Sire Evaluation Research Articles

Sire Evaluation Considering First Lactation Yield for Improvement of Life Time Production in Sahiwal and Crossbred Cattle

Sire Evaluation Considering First Lactation Yield for Improvement of Life Time Production in Sahiwal and Crossbred Cattle

Genetic evaluation of the functional productive life in Slovak Simmental cattle

Abstract. Genetic evaluation of sires based on length of functional productive life of their daughters was carried out using a Weibull proportional hazard sire-maternal grandsire model. The data consisted of 214634 registered Slovak Simmental cows with censoring of 21.34%. Besides the random sire and maternal grandsire effects, the model included time dependent effects parity × stage of lactation interaction, within-herd standard deviations of milk production, herd × year × season interaction, change of herd size with respect to the previous year, and time independent effect age at first calving. Within-herd, the standard deviations of milk production had the most important influence on functional productive life. The highest risk of culling was found in cows with the lowest milk production class (uncompleted lactation). Risk of culling decreased with an increasing milk production class. Estimated heritability of functional productive life was 0.05 on the original scale. Breeding values of sires expressed as a risk ratio of their daughters were between −0.57 and 0.53.

Genetic evaluation for longevity of Croatian Simmental bulls using a piecewise Weibull model

Abstract. Genetic evaluation of sires for functional longevity was conducted using survival analysis techniques. The data set consisted of 49 659 Simmental cows with first calving from 1997 to 2008. A piecewise Weibull sire model was used to estimate breeding values of 251 bulls for functional length of productive life of their daughters. The model was stratified by parity i.e. a separate baseline hazard was computed for each stratum. Besides the random sire effect, the model included the fixed time independent effects of age at first calving, herd size and region as well as the time dependent effects of relative milk production and year*season of first calving. The highest impact on longevity was found for relative milk production. Cows with the lowest milk yields were at approximately 2.7 times higher risk of culling compared to cows with average milk production. Effects of age at first calving, herd size and country region had lower impact on longevity. Sire variance was 0.023 which results in a heritability of 0.06 for functional length of productive life. The average approximate reliability of estimated breeding values was 0.49. Genetic trend showed no clear tendency by year of birth of bulls.

Development of a genetic evaluation for body condition score for Canadian Holsteins

Valacta (Sainte-Anne-de-Bellevue, Québec, Canada) is the Canadian Dairy Herd Improvement organization responsible for milk recording in Québec and Atlantic provinces. Up to 14 first-lactation body condition score (BCS) records were collected per cow (average of 2.5 records per cow), allowing the trait to be described by a random regression animal model so that animals could be ranked by the shape of their BCS curve. However, Valacta’s BCS are available from Québec herds only and the long-term objective of this research is to develop a nationwide genetic evaluation of sires and cows for BCS. Alternatively, Holstein Canada (Brantford, Ontario, Canada) collects type trait records nationwide, primarily for first-lactation cows. Holstein Canada typically collects a single record per trait, so that selection for Holstein Canada BCS would be based on overall BCS level rather than the shape of the BCS curve. Several different methods of genetically evaluating Valacta’s BCS were investigated, including consideration of average BCS level across lactation, the amount of fluctuation in the BCS curve during lactation, and combinations of BCS level and BCS fluctuation. Sires with ≥25 daughters were compared (as opposed to comparing cows) because their BCS estimated breeding values (EBV) are based on more information, and so should be more reliable. Of the different methods of calculating Valacta BCS EBV, ranking bulls based on overall BCS level gave the best results in that their daughter phenotypic BCS curves showed limited loss in early lactation BCS and replenished condition by the end of lactation. Whereas Valacta’s BCS were analyzed using a random regression animal model, Holstein Canada only needs to collect 1 BCS record per cow at classification and the resulting BCS EBV was strongly correlated with Valacta’s BCS EBV. Furthermore, because Holstein Canada’s BCS are collected nationally and Valacta’s BCS are not, a national genetic evaluation for Holstein Canada’s BCS is more convenient. The results of this study do not eliminate the possibility of a genetic evaluation of BCS as a longitudinal trait, but indicate that other methods of calculating Valacta BCS EBV should be explored. Until that time, genetically evaluating Holstein Canada’s BCS is simple, easily implemented, and may be effective in altering the level and shape of the genetic BCS curve.

Sire evaluation of milk producers’ co-operative union limited of Bangladesh

Data on 3637 cows of seven genetic groups at Baghabarighat milk shed area, from 1991 to 2000 were analyzed. The genetic groups were Pabna Milking (PM) cows, ½PM×½ Sahiwal (PM×SL), ½PM×½Frisian (PM×FN), Australian Friesian Sahiwal (AFS), ½Sahiwal×¼PM×¼ Friesian [SL(PM×FN)], ½Friesian ×¼PM×¼Sahiwal [FN(PM×SL)] and ½Friesian×¼Sahiwal×¼ Jersey [FN(SL×JR)]. The purpose of this study was to predict breeding values (PBV) of dairy sires using individual daughters performance (birth weight, lactation yield, fat% and SNF%) records at Baghabarighat milk shed area. The heritability values were estimated as 0.27±0.05 for birth weight, 0.45±0.03 for lactation yield, 0.37±0.04 for fat% and 0.46±0.01 for SNF%. The high genetic variability of birth weight, lactation yield, fat and SNF% indicates that there is a great opportunity or genetic improvement when these traits are included in a selection scheme. The first 3 top sires were 24, 14 and 20 for birth weight; sire number 19, 36 and 23 for lactation yield; sire number 16, 11 and 26 for fat % and sire number 14, 19 and 16 for SNF% were ranked on the basis of PBV.DOI: http://dx.doi.org/10.3329/bjas.v41i2.14104Bang. J. Anim. Sci. 2012. 41 (2): 74-78

Sire evaluation based on predicted first lactation 305-day milk yield using monthly test day milk yield values of Karan Fries cattle

The present investigation was carried out using data of first lactation monthly (MTDY) test day milk yield records of 1345 Karan Fries cows sired by 84 bulls from 1984–2006 maintained at the NDRI, Karnal. The breeding values of Karan Fries sires were estimated for predicted first lactation 305-day by step-wise backward multiple regression using monthly test day milk yields. The breeding values were estimated by 4 methods, viz. least squares method (LSQ), simple regressed least squares method (SRLS), contemporary comparison method (CC) and best linear unbiased prediction (BLUP). The effectiveness of LSQ, SRLS and BLUP methods of sire evaluation was compared on the basis of rank correlations, error variance, coefficients of determination (R2) and coefficients of variation (CV). The rank correlation for LSQ with SRLS (0.92–0.99) was highest followed by LSQ with BLUP (0.89–0.91) and SRLS with BLUP (0.81– 0.91) which were very close. The lowest rank correlation was observed in LSQ with CC (0.10–0.16) and SRLS with CC (0.10–0.17). It was observed that all the rank correlations between CC with BLUP were negative. The relative efficiency of LSQ and SRLS in comparison with BLUP was more than 95%. The coefficient of determination (R2) for LSQ and SRLS was nearly equal (16.30% to 17.58%) and BLUP had lower R2 (13.10% to 14.75%) than LSQ and SRLS. The narrow range of coefficient of variation (CV) for LSQ, SRLS and BLUP (23.5% to 24.5%) and small deviation from CV of unadjusted data (25.35%) indicated that all the 3 methods were almost equally stable. The BLUP method which had lower error variance was found to be more efficient than the LSQ and SRLS methods using the 305-day milk yield predicted by regression equation considering fourth, sixth and ninth MTDYs.

10 TRACEABILITY SYSTEM FOR AN INDIVIDUAL FROZEN SEMEN STRAW BY A TINY RADIO FREQUENCY IDENTIFICATION CHIP

A traceability of frozen semen straws that certify the bloodline of a sire will improve the efficiency of cattle breeding. Semen of the sire can be generally identified by the colour of a straw and printing on a straw. However, it is difficult to identify individual frozen semen straws by the conventional method. To identify straws individually, each straw must be tagged with a unique ID that is able to be read quickly in the frozen state. We have established the identification method for individual frozen semen straws using radio frequency identification (RFID) and developed a traceability system that is able to record the distribution history of an individual semen straw from the production of frozen semen to artificial insemination (AI). We used a 2.5-mm diameter straw combined with an RFID tag, which consisted of a tiny RFID chip (μ-Chip: Hitachi Co. Ltd, 0.4 × 0.4 × 0.2 mm) and a thin aluminum antenna on the polyester sheet (54 × 1.5 × 0.05 mm). The μ-chip contains a unique ID (128 bit). It responds to the 2.45 GHz microwave frequency that is emitted from the RFID reader and transmits its ID to the RFID reader. The μ-Chip retains its function on a straw, which has been stored in the liquid nitrogen (–196°C). Artificial insemination of the frozen semen straw with the RFID tag could be performed using a conventional AI gun. The semen traceability system consisted of the database server and the client software. Information about semen straws is connected with their ID and stored on the database server. Producers and distributors of frozen semen can count the number of semen straws correctly by reading their ID one by one and can send information to the database server through the web by easy operation using the client software. Artificial insemination information can be instantly recorded by the handy terminal that is able to read both a bar-code on the ear tag of the cow and the RFID tag of the straw. The system has been used on fields at Gifu Prefecture in Japan for ∼3 months. Eight hundred thirty-one frozen semen straws with the RFID tag were produced from 3 bulls. After freezing of the straws, 17 straws were not identified with their ID. It was speculated that their μ-Chips were disconnected from the antenna during freezing. Six hundred ninety-four straws were distributed to the 7 AI centers. Five hundred thirty straws were used for AI by 15 inseminators to a total of 424 cows at the 101 farms. Although only one straw could not read its ID after AI, information of the remaining 529 straws were recorded on the database accurately. A strict traceability of frozen semen straws can be established using the individual identification of straws by RFID. Information stored in the database would be useful for the evaluation of sire and the reproductive management of cows. This work was supported by a grant from the Ministry of Agriculture, Forestry and Fisheries of Japan (MAFF).

Estimation Of Genetic And Phenotypic Parameters Of Certain Egg Quality Traits In Quails

The present study was used at the poultry farm on quail flock (Coturnix Japonica), (78 family).The objective of this study was to estimate the genetic and phenotypic parameters (heritability, genetic and phenotypic correlations) depending on qualitative Traits of eggs (egg weight, yolk weight, albumin weight, yolk diameter, yolk to albumin ratio), and to study the effect of season and hatch effects. The study also included genetic evaluation of certain sires according to progeny data. Results obtained can be summarized as: The overall means of the qualitative traits of eggs were 8.95 (g),21.07 (ml) , 3.14 (g) , 4.08 (g) ,0.69 for egg weight, yolk and albumen diameter, yolk and albumen weight, yolk to albumin ratio respectively. Highly significant (p≤ 0.05) effects of season on egg quality traits, and the study showed no significant of hatch factor on all studied traits. Heritability of egg quality traits for the three months were for yolk weight ,yolk diameter and albumen weight, yolk to albumen ratio respectively,(0.19,0.19 ,0.18 ), (0.21,0.22,0.20),(0.13,0.15,0.19),(0.19,0.17,0.22).The genetic and phenotypic correlation among different studied traits were highly significant .The highest value was (0.82),(0.94) between egg weight and albumen weight, egg weight and yolk diameter for third month, and (-0.58) or (-0.56) between yolk to albumen ratio with albumen weight for first month, and the least values was (0.01) between egg weight for second month and egg mass for first month. Wide range of breeding values for certain traits was observed indicate the presence of additive genetic variance that could be used in selection programs. The estimated values of genetic and phenotypic correlation among egg quality traits highly significant of third month compared with first and second months.

Principal component and factor analytic models in international sire evaluation.

BackgroundInterbull is a non-profit organization that provides internationally comparable breeding values for globalized dairy cattle breeding programmes. Due to different trait definitions and models for genetic evaluation between countries, each biological trait is treated as a different trait in each of the participating countries. This yields a genetic covariance matrix of dimension equal to the number of countries which typically involves high genetic correlations between countries. This gives rise to several problems such as over-parameterized models and increased sampling variances, if genetic (co)variance matrices are considered to be unstructured.MethodsPrincipal component (PC) and factor analytic (FA) models allow highly parsimonious representations of the (co)variance matrix compared to the standard multi-trait model and have, therefore, attracted considerable interest for their potential to ease the burden of the estimation process for multiple-trait across country evaluation (MACE). This study evaluated the utility of PC and FA models to estimate variance components and to predict breeding values for MACE for protein yield. This was tested using a dataset comprising Holstein bull evaluations obtained in 2007 from 25 countries.ResultsIn total, 19 principal components or nine factors were needed to explain the genetic variation in the test dataset. Estimates of the genetic parameters under the optimal fit were almost identical for the two approaches. Furthermore, the results were in a good agreement with those obtained from the full rank model and with those provided by Interbull. The estimation time was shortest for models fitting the optimal number of parameters and prolonged when under- or over-parameterized models were applied. Correlations between estimated breeding values (EBV) from the PC19 and PC25 were unity. With few exceptions, correlations between EBV obtained using FA and PC approaches under the optimal fit were ≥ 0.99. For both approaches, EBV correlations decreased when the optimal model and models fitting too few parameters were compared.ConclusionsGenetic parameters from the PC and FA approaches were very similar when the optimal number of principal components or factors was fitted. Over-fitting increased estimation time and standard errors of the estimates but did not affect the estimates of genetic correlations or the predictions of breeding values, whereas fitting too few parameters affected bull rankings in different countries.

국내산 더러브렛 경주마의 씨수말 평가 기준으로 이용되는 연간수득상금 분석

본 연구는 연간수득상금형질을 이용한 국내 씨수말 평가시스템을 분석하여 주파기록과의 관계를 구명하고자 수행되었다. 씨수말 당평균 자마수와 출주수는 각각 34두와 221회였다. 반면에 평균 2세 자마수와 출주수는 각각 9두와 25회였으며, 2세 자마들이 벌어들인 상금은 연간 수득상금의 8.3%였다. 연간수득상금에 대한 자마수와 출주수간의 단순상관계수는 각각 0.922와 0.934, 그리고 자마수와 출주수간의 단순상관계수는 0.985로 매우 높게 나타났다. 씨수말의 검정경력 첫해의 평균 자마수는 6두, 출주수는 17회로 매우 낮았으며, 검정경력에 따른 자마수와 연간수득상금은 매우 밀접한 관계를 나타내었다. 검정경력 4년차에서 40두 이상의 자마수를 확보하는 것으로 나타났으며, 자마수가 증가할수록 평균수득상금지수는 일괄적으로 증가하였다. 자마수가 30두 이하의 씨수말들의 평균수득상금지수는 1.00 보다 낮았으며, 자마수가 10두 이하인 경우에는 0.06에서 0.13의 범위를 나타내어 자마수는 씨수말의 순위 결정에 매우 큰 영향을 미치고 있었다. 주파기록에 대한 육종가와 출주당 수득상금의 상관계수는 다른 형질들에 비하여 가장 높은 -0.524에서 -0.633의 범위를 나타내었다. This study was conducted to analyze demerits of the sire evaluation system using annual earnings and to examine relationship between annual earnings and finish time in home-produced thoroughbred racehorses. The average number of progenies and number of starts per sire were 34 heads and 221 times, respectively. On the other hand, the number of progenies with the average age of 2 years and the number of starts were 9 heads and 25 times, respectively. The earnings of the horses with the age of 2 years accounted for 8.3% of annual earnings. The simple correlation coefficient between the number of progenies and the number of starts in annual earnings were 0.922 and 0.934, respectively. The correlation coefficient between the number of progenies and the number of starts was very high (0.985). The number of progenies and starts of sires for the first year of test career were very low (6 heads and 17 times), and there was very close relationship between number of progenies and annual earnings by the year of test career. The number of progenies was over 40 heads during the first 4 years of test career, and as the number of progenies increased the average earning index increased. The average earning index of sires with less than 30 progenies was lower than 1.00. When the number of progenies was less than 10, the average earning index was in the range of 0.06~0.13, indicating that the number of progenies affects much for determining the ranking of sires. The correlation coefficient between breeding value for finish time and annual earnings per start was very high (-0.524~-0.633) compared with other traits.

Genetic evaluation of sires and daughters for average daily milk yield in two stations of Holstein cows

A total of 2714 records of average daily milk yield and 2035 records of average milk yield per day of calving interval belonged to Holstein cows maintained at Nasr and Esihaqi dairy cattle over period from 1995 to 2001 were analyzed. The aim is to evaluated sires and daughters genetically according to average daily milk yield and average milk yield per day of calving interval before adjusting for fixed effects and to estimate heritability and repeatability for two traits. The General Linear Model within SAS program (2001) was used to investigate the effects of some factors (season and year of calving, parity, age at first calving, herd and length of lactation) as groups, on average daily milk yield, and also to study the same effects except length of lactation which was changed to length of calving interval on average milk yield per day of calving interval. Component of variance for the random effects was estimated by RMEL method. The Harvey (1991) program was also used to estimate BLUP values for sires and daughters. The overall means of average milk yield was 11.81 kg and the effect of all fixed factors were significant (p < 0.01) except age at first calving which was not significant .whereas means of average milk yield per day of calving interval was 9.24 kg and all fixed factors were significant ( p < 0.01). The heritability and repeatability for average milk yield were is 0.17 and 0.23 respectively, the same parameters for average milk yield per day of calving are 0.14 and 0.23 respectively. There is a wide range in BLUP values of average milk yield estimated %ranged from- 2.37 to 1.33 kg for sires and -4.32 to 4.38 kg for daughters Whereas BLUP values of average milk per day of calving interval ranged from – 0.51 to 1.04 kg for sires and –3.86 to 5.14 kg for daughters.

Principal component approach in variance component estimation for international sire evaluation

BackgroundThe dairy cattle breeding industry is a highly globalized business, which needs internationally comparable and reliable breeding values of sires. The international Bull Evaluation Service, Interbull, was established in 1983 to respond to this need. Currently, Interbull performs multiple-trait across country evaluations (MACE) for several traits and breeds in dairy cattle and provides international breeding values to its member countries. Estimating parameters for MACE is challenging since the structure of datasets and conventional use of multiple-trait models easily result in over-parameterized genetic covariance matrices. The number of parameters to be estimated can be reduced by taking into account only the leading principal components of the traits considered. For MACE, this is readily implemented in a random regression model.MethodsThis article compares two principal component approaches to estimate variance components for MACE using real datasets. The methods tested were a REML approach that directly estimates the genetic principal components (direct PC) and the so-called bottom-up REML approach (bottom-up PC), in which traits are sequentially added to the analysis and the statistically significant genetic principal components are retained. Furthermore, this article evaluates the utility of the bottom-up PC approach to determine the appropriate rank of the (co)variance matrix.ResultsOur study demonstrates the usefulness of both approaches and shows that they can be applied to large multi-country models considering all concerned countries simultaneously. These strategies can thus replace the current practice of estimating the covariance components required through a series of analyses involving selected subsets of traits. Our results support the importance of using the appropriate rank in the genetic (co)variance matrix. Using too low a rank resulted in biased parameter estimates, whereas too high a rank did not result in bias, but increased standard errors of the estimates and notably the computing time.ConclusionsIn terms of estimation's accuracy, both principal component approaches performed equally well and permitted the use of more parsimonious models through random regression MACE. The advantage of the bottom-up PC approach is that it does not need any previous knowledge on the rank. However, with a predetermined rank, the direct PC approach needs less computing time than the bottom-up PC.

Genetic analysis of fertility-related diseases and disorders in Norwegian Red cows

Heritability of and genetic correlations among silent heat (SH), cystic ovaries (CO), metritis (MET), and retained placenta (RP) were inferred. These traits were chosen because they are the 4 most frequent fertility-related diseases and disorders among first-lactation cows in Norway. Records of 503,683 first-lactation daughters of 1,058 Norwegian Red sires with first calving from 2000 through 2006 were analyzed with a 4-variate threshold sire model. Presence or absence of each of the 4 diseases was scored as 1 or 0 based on whether or not the cow had at least 1 veterinary treatment for the disease. The mean frequency was 3.1% for SH, 0.9% for MET, 0.5% for CO, and 1.5% for RP. The model for liability had effects of age at calving and of month-year of calving, herd, sire of the cow, and a residual. Posterior mean (SD) of heritability of liability was 0.06 (0.01) for SH, 0.03 (0.01) for MET, 0.07 (0.01) for CO, and 0.06 (0.01) for RP. The genetic correlation between MET and RP was strong, with posterior mean (SD) 0.64 (0.10). A negative genetic correlation (−0.26) was found between RP and CO. The posterior distributions of the other genetic correlations included zero with high density, and could not be considered different from zero. The frequency of fertility-related diseases and disorders is very low in the Norwegian Red population at present, so there is limited scope for genetic improvement. However, this study indicates that reasonably precise genetic evaluation of sires is feasible for these traits given information from large daughter groups.

Need for sharp phenotypes in QTL detection for calving traits in dairy cattle

The aim of the study was to investigate whether parity-specific phenotypes provide a clearer picture of quantitative trait loci (QTL) affecting calving traits in German Holsteins than breeding values estimated across parities. In experiment I, approximate daughter yield deviations were calculated by applying a univariate sire model assuming unrelated sires used as phenotypes in a QTL mapping study. These results were compared with those obtained using deregressed estimated breeding values obtained from the routine German sire evaluation (experiment II). In experiment I, 17 chromosome-wise significant QTL were found for the first parity, but only 12 for the second parity. Only three QTL for maternal stillbirth, located on BTA7, 15 and 23, showed an experiment-wise significance. Experiment II revealed 15 chromosome-wise significant QTL. The results differed markedly between first and second parity within experiment I, as well as between experiment I and II. The present study showed that parity-specific daughter yield deviations are beneficial for mapping QTL for calving traits. Furthermore, it is expected that the use of sharper phenotypes will also be advantageous for QTL fine mapping and the identification of candidate genes.

Selection response for milk production in conventional production systems in Mexico, using genetic evaluations of Holstein sires from Canada and the United States

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

Identification of a two-marker-haplotype on Bos taurus autosome 18 associated with somatic cell score in German Holstein cattle

BackgroundThe somatic cell score (SCS) is implemented in routine sire evaluations in many countries as an indicator trait for udder health. Somatic cell score is highly correlated with clinical mastitis, and in the German Holstein population quantitative trait loci (QTL) for SCS have been repeatedly mapped on Bos taurus autosome 18 (BTA18). In the present study, we report a refined analysis of previously detected QTL regions on BTA18 with the aim of identifying marker and marker haplotypes in linkage disequilibrium with SCS. A combined linkage and linkage disequilibrium approach was implemented, and association analyses of marker genotypes and maternally inherited two-marker-haplotypes were conducted to identify marker and haplotypes in linkage disequilibrium with a locus affecting SCS in the German Holstein population.ResultsWe detected a genome-wide significant QTL within marker interval 9 (HAMP_c.366+109G>A - BMS833) in the middle to telomeric region on BTA18 and a second putative QTL in marker interval 12-13 (BB710 - PVRL2_c.392G>A). Association analyses with genotypes of markers flanking the most likely QTL positions revealed the microsatellite marker BMS833 (interval 9) to be associated with a locus affecting SCS within the families investigated. A further analysis of maternally inherited two-marker haplotypes and effects of maternally inherited two-marker-interval gametes indicated haplotype 249-G in marker interval 12-13 (BB710 - PVRL2_c.392G>A) to be associated with SCS in the German Holstein population.ConclusionOur results confirmed previous QTL mapping results for SCS and support the hypothesis that more than one locus presumably affects udder health in the middle to telomeric region of BTA18. However, a subsequent investigation of the reported QTL regions is necessary to verify the two-QTL hypothesis and confirm the association of two-marker-haplotype 249-G in marker interval 12-13 (BB710 - PVRL2_c.392G>A) with SCS. For this purpose, higher marker density and multiple-trait and multiple-QTL models are required to narrow down the position of the causal mutation or mutations affecting SCS in German Holstein cattle.

Assessment of Poisson, logit, and linear models for genetic analysis of clinical mastitis in Norwegian Red cows

Clinical mastitis is typically coded as presence/absence during some period of exposure, and records are analyzed with linear or binary data models. Because presence includes cows with multiple episodes, there is loss of information when a count is treated as a binary response. The Poisson model is designed for counting random variables, and although it is used extensively in epidemiology of mastitis, it has rarely been used for studying the genetics of mastitis. Many models have been proposed for genetic analysis of mastitis, but they have not been formally compared. The main goal of this study was to compare linear (Gaussian), Bernoulli (with logit link), and Poisson models for the purpose of genetic evaluation of sires for mastitis in dairy cattle. The response variables were clinical mastitis (CM; 0, 1) and number of CM cases (NCM; 0, 1, 2, …). Data consisted of records on 36,178 first-lactation daughters of 245 Norwegian Red sires distributed over 5,286 herds. Predictive ability of models was assessed via a 3-fold cross-validation using mean squared error of prediction (MSEP) as the end-point. Between-sire variance estimates for NCM were 0.065 in Poisson and 0.007 in the linear model. For CM the between-sire variance was 0.093 in logit and 0.003 in the linear model. The ratio between herd and sire variances for the models with NCM response was 4.6 and 3.5 for Poisson and linear, respectively, and for model for CM was 3.7 in both logit and linear models. The MSEP for all cows was similar. However, within healthy animals, MSEP was 0.085 (Poisson), 0.090 (linear for NCM), 0.053 (logit), and 0.056 (linear for CM). For mastitic animals the MSEP values were 1.206 (Poisson), 1.185 (linear for NCM response), 1.333 (logit), and 1.319 (linear for CM response). The models for count variables had a better performance when predicting diseased animals and also had a similar performance between them. Logit and linear models for CM had better predictive ability for healthy cows and had a similar performance between them.

Genetic analysis of clinical mastitis during different risk periods in Finnish Ayrshire

Clinical mastitis (CM) records from first-lactation Finnish Ayrshire were analysed by linear and threshold models to assess the effects trait definition on estimates of genetic parameters and sire evaluation. The studied CM traits were defined by dividing lactation into six lactation stages (risk periods) by days (d) after calving: CM1 (-7 to 150 d), CM2 (-30 to 30 d), CM3 (-30 to 150 d), CM4 (31 to 150 d), CM5 (150 to 300 d), CM6 (-30 to 300 d). In addition, two data sets were prepared to assess the effect of excluding (Data I) or including (Data II) records of culled cows on estimates of genetic parameters. Sire variances and heritabilities were larger using Data II. When data from longer intervals was used heritabilities of CM were slightly higher than shorter intervals indicating that longer intervals tend to obscure genetic variation between animals. Of all CM traits, heritability of liability to CM with threshold-liability model was highest for CM2 (h2=0.083) implying that most of the genetic information on CM is in early lactation. In sire evaluation, a multitrait index calculated by combining CM2, CM4 and CM5 had the highest correlation with all other univariate CM trait evaluations. This and the magnitude (less than 1.0) of genetic correlations between CM traits suggest that a multitrait model considering CM from the different risk periods would be appropriate for CM sire evaluation.;

Short Communication: Use of Culling Information in Genetic Evaluation of Fertility and Mastitis in Norwegian Red Cows

Breeding values for clinical mastitis, interval from calving to first insemination, and 56-d nonreturn rate for heifers and primiparous cows, were predicted using multivariate linear-threshold sire models, with or without including information on culling during the first lactation. Breeding values for 3,064 sires were predicted using 3 data sets with an average of 273, 135, and 68 first-crop daughters per sire, respectively. For each data set, accuracies of selection for health and fertility traits were evaluated through the predictive ability of predicted sire breeding values with respect to phenotypic performance of second-crop daughters. The predictive ability of estimated breeding values for clinical mastitis and interval from calving to first insemination did not improve when including information on early culling, irrespective of the size of first-crop daughter groups. For 56-d nonreturn rates (heifer and primiparous cow), sire evaluations based on reduced size of daughter groups tended to predict performance of the future daughters slightly better when including data on early culling. Hence, for breeding programs with direct selection for health and fertility traits there is little to gain by including early culling as additional information.

Nonparametric Methods for Incorporating Genomic Information Into Genetic Evaluations: An Application to Mortality in Broilers

Four approaches using single-nucleotide polymorphism (SNP) information (F(infinity)-metric model, kernel regression, reproducing kernel Hilbert spaces (RKHS) regression, and a Bayesian regression) were compared with a standard procedure of genetic evaluation (E-BLUP) of sires using mortality rates in broilers as a response variable, working in a Bayesian framework. Late mortality (14-42 days of age) records on 12,167 progeny of 200 sires were precorrected for fixed and random (nongenetic) effects used in the model for genetic evaluation and for the mate effect. The average of the corrected records was computed for each sire. Twenty-four SNPs seemingly associated with late mortality were included in three methods used for genomic assisted evaluations. One thousand SNPs were included in the Bayesian regression, to account for markers along the whole genome. The posterior mean of heritability of mortality was 0.02 in the E-BLUP approach, suggesting that genetic evaluation could be improved if suitable molecular markers were available. Estimates of posterior means and standard deviations of the residual variance were 24.38 (3.88), 29.97 (3.22), 17.07 (3.02), and 20.74 (2.87) for E-BLUP, the linear model on SNPs, RKHS regression, and the Bayesian regression, respectively, suggesting that RKHS accounted for more variance in the data. The two nonparametric methods (kernel and RKHS regression) fitted the data better, having a lower residual sum of squares. Predictive ability, assessed by cross-validation, indicated advantages of the RKHS approach, where accuracy was increased from 25 to 150%, relative to other methods.