brazil. Genetic and phenotypic data of 1,400 broilers for 68 traits related to body performance, organ weights, weight of carcass parts, and yields as a percentage of organs and carcass parts were used. The maximum likelihood method, considering 4 analytical models, was used to analyze the genetic association between the SNP and these important economic traits. The association analysis was performed using a mixed animal model including the random effect of the animal (polygenic), and the fixed effects of sex (2 levels), hatch (5 levels) and SNP (3 levels), besides the random error. The traits significantly associated (P<0.05) with the SNP were analyzed, along with body weight at 42 days of age (BW42), by the restricted maximum likelihood method using the multi-trait animal model to estimate genetic parameters. The analysis included the residual and additive genetic random effects and the sex-hatch fixed effect. The additive effects of the SNP were associated with breast meat (BMY), liver yield (LIVY), body weight at 35 days of age (BW35); drumstick skin (DSW), drumstick (DW) and breast (BW) weights. The heritability estimates for these traits, in addition to BW42, ranged from 0.24±0.06 to 0.45±0.08 for LIVY and BW35, respectively. The genetic correlation ranged from 0.02±0.18 for LIVY and BMY to 0.97±0.01 for BW35 and BW42. Based on the results of this study, it can be concluded that ACTA1 gene is associated with performance traits BW35, LIV and BMY, DW, BW and DW adjusted for body weight at 42 days of age. Therefore, the ACTA1 gene is an important molecular marker that could be used together with others already described to increase the economically important traits in broilers.

Phenotypic, genetic and environmental parameters for traits related to femur bone integrity and body weight at 42 days of age in a broiler population.

Intense selection among broilers, especially for performance and carcass traits, currently favors locomotion problems and bone resistance. Conducting studies relating to development and growth of bone tissue in broilers is necessary to minimize losses. Thus, genetic parameters were estimated for a broiler population's phenotypic traits such as BW at 42 d of age (BW42), chilled femur weight (CFW) and its yield (CFY), and femur measurements: calcium, DM, magnesium, phosphorus, and zinc content; breaking strength; rigidity; length; and thickness. Variance components were estimated through multitrait analyses using the restricted maximum likelihood method. The model included a fixed group effect (sex and hatch) and additive and residual genetic random effects. The heritability estimates we obtained ranged from 0.10 ± 0.05 to 0.50 ± 0.08 for chilled femur yield and BW42, respectively, and indicated that the traits can respond to the selection process, except for CFY, which presented low-magnitude heritability coefficients. Genetic correlation estimates between breaking strength, rigidity, and traits related to mineral content indicated that selection that aims to improve the breaking strength resistance of the femur is highly correlated with mineral content. Given the genetic correlation estimates between BW42 and minerals, it is suggested that in this population, selection for BW42 can be performed with greater intensity without affecting femoral integrity.

Genetic and phenotypic parameters of carcass and organ traits of broiler chickens.

The objective of this study was to estimate the genetic and environmental parameters for carcass, carcass part, and organ weights in a paternal strain of broiler chickens that was selected mainly for body weight at 42 days of age (BW42) to provide support for poultry genetic improvement programs. A total of 1448 chickens were used that resulted from the expansion of a pure paternal strain named TT, which was developed by Embrapa Suínos e Aves. The following weights were evaluated: BW42, chilled carcass, wing, drumstick meat, thigh meat, breast meat, breast fillet, back, liver, heart (HRT), and gizzard (GIZ). The variance component was estimated by the restricted maximum likelihood method using a multi-trait animal model. The general model included the additive genetic and residual random effects and the fixed effect of the sex-hatch group (10 levels). The heritability estimates ranged from 0.27 ± 0.06 for HRT to 0.44 ± 0.08 for GIZ. These results indicated that all the traits have enough additive genetic variability to respond to selection. The genetic correlation estimates between BW42 and the carcass and carcass part weights were high and positive. However, the genetic correlation estimates between BW42 and organ weights were low. In this population, the carcass traits might respond indirectly to selection applied to BW42. It can be concluded that selection to increase BW42 is not effective in improving broiler organ weight. Therefore, to obtain suitable genetic improvement for these traits, the selection indexes for broilers should include organ weight-based criteria.

Phenotypic and genetic variability for body weight of ostriches (Struthio camelus).

1. objective of the present study was to estimate heritability for hatch weight (HW), body weight at 90 (W90) and 180 (W180) d of age in Brazilian ostriches. 2. The heritability estimates were obtained through the restricted maximum likelihood method for an animal model. Least squares method was used to define possible fixed effects for consideration in the analysis model. 3. The estimates of heritability were 0.42 ± 0.05, 0.16 ± 0.04 and 0.24 ± 0.08 for HW, W90 and W180, respectively. 4. Heritability estimates showed that there are sufficient levels of additive genetic variation present in the traits studied, and these traits may respond to selection.

Genetic parameter estimates and principal component analysis of breeding values of reproduction and growth traits in female Canchim cattle.

Phenotypic data from female Canchim beef cattle were used to obtain estimates of genetic parameters for reproduction and growth traits using a linear animal mixed model. In addition, relationships among animal estimated breeding values (EBVs) for these traits were explored using principal component analysis. The traits studied in female Canchim cattle were age at first calving (AFC), age at second calving (ASC), calving interval (CI), and bodyweight at 420 days of age (BW420). The heritability estimates for AFC, ASC, CI and BW420 were 0.03±0.01, 0.07±0.01, 0.06±0.02, and 0.24±0.02, respectively. The genetic correlations for AFC with ASC, AFC with CI, AFC with BW420, ASC with CI, ASC with BW420, and CI with BW420 were 0.87±0.07, 0.23±0.02, -0.15±0.01, 0.67±0.13, -0.07±0.13, and 0.02±0.14, respectively. Standardised EBVs for AFC, ASC and CI exhibited a high association with the first principal component, whereas the standardised EBV for BW420 was closely associated with the second principal component. The heritability estimates for AFC, ASC and CI suggest that these traits would respond slowly to selection. However, selection response could be enhanced by constructing selection indices based on the principal components.

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows.

The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated.

Growth curves for ostriches (Struthio camelus) in a Brazilian population.

The objective of this study was to fit growth curves using nonlinear and linear functions to describe the growth of ostriches in a Brazilian population. The data set consisted of 112 animals with BW measurements from hatching to 383 d of age. Two nonlinear growth functions (Gompertz and logistic) and a third-order polynomial function were applied. The parameters for the models were estimated using the least-squares method and Gauss-Newton algorithm. The goodness-of-fit of the models was assessed using R(2) and the Akaike information criterion. The R(2) calculated for the logistic growth model was 0.945 for hens and 0.928 for cockerels and for the Gompertz growth model, 0.938 for hens and 0.924 for cockerels. The third-order polynomial fit gave R(2) of 0.938 for hens and 0.924 for cockerels. Among the Akaike information criterion calculations, the logistic growth model presented the lowest values in this study, both for hens and for cockerels. Nonlinear models are more appropriate for describing the sigmoid nature of ostrich growth.

Genetic parameters and principal component analysis for egg production from White Leghorn hens.

The objectives of this study were to estimate genetic parameters for accumulated egg production over 3-wk periods and for total egg production over 54 wk of egg-laying, and using principal component analysis (PCA), to explore the relationships among the breeding values of these traits to identify the possible genetic relationships present among them and hence to observe which of them could be used as selection criteria for improving egg production. Egg production was measured among 1,512 females of a line of White Leghorn laying hens. The traits analyzed were the number of eggs produced over partial periods of 3 wk, thus totaling 18 partial periods (P1 to P18), and the total number of eggs produced over the period between the 17 and 70 wk of age (PTOT), thus totaling 54 wk of egg production. Estimates of genetic parameters were obtained by means of the restricted maximum likelihood method, using 2-trait animal models. The PCA was done using the breeding values of partial and total egg production. The heritability estimates ranged from 0.05 ± 0.03 (P1 and P8) to 0.27 ± 0.06 (P4) in the 2-trait analysis. The genetic correlations between PTOT and partial periods ranged from 0.19 ± 0.31 (P1) to 1.00 ± 0.05 (P10, P11, and P12). Despite the high genetic correlation, selection of birds based on P10, P11, and P12 did not result in an increase in PTOT because of the low heritability estimates for these periods (0.06 ± 0.03, 0.12 ± 0.04, and 0.10 ± 0.04, respectively). The PCA showed that egg production can be divided genetically into 4 periods, and that P1 and P2 are independent and have little genetic association with the other periods.

Estimation of genetic parameters for partial egg production periods by means of random regression models.

We estimated genetic parameters for egg production in different periods by means of random regression models, aiming at selection based on partial egg production from a generation of layers. The production was evaluated for each individual by recording the number of eggs produced from 20 to 70 weeks of age, with partial records taken every three weeks for a total of 17 periods. The covariance functions were estimated with a random regression model by the restricted maximum likelihood method. A model composed of third-order polynomials for the additive effect, ninth-order polynomials for the permanent environment, and a residual variance structure with five distinct classes, was found to be most suitable for adjusting the egg production data for laying hens. The heritability estimates varied from 0.04 to 0.14. The genetic correlations were all positive, varying from 0.10 to 0.99. Selection applied in partial egg production periods will result in greater genetic profit for the adjacent periods. However, as the distance in time between periods increases, selection becomes less efficient. Selection based on the second period (23 to 25 weeks of age), where greater heritability was estimated, would note benefit the final egg-laying cycle periods.

Egg production curve fitting using nonlinear models for selected and nonselected lines of White Leghorn hens.

Egg production curves describe the laying patterns of hen populations over time. The objectives of this study were to fit the weekly egg production rate of selected and nonselected lines of a White Leghorn hen population, using nonlinear and segmented polynomial models, and to study how the selection process changed the egg-laying patterns between these 2 lines. Weekly egg production rates over 54 wk of egg production (from 17 to 70 wk of age) were measured from 1,693 and 282 laying hens from one selected and one nonselected (control) genetic line, respectively. Six nonlinear and one segmented polynomial models were gathered from the literature to investigate whether they could be used to fit curves for the weekly egg production rate. The goodness of fit of the models was measured using Akaike's information criterion, mean square error, coefficient of determination, graphical analysis of the fitted curves, and the deviations of the fitted curves. The Logistic, Yang, Segmented Polynomial, and Grossman models presented the best goodness of fit. In this population, there were significant differences between the parameter estimates of the curves fitted for the selected and nonselected lines, thus indicating that the effect of selection changed the shape of the egg production curves. The selection for egg production was efficient in modifying the birds' egg production curve in this population, thus resulting in genetic gain from the 5th to the 54th week of egg laying and improved the peak egg production and the persistence of egg laying.

Heritabilities and genetic correlations for reproductive traits in an F2 reciprocal cross chicken population.

Studies estimating genetic parameters for reproductive traits in chickens can be useful for understanding and improvement of their genetic architecture. A total of 1276 observations of fertility (FERT), hatchability of fertile eggs (HFE) and hatchability of total eggs (HTE) were used to estimate the genetic and phenotypic parameters of 467 females from an F2 population generated by reciprocal crossing between a broiler line and a layer line, which were developed through a poultry genetics breeding program, maintained by Embrapa Swine and Poultry, Concordia, Santa Catarina, Brazil. Estimates of heritability and genetic and phenotypic correlations were obtained using restricted maximum likelihood calculations under the two-trait animal model, including the fixed effect of group (hatching of birds from the same genetic group) and the random additive genetic and residual effects. The mean percentages for FERT, HFE and HTE were 87.91 ± 19.77, 80.07 ± 26.81 and 70.67 ± 28.55%, respectively. The highest heritability estimate (h(2)) was 0.28 ± 0.04 for HTE. Genetic correlations for FERT with HFE (0.43 ± 0.17), HFE with HTE (0.98 ± 0.02) and FERT with HTE (0.69 ± 0.10) were positive and significant. Individuals with high breeding value for HTE would have high breeding values for HFE and FERT because of the high genetic association between them. These results suggest that HTE should be included as a selection criterion in genetic breeding programs to improve the reproductive performance of chickens, because HTE had the highest heritability estimate and high genetic correlation with FERT and HFE, and it is the easiest to measure.

Comparison of logistic and neural network models to fit to the egg production curve of White Leghorn hens.

Neural networks are capable of modeling any complex function and can be used in the poultry and animal production areas. The aim of this study was to investigate the possibility of using neural networks on an egg production data set and fitting models to the egg production curve by applying 2 approaches, one using a nonlinear logistic model and the other using 2 artificial neural network models [multilayer perceptron (MLP) and radial basis function]. Two data sets from 2 generations of a White Leghorn strain that had been selected mainly for egg production were used. In the first data set, the mean weekly egg-laying rate was ascertained over a 54-wk egg production period. This data set was used to adjust and test the logistic model and to train and test the neural networks. The second data set, covering 52 wk of egg production, was used to validate the models. The mean absolute deviation, mean square error, and R(2) were used to evaluate the fit of the models. The MLP neural network had the best fit in the test and validation phases. The advantage of using neural networks is that they can be fitted to any kind of data set and do not require model assumptions such as those required in the nonlinear methodology. The results confirm that MLP neural networks can be used as an alternative tool to fit to egg production. The benefits of the MLP are the great flexibility and their lack of a priori assumptions when estimating a noisy nonlinear model.

Estimates of genetic parameters, and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population.

The objectives of this paper were to identify the phenotypic egg-laying patterns in a White Leghorn line mainly selected for egg production, to estimate genetic parameters of traits related to egg production and to evaluate the genetic association between these by principal components analysis to identify trait(s) that could be used as selection criteria to improve egg production. Records of 54 wk of egg production from a White Leghorn population were used. The data set contained records of the length:width ratio of eggs at 32, 37, and 40 wk of age; egg weight at 32, 37, and 40 wk of age; BW at 54 and 62 wk of age; age at first egg; early partial egg production rate from 17 to 30 wk and from 17 to 40 wk of age; late partial egg production rate from 30 to 70 wk and from 40 to 70 wk of age; and total egg production rate (TEP). The estimates of genetic parameters between these traits were estimated by the restricted maximum likelihood method. Multivariate analyses were performed: a hierarchical cluster analysis, a nonhierarchical clustering analysis by the k-means method of weekly egg production rate to describe the egg-laying patterns of hens, and a principal components analysis using the breeding values of all traits. The highest heritability estimates were obtained for BW at 54 wk of age (0.68 ± 0.07) and age at first egg (0.53 ± 0.07). It is recommended that a preliminary clustering analysis be performed to obtain the population structure that takes into account the pattern of egg production, rather than the TEP, because hens may have the same final egg production with different patterns of egg laying. Early partial production periods were not good indicators for use in improving total egg production because these traits presented an overestimated genetic correlation with TEP because of the part-whole genetic correlation component. Egg production might be improved by selecting individuals based on TEP.

Genetic growth potential characterization in the Japanese quail: a meta-analysis.

The description of the growth of the Japanese quails is necessary to characterize the genetic potential of these birds raised in different countries. Thus, the aim of this study was to describe the genetic potential of Japanese quails by conducting a meta-analysis considering studies conducted in different countries. Only data about the subspecies Coturnix coturnix japonica were considered; studies regarding Coturnix coturnix coturnix were not examined. The criteria investigated were BW (W), age (t), year of publication and location of the study. Each set of genetic material within a publication was coded as one study. The Gompertz function was used to interpret the growth of laying quails; thus, each study was represented by Gompertz parameters. The W and t data were applied to estimate the values of Gompertz growth parameters, including BW at maturity (Wm), BW at birth (Wi), maturity rate (B) and inflection point (IP). The age at which the maximum growth rate was achieved (t*) was calculated considering the parameters Wm, Wi and B. To estimate these parameters, random regression was used to randomize the parameter Wm. The parameters estimated for each assay were used in exploratory, grouping, and principal component analyses. The values of Wi ranged from 4.1 to 11.6 g. The values of B ranged from 0.0393 to 0.1039/day, and consequently, the values of t* and IP ranged from 14 to 31 days and 9.21 to 31.03 g, respectively. These results show that there is considerable variability in the growth potential of Japanese quails. To better understand this variation, two groups were examined: Brazil and other countries, according to the grouping of Wi, Wm, B and t*; parameter B was the variable that presented the highest specificity, indicating that both groups modified the maturity rate. For the principal component analysis, the year of publication showed a relationship with the growth parameters but only for studies performed in Brazil. For studies carried out in other countries, the changes in growth parameters were not related to the year of publication. In Brazilian studies, there was a decrease in the maturity rate, but the weight at maturity was higher. Therefore, it appears that different strategies of genetic selection were adopted in Brazil compared to other countries.

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

Summary 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.