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.

SNP and INDEL detection in a QTL region on chicken chromosome 2 associated with muscle deposition.

Genetic improvement is important for the poultry industry, contributing to increased efficiency of meat production and quality. Because breast muscle is the most valuable part of the chicken carcass, knowledge of polymorphisms influencing this trait can help breeding programs. Therefore, the complete genome of 18 chickens from two different experimental lines (broiler and layer) from EMBRAPA was sequenced, and SNPs and INDELs were detected in a QTL region for breast muscle deposition on chicken chromosome 2 between microsatellite markers MCW0185 and MCW0264 (105,849-112,649 kb). Initially, 94,674 unique SNPs and 10,448 unique INDELs were identified in the target region. After quality filtration, 77% of the SNPs (85,765) and 60% of the INDELs (7828) were retained. The studied region contains 66 genes, and functional annotation of the filtered variants identified 517 SNPs and three INDELs in exonic regions. Of these, 357 SNPs were classified as synonymous, 153 as non-synonymous, three as stopgain, four INDELs as frameshift and three INDELs as non-frameshift. These exonic mutations were identified in 37 of the 66 genes from the target region, three of which are related to muscle development (DTNA, RB1CC1 and MOS). Fifteen non-tolerated SNPs were detected in several genes (MEP1B, PRKDC, NSMAF, TRAPPC8, SDR16C5, CHD7, ST18 and RB1CC1). These loss-of-function and exonic variants present in genes related to muscle development can be considered candidate variants for further studies in chickens. Further association studies should be performed with these candidate mutations as should validation in commercial populations to allow a better explanation of QTL effects.

Variant discovery in a QTL region on chromosome 3 associated with fatness in chickens.

Abdominal fat content is an economically important trait in commercially bred chickens. Although many quantitative trait loci (QTL) related to fat deposition have been detected, the resolution for these regions is low and functional variants are still unknown. The current study was conducted aiming at increasing resolution for a region previously shown to have a QTL associated with fat deposition, to detect novel variants from this region and to annotate those variants to delineate potentially functional ones as candidates for future studies. To achieve this, 18 chickens from a parental generation used in a reciprocal cross between broiler and layer lines were sequenced using the Illumina next-generation platform with an initial coverage of 18X/chicken. The discovery of genetic variants was performed in a QTL region located on chromosome 3 between microsatellite markers LEI0161 and ADL0371 (33,595,706-42,632,651 bp). A total of 136,054 unique SNPs and 15,496 unique INDELs were detected in this region, and after quality filtering, 123,985 SNPs and 11,298 INDELs were retained. Of these variants, 386 SNPs and 15 INDELs were located in coding regions of genes related to important metabolic pathways. Loss-of-function variants were identified in several genes, and six of those, namely LOC771163, EGLN1, GNPAT, FAM120B, THBS2 and GGPS1, were related to fat deposition. Therefore, these loss-of-function variants are candidate mutations for conducting further studies on this important trait in chickens.

Identification of polymorphisms associated with production traits on chicken (Gallus gallus) chromosome 4.

Genetic selection for production traits has resulted in a rapid improvement in animal performance and development. Previous studies have mapped quantitative trait loci for body weight at 35 and 41 days, and drum and thigh yield, onto chicken chromosome 4. We investigated this region for single nucleotide polymorphisms and their associations with important economic traits. Three positional candidate genes were studied: KLF3 (Krüeppel-like factor 3), SLIT2 (Slit homolog 2), and PPARGC1A (peroxisome proliferator-activated receptor gamma, coactivator 1 alpha). Fragment sequencing of these genes was conducted in 11 F1 animals, and one polymorphism in each gene was selected and genotyped in an F2 population (N = 276) and a paternal broiler line TT (N = 840). Associations were identified with growth, carcass, and fat traits in the F2 and the paternal line (P < 0.05). Using single markers in both the F2 and the TT line, KLF3 was associated with weight gain (P < 0.05), PPPARGC1A was associated with liver and wing-parts weights and yields (P < 0.05), and SLIT2 was associated with back yield (P < 0.05) and fat traits (P < 0.05). Using multiple markers, KLF3 lost its significance in both populations, and SLIT2 was associated with feed conversion only in the TT population (P < 0.05). The QTLs mapped in the F2 population could be partly explained by PPARGC1A and SLIT2, which were associated with body weight at 35 and 41 days, respectively, and with drum and thigh yield in the same population. The results of this study indicate the importance of these genes for production traits.

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.

Identification and characterization of microRNAs expressed in chicken skeletal muscle.

MicroRNAs (miRNAs, miRs) encompass a class of small non-coding RNAs that often negatively regulate gene expression. miRNAs play an essential role in skeletal muscle, determining the proper development and maintenance of this tissue. In comparison to other organs and tissues, the full set of muscle miRNAs and its expression patterns are still poorly understood. In this report, a chicken skeletal muscle miRNA library was constructed, and the expression of selected miRNAs was further characterized during muscle development in chicken lines with distinct muscling phenotypes. Clone library sequence analysis revealed 40 small RNAs with similarities to previously described chicken miRNAs, seven miRNAs that were never identified before in chicken, and some sequence clusters representing other possible novel miRNAs. Temporal expression profiles of three miRNAs associated with cell proliferation and differentiation (miR-125b, miR-221, and miR-206) in two chicken lines (broiler and layer) revealed the differential steady-state levels of these miRs during skeletal muscle growth and suggests that miR-206 is involved in the muscling phenotype that is observed in growth-selected chicken lines.

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.

Identification and association of polymorphisms in CAPN1 and CAPN3 candidate genes related to performance and meat quality traits in chickens.

Meat quality is an important feature for the poultry industry and is associated with consumer satisfaction. The calpain 1 (CAPN1) gene is related to the tenderness process of meat post- mortem, and the calpain 3 (CAPN3) gene plays an important role in myofibrillar organization and growth. The objective of the present study was to identify polymorphisms in these genes and to determine the association between these polymorphisms and traits of economic interest in poultry. Eleven animals (F1) from an experimental poultry population at Embrapa Swine and Poultry were used to identify the polymorphisms. Four single nucleotide polymorphisms (SNPs) were found in the CAPN1 gene, and one SNP was found in the CAPN3 gene. A polymorphism from each gene was selected for genotyping in 152 chickens from the Embrapa F2 experimental population and 311 chickens from a commercial population. Polymorphism g.2554T>C (CAPN1) was associated with body weight at 35 to 42 days, thigh weight, breast weight, carcass weight, and meat lightness content. SNP g.15486C>T (CAPN3) was associated with thigh yield, thawing-cooking loss, and shear force. Results suggest the possibility of using molecular markers in CAPN1 and CAPN3 genes as a tool for performance and meat quality traits in poultry breeding programs.

Polymorphisms in FGFBP1 and FGFBP2 genes associated with carcass and meat quality traits in chickens.

In the past, the focus of broiler breeding programs on yield and carcass traits improvement led to problems related to meat quality. Awareness of public concern for quality resulted in inclusion of meat quality traits in the evaluation process. Nevertheless, few genes associated with meat quality attributes are known. Previous studies mapped quantitative trait loci for weight at 35 and 42 days in a region of GGA4 flanked by the microsatellite markers, MCW0240 and LEI0063. In this region, there are 2 fibroblast growth factor binding protein (FGFBP) genes that play an important role in embryogenesis, cellular differentiation, and proliferation in chickens. The objective of this study was to identify and associate single nucleotide polymorphisms (SNPs) in FGFBP1 and FGFBP2 with performance, carcass, and meat quality in experimental and commercial chicken populations. In the commercial population, SNP g.2014G>A in FGFBP1 was associated with decreased carcass weight (P < 0.05), and SNP g.651G>A in FGFBP2 was associated with thawing loss and meat redness content (P < 0.05). Four haplotypes were constructed based on 2 SNPs and were associated with breast weight, thawing loss, and meat redness content. The diplotypes were associated with thawing loss, lightness, and redness content. The SNPs evaluated in the present study may be used as markers in poultry breeding programs to aid in improving growth and meat quality traits.

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.

Quantitative trait loci associated with chemical composition of the chicken carcass.

Major objectives of the poultry industry are to increase meat production and to reduce carcass fatness, mainly abdominal fat. Information on growth performance and carcass composition are important for the selection of leaner meat chickens. To enhance our understanding of the genetic architecture underlying the chemical composition of chicken carcasses, an F(2) population developed from a broiler × layer cross was used to map quantitative trait loci (QTL) affecting protein, fat, water and ash contents in chicken carcasses. Two genetic models were applied in the QTL analysis: the line-cross and the half-sib models, both using the regression interval mapping method. Six significant and five suggestive QTL were mapped in the line-cross analysis, and four significant and six suggestive QTL were mapped in the half-sib analysis. A total of eleven QTL were mapped for fat (ether extract), five for protein, four for ash and one for water contents in the carcass using both analyses. No study to date has reported QTL for carcass chemical composition in chickens. Some QTL mapped here for carcass fat content match, as expected, QTL regions previously associated with abdominal fat in the same or in different populations, and novel QTL for protein, ash and water contents in the carcass are presented here. The results described here also reinforce the need for fine mapping and to perform multi-trait analyses to better understand the genetic architecture of these traits.

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.

QTL for percentage of carcass and carcass parts in a broiler x layer cross.

An F2 experimental population, developed from a broiler layer cross, was used in a genome scan of QTL for percentage of carcass, carcass parts, shank and head. Up to 649 F2 chickens from four paternal half-sib families were genotyped with 128 genetic markers covering 22 linkage groups. Total map length was 2630 cM, covering approximately 63% of the genome. QTL interval mapping using regression methods was applied to line-cross and half-sib models. Under the line-cross model, 12 genome-wide significant QTL and 17 suggestive linkages for percentages of carcass parts, shank and head were mapped to 13 linkage groups (GGA1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 14, 18 and 27). Under the paternal half-sib model, six genome-wide significant QTL and 18 suggestive linkages for percentages of carcass parts, shank and head were detected on nine chicken linkage groups (GGA1, 2, 3, 4, 5, 12, 14, 15 and 27), seven of which seemed to corroborate positions revealed by the previous model. Overall, three novel QTL of importance to the broiler industry were mapped (one significant for shank% on GGA3 and two suggestive for carcass and breast percentages on GGA14 and drums and thighs percentage on GGA15). One novel QTL for wings% was mapped to GGA3, six novel QTL (GGA1, 3, 7, 8, 9 and 27) and suggestive linkages (GGA2, 4, and 5) were mapped for head%, and suggestive linkages were identified for back% on GGA2, 11 and 12. In addition, many of the QTL mapped in this study confirmed QTL previously reported in other populations.

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.