• Journal of Embryo Transfer
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• v.22 no.3
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• pp.167-172
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• 2007

Pituitary-specific transcription factor (PIT1) 유전자는 동물의 성장을 조절하고 근육 형성에 관여하는 유전자로서 최근에는 단일염기다형성 변이가 한우를 비롯한 동물에서 관찰되었으며, 한우의 경제 형질과 연관성이 보고되었다. 본 연구는 PIT1 유전자의 단일염기다형성 변이가 한우에서 성장 인자에 미치는 영향과 경제 형질에 대한 유전자형간 육종가와의 상관성에 대해 알아보고자 하였다. 도체 성적을 보유하고 있는 한우 후보종모우 집단 268두를 대상으로 PIT1 유전자 A1256G 다형성을 조사하여 유전자형의 빈도를 분석하였고 각각의 유전형에 따른 기본적인 검정 성적을 바탕으로 경제 형질과의 연관성을 비교 분석하였다. 268두의 한우에서 PIT1 유전자의 A1256G 유전자형 빈도는 MseI 제한 효소를 사용했을 때 A 유전자 빈도(0.37)보다 G 유전자 빈도(0.62)가 높게 나타났다. 통계적 분석을 통하여 각 유전자형에 대한 경제 형질과의 관련성을 분석한 결과, 각 유전자형 간에 12개월령 체중 (body weight 12, BW12)에서 유의한 차이를 보였고, 등지방 두께 육종가 (Backfat thickness-estimated breeding value, BF-EBV)와도 유의한 차이가 있었지만 (p<0.05), marbling score (MS), carcass weight (CW), M. longissimus dorsi area (LDA) 등 다른 경제 형질과는 통계학적으로 유의한 차이가 없었다. PIT1 유전자의 A1256G 다형성은 한우의 성장과 도체체중에 관여하는 인자로 작용하는 것으로 보여진다.

• Journal of Life Science
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• v.28 no.7
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• pp.795-801
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• 2018

This study was conducted to investigate the association of single nucleotide polymorphism (SNP) markers on equine chromosomes (ECA) 3 and 9 with body weight in Jeju horses. We used DNA samples and body weight data of 320 horses provided by the Livestock Promotion Agency, Jeju Special Self-Governing Province, and the Korean Racing Association, respectively. We genotyped all the experimental animals using nine SNP markers located on ECA 3 (BIEC2-808466, BIEC2-808543, BIEC2-808967, and BIEC2-809370) and ECA 9 (BIEC2-1105370, BIEC2-1105372, BIEC2-1105377, BIEC21105505, and BIEC2-1105840). These markers were selected due to their effects on body conformation traits in horses. The joint effect of the genotypes of the two SNP markers (BIEC2-808467 and BIEC2-1105377) regarding body weight were also evaluated. The estimated breeding value (EBV) of body weight was obtained as the dependent variable for association analyses using a linear mixed model. Significant associations were detected between SNP markers (BIEC2-808543, BIEC2-808967, BIEC2-809370, BIEC2-1105370, BIEC2-1105372, and BIEC2-1105377) and the body weight EBV. In addition, the joint genotype effect of the BIEC2-808467 and BIEC2-1105377 on the body weight EBV was significant. These results indicate that the SNP markers, which showed their significant effects on body conformation, can be used as genetic markers to improve the efficiency of the selective breeding program for the body weight traits in Jeju horses.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1544-1557
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• 2020

Objective: Genomic selection (GS) is becoming popular in animals' genetic development. We, therefore, investigated the single-step genomic best linear unbiased prediction (ssGBLUP) as tool for GS, and compared its efficacy with the traditional pedigree BLUP (pedBLUP) method. Methods: A total of 9,952 males born between 1997 and 2018 under Hanwoo proven-bull selection program was studied. We analyzed body weight at 12 months and carcass weight (kg), backfat thickness, eye muscle area, and marbling score traits. About 7,387 bulls were genotyped using Illumina 50K BeadChip Arrays. Multiple-trait animal model analyses were performed using BLUPF90 software programs. Breeding value accuracy was calculated using two methods: i) Pearson's correlation of genomic estimated breeding value (GEBV) with EBV of all animals (r_M1) and ii) correlation using inverse of coefficient matrix from the mixed-model equations (r_M2). Then, we compared these accuracies by overall population, info-type (PHEN, phenotyped-only; GEN, genotyped-only; and PH+GEN, phenotyped and genotyped), and bull-types (YBULL, young male calves; CBULL, young candidate bulls; and PBULL, proven bulls). Results: The r_M1 estimates in the study were between 0.90 and 0.96 among five traits. The r_M1 estimates varied slightly by population and info-type, but noticeably by bull-type for traits. Generally average r_M2 estimates were much smaller than r_M1 (pedBLUP, 0.40 to0.44; ssGBLUP, 0.41 to 0.45) at population level. However, r_M2 from both BLUP models varied noticeably across info-types and bull-types. The ssGBLUP estimates of r_M2 in PHEN, GEN, and PH+ GEN ranged between 0.51 and 0.63, 0.66 and 0.70, and 0.68 and 0.73, respectively. In YBULL, CBULL, and PBULL, the r_M2 estimates ranged between 0.54 and 0.57, 0.55 and 0.62, and 0.70 and 0.74, respectively. The pedBLUP based r_M2 estimates were also relatively lower than ssGBLUP estimates. At the population level, we found an increase in accuracy by 2.0% to 4.5% among traits. Traits in PHEN were least influenced by ssGBLUP (0% to 2.0%), whereas the highest positive changes were in GEN (8.1% to 10.7%). PH+GEN also showed 6.5% to 8.5% increase in accuracy by ssGBLUP. However, the highest improvements were found in bull-types (YBULL, 21% to 35.7%; CBULL, 3.3% to 9.3%; PBULL, 2.8% to 6.1%). Conclusion: A noticeable improvement by ssGBLUP was observed in this study. Findings of differential responses to ssGBLUP by various bulls could assist in better selection decision making as well. We, therefore, suggest that ssGBLUP could be used for GS in Hanwoo proven-bull evaluation program.