scholarly journals Impact of including the cause of missing records on genetic evaluations for growth in commercial pigs

2021 ◽  
Author(s):  
Mary Kate Hollifield ◽  
Daniela Lourenco ◽  
Shogo Tsuruta ◽  
Matias Bermann ◽  
Jeremy T Howard ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Linear Model ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Pedigree Information ◽  
Linear Regression Method ◽  
Classical Models ◽  
Group Sex ◽  
Genetic Evaluations ◽  
Pearson Correlations

Abstract It is of interest to evaluate crossbred pigs for hot carcass weight (HCW) and birth weight (BW); however, obtaining a HCW record is dependent on livability (LIV) and retained tag (RT). The purpose of this study is to analyze how HCW evaluations are affected when herd removal and missing identification are included in the model and examine if accounting for the reasons for missing traits improves the accuracy of predicting breeding values. Pedigree information was available for 1,965,077 purebred and crossbred animals. Records for 503,716 commercial three-way crossbred terminal animals from 2014 to 2019 were provided by Smithfield Premium Genetics. Two pedigree-based models were compared; model 1 (M1) was a threshold-linear model with all four traits (BW, HCW, RT, and LIV), and model 2 (M2) was a linear model including only BW and HCW. The fixed effects used in the model were contemporary group, sex, age at harvest (for HCW only), and dam parity. The random effects included direct additive genetic and random litter effects. Accuracy, dispersion, bias, and Pearson correlations were estimated using the linear regression method. The heritabilities were 0.11, 0.07, 0.02, and 0.04 for BW, HCW, RT, and LIV, respectively, with standard errors less than 0.01. No difference was observed in heritabilities or accuracies for BW and HCW between M1 and M2. Accuracies were 0.33, 0.37, 0.19, and 0.23 for BW, HCW, RT, and LIV respectively. The genetic correlation between BW and RT was 0.34 ± 0.03, and between BW and LIV was 0.56 ± 0.03. Similarly, the genetic correlation between HCW and RT was 0.26 ± 0.04, and between HCW and LIV was 0.09 ± 0.05, respectively. The positive and moderate genetic correlations between BW and other traits imply a heavier BW resulted in a higher probability of surviving to harvest. Genetic correlations between HCW and other traits were lower due to the large quantity of missing records. Despite the heritable and correlated aspects of RT and LIV, results imply no major differences between M1 and M2; hence, it is unnecessary to include these traits in classical models for BW and HCW.

33 Impact of Including the Cause of Missing Records on Genetic Evaluations for Growth in Commercial Pigs

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 18-18
Author(s):  
Mary Kate Hollifield ◽  
Daniela Lourenco ◽  
Shogo Tsuruta ◽  
Matias Bermann ◽  
Jeremy T Howard ◽  
...  
Keyword(s):  
Linear Model ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Pedigree Information ◽  
Linear Regression Method ◽  
Classical Models ◽  
Group Sex ◽  
Genetic Evaluations ◽  
Pearson Correlations ◽  
Crossbred Pigs

Abstract It is of interest to evaluate crossbred pigs for hot carcass weight (HCW) and birth weight (BW); however, obtaining a HCW record is dependent on livability (LIV) and retained tag (RT). The purpose of this study is to analyze how HCW evaluations are affected when herd removal and missing identification are included in the model and examine if accounting for the reasons for missing traits improves the accuracy of predicting breeding values. Pedigree information was available for 1,965,077 purebred and crossbred animals. Records for 503,716 commercial three-way crossbred terminal animals from 2014 to 2019 were provided by Smithfield Premium Genetics. Two pedigree-based models were compared; model 1 (M1) was a threshold-linear model with all four traits (BW, HCW, RT, and LIV), and model 2 (M2) was a linear model including only BW and HCW. The fixed effects used in the model were contemporary group, sex, age at harvest (for HCW only), and dam parity. The random effects included direct additive genetic and random litter effects. Accuracy, dispersion, bias, and Pearson correlations were estimated using the linear regression method. The heritabilities were 0.11, 0.07, 0.02, and 0.04 for BW, HCW, RT, and LIV, respectively, with standard errors less than 0.01. No difference was observed in heritabilities or accuracies for BW and HCW between M1 and M2. Accuracies were 0.33, 0.37, 0.19, and 0.23 for BW, HCW, RT, and LIV respectively. The genetic correlation between BW and RT was 0.34 ± 0.03, and between BW and LIV was 0.56 ± 0.03. The positive and moderate genetic correlations between BW and other traits imply a heavier BW resulted in a higher probability of surviving to harvest. Despite the heritable and correlated aspects of RT and LIV, results imply no major differences between M1 and M2; hence, it is unnecessary to include these traits in classical models for BW and HCW.

Genetic parameters for Australian maternal and dual-purpose meatsheep breeds. III. Liveweight, fat depth and wool production in Coopworth sheep

1994 ◽  
Vol 45 (2) ◽  
pp. 481 ◽  
Author(s):  
LD Brash ◽  
NM Fogarty ◽  
AR Gilmour
Keyword(s):  
Genetic Correlation ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Dual Purpose ◽  
Management Group ◽  
Derivative Free ◽  
Fleece Weight ◽  
Group Sex ◽  
Birth Type

Heritability was estimated for weaning liveweight of 7030 Coopworth sheep from 10 flocks representing 92 sires by derivative-free restricted maximum likelihood procedures using an animal model. Similar analyses were used for yearling liveweight and greasy fleece weight with over 4000 animals, fat depth on 2184 animals and fibre diameter on 966 animals. The fixed effects of flock-year-management group, sex, birth type, rearing type and age were significant for most traits. Estimates of heritability were 0.45 � 0 - 07 for weaning liveweight, 0.38 � 0.07 for yearling liveweight, 0 28 � 0.05 for greasy fleece weight, 0.18 � 0 08 for fibre diameter and 0.13 � 0.04 for ultrasonic fat depth at the C site. The genetic correlations of liveweights with greasy fleece weight were positive, but close to zero with fibre diameter. The genetic correlation between greasy fleece weight and fibre diameter was 0.422 � 0.25. Fat depth was highly genetically correlated with liveweights at weaning (0.53 � 0.22) and yearling (0.64 � 0- 20) ages, was highly negatively correlated with fibre diameter (-0.55 � 0.28) and had a small positive genetic correlation with greasy fleece weight (0.15 � 0.34).

scholarly journals PSVIII-38 Late-Breaking Abstract: Estimating genetic parameters of feed efficiency traits in American mink

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 347-347
Author(s):  
Pourya Davoudi ◽  
Duy Ngoc Do ◽  
Guoyu Hu ◽  
Siavash Salek Ardestani ◽  
Younes Miar
Keyword(s):  
Body Weight ◽  
Genetic Correlation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
American Mink ◽  
Genetic Correlations ◽  
Final Body Weight ◽  
Selection For

Abstract Feed cost is the major input cost in the mink industry and thus improvement of feed efficiency through selection for high feed efficient mink is necessary for the mink farmers. The objective of this study was to estimate the heritability, phenotypic and genetic correlations for different feed efficiency measures, including final body weight (FBW), daily feed intake (DFI), average daily gain (ADG), feed conversion ratio (FCR) and residual feed intake (RFI). For this purpose, 1,088 American mink from the Canadian Center for Fur Animal Research at Dalhousie Faculty of Agriculture were recorded for daily feed intake and body weight from August 1 to November 14 in 2018 and 2019. The univariate models were used to test the significance of sex, birth year and color as fixed effects, and dam as a random effect. Genetic parameters were estimated via bivariate models using ASReml-R version 4. Estimates of heritabilities (±SE) were 0.41±0.10, 0.37±0.11, 0.33±0.14, 0.24±0.09 and 0.22±0.09 for FBW, DFI, ADG, FCR and RFI, respectively. The genetic correlation (±SE) was moderate to high between FCR and RFI (0.68±0.15) and between FCR and ADG (-0.86±0.06). In addition, RFI had low non-significant (P > 0.05) genetic correlations with ADG (0.04 ± 0.26) and BW (0.16 ± 0.24) but significant (P < 0.05) high genetic correlation with DFI (0.74 ± 0.11) indicating that selection for lower RFI will reduce feed intake without adverse effects on the animal size and growth rate. The results suggested that RFI can be implemented in genetic/genomic selection programs to reduce feed intake in the mink production system.

Genetic parameter estimations and genomic insights for teat and udder structure in young and mature Canadian Angus cows

2021 ◽  
Author(s):  
K Devani ◽  
J J Crowley ◽  
G Plastow ◽  
K Orsel ◽  
T S Valente
Keyword(s):  
Animal Model ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Age Groups ◽  
Morbidity And Mortality ◽  
Parameter Estimations ◽  
Angus Cattle ◽  
Genetic Evaluations

Abstract Poor teat and udder structure, frequently associated with older cows, impact cow production and health, as well as calf morbidity and mortality. However, producer culling, for reasons including age, production, feed availability, and beef markets, creates a bias in teat and udder scores assessed and submitted to the Canadian Angus Association for genetic evaluations towards improved mammary structure. In addition, due to the infancy of the reporting program, repeated scores are rare. Prior to adoption of genetic evaluations for teat and udder scores in Canadian Angus cattle, it is imperative to verify that teat and udder scores from young cows are the same trait as teat and udder scores estimated on mature cows. Genetic parameters for teat and udder scores from all cows (n=4,192), and then from young cows (parity 1 and 2) and from mature cows (parity ≥ 4) were estimated using a single trait animal model. Genetic correlations for the traits between the two cow age groups were estimated using a two-trait animal model. Estimates of heritability (PSD) were 0.32 (0.07) and 0.45 (0.07) for young teat and udder score, and 0.27 (0.07) and 0.31 (0.07) for mature teat and udder score, respectively. Genetic correlation (PSD) between the young and mature traits was 0.87 (0.13) for teat score and 0.40 (0.17) for udder score. GWAS were used to further explore the genetic and biological commonalities and differences between the two groups. Although there were no genes in common for the two udder scores, 12 genes overlapped for teat score in the two cow age groups. Interestingly, there were also 23 genes in common between teat and udder scores in mature cows. Based on these findings, it is recommended that producers collect teat and udder score on their cow herd annually.

Results of multivariate individual animal model genetic evaluations of british pedigree beef cattle

1997 ◽  
Vol 65 (2) ◽  
pp. 199-207 ◽  
Author(s):  
R. E. Crumps ◽  
G. Simm ◽  
D. Nicholson ◽  
R. H. Findlay ◽  
J. G. E. Bryan ◽  
...  
Keyword(s):  
Animal Model ◽  
Birth Weight ◽  
Beef Cattle ◽  
Fixed Effects ◽  
Breeding Value ◽  
Individual Animal ◽  
Group Sex ◽  
The Uk ◽  
Genetic Evaluations ◽  
Genetic Trends

AbstractThis paper reports the procedures put into place in the UK for the genetic evaluation of pedigree beef cattle and estimation of genetic trends using a comprehensive model to allow critical analysis of progress made under previous data recording schemes. Live weights of Simmental, Limousin, Charolais, South Devon and Aberdeen Angus beef cattle, recorded by the Meat and Livestock Commission (MLC) from 1970 to 1992 were analysed, as part of a project to introduce best linear unbiased predictions (BLUP) of breeding value in the British beef industry. Birth weights were available from MLC or the relevant breed society, (4000 to 84000 records, depending on the breed) and 200- and 400-day weights were estimated by within-animal linear regression on all available weights (resulting in 8000 to 48000 records per breed). Animals were retrospectively assigned to contemporary groups within herds, separately for each trait, taking account of observed calving patterns. Records were adjusted to correct for heterogeneity of variance between herds. BLUP evaluations were then performed within breed, fitting a multivariate individual animal model. In addition to additive direct genetic effects, additive maternal genetic and dam permanent environmental effects were included for birth weight and 200-day weight. Unknown parents were assigned to genetic groups, based on estimated date of birth. The model included fixed effects for contemporary group, sex, month of birth, birth type (single or multiple), embryo transfer births, fostered calves, breed of dam, proportion purebred and age of dam. Genetic trends were estimated by regressing estimated breeding values for animals on their year of birth. Trends in birth weight, 200-day weight and 400-day weight between 1970 and 1992 were approximately 0·09, 0·73 and 1·38 kg per annum respectively for the Charolais breed; 0·08, 0·76 and 1·33 kg per annum for the Simmental; 0·06, 0·53 and 0·89 kg per annum for the Limousin; 0·12, 1·02 and 1·86 kg per annum for the Aberdeen Angus; and 0·03, 0·38 and 0·82 kg per annum for the South Devon breed.

scholarly journals Analysis of non-genetic and genetic influences underlying the growth of Kajli lambs

2020 ◽  
Vol 50 (4) ◽  
pp. 613-625
Author(s):  
A. Ali ◽  
K. Javed ◽  
I. Zahoor ◽  
K.M. Anjum
Keyword(s):  
Birth Weight ◽  
Genetic Correlation ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Breeding Value ◽  
Season Of Birth ◽  
Genetic Trend ◽  
Breeding Values ◽  
Heritability Estimates ◽  
Birth Type

Data on 2931 Kajli lambs, born from 2007 to 2018, were used to quantify environmental and genetic effects on growth performance of Kajli sheep. Traits considered for evaluation were birth weight (BWT), 120-day adjusted weight (120DWT), 180-day adjusted weight (180DWT), 270-day adjusted weight (270DWT), and 365-day adjusted weight (365DWT). Fixed effects of year of birth, season of birth, sex, birth type, and dam age on these traits were evaluated using linear procedures of SAS, 9.1. Similarly, BWT, 120DWT, 180DWT, and 270DWT were used as fixed effects mixed model analyses. Variance components, heritability and breeding values were estimated by restricted maximum likelihood. The genetic trend for each trait was obtained by regression of the estimated breeding values (EBV) on year of birth. Analyses revealed substantial influence of birth year on all traits. Sex and birth type were the significant sources of variation for BWT and 120DWT. Season of birth did not influence birth weight meaningfully, but had a significant role in the expression of 120DWT, 180DWT, and 270DWT. Heritability estimates were generally low (0.003 ± 0.018 to 0.099 ± 0.067) for all traits. With the exception of the genetic correlation of 180DWT and 365DWT, the genetic correlations between trait were strong and positive. Only 365DWT had a positive genetic trend. Although the heritability estimates for almost all weight traits were low, high and positive genetic correlations between BWT and other weight traits suggest that selection based on BWT would result in the improvement of other weight traits as a correlated response.Keywords: bodyweight, breeding value, genetic correlation, sheep

scholarly journals Heritability and genetic correlations of feed intake, body weight gain, residual gain, and residual feed intake of beef cattle as heifers and cows

2020 ◽  
Vol 98 (1) ◽  
Author(s):  
Harvey C Freetly ◽  
Larry A Kuehn ◽  
Richard M Thallman ◽  
Warren M Snelling
Keyword(s):  
Beef Cattle ◽  
Genetic Correlation ◽  
Feed Intake ◽  
Body Weight Gain ◽  
Genetic Correlations ◽  
Residual Feed Intake ◽  
Feed Resources ◽  
Genetic Evaluations ◽  
The Relationship ◽  
Made In

Abstract The cow herd consumes approximately 70% of the annual feed resources. To date, most genetic evaluations of feed intake in beef cattle have been made in growing animals and little information is available for mature cows. Genetic evaluations in mature cows have predominately been confined to lactating dairy cows and the relationship between feed intake as growing heifers and mature cows has not been addressed. It was the purpose of this study to estimate the heritability of feed intake when measured as growing heifers and mature cows and determine the genetic correlation between these measurements. Individual feed intake and BW gain were measured on 687 heifers and 622 5-yr-old cows. The heritability of average daily DMI (ADDMI) estimated in heifers was 0.84 ± 0.12 and 0.53 ± 0.12 in cows. The heritability of ADG estimated in heifers was 0.53 ± 0.12 and 0.34 ± 0.11 in cows. The genetic correlation between heifer and cow ADDMI was 0.84 ± 0.09. The genetic correlation between heifer and cow ADG was 0.73 ± 019. Heritability of residual feed intake in heifers was 0.25 ± 0.11 and 0.16 ± 0.10 in cows. Heritability for residual gain in heifers was 0.21 ± 0.11 and 0.14 ± 0.10 in cows. Feed intake and ADG are heritable and genetically correlated between heifers and cows. Selection for decreased feed intake and ADG in growing animals will probably have the same directional effects on mature cows.

scholarly journals Association Between Backfat Thickness at 28 Weeks Old and Production Traits of Primiparous Landrace Sows Raised Under Tropical Conditions

2021 ◽  
Author(s):  
Praew Thiengpimol ◽  
Skorn Koonawootrittriron ◽  
Thanathip Suwanasopee
Keyword(s):  
Genetic Correlation ◽  
Selection Index ◽  
Genetic Correlations ◽  
High Standard ◽  
Backfat Thickness ◽  
Pedigree Information ◽  
Production Traits ◽  
Population Means ◽  
Maximum Likelihood Procedure ◽  
Tropical Conditions

Abstract Backfat thickness could reflex energy reserve of the female pigs that is required for their productivity, especially gilts that might be selected for the replacements. Therefore, phenotypic and genetic correlations between backfat thickness (BF) and production traits were estimated and considered for the possibility of using BF at pre-selective stage as an early indicator for productivity of the sow. Pedigree information, BF and body weight (BW) at 28 weeks old, age at first farrowing (AFF), transformed proportion of piglet loss at birth (tPL) and transformed weaning to first service interval (tWSI) of 806 primiparous Landrace sows were used to estimate the variance components by restricted maximum likelihood procedure with an average information algorithm for multivariate analysis. Genetic correlation between BF and BW was 0.70 ± 0.13. Both BF and BW had negative genetic correlation with AFF, but not tWSI. Unfortunately, genetic correlation estimates between tPL and other traits was unclear due to high standard error. The genetic correlation between AFF and tWSI was 0.78 ± 0.36. Besides 19.35% of sires, 26.34% of dams and 25.81% of sows had genetic ability for BF, BW, AFF and WSI above the population means. The genetic association between BF, BW, AFF and tWSI indicated the feasibility of using selection index to improve BF and BW at pre-selective stage and reduce AFF and tWSI of replacement gilt simultaneously. However, the estimation of genetic correlation between PL and other traits should be repeated in a larger population.

scholarly journals 39 Impact of inclusion rates of crossbred phenotypes and genotypes in nucleus selection programs

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 8-8
Author(s):  
Garrett See ◽  
Benny E Mote ◽  
Matthew L Spangler
Keyword(s):  
Genetic Correlation ◽  
Cost Benefit ◽  
Snp Markers ◽  
Minimal Change ◽  
Pedigree Information ◽  
Benefit Ratio ◽  
Cost Benefit Ratio ◽  
Genetic Evaluations ◽  
The Cost

Abstract The aim of this study was to investigate different inclusion rates of purebred (PB) and CB phenotypes and genotypes in genetic evaluations. Assuming PB and CB traits with moderate heritabilities (h2 = 0.4), a three-way swine crossbreeding scheme was simulated, and selection was practiced for 6 generations. The goal was to increase the CB phenotype. Phenotypes, genotypes and pedigrees for three purebred breeds (each consisting of 25 males and 175 females), F1 crosses (400 females) and terminal cross progeny (2500) were simulated using AlphaSimR. The genome consisted of 18 chromosomes with 1,800 QTL and 59.4k SNP markers. Selection was performed using EBV produced by the BLUPf90 suite of programs for each phenotyping/genotyping strategy. Strategies investigated were 1) increasing the proportion of CB with genotypes, phenotypes and sire pedigree information, 2) decreasing the proportion of PB phenotypes and genotypes, and 3) altering the genetic correlation between PB and CB traits (rpc). Each strategy was replicated 15 times. Results showed that including CB performance improved the CB phenotype regardless of rpc or phenotyping/genotyping strategy. Compared to using only PB information, including 10% of possible CB animals per generation with sire pedigrees and phenotypes increased the response in CB phenotype when rpc was 0.1, 0.3, 0.5, 0.7, and 0.9 by 192, 64, 41, 25 and 21%, respectively. Including CB genotypes dramatically improved the previously mentioned increases in response. Minimal change was observed in the CB phenotype when PB phenotypes were included or removed, if CB phenotypes, genotypes and sire pedigrees were included. PB genotypes were more informative than phenotypes in enabling prediction for CB traits. In practice, the inclusion rates of CB and PB data depends upon the degree of connectedness between CB animals and PB selection candidates and the cost-benefit ratio of increased CB performance and genotyping/phenotyping costs.

scholarly journals Genetic evaluation of partial growth trajectory of Santa Inês breed using random regression models

2010 ◽  
Vol 39 (5) ◽  
pp. 1029-1036 ◽  
Author(s):  
Kassiana Adriano Pinto de Oliveira ◽  
Raimundo Nonato Braga Lôbo ◽  
Olivardo Facó
Keyword(s):  
Legendre Polynomials ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Growth Trajectory ◽  
Random Regression ◽  
Data Set ◽  
Average Growth ◽  
Santa Inês ◽  
Group Sex ◽  
Different Order

It was evaluated data set of 19,303 weight records of Santa Inês sheep in order to evaluate distinct polynomial functions with different order for better adjustements of fixed and random regressions of growth trajectory and to estimate (co)variances components and genetic parameters of this trajectory. Fixed effects used in analysis were contemporary group, sex and birth type. Ordinary and Legendre polynomials, ranging from two to four orders, were evaluated for fixed regression of average growth trajectory. Legendre and quadratic b-spline functions, ranging from three to four orders, were evaluated for random regressions. Legendre polynomials of order fourth were suitable to fit random regression, while ordinary polynomials of third order were the best for fixed trajectory. Direct heritabilities on days 1, 50, 150, 250 and 411 were 0.24, 0.12, 0.44, 0.84, and 0.96, respectively, while maternal heritabilities for the same ages were 0.24, 0.19, 0.09, 0.02, and 0.01, respectively. Genetic correlations among weights in subsequent ages were high, tending to unity, and there were negative correlations between weights at early ages and weights at late ages. It is possible to modify the growth trajectory by selection with the observed genetic variability. Genetic control of weights at initial ages is not the same in late ages. So, selection of animals for slaughter in early age must be different from that of replacement animals.

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