Beef trait genetic parameters based on old and recent data and its implications for genomic predictions in Italian Simmental cattle

Abstract This study aimed to evaluate the changes in variance components over time to identify a subset of data from the Italian Simmental (IS) population that would yield the most appropriate estimates of genetic parameters and breeding values for beef traits to select young bulls. Data from bulls raised between 1986 and 2017 were used to estimate genetic parameters and breeding values for four beef traits (average daily gain [ADG], body size [BS], muscularity [MUS], and feet and legs [FL]). The phenotypic mean increased during the years of the study for ADG, but it decreased for BS, MUS, and FL. The complete dataset (ALL) was divided into four generational subsets (Gen1, Gen2, Gen3, and Gen4). Additionally, ALL was divided into two larger subsets: the first one (OLD) combined data from Gen1 and Gen2 to represent the starting population, and the second one (CUR) combined data from Gen3 and Gen4 to represent a subpopulation with stronger ties to the current population. Genetic parameters were estimated with a four-trait genomic animal model using a single-step genomic average information restricted maximum likelihood algorithm. Heritability estimates from ALL were 0.26 ± 0.03 for ADG, 0.33 ± 0.04 for BS, 0.55 ± 0.03 for MUS, and 0.23 ± 0.03 for FL. Higher heritability estimates were obtained with OLD and ALL than with CUR. Considerable changes in heritability existed between Gen1 and Gen4 due to fluctuations in both additive genetic and residual variances. Genetic correlations also changed over time, with some values moving from positive to negative or even to zero. Genetic correlations from OLD were stronger than those from CUR. Changes in genetic parameters over time indicated that they should be updated regularly to avoid biases in genomic estimated breeding values (GEBV) and low selection accuracies. GEBV estimated using CUR variance components were less biased and more consistent than those estimated with OLD and ALL variance components. Validation results indicated that data from recent generations produced genetic parameters that more appropriately represent the structure of the current population, yielding accurate GEBV to select young animals and increasing the likelihood of higher genetic gains.

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Estimation of genetic parameters and accuracy of genomic prediction for production traits in Duroc pigs

Czech Journal of Animal Science ◽

10.17221/150/2018-cjas ◽

2019 ◽

Vol 64 (No. 4) ◽

pp. 160-165 ◽

Cited By ~ 1

Author(s):

Bryan Irvine Lopez ◽

Vanessa Viterbo ◽

Choul Won Song ◽

Kang Seok Seo

Keyword(s):

Genomic Prediction ◽

Genetic Parameters ◽

Average Daily Gain ◽

Genetic Correlations ◽

Single Step ◽

Production Traits ◽

Muscle Area ◽

Genomic Breeding ◽

Breeding Values ◽

Heritability Estimates

Abstract: Genetic parameters and accuracy of genomic prediction for production traits in a Duroc population were estimated. Data were on 24 828 purebred Duroc pigs born in 2000–2016. After quality control procedures, 30 263 single nucleotide polymorphism markers and 560 animals remained that were used to predict the genomic breeding values of individuals. Accuracies of predicted breeding values for average daily gain (ADG), backfat thickness (BF), loin muscle area (LMA), lean percentage (LP) and age at 90 kg (D90) between pedigree-based and single-step methods were compared. Analyses were carried out with a multivariate animal model to estimate genetic parameters for production traits while univariate analyses were performed to predict the genomic breeding values of individuals. Heritability estimates from pedigree analysis were moderate to high. Heritability estimates and standard error for ADG, BF, LMA, LP and D90 were 0.35 ± 0.01, 0.35 ± 0.11, 0.24 ± 0.04, 0.42 ± 0.11 and 0.37 ± 0.03, respectively. Genetic correlations of ADG with BF and LP were low and negative. Genetic correlations of LMA with ADG, BF, LP and D90 were –0.37, –0.27, 0.48 and 0.31, respectively. High correlations were observed between ADG and D90 (–0.98), and also between BF and LP (–0.93). Accuracies of genomic breeding values for ADG, BF, LMA, LP and D90 were 0.30, 0.33, 0.38, 0.40 and 0.28, respectively. Corresponding accuracies using pedigree-based method were 0.29, 0.32, 0.38, 0.39 and 0.27, respectively. The results showed that the single-step method did not show significant advantage compared to the pedigree-based method.

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211 Changes in genetic parameters of fitness and growth traits under genomic selection in pigs

Journal of Animal Science ◽

10.1093/jas/skz258.081 ◽

2019 ◽

Vol 97 (Supplement_3) ◽

pp. 41-41

Author(s):

Jorge Hidalgo ◽

Shogo Tsuruta ◽

Daniela Lourenco ◽

Yijian Huang ◽

Kent Gray ◽

...

Keyword(s):

Genetic Variation ◽

Genomic Selection ◽

Variance Components ◽

Genetic Parameters ◽

Growth Traits ◽

Average Daily Gain ◽

Genetic Correlations ◽

Data Set ◽

Daily Gain ◽

Over Time

Abstract Genomic selection increases intensity of selection and decreases generation interval. However, intensive selection reduces genetic variation and can strengthen undesirable genetic correlations. The purpose of this study was to investigate changes in genetic parameters of litter size (LS), number born alive (NBA), number born dead (NBD) and average daily gain (ADG) and weight at off-test (WT) in pigs over time. The data set contained 20,086 (LS), 21,230 (NBA), 21,230 (NBD), 144,717 (ADG) and 144,718 (WT) phenotypic records. Pedigree file included 369,776 animals born between 2001 and 2018, of which 39,038 were genotyped. Two trait models were evaluated (LS-ADG, LS-WT, NBA-ADG, NBA-WT, NBD-ADG and NBD-WT) using 3-year sliding subsets starting from 2010. Variance components and genetic parameters were estimated using GIBBS2F90 program. Computations were performed with (BLUP) or without (ssGBLUP) genotypes. For BLUP (ssGBLUP), the changes in heritability from 2010–2012 to 2015–2018 were 0.08 to 0.09 (0.08 to 0.06) for LS, 0.33 to 0.24 (0.37 to 0.16) for ADG, 0.11 to 0.07 (0.10 to 0.07) for NBD, and 0.32 to 0.24 (0.38 to 0.17) for WT. Differences were also observed for genetic correlations as they were -0.23 to -0.73 (-0.31 to -0.58) for LS-ADG, -0.24 to -0.74 (-0.31 to -0.50) for LS-WT, -0.33 to -0.65 (-0.41 to -0.53) for NBA-ADG, -0.35 to -0.66 (-0.42 to -0.45) for NBA-WT, 0.12 to 0.04 (0.12 to 0.16) for NBD-ADG, and 0.11 to 0.05 (0.11 to 0.22) for NBD-WT. Genomic selection in pigs reduced heritabilities and emphasized the antagonistic relationship that are under strong selection. Heritabilities estimated from ssGBLUP declined more than those by BLUP while changes in the genetic correlations were smaller and more gradual by ssGBLUP. Differences between ssGBLUP and BLUP could be caused by genomic pre-selection unaccounted for by BLUP.

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(Co)variance components and genetic parameters for growth rate and Kleiber ratio in fat-tailed Mehraban sheep

Archives Animal Breeding ◽

10.7482/0003-9438-56-055 ◽

2013 ◽

Vol 56 (1) ◽

pp. 564-572 ◽

Cited By ~ 1

Author(s):

F. Ghafouri-Kesbi

Keyword(s):

Growth Rate ◽

Variance Components ◽

Genetic Parameters ◽

Average Daily Gain ◽

Genetic Correlations ◽

Phenotypic Variance ◽

Genetic Progress ◽

Kleiber Ratio ◽

Derivative Free ◽

Maternal Heritability

Abstract. The aim of the present study was to estimate (co)variance components and genetic parameters for average daily gain from birth to weaning (ADGa), weaning to 6 months (ADGb), weaning to 9 months (ADGc), 6 months to 9 months (ADGd) and corresponding Kleiber ratios (KRa, KRb, KRc and KRd) in Mehraban sheep. A derivative-free algorithm combined with a series of six univariate linear animal models was used to estimate phenotypic variance and its direct, maternal and residual components. In addition, bivariate analyses were done to estimate (co)variance components between traits. Estimates of direct heritability (h2) were 0.10, 0.11, 0.16, 0.09, 0.13, 0.13, 0.15 and 0.08 for ADGa, ADGb, ADGc, ADGd, KRa, KRb, KRc and KRd, respectively and indicate that in Mehraban sheep genes contribute very little to the variance of the growth rate and Kleiber ratio. Estimates of maternal heritability (m2) were 0.10, 0.08 and 0.05 for ADGa, KRa and KRb, respectively. Direct additive genetic correlations ranged from −0.32 (KRa-KRd) to 0.99 (ADGb-KRb) and phenotypic correlations ranged from −0.53 (ADGa- ADGd) to 0.99 (ADGa-KRa). Estimates of direct heritability and genetic correlations show that genetic improvement in efficiency of feed utilization through selection programmes is possible, though it would generate a relatively slow genetic progress.

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Heritability of sow longevity and lifetime prolificacy in Finnish Yorkshire and Landrace pigs

Agricultural and Food Science ◽

10.23986/afsci.7991 ◽

2013 ◽

Vol 22 (3) ◽

pp. 325-330 ◽

Cited By ~ 7

Author(s):

Marja-Liisa Sevón-Aimonen ◽

Pekka Uimari

Keyword(s):

Genetic Variation ◽

Variance Components ◽

Genetic Parameters ◽

Genetic Correlations ◽

Sow Longevity ◽

Piglet Mortality ◽

Heritability Estimates ◽

Mortality Percentage

The objective of this study was to estimate genetic parameters for longevity traits in Finnish pig populations. Analyzed traits were length of productive herd life (LPL), total number of parities (TNP), total number of piglets born (TNB), total number born alive (TBA) and stillborn (TSB), percentage stillborn (SB%), total number of piglets dead before weaning (TPM), mortality percentage (PM%), and total number weaned (TNW). Data contained litter records from 29 805 Finnish Landrace and 25 807 Finnish Yorkshire sows. Variance components were estimated using the AI-REML method. Heritability estimates varied from 0.06 to 0.11 in Finnish Landrace and from 0.09 to 0.12 in Finnish Yorkshire. Genetic correlations were high (> 0.9) between LPL, TNP, TNB, TBA, and TNW, and low between piglet mortality traits (SB% and PM%) and other longevity traits. The obtained heritability estimates indicate that there is sufficient genetic variation for selection.

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Genetic parameters and purebred–crossbred genetic correlations for growth, meat quality, and carcass traits in pigs

Journal of Animal Science ◽

10.1093/jas/skaa379 ◽

2020 ◽

Vol 98 (12) ◽

Author(s):

Hadi Esfandyari ◽

Dinesh Thekkoot ◽

Robert Kemp ◽

Graham Plastow ◽

Jack Dekkers

Keyword(s):

Meat Quality ◽

Genetic Parameters ◽

Carcass Traits ◽

Genetic Correlations ◽

Single Step ◽

Pedigree Information ◽

Genomic Information ◽

Genetic Progress ◽

Wide Range ◽

Heritability Estimates

Abstract Growth, meat quality, and carcass traits are of economic importance in swine breeding. Understanding their genetic basis in purebred (PB) and commercial crossbred (CB) pigs is necessary for a successful breeding program because, although the breeding goal is to improve CB performance, phenotype collection and selection are usually carried out in PB populations housed in biosecure nucleus herds. Thus, the selection is indirect, and the accuracy of selection depends on the genetic correlation between PB and CB performance (rpc). The objectives of this study were to 1) estimate genetic parameters for growth, meat quality, and carcass traits in a PB sire line and related commercial CB pigs and 2) estimate the corresponding genetic correlations between purebred and crossbred performance (rpc). Both objectives were investigated by using pedigree information only (PBLUP) and by combining pedigree and genomic information in a single-step genomic BLUP (ssGBLUP) procedure. Growth rate showed moderate estimates of heritability for both PB and CB based on PBLUP, while estimates were higher in CB based on ssGBLUP. Heritability estimates for meat quality traits were diverse and slightly different based on PB and CB data with both methods. Carcass traits had higher heritability estimates based on PB compared with CB data based on PBLUP and slightly higher estimates for CB data based on ssGBLUP. A wide range of estimates of genetic correlations were obtained among traits within the PB and CB data. In the PB population, estimates of heritabilities and genetic correlations were similar based on PBLUP and ssGBLUP for all traits, while based on the CB data, ssGBLUP resulted in different estimates of genetic parameters with lower SEs. With some exceptions, estimates of rpc were moderate to high. The SE on the rpc estimates was generally large when based on PBLUP due to limited sample size, especially for CBs. In contrast, estimates of rpc based on ssGBLUP were not only more precise but also more consistent among pairs of traits, considering their genetic correlations within the PB and CB data. The wide range of estimates of rpc (less than 0.70 for 7 out of 13 traits) indicates that the use of CB phenotypes recorded on commercial farms, along with genomic information, for selection in the PB population has potential to increase the genetic progress of CB performance.

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Estimation of the Genetic Parameters for Semen Traits in Spanish Dairy Sheep

Animals ◽

10.3390/ani9121147 ◽

2019 ◽

Vol 9 (12) ◽

pp. 1147 ◽

Cited By ~ 1

Author(s):

Rocío Pelayo ◽

Manuel Ramón ◽

Itsasne Granado-Tajada ◽

Eva Ugarte ◽

Malena Serrano ◽

...

Keyword(s):

Variance Components ◽

Genetic Parameters ◽

Genetic Correlations ◽

Response To Selection ◽

Dairy Sheep ◽

Multiple Trait ◽

Adequate Response ◽

Heritability Estimates ◽

Average Information ◽

Moderate Magnitude

This work aimed to estimate genetic parameters for traits related to semen production and quality in Spanish dairy sheep breeds. For that, ejaculates of rams from Assaf, Churra, Latxa Cara Negra, Latxa Cara Rubia, and Manchega breeds were analyzed to measure volume, semen concentration, and motility. Estimates of variance components were obtained with multiple-trait animal models using the average information REML method in the BLUPF90 family of programs. Repeatability estimates for all the traits were also calculated, with values ranging from 0.077 to 0.304 for the motility and the semen concentration traits, respectively. Heritability estimates were of low to moderate magnitude, ranging from 0.014 (motility in Latxa Cara Rubia) to 0.198 (volume in Churra), although the estimates differed among the breeds. The estimated genetic correlations among the three semen traits showed adequate precision only in the MAN breed. The heritability estimates for the semen traits reported in the present paper suggest an adequate response to selection. The practical extension of these results to the other breeds studied here will be secondary to the estimation of more reliable genetic correlations in these breeds.

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Genetic parameters and prediction of breeding values in Castanopsis hystrix A.DC. for growth and form traits

Silvae Genetica ◽

10.1515/sg-2015-0007 ◽

2015 ◽

Vol 64 (1-6) ◽

pp. 81-90 ◽

Cited By ~ 1

Author(s):

F. Q. Zhang ◽

B. Xu ◽

H. X. Yang ◽

W. H. Zhang ◽

B. Z. Zhu ◽

...

Keyword(s):

Variance Component ◽

Genetic Parameters ◽

Genetic Correlations ◽

Forward Selection ◽

Breeding Values ◽

Breast Height ◽

Crown Width ◽

Multipurpose Tree Species ◽

Heritability Estimates ◽

Trait Correlations

AbstractCastanopsis hystrix A.DC. is one of the most important and multipurpose tree species native to China. 157 open-pollinated families collected from 11 provenances in Guangdong, Guangxi, and Fujian province were used to estimate genetic parameters for height (H), diameter at breast height (DBH), ground diameter (GD), and crown width (CW) for each province and combined three provinces at ages from 3 to 9 years. The variance component was small and non-significant among provenances but was highly significant among families within provenances for H, DBH, GD, and CW. Heritability estimates were significant except for a few traits from Fujian’s provenances. Heritability ranged from 0.20 to 0.57 for H, 0.19 to 0.38 for DBH, 0.21 to 0.55 for GD, and 0.09 to 0.39 for CW. Heritability estimates for H and DBH decreased with increased age for each province and combined three provinces. Significantly high genetic correlations were observed for ageage and trait-trait correlations, indicating that genetic performance at one trait was well correlated with another trait. In total, 22 families and 60 individuals were selected for backward and forward selection based on breeding values.

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Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽

10.1093/genetics/143.3.1409 ◽

1996 ◽

Vol 143 (3) ◽

pp. 1409-1416 ◽

Cited By ~ 1

Author(s):

Kenneth R Koots ◽

John P Gibson

Keyword(s):

Genetic Correlation ◽

Genetic Parameters ◽

Genetic Parameter ◽

Genetic Correlations ◽

Phenotypic Correlation ◽

Parameter Estimates ◽

Sampling Variance ◽

Phenotypic Correlations ◽

Genetic And Phenotypic Correlations ◽

Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

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A note on genetic parameters and accuracy of estimated breeding values in honey bees

Genetics Selection Evolution ◽

10.1186/s12711-019-0510-6 ◽

2019 ◽

Vol 51 (1) ◽

Cited By ~ 6

Author(s):

Evert W. Brascamp ◽

Piter Bijma

Keyword(s):

Honey Bees ◽

Variance Components ◽

Genetic Parameters ◽

Additive Genetic Variance ◽

Breeding Value ◽

Phenotypic Variance ◽

Breeding Values ◽

Estimated Breeding Values ◽

Additive Genetic Relationship ◽

The Relationship

Abstract Background In honey bees, observations are usually made on colonies. The phenotype of a colony is affected by the average breeding value for the worker effect of the thousands of workers in the colony (the worker group) and by the breeding value for the queen effect of the queen of the colony. Because the worker group consists of multiple individuals, interpretation of the variance components and heritabilities of phenotypes observed on the colony and of the accuracy of selection is not straightforward. The additive genetic variance among worker groups depends on the additive genetic relationship between the drone-producing queens (DPQ) that produce the drones that mate with the queen. Results Here, we clarify how the relatedness between DPQ affects phenotypic variance, heritability and accuracy of the estimated breeding values of replacement queens. Second, we use simulation to investigate the effect of assumptions about the relatedness between DPQ in the base population on estimates of genetic parameters. Relatedness between DPQ in the base generation may differ considerably between populations because of their history. Conclusions Our results show that estimates of (co)variance components and derived genetic parameters were seriously biased (25% too high or too low) when assumptions on the relationship between DPQ in the statistical analysis did not agree with reality.

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An analysis of the variation in the lean tissue distribution of sheep

Animal Science ◽

10.1017/s0003356100010199 ◽

1982 ◽

Vol 34 (3) ◽

pp. 257-264 ◽

Cited By ~ 13

Author(s):

B. T. Wolf

Keyword(s):

Tissue Distribution ◽

Genetic Correlation ◽

Average Daily Gain ◽

Genetic Correlations ◽

Maximum Difference ◽

Lean Tissue ◽

Heritability Estimates ◽

The Relationship ◽

Daily Gain ◽

Sire Breed

ABSTRACTThe distribution of lean tissue between eight standard joints was examined in 956 crossbred lambs slaughtered at constant live weights of either 35 or 40 kg. The sire breeds used were the Dorset Down, Ile-de-France, Oldenburg, Oxford, Suffolk and Texel. Sire breed did not have a significant effect on the proportion of total carcass lean found in the higher-priced joints but did show significant differences in the proportion of total carcass lean found in individual joints, with a maximum difference of 7·7 g total lean per kg joint being recorded. Similarly, small but significant effects due to ewe age (1 to 3 years), rearing type (single, twin, triplet), sex (male castrate, female) and weight of total lean were reported for the proportion of total carcass lean found in different joints.Heritability estimates ranged from 0·07 (s.e. 008) to 0·65 (s.e. 0·16) for the proportion of total lean in the best-end neck and higher-priced joints respectively. Phenotypic standard deviations of 5·8g/kg and 17·9g/kg were reported for the proportion of total lean found in the best-end neck and the higher-priced joints respectively. The genetic correlations between the proportion of total lean in each of the higher-priced joints and the proportion of total lean in the higher-priced joints combined were positive. A genetic correlation of 017 (s.e. 0·20) was found for the relationship between average daily gain from birth to slaughter and the proportion of total lean in the higher-priced joints.

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