Status as of: 2016-05-30

Form GENO

DESCRIPTION OF NATIONAL GENOMIC EVALUATION SYSTEMS

Country (or countries)	ITA	
Main trait group1
NOTE! Only one trait group per form!	Production (protein)
	
Breed(s)	Brown Swiss	
Trait definition(s) and unit(s) of measurement2
Attach an appendix if needed	Protein yield, KG
	
Source of genotypes (chips used)	Illumina Bovine SNP50 BeadChip	
Imputation method for missing genotypes	Missing genotypes filled using a combination of population and pedigree haplotyping in findhap.f90	
Propagation of genomic information to non-genotyped descendants and ancestors	Not applicable yet.	
Animals included in reference population (males, females, countries included, total number)	Reference animals included 6695 bulls from AUT, CHE, DEU, FRA, ITA, SVN and the USA
	
Source of phenotypic data (DYD, deregressed proofs, national EBVs and/or MACE evaluations)	De-regressed predicted genetic merit (DPGM) is calculated from international (MACE) PGM (EBV) on ITA scale: DPGM= PA + (PGM - PA) / RELdau, where RELdau is reliability from daughters. In the genomic model, DPGM are weighted by RELdau / (1 - RELdau).	
Other criteria (data edits) for inclusion of records	The 42,437 selected SNP had minor genotype frequency of  ≥ 0.04% (equivalent to MAF ≥ 2%),  few parent–progeny conflicts (≤1%), and a high call rate (≥75%). 	
Criteria for extension of records (if applicable)		
Sire categories		
Genomic model (linear, Bayesian, polygenic effect, genotypes or haplotypes)	An iterative, nonlinear model with heavy-tailed prior for marker effects analogous to Bayes A is used. Base population allele frequencies are subtracted from genotypes, and a polygenic effect  (poly) with 10% of additive variance is fit in the model:
DPGM = mean + ∑genotypes*effects + poly + error.	
Blending of direct genomic value (DGV) with traditional EBV	The evaluation model includes international (MACE) evaluation of ancestors, and consequently the foreign information for non-genotyped ancestors is included.	
Environmental effects in the genetic evaluation model		
Adjustment for heterogeneous variance in evaluation model		
Computation of genomic reliability	Reliability of direct genomic value is computed from the traditional daughter equivalents plus the genomic daughter equivalents, which differ for each animal depending on its average genomic relationship to the reference population. Final reliability is computed by selection index using reliabilities of DGV, traditional PGM, and subset PGM. 	
Blending of foreign/Interbull information in evaluation	Calculation of DGV includes foreign information from a subset of the current Interbull evaluation for the genotyped animals. 	
Genetic parameters in the evaluation	Use Appendix GENO for heritability/genetic variance estimates; for multiple-trait genetic evaluations, provide genetic correlation estimates between traits separately.
Use also appendices PR, CO, BCO, SM, LO, CA, as applicable, if you participate in the international genetic evaluations of Interbull	
System validation	De-regressed proofs for bulls proven after 2006 were predicted from PGM available in 2006.	
Expression of genetic evaluations
If standardised (e.g. RBV), give standardisation formula in the appendix	GEBV, KG	
Definition of genetic reference base	The same as used in the national genetic evaluation	
Labeling of genomic evaluations	Not applicable yet.	
Criteria for official publication of evaluations	All genomic value are published	
Number of evaluations / publications per year	3 evaluations: april, august, december	
Use in total merit index	ITE:
35*Protein kg + 8 *% protein + 10* Fat kg + 2 *% fat  – 5 *scs+ +10*ocs  + 10*milking speed + 10*dlo + 5 * ofl – 5 int	
Anticipated changes in the near future	Not applicable yet.	
Key reference on methodology applied	VanRaden, P.M. Efficient methods to compute genomic predictions. J. Dairy Sci. 91(11):4414–4423. 2008.
VanRaden, P.M., Van Tassell, C.P., Wiggans, G.R., Sonstegard, T.S., Schnabel, R.D., Taylor, J.F., and Schenkel, F.S. Invited review: Reliability of genomic predictions for North American Holstein bulls. J. Dairy Sci. 92(1):16–24. 2009.
Wiggans, G.R., VanRaden, P.M., Bacheller, L.R., Tooker, M.E., Hutchison, J.L., Cooper, T.A., and Sonstegard, T.S. Selection and management of DNA markers for use in genomic evaluation . J. Dairy Sci. 93(5):2287-2292. 2010.	
Key organisation: name, address, phone, fax, e-mail, web site	Anarb 
Loc ferlina 204 Bussolengo Verona Italy
Phone: 045/6760135
Fax: 045/7156655
ricerca@anarb.it
attilio.rossoni@anarb.it
chiara.nicoletti@anarb.it
www.anarb.it
	
1) Either: 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.

Form GENO	Appendix GENO

Parameters used in genetic evaluation

Country (or countries):		
Main trait group:		
Breed (repeat as necessary):		

Trait	Definition	ITBa	h2b	genetic
varianceb	official proof
standardisation formulac	
Protein		X	0.180			

						

						

						

						

						
						
a	Indicate, with X, traits that are submitted to Interbull for international genetic evaluations.
b	If 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.
c	Expressed 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.