Status as of: 2016-01-26 
Form GENO
DESCRIPTION OF NATIONAL GENOMIC EVALUATION SYSTEMS
Country (or countries) 	DEA (Germany and Austria)	
Main trait groupa. 
NOTE. Only one trait group per form! 	Production	
Breed(s) 	Brown Swiss	
Trait definition(s) and unit(s) of measurement
Attach an appendix if needed 	Milk, fat and protein yields in kg	
Source of genotypes (chips used) 	Illumina 54k Bovine chip	
Imputation method for missing genotypes 	findhap.f90, version 2 (VanRaden, 2011) is used to impute missing genotypes	
Propagation of genomic information to non-genotyped descendants and ancestors 	no	
Animals included in reference population (males, females, countries included, total number) 	Genotyped and progeny tested bulls from Germany, Austria, Switzerland, Italy and United States are included (Intergenomics genotype-pool), except bulls registered as ‘Original Braunvieh’. Calibration group sizes are dependent on availability of a phenotype (EDC≥20) and therefore trait dependent.  Size of reference group for production traits is currently around 4 300 bulls.	
Source of phenotypic data (DYD, de-regressed proofs, national EBVs and/or MACE evaluations) 	Deregressed proofs and associated reliabilities from conventional genetic evaluation. Deregressed proofs are based on MACE EBVs for bulls.	
Other criteria (data edits) for inclusion of records 	At least a call-rate of 95% is necessary for a genotype to be declared as valid. Animals showing genotype inconsistencies with otherwise confirmed parent genotypes are excluded. If parent genotype cannot be confirmed, both genotypes are excluded.	
Criteria for extension of records (if applicable) 		
Sire categories 		
Genomic model (linear, Bayesian, polygenic effect, genotypes or haplotypes) 	Single trait G-BLUP using genomic relationship matrix. A polygenic effect with 15% (MY), 20% (FY) and 15% (PY) additive genetic variance is included.
NEW: Starting with April 2014 we will routinely use an improved scaling and shrinkage of the genomic relationship matrix as described by Meuwissen et al. (2011) and Ertl et al. (2014). These changes are already considered in this validation run (January 2014).	
Blending of direct genomic value (DGV) with traditional EBV 	DGV and the conventional EBV (PA) are combined using selection index theory. Covariance between DGV and conventional EBV is approximated by calculation of covariance between subset-EBV (conventional EBV solution only including genotyped animals) and DGV.	
Environmental effects in the genetic evaluation model 		
Adjustment for heterogeneous variance in evaluation model 		
Computation of genomic reliability 	Reliability of DGV is derived by direct inversion of the genomic equation system. Reliability of GEBV is the reliability of the index used for ‘blending’ of the DGV and the conventional system EBV.	
Blending of foreign/Interbull information in evaluation 		
Genetic parameters in the evaluation 	Same as in the conventional evaluation (see Form 1).	
Expression of genetic evaluations
If standardized (e.g. RBV), give standardization formula in the appendix 	kg	
Definition of genetic reference base 	Same as in the conventional evaluation.	
Labeling of genomic evaluations 	Lowercase ‘g’ for ‘genomic’.	
Criteria for official publication of evaluations 	a) registered AI-bull, b) valid genotype and c) reliability of GEBV of milk production index >= 50%.	
Number of evaluations / publications per year 	Genomic evaluations conducted every month (12 times per year).	
Use in total merit index 	Yes. Same index as used in the conventional genetic evaluation.	
Anticipated changes in the near future 		
Key reference on methodology applied 	VanRaden, P.M. (2008): Efficient Methods to Compute Genomic Predictions. J. Dairy Sci. 91:4414-4423.
VanRaden, P.M. et al. (2009): Invited review: Reliability of genomic predictions for North American Holstein bulls. J. Dairy Sci., 92:16-24.
VanRaden, P.M. et al. (2011): Genomic evaluations with many more genotypes. Genet Sel Evol., 2011; 43(1): 10.
Edel, C., Emmerling, R, Götz, K.U. (2010): A Modification of VanRaden’s Index for the Blending of Genomic Breeding Values. WCGALP 2010, Leipzig.
Meuwissen, T.H.E. et al. (2011): The unified approach to the use of genomic and pedigree information in genomic evaluations revisisted. J. Anim. Breed. Genet. 1011:429:439.
Ertl, J. et al. (2014): On the limited increase in validation reliability using high-density genotypes in genomic best linear unbiased prediction: Observations from Fleckvieh cattle. J. Dairy Sci., 97:487:496.	
Key organization: name, address, phone, fax, e-mail, web site 	Bavarian State Research Center for Agriculture, Institute for Animal Breeding, Prof.-Dürrwaechter-Platz 1, 85586 Poing-Grub, Germany.
Phone: ++49(0)89 99141-144 or  -141
Mail: Christian.Edel@LfL.bayern.de, 
Eduardo.Pimentel@LfL.bayern.de, Reiner.Emmerling@LfL.bayern.de
Web: http://www.lfl.bayern.de/	
aEither: Production (e.g. milk, fat, protein), Conformation, Health (e.g. mastitis resistance, milk somatic cell, resistance to diseases other than mastitis), Longevity, Calving (e.g. stillbirth, calving ease), Female fertility (e.g. non-return rate, interval between reproductive events, number of AI’s, heat strength), Workability (e.g. milking speed, temperament), Beef production, Efficiency (e.g. body weight, energy balance, body conditioning score), or Other traits. 

System Validation
Approximate number of test bulls for this trait group:	420	
If including foreign reference bulls:
4-yr old de-regressed MACE EBVs, OR
Current de-regressed MACE EBVs
If including foreign test bulls (type of proof 21 or 22), provide the reason.	4-yr old de-regressed MACE EBVs	
If using a truncation ≠ 4 years, provide the reason.		
If applying an age cutoff for test bulls ≠ (YYYY-8), provide the reason		

Appendix GENO
Parameters used in genetic/genomic evaluation 
Country (or countries): 		
Main trait group: 		
Breed (repeat as necessary): 		
Trait 	Definition 	ITBa 	h2b 	Genetic varianceb 	Official proof standardisation formulac 	

aIndicate, with X, traits that are submitted to Interbull for international genetic evaluations.
bIf repeated records are treated as separate traits, provide heritability estimates and genetic variances separately for each trait, as well as for all traits pooled, i.e. for the trait submitted to Interbull.
cExpressed as follows: StandEval=((eval-a)/b)*c+d where a=mean of the base adjustment, b=standard deviation of the base, c=standard deviation of expression (include sign if scale is reversed), and d=base of expression.