Elopaino, kuntoluokka ja maidon pitoisuudet lehmän energiataseen kuvaajana

201

Reliability of breeding values for feed intake and feed efficiency traits in dairy cattle: When dry matter intake recordings are sparse under different scenarios

In Press, Corrected Proof201

Bpop: an efficient program for estimating base population allele frequencies in single and multiple group structured populations

Base population allele frequencies (AF) should be used in genomic evaluations. A program named Bpop was implemented to estimate base population AF using a generalized least squares (GLS) method when the base population individuals can be assigned to groups. The required dense matrix products involving (A22 )-1v were implemented efficiently using sparse submatrices of A-1, where A and A22 are pedigree relationship matrices for all and genotyped animals, respectively. Three approaches were implemented: iteration on pedigree (IOP), iteration in memory (IM), and direct inversion by sparsity preserving Cholesky decomposition (CHM). The test data had 1.5 million animals genotyped using 50240 markers. Total computing time (the product (A22)-11) was 53 min (1.2 min) by IOP, 51 min (0.3 min) by IM, and 56 min (4.6 min) by CHM. Peak computer core memory use was 0.67 GB by IOP, 0.80 GB by IM, and 7.53 GB by CHM. Thus, the IOP and IM approaches can be recommended for large data sets because of their low memory use and computing time

Lypsylehmien muuntokelpoisen energian saannin mallinnus rehuhyötysuhdeominaisuuksien kehittämistä varten

201

Valintaindeksi jälkeläisarvosteltujen keinosiemennyssonnien kokonaisjalostusarvon kuvaajana

vokKirjasto Aj-

Genomisessa eläinmallissa käytetään sekä genotyypitettyjen että genotyypittämättömien eläinten tietoja

201

Multitrait-multiparity model for joint genetic evaluation of Nordic bulls for udder health traits

not availabl

Pre-selection approaches or some models with Mendelian sampling terms

Two equivalent models based on orthogonal random effects were presented. The first model was based on the LDL transformation of the relationship matrix of animals with observations, the second model was based on the LDL transformation of the full relationship matrix of all animals in the pedigree. The latter model yields directly the estimates of Mendelian Sampling terms, which can then be back transformed to breeding values. Models were tested using a small three country MACE protein data. Being analogous to the SNP-BLUP model, the transformed models were fitted using a regression design matrix approach with off-the-shelf breeding value estimation program MiX99. Both the orthogonal models and the original MACE model gave the same estimates for breeding values. From the new approaches, the full pedigree transformation was computationally more efficient although it required many more iterations to converge than the normal MACE model. The reason for better efficiency was postulated to the sparsity (low number of non-zeros) in the transformed design matrix. An approach to account for the reduction in MS-term variance due to genomic preselection was suggested