한우에 있어서 유전체 육종가 추정

이승환,김형철,임다정,당창권,조용민,김시동,이학교,이준헌,양보석,오성종,홍성구,장원경,Lee, Seung Hwan,Kim, Heong Cheul,Lim, Dajeong,Dang, Chang Gwan,Cho, Yong Min,Kim, Si Dong,Lee, Hak Kyo,Lee, Jun Heon,Yang, Boh Suk,Oh, Sung Jong,Hong, S Institute of Agricultural Science 2012 Korean Journal of Agricultural Science Vol.39 No.3

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).

혈중 인슐린 및 렙틴이 한우 지방형질에 미치는 효과

김형철(Hyeong Cheul Kim),이승환(Seung Hwan Lee),당창권(Chang Gwan Dang),임다정(Dajeong Lim),최봉환(Bong Hwan Choi),장선식(Sun Sik Chang),조영무(Young Moo Cho),전기준(Gi Jun Jeon),박응우(Eung Woo Park),조용민(Yong Min Cho),이준헌(Jun 충남대학교 농업과학연구소 2012 농업과학연구 Vol.39 No.2

The objective of this study was to examine the effect of plasma leptin and insulin concentrations on fat traits in Hanwoo. If a biological indicator such as plasma leptin and insulin was identified, it would be a useful biological marker that can be predicted marbling score in young animal. The relationship between plasma hormone (leptin and insulin) and fat traits (marbling score, back fat thickness and P8 fat thickness) was investigated. The experiment studies 100 Hanwoo that were randomly sampled from Hanwoo Experimental Station Herd. The concentration of plasma insulin was significantly associated with marbling score (P=0.02) but was not significantly with back fat thickness (P=0.07) and P8 fat thickness (P=0.09). Statistical model determinant that plasma insulin concentration account for phenotypes was moderate on marbling score (5%), back fat thickness (3%) and P8 fat thickness (9%). On the other hand, plasma leptin concentration was significantly associated with marbling score (P=0.03) and back fat thickness (P=0.02), but was not significant on P8 fat thickness (0.07). Statistical model determinant that plasma leptin concentration accounting for phenotypes was moderate effect on marbling score (3%) and back fat thickness (2%), but it has a slightly bigger effect on P8 fat thickness (7%). In conclusion, the plasma leptin and insulin seems to have an effect on fat traits (marbling score, backfat thickness and P8 fat thickness) in Hanwoo.

Prediction of genomic breeding values of carcass traits using whole genome SNP data in Hanwoo (Korean cattle)

Seung Hwan Lee(이승환),Heong Cheul Kim(김형철),Dajeong Lim(임다정),Chang Gwan Dang(당창권),Yong Min Cho(조용민),Si Dong Kim(김시동),Hak Kyo Lee(이학교),Jun Heon Lee(이준헌),Boh Suk Yang(양보석),Sung Jong Oh(오성종),Seong Koo Hong( 충남대학교 농업과학연구소 2012 농업과학연구 Vol.39 No.3

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 (r²) of GEBV for marbling predicted based only on SNP effects was 0.47, while the r² 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).

한우, 칡소 및 제주 흑우 Calpain-Calpastatin 유전자 다양성

이승환,김승창,조수현,최봉환,Aditi Sharma,임다정,당창권,장선식,김재환,고문석,양보석,강희설 충남대학교 농업과학연구소 2013 농업과학연구 Vol.40 No.2

The aim of study was to investigate genetic diversity for the calpain/calpastatin gene in three Hanwoo breeds [(Brown (n=62), Brindle (n=81) and Jeju Black (n=30)]. Random samples from three breeds of Hanwoo were selected and genotyped for the 7 SNPs of calpain/calpastatin using TaqMan method. Allele frequencies were investigated for CAPN1/CAST gene. Allele frequency of CAST2 SNP was 0.75, 0.59 and 0.22 for Brown, Brindle and Jeju black, respectively. The CAST3 revealed allele frequency of 0.59 and 0.57 in Brown and Jeju Black, while it showed very low allele frequency (0.07) in Brindle. In particular, favorable allele (G allele) for the CAPN1-2 SNP which was shown a strong association with tenderness in Taurine and Indicine cattle revealed 16% and 17% higher allele frequency in Brown Hanwoo (0.82) comparing Brindle (0.66) and Jeju Black Hanwoo (0.65). AMOVA demonstrated that among population variance occupied only 10% of total variance and among individual variance was 0%, while within individual variance was 90% of total variance. This result showed that population effect contributed very small portion of genetic to these three Hanwoo breeds, while within individual variance contributed large portion of genetic diversity within these Hanwoo breeds. In conclusion, three Hanwoo breeds (Brown, Brindle and Jeju black) showed a genetically homogeneous based on the 7 SNPs of CAPN1/CAST gene and it came from same ancestor to form modern Hanwoo breed.

전장 유전체 관련성 분석을 통한 한우 도체수율 관련 양적형질좌위 탐색

이승환,임다정,당창권,장선식,김형철,전기준,연성흠,장길원,박응우,오재돈,이학교,이준헌,강희설,윤두학 충남대학교 농업과학연구소 2013 농업과학연구 Vol.40 No.2

Genome-wide association study was performed on data from 266 Hanwoo steers derived from 66 sire using bovine 10K mapping chip in Hanwoo (Korean Cattle). SNPs were excluded from the analysis if they failed in over 5% of the genotypes, had median GC scores below 0.6, had GC scores under 0.6 in less than 90% of the samples, deviated in heterozygosity more than 3 standard deviations from the other SNPs and were out of Hardy-Weinberg equilibrium for a cutoff p-value of 1-15. Unmapped and SNPs on sex chromosomes were also excluded. A total of 4,522 SNPs were included in the analysis. To test an association between SNP and QTL, GWAS for five genetic mode(additive, dominant, overdominant, recessive and codominant) was implemented in this study. Three SNPs (rs29018694, ss46526851 and rs29018222) at a threshold p<1.11×10-5 were detected on BTA12 and BTA21 for dressing percentages in codominant and recessive genetic mode. The G allele for rs29018694 has 4.9% higher dressing percentage than A allele, while the T allele for ss46526851 has 2.57 % higher dressing percentage than C allele. Therefore, rs29018694 SNP showed a bigger effect than the other two SNPs (ss46526851 and rs29018222) in this study. In conclusion, this study identifies three loci with moderate effects and many loci with infinitesimally small effect across genome in Hanwoo.