Monitoring inbreeding trends and inbreeding depression for economically important traits of Holstein cattle in Iran

Pedigree information of 852,443 registered Holstein cows and bulls, collected by the Animal Breeding Center of Iran from 1971 to 2007, was used to calculate inbreeding coefficients and their effect on production, reproduction, somatic cell count, calving ease, and longevity traits. The average inbreeding coefficient for the entire population was 2.90%, ranging from zero to 47.03%. The rates of inbreeding from 1989 to 2007 were 0.22 and 0.15% per year for females and males, respectively. The rates were higher after 2000, being 0.31 and 0.21% per year for females and males, respectively. Inbreeding had a deleterious effect on most traits. For the first 3 lactations, the inbreeding depression per 1% increase in inbreeding was −18.72, −16.19, and −27.38 kg for milk yield, −0.443, −0.367, and −0.690 kg for fat yield, and −0.476, −0.425, and −0.66 kg for protein yield, respectively. For all reproductive traits, the observed undesirable effect of inbreeding was not significant, except for the calving interval (0.53 d per 1% increase in inbreeding) in the third parity and age at first calving (0.45 d per 1% increase in inbreeding). Calving ease in heifers and cows was significantly influenced by the inbreeding of the dam, indicating that highly inbred cows had a higher incidence of difficult calvings. The estimate of inbreeding depression for somatic cell score was low and significant only for the third lactation. However, animals with high inbreeding coefficient tended to have higher somatic cell scores than animals with low inbreeding coefficients. For type traits, the influence of inbreeding was significant only for stature, chest width, body depth, size, rear udder height, suspensory ligament, udder depth, and front and rear teat placement. Cows with high levels of inbreeding coefficient were at higher relative risk of being culled.     

Accuracy of genomic prediction for milk production traits in the Chinese Holstein population using a reference population consisting of cows

Genomic selection using dense markers covering the whole genome is a tool for the genetic improvement of livestock and is revolutionizing the breeding system in dairy cattle. Progeny-tested bulls have been used to form reference populations in almost all countries where genomic selection has been implemented. In this study, the accuracy of genomic prediction when cows are used to form the reference population was investigated. The reference population consisted of 3,087 cows. All individuals were genotyped with Illumina BovineSNP50. After genotype imputation and editing, 48,676 single nucleotide polymorphisms were available for analysis. Two methods, genomic BLUP (GBLUP) and BayesB, were used to render genomic estimated breeding values (GEBV) for 5 milk production traits. Accuracies of GEBV were assessed in 3 ways: r_GEBV,EBV (the correlation between GEBV and conventional EBV) in 67 progeny-tested bulls, r_GEBV,EBV from a 5-fold cross validation in the 3,087 cow reference population, and the theoretical accuracy (for GBLUP) calculated in the same way as for conventional BLUP. The results showed that using GBLUP, the r_GEBV,EBV and theoretical accuracy of genomic prediction in Chinese Holstein ranged from 0.59 to 0.76 and 0.70 to 0.80, respectively, which was 0.13 to 0.30 and 0.23 to 0.33 higher than the accuracies of conventional pedigree index, respectively. The results indicate that, as an alternative, genomic selection using cows in the reference population is feasible.     

Exploring genome-wide differentiation and signatures of selection in Italian and North American Holstein populations

Among Italian dairy cattle, the Holstein is the most reared breed for the production of Parmigiano Reggiano protected designation of origin cheese, which represents one of the most renowned products in the entire Italian dairy industry. In this work, we used a medium-density genome-wide data set consisting of 79,464 imputed SNPs to study the genetic structure of Italian Holstein breed, including the population reared in the area of Parmigiano Reggiano cheese production, and assessing its distinctiveness from the North American population. Multidimensional scaling and ADMIXTURE approaches were used to explore the genetic structure among populations. We also investigated putative genomic regions under selection among these 3 populations by combining 4 different statistical methods based either on allele frequencies (single marker and window-based) or extended haplotype homozygosity (EHH; standardized log-ratio of integrated EHH and cross-population EHH). The genetic structure results allowed us to clearly distinguish the 3 Holstein populations; however, the most remarkable difference was observed between Italian and North American stock. Selection signature analyses identified several significant SNPs falling within or closer to genes with known roles in several traits such as milk quality, resistance to disease, and fertility. In particular, a total of 22 genes related to milk production have been identified using the 2 allele frequency approaches. Among these, a convergent signal has been found in the VPS8 gene which resulted to be involved in milk traits, whereas other genes (CYP7B1, KSR2, C4A, LIPE, DCDC1, GPR20, and ST3GAL1) resulted to be associated with quantitative trait loci related to milk yield and composition in terms of fat and protein percentage. In contrast, a total of 7 genomic regions were identified combining the results of standardized log-ratio of integrated EHH and cross-population EHH. In these regions candidate genes for milk traits were also identified. Moreover, this was also confirmed by the enrichment analyses in which we found that the majority of the significantly enriched quantitative trait loci were linked to milk traits, whereas the gene ontology and pathway enrichment analysis pointed to molecular functions and biological processes involved in AA transmembrane transport and methane metabolism pathway. This study provides information on the genetic structure of the examined populations, showing that they are distinguishable from each other. Furthermore, the selection signature analyses can be considered as a starting point for future studies in the identification of causal mutations and consequent implementation of more practical application.     

Short communication: Genetic relationships between the Holstein cow populations of three European dairy countries

The degree of relatedness was studied in 3 dairy cow populations from Great Britain (GBR), Italy (ITA), and Ireland (IRL) by using cows born from 2003 to 2006. Effective population size, inbreeding coefficient (F), and average relationship in the top and bottom 4,000 cows ranked on a profit index value (PIV) or milk yield evaluations were studied. Average inbreeding was approximately 2% in GBR and ITA, was 1% in IRL, but was slightly more than 2% when the joint pedigree was used. The average F for the joint population was 10 to 15% higher than estimates averaged across the 3 populations, reflecting the increased completeness of pedigree information in the joint pedigree. Effective population size in the joint pedigree was approximately 12% lower than estimates within the individual countries. The average genetic relationships for the top 4,000 PIV cows were not markedly different from those based on milk evaluation in GBR and ITA, but were approximately 2% lower in IRL. This was due to the use of an index with less weight on production traits in IRL compared with GBR and ITA. However, selection of the top 4,000 cows on PIV reduced the degree of relatedness across the 3 countries. The use of common sires accounted for most of the relatedness across the 3 countries, more than did the use of related sires or common foreign dams.     

Short communication: Genomic selection using a multi-breed, across-country reference population

Three breeds (Fleckvieh, Holstein, and Jersey) were included in a reference population, separately and together, to assess the accuracy of prediction of genomic breeding values in single-breed validation populations. The accuracy of genomic selection was defined as the correlation between estimated breeding values, calculated using phenotypic data, and genomic breeding values. The Holstein and Jersey populations were from Australia, whereas the Fleckvieh population (dual-purpose Simmental) was from Austria and Germany. Both a BLUP with a multi-breed genomic relationship matrix (GBLUP) and a Bayesian method (BayesA) were used to derive the prediction equations. The hypothesis tested was that having a multi-breed reference population increased the accuracy of genomic selection. Minimal advantage existed of either GBLUP or BayesA multi-breed genomic evaluations over single-breed evaluations. However, when the goal was to predict genomic breeding values for a breed with no individuals in the reference population, using 2 other breeds in the reference was generally better than only 1 breed.     

Invited review: Inbreeding in the genomics era: Inbreeding,inbreeding depression,and management of genomic variability

Traditionally, pedigree-based relationship coefficients have been used to manage the inbreeding and degree of inbreeding depression that exists within a population. The widespread incorporation of genomic information in dairy cattle genetic evaluations allows for the opportunity to develop and implement methods to manage populations at the genomic level. As a result, the realized proportion of the genome that 2 individuals share can be more accurately estimated instead of using pedigree information to estimate the expected proportion of shared alleles. Furthermore, genomic information allows genome-wide relationship or inbreeding estimates to be augmented to characterize relationships for specific regions of the genome. Region-specific stretches can be used to more effectively manage areas of low genetic diversity or areas that, when homozygous, result in reduced performance across economically important traits. The use of region-specific metrics should allow breeders to more precisely manage the trade-off between the genetic value of the progeny and undesirable side effects associated with inbreeding. Methods tailored toward more effectively identifying regions affected by inbreeding and their associated use to manage the genome at the herd level, however, still need to be developed. We have reviewed topics related to inbreeding, measures of relatedness, genetic diversity and methods to manage populations at the genomic level, and we discuss future challenges related to managing populations through implementing genomic methods at the herd and population levels.     

Factors affecting incorrect paternity assignment in the Israeli Holstein population

A total of 6040 Israeli Holstein cows from 181 Kibbutz herds listed as progeny of 11 sires were genotyped for 104 microsatellites. Seventeen markers were deleted due to a frequency of erroneous genotypes >1%, leaving 160,470 valid genotypes. Conflicts between the putative sire and daughter in at least 2 markers and for at least 10% of the markers genotyped per cow were required to reject paternity. Cows that did not meet the requirements for paternity confirmation or rejection were deleted from further analysis. The frequency of rejected paternity was 11.7%. The effects of recorded sire, birth year, geographical region, herd, and inseminator on the frequency of paternity rejection were analyzed with linear and nonlinear models. Only the effects of inseminator and recorded sire were significant in all models tested that included these effects. The main causes of incorrect paternity recording appear to be inseminator recording mistakes, and possibly mistakes with respect to semen labeling at the AI institutes. Incorrect paternity recording due to multiple inseminations by different sires could explain, at most, 20% of the paternity mistakes. Instituting a system of quality control, especially at the level of the inseminator, should reduce paternity errors to no more than 8%, and increase genetic progress by at least 1%.     

Quantitative trait loci mapping of functional traits in the German Holstein cattle population

A whole-genome scan to detect quantitative trait loci (QTL) for functional traits was performed in the German Holstein cattle population. For this purpose, 263 genetic markers across all autosomes and the pseudoautosomal region of the sex chromosomes were genotyped in 16 granddaughter-design families with 872 sons. The traits investigated were deregressed breedingvalues for maternal and direct effects on dystocia (DYSm, DYSd) and stillbirth (STIm, STId) as well as maternal and paternal effects on nonreturn rates of 90 d (NR90m, NR90p). Furthermore, deregressed breeding values for functional herd life (FHL) and daughter yield deviation for somatic cell count (SCC) were investigated. Weighted multimarker regression analyses across families and permutation tests were applied for the detection of QTL and the calculation of statistical significance. A ten percent genomewise significant QTL was localized for DYSm on chromosome 8 and for SCC on chromosome 18. A further 24 putative QTL exceeding the 5% chromosomewise threshold were detected. On chromosomes 7, 8, 10, 18, and X/Yps, coincidence of QTL for several traits was observed. Our results suggest that loci with influence on udder health may also contribute to genetic variance of longevity. Prior to implementation of these QTL in marker assisted selection programs for functional traits, information about direct and correlated effects of these QTL as well as fine mapping of their chromosomal positions is required.     

Genetic diversity and background linkage disequilibrium in the North American Holstein cattle population

The objectives of this study were to 1) identify highly heterozygous Holstein bulls that are as unrelated as possible and widely used in the US dairy industry; 2) quantify the level of genetic diversity in US Holsteins; and 3) determine the extent of background linkage disequilibrium (BLD) and disease trait associated linkage disequilibrium (DLD) in the US Holstein population. Twenty-three Holstein bulls that are not closely related but were widely used in the US dairy industry were genotyped for 54 microsatellite loci. The genotyping was performed on automated DNA sequencers (PE Applied Biosystems, CA), following polymerase chain reaction amplification with fluorescent dye-labeled primers. The heterozygosity for the sampled population ranged from 0.43 to 0.80. This wide range of heterozygosity allows selection of the most heterozygous bulls to develop informative families for gene mapping studies. The degree of genetic diversity in this population is significant and allows selection for traits of economic importance. As expected, there is extensive linkage disequilibrium (LD) in the US Holstein population. About half of the syntenic marker pairs presented a typical pattern of LD produced by DLD. Most of the nonsyntenic marker pairs had a typical pattern of LD arising from BLD. These results suggest that the observed LD is not purely due to genetic drift and migration and that a portion might be due to DLD. This raises our hopes of successful fine-localization of genes for complex traits using LD mapping.     

Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population

Genealogical information is an essential tool for carrying out any genetic improvement program. The objective of this study was to determine the accuracy of pedigree information in the Mexican registered Holstein population using genomic data available in Mexico and for the US Holstein population. The study included 7,508 animals (158 sires and 7,350 cows) that were born from 2002 through 2014, registered with Holstein de México, and genotyped with single nucleotide polymorphism arrays of different densities. Parentage could not be validated for 17% of sires of cows and 12% of sires of bulls. Most (79%) of the dams of cows and the dams of bulls had no genotype available and could not be validated. A parentage test was possible for only 6,104 sires of cows, 139 sires of bulls, 1,519 dams of cows, and 33 dams of bulls. Of the animals with a parentage test, parent assignment was confirmed for 89% of sires of cows, 92% of dams of cows, 95% of sires of bulls, and 97% of dams of bulls. Parent discovery was possible for some animals without confirmed parents: 17% for sires of cows, 2.5% for dams of cows, 43% for sires of bulls, and 0% for dams of bulls. Of the 7,795 progeny tests, 777 had parent conflicts, which is an error rate of 9.97% for parental recording in the population, a rate that is similar to those recently reported for other populations. True parents for some progeny conflicts (15%) were discovered for the Mexican population, and the remaining parents were assigned as unknown. Expected effects of misidentification on rate of genetic gain could be decreased by half if genealogical errors were decreased to 5%. This study indicates that genotyping and genealogy recovery may help in increasing rates of genetic improvement in the Mexican registered Holstein population.     

Modeling heat stress effect on Holstein cows under hot and dry conditions: Selection tools

Data from milk recording of Holstein-Friesian cows together with weather information from 2 regions in Southern Spain were used to define the models that can better describe heat stress response for production traits and somatic cell score (SCS). Two sets of analyses were performed, one aimed at defining the population phenotypic response and the other at studying the genetic components. The first involved 2,514,762 test-day records from up to 5 lactations of 128,112 cows. Two models, one fitting a comfort threshold for temperature and a slope of decay after the threshold, and the other a cubic Legendre polynomial (LP) model were tested. Average (T_AVE) and maximum daily temperatures were alternatively considered as covariates. The LP model using T_AVE as covariate showed the best goodness of fit for all traits. Estimated rates of decay from this model for production at 25 and 34°C were 36 and 170, 3.8 and 3.0, and 3.9 and 8.2 g/d per degree Celsius for milk, fat, and protein yield, respectively. In the second set of analyses, a sample of 280,958 test-day records from first lactations of 29,114 cows was used. Random regression models including quadratic or cubic LP regressions (TEM_) on T_AVE or a fixed threshold and an unknown slope (DUMMY), including or not cubic regressions on days in milk (DIM3_), were tested. For milk and SCS, the best models were the DIM3_ models. In contrast, for fat and protein yield, the best model was TEM3. The DIM3DUMMY models showed similar performance to DIM3TEM3. The estimated genetic correlations between the same trait under cold and hot temperatures (ρ) indicated the existence of a large genotype by environment interaction for fat (ρ = 0.53 for model TEM3) and protein yield (ρ around 0.6 for DIM3TEM3) and for SCS (ρ = 0.64 for model DIM3TEM3), and a small genotype by environment interaction for milk (ρ over 0.8). The eigendecomposition of the additive genetic covariance matrix from model TEM3 showed the existence of a dominant component, a constant term that is not affected by temperature, representing from 64% of the variation for SCS to 91% of the variation for milk. The second component, showing a flat pattern at intermediate temperatures and increasing or decreasing slopes for the extremes, gathered 15, 11, and 24% of the variation for fat and protein yield and SCS, respectively. This component could be further evaluated as a selection criterion for heat tolerance independently of the production level.     

Inbreeding and effective population size in French dairy sheep: Comparison between genomic and pedigree estimates

Before availability of dense SNP data, genetic diversity was characterized and managed with pedigree-based information. Besides this classical approach, 2 methodologies have been proposed in recent years to characterize and manage diversity from dense SNP data: the SNP-by-SNP approach and the alternative based on runs of homozygosity (ROH). The establishment of criteria to identify ROH is a current constraint in the literature dealing with ROH. The objective of this study was, using a medium-density SNP chip, to quantify by 3 methods (pedigree, SNP-by-SNP, and ROH) the genetic diversity on 5 selected French dairy sheep subpopulations and breeds and to assess the effect of the definition of ROH on these estimates. The data set available included individuals from the breeds Basco-Béarnaise, Manech Tête Noire, Manech Tête Rousse, and 2 subpopulations of Lacaune: Lacaune Confederation and Lacaune Ovitest. Animals were genotyped with the Illumina OvineSNP50 BeadChip (Illumina Inc., San Diego, CA). After filtering, the genomic data included 38,287 autosomal SNP and 8,700 individuals, which comprised 72,803 animals in the pedigree. The results indicated that no significant differences were observed in effective population size estimates obtained from pedigree or genomic (SNP-by-SNP or ROH) information. In general, estimates of effective population size were above 200 in Lacaune Confederation and Lacaune Ovitest subpopulations and below 200 in Basco-Béarnaise, Manech Tête Noire, and Manech Tête Rousse breeds. The minimum length that constituted a ROH, the minimum number of SNP that constituted a ROH, as well as the minimum density and the maximum distance allowed between 2 homozygous SNP are ROH-defining factors with important implications in the estimation of the rate of inbreeding. The ROH-based rates of inbreeding in concordance with those obtained from pedigree information require a specific set of values. This particular set of values is different from that identified to obtain ROH-based rates of inbreeding similar to those obtained on a SNP-by-SNP basis. Factors to define ROH do not change the results much unless extreme values are considered, although further research on ROH-based inbreeding is still required.     

Maternal and fetal inbreeding depression for 70-day nonreturn and calving rate in Holsteins and Jerseys

Inbreeding depression for 70-d nonreturn rate was estimated in 50,613 Holstein and 47,673 Jersey cows with five-generation pedigrees using an animal model. Heritabilities of 70-d nonreturn rate were very low for both breeds (1 to 2%). Maternal inbreeding depression was small (3% reduction for 10% inbreeding) and significant only for Jerseys. Fetal and maternal inbreeding depression was not significant for individual parities in Holsteins, but maternal inbreeding depression was significant in first parity only in Jerseys. Maternal and fetal inbreeding depression of calving rate (verified by a subsequent calving) was estimated on separate datasets by parity from 13,229 to 26,876 Holstein and 7374 to 11,742 Jersey cows. First-parity estimates for heritability of calving rate were 1% or less, whereas estimates for later parities varied from 1 to 6%. Significant inbreeding depression in first-parity Holsteins reduced calving rate by 4% per 10% maternal or fetal inbreeding, but effects, while undesirable, were not consistently significant in other parities. In Jerseys, maternal inbreeding significantly reduced calving rate by 6% per 10% inbreeding in first parity, and was undesirable but not significant for second through fourth parities. Fetal inbreeding depression was not significant in Jerseys. Maternal inbreeding depression of 70-d nonreturn and calving rate was small, undesirable, but not consistently significant across breeds and parities. The cumulative economic impact of maternal or fetal inbreeding on lifetime reproductive performance of Holstein or Jersey cows would be more dramatic than results for a single breeding.     

Strategies for continual application of marker-assisted selection in an open nucleus population

The objectives of this study were to develop and simulate the implementation of several strategies for repeated application of quantitative trait loci (QTL) detection and marker-assisted selection (MAS) and to compare the short-term and continual genetic responses. A finite locus model was simulated with 20 QTL randomly distributed across 30 chromosome. Three hundred markers were evenly spaced across the genome. Allelic effects were sampled from a double exponential distribution. A daughter design was used every generation to determine the marker alleles favorably associated to QTL alleles. The MAS was applied within family to young bulls, before progeny testing, as part of an open nucleus. Young bulls were selected using strategies based on 1) the single marker with greatest contrast (BEST1), 2) the sum of n greatest contrasts (BESTn), 3) the best n contrasts, limited to one per chromosome (LIMn), 4) the sum of all contrasts exceeding a given threshold n (THRESn), and 5) the sum of contrasts exceeding a threshold, but limited to one per chromosome (LIMT). The maximum progress was achieved by strategies that selected upon several markers flanking multiple QTL in each generation. When THRES was applied, the mean true breeding value (TBV) of selected bulls was increased by 11.98% (over conventional selection) versus 6.73% for BEST1 in the first generation. Applying a full genome scan in each generation allowed selection for different QTL across time. By selecting for multiple QTL over time, MAS maintained superiority over conventional selection for many generations.     

Progeny testing and selection intensity for Holstein bulls in different countries

International Bull Evaluation Service (Interbull) Holstein evaluations from February 1995 through February 2003 were used to determine characteristics of progeny testing for Holstein bulls in Australia, Canada, Denmark, France, Germany, Italy, New Zealand, Sweden, The Netherlands, and the United States. The decision to graduate a bull from progeny test (PT) was assumed to have been made based on the second Interbull evaluation, and graduation was defined as the addition of 200 daughters in the period 2.5 to 4.5 yr later. Mean bull age at PT decision varied across countries by 12 mo. Mean numbers of herds and daughters ranged from 39 to 111 and 54 to 144, respectively. Countries with higher requirements for official evaluations generally had more herds and daughters but older bulls at PT decision. Mean estimated breeding values for yield traits of sires of tested bulls were most similar across countries for fat, differing by only 6.4 kg. The four countries highest for sire protein differed only by 1 kg; however, the range was 12 kg. Percentages of bulls graduated ranged from 4.4 to 14.7 across countries. Selection intensities (standardized selection differentials) tended to be about 1.0 for yield traits. Selection intensities for somatic cell score were generally unfavorable, reflecting selection for negatively correlated yield traits. Reflecting variation in national breeding goals, selection intensities for stature were positive for most countries and highly negative for New Zealand. Selection intensity for fore udder was generally the lowest among the traits examined. All but one country showed positive selection for udder support. These statistics permit comparison of the components of PT programs across country, illustrating possible opportunities for improvement.     

Dynamics of culling for Jersey,Holstein, and Jersey × Holstein crossbred cows in large multibreed dairy herds

The objective of this observational study was to describe and compare the dynamics of reason-specific culling risk for the genetic groups Jerseys (JE), Holsteins (HO), and Jersey × Holstein crossbreds (JH), considering parity, stage of lactation, and milk yield, among other variables, in large multibreed dairy herds in Texas. The secondary objective was to analyze the association between survival and management factors, such as breeding and replacement policies, type of facilities, and use of cooling systems. After edits, available data included 202,384 lactations in 16 herds, ranging from 407 to 8,773 cows calving per year during the study period from 2007 to 2011. The distribution of lactation records by genetic group was 58, 36, and 6% for HO, JE, and JH crosses, respectively. Overall culling rates across breeds were 30.1, 32.1, and 35.0% for JH, JE, and HO, respectively. The dynamics of reason-specific culling were dependent on genetic group, parity, stage of lactation, milk yield, and herd characteristics. Early lactation was a critical period for “died” and “injury-sick” culling. The risk increased with days after calving for “breeding” and, in the case of HO, “low production” culling. Open cows had a 3.5 to 4.6 times greater risk for overall culling compared with pregnant cows. The odds of culling with reason “died” within the first 60 d in milk (DIM) were not significantly associated with genetic group. However, both JE and JH crosses had lower odds of live culling within the first 60 DIM compared with HO cows (OR = 0.72 and 0.82, respectively). Other cow variables significantly associated with the risk of dying within the first 60 DIM were cow relative 305-d mature equivalent (305ME) milk yield, parity, and season of calving. Significant herd-related variables for death included herd size and origin of replacements. In addition to genetic group, the risk of live culling within 60 DIM was associated with cow-relative 305ME milk yield, parity, and season of calving. Significant herd-related variables for live culling included herd-relative 305ME milk yield, herd size, type of facility, origin of replacement, and type of maternity. Overall, reason-specific culling followed similar patterns across DIM in the 3 genetic groups.     

How genomic selection has increased rates of genetic gain and inbreeding in the Australian national herd,genomic information nucleus,and bulls

Genomic selection has been commonly used for selection for over a decade. In this time, the rate of genetic gain has more than doubled in some countries, while inbreeding per year has also increased. Inbreeding can result in a loss of genetic diversity, decreased long-term response to selection, reduced animal performance and ultimately, decreased farm profitability. We quantified and compared changes in genetic gain and diversity resulting from genomic selection in Australian Holstein and Jersey cattle populations. To increase the accuracy of genomic selection, Australia has had a female genomic reference population since 2013, specifically designed to be representative of commercial populations and thus including both Holstein and Jersey cows. Herds that kept excellent health and fertility data were invited to join this population and most their animals were genotyped. In both breeds, the rate of genetic gain and inbreeding was greatest in bulls, and then the female genomic reference population, and finally the wider national herd. When comparing pre- and postgenomic selection, the rates of genetic gain for the national economic index has increased by ~160% in Holstein females and ~100% in Jersey females. This has been accompanied by doubling of the rates of inbreeding in female populations, and the rate of inbreeding has increased several fold in Holstein bulls since the widespread use of genomic selection. Where cow genotype data were available to perform a more accurate genomic analysis, greater rates of pedigree and genomic inbreeding were observed, indicating actual inbreeding levels could be underestimated in the national population due to gaps in pedigrees. Based on current rates of genetic gain, the female reference population is progressing ahead of the national herd and could be used to infer and track the future inbreeding and genetic trends of the national herds.     

Inbreeding depression on female fertility and calving ease in Spanish dairy cattle

Inbreeding depression on female fertility and calving ease in Spanish dairy cattle was studied by the traditional inbreeding coefficient (F) and an alternative measurement indicating the inbreeding rate (ΔF) for each animal. Data included records from 49,497 and 62,134 cows for fertility and calving ease, respectively. Both inbreeding measurements were included separately in the routine genetic evaluation models for number of insemination to conception (sequential threshold animal model) and calving ease (sire-maternal grandsire threshold model). The F was included in the model as a categorical effect, whereas ΔF was included as a linear covariate. Inbred cows showed impaired fertility and tended to have more difficult calvings than low or noninbred cows. Pregnancy rate decreased by 1.68% on average for cows with F from 6.25 to 12.5%. This amount of inbreeding, however, did not seem to increase dystocia incidence. Inbreeding depression was larger for F greater than 12.5%. Cows with F greater than 25% had lower pregnancy rate and higher dystocia rate (−6.37 and 1.67%, respectively) than low or noninbred cows. The ΔF had a significant effect on female fertility. A ΔF = 0.01, corresponding to an inbreeding coefficient of 5.62% for the average equivalent generations in the data used (5.68), lowered pregnancy rate by 1.5%. However, the posterior estimate for the effect of ΔF on calving ease was not significantly different from zero. Although similar patterns were found with both F and ΔF, the latter detected a lowered pregnancy rate at an equivalent F, probably because it may consider the known depth of the pedigree. The inbreeding rate might be an alternative choice to measure inbreeding depression.     

Deterministic models of breeding scheme designs that incorporate genomic selection

A deterministic model to calculate rates of genetic gain and inbreeding was used to compare a range of breeding scheme designs under genomic selection (GS) for a population of 140,000 cows. For most schemes it was assumed that the reliability of genomic breeding values (GEBV) was 0.6 across 4 pathways of selection. In addition, the effect of varying reliability on the ranking of schemes was also investigated. The schemes considered included intense selection in male pathways and genotyping of 1,000 young bulls (GS-Y). This scheme was extended to include selection in females and to include a “worldwide” scheme similar to GS-Y, but 6 times as large and assuming genotypes were freely exchanged between 6 countries. An additional worldwide scheme was modeled where GEBV were available through international genetic evaluations without exchange of genotypes. Finally, a closed nucleus herd that used juvenile in vitro embryo transfer in heifers was modeled so that the generation interval in female pathways was reduced to 1 or 2 yr. When the breeding schemes were compared using a GEBV reliability of 0.6, the rates of genetic gain were between 59 and 130% greater than the rate of genetic gain achieved in progeny testing. This was mainly through reducing the generation interval and increasing selection intensity. Genomic selection of females resulted in a 50% higher rate of genetic gain compared with restricting GS to young bulls only. The annual rates of inbreeding were, in general, 60% lower than with progeny testing, because more sires of bulls and sires of cows were selected, thus increasing the effective population size. The exception was in nucleus breeding schemes that had very short generation intervals, resulting in higher rates of both gain and inbreeding. It is likely that breeding companies will move rapidly to alter their breeding schemes to make use of genomic selection because benefits to the breeding companies and to the industry are considerable.