Average Information Restricted Maximum Likelihood Research Articles

Estimation of heritability with genomic information by method R.

Estimating heritabilities with large genomic models by established methods such as restricted maximum likelihood (REML) or Bayesian via Gibbs sampling is computationally expensive. Alternatively, heritability can be estimated indirectly by method R and by maximum predictivity, referred to as MaxPred here, at a much lower computing cost. By method R, the heritability used for predictions with whole and partial data is considered the best estimate when the predictions based on partial data are unbiased relative to those with the complete data. By MaxPred, the heritability estimate is the one that maximizes predictivity. This study compared heritability estimation with genomic information using average information REML (AI-REML), method R and MaxPred. A simulated population was generated with ten generations of 5000 animals each and an effective population size of 80. Each animal had one record for a trait with a heritability of 0.3, a phenotypic variance of 10.0 and was genotyped at 50 k SNP. In method R, the heritability estimate is found when the expectation of a regression coefficient is equal to one. The regression is the EBV of selection candidates calculated with the whole dataset regressed on the EBV of candidates calculated from a partial dataset. In this study, we used the GBLUP framework and therefore, GEBV was calculated. The partial dataset was created by removing the last generation of phenotypes. Predictivity was defined as the correlation between the adjusted phenotypes of the selection candidates and their GEBV calculated from the partial data. We estimated the heritability for populations that included between three and 10 generations. In every scenario, predictivity increased as more data was used and was the highest at the simulated heritability. However, the predictivity for all data subsets and all heritabilities compared did not differ more than 0.01, suggesting MaxPred is not the best indication for heritability estimation. For the whole dataset, the heritability was estimated as 0.30 ± 0.01, 0.26 ± 0.01 and 0.30 ± 0.04 for AI-REML without genomics, AI-REML with genomics and method R with genomics, respectively. Heritability estimation with genomics by method R reduced timing by 83%, implying a reduction in computing time from 9.5 to 1.6 h, on average, compared to AI-REML with genomics. Method R has the potential to estimate heritabilities with large genomic information at a low cost when many generations of animals are present; however, the standard error can be high when only a few iterations are used.

Genetic parameters for ewe lifetime productivity traits in Central Anatolian Merino sheep

Rapidly increasing population size, recent breaks in production and supply chains, due to pandemics, and those further expected because of climate change emphasize the compelling importance of animal productivity. Traits associated with the productivity of ewes have a direct impact on the overall productivity, profitability and efficiency of sheep farms. Therefore, the objective of the current study was to estimate the variance components, heritabilities as well as genetic and phenotypic correlations, for traits associated with the lifetime productivity of Central Anatolian Merino ewes. Birth and weaning records of lambs for each ewe as well as environmental factors such as sex and birth type were utilized for deriving ewe lifetime productivity traits. Genetic parameter estimations involved observations from 3101 Central Anatolian Merino ewes, encompassing mean and total lamb birth weight per ewe (MBW and TBW), mean and total lamb weaning weight per ewe (MWW and TWW), and the mean and total number of lambs weaned (MNLW and TNLW). This analysis utilized a pedigree comprising 13229 animals. Average Information Restricted Maximum Likelihood (AIREML) based Animal Linear Mixed Model estimations for the decomposition of (co)variance components were implemented based on pedigree-derived numerator relationship matrix by also accounting for the number of parities as a fixed factor. Low to moderate heritability estimates, ranging between 0.29 and 0.42, were observed for the lifetime productivity traits of the breed. A wide range of genetic and phenotypic correlations (between −0.56 and 0.99) was observed among the traits of interest. The outcomes of the study are anticipated to significantly enhance the global sheep production systems by uncovering the essential parameters for incorporating ewe’s lifetime reproductive performance and productivity into the selection indices. This will also benefit Central Anatolian Merino farmers, who form a large proportion of sheep producers in Turkey.

Genetic background of hematological parameters in Holstein cattle based on genome-wide association and RNA sequencing analyses

Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the Average Information Restricted Maximum Likelihood (AIREML) method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low to moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One-hundred-and-99 significant single nucleotide polymorphisms (SNP) located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle.

Estimation of genetic parameters for growth traits and kleiber ratio in dorper sheep breed

The study aimed to estimate genetic and phenotypic parameters for growth traits and Kleiber ratio in Dorper sheep breed. Data used in this study were collected over 12 years (2012–2023) at Debre Birhan Agricultural Research Center sheep research station in Ethiopia. Studied traits were body weights at birth (WT0), weaning (WT3), six month (WT6), and yearling (WT12) age; average daily gains from birth to weaning (ADG0-3), from weaning to six months (ADG3-6), from six months to yearling (ADG6-12); and Kleiber ratios from birth to weaning (KR1) and from weaning to six months (KR2). The (co)variance components were estimated with different animal models using Average Information Restricted Maximum Likelihood (AI-REML) procedure. The best-fitted model for each trait was determined using likelihood ratio tests. Phenotypic performance for WT3, WT6, WT12, ADG0-3 and ADG3-6 showed a decline trend at a rate of 0.216 kg, 0.794 kg, 0.671 kg, 2.601 g and 4.865 g over years respectively. However, WT3, WT6, WT12, ADG0-3 showed a positive genetic improvement trend at a rate of 0.029 kg, 0.043 kg, 0.049 kg and 0.257 g over years respectively. Year of birth had a significant effect (P < 0.001) on all studied traits. Model including direct genetic as well as permanent environmental effect (Model 2) was chosen as the most appropriate model for WT0. Model which included only direct genetic effect (Model 1) was the best-fit model for all other studied traits. Direct heritability estimates based on suitable models were 0.07 ± 0.06, 0.11 ± 0.06, 0.09 ± 0.07, 0.11 ± 0.09 0.11 ± 0.06, 0.00 ± 0.04, 0.15 ± 0.07 and 0.00 ± 0.04 for WT0, WT3, WT6, WT12, ADG0-3, ADG3-6, KR1 and KR2 respectively. The variance ratio for the permanent environmental effect was 0.13 ± 0.04 for WT0. Genetic correlations among the traits ranged from negative (−0.39) for WT0-KR1 to high (0.99) for WT3-ADG0-3 and phenotypic correlations ranged from negative (−0.31) for WT0-KR1 to high (0.98) for WT3-ADG0-3. The low direct heritability estimates for the studied traits indicated that genetic improvement by direct selection might be difficult. Further investigation for the unexpected declined trend of phenotypic performance over years need to be required.

Estimation of (Co) Variance Components and Genetic Parameters for Pre- and Post-Weaning Growth Traits in Dağlıç Sheep.

The goal of this study was to estimate (co) variance components and genetic parameters for pre- and post-weaning growth traits in Dağlıç sheep, considering the direct additive genetic, maternal genetic, and maternal permanent environmental effects, with different statistical models. The information of 21,735 native Dağlıç lambs born between 2011 and 2021 was used to estimate (co) variance components by the Average Information-Restricted Maximum Likelihood algorithm. The results showed that the most suitable model was Model 3 for birth weight (BW), average daily gain (ADG), and weaning weight (WW). Model 4 was the most appropriate for weight at three (W3), weight at six (W6), and weight at twelve months of age (W12). The direct heritabilities for BW, W3, ADG, WW, W6, and W12 were 0.35 ± 0.02, 0.36 ± 0.03, 0.27 ± 0.02, 0.22 ± 0.02, 0.47 ± 0.05, and 0.47 ± 0.05, respectively. Genetic and phenotypic correlations amongst the traits were in the range of 0.103 ± 0.008 to 0.995 ± 0.002. These results can be used for the improvement of growth traits in the Dağlıç breed of sheep through selection.

Genetic and Phenotypic Trend and Inbreeding Effects for Sexual and Egg Production Traits of Iraqi Local Chickens

A study was conducted to estimate genetic and phenotypic trend and inbreeding effect on a sexual and egg production trait in Iraqi brown local chickens. Data on 2234 hens raised in poultry research stations from successive 6 generations of selection for high egg production during the first 24 weeks of production were used. Data of age at sexual maturity (ASM), body weight at sexual maturity (BWSM), first egg weight (FEWT), egg weight (EW), egg number (EN), and egg mass (EM) were recorded individually. The univariate animal models under Average Information Restricted Maximum Likelihood (AI-REML) of Wombat package were applied to estimate the heritability, BLUP-breeding value and inbreeding rate. The heritability estimates based on individual animal model was 0.39±0.05, 0.42±0.05, 0.17±0.04, 0.68±0.04, 0.40±0.05 and 0.40±0.05 for the traits mentioned above respectively. Average breeding values across generation tend to be positive in productive traits but it was negative in ASM, BWSM and FEW. The overall predicted genetic gains, after 6 generations of selection, estimated by the regression coefficients of the breeding value on generation number were equal to -0.010, 0.029, 0.033, -0.397, -1.514, and -41.541, for ASM, BWSM, FEWT, EW, EN and EM, respectively. In conclusion, the moderate to high heritability estimated for egg production traits suggested that these traits could be improved through selection. The effect of the inbreeding rate negatively on some traits and positively on other traits suggested that both traits could not be improved simultaneously using additive selection. The inconsistency between phenotypic and genetic trends suggests that genetic progress was not achieved in a higher magnitude.

Optimizing selection strategy for enhancing reproduction efficiency in Indian crossbred goats using milk productivity as a selection criterion.

The present study was aimed at optimizing the selection strategy for enhancing reproductive efficiency and milk productivity of Alpine × Beetal crossbred goats. The data set included 2949 milk trait records across parities and 1389 milk records from first parity and corresponding reproductive traits. The traits included for analysis were 150-day milk yield (150DMY), days in milk (DIM), peak yield (PY) and total milk yield (TMY). The litter size (LS) and litter weight (LW) were used for specifically formulating selection plan using indirect selection. The least squares mean for lactation traits during the first parity were 150DMY: 195.32 ± 2.09 kg, DIM: 236.42 ± 3.04 days, PY: 1.82 ± 0.02 kg, TMY: 269.62 ± 4.52 kg. Notably, Alpine × Beetal goats demonstrated genetic superiority pan India for milk productivity as compared to other native goat breeds. The least squares mean for 150DMY across all parities was 236 ± 3.13 kg. An animal model employing average information restricted maximum likelihood was used for (co)variance component estimation to get the genetic parameters. The analysis revealed total heritability estimates for 150DMY, DIM, PY and TMY as 0.18 ± 0.06, 0.04 ± 0.04, 0.12 ± 0.06 and 0.08 ± 0.05, respectively. Repeatability estimates for 150DMY, DIM, and TMY were 0.28 ± 0.04, 0.21 ± 0.03 and 0.37 ± 0.03, respectively. Bivariate analysis of 150DMY with reproductive traits revealed heritability for LS and LW as 0.05 ± 0.01 and 0.10 ± 0.01, respectively using Gibbs sampling. Strong and positive genetic correlations of 150DMY with other production and reproduction traits was observed, such as DIM (0.72), PY (0.98), TMY (0.88), LS (0.57) and LW (0.33). Moderate heritability and repeatability estimate of 150DMY, along with its positive correlation with production and reproductive traits suggested it as a suitable selection criterion for early selection and overall genetic progress of lactation traits. The genetic trend analysis showed an overall improvement in all these traits, with observed gain of 98.4 g per year for 150DMY, 0.04 days per year for DIM, 0.5 g per year for PY and 220.5 g per year for TMY. We observed that selecting based on 150DMY would lead to a favourable indirect improvement for LW as 79 g and LS 0.04 units per generation. We, therefore, recommend employing 150DMY as the single trait selection criteria to enhance both milk productivity and reproductive potential of Alpine × Beetal goats.

GENETIC PARAMETERS AND CORRELATIONS OF EARLY WEIGHT TRAITS IN A NIGERIAN INDIGENOUS HEAVY X LIGHT ECOTYPES POPULATION OF CHICKENS

&lt;p&gt;&lt;strong&gt;Background&lt;/strong&gt;: Improvement of the Nigerian indigenous chickens is desirable because of its socioeconomic important. &lt;strong&gt;Objective&lt;/strong&gt;: To estimate the heritability, genetic and phenotypic correlations among body weight, body length, wing length and shank length of the mating of heavy ecotype cocks with light ecotype hens of Nigerian indigenous chickens. &lt;strong&gt;Methodology&lt;/strong&gt;: The mating design was such that one heavy ecotype cock mated with 10 light ecotype hens in twenty replicate pens. The mating produced 752 chicks from ten batches of hatch. The estimates of variance components were obtained from paternal half sib analysis using the average information restricted maximum likelihood of BLUPF90 family of programs. &lt;strong&gt;Results&lt;/strong&gt;: The heritability of body weight ranged from 0.20 to 0.44 from 6 to 12 weeks of age. Similarly, the heritability of body length, wing length and shank length ranged from 0.39 to 0.63, 0.51 to 0.71 and 0.31 to 0.54 respectively from 6 to 12 weeks of age. The genetic correlations among the early growth traits measured were negative to positive in magnitude and ranged from -0.99 to 0.66 while the phenotypic correlations ranged from -0.15 to 0.91. &lt;strong&gt;Implication&lt;/strong&gt;: The results imply that early growth traits of light and heavy ecotype Nigerian indigenous chicken could be improved through mass selection. &lt;strong&gt;Conclusion&lt;/strong&gt;: It is concluded from this study that the heritability of early growth traits were moderate to high in magnitude and the genetic and phenotypic correlations mostly positive.&lt;/p&gt;

Estimation of Additive and Dominance Genetic Variances for Growth and Multiple‐stress at Different Ages in Litopenaeus vannamei

AbstractThis study aimed to estimate the additive and dominance genetic variance in growth and multiple stress‐tolerance traits in 7 week and 15 week Litopenaeus vannamei shrimp. Four different animal models were studied by including all or different subsets of the following effects: additive genetic effects (A), additive genetic and common environmental effects (A+C), additive genetic and dominance effects (A+D), and additive, common environmental, and dominance effects (A+D+C). Variance components were estimated using the Average Information Restricted Maximum Likelihood (AIREML) method. In general, estimates of additive genetic variance were inflated under the simple model (A) and decreased remarkably under the more complex models (A+C, A+D, and A+D+C). The genetic parameters of two‐stage (7 week and 15 week shrimp) growth and multiple stress‐tolerance traits were more suitable for estimation using the A+C model. The additive effects (0.311~0.754) of seven traits in 7 week shrimp were greater than the dominance effects (4.950× 10‐7~0.201), whereas the additive effects of the same seven traits in adult shrimp ranged from 7.712×10‐8 to 0.468 and the dominance effects ranged from 0.074 to 0.577. Except for survival time, carapace length, and carapace width, the additive effects of the other traits were smaller than the corresponding dominance effects. Thus, better genetic improvement of 7 week and 15 week shrimp growth and multiple‐stress tolerance can be obtained with selective breeding than with cross‐breeding, and better genetic improvement of 7 week shrimp growth traits can be obtained with cross‐breeding than with selective breeding. Our study further enriches the database for enhancing growth and stress resistance in L. vannamei and provides reference information for growth improvement and multiple stress‐resistance breeding.

Growth rate and efficiency-related traits in Kermani lambs: estimations of (co)variance components and genetic parameters.

Using Kermani sheep, the current study estimated (co)variance components and genetic parameters for average daily gain, Kleiber's ratio, growth efficiency, and relative growth rate. Data were analyzed by the average information restricted maximum likelihood (AI-REML) method using six animal models with different combinations of direct and maternal effects. The best-fitting model was determined after testing for improvement in log-likelihood values. The estimates of h2 for average daily gain (ADG), Klieber's ratio (KR), growth efficiency (GE), and relative growth rate (RGR) in pre- and post-weaning phases were 0.13 ± 0.6 and 0.17 ± 0.02, 0.12 ± 0.04, and 0.16 ± 0.03; 0.05 ± 0.05 and 0.07 ± 0.03 and 0.06 ± 0.02 and 0.07 ± 0.01, respectively. Maternal heritabilities (m2) ranged from 0.03 ± 0.01 for relative growth rate in pre-weaning phase to 0.11 ± 0.04 for average daily gain in post-weaning period. The maternal permanent environmental component (Pe2) accounted for 3 to 13% to the phenotypic variance for all the studied traits. Estimated values of additive coefficient of variations (CVA) ranged from 2.79% for relative growth rate at 6 months of age to 23.74% for growth efficiency at yearling age. Genetic and phenotypic correlations among traits were ranged from -0.687 to 0.946 and -0.648 to 0.918, respectively. The result indicated that selection for growth rate and efficiency-related traits would also be less effective in achieving genetic change, because there was little additive genetic variation among Kermani lambs.

Devising a selection strategy for the Jamunapari goat for improving lactation performance.

This study aimed to evaluate the genetic potential of the Jamunapari goat and formulate a selection strategy for improving lactation traits. The data set included 4049 phenotypic records for across parity milk yield at 90days (MY90), 140days (MY140), total milk yield (TMY), and lactation length (LL) obtained from the progeny of 83 sires and 1643 dams between the period 1990 and 2019. Animal model employing average information restricted maximum likelihood (AIREML) was used to estimate genetic parameters for milk yield traits and LL. The direct additive heritability estimates for across parity lactation traits that used repeatability model were 0.10 ± 0.03, 0.08 ± 0.03, and 0.12 ± 0.02 for MY90, MY140, and TMY, respectively, while it was low for LL (0.06 ± 0.02). The repeatability estimates were moderate ranging from 0.17 to 0.22 for milk yield traits and LL, indicating persistent performance over the parities. Animal permanent environment influence (c2) was significant in milk yield attributes, whereas direct maternal genetic effects were absent. As the early selection criteria based on first parity records are essential, we analyzed the data for the first parity separately and obtained moderate h2 estimates, viz., 0.26 ± 0.05, 0.16 ± 0.06, and 0.25 ± 0.06 for MY90, MY140, and TMY, respectively. These estimates augur further scope of selection in Jamunapari goats for higher milk yield. High and positive genetic correlation of MY90 with MY140 (0.97 ± 0.01) and TMY (0.91 ± 0.05) revealed the scope of using MY90 as the selection criterion. Based on these results, we recommend use of first parity MY90 as a single trait selection criterion for genetic improvement of all lactation traits in Jamunapari goat.

Multivariate Animal Model-based Analysis of Fiber Traits in Kashmir Merino Sheep

ABSTRACT An attempt was made in the present study to elucidate the (co)variance components and genetic parameters of fiber traits in Kashmir Merino sheep population using multivariate animal model. The data pertained to a total of 6836 sheep lambs born over a period of 21 years (1997–2017) and included information on different fiber traits [greasy fleece weight at first (GFW1) and second (GFW2) clips; and fiber diameter (FD) and staple length (SL) at second clip]. Genetic analysis was undertaken using average information restricted maximum likelihood (AI-REML) algorithm in WOMBAT program. The model incorporated six fixed (sex of lamb, season and period of birth, farm of origin, breed and type of birth) and two random effects (direct additive genetic and maternal genetic effects without any covariance between them) in it. The additive genetic heritability estimates for fiber traits were 0.300 ± 0.031; 0.289 ± 0.022; 0.254 ± 0.029 and 0.189 ± 0.028 for GFW1, GFW2, FD, and SL, respectively. The maternal genetic heritability estimates were very low for all traits under study. The genetic correlation between different traits was positive and estimates ranged from moderate to high. The results from present study imply that the variation in these traits has genetic basis which can be exploited in the selection programmes for their improvement. The correlation between different fiber traits was found to be favorable, which can lead to indirect selection response upon formulation of efficient breeding programmes.

Estimation of genetic parameters of growth traits for direct and maternal effects in Murrah buffalo.

An understanding of genetic principles and environmental factors affecting the growth traits is essential to implement optimal breeding and selection programs. Early growth is an indicator of future success in production and reproduction status of dairy animals. In this study, a total of 18,989 records of body weight were used to estimate genetic parameters of body weight at birth (BW), 3months (3BW), 6months (6BW), 9months (9BW),12months (12BW), 18months (18BW), 24months (24 BW), 30months (3BW), and 36months (36BW) in Murrah buffalo at ICAR-NDRI Karnal, Haryana, for the period 1974-2019. The genetic parameters were estimated using the average information restricted maximum likelihood (AIREML) procedure by excluding or including maternal effects. Six analytical models were fitted in order to optimize the model for each trait. The most appropriate univariate model was selected based on the log likelihood ratio test (LRT). Influencing factors like calf sex, period of birth, season of birth, and dam's parity were investigated. The results showed that the maternal genetic effects, in addition to direct additive effects, were important for unbiased and accurate genetic parameter estimates of growth traits in Murrah buffaloes. Total heritability estimates h2T1 for BW, 3BW, 6BW, 9BW, 12BW, 18BW, 24BW, 30BW, and 36BW were 0.25, 0.04, 0.14, 0.16, 0.10, 0.15, 0.21, 0.24, and 0.23, respectively. Maternal effect was significant for birth weight and accounted for 13% variation through maternal genetic and 5% variability through maternal permanent environmental effect. Maternal genetic effect was also important for other traits. However, it interfered with the estimates of variance ratios in live weight traits owing to large and negative covariance between direct and maternal genetic effects. Direct genetic correlations between body weight traits were positive and high ranging from 0.10 to 0.94. Results revealed that the Murrah herd has a sizable genetic variability for growth traits and hence, there is sufficient scope for selection for achieving better growth rate if selection in this direction is applied. Owing to higher positive genetic correlation of 6BW with later ages, the scope of indirect selection for optimum growth in later ages can be aimed at by selecting animals for their higher 6-month live weight.

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.

Estimation of genetic parameters of Wood’s lactation curve parameters using Bayesian and REML methods for milk production trait of Holstein dairy cattle

ABSTRACT Bayesian and average information restricted maximum likelihood (AI-REML) approaches were used to estimate variance components and genetic parameters of Wood’s lactation curve parameters of milk production traits in three lactations of Iranian Holstein dairy cows. Wood’s function parameters (a, b, and c) of each lactation were initially estimated for individual cows using the NLIN procedure of the SAS programme, separately. The variance components of the parameters of each lactation were estimated by the AI-REML method using a single-trait animal model inairemlf90 programme. To do this with the Bayesian method by using the Gibbs sampling technique, the same animal model was used in the gibbs3f90 programme. The estimated heritability values by the AI-REML were 0.018, 0.00, and 0.019 for a parameter; 0.015, 0.007, and 0.02 for b parameter; and 0.23, 0.625, and 0.049 for c parameter in the 1st, 2nd, and 3rd lactations, respectively. The corresponding results from the Bayesian procedure (a posterior means) were 0.019, 0.01, and 0.035 for a parameter; 0.018, 0.019, and 0.043 for b parameter; and 0.024, 0.1, and 0.058 for c parameter, respectively. These obtained results reveal that the differences between the Bayesian and AI-REML methods in terms of estimation of heritability and variance components were small.

Estimates of genetic parameters for linear body measurements and prediction of body weight in goat.

The objective of this study is to estimate genetic parameters for linear body measurements along with their correlation to live weight with a focus on devising a scale to predict live weights from body measurement. A total of 142,564 records on body measures and live weights were collected from 8701 Jamunapari goats. Genetic parameters were obtained for body length (L), height at withers (H) and heart girth (G) from birth to adult stage by univariate and multivariate analysis using the average information restricted maximum likelihood method. The best model for body measures at birth included the additive effect of animal and dam along with their covariance and maternal environment, whereas for traits measured later in life, the maternal environment was not significant. After accounting for the direct maternal correlation (ram ), the total heritability estimates for linear body measurements (L,H and G) at the preweaning and postweaning stages of growth ranged from 0.14 to 0.20. Significant genetic variability implies further scope for selection. The genetic correlations of live weight at birth, 3, 6, 9 and 12 months with corresponding L,H and G were high in magnitude indicating scope to select animals for higher weight using morphometric measurements. When weighing scales are unavailable in the field, prediction of weight using L and G was recommended [live weight=(0.291×L)+(0.306×G)-16.8]. We recommend the use of body measurements in the Jamunapari goat breeding program owing to their high genetic correlation with corresponding live weights.

Comparison of different models for estimation of direct and maternal genetic parameters on body weights in Awassi sheep.

The present study was conducted to estimate the (co)variance components for birth and weaning weight (BW and WW) in 8142 Awassi sheep between 2015 and 2017. Estimates were calculated with single-trait analysis by the average information restricted maximum likelihood (AI-REML) method, using a derivative-free algorithm by fitting six different univariate animal models. The negative of the log-likelihood function (LogL), Akaike information criterion (AIC), and Bayesian information criterion (BIC) tests were used for selecting the best fitted model. In addition, the goodness of fit between the two models was compared with the likelihood ratio test (LRT). Depending on the models, and ranged from 0.230 to 0.240 and 0.015 to 0.033 for BW, and 0.108 to 0.168 and 0.024 to 0.081 for WW, respectively. Model 3 for BW and Model 2 for WW were chosen as the best models by LogL comparison criteria. According to the LRT ratio test Model 2, Model 3, and Model 4 for BW and Model 2, Model 3, Model 4, Model 5, and Model 6 for WW were significant (). Including maternal genetic or maternal permanent environmental effects in these models was found to be significant in terms of parameter estimates.

Genetic studies on the estimates of (Co) variance components for growth traits in Barbari goat

The objectives of the current study were to evaluate the genetic progress and variability for growth traits and also to suggest a suitable direction to the existing breeding program of the Barbari goat population in India. The analysis included 10,648 animals descended from 2697 dams and 420 sires at the ICAR-Central Institute for Research on Goats, Makhdoom between 1993 and 2020 (28 years). The effect of fixed factors such as period and season of kidding, sex of the kid, type of birth, parity of doe, and doe weight at kidding on live weights were significant (P < 0.05). Animal models with average information restricted maximum likelihood (AIREML) approach were used to estimate genetic parameters for growth traits. The mean of inbreeding coefficient for the whole pedigree was 2.16%. For the inbred animals it was 3.32%, indicating within normal estimate for average inbreeding in a nucleus flock. Results suggested that the genetic model for additive direct effects of animal and dam and their covariance, as well as dam's permanent environment, was best for birth weight (BW), weaning weight (WW), weight at six months (6 W), and weight at nine months (9 W), whereas the model with direct effects of animal and dam and their covariance was best for weight at 12 months (12 W). The estimates of direct heritability (h2) for Barbari goat were 0.31 ± 0.04, 0.23 ± 0.03, 0.18 ± 0.03, 0.13 ± 0.03 and 0.21 ± 0.04 for BW, WW, 6 W, 9 W, and 12 W, respectively. However, the estimates were influenced by negative correlation between direct additive effects of animal and dam. We also observed substantial variance for additive maternal effect (0.09–0.15) and maternal permanent environment effect (0.11–0.17) across traits analysed. Pre-weaning growth traits had a significant maternal effect that receded as age advanced. The prospect of selecting Barbari goats for growth traits is indicated by moderate h2 estimates. The positive and desired genetic trend revealed favourable response to selection in the nucleus of the Barbari goat for growth traits. The significant and positive genetic and phenotypic correlation between post-weaning weights (6–9 W= 0.89) suggests scope for early selection of Barbari goats by decreasing the age for selection from 9 to 6 months.

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).

Simple SummaryNative chickens play a vital role in the rural economies of many countries and are considered a valuable genetic resource for use in the development of high-yielding breeds. Native breeds are used as foundation stocks for breeding through a system of crossbreeding with commercial breeds, taking advantage of heterosis. However, due to the constraints of their slow growth rate and low egg production, there is insufficient supply to meet consumer demand. Therefore, improving genetic knowledge is one way to solve these problems and achieve sustainable results. In this paper, a multi-trait animal model and a selection index are developed as a solution for this problem to improve growth and egg performance.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 and non-genetic effects associated with ewe productivity in Harnali sheep.

The objective of the current study was to estimate the genetic parameters for ewe productivity traits of Harnali sheep by examining non-genetic effects. The data records of 440 animals born to 85 sires and 259 dams were collected with respect to various traits such as litter size at birth (LSB), litter weight at birth (LWB), litter size at weaning (LSW), litter weight at weaning (LWW) and age at first lambing (AFL) for the period of 2001 to 2020. Genetic parameters were estimated by fitting a series of animal models using an average information restricted maximum likelihood (REML) algorithm in WOMBAT software. Least-squares analysis revealed significant (P < 0.05) influences of period of lambing, age and weight of ewe at lambing on the studied traits. These results indicated that heavier ewes had significantly higher (P < 0.05) values of litter weight traits than their counterparts. On the basis of likelihood ratio test, the estimates of direct heritability under best model for AFL, LSB, LWB, LSW and LWW were 0.06, 0.18, 0.09, 0.07 and 0.16, respectively. Maternal permanent environment effect made a significant contribution to the LSB trait (0.20). The genetic correlation between litter size and LWW was negative, while the remaining correlations were positive. The present results suggest that selection based on ewe productivity traits will result in low genetic progress and therefore the management role is more important for better gains.