Modeling missing pedigree in single-step genomic BLUP

The objective was to compare methods of modeling missing pedigree in single-step genomic BLUP (ssGBLUP). Options for modeling missing pedigree included ignoring the missing pedigree, unknown parent groups (UPG) based on A (the numerator relationship matrix) or H (the unified pedigree and genomic relationship matrix), and metafounders. The assumptions for the distribution of estimated breeding values changed with the different models. We simulated data with heritabilities of 0.3 and 0.1 for dairy cattle populations that had more missing pedigrees for animals of lesser genetic merit. Predictions for the youngest generation and UPG solutions were compared with the true values for validation. For both traits, ssGBLUP with metafounders provided accurate and unbiased predictions for young animals while also appropriately accounting for genetic trend. Accuracy was least and bias was greatest for ssGBLUP with UPG for H for the trait with heritability of 0.3 and with UPG for A for the trait with heritability of 0.1. For the trait with heritability of 0.1 and UPG for H, the UPG accuracy (SD) was ?0.49 (0.12), suggesting poor estimates of genetic trend despite having little bias for validations on young, genotyped animals. Problems with UPG estimates were likely caused by the lesser amount of information available for the lower heritability trait. Hence, UPG need to be defined differently based on the trait and amount of information. More research is needed to investigate accounting for UPG in A₂₂ to better account for missing pedigrees for genotyped animals.     

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.     

Udder health shows inbreeding depression in Danish Holsteins

The purpose of this study was to estimate inbreeding depression for udder health using records on mastitis incidence and somatic cell count (SCC). Data were selected based on a pedigree completeness index so that inbreeding coefficients were reliable. Average inbreeding was 3.3%. The presence or absence of mastitis was considered in first (CM1), second (CM2), and third (CM3) lactations, and was recorded as a binary trait. Somatic cell count was also included and analyzed on the log scale. A minimum of 140,000 cows with records were included per trait. Linear sire models were used and (co)variance components were estimated. Linear and curvilinear effects of the coefficient of inbreeding were included. Inbreeding significantly affected all traits investigated. Three traits, CM1, CM3, and SCC, showed a nonlinear relationship between phenotype and inbreeding coefficient. A cow with 5% inbreeding compared with a cow with 2% inbreeding had a higher SCC and a higher incidence of mastitis. The SCC increased by 1,500 cells/mL in first lactation and the incidence of mastitis increased by 1.08, 0.55, and 0.98% in first, second, and third lactation, respectively. The corresponding reduction in net return from these traits over 3 lactations amounted to US$11.00 under Danish production circumstances. These results are a step on the way to estimating the total cost of inbreeding depression to determine an acceptable rate of inbreeding.     

Bimodality and the genetics of milk flow traits in the Italian Holstein-Friesian breed

The overall goal of this study was to investigate milk flow traits in Italian Holstein-Friesian cows and, in particular, the bimodality of milk flow, defined as delayed milk ejection at the start of milking. Using a milkometer, 2,886 records were collected from 133 herds in northern Italy from 2001 to 2007. All records included 5 time-period measurements for milk flow, somatic cell score (SCS), milk yield, 8 udder type traits, and the presence or absence of bimodality in milk flow. Genetic parameters were estimated using linear animal models for continuous traits such as milk flow, udder type, SCS, and milk production, whereas bimodality was analyzed as a categorical trait. With the exception of decreasing time (which had a very small heritability value of 0.06), heritability values for milk flow traits were moderate, ranging from 0.10 (ascending time) to 0.41 (maximum milk flow). In addition, moderate to high genetic correlations were estimated between total milking time and other time measures (from 0.78 to 0.87), and among time flow traits (from 0.62 to 0.91). The decreasing time was the trait most genetically correlated with udder type traits, with correlation values of 0.92 with rear udder height, 0.85 with rear udder width, and 0.73 with teat placement. Large udders with strong attachments were also associated with greater milk production. Heritability estimated for bimodality was 0.43, and its genetic correlation with milk flow traits and SCS indicated a sizable genetic component underlying this trait. Bimodality was negatively associated with milk production; shorter milking times and greater peak milk levels were genetically correlated with more frequent bimodal flows, indicating that faster milk release would result in an increase in bimodal patterns. The negative genetic correlation of bimodality with SCS (−0.30) and the genetic correlation between milk flow traits and SCS suggest that the relationship between milkability and SCS is probably nonlinear and that intermediate flow rates are optimal with respect to mastitis susceptibility. Quicker milk flow over a shorter period would increase the frequency of bimodal curves in milking, whereas the correlation between bimodality and both ascending and descending time was less clear.     

Durability of Traits: Nonlinear Association between Initial and Subsequent Measures

Subjective linearized scores were recorded for milking speed, fore udder smoothness, shoulder looseness, and udder depth on 7357 and 3730 Holstein cows during first and second lactations. Random sire effects in threshold models were estimated for each trait and lactation. There were 95 sires that had estimated effects for all the traits in both lactations. For each trait, sire effects for first and second lactations were used as independent and dependent variables, respectively, in quadratic regression. Sire effects corresponding to milking speed in second lactation had linear relationship to sire effects corresponding to milking speed in first lactation. Similar relationships for udder smoothness, shoulder looseness, and udder depth appeared nonlinear. The quadratic terms associated with prediction equations for shoulder looseness and udder depth were significant. Nonlinear associations between genetic evaluations in first and second lactations may have resulted from aging.     

Genomic selection in the French Lacaune dairy sheep breed

Genomic selection aims to increase accuracy and to decrease generation intervals, thus increasing genetic gains in animal breeding. Using real data of the French Lacaune dairy sheep breed, the purpose of this study was to compare the observed accuracies of genomic estimated breeding values using different models (infinitesimal only, markers only, and joint estimation of infinitesimal and marker effects) and methods [BLUP, Bayes Cπ, partial least squares (PLS), and sparse PLS]. The training data set included results of progeny tests of 1,886 rams born from 1998 to 2006, whereas the validation set had results of 681 rams born in 2007 and 2008. The 3 lactation traits studied (milk yield, fat content, and somatic cell scores) had heritabilities varying from 0.14 to 0.41. The inclusion of molecular information, as compared with traditional schemes, increased accuracies of estimated breeding values of young males at birth from 18 up to 25%, according to the trait. Accuracies of genomic methods varied from 0.4 to 0.6, according to the traits, with minor differences among genomic approaches. In Bayes Cπ, the joint estimation of marker and infinitesimal effects had a slightly favorable effect on the accuracies of genomic estimated breeding values, and were especially beneficial for somatic cell counts, the less heritable trait. Inclusion of infinitesimal effects also improved slopes of predictive regression equations. Methods that select markers implicitly (Bayes Cπ and sparse PLS) were advantageous for some models and traits, and are of interest for further quantitative trait loci studies.     

Feasibility of a linear scoring method of udder morphology for the selection scheme of Sardinian sheep

Breeders are increasingly interested in improving the machine milkability of Sardinian dairy sheep by selection for udder morphology. Nine-point linear scales were developed to appraise teat placement, degree of suspension of the udder, udder depth, and degree of separation of the 2 halves. Repeatabilities within and across lactation were estimated on an experimental flock. Ewes were scored at least 3 times a year from 1999 to 2003. Within-lactation repeatabilities were greater than 0.70 for all linear traits, whereas across-lactation repeatabilities ranged from 0.59 to 0.66. The first linear combination of basic traits, obtained by principal component analysis, was highly correlated with teat placement, degree of suspension of the udder, and udder depth and showed an across-lactation repeatability of 0.76. These results indicate that an accurate evaluation of animals is possible by a single, early lifetime score. Genetic parameters of linear udder traits were estimated using a REML method applied to a sire model. Data were selected from 76,984 scores of Sardinian yearling ewes collected by 31 classifiers from 1999 to 2004. Two models were compared, one fitting the contemporary group effect as fixed and the other as random. Heritabilities of udder traits ranged from 0.19 to 0.31. The model with the random contemporary group effect produced slightly higher heritabilities and higher correlations between the sires’ estimated breeding values and the daughters’ average scores. As a whole, the genetic correlations between udder traits were favorable, indicating that selection for one trait will produce a positive evolution of the overall udder conformation. In particular, the degree of suspension of the udder was highly correlated with udder depth (0.82). Genetic correlations with milk yield were unfavorable but generally low, with the exception of udder depth (−0.48). Genetic trends were estimated using an animal model. Only udder depth showed a negative constant genetic trend. Overall results indicated that genetic improvement of the udder morphology of Sardinian ewes is feasible, with major emphasis on teat placement and degree of udder suspension, traits showing the highest heritabilities and low unfavorable genetic correlations with milk yield.     

Whole genome scan to detect chromosomal regions affecting multiple traits in dairy cattle

Chromosomal regions affecting multiple traits (multiple trait quantitative trait regions or MQR) in dairy cattle were detected using a method based on results from single trait analyses to detect quantitative trait loci (QTL). The covariance between contrasts for different traits in single trait regression analysis was computed. A chromosomal region was considered an MQR when the observed covariance between contrasts deviated from the expected covariance under the null hypothesis of no pleiotropy or close linkage. The expected covariance and the confidence interval for the expected covariance were determined by permutation of the data. Four categories of traits were analyzed: production (5 traits), udder conformation (6 traits), udder health (2 traits), and fertility (2 traits). The analysis of a granddaughter design involving 833 sons of 20 grandsires resulted in 59 MQR (alpha = 0.01, chromosomewise). Fifteen MQR were found on Bos taurus autosome (BTA) 14. Four or more MQR were found on BTA 6, 13, 19, 22, 23, and 25. Eight MQR involving udder conformation and udder health and 4 MQR involving production traits and udder health were found. Five MQR were identified for combinations of fertility and udder conformation traits, and another 5 MQR were identified for combinations of fertility and production traits. For 22 MQR, the difference between the correlation attributable to the MQR and the overall genetic correlation was >0.60. Although the false discovery rate was relatively high (0.52), it was considered important to present these results to assess potential consequences of using these MQR for marker-assisted selection.     

Genetic and genomic analysis of hyperthelia in Brown Swiss cattle

Supernumerary teats (SNT) are any abnormal teats found on a calf in addition to the usual and functional 4 teats. The presence of SNT has also been termed “hyperthelia” since the end of the 19th century. Supernumerary teats can act as an incubator for bacteria, infecting the whole udder, and can interfere with the positioning of the milking machine, and consequently, have economic relevance. Different types of SNT are observed at different positions on the udder. Caudal teats are in the rear, ramal teats are attached to another teat, and intercalary teats are found between 2 regular teats. Not all teats are equally developed; some are completely functional but most are rudimentary and not attached to any mammary gland tissue. Recently, different studies showed the poly/oligogenic character of these malformations in cattle as well as in other mammalian species. The objective of this study was to analyze the genetic architecture and incidence of hyperthelia in Swiss Brown Swiss cattle using both traditional genetic evaluation as well as imputed whole genome sequence variant information. First, phenotypes collected over the last 20 yr were used together with pedigree information for estimation of genetic variance. Second, breeding values of Brown Swiss bulls were estimated applying the BLUP algorithm. The BLUP-EBV were deregressed and used as phenotypes in genome-wide association studies. The gene LGR5 on chromosome 5 was identified as a candidate for the presence of SNT. Using alternative trait coding, genomic regions on chromosome 17 and 20 were also identified as being involved in the development of SNT with their own supernumerary mammary gland tissue. Implementing knowledge gained in this study as a routine application allows a more accurate evaluation of the trait and reduction of SNT prevalence in the Swiss Brown Swiss cattle population.     

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.     

Analysis of the relationship between type traits, inbreeding, and functional survival in Jersey cattle using a Weibull proportional hazards model

A Weibull proportional hazards model was used to analyze the effects of 13 linear type traits, final score, and inbreeding on the functional survival of 268,008 US Jersey cows in 2416 herds with first calving from 1981 to 2000. Functional survival was defined as the number of days from first calving until involuntary culling or censoring. The statistical model included the time-dependent effects of herd-year-season of calving, parity by stage of lactation interaction, and within-herd-year quintile for mature equivalent milk yield, as well as the time-independent effects of inbreeding, age at first calving, and linear type traits or final score (analyzed one at a time). Each type trait was divided into 10 classes, and the relative risk of involuntary culling was calculated for animals in each class after accounting for the aforementioned management factors. Type traits with the greatest contribution to the likelihood function were udder depth, fore udder attachment, front teat placement, and udder support. Cows with low scores for these traits had a risk of culling that was 1.3 to 1.8 times that of cows with intermediate scores. Cows with high scores for udder depth and udder support had a risk of culling only 0.7 to 0.85 as great as that of cows with intermediate scores. Intermediate scores were desirable for rear leg set, dairy form, and strength, but stature, rump angle, and rump width had negligible effects on survival. Cows with low final scores had a risk of culling that was 1.35 times that of cows with intermediate scores, whereas cows with high final scores had a risk of culling that was 0.8 times that of cows with intermediate scores. Animals with inbreeding coefficients greater than 10% had a slightly higher risk of culling than animals with inbreeding coefficients less than 5%.     

Genetic correlations among production, body size, udder, and productive life traits over time in Holsteins

Genetic correlations among milk, fat, and protein yields; body size composite (BSC); udder composite (UDC); and productive life (PL) in Holsteins were investigated over time. The data set contained 25,280 records of cows born in Wisconsin between 1979 and 1993. The multiple trait random regression (MT-RR) animal model included registration status, herd-year, age group, and stage of lactation as fixed effects; additive genetic effects with random regressions (RR) on year of birth using the first-order Legendre polynomial; and residual effects. Heterogeneous residual variances were considered in the model. Estimates of variance components and genetic correlations among traits from MT-RR were compared with those estimated with a multiple trait interval (MT-I) model, which assumed that every 3-yr interval was a separate trait and included the same effects as in the MT-RR model except for the RR. Genetic correlations estimated with MT-RR and MT-I models over time among all traits were compared with correlations among breeding values predicted with the single trait (ST) model without RR. Correlations among breeding values predicted with MT-RR, ST, and MT models were also calculated. Additive genetic and residual variances for all traits except PL increased over time; those for PL were constant. As a result, heritability estimates had no significant changes during the 15 yr. Genetic correlations of PL with milk, fat, protein, and BSC declined to zero or negative; those with UDC remained positive. Correlations among breeding values predicted with ST, MT, and MT-RR models were relatively high for all traits except PL. Genetic correlations between PL and other traits varied over time, with some correlations changing sign. For accurate indirect prediction of PL from other traits, the genetic correlations among the traits need to be re-estimated periodically.     

Marker-assisted selection can reduce true as well as pedigree-estimated inbreeding

This study investigated whether selection using genotype information reduced the rate and level of true inbreeding, that is, identity by descent, at a selectively neutral locus as well as a locus under selection compared with traditional BLUP selection. In addition, the founder representation at these loci and the within-family selection at the nonneutral locus were studied. The study was carried out using stochastic simulation of a population resembling the breeding nucleus of a dairy cattle population for 25 yr. Each year, 10 proven bulls were selected across herds along with 100 dams from within each of 40 herds. Selection was performed using BLUP, marker-assisted, or gene-assisted selection for a trait with low heritability (h² = 0.04) only expressed in females, mimicking a health trait. The simulated genome consisted of 2 chromosomes. One biallelic quantitative trait loci (QTL) with an initial frequency of the favorable allele of 0.1, and initially explaining 25% of the genetic variance as well as 4 markers were simulated in linkage disequilibrium, all positioned at chromosome 1. Chromosome 2 was selectively neutral, and consisted of a single neutral locus. The results showed that in addition to reducing pedigree-estimated inbreeding, the incorporation of genotype information in the selection criteria also reduced the level and rate of true inbreeding. In general, true inbreeding in the QTL was greater than pedigree-estimated inbreeding with respect to both the level and rate of inbreeding, as expected. Also as expected, true and pedigree-estimated inbreeding in the neutral locus were the same. Furthermore, after 25 yr, or approximately 5 generations, the pedigree-estimated level of inbreeding was reduced by 11 and 24% compared with BLUP in gene- and marker-assisted selection, respectively, and the level of true inbreeding in the QTL was reduced by 22 and 13%, respectively. The difference between selection scenarios was found to be caused by a larger number of founders being represented at the QTL when using genotype information in the selection criteria. This in turn was caused by an increased selection of individuals sharing the favorable QTL allele rather than individuals sharing genes on average, which was shown by a higher Mendelian selection differential in the QTL. Hence, even though the selection pressure was increased at the QTL, more variation was retained. The results suggest that marker-assisted selection is a useful selection strategy.     

Hot topic: Effect of breeding strategies using genomic information on fitness and health

A complex deterministic approach was used to model the breeding goal and breeding structure for the Austrian Fleckvieh (dual-purpose Simmental) breed. The reference breeding goal corresponded to the current total merit index (TMI-R), where dairy traits have a relative weight of 37.9% and fitness traits of 43.7% (beef traits 16.5%; milkability 2%). The breeding program was characterized by 280,000 cows under performance recording, 3,200 bull dams, 100 test bulls with a test capacity of 25%, and 15 proven bulls and 8 bull sires per year. The annual monetary genetic gain (AMGG) was generated mainly by increases in milk fat and milk protein yield (80.6%) and only to a small extent by fitness traits (6.6%). The inclusion of direct health traits (early reproductive disorders, cystic ovaries, and mastitis) with their economic weights increased the relative AMGG for fitness traits from 6.6 to 11.2%. The presently slightly negative AMGG for fertility index and udder health changed in a positive direction. Increasing the weight on the direct health traits by 50% resulted in a further shift toward fitness and health. The effect of strategies using genomic information in a total merit index (TMI) with varying weights on fitness and health traits was also analyzed. The conventional progeny-testing scheme was defined as the reference breeding program. A breeding program was considered to be genomically enhanced (GS50) when 50% of inseminations of herdbook cows and of bull dams were from young bulls with a genomic TMI, and a second program (GS100) did not rely on progeny-tested bulls at all. For GS50, a clear shift of the relative gain in AMGG toward fitness and health traits was observed for all 3 TMI scenarios, as a result of larger progeny groups and a shorter generation interval. For GS100, where no gene flow from progeny-tested bulls was assumed, the genetic gain per generation was lower for the fertility and udder health index but higher per year. The results based on natural genetic gain per year showed that no positive genetic response for fertility and udder health index were achieved for TMI-R (without the inclusion of direct health traits) in GS50 and GS100. The direction of the genetic trend was determined by the weights given to fertility and udder health indices within the TMI. When appropriate weights generated a clear positive trend, GS50 and GS100 reinforced this trend.     

Accuracy of genomic evaluation with weighted single-step genomic best linear unbiased prediction for milk production traits,udder type traits,and somatic cell scores in French dairy goats

Genomic evaluation of French dairy goats is routinely conducted using the single-step genomic BLUP (ssGBLUP) method. This method has the advantage of simultaneously using all phenotypes, pedigrees, and genotypes. However, ssGBLUP assumes that all SNP explain the same amount of genetic variance, which is unlikely in the case of traits whose major genes or QTL are segregating. In this study, we investigated the effect of weighted ssGBLUP and its alternatives, which give more weight to SNP associated with the trait, on the accuracy of genomic evaluation of milk production, udder type traits, and somatic cell scores. The data set included 2,955 genotyped animals and 2,543,680 pedigree animals. The number of phenotypes varied with the trait. The accuracy of genomic evaluation was assessed on 205 genotyped Alpine and 146 genotyped Saanen goats born between 2009 and 2012. For traits with unknown QTL, weighted ssGBLUP was less accurate than, or as accurate as, ssGBLUP. For traits with identified QTL (i.e., QTL only present in the Saanen breed), weighted ssGBLUP outperformed ssGBLUP by between 2 and 14%.     

Genotyping strategies for maximizing genomic information in evaluations of the Latxa dairy sheep breed

Genomic selection has been implemented over the years in several livestock species, due to the achievable higher genetic progress. The use of genomic information in evaluations provides better prediction accuracy than do pedigree-based evaluations, and the makeup of the genotyped population is a decisive point. The aim of this work is to compare the effect of different genotyping strategies (number and type of animals) on the prediction accuracy for dairy sheep Latxa breeds. A simulation study was designed based on the real data structure of each population, and the phenotypic and genotypic data obtained were used in genetic (BLUP) and genomic (single-step genomic BLUP) evaluations of different genotyping strategies. The genotyping of males was beneficial when they were genetically connected individuals and if they had daughters with phenotypic records. Genotyping females with their own lactation records increased prediction accuracy, and the connection level has less relevance. The differences in genotyping females were independent of their estimated breeding value. The combined genotyping of males and females provided intermediate accuracy results regardless of the female selection strategy. Therefore, assuming that genotyping rams is interesting, the incorporation of genotyped females would be beneficial and worthwhile. The benefits of genotyping individuals from various generations were highlighted, although it was also possible to gain prediction accuracy when historic individuals were not considered. Greater genotyped population sizes resulted in more accuracy, even if the increase seems to reach a plateau.     

Bias in genomic predictions by mating practices for linear type traits in a large-scale genomic evaluation

The objective of this study was to clarify how bias in genomic predictions is created by investigating a relationship among selection intensity, a change in heritability (Δh²), and assortative mating (ASM). A change in heritability, resulting from selection, reflects the impact that the Bulmer effect has on the reduction in between-family variation, whereas assortative mating impacts the within-family variance or Mendelian sampling variation. A partial data set up to 2014, including 841K genotyped animals, was used to calculate genomic predictions with a single-step genomic model for 18 linear type traits in US Holsteins. A full data set up to 2018, including 2.3 million genotyped animals, was used to calculate benchmark genomic predictions. Inbreeding and unknown parent groups for missing parents of animals were included in the model. Genomic evaluation was performed using 2 different genetic parameters: those estimated 14 yr ago, which have been used in the national genetic evaluation for linear type traits in the United States, and those newly estimated with recent records from 2015 to 2018 and those corresponding pedigrees. Genetic trends for 18 type traits were estimated for bulls with daughters and cows with phenotypes in 2018. Based on selection intensity and mating decisions, these traits can be categorized into 3 groups: (a) high directional selection, (b) moderate selection, and (c) intermediate optimum selection. The first 2 categories can be explained by positive assortative mating, and the last can be explained by negative assortative or disassortative mating. Genetic progress was defined by genetic gain per year based on average standardized genomic predictions for cows from 2000 to 2014. Traits with more genetic progress tended to have more “inflated” genomic predictions (i.e., “inflation” means here that genomic predictions are larger in absolute values than expected, whereas “deflation” means smaller than expected). Heritability estimates for 14 out of 18 traits declined in the last 16 yr, and Δh² ranged from ?0.09 to 0.04. Traits with a greater decline in heritability tended to have more deflated genomic predictions. Biases (inflation or deflation) in genomic predictions were not improved by using the latest genetic parameters, implying that bias in genomic predictions due to preselection was not substantial for a large-scale genomic evaluation. Moreover, the strong selection intensity was not fully responsible for bias in genomic predictions. The directional selection can decrease heritability; however, positive assortative mating, which was strongly associated with large genetic gains, could minimize the decline in heritability for a trait under strong selection and could affect bias in genomic predictions.     

Genetic parameters for clinical mastitis, somatic cell score, and production in the first three lactations of Swedish holstein cows

Using a mixed linear animal model, genetic parameters were estimated for clinical mastitis (MAST), lactation average somatic cell score (LSCS), and milk production traits in the first 3 lactations of more than 200,000 Swedish Holstein cows with first calving from 1995 to 2000. Heritability estimates for MAST (0.01 to 0.03) were distinctly lower than those for LSCS (0.10 to 0.14) and production traits (0.23 to 0.36). The genetic correlation between MAST and LSCS was high for all lactations (mean 0.70), implying that selection for low LSCS will reduce the incidence of mastitis. Undesirable genetic relationships with production were found for both MAST and LSCS with genetic correlations ranging from 0.01 to 0.45. This emphasizes the need for including udder health traits in the breeding goal. Genetic correlations across lactations for the same trait were positive and high for both MAST (>0.7), LSCS (>0.8), and production traits (>0.9), with the strongest correlations between second and third parity for all traits (>0.9 for udder health traits and close to unity for production traits).     

Comparison of genomic predictions for lowly heritable traits using multi-step and single-step genomic best linear unbiased predictor in Holstein cattle

The success and sustainability of a breeding program incorporating genomic information is largely dependent on the accuracy of predictions. For low heritability traits, large training populations are required to achieve high accuracies of genomic estimated breeding values (GEBV). By including genotyped and nongenotyped animals simultaneously in the evaluation, the single-step genomic BLUP (ssGBLUP) approach has the potential to deliver more accurate and less biased genomic evaluations. The aim of this study was to compare the accuracy and bias of genomic predictions for various traits in Canadian Holstein cattle using ssGBLUP and multi-step genomic BLUP (msGBLUP) under different strategies, such as (1) adding genomic information of cows in the analysis, (2) testing different adjustments of the genomic relationship matrix, and (3) using a blending approach to obtain GEBV from msGBLUP. The following genomic predictions were evaluated regarding accuracy and bias: (1) GEBV estimated by ssGBLUP; (2) direct genomic value estimated by msGBLUP with polygenic effects of 5 and 20%; and (3) GEBV calculated by a blending approach of direct genomic value with estimated breeding values using polygenic effects of 5 and 20%. The effect of adding genomic information of cows in the evaluation was also assessed for each approach. When genomic information was included in the analyses, the average improvement in observed reliability of predictions was observed to be 7 and 13 percentage points for reproductive and workability traits, respectively, compared with traditional BLUP. Absolute deviation from 1 of the regression coefficient of the linear regression of de-regressed estimated breeding values on genomic predictions went from 0.19 when using traditional BLUP to 0.22 when using the msGBLUP method, and to 0.14 when using the ssGBLUP method. The use of polygenic weight of 20% in the msGBLUP slightly improved the reliability of predictions, while reducing the bias. A similar trend was observed when a blending approach was used. Adding genomic information of cows increased reliabilities, while decreasing bias of genomic predictions when using the ssGBLUP method. Differences between using a training population with cows and bulls or with only bulls for the msGBLUP method were small, likely due to the small number of cows included in the analysis. Predictions for lowly heritable traits benefit greatly from genomic information, especially when all phenotypes, pedigrees, and genotypes are used in a single-step approach.