• 제목/요약/키워드: Multiple Traits Animal Model

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한우에 있어서 유전체 육종가 추정 (Prediction of genomic breeding values of carcass traits using whole genome SNP data in Hanwoo (Korean cattle))

  • 이승환;김형철;임다정;당창권;조용민;김시동;이학교;이준헌;양보석;오성종;홍성구;장원경
    • 농업과학연구
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    • 제39권3호
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    • pp.357-364
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    • 2012
  • Genomic breeding value (GEBV) has recently become available in the beef cattle industry. Genomic selection methods are exceptionally valuable for selecting traits, such as marbling, that are difficult to measure until later in life. One method to utilize information from sparse marker panels is the Bayesian model selection method with RJMCMC. The accuracy of prediction varies between a multiple SNP model with RJMCMC (0.47 to 0.73) and a least squares method (0.11 to 0.41) when using SNP information, while the accuracy of prediction increases in the multiple SNP (0.56 to 0.90) and least square methods (0.21 to 0.63) when including a polygenic effect. In the multiple SNP model with RJMCMC model selection method, the accuracy ($r^2$) of GEBV for marbling predicted based only on SNP effects was 0.47, while the $r^2$ of GEBV predicted by SNP plus polygenic effect was 0.56. The accuracies of GEBV predicted using only SNP information were 0.62, 0.68 and 0.73 for CWT, EMA and BF, respectively. However, when polygenic effects were included, the accuracies of GEBV were increased to 0.89, 0.90 and 0.89 for CWT, EMA and BF, respectively. Our data demonstrate that SNP information alone is missing genetic variation information that contributes to phenotypes for carcass traits, and that polygenic effects compensate genetic variation that whole genome SNP data do not explain. Overall, the multiple SNP model with the RJMCMC model selection method provides a better prediction of GEBV than does the least squares method (single marker regression).

반복모형을 이용한 한우 초음파 측정형질의 유전모수추정 (Repeated Records Animal Model to Estimate Genetic Parameters of Ultrasound Measurement Traits in Hanwoo Cows)

  • 박철현;구양모;김병우;선두원;김정일;송치은;이기환;이재윤;정용호;이정규
    • Journal of Animal Science and Technology
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    • 제54권2호
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    • pp.71-75
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    • 2012
  • 본 연구는 한우 암소 초음파 측정자료 특징을 알아보고, 측정형질에 대한 유전모수를 추정하여 육질 또는 육량 개량을 위한 기초자료를 제공하기 위해 수행되었으며, 2001년부터 2009년까지 한국종축개량협회에 의해 측정된 한우 암소 36,893두를 이용하였고, 그 중 반복기록이 있는 개체는 7,913두였다. 유전모수 추정을 위하여 반복개체모형을 이용하였으며, 유전모수 추정에는 REMLF90 (Miztal, 2001)을 이용하였다. 유전모수 추정모형의 설정을 위하여 흉위, 영양도 및 초음파 측정치에 대한 출생년도, 출생계절, 측정년도, 측정계절, 측정지역, 측정연령 등의 환경효과를 추정하였다. 반복개체모형으로 추정된 배최장근단면적, 등지방두께 및 근내지방도에 대한 유전력이 각각 0.31, 0.38, 0.27로 나타났고, 다형질개체모형으로 추정한 유전력은 각각 0.02, 0.09, 0.07로 낮게 추정되었다. 반복개체모형을 이용한 반복력은 배최장근단면적, 등지방두께, 근내지방도가 각각 0.46, 0.57, 0.39로 나타났다. 분석모형 간의 추정치의 차이를 비교 할 때 반복모형에서의 유전력과 반복력이 높게 추정되었다. 따라서 반복형질 값을 가진 형질들의 측정치를 표준화하여 한우암소개량을 위한 기초자료로 활용된다면 유전능력평가와 개량사업 비용절감에 도움이 될 것으로 기대된다.

다형질 Threshold 개체모형에서 Missing 기록을 포함한 이산형 자료에 대한 Bayesian 분석 (Bayesian Analysis for Categorical Data with Missing Traits Under a Multivariate Threshold Animal Model)

  • 이득환
    • Journal of Animal Science and Technology
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    • 제44권2호
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    • pp.151-164
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    • 2002
  • 한우의 근내지방도 또는 임신 여부 등과 같이 이산형 분포의 성질을 갖는 다수의 형질들에 대한 유전모수 및 종축의 유전능력을 평가하기 위한 방법으로써 Threshold 모형하에서 Bayesian 추론방법의 일종인 Gibbs sampling방법을 모의실험을 통하여 알아보았으며 기록이 누락된 다수의 형질을 포함하는 다형질 Threshold 개체모형에서의 종축평가 방법론을 제시하였다. 이산형 형질의 관측치에 대응하는 임의의 잠재변수는 기록을 갖고 있는 형질들에 대한 사전정보를 고려한 사후조건확률분포에서 Gibbs sampling을 할 때 모수에 근접하는 확률분포를 얻을 수 있었으며 이러한 이산형 기록들에 대한 육종가 추정치는 선형모형에서 보다 Threshold 모형에서의 추정치가 실제 모수에 더욱 근접하는 것을 알 수 있었다. 따라서 기록이 누락된 개체들에 대한 이산형 분포를 갖는 형질들에 대하여 선형분포를 갖는 형질들과 함께 동시 유전분석할 때 Threshod 모형이 일반 선형모형 보다 적합함을 알 수 있었다.

Estimation of genetic parameters for pork belly traits

  • Seung-Hoon Lee;Sang-Hoon Lee;Hee-Bok Park;Jun-Mo Kim
    • Animal Bioscience
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    • 제36권8호
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    • pp.1156-1166
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    • 2023
  • Objective: Pork belly is a cut of meat with high worldwide demand. However, although the belly is comprised of multiple muscles and fat, unlike the loin muscle, research on their genetic parameters has yet to focus on a representative cut. To use swine breeding, it is necessary to estimate heritability against pork belly traits. Moreover, estimating genetic correlations is needed to identify genetic relationship among the traditional carcass and meat quality traits. This study sought to estimate the heritability of the carcass, belly, and their component traits, as well as the genetic correlations among them, to confirm whether these traits can be improved. Methods: A total of 543 Yorkshire pigs (406 castrated males and 137 females) from 49 sires and 244 dam were used in this study. To estimate genetic parameters, a total of 12 traits such as lean meat production ability, meat quality and pork belly traits were chosen. The heritabilities were estimated by using genome-wide efficient mixed model association software. The statistical model was selected so that farm, carcass weight, sex, and slaughter season were fixed effects. In addition, its genetic parameters were calculated via MTG2 software. Results: The heritability estimates for the 7th belly slice along the whole plate and its components were low to moderate (0.07±0.07 to 0.33±0.07). Moreover, the genetic correlations among the carcass and belly traits were moderate to high (0.28±0.20 to 0.99±0.31). Particularly, the rectus abdominis muscle exhibited a high absolute genetic correlation with the belly and meat quality (0.73±52 to 0.93±0.43). Conclusion: A moderate to high correlation coefficient was obtained based on the genetic parameters. The belly could be genetically improved to contain a larger proportion of muscle regardless of lean meat production ability.

Estimation of Genetic Variance and Covariance Components for Litter Size and Litter Weight in Danish Landrace Swine Using a Multivariate Mixed Model

  • Wang, C.D.;Lee, C.
    • Asian-Australasian Journal of Animal Sciences
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    • 제12권7호
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    • pp.1015-1018
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    • 1999
  • Single trait mixed models have been dominantly utilized for genetic evaluation of the reproductive traits in swine. However employing multiple trait approach may lead to more accurate genetic evaluations. For 5 litter size and litter weight traits of Danish Landrace, genetic parameters were estimated with a multiple trait mixed model. The heritability estimates were 0.02, 0.03, 0.03, 0.05, and 0.07, respectively for litter size at birth, litter size born alive, litter weight at birth, litter size at weaning, and litter weight at weaning. Negative genetic correlations were all positive. The litter weight at birth showed genetic antagonism with litter size born alive (-0.65) and litter size at weaning (-0.31), but positive with litter size at birth (0.47) and litter weight at weaning (0.31). The estimates of environmental correlations were larger than their corresponding genetic correlation estimates except for those between litter weight at birth and the other four traits. This study recommends simultaneous selection for two or more traits with multivariate mixed models in order to improve overall economic response.

Genetic Parameter Estimation of Carcass Traits of Duroc Predicted Using Ultrasound Scanning Modes

  • Salces, Agapita J.;Seo, Kang Seok;Cho, Kyu Ho;Kim, SiDong;Lee, Young Chang
    • Asian-Australasian Journal of Animal Sciences
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    • 제19권10호
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    • pp.1379-1383
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    • 2006
  • A total of 6,804 records for Duroc breed were collected from three farms registered at the Korean Animal Improvement Association (KAIA) from 1998 to 2004 of which both records from two ultrasound modes (A and B) were analyzed to estimate the variance components of carcass traits. Three carcass traits backfat thickness (bf), loin eye muscle area (lma) and lean meat percentage (lmp) were measured. These traits were analyzed separately as bf1, lma1 and lmp1 for ultrasound mode A and bf2, lma2 and lmp2 for ultrasound mode B with multiple trait animal model by using MTDFREML (Boldman et al., 1993). All the traits revealed medium heritability values. Estimated heritabilities for bf1, bf2, lma1, lma2, lmp1 and lmp2 were 0.45, 0.39, 0.32, 0.25, 0.28 and 0.39, respectively. Estimated genetic correlations for traits bf1 and bf2, lma1 and lma2, lmp1 and lmp2 were positive but low. Specifically, genetic correlations between bf1 and bf2 was 0.30 while the estimates for lean traits between lma1 and lma2 and between lmp1 and lmp2 were 0.15 and 0.18, respectively. Conversely, high negative genetic correlations existed between bf1 and the lean traits lma2, lmp2. Likewise, the estimated genetic correlations between lma1 and lma2 and lmp1 and lmp2 were low.

Multifactor Dimensionality Reduction (MDR) Analysis to Detect Single Nucleotide Polymorphisms Associated with a Carcass Trait in a Hanwoo Population

  • Lee, Jea-Young;Kwon, Jae-Chul;Kim, Jong-Joo
    • Asian-Australasian Journal of Animal Sciences
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    • 제21권6호
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    • pp.784-788
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    • 2008
  • Studies to detect genes responsible for economic traits in farm animals have been performed using parametric linear models. A non-parametric, model-free approach using the 'expanded multifactor-dimensionality reduction (MDR) method' considering high dimensionalities of interaction effects between multiple single nucleotide polymorphisms (SNPs), was applied to identify interaction effects of SNPs responsible for carcass traits in a Hanwoo beef cattle population. Data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, and comprised 299 steers from 16 paternal half-sib proven sires that were delivered in Namwon or Daegwanryong livestock testing stations between spring of 2002 and fall of 2003. For each steer at approximately 722 days of age, the Longssimus dorsi muscle area (LMA) was measured after slaughter. Three functional SNPs (19_1, 18_4, 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the QTL for meat quality were previously detected, were assessed. Application of the expanded MDR method revealed the best model with an interaction effect between the SNPs 19_1 and 28_2, while only one main effect of SNP19_1 was statistically significant for LMA (p<0.01) under a general linear mixed model. Our results suggest that the expanded MDR method better identifies interaction effects between multiple genes that are related to polygenic traits, and that the method is an alternative to the current model choices to find associations of multiple functional SNPs and/or their interaction effects with economic traits in livestock populations.

Estimation of Genetic Parameters and Trends for Weaning-to-first Service Interval and Litter Traits in a Commercial Landrace-Large White Swine Population in Northern Thailand

  • Chansomboon, C.;Elzo, M.A.;Suwanasopee, T.;Koonawootrittriron, S.
    • Asian-Australasian Journal of Animal Sciences
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    • 제23권5호
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    • pp.543-555
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    • 2010
  • The objectives of this research were the estimation of genetic parameters and trends for weaning-to-first service interval (WSI), and litter traits in a commercial swine population composed of Landrace (L), Large White (T), LT, and TL animals in Chiang Mai, Northern Thailand. The dataset contained 4,399 records of WSI, number of piglets born alive (NBA), litter weight of live piglets at birth (LBW), number of piglets at weaning (NPW), and litter weight at weaning (LWW). Variance and covariance components were estimated with REML using 2-trait analyses. An animal model was used for WSI and a sire-dam model for litter traits. Fixed effects were farrowing year-season, breed group of sow, breed group of boar (litter traits), parity, heterosis (litter traits), sow age, and lactation length (NPW and LWW). Random effects were boar (litter traits), sow, permanent environment, and residual. Heritabilities for direct genetic effects were low for WSI (0.04${\pm}$0.02) and litter traits (0.05${\pm}$0.02 to 0.06${\pm}$0.02). Most heritabilities for maternal litter trait effects were 20% to 50% lower than their direct counterparts. Repeatability for WSI was similar to its heritability. Repeatabilities for litter traits ranged from 0.15${\pm}$0.02 to 0.18${\pm}$F0.02. Direct genetic, permanent environment, and phenotypic correlations between WSI and litter traits were near zero. Direct genetic correlations among litter traits ranged from 0.56${\pm}$0.20 to 0.95${\pm}$0.05, except for near zero estimates between NBA and LWW, and LBW and LWW. Maternal, permanent environment, and phenotypic correlations among litter traits had similar patterns of values to direct genetic correlations. Boar genetic trends were small and significant only for NBA (-0.015${\pm}$0.005 piglets/yr, p<0.004). Sow genetic trends were small, negative, and significant (-0.036${\pm}$0.013 d/yr, p<0.01 for WSI; -0.017${\pm}$0.005 piglets/yr, p<0.007, for NBA; -0.015${\pm}$0.005 kg/yr, p<0.01, for LBW; -0.019${\pm}$0.008 piglets/yr, p<0.02, for NPW; and -0.022${\pm}$0.006 kg/yr, p<0.003, for LWW). Permanent environmental correlations were small, negative, and significant only for WSI (-0.028${\pm}$0.011 d/yr, p<0.02). Environmental trends were positive and significant only for litter traits (p<0.01 to p<0.0003). Selection based on predicted genetic values rather than phenotypes could be advantageous in this population. A single trait analysis could be used for WSI and a multiple trait analysis could be implemented for litter traits.

Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials

  • Zaabza, Hafedh Ben;Gara, Abderrahmen Ben;Rekik, Boulbaba
    • Asian-Australasian Journal of Animal Sciences
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    • 제31권5호
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    • pp.636-642
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    • 2018
  • Objective: The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods: A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results: All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from $0.78{\pm}0.01$ to $0.82{\pm}0.03$, between the first and second parities, from $0.73{\pm}0.03$ to $0.8{\pm}0.04$ between the first and third parities, and from $0.82{\pm}0.02$ to $0.84{\pm}0.04$ between the second and third parities. Conclusion: These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.

Methodology of Mapping Quantitative Trait Loci for Binary Traits in a Half-sib Design Using Maximum Likelihood

  • Yin, Zongjun;Zhang, Qin;Zhang, Jigang;Ding, Xiangdong;Wang, Chunkao
    • Asian-Australasian Journal of Animal Sciences
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    • 제18권12호
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    • pp.1669-1674
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    • 2005
  • Maximum likelihood methodology was applied to analyze the efficiency and statistical power of interval mapping by using a threshold model. The factors that affect QTL detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the size of segregating population is 500. The results showed that the threshold model has a great advantage in parameters estimation and power of QTL mapping, and has nice efficiency and accuracy for discrete traits. In addition, the accuracy and power of QTL mapping depended on the effect of putative quantitative trait loci, the value of heritability and incidence directly. With the increase of QTL effect, heritability and incidence of categories, the accuracy and power of QTL mapping improved correspondingly.