A simple method for genomic selection of moderately sized dairy cattle populations

An efficient algorithm for genomic selection of moderately sized populations based on single nucleotide polymorphism chip technology is described. A total of 995 Israeli Holstein bulls with genetic evaluations based on daughter records were genotyped for either the BovineSNP50 BeadChip or the BovineSNP50 v2 BeadChip. Milk, fat, protein, somatic cell score, female fertility, milk production persistency and herd-life were analyzed. The 400 markers with the greatest effects on each trait were first selected based on individual analysis of each marker with the genetic evaluations of the bulls as the dependent variable. The effects of all 400 markers were estimated jointly using a 'cow model,' estimated from the data truncated to exclude lactations with freshening dates after September 2006. Genotype probabilities for each locus were computed for all animals with missing genotypes. In Method I, genetic evaluations were computed by analysis of the truncated data set with the sum of the marker effects subtracted from each record. Genomic estimated breeding values for the young bulls with genotypes, but without daughter records, were then computed as their parent averages combined with the sum of each animal's marker effects. Method II genomic breeding values were computed based on regressions of estimated breeding values of bulls with daughter record on their parent averages, sum of marker effects and birth year. Method II correlations of the current breeding values of young bulls without daughter records in the truncated data set were higher than the correlations of the current breeding values with the parent averages for fat and protein production, persistency and herd-life. Bias of evaluations, estimated as a difference between the mean of current breeding values of the young bulls and their genomic evaluations, was reduced for milk production traits, persistency and herd-life. Bias for milk production traits was slightly negative, as opposed to the positive bias of parent averages. Correlations of Method II with the means of daughter records adjusted for fixed effects were higher than parent averages for fat, protein, fertility, persistency and herd-life. Reducing the number of markers included in the analysis from 400 to 300 did not reduce correlations of genomic breeding values for protein with current breeding values, but did slightly reduce correlations with means of daughter records. Method II has the advantages as compared with the method of VanRaden in that genotypes of cows can be readily incorporated into the Method II analysis, and it is more effective for moderately sized populations.     

Effect of leptin gene polymorphism on the breeding value of milk production traits in Iranian Holstein

New molecular techniques focused on genome analysis, open new possibilities for more accurate evaluation of economiclly important traits in farm animals. Milk production traits are typical quantitative characteristics controlled by a number of genes. Mutations in their sequences may alter animal performance as well as their breeding values. In this study, we investigated the effect of Kpn2I restriction fragment length polymorphisms in the leptin gene, on bull breeding values for milk yield, fat, and protein yield, and their percentage. In order to test for an association between the leptin single-nucleotide polymorphism in exon 2 and milk productivity, we genotyped 134 Iranian Holstein bulls. Breeding values for milk-related traits (milk yield, fat, and protein yield and percentage) were estimated using the BLUP based on an animal model. The effect of the genotypes of Kpn2I polymorphism on the breeding values for milk-related traits was examined using least square methods. The T allele frequency was 0.425. Genotypes were distributed according to the Hardy-Weinberg equilibrium. Bulls with TT genotype had higher milk, fat and protein yield compared with TC and CC bulls (P < 0.05). Bulls with CC genotype had higher protein percentage compared with TT and TC bulls (P < 0.05). The association between leptin polymorphism with milk production traits suggests that this marker may be useful for selection based on molecular information.     

Linkage between amylase-1 locus and a major gene for milk fat content in cattle

Summary
Linkage between the amylase-1 ( Am-1 ) locus and a quantitative trait locus influencing fat content in milk was studied in offspring from heterozygous sires of the Swedish Red and White dairy breed. The effect on bull breeding values for fat content was estimated as interactions between sire and paternal Am-1 allele using a model eliminating the direct effects of sire and Am-1 allele. There were strong indications of linkage, confirming results of previous studies. The interaction was caused by strong associations in 7 out of 14 sire families. A test for within-family variance heterogeneity performed on the whole population of breeding bulls also supported the presence of a major gene for fat content in milk. The results indicate that there is genetic linkage between the Am-1 locus and a locus with large effect on milk fat content.     

Mapping quantitative trait loci with DNA microsatellites in a commercial dairy cattle population

Individual loci affecting economically important traits can be located using genetic linkage between quantitative trait loci and genetic markers. In the ‘granddaughter’ experimental design, heterozygous grandsires and their sons are genotyped for the genetic marker, while the quantitative trait records of the granddaughters are used for statistical analysis. Ten DNA microsatellite markers were used to look for associations with quantitative trait loci affecting milk production traits in seven Israeli Holstein grandsire families. At least 60% more grandsires were heterozygous, and 40% fewer individuals were discarded because of unknown paternal allele origin, as compared with diallelic markers. The effects of paternal alleles for locus D21S4 on kg milk and protein were significant (P < 0.025). The allele substitution effects for sire 783 were 283 kg milk and 5.7 kg protein. For both traits, progeny of sire 783 that inherited allele ‘18’ had higher evaluations than progeny that inherited allele ‘21’. These results were verified by genotyping 151 of his daughters. Thus, the rate of genetic gain for protein production can be increased by selecting progeny of sire 783 carrying allele ‘18’ at this locus.     

Genome Wide Analysis of Fertility and Production Traits in Italian Holstein Cattle

A genome wide scan was performed on a total of 2093 Italian Holstein proven bulls genotyped with 50K single nucleotide polymorphisms (SNPs), with the objective of identifying loci associated with fertility related traits and to test their effects on milk production traits. The analysis was carried out using estimated breeding values for the aggregate fertility index and for each trait contributing to the index: angularity, calving interval, non-return rate at 56 days, days to first service, and 305 day first parity lactation. In addition, two production traits not included in the aggregate fertility index were analysed: fat yield and protein yield. Analyses were carried out using all SNPs treated separately, further the most significant marker on BTA14 associated to milk quality located in the DGAT1 region was treated as fixed effect. Genome wide association analysis identified 61 significant SNPs and 75 significant marker-trait associations. Eight additional SNP associations were detected when SNP located near DGAT1 was included as a fixed effect. As there were no obvious common SNPs between the traits analyzed independently in this study, a network analysis was carried out to identify unforeseen relationships that may link production and fertility traits.     

Restriction fragment length polymorphism of bovine lysozyme genes

Genetic polymorphism of bovine lysozyme (LYZ) genes was investigated by analysing restriction fragment length polymorphism (RFLP). The analysis revealed three RFLP loci designated LYZ1, LYZ2 and LYZ2. Each system included two or three allelic variants. Evidence for close genetic linkage of the three loci was found. There was also a significant linkage disequilibrium among the three loci in a sample of about 200 breeding bulls from one breed. No statistically significant association was found between LYZ RFLPs and breeding values of bulls for disease or milk production traits.     

Reliabilities of genomic estimated breeding values in Danish Jersey

In order to optimize the use of genomic selection in breeding plans, it is essential to have reliable estimates of the genomic breeding values. This study investigated reliabilities of direct genomic values (DGVs) in the Jersey population estimated by three different methods. The validation methods were (i) fivefold cross-validation and (ii) validation on the most recent 3 years of bulls. The reliability of DGV was assessed using squared correlations between DGV and deregressed proofs (DRPs). In the recent 3-year validation model, estimated reliabilities were also used to assess the reliabilities of DGV. The data set consisted of 1003 Danish Jersey bulls with conventional estimated breeding values (EBVs) for 14 different traits included in the Nordic selection index. The bulls were genotyped for Single-nucleotide polymorphism (SNP) markers using the Illumina 54 K chip. A Bayesian method was used to estimate the SNP marker effects. The corrected squared correlations between DGV and DRP were on average across all traits 0.04 higher than the squared correlation between DRP and the pedigree index. This shows that there is a gain in accuracy due to incorporation of marker information compared with parent index pre-selection only. Averaged across traits, the estimates of reliability of DGVs ranged from 0.20 for validation on the most recent 3 years of bulls and up to 0.42 for expected reliabilities. Reliabilities from the cross-validation were on average 0.24. For the individual traits, the reliability varied from 0.12 (direct birth) to 0.39 (milk). Bulls whose sires were included in the reference group had an average reliability of 0.25, whereas the bulls whose sires were not included in the reference group had an average reliability that was 0.05 lower.     

Structural variation around prolactin gene linked to quantitative traits in an elite Holstein sire family

Summary Digestion of genomic DNA with the restriction endonuclease Avail disclosed a probable insertion deletion of approximately 200 base pairs (bp) near the prolactin gene. Two alleles were apparent as three distinct hybridization patterns. These alleles were statistically associated with quantitative trait loci among sons of one elite Holstein sire family. The favorable genotype was correlated with the presence of a 1.15-kb hybridization band inherited from the sire when genomic DNA was probed with a full-length cDNA for prolactin. Pedigree estimates of genetic merit among genotypes were similar, differing by only 19.3 kg for milk in ancestor merit. Comparisons of genetic estimates for quantitative yield traits in offspring of this heterozygous sire showed significant (P<0.05) differences between homozygous genotypes for predicted difference milk (PDM), predicted difference dollars (PD$), cheese yield dollars, and protein dollars. The estimated differences between homozygous genotypes for USDA Transmitting Abilities of PDM, PD$, Cheese Yield $ and Protein $ were 282.93 kg, $74.35, $48.58 and $53.67, respectively. However, the estimated breeding values from progeny ranged over 900 kg in transmitting ability for milk. Frequency of the favorable marker allele was estimated to be 0.231 in the elite cow population used as dams of sons. These results demonstrate the potential of molecular biological techniques to discriminate between individuals within a family and to predict breeding values for selection schemes.     

Fitting and validating the genomic evaluation model to Polish Holstein-Friesian cattle

The aim of the study was to fit the genomic evaluation model to Polish Holstein-Friesian dairy cattle. A training data set for the estimation of additive effects of single nucleotide polymorphisms (SNPs) consisted of 1227 Polish Holstein-Friesian bulls. Genotypes were obtained by the use of Illumina BovineSNP50 Genotyping BeadChip. Altogether 29 traits were considered: milk-, fat- and protein- yields, somatic cell score, four female fertility traits, and 21 traits describing conformation. The prediction of direct genomic values was based on a mixed model containing deregressed national proofs as a dependent variable and random SNP effects as independent variables. The correlations between direct genomic values and conventional estimated breeding values estimated for the whole data set were overall very high and varied between 0.98 for production traits and 0.78 for non return rates for cows. For the validation data set of 232 bulls the corresponding correlations were 0.38 for milk-, 0.37 for protein-, and 0.32 for fat yields, while the correlations between genomic enhanced breeding values and conventional estimated breeding values for the four traits were: 0.43, 0.44, 0.31, and 0.35. This model was able to pass the interbull validation criteria for genomic selection, which indicates that it is realistic to implement genomic selection in Polish Holstein-Friesian cattle.     

Quantitative trait loci for fertility traits in Finnish Ayrshire cattle

A whole genome scan was carried out to detect quantitative trait loci (QTL) for fertility traits in Finnish Ayrshire cattle. The mapping population consisted of 12 bulls and 493 sons. Estimated breeding values for days open, fertility treatments, maternal calf mortality and paternal non-return rate were used as phenotypic data. In a granddaughter design, 171 markers were typed on all 29 bovine autosomes. Associations between markers and traits were analysed by multiple marker regression. Multi-trait analyses were carried out with a variance component based approach for the chromosomes and trait combinations, which were observed significant in the regression method. Twenty-two chromosome-wise significant QTL were detected. Several of the detected QTL areas were overlapping with milk production QTL previously identified in the same population. Multi-trait QTL analyses were carried out to test if these effects were due to a pleiotropic QTL affecting fertility and milk yield traits or to linked QTL causing the effects. This distinction could only be made with confidence on BTA1 where a QTL affecting milk yield is linked to a pleiotropic QTL affecting days open and fertility treatments.