Estimation of heritability and genetic correlation of body weight gain and growth curve parameters in Korean native chicken

Genetic variance components of the growth curve for Isfahan indigenous chicken

BACKGROUND

Being able to model a growth curve using three or four non-linear functional parameters could help explain the growth phenomenon in a precise way and would allow the comparison of an animal's development rate, optimize management and feeding strategies and guide animal production strategies.

OBJECTIVE

The goal of this study was to estimate the genetic parameters of growth traits of Isfahan indigenous chicken in Iran and to determine the best non-linear model describing the growth curve.

METHODS

The prediction of additive genetic parameters was performed using the REML method by WOMBAT. Direct heritability of the studied traits and genetic correlations between them were obtained. The Logistic, Gompertz, von Bertalanffy, Brody, Negative exponential, Weibull, Janoschek and Bridges models were compared based on the coefficient of determination (R2 ), mean square error (MSE) and akaike information criterion.

RESULTS

The Gompertz model was identified as the best model for describing the growth curve for Isfahan native chicken. The heritability of maturity weights (A), initial weight (B) and maturity rate (K) parameters were 0.223 ± 0.002, 0.016 ± 0.005 and 0.087 ± 0.001, respectively.

CONCLUSION

This study shows that Isfahan indigenous chicken has the genetic potential for improving growth and reproduction based on their desirable heritabilities and correlations using appropriate models.

A Study on the Growth and Development Characteristics of Lindian Chickens

As an excellent chicken breed found in a high-altitude zone of northern China, Lindian chickens are characterized by good egg and meat production, strong adaptability, cold tolerance, rough feeding resistance, excellent egg quality, and delicious meat quality. To facilitate the exploitation of the unique qualities of the Lindian chicken, the varying patterns and correlations of various body size and carcass traits of 3-22-week-old Lindian chickens were analyzed in this study. The optimal growth model of these traits was determined by growth curve fitting analysis. The results showed that most traits of Lindian chickens increased steadily with increasing age, and most of them increased rapidly before 10 weeks of age. In addition, the inflection point age of each trait was predicted to be between 4 and 10 weeks. Furthermore, this study revealed that body size traits were closely related to carcass traits in Lindian chickens. In summary, Lindian chickens are in a rapid growth stage before the age of 10 weeks, and better slaughter performance can be achieved through good feeding management during this stage. The reproductive traits and muscles are the main developmental focus after the age of 19 weeks, so it is important to adequately meet their energy requirements for subsequent good breeding performance.

Heat stress effects on the genetics of growth traits in Thai native chickens (Pradu Hang dum)

OBJECTIVE

The objective of this study was to investigate the effect of heat stress on the growth traits and genetic parameters of Thai native chickens.

METHODS

A total of 16,487 records for growth traits of Thai native chickens between 2017 and 2022 were used in this study. Data included the body weight at birth, body weight at 4, 8, and 12 weeks of age (BW0, BW4, BW8, BW12), average daily gain during 0 to 4, 4 to 8, and 8 to 12 weeks of age (ADG0-4, ADG4-8, ADG8-12), absolute growth rate at birth, at 4, 8, and 12 weeks of age (AGR0, AGR4, AGR8, AGR12). The repeatability test day model used the reaction-norm procedure to analyze the threshold point of heat stress, rate of decline of growth traits, and genetic parameters.

RESULTS

At temperature and humidity index (THI) of 76, Thai native chickens began to lose their growth traits, which was the onset of heat stress in this study. The estimated heritability, genetic correlation between animal and heat stress effect, and correlations between the intercept and slope of the permanent environmental effects were 0.27, -0.85, and -0.83 for BW, 0.17, -0.81, and -0.95 for ADG, 0.25, -0.61, and -0.83 for AGR, respectively. Male chickens are more affected by heat stress than female chickens with a greater reduction of BW, ADG, and AGR, values equal to -9.30, -0.23, -15.21 (in males) and -6.04, -0.21, -10.10 (in females) gram per 1 level increase of THI from the THI of 76.

CONCLUSION

The influence of thermal stress had a strong effect on the decline in growth traits and genetic parameters in Thai native chickens. This study indicated that genetic models used in conjunction with THI data are an effective method for the analysis and assessment of the effects of heat stress on the growth traits and genetics of native chickens.

Comparative population genomics analysis uncovers genomic footprints and genes influencing body weight trait in Chinese indigenous chicken

Body weight of chicken is a typical quantitative trait, which shows phenotypic variations due to selective breeding. Despite some QTL loci have been obtained, the body weight of native chicken breeds in different geographic regions varies greatly, its genetic basis remains unresolved questions. To address this issue, we analyzed 117 Chinese indigenous chickens from 10 breeds (Huiyang Bearded, Xinhua, Hotan Black, Baicheng You, Liyang, Yunyang Da, Jining Bairi, Lindian, Beijing You, Tibetan). We applied fixation index (FST) analysis to find selected genomic regions and genes associated with body weight traits. Our study suggests that NELL1, XYLT1, and NCAPG/LCORL genes are strongly selected in the body weight trait of Chinese indigenous chicken breeds. In addition, the IL1RAPL1 gene was strongly selected in large body weight chickens, while the PCDH17 and CADM2 genes were strongly selected in small body weight chickens. This result suggests that the patterns of genetic variation of native chicken and commercial chicken, and/or distinct local chicken breeds may follow different evolutionary mechanisms.

Comparative study and relationship analysis between purine content, uric acid, superoxide dismutase, and growth traits in purebred and crossbred Thai native chickens

The objective was to compare and analyze the relationship between growth, purine content, uric acid, and superoxide dismutase (SOD) in purebred and crossbred Thai native chickens. A total of 300 Thai native chickens were divided into 3 groups. Group 1 was purebred Thai native chickens (100%TN), Group 2 was 50% Thai native chickens (50%TN), and Group 3 was 25% Thai native chickens (25%TN). Data included the body weight (BW), average daily gain (ADG), and breast circumference (BrC). At 6, 8, and 10 weeks of age, 10 chickens from each group were randomly euthanized to collect breast meat, liver, and blood samples to analyze the purine content consisting of total purine, adenine, guanine, xanthine, and hypoxanthine, and uric acid, in breast meat and liver and SOD in blood. A general linear model, Pearson correlation and principal component analysis were used to analyze the significant differences and relationship between variables. The results showed the 25%TN group had the highest growth traits at every age, while the 100%TN group had the lowest (p < 0.05). Consistent with the analysis results of purine values, purine content and uric acid in breast meat and liver and SOD in blood decreased with age (p < 0.05). The correlations between purine content (total purine, adenine, guanine, xanthine, and hypoxanthine) and growth traits (BW, ADG, and BrC) ranged from moderate negative to moderate positive (-0.542 to 0.253)(p < 0.05). The correlations between uric acid and growth traits (0.348-0.760) and SOD and growth traits (0.132-0.516) were low to moderate positive with significant differences (p < 0.05). The principal component plot, which highlighted three principal components (PC 1, PC 2, and PC 3), explained 86.44 and 86.53% of the total information in breast meat and liver for selecting animals for optimal balance of the variation in the growth traits, purine content, uric acid, and SOD. Although purebred Thai native chickens showed the lowest growth traits, purine content, uric acid, and SOD were also lowest compared to crossbred Thai native chickens. Therefore, the development of genetics in Thai native chickens to produce healthy food could be possible.

Early Growth and Development and Nonlinear Model Fitting Analysis of Ashidan Yak

Understanding animal growth plays an important role in improving animal genetics and breeding. In order to explore the early growth and development law of Ashidan yak, the body weight (BW), wither height (WH), body oblique length (BL) and chest girth (CG) of 260 female Ashidan yaks were measured. These individuals grew under grazing conditions, and growth traits were measured at 6, 12, 18 and 30 months of age. Then the absolute growth and relative growth of Ashidan yak were calculated, and five nonlinear models (Logistic model, Gompertz model, Brody model, von Bertalanffy model and Richards model) were used to fit the growth curve of Ashidan yak. The fitting effect of the model was evaluated according to MSE, AIC and BIC. The results showed that the growth rate of Ashidan yak was the fastest from 12 to 18 months old, and the growth was slow or even stagnant from 6 to 12 months old. The AIC and BIC values of the Richards model were the lowest among the five models, with an AIC value of 4543.98 and a BIC value of 4563.19. The Richards model estimated body weight at 155.642 kg. In summary, the growth rate of female Ashidan yak changes with the seasons, growing faster in warm seasons and slower in cold seasons. Richards model is the best model to describe the growth curve of female Ashidan yak in five nonlinear models.

Heritability Estimation Approaches Utilizing Genome-Wide Data

Prior to the development of genome-wide arrays and whole genome sequencing technologies, heritability estimation mainly relied on the study of related individuals. Over the past decade, various approaches have been developed to estimate SNP-based narrow-sense heritability (h SNP 2 ${\rm{h}}_{{\rm{SNP}}}^2$ ) in unrelated individuals. These latter approaches use either individual-level genetic variations or summary results from genome-wide association studies (GWAS). Recently, several studies compared these approaches using extensive simulations and empirical datasets. However, sparse information on hands-on training necessitates revisiting these approaches from the perspective of a stepwise guide for practical applications. Here, we provide an overview of the commonly used SNP-heritability estimation approaches utilizing genome-wide array, imputed or whole genome data from unrelated individuals, or summary results. We not only discuss these approaches based on their statistical concepts, utility, advantages, and limitations, but also provide step-by-step protocols to apply these approaches. For illustration purposes, we estimateh SNP 2 ${\rm{h}}_{{\rm{SNP}}}^2$ of height and BMI utilizing individual-level data from The Northern Finland Birth Cohort (NFBC) and summary results from the Genetic Investigation of ANthropometric Traits (GIANT;) consortium. We present this review as a template for the researchers who estimate and use heritability in their studies and as a reference for geneticists who develop or extend heritability estimation approaches. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: GREML (GCTA) Alternate Protocol 1: Stratified GREML Basic Protocol 2: LDAK Alternate Protocol 2: Stratified LDAK Basic Protocol 3: Threshold GREML Basic Protocol 4: LD score (LDSC) regression Basic Protocol 5: SumHer.

Estimation of genetic parameters for production, reproduction, and growth curve of Fars indigenous chicken

Iranian native chicken, including Fars indigenous chicken, is an important genetic resource due to its adaptation to stressful environmental conditions, good endurance and resistance to disease. The aim of this research was to determine the genetic infrastructure of Fars indigenous chicken using several nonlinear functions. The dataset included body weight at hatch (BW1), body weight at the 8th week (BW8), body weight at the 12th week (BW12), weight at sexual maturity (WSM), age at sexual maturity (ASM), number of eggs in the first 12 weeks of laying period (EN), egg weight at the first day of laying (EW1), average egg weight at the 28thday of laying (EW28), and average egg weight at weeks 28, 30, and 32 of the laying period (AEW). Growth models were fitted using the NLIN procedure and WOMBAT software was used to predict variance components for the best fit model parameters. Results suggested three-parameter models, for example, Gompertz, fitted better to the data than others. The maturity weight (A), initial weight (B), and maturity rate (K) parameters in the Gompertz model were 1996.8 ± 6.63, 4.11 ± 0.03, and 0.021 ± 0.0001, respectively. The heritability of A, B, and K parameters were 0.03, 0.05, and 0.12, respectively.

Genetic Comparisons of Body Weight, Average Daily Gain, and Breast Circumference between Slow-Growing Thai Native Chickens (Pradu Hang dum) Raised On-Site Farm and On-Station

To ensure that any new technology developed within an experimental station is appropriate to the community’s needs and compatible with the existing systems, on-site farm research is an important component in examining the effectiveness of agricultural research. The present study examined the growth performance and genetics of Thai native chickens under conditions typically experienced by farmers on smallholder farms (on-site farms) compared with at an experimental unit (on-station). There were 1694 Thai native chickens (Pradu Hang dum) used in this experiment, and they were divided into 613 chickens for the on-station and 1081 chickens for the on-site farm experiments. The individual chicken data included the birth weight (BW0) and body weight at 4, 8, 12, and 16 weeks of age (BW4, BW8, BW12, and BW16, respectively), ADG from 0−4, 4−8, 8−12, 12−16 weeks of age (ADG0−4, ADG4−8, ADG8−12, ADG12−16, respectively), and breast circumference at 8, 12, and 16 weeks of age (BrC8, BrC12, BrC16, respectively). A multiple traits animal model and a selection index were used to estimate the variance components, genetic parameters, and breeding values of growth traits. The results showed that the body weight, average daily gain, and breast circumference at 8, 12, and 16 weeks of age of Thai native chickens raised on-station were higher than those raised on-site at the farm among mixed-sex and sex-segregated chickens, while the birth weight and body weight at four weeks of age (BW0 and BW4) and ADG from 0−4 weeks of age (ADG0−4) were not significantly different (p > 0.05). The heritability estimates of body weight, average daily gain, and breast circumference in the chickens raised at the on-site farm and on-station were moderate to high, with on-station values slightly higher than on-site farm values. The heritability estimates of body weight were 0.236 to 0.499 for the on-site farm, and 0.291 to 0.499 for on-station. For average daily gain, the heritability estimates were 0.274 to 0.283 for the on-site farm and 0.298 to 0.313 for on-station; meanwhile, and for breast circumference, the heritability estimates were 0.204 to 0.268 for the on-site farm and 0.278 to 0.296 for on-station. Both phenotypic and genetic correlations among and between growth traits were positive and ranged from low to high values. The top 20% of the estimated breeding values and selection indices in the on-site farm and on-station experiments showed that the body weight at eight weeks of age (BW8), ADG from 4−8 weeks of age (ADG4−8), and breast circumference at eight weeks of age (BrC8) should be used as selection criteria for Thai native chicken breeding programs. In conclusion, the genetic parameters and breeding values in on-station experiments showed that the breeding program by selection index for improving growth performance is valid. Therefore, to implement such a breeding program in an on-site farm, an intensive or semi-intensive farm system should be considered to minimize the effect of genotype-environment interaction.

Comparative Study of Phenotypes and Genetics Related to the Growth Performance of Crossbred Thai Indigenous (KKU1 vs. KKU2) Chickens under Hot and Humid Conditions

To improve the body weight and growth performance traits of crossbred Thai indigenous chickens, phenotypic performance and genetic values were estimated. Crossbred Thai indigenous chickens, designated KKU1 and KKU2, were compared. The data included 1375 records of body weight (BW0, BW2, BW4, and BW16), breast circumference at 6 weeks of age (BrC6), and average daily gain (ADG0−2, ADG0−4, and ADG0−6). A multi-trait animal model with the average information-restricted maximum likelihood (AI-REML) was used to estimate the genetic parameters and breeding values. The results showed that the body weight and breast circumference traits (BW2, BW4, BW6, and BrC6) for the mixed sex KKU1 chickens were higher than for the KKU2 chickens (p < 0.05). For the growth performance traits, the KKU1 chickens had higher average daily gain and feed intake and a lower feed conversion ratio than the KKU2 chickens (p < 0.05). The survival rates were not different except at up to 6 weeks of age, when that of the KKU1 chickens was slightly lower. The specific combining ability, heritability, genetic and phenotypic correlations, and estimated breeding values showed that the KKU1 chickens had better genetics than the KKU2 chickens. In conclusion, KKU1 chickens are suitable for development as crossbred Thai indigenous chickens for enhanced growth performance and for commercial use.

Mexican Creole chickens: effect of data collection periods on goodness-of-fit and parameter precision of growth models

The objective of this study was to estimate the good-of-fitness and precision of parameters of the Gompertz-Laird, Logistic, Richards, and Von Bertalanffy growth models, using different data collection periods (DCP). Two hundred and sixty-two Mexican Creole chicks (116 females and 146 males), were individually weighed to form the following sets of data for each sex: DCP₁ (weights recorded weekly from hatching to 63 d, and every 2 wk, from 63 to 133 d of age), DCP₂ (weights recorded weekly from hatching to 133 d of age), DCP₃ (weights recorded every third day, from hatching to 63 d, and every 14 d, from 63 to 133 d of age), and DCP₄ (weights recorded every third day, from hatching to 63 d, and weekly, from 63 to 133 d of age). Data were analyzed using the NLIN procedure of SAS (Marquardt algorithm). For all growth models, the width of confidence interval (CI) of each parameter, was estimated (α = 0.05). The adjusted coefficient of determination (AR²), as well as the Akaike (AIC) and Bayesian information criteria (BIC) were used to select the best model. The higher the AR², and the lower the width of CI, as well as the AIC and BIC values, the better the model. The Gompertz-Laird model, more frequently showed the highest AR², and the lowest AIC and BIC values compared to the other models. Moreover, for all models, both sexes and all parameters, most confidence interval widths (all with the Gompertz-Laird model) were the lowest with DCP₃ when compared to the other sets of data. In conclusion, the Gompertz-Laird model was the best provided that the chickens are weighed every third day from hatching until 63 d of age, and every 2 wk thereafter.

Genetic Evaluation of Body Weights and Egg Production Traits Using a Multi-Trait Animal Model and Selection Index in Thai Native Synthetic Chickens (Kaimook e-san2)

To improve the genetics of both growth and egg production, which are limitations in purebred native chickens, new genetic lines can be developed using an appropriate genetic approach. The data used in this study included 2713 body weight (BW0, BW4, BW6, BW8, and BW10), breast circumference (BrC6), chicken age at first egg (AFE), and egg production (240EP, 270EP, 300EP, and 365EP) records covering the period 2015 to 2020. A multi-trait animal model with the average information-restricted maximum likelihood (AI-REML) and a selection index was used to estimate the variance components, genetic parameters, and breeding values. The results showed that males had significantly higher weights than females (p < 0.05) from 4 to 10 weeks of age and that this difference increased over the generations. The differences between BW0 and BrC6 by sex and generation were not significant (p > 0.05). The estimated heritability of body weight ranged from 0.642 (BW0) to 0.280 (BW10); meanwhile, the estimated heritability of BrC6 was moderate (0.284). For egg production traits, the estimated heritability of 240EP, 270EP, 300EP, and 365EP was 0.427, 0.403, 0.404, and 0.426, respectively, while the estimated heritability of AFE was 0.269. The genetic and phenotypic correlations among the growth traits (BW0 to BW10) were low to highly positive. The genetic and phenotypic correlations between growth (BW0 to BW10) and BrC6 traits were positive, and the genetic correlations between BW6 (0.80), BW8 (0.84), BW10 (0.93), and BrC6 were strongly positive. Genetic correlations among the egg production traits (240EP, 270EP, 300EP, and 365EP) were low to highly positive and ranged from 0.04 to 0.86. The genetic correlations between AFE and all egg production traits were low to moderately negative and ranged from −0.14 to −0.29. The positive genetic correlations between body weight (BW6, BW8, and BW10) and egg production traits were found only in 240EP. The average genetic progress of body weight traits ranged from −0.38 to 30.12 g per generation for BW0 to BW10 (p < 0.05); the genetic progress was 0.28 cm per generation for BrC6 (p > 0.05). The average genetic progress of cumulative egg production traits ranged from 4.25 to 12.42 eggs per generation for 240EP to 365EP (p < 0.05), while the average genetic progress of AFE was −7.12 days per generation (p < 0.05). In conclusion, our study suggests that the body weight at six weeks of age (BW6), breast circumference at six weeks of age (BrC6), cumulative egg production at 240 days of age (240EP), and age at first egg (AFE) are the traits that should be used as selection criteria, as they have a positive effect on the development of growth and egg production.

Genetic Effect and Growth Curve Parameter Estimation under Heat Stress in Slow-Growing Thai Native Chickens

Heat stress is becoming a major problem because it limits growth in poultry production, especially in tropical areas. The development of genetic lines of Thai native chickens (TNC) which can tolerate the tropical climate with the least compromise on growth performance is therefore necessary. This research aims to analyze the appropriate growth curve function and to estimate the effect of heat stress on the genetic absolute growth rate (AGR) in TNC and Thai synthetic chickens (TSC). The data comprised 35,355 records for body weight from hatching to slaughtering weight of 7241 TNC and 10,220 records of 2022 TSC. The best-fitting growth curve was investigated from three nonlinear regression models (von Bertalanffy, Gompertz, and logistic) and used to analyze the individual AGR. In addition, a repeatability test-day model on the temperature-humidity index (THI) function was used to estimate the genetic parameters for heat stress. The Gompertz function produced the lowest mean squared error (MSE) and Akaike information criterion (AIC) and highest the pseudo-coefficient of determination (Pseudo-R²) in both chicken breeds. The growth rates in TSC were higher than TNC; the growth rates of males were greater than females, but the age at inflection point in females was lower than in males in both chicken breeds. The THI threshold started at 76. The heritability of the AGR was 0.23 and 0.18 in TNC and TSC, respectively. The additive variance and permanent environmental variance of the heat stress effect increased sharply after the THI of 76. The growth rate decreased more severely in TSC than TNC. In conclusion, the Gompertz function can be applied with the THI to evaluate genetic performance for heat tolerance and increase growth performance in slow-growing chicken.

Evaluation of non-linear growth curve models in the Vietnamese indigenous Mia chicken

Understanding of animal growth is important for the improvement of management and feeding practices; however, little is known about the growth curve in Vietnamese indigenous chicken. This study was performed to determine the most appropriate models for describing the growth curve of Vietnamese Mia chicken. The study evaluated the performances of the Logistic, Gompertz, Richards, and Bridges models of body weights in 224 Mia chickens. Models were fitted using minpack.lm package in R software and Akaike's information criterion and Bayesian information criterion were used for model comparison. Based on these criteria, the Gompertz and Bridges were the best models for males and females, respectively. Estimated asymmetric weights (α) were ranged from 2,241.91 ± 14.74 (g) (Logistic) to 2,623.86 ± 30.23 (g) (Gompertz) for males and from 1,537.36 ± 10.97 (g) (Logistic) and 1,958.36 ± 72.92 (g) (Bridges) for females, respectively. The age at the inflection point was estimated from 9.32 to 10.5 weeks and from 8.51 to 9.86 weeks for males and females, respectively. In conclusion, the Gompertz model is the most suitable model for describing the growth curve of Mia chicken. The parameters obtained from growth models could help define feeding programs to meet nutritional needs from hatching to the age of maximum growth, reproduction programs, and marketing strategies.

Thai Native Chicken as a Potential Functional Meat Source Rich in Anserine, Anserine/Carnosine, and Antioxidant Substances

This study identified anserine and anserine/carnosine in chicken breast of Thai native chicken (TNC; 100% Thai native), Thai synthetic chicken (TSC; 50% Thai native), and Thai native crossbred chicken (TNC crossbred; 25% Thai native) compared with commercial broiler chicken (BR; 0% Thai native) using nuclear magnetic resonance (NMR) spectroscopy and the effect on antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl assay (DPPH). We conducted experiments with a completely randomized design and explored principal components analysis (PCA) and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) to identify the distinguishing metabolites and relative concentrations from 1H NMR spectra among the groups. The relative concentrations and antioxidant properties among the groups were analyzed by analysis of variance (ANOVA) using the general linear model (GLM). This study revealed seven metabolites alanine, inositol monophosphate (IMP), inosine, and anserine/carnosine, lactate, anserine, and creatine. Lactate, anserine, and creatine were major components. In terms of PCA, the plots can distinguish BR from other groups. OPLS-DA revealed that anserine and anserine/carnosine in the chicken breast were significantly higher in TNC, TSC, and TNC crossbred than BR according to their relative concentrations and antioxidant properties (p < 0.01). Therefore, TNCs and their crossbreeds might have the potential to be functional meat sources.

Quantifying the effect of inbreeding on average daily gain and Kleiber ratio in Mazandaran native chickens

The aims of this study was to evaluate inbreeding effects for growth rate (average daily gain from hatch to 8 weeks of age (ADG1-8), average daily gain from hatch to 12 weeks of age (ADG1-12), average daily gain from 8 weeks of age to 12 weeks (ADG8-12), average daily gain from hatch to sex maturity (ADG1-SM), average daily gain from 8 weeks of age to sex maturity (ADG8-SM), average daily gain from 12 weeks to sex maturity (ADG12-SM), and Kleiber ratios (KR1-8, KR1-12, KR8-12) in Mazandaran native chickens. The data set of 82,446 pedigreed individuals over 21 generations was analyzed. All individuals were grouped into three classes based on the inbreeding coefficient: First class contained non-inbred birds (F = 0) and second and third classes contained inbred individuals (0 < F ≤ 5% and F > 5%, respectively). The effects of inbreeding coefficient on the studied traits were estimated by the restricted maximum likelihood method (REML) applying the WOMBAT software and fitting individual increase in inbreeding coefficient (ΔFi) of birds as linear covariates under 6 different animal models. ADG8-SM and ADG12-SM increased non-significantly by 0.003 and 0.005 g, respectively, due to 1% increase in ΔFi, while ADG1-8, ADG1-12, ADG8-12, ADG1-SM, KR1-8, and KR1-12 decreased (P < 0.001), respectively, by 0.012 g, 0.011 g, 0.010 g, 0.014 g, 0.003 g, and 0.002 g. Also, KR8-12 non-significantly decreased by 0.001 g. Estimates of direct heritability of traits based on the most appropriate models ranged from 0.05 (KR8-12) to 0.26 (ADG12-SM). Results showed that it is important to regularly analyze inbreeding level in the herd in an attempt to prevent the reduction of performance.

Genomic predictions of growth curves in Holstein dairy cattle based on parameter estimates from nonlinear models combined with different kernel functions

Availability of longitudinal body weight (BW) records allows the application of nonlinear models (NLINM) to predict phenotypic and genomic growth curves in dairy cattle. In this regard, we considered a data set including 31,722 BW records from 4,952 female Holstein cattle, during the period from birth (mo 0) to approximately age at first calving (mo 24). Parameters of the growth curves were estimated using 3 NLINM: the logistic (LOG), the Gompertz (GOM), and the Richards (RICH) functions. Residuals for the growth curve parameters from the NLINM applications were used as pseudo-phenotypes in the ongoing genomic analyses with different similarity matrices, including 2 genomic relationship matrices (G1 and G2), a combined pedigree and genomic relationship matrix (H), and 3 kernel matrices. The kernels were a weighted "alike by state" kernel function (K1), an exponential dissimilarity kernel (K2), and a Gaussian kernel (K3). On the basis of G1 and G2 matrices, genomic heritabilities for the growth curve parameters birth weight (W₀), mature weight (W_m), and growth rate (k), and the shape parameter (m; only available from RICH) were moderate to large, in the range from 0.29 (m from RICH) to 0.46 (k from RICH). Fitting the similarity matrices based on kernel functions contributed to an increase of the ratio of the variance explained by the similarity matrix in relation to the total variance (compared with the heritability when modeling G1 or G2). Genetic correlations between W₀, W_m, and k were always positive (>0.30), especially for the same growth curve parameters estimated from different NLINM (>0.90). The shape parameter m from RICH was negatively correlated with other growth curve parameters, from -0.29 to -0.95. In a next step, estimated genomic breeding values for growth curve parameters were input data for the respective NLINM, aiming to construct genomic growth curves. Prediction accuracies were correlations between genomic growth curves and genomic breeding values from random regression models for sires and female cattle. Considering all genotyped female cattle with pseudo-phenotypes, prediction accuracies were larger from RICH than from LOG and GOM. However, differences in prediction accuracies from the NLINM × similarity matrix combinations were quite small. Accordingly, in 5-fold cross-validations using heifer groups with masked phenotypes, very similar prediction accuracies across modeling approaches were identified. Especially for specific age months, genomic growth curve predictions were more accurate for sires than for female cattle, indicating that the relationships between animals in training and validation sets are more important than the selection of specific NLINM × similarity matrix combinations.

Association of the thyroid hormone responsive spot 14 alpha gene with growth-related traits in Korean native chicken

Objective

Thyroid hormone responsive spot 14 alpha (THRSP) has been used to investigate the regulation of de novo lipogenesis because the variation of THRSP mRNA content in the tissue affects directly the ability of that tissue to synthetize lipids. Also, this gene responds to thyroid hormone stimulation and high level of carbohydrate feeding or insulin-injection. This study was carried out to investigate variations within THRSP and their effects on body and carcass weights in Korean native chicken (KNC).

Methods

A total of 585 chickens which represent the five lines of KNC (Black, Gray-Brown, Red-Brown, White, and Yellow-Brown) were reared and body weight data were recorded every two weeks from hatch until 20 weeks of age. Polymerase chain reaction-restriction fragment length polymorphism, DNA chips for Agilent 2100 Bioanalyzer, and Fluidigm Genotyping Technology, were applied to genotype selected markers. A linear mixed-effect model was used to access association between these single nucleotide polymorphism (SNP) markers and growth-related traits.

Results

A total of 30 polymorphisms were investigated in THRSP. Of these, nine SNPs for loci were selected to perform association analyses. Significant associations were detected between g.-49G>T SNP with body weight at 20 weeks of age (BW20), g.451T>C SNP with growth at 10 to 12 weeks of age (GR10-12), and g.1432A>C SNP with growth at 14 to 16 weeks trait (GR14-16) and body weight at 18 weeks of age (BW18). Moreover, diplotype of the THRSP gene significantly affected body weight at 12 weeks of age (BW12) and GR10-12 traits. Diplotype of ht1/ht2 was favorable for BW12 and GR10-12 traits.

Conclusion

These results suggest that THRSP can be regarded as a candidate gene for growth traits in KNC.

POU class 1 homeobox 1 gene polymorphisms associated with growth traits in Korean native chicken

Objective

POU class 1 homeobox 1 (POU1F1) mediates growth hormone expression and activity by altering transcription, eventually resulting in growth rate variations. Therefore, we aimed to identify chicken POU1F1 polymorphisms and evaluate the association between single nucleotide polymorphisms (SNPs) and growth-related traits, and logistic growth curve parameter traits (α, β, and γ).

Methods

Three SNPs (M_1 to M_3) were used to genotype 585 F₁ and 88 F₀ birds from five Korean native chicken lines using a polymerase chain reaction–restriction fragment length polymorphism method.

Results

Single marker analyses and traits association analyses showed that M_2 was significantly associated with body weight at two weeks, weight gain from hatch to 2 weeks, and weight gain from 16 to 18 weeks (p<0.05). M_3 was significantly associated with weight gain from 14 to 16 weeks and from 16 to 18 weeks, and asymptotic body weight (α) (p<0.05). No traits were associated with M_1. The POU1F1 haplogroups were significantly associated with weight gain from 14 to 16 weeks (p = 0.020). Linkage disequilibrium test and Haploview analysis shown one main haploblock between M_2 and M_3 SNP.

Conclusion

Thus, POU1F1 significantly affects the growth of Korean native chickens and their growth curve traits.