L Longitudinal effects of muscular hypertrophy it di l ff t f l h t h allele on milk production traits during the lactation using a novel equivalent model when molecular information is limited Colinet F.G. 1 and Gengler N. 1,2 g 1 Animal Science Unit Gembloux Agro-Bio Tech ULg Belgium Animal Science Unit, Gembloux Agro Bio Tech, ULg, Belgium 2 National Fund for Scientific Research, Belgium 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 1
Context Context � In 1973, Mid and High Belgian breed was divided officially into 2 types y yp � 1 st type: Meat Belgian Blue Young bull Young bull Cow Cow 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 2
Context Context � Meat Belgian Blue (BBB) • Double muscling phenotype Double muscling phenotype • Muscle Hypertrophy ( mh ) syndrome • Caused by 11 bp deletion in Myostatin gene C d b 11 b d l ti i M t ti � mh allele: deletion � + allele: allele without deletion � mh allele frequency close to 100 % 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 3
Context Context � 2 nd type: Dual Purpose Belgian Blue (DP ‐ BBB) • Local breed in Belgium Local breed in Belgium • Vulnerable status (FAO criteria) • Related to the Bleue du Nord (in France) R l t d t th Bl d N d (i F ) • Supported by an INTERREG IVa project 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 4
Context Context � Dual Purpose Belgian Blue (DP ‐ BBB) • Average milk yield: 4 000 kg (up to 7 000 kg) Average milk yield: 4,000 kg (up to 7,000 kg) • Strong muscling (much less caesareans) • mh allele h ll l � less frequent than BBB (allele frequency: 60 %) 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 5
Context Context � DP ‐ BBB: mh / mh Bull Cow 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 6
Context Context � DP ‐ BBB: +/+ Bull Cow 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 7
General objective General objective mh allele could influence milk production But molecular information is limited But molecular information is limited � We need a practical method to integrate molecular information integrate molecular information 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 8
Methodology Methodology � Mixed Inheritance Model • Combining fixed gene effects g and random polygenic Combining fixed gene effects g and random polygenic u effects = = + + + + + + y y X β X β ZQg ZQg Zu Zu e e • Usual assumptions concerning distribution of random effects effects ⎡ ⎡ ⎤ ⎤ ⎡ ⎡ ⎤ ⎤ ⎡ ⎡ ⎤ ⎤ ⎡ ⎡ ⎤ ⎤ u 0 u G 0 = = E ⎢ ⎥ ⎢ ⎥ and Var ⎢ ⎥ ⎢ ⎥ e 0 e 0 R ⎣ ⎦ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦ 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 9
Methodology Methodology � Equivalent Mixed Inheritance Model • Fixed gene effects and random polygenic effects Fixed gene effects and random polygenic effects replaced by a combined genetic effect u * = + + = + y X β Zu * e u* Qg u where • Modification of assumptions ⎡ ⎡ u u * ⎤ ⎤ ⎡ ⎡ Qg Qg ⎤ ⎤ ⎡ ⎡ u u * ⎤ ⎤ ⎡ ⎡ G G 0 0 ⎤ ⎤ = = E ⎢ ⎥ ⎢ ⎥ and Var ⎢ ⎥ ⎢ ⎥ e 0 e 0 R ⎣ ⎦ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦ 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 10
Methodology Methodology � Associated Mixed Model Equations • Following Quaas ( J Dairy Sci 1988 71 1338 ‐ 1345) Following Quaas ( J. Dairy Sci. 1988, 71, 1338 1345) • Same strategy to integrate genetic groups • Joint estimation of β , u * and g * J i t ti ti f β d ⎡ ⎡ ⎤ ⎤ ⎡ ⎡ ⎤ ⎤ − − 1 1 1 1 ˆ ⎡ ⎡ ⎤ ⎤ X' X' R R X X X' X' R R Z Z 0 0 β β X' X' Ry Ry ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ − − − − + − = 1 1 1 1 Z ' R X Z ' R Z G G Q û * Z ' Ry ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎢ ⎥ ⎥ ⎢ ⎢ ⎥ ⎥ ⎢ ⎢ ⎥ ⎥ − − − 1 1 1 1 0 0 Q' Q' G G Q' Q' G G Q Q g 0 0 ˆ ⎣ ⎣ ⎦ ⎦ ⎣ ⎦ ⎣ ⎦ 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 11
Methodology Methodology � Associated Mixed Model Equations ⎡ ⎡ ⎤ ⎤ ⎡ ⎡ − − ⎤ ⎤ 1 1 ˆ X X' R R X X X X' R R Z Z 0 0 β β ⎡ ⎡ X' X Ry Ry ⎤ ⎤ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ − − + − − − = 1 1 1 1 Z ' R X Z ' R Z G G Q û * Z ' Ry ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎢ ⎥ ⎥ ⎢ ⎢ ⎥ ⎥ − − ⎢ ⎢ ⎥ ⎥ − 1 1 0 0 Q' Q G G Q' Q G G Q Q g g 0 0 ˆ ⎣ ⎣ ⎦ ⎦ ⎣ ⎣ ⎦ ⎦ ⎣ ⎣ ⎦ ⎦ • Solving of whole system is equivalent of solving iteratively two systems of equations � 1 st , solving for the third row − = − 1 1 Q' G Q g Q' G û * ˆ 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 12
Methodology Methodology � Associated Mixed Model Equations ⎡ ⎡ ⎤ ⎤ ⎡ ⎡ − − ⎤ ⎤ 1 1 ˆ X X' R R X X X X' R R Z Z 0 0 β β ⎡ ⎡ X X' Ry Ry ⎤ ⎤ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ − − + − − − = 1 1 1 1 Z ' R X Z ' R Z G G Q û * Z ' Ry ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎢ ⎥ ⎥ ⎢ ⎢ ⎥ ⎥ − − ⎢ ⎢ ⎥ ⎥ − 1 1 0 0 Q Q' G G Q Q' G G Q Q g g 0 0 ˆ ⎣ ⎣ ⎦ ⎦ ⎣ ⎣ ⎦ ⎦ ⎣ ⎣ ⎦ ⎦ • Solving of whole system is equivalent of solving iteratively two systems of equations � 2 nd , solving the system ⎡ ⎤ ⎡ − − ⎤ ⎡ − ⎤ 1 1 ˆ 1 X' R X X' R Z X' R y β = ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ − − − − − 1 1 + 1 1 + 1 Z ' R X Z ' R Z G Z ' R y y G Q g g ⎢ ⎢ û * ⎥ ⎥ ˆ ⎣ ⎣ ⎦ ⎦ ⎣ ⎣ ⎦ ⎦ ⎣ ⎣ ⎦ ⎦ 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 13
Methodology Methodology � Associated Mixed Model Equations • Solving iteratively until relative differences in Solving iteratively until relative differences in estimation of g < 10 ‐ 5 � Advantages • Could allow solving when only limited number of genotyped animals • Gene effect could be estimated from limited known genotypes g yp 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 14
Material Material � Data used for official genetic evaluations in the Walloon Region of Belgium g g • Pedigree: 1,606,024 animals • Data: 11 117 505 Test day records • Data: 11,117,505 Test ‐ day records • 689,057 cows with production records 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 15
Material Material � Molecular information • mh genotypes available mh genotypes available � 108 DP ‐ BBB bulls � 1 891 DP BBB cows with production records � 1,891 DP ‐ BBB cows with production records • Offspring of genotyped animals � � 11,768 cows with production records i h d i d 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 16
Statistical Model Statistical Model � Random regression test ‐ day model • Official Walloon Model used for routine run Official Walloon Model used for routine run • Multi ‐ trait multi ‐ lactation model � 3 t � 3 traits x 3 lactations it 3 l t ti 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 17
Results Results Phenotypic means of daily milk production in 3 rd lactation Phenotypic means of daily milk production in 3 lactation 30 305 ‐ days milk production (modified Best Prediction (Gillon et al ., 2010)) 25 25 + / + + / + 5471 kg 5471 kg mh / + 4922 kg 20 mh / mh 4434 kg ) Milk (kg 15 +/+ mh/+ 10 mh/mh 5 0 Days in milk 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 18
Results Results � Allelic substitution effect of the mh allele on 305 ‐ days production yields (kg) y p y ( g) Milk Fat Protein 1 st lactation 1 lactation ‐ 155 8 155.8 ‐ 8 73 8.73 ‐ 5 27 5.27 2 nd lactation ‐ 142.0 ‐ 8.40 ‐ 5.43 3 rd lactation ‐ 178.2 ‐ 9.67 ‐ 6.23 Means ‐ 3 lact. ‐ 158.7 ‐ 8.93 ‐ 5.64 305 ‐ days production yields (kg, modified Best Prediction, Gillon et al ., 2010) Milk Fat Protein Means ‐ 3 lact. 4420 157 145 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 19
Results Results � Allelic substitution effect of the mh allele on 305 ‐ days production yields (kg) y p y ( g) • Buske et al. (2010) J. Anim. Breed. Genet. 127: 272 ‐ 279 � Based on a Bayesian approach using additional prior � Based on a Bayesian approach using additional prior information on the distribution of external EBV � Additive effect � Additive effect ‐ 120.3 kg Milk ‐ 5.5 kg Fat ‐ 4.0 kg Protein 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 20
Results Results � Allelic substitution effect of the mh allele on 305 ‐ days production yields (kg) y p y ( g) • Buske et al. (2010) Animal (accepted) � By regression on observed or estimated gene content � By regression on observed or estimated gene content � Estimated gene content using method of Gengler et al. (2007 Animal 1:21 ‐ 28 ) (2007, Animal 1:21 ‐ 28 ) � Additive effect ‐ 76.1 kg Milk ‐ 3.6 kg Fat ‐ 2.8 kg Protein 76 1 kg Milk 3 6 kg Fat 2 8 kg Protein 9 th WCGALP – Leipzig, Germany (August 1 ‐ 6, 2010) 21
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