Novel strategies to minimize progeny inbreeding while maximizing genetic gain using genomic information

In this study, 3 strategies for controlling progeny inbreeding in mating plans were compared. The strategies used information from pedigree inbreeding coefficients, genomic relationships, or shared runs of homozygosity. The strategies were compared for the reduction in genetic gain and progeny inbreeding that would be expected from selected matings, and for the decrease of homozygosity of deleterious recessive alleles. Using real pedigree, genotype [43,115 single nucleotide polymorphism (SNP) markers], and estimated breeding value data from Holstein cattle, mating plans were derived for herds of 300 cows with 20 sires available for mating, replicated 50 times. Each of the 300 individuals allocated as dams were matched to 1 of 20 sires to maximize genetic merit minus the penalty for estimated progeny inbreeding, and given the restriction that the sire could not be mated to more than 10% of the cows. The strategy that used a genomic relationship matrix (GRM) was the most effective in reducing average progeny inbreeding; this strategy also resulted in fewer homozygous SNP out of 1,000 low-frequency SNP compared with the strategy using pedigree information. In the future, large numbers of cattle may be genotyped for low-density SNP panels. A GRM constructed using 3,123 SNP produced results similar to a GRM constructed using the full 43,115 SNP. These results demonstrate that using GRM information, a 1% reduction in progeny inbreeding (valued at around $5 per cow) can be made with very little compromise in the overall breeding objective. These results and the availability of low-cost, low-density genotyping make it attractive to apply mating plans that use genomic information in commercial dairy herds.     

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.     

Genomic and pedigree estimation of inbreeding depression for semen traits in the Basco-Béarnaise dairy sheep breed

Inbreeding depression is associated with a decrease in performance and fitness of the animals. The goal of this study was to evaluate pedigree-based and genomic methods to estimate the level of inbreeding and inbreeding depression for 3 semen traits (volume, concentration, and motility score) in the Basco-Béarnaise sheep breed. Data comprised 16,196 (or 15,071) phenotypic records from 620 rams (of which 533 rams had genotypes of 36,464 SNPs). The pedigree included 8,266 animals, composed of the 620 rams and their ancestors. The number of equivalent complete generations for the 620 rams was 7.04. Inbreeding coefficients were estimated using genomic and pedigree-based information. Genomic inbreeding coefficients were estimated from individual SNP and using segments of homozygous SNP (runs of homozygosity, ROH). Short ROH are of old origin, whereas long ROH are due to recent inbreeding. Considering that the equivalent number of generations in Basco-Béarnaise was 6, inbreeding coefficients for ROH with a length >4 Mb refer to all (recent + old) inbreeding, those with a length >17 Mb correspond to recent inbreeding, and the difference between them indicates old inbreeding. Pedigree-based inbreeding coefficients were also estimated classically, or accounting for nonzero relationships for unknown parents, or including metafounder relationships (estimated using markers) to account for missing pedigree information. Finally, inbreeding coefficients combining genotyped and nongenotyped animal information were computed from matrix H of the single-step approach, also including metafounders. Inbreeding depression was estimated differently depending on the approach used to compute inbreeding coefficients. These 8 estimators of inbreeding coefficients were included as covariates in different animal models. No inbreeding depression was detected for sperm volume or sperm concentration. Inbreeding depression was significant for the motility of spermatozoa. The effect of old and recent inbreeding on motility was null and negative, respectively, demonstrating the existence of purging by selection of deleterious recessive alleles affecting motility. A 10% increase in inbreeding would result in a reduction in mean motility ranging between 0.09 and 0.22 points in the score (from 0 to 5). Motility is unfavorably affected by increasing recent inbreeding but the impact is very small. Runs of homozygosity and metafounders allow us to accurately estimate inbreeding depression and detect recent inbreeding.     

Genomic inbreeding coefficients using imputed genotypes: Assessing different estimators in Holstein-Friesian dairy cows

The objective of this study was to estimate inbreeding coefficients in Holstein dairy cattle using imputed SNPs data. A data set of 95,540 Italian Holstein dairy cows from the routine genomic evaluations of the Italian National Association of Holstein, Brown, and Jersey Breeders were analyzed, with 84,445 imputed SNP. Ten widely used genomic inbreeding estimators were tested, including 4 PLINK v1.9 estimators (F, F_HAT1, F_HAT2, F_HAT3), 3 genomic relationship matrix (GRM)-based methods [VanRaden's first method with observed allele frequencies (F_GRM) or with fixed frequencies at 0.5 (F_GRM05), VanRaden's third method, allelic frequency free and pedigree regressed (F_GRM2)], runs of homozygosity (ROH)-based estimators in a complete (F_ROH) and simplified version (F_ROH2), and proportion of homozygous SNP (F_PH). Pairwise comparisons among them were made, including the comparison with traditional pedigree-based inbreeding coefficients (F_PED). Our results showed variability among the genomic inbreeding estimators. Coefficients of F_GRM and F_HAT3 were >1, meaning that more variability has been lost than the variability that existed in the base population. Regarding the remaining ones, F_GRM05, F_ROH, F_ROH2, and F_PH provided coefficients within the [0,1] space and are considered comparable to F_PED. Not comparable to F_PED, yet with an interpretable value, can be considered the coefficients of F, F_HAT2, and F_GRM2. Estimators based on ROH had the highest correlation with pedigree-based coefficients (0.59–0.66), among all estimators tested. In this study, Spearman correlations were shown to possibly provide a clearer estimation of the strength of the relationship between estimators. We hypothesize that imputation might cause extreme genomic inbreeding values that deserves further investigation.     

Inbreeding coefficients and runs of homozygosity islands in Brazilian water buffalo

Characterization of autozygosity is relevant to monitor genetic diversity and manage inbreeding levels in breeding programs. Identification of autozygosity hotspots can unravel genomic regions targeted by selection for economically important traits and can help identify candidate genes for selection. In this study, we estimated the inbreeding levels of a Brazilian population of Murrah buffalo undergoing selection for milk production traits, particularly milk yield. We also studied the distribution of runs of homozygosity (ROH) islands and identified putative genes and quantitative trait loci (QTL) under selection. We genotyped 422 Murrah buffalo for 51,611 SNP; 350 of these had ROH longer than 10 Mb, indicating the occurrence of inbreeding in the last 5 generations. The mean length of the ROH per animal was 4.28 ± 1.85 Mb. Inbreeding coefficients were calculated from the genomic relationship matrix, the pedigree, and the ROH, with estimates varying between 0.242 and 0.035. Inbreeding estimates from the pedigree had a low correlation with the genomic estimates, and estimates from the genomic relationship matrix were much higher than those from the pedigree or the ROH. Signatures of selection were identified in 6 genomic regions, located on chromosomes 1, 2, 3, 5, 16, and 18, encompassing a total of 190 genes and 174 QTL. Many of the genes (e.g., APRT and ACSF3) and QTL identified are related to milk production traits, such as milk yield, milk fat yield and percentage, and milk protein yield and percentage. Other genes are associated with reproduction and immune response traits as well as morphological aspects of the buffalo species. Inbreeding levels in this population are still low but are increasing due to selection and should be managed to avoid future losses due to inbreeding depression. The proximity of genes linked to milk production traits with genes associated with reproduction and immune system traits suggests the need to include these latter genes in the breeding program to avoid negatively affecting them due to selection for production traits.     

Comparative analysis of inbreeding parameters and runs of homozygosity islands in 2 Italian autochthonous cattle breeds mainly raised in the Parmigiano-Reggiano cheese production region

Reggiana and Modenese are autochthonous cattle breeds, reared in the North of Italy, that can be mainly distinguished for their standard coat color (Reggiana is red, whereas Modenese is white with some pale gray shades). Almost all milk produced by these breeds is transformed into 2 mono-breed branded Parmigiano-Reggiano cheeses, from which farmers receive the economic incomes needed for the sustainable conservation of these animal genetic resources. After the setting up of their herd books in 1960s, these breeds experienced a strong reduction in the population size that was subsequently reverted starting in the 1990s (Reggiana) or more recently (Modenese) reaching at present a total of about 2,800 and 500 registered cows, respectively. Due to the small population size of these breeds, inbreeding is a very important cause of concern for their conservation programs. Inbreeding is traditionally estimated using pedigree data, which are summarized in an inbreeding coefficient calculated at the individual level (F_PED). However, incompleteness of pedigree information and registration errors can affect the effectiveness of conservation strategies. High-throughput SNP genotyping platforms allow investigation of inbreeding using genome information that can overcome the limits of pedigree data. Several approaches have been proposed to estimate genomic inbreeding, with the use of runs of homozygosity (ROH) considered to be the more appropriate. In this study, several pedigree and genomic inbreeding parameters, calculated using the whole herd book populations or considering genotyping information (GeneSeek GGP Bovine 150K) from 1,684 Reggiana cattle and 323 Modenese cattle, were compared. Average inbreeding values per year were used to calculate effective population size. Reggiana breed had generally lower genomic inbreeding values than Modenese breed. The low correlation between pedigree-based and genomic-based parameters (ranging from 0.187 to 0.195 and 0.319 to 0.323 in the Reggiana and Modenese breeds, respectively) reflected the common problems of local populations in which pedigree records are not complete. The high proportion of short ROH over the total number of ROH indicates no major recent inbreeding events in both breeds. ROH islands spread over the genome of the 2 breeds (15 in Reggiana and 14 in Modenese) identified several signatures of selection. Some of these included genes affecting milk production traits, stature, body conformation traits (with a main ROH island in both breeds on BTA6 containing the ABCG2, NCAPG, and LCORL genes) and coat color (on BTA13 in Modenese containing the ASIP gene). In conclusion, this work provides an extensive comparative analysis of pedigree and genomic inbreeding parameters and relevant genomic information that will be useful in the conservation strategies of these 2 iconic local cattle breeds.     

Mating programs including genomic relationships and dominance effects

Computerized mating programs using genomic information are needed by breed associations, artificial-insemination organizations, and on-farm software providers, but such software is already challenged by the size of the relationship matrix. As of October 2012, over 230,000 Holsteins obtained genomic predictions in North America. Efficient methods of storing, computing, and transferring genomic relationships from a central database to customers via a web query were developed for approximately 165,000 genotyped cows and the subset of 1,518 bulls whose semen was available for purchase at that time. This study, utilizing 3 breeds, investigated differences in sire selection, methods of assigning mates, the use of genomic or pedigree relationships, and the effect of including dominance effects in a mating program. For both Jerseys and Holsteins, selection and mating programs were tested using the top 50 marketed bulls for genomic and traditional lifetime net merit as well as 50 randomly selected bulls. The 500 youngest genotyped cows in the largest herd in each breed were assigned mates of the same breed with limits of 10 cows per bull and 1 bull per cow (only 79 cows and 8 bulls for Brown Swiss). A dominance variance of 4.1 and 3.7% was estimated for Holsteins and Jerseys using 45,187 markers and management group deviation for milk yield. Sire selection was identified as the most important component of improving expected progeny value, followed by managing inbreeding and then inclusion of dominance. The respective percentage gains for milk yield in this study were 64, 27, and 9, for Holsteins and 73, 20, and 7 for Jerseys. The linear programming method of assigning a mate outperformed sequential selection by reducing genomic or pedigree inbreeding by 0.86 to 1.06 and 0.93 to 1.41, respectively. Use of genomic over pedigree relationship information provided a larger decrease in expected progeny inbreeding and thus greater expected progeny value. Based on lifetime net merit, the economic value of using genomic relationships was >$3 million per year for Holsteins when applied to all genotyped females, assuming that each will provide 1 replacement. Previous mating programs required transferring only a pedigree file to customers, but better service is possible by incorporating genomic relationships, more precise mate allocation, and dominance effects. Economic benefits will continue to grow as more females are genotyped.     

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.     

Controlling bias in genomic breeding values for young genotyped bulls

The objectives of this study were to investigate bias in genomic predictions for dairy cattle and to find a practical approach to reduce the bias. The simulated data included phenotypes, pedigrees, and genotypes, mimicking a dairy cattle population (i.e., cows with phenotypes and bulls with no phenotypes) and assuming selection by breeding values or no selection. With the simulated data, genomic estimated breeding values (GEBV) were calculated with a single-step genomic BLUP and compared with true breeding values. Phenotypes and genotypes were simulated in 10 generations and in the last 4 generations, respectively. Phenotypes in the last generation were removed to predict breeding values for those individuals using only genomic and pedigree information. Complete pedigrees and incomplete pedigrees with 50% missing dams were created to construct the pedigree-based relationship matrix with and without inbreeding. With missing dams, unknown parent groups (UPG) were assigned in relationship matrices. Regression coefficients (b₁) and coefficients of determination (R²) of true breeding values on (G)EBV were calculated to investigate inflation and accuracy in GEBV for genotyped animals, respectively. In addition to the simulation study, 18 linear type traits of US Holsteins were examined. For the 18 type traits, b₁ and R² of GEBV with full data sets on GEBV with partial data sets for young genotyped bulls were calculated. The results from the simulation study indicated inflation in GEBV for genotyped males that were evaluated with only pedigree and genomic information under BLUP selection. However, when UPG for only pedigree-based relationships were included, the inflation was reduced, accuracy was highest, and genetic trends had no bias. For the linear type traits, when UPG for only pedigree-based relationships were included, the results were generally in agreement with those from the simulation study, implying less bias in genetic trends. However, when including no UPG, UPG in pedigree-based relationships, or UPG in genomic relationships, inflation and accuracy in GEBV were similar. The results from the simulation and type traits suggest that UPG must be defined accurately to be estimable and inbreeding should be included in pedigree-based relationships. In dairy cattle, known pedigree information with inbreeding and estimable UPG plays an important role in improving compatibility between pedigree-based and genomic relationship matrices, resulting in more reliable genomic predictions.     

Genome-wide mapping and estimation of inbreeding depression of semen quality traits in a cattle population

Inbreeding depression is known to affect quantitative traits such as male fertility and sperm quality, but the genetic basis for these associations is poorly understood. Most studies have been limited to examining how pedigree- or marker-derived genome-wide autozygosity is associated with quantitative phenotypes. In this study, we analyzed possible associations of genetic features of inbreeding depression with percentage of live spermatozoa and total number of spermatozoa in 19,720 ejaculates obtained from 554 Austrian Fleckvieh bulls during routine artificial insemination programs. Genome-wide inbreeding depression was estimated and genomic regions contributing to inbreeding depression were mapped. Inbreeding depression did affect total number of spermatozoa, and such depression was predicted by pedigree-based inbreeding levels and genome-wide inbreeding levels based on runs of homozygosity (ROH). Genome-wide inbreeding depression did not seem to affect percentage of live spermatozoa. A model incorporating genetic effects of the bull, environmental factors, and additive genetic and ROH status effects of individual single-nucleotide polymorphisms revealed genomic regions significantly associated with ROH status for total number of spermatozoa (4 regions) or percentage of live spermatozoa (5 regions). All but one region contains genes related to spermatogenesis and sperm morphology. These genomic regions contain genes affecting sperm morphogenesis and efficacy. The results highlight that next-generation sequencing may help explain some of the genetic factors contributing to inbreeding depression of sperm quality traits in Fleckvieh bulls.     

A 100-Year Review: Methods and impact of genetic selection in dairy cattle—From daughter–dam comparisons to deep learning algorithms

In the early 1900s, breed society herdbooks had been established and milk-recording programs were in their infancy. Farmers wanted to improve the productivity of their cattle, but the foundations of population genetics, quantitative genetics, and animal breeding had not been laid. Early animal breeders struggled to identify genetically superior families using performance records that were influenced by local environmental conditions and herd-specific management practices. Daughter–dam comparisons were used for more than 30 yr and, although genetic progress was minimal, the attention given to performance recording, genetic theory, and statistical methods paid off in future years. Contemporary (herdmate) comparison methods allowed more accurate accounting for environmental factors and genetic progress began to accelerate when these methods were coupled with artificial insemination and progeny testing. Advances in computing facilitated the implementation of mixed linear models that used pedigree and performance data optimally and enabled accurate selection decisions. Sequencing of the bovine genome led to a revolution in dairy cattle breeding, and the pace of scientific discovery and genetic progress accelerated rapidly. Pedigree-based models have given way to whole-genome prediction, and Bayesian regression models and machine learning algorithms have joined mixed linear models in the toolbox of modern animal breeders. Future developments will likely include elucidation of the mechanisms of genetic inheritance and epigenetic modification in key biological pathways, and genomic data will be used with data from on-farm sensors to facilitate precision management on modern dairy farms.     

Genomic inbreeding and relationships among Holsteins, Jerseys, and Brown Swiss

Genomic measures of relationship and inbreeding within and across breeds were compared with pedigree measures using genotypes for 43,385 loci of 25,219 Holsteins, 3,068 Jerseys, and 872 Brown Swiss. Adjustment factors allow genomic and pedigree relationships to match more closely within breeds and in multibreed populations and were estimated using means and regressions of genomic on pedigree relationships and allele frequencies in base populations. Correlations of genomic relationships with pedigree inbreeding were higher within each breed when an allele frequency of 0.5, rather than base population frequencies, was used, whereas correlations of average genomic relationships with average pedigree relationships and also reliabilities of genomic evaluations were higher using base population frequencies. Allele frequencies differed in the 3 breeds and were correlated by 0.65 to 0.67 when estimated from genotyped animals compared with 0.72 to 0.74 when estimated from breed base populations. The largest difference in allele frequency was between Holstein and the other breeds on chromosome Bos taurus autosome 4 near a gene affecting appearance of white skin patches (vitiligo) in humans. Each animal's breed composition was predicted very accurately with a standard deviation of <3% using regressions on genotypes at all loci or less accurately with a standard deviation of <6% using subsets of loci. Genomic future inbreeding (half an animal's mean genomic relationship to current animals of the same breed) was correlated by 0.75 to 0.94 with expected future inbreeding (half the average pedigree relationship). Correlations of both were slightly higher with parent averages than with genomic evaluations for net merit of young Holstein bulls. Thus, rates of increase in genomic and pedigree inbreeding per generation should be slightly reduced with genomic selection, in agreement with previous simulations. Genomic inbreeding and future inbreeding have been provided with individual genomic predictions since 2008. New methods to adjust pedigree and genomic relationship matrices so that they match may provide an improved basis for multibreed genomic evaluation. Positive definite matrices can be obtained by adjusting pedigree relationships for covariances among base animals within breed, whereas adjusting genomic relationships to match pedigree relationships can introduce negative eigenvalues. Pedigree relationship matrices ignore common ancestry shared by base animals within breed and may not approximate genomic relationships well in multibreed populations.     

Estimation of intrachromosomal inbreeding depression on female fertility using runs of homozygosity in Finnish Ayrshire cattle

Inbreeding increases homozygosity, which in turn increases the frequency of harmful recessive alleles, resulting in inbreeding depression. Inbreeding depression on fertility reduces the profitability of dairy farming by decreasing the lifetime milk production of cows and by increasing insemination and veterinary costs. Continuous homozygous segments, called runs of homozygosity (ROH), are currently considered to provide an effective measure of genomic inbreeding. The aim of this study was to estimate the effect of increased intrachromosomal homozygosity for female fertility in the Finnish Ayrshire population using ROH and haplotype analysis. Genotypes were obtained from 13,712 females with the Illumina BovineLD v.2 BeadChip low-density panel (Illumina Inc., San Diego, CA) and imputed to 50K density. After quality control, 40,554 single nucleotide polymorphisms remained for the analysis. Phenotypic data consisted of records for nonreturn rate, intervals from first to last insemination (IFL), and intervals from calving to first insemination. The raw phenotypic values were preadjusted for systematic effects before statistical analyses. The ROH-based inbreeding coefficients (F_ROH) were used as covariates in the mixed model equation to estimate the association between inbreeding and inbreeding depression on female fertility. First, we estimated the effect of increased chromosomal F_ROH. We detected significant inbreeding depression on IFL. Based on our results, a 10% increase in F_ROH on chromosomes 2, 18, and 22 were associated with IFL of heifers lengthening by 1.6, 0.9, and 0.7 d, respectively. Similarly, a 10% increase in F_ROH on chromosome 15 was associated with IFL of second-parity cows increasing by 2.3 d. Next, we located the regions within the chromosomes showing inbreeding depression. Our analysis revealed regions near the beginning of chromosome 2 and toward the ends of chromosomes 15, 18, and 22 that were associated with inbreeding depression on IFL. Last, we performed a haplotype analysis for the detected regions. The most promising haplotypes of each region were associated with IFL of heifers increasing by 4.4, 3.2, and 4.1 d on chromosomes 2, 18, and 22, respectively. The haplotype on chromosome 15 associated with IFL of second-parity cows increasing by 7.6 d. Overall, the breeding program requires inbreeding control, as increased genomic inbreeding in our study was associated with reduced reproductive ability in Finnish Ayrshire cattle.     

Use of computerized mate selection programs to control inbreeding of Holstein and Jersey cattle in the next generation

The expected role of computerized mate selection programs with regard to inbreeding and lifetime profitability of Holstein and Jersey cattle was examined using data from 25 large registered herds of each breed. Sire selection and mate allocation were carried out using linear programming with the following objectives: 1) minimum inbreeding, 2) maximum net merit subject to a fixed inbreeding threshold, and 3) maximum expected lifetime profit after adjustment for inbreeding depression. Inbreeding of actual matings was similar to inbreeding from random matings, indicating that current inbreeding avoidance programs in these herds are ineffective. Inbreeding was reduced by 1.6 and 1.9% in Holsteins and Jerseys, respectively, when a mate allocation program was applied with service sires and usage levels fixed at the actual values. Benefits of mate selection programs increased when both sire selection and mate pair allocation were considered. Maximization of mean net merit with inbreeding restricted to a fixed level (5% in Holsteins and 8% in Jerseys) led to decreases in inbreeding of 0.9 and 1.4% and increases in lifetime profit of $16.66 and $26.86 in Holsteins and Jerseys, respectively, relative to programs that ignored inbreeding. Maximization of mean expected lifetime profit after adjustment for inbreeding depression decreased inbreeding by 1.8 and 2.8% and increased lifetime profit by $37.37 and $59.77 in Holsteins and Jerseys, respectively. Inbreeding coefficients estimated with pedigree traced to 1985 were inadequate predictors of inbreeding coefficients estimated with pedigrees traced to 1960. Mate selection programs cannot function optimally unless extensive historical pedigree data are available, particularly for service sires. Computerized mate selection programs can reduce inbreeding in the next generation, which will lead to an increase in farm profitability. However, if genetic diversity is to be maintained in the long term, procedures for selecting parents of AI sires must also be considered.     

Controlling Inbreeding in Modern Breeding Programs

Modern livestock breeding programs feature accurate breeding value estimation and advanced reproductive technology. Such programs lead to rapid genetic progress, but they also lead to the accumulation of inbreeding via heavy impact of a few selected individuals or families. Inbreeding rates are accelerating in most species, and economic losses due to inbreeding depression in production, growth, health, and fertility are a serious concern. Most research has focused on preservation of rare breeds or maintenance of genetic diversity within closed nucleus breeding schemes. However, the apparently large population size of many livestock breeds is misleading, because inbreeding is primarily a function of selection intensity. Strategies for maintaining variation by restricting relationships between selected animals or by artificially increasing the emphasis on within-family information when estimating breeding values have been suggested, and some approaches seem to provide greater long-term responses than BLUP selection. Corrective mating programs are widely used in some species, and these can be modified to consider selection for economic merit adjusted for inbreeding depression. Selection of parents of AI bulls based on optimal genetic contributions to future generations, which are a function of estimated breeding values and genetic relationships between selected individuals, appears most promising. Rapid implementation of such procedures is necessary to avoid further reductions in effective population size. Missing pedigree information is a problem in practice, and the low net present value of future genetic gains makes it difficult for breeding companies to sacrifice short-term economic gains in favor of long-term diversity issues.     

Selection with inbreeding control in simulated young bull schemes for local dairy cattle breeds

Local breeds are rarely subject to modern selection techniques; however, selection programs will be required if local breeds are to remain a viable livelihood option for farmers. Selection in small populations needs to take into account accurate inbreeding control. Optimum contribution selection (OCS) is efficient in controlling inbreeding and maximizes genetic gain. The current paper investigates genetic progress in simulated dairy cattle populations from 500 to 6,000 cows undergoing young bull selection schemes with OCS compared with truncation selection (TS) at an annual inbreeding rate of 0.003. Selection is carried out for a dairy trait with a base heritability of 0.3. A young bull selection scheme was used because of its simplicity in implementation. With TS, annual genetic gain from 0.111 standard deviation units with 500 cows increases rapidly to 0.145 standard deviation units with 4,000 cows. Then, genetic gain increases more slowly up to 6,000 cows. At the same inbreeding rate, OCS produces higher genetic progress than TS. Differences in genetic gain between OCS and TS vary from to 2 to 6.3%. Genetic gain is also improved by increasing the number of years that males can be used as sires of sires. When comparing OCS versus TS at different heritabilities, we observe an advantage of OCS only at high heritability, up to 8% with heritability of 0.9. By increasing the constraint on inbreeding, the difference of genetic gain between the 2 selection methods increases in favor of OCS, and the advantage at the inbreeding rate of 0.001 per generation is 6 times more than at the inbreeding rate of 0.003. Opportunities exist for selection even in dairy cattle populations of a few hundred females. In any case, selection in local breeds will most often require specific investments in infrastructure and manpower, including systems for accurate data recording and selection skills and the presence of artificial insemination and breeders organizations. A cost-benefit analysis is therefore advisable before considering the implementation of selection schemes in local dairy cattle breeds.     

Mating allocations in Nordic Red Dairy Cattle using genomic information

In this study, we compared mating allocations in Nordic Red Dairy Cattle using genomic information. We used linear programming to optimize different economic scores within each herd, considering genetic level, semen cost, the economic impact of recessive genetic defects, and genetic relationships. We selected 9,841 genotyped females born in Denmark, Finland, or Sweden in 2019 for mating allocations. We used 2 different pedigree relationship coefficients, the first tracing the pedigree 3 generations back from the parents of the potential mating and the second based on all available pedigree information. We used 3 different genomic relationship coefficients, 1 SNP-by-SNP genomic relationship and 2 based on shared genomic segments. We found high correlations (≥0.83) between the pedigree and genomic relationship measures. The mating results showed that it was possible to reduce the different genetic relationships between parents with minimal effect on genetic level. Including the cost of known recessive genetic defects eliminated expression of genetic defects. It was possible to reduce genomic relationships between parents with pedigree measures, but it was best done with genomic measures. Linear programming maximized the economic score for all herds studied within seconds, which means that it is suitable for implementation in mating software to be used by advisors and farmers.     

Assessment of inbreeding depression in a Guzerat dairy herd: Effects of individual increase in inbreeding coefficients on production and reproduction

Influences of inbreeding on daily milk yield (DMY), age at first calving (AFC), and calving intervals (CI) were determined on a highly inbred zebu dairy subpopulation of the Guzerat breed. Variance components were estimated using animal models in single-trait analyses. Two approaches were employed to estimate inbreeding depression: using individual increase in inbreeding coefficients or using inbreeding coefficients as possible covariates included in the statistical models. The pedigree file included 9,915 animals, of which 9,055 were inbred, with an average inbreeding coefficient of 15.2%. The maximum inbreeding coefficient observed was 49.45%, and the average inbreeding for the females still in the herd during the analysis was 26.42%. Heritability estimates were 0.27 for DMY and 0.38 for AFC. The genetic variance ratio estimated with the random regression model for CI ranged around 0.10. Increased inbreeding caused poorer performance in DMY, AFC, and CI. However, some of the cows with the highest milk yield were among the highly inbred animals in this subpopulation. Individual increase in inbreeding used as a covariate in the statistical models accounted for inbreeding depression while avoiding overestimation that may result when fitting inbreeding coefficients.     

Genome-wide analysis of runs of homozygosity in Italian Mediterranean buffalo

Runs of homozygosity (ROH) are a powerful tool to explore patterns of genomic inbreeding in animal populations and detect signatures of selection. The present study used ROH analysis to evaluate the genome-wide patterns of homozygosity, inbreeding levels, and distribution of ROH islands using the SNP data sets from 899 Mediterranean buffaloes. A total of 42,433 ROH segments were identified, with an average of 47.20 segments per individual. The ROH comprising mostly shorter segments (1–4 Mb) accounted for approximately 72.29% of all ROH. In contrast, the larger ROH (>8 Mb) class accounted for only 7.97% of all ROH segments. Estimated inbreeding coefficients from ROH (F_ROH) ranged from 0.0201 to 0.0371. Pearson correlations between F_ROH and genomic relationship matrix increased with the increase of ROH length. We identified ROH hotspots in 12 genomic regions, located on chromosomes 1, 2, 3, 5, 17, and 19, harboring a total of 122 genes. Protein-protein interaction (PPI) analysis revealed the clustering of these genes into 7 PPI networks. Many genes located in these regions were associated with different production traits. In addition, 5 ROH islands overlapped with cattle quantitative trait loci that were mainly associated with milk traits. These findings revealed the genome-wide autozygosity patterns and inbreeding levels in Mediterranean buffalo. Our study identified many candidate genes related to production traits that could be used to assist in selective breeding for genetic improvement of buffalo.     

Inbreeding trends and application of optimized selection in the UK Holstein population

Important increases in the rates of inbreeding have recently been observed in dairy cattle populations, and methods have been proposed to address these increases. The aims of this study were to estimate the current level and rates of inbreeding in the UK Holstein population and to investigate the potential of applying optimized selection to manage the rates of inbreeding. Inbreeding coefficients were calculated for the entire UK Holstein population using 1940 as the base year. Rates of inbreeding were obtained for 3 time periods by regressing mean inbreeding coefficients on the year of birth of the animals. The expected average pedigree index and expected inbreeding of offspring using optimized contributions for a given set of selection candidates was compared to the expected pedigree index and inbreeding of offspring for the same set of selection candidates using observed contributions. The rate of inbreeding in the UK Holstein population has increased substantially since 1990 when compared to previous time periods. This increase is most likely due to the large influence of a few related sires on the breed in the mid- to late 1980s. The introduction of the individual animal model in the early 1990s may also have contributed to increased inbreeding. Optimized selection appears to represent a promising selection tool, not only to manage rates of inbreeding, but also to increase genetic gain at the same rate of inbreeding.