Seven years after the introduction of genomic selection in the United States, it is now possible to evaluate the impact of this technology on the population. Selection differential(s) (SD) and generation interval(s) (GI) were characterized in a four-path selection model that included sire(s) of bulls (SB), sire(s) of cows (SC), dam(s) of bulls (DB), and dam(s) of cows (DC). Changes in SD over time were estimated for milk, fat, and protein yield; somatic cell score (SCS); productive life (PL); and daughter pregnancy rate (DPR) for the Holstein breed. In the period following implementation of genomic selection, dramatic reductions were seen in GI, especially the SB and SC paths. The SB GI reduced from ∼7 y to less than 2.5 y, and the DB GI fell from about 4 y to nearly 2.5 y. SD were relatively stable for yield traits, although modest gains were noted in recent years. The most dramatic response to genomic selection was observed for the lowly heritable traits DPR, PL, and SCS. Genetic trends changed from close to zero to large and favorable, resulting in rapid genetic improvement in fertility, lifespan, and health in a breed where these traits eroded over time. These results clearly demonstrate the positive impact of genomic selection in US dairy cattle, even though this technology has only been in use for a short time. Based on the four-path selection model, rates of genetic gain per year increased from ∼50–100% for yield traits and from threefold to fourfold for lowly heritable traits.

Genetic and phenotypic parameters for Mexican Holstein cows were estimated for first- to third-parity cows with records from 1998 to 2003 (n=2,971-15,927) for 305-d mature equivalent milk production (MEM), fat production (MEF), and protein production (MEP), somatic cell score (SCS), subsequent calving interval (CAI), and age at first calving (AFC). Genetic parameters were obtained by average information matrix-REML methodology using 6-trait (first-parity data) and 5-trait (second- and third-parity data) animal models. Heritability estimates for production traits were between 0.17+/-0.02 and 0.23+/-0.02 for first- and second-parity cows and between 0.12+/-0.03 and 0.13+/-0.03 for third-parity cows. Heritability estimates for SCS were similar for all parities (0.10+/-0.02 to 0.11+/-0.03). For CAI, estimates of heritability were 0.01+/-0.05 for third-parity cows and 0.02+/-0.02 for second-parity cows. The heritability for AFC was moderate (0.28+/-0.03). No unfavorable estimates of correlations were found among MEM, MEF, MEP, CAI, and SCS. Estimates of environmental and phenotypic correlations were large and positive among production traits; favorable between SCS and CAI; slightly favorable between MEM, MEF, and MEP and SCS, between AFC and SCS, and between SCS and CAI; and small but unfavorable between production traits and CAI. Estimates of genetic variation and heritability indicate that selection would result in genetic improvement of production traits, AFC, and SCS. Estimates of both heritability and genetic variation for CAI were small, which indicates that genetic improvement would be difficult.

The effects of reference population size and the availability of information from genotyped ancestors on the accuracy of imputation of single nucleotide polymorphisms (SNP) were investigated for Mexican Holstein cattle. Three scenarios for reference population size were examined: (1) a local population of 2,011 genotyped Mexican Holsteins, (2) animals in scenario 1 plus 866 Holsteins in the US genotype database (GDB) with genotyped Mexican daughters, and (3) animals in scenario 1 and all US GDB Holsteins (338,073). Genotypes from 4 chip densities (2 low density, 1 mid density, and 1 high density) were imputed using findhap (version 3) to the 45,195 markers on the mid-density chip. Imputation success was determined by comparing the numbers of SNP with 1 or 2 alleles missing and the numbers of differently predicted SNP (conflicts) among the 3 scenarios. Imputation accuracy improved as chip density and numbers of genotyped ancestors increased, and the percentage of SNP with 1 missing allele was greater than that for 2 missing alleles for all scenarios. The largest numbers of conflicts were found between scenarios 1 and 3. The inclusion of information from direct ancestors (dam or sire) with US GDB genotypes in the imputation of Mexican Holstein genotypes increased imputation accuracy by 1 percentage point for low-density genotypes and by 0.5 percentage points for high-density genotypes, which was about half the gain found with information from all US GDB Holsteins. A larger reference population and the availability of genotyped ancestors improved imputation; animals with genotyped parents in a large reference population had higher imputation accuracy than those with no or few genotyped relatives in a small reference population. For small local populations, including genotypes from other related populations can aid in improving imputation accuracy.

Polynomial regression models of the first, second, and third order were used to fit milk production deviations of daughters in Mexico on Canadian and US predicted transmitting ability values for 305-d mature-equivalent milk production (kg). For the pairs Canada-Mexico and Mexico-United States, 40 and 73 bulls with a minimum reliability of 0.75 were analyzed, respectively. Genetic correlations between pairs of countries were also estimated. The parameters were evaluated for all data, and for sires grouped according to the mean of the average phenotypic milk production (high and low) of their daughters' herd mates. Quadratic and cubic effects were not significant in any analysis. From linear regression models, slopes of Mexican daughter deviations on US and Canadian predicted transmitting abilities were 1.01 and 0.93, respectively. Slopes were greater but intercepts were smaller for the high versus low level of production of the sires' herd mates in Mexico. A greater difference between the genetic correlations was found for the high versus low environmental level than for the low level (0.79 vs. 0.70) for Mexico-US data compared with Canada-Mexico data (0.81 vs. 0.78). Genetic correlations between Mexico and the United States (0.74), and between Mexico and Canada (0.77), were smaller than the genetic correlation between the same Canadian and US sires (0.92), suggesting the presence of a moderate degree of genotype-environment interaction for milk production between Canada and the United States, and Mexico.