The transmission-disequilibrium test (TDT) is a model-free method to detect linkage between a marker and a trait locus. Originally developed to map disease genes in human genetics, this statistic has been recently extended to deal with quantitative characters. The emphasis of current research is on investigating statistical properties of the test applied to data from livestock populations. For various constellations of sample parameters, it is shown via simulation that the empirically derived null hypothesis distribution of TDT remains in good agreement with its asymptotic distribution while its power is satisfactory only for very close linkage. TDT is then applied to a real data set from milk production data of a dairy cattle population.
The study investigated the existence of heterogeneous variance in first-lactation daily milk yield of Polish Black-and-White cows across herds in different years. Bayesian Information Criterion was used to show that the model with unequal residual variances for different herd-years was more plausible than the model assuming equal variances. A method of adjusting phenotypic records was developed to account for unequal variability in herd-years. Factors used for the data adjustment considered variation of general residuals and residuals for specific herd-years. The size of herd-year was also taken into account. Varied power of corrections was used to analyze the effect of adjustment on estimated breeding values. The method was applied to daily milk records of 817 165 primiparous cows. The effectiveness of the data adjustment was evaluated by the analysis of differences between each bull's breeding value and its parental index. Data correction reduced the average difference and variance of differences between breeding values and parental indices. Accounting for the size of herd-year classes in correction factors improved the efficiency of heterogeneous variance adjustment.
Daughter yield deviations (DYDs) of bulls and yield deviations (YDs) of cows, besides estimated breeding values (EBVs), are standard measures of animals' genetic merits in routine genetic evaluations worldwide. In this contribution, we first point out differences and similarities between DYDs and EBVs calculated for milk, fat and protein yields. While the latter measure represents the additive polygenic value of an animal, the former consists of both the additive polygenic and residual components. Then, a summary of DYDs and YDs calculated for the Polish population of dairy cattle is presented. The estimated correlations between DYDs and EBVs are generally high, but vary considerably depending on the minimum number of daughters used for calculation of DYDs and on the accuracy of calculated DYDs. Using DYDs estimated for each production year for 16 452 bulls, we demonstrate how to use DYDs for the validation of genetic trend estimated in the model used for genetic evaluation. Based on genotypic data of 252 bulls, we show that DYDs can be used for the estimation of candidate gene effects. For each of the yield traits, the within-bull genetic trend was relatively high, ranging between 1.39% of genetic standard deviation per production year for milk and 7.67% of genetic standard deviation per production year for fat, both in the 2nd lactation. Out of 8 polymorphisms tested, 5 showed a significant correlation with DYD, with the highest effect attributed to the polymorphism within the leptin receptor gene, whose additive effect was estimated as 247.33 kg of milk at 2nd parity.
The main aim of this study was to determine if there exist any major gene for milk yield (MY), milking speed (MS), dry matter intake (DMI), and body weight (BW) recorded at various stages of lactation in first-lactation dairy cows (2543 observations from 320 cows) kept at the research farm of the Swiss Federal Institute of Technology between April 1994 and April 2004. Data were modelled based a simple repeatability covariance structure and analysed by using Bayesian segregation analyses. Gibbs sampling was used to make statistical inferences on posterior distributions; inferences were based on a single run of the Markov chain for each trait with 500 000 samples, with each 10th sample collected because of the high correlation among the samples. The posterior mean (?SD) of major gene variance was 2.61 (?2.46) for MY, 0.83 (?1.26) for MS, 4.37 (?2.34) for DMI, and 2056.43 (?665.67) for BW. Highest posterior density regions for 3 of the 4 traits did not include 0 (except MS), which supported the evidence for major gene. With additional tests for agreement with Mendelian transmission probabilities, we could only confirm the existence of a major gene for MY, but not for MS, DMI, and BW. Expected Mendelian transmission probabilities and their model fits were also compared.
Prolactin plays an important regulatory function in mammary gland development, milk secretion, and expression of milk protein genes. Hence the PRL gene is a potential quantitative trait locus and genetic marker of production traits in dairy cattle. We analysed the sequence of the PRL gene to investigate whether mutations in this sequence might be responsible for quantitative variations in milk yield and composition. Using SSCP and direct sequencing, we detected six single-nucleotide polymorphisms within a 294-bp prolactin gene fragment involving exon 4. All detected mutations were silent with respect to the amino acid sequence of the protein. PCR-RFLP genotyping of SNP 8398 R (RsaI) was used to assess allele frequencies in 186 Black-and-White cows (0.113 and 0.887 for A and G, respectively) and in 138 Jersey cows (0.706 and 0.294 for A and G, respectively). Black-and-White cows with genotype AG showed the highest milk yield, while cows with genotype GG showed the highest fat content.
The selection index and single- and multi-trait animal models were used for genetic evaluation of 100,983 cows. Genetic and environmenta? al (co)variances of five milk production traits were estimated using MTDFREML. The highest heritabilities were found for fat and protein contents in all three lactations (0.29-0.33), and the lowest for protein yield in the third lactation (0.08). Phenotypic and genetic correlations between yield traits in adjacent lactations were higher than between the first and third lactations. Correlations between breeding values for fat content were higher than for yield traits. The magnitude of correlations between the index and animal model evaluations depended on the number of lactation records included in both procedures. Usually the relationships between breeding values based on the same lactations were close to unity. The correlations between single-trait and multi-trait evaluations decreased with increasing numbers of lactations in the model. This was the result of using variances and covariances of later lactations in the multi-trait model.
Four statistical models for genetic evaluations utilising dairy test day data are considered. These are: the fixed regression model, the random regression model, the autoregressive model and a multiple trait model. The emphasis is put on the comparison of these models in terms of their assumed covariance structure, modelling and prediction of breeding values and parameterisation. In the future one of the models should be used for a routine genetic evaluation of the Polish Black-and-White dairy cattle. Therefore, characteristics of test day data from the Polish population are given. In conclusion, it appears that thanks to its flexibility in handling heterogeneous variances during lactation, variable autocorrelation and non-uniform spacing between tests, the random regression model forms the most suitable approach.
DUMPS (Deficiency of Uridine Monophosphate Synthase) is a hereditary recessive disorder in Holstein cattle causing early embryo mortality during its implantation in the uterus. The only way to avoid the economic losses is early detection of DUMPS carriers. Because American Holstein semen has been intensively imported to Poland since 1970, there was a risk that DUMPS could have spread in Polish dairy cattle. In our study, 2209 dairy cattle of the Polish Holstein breed have been screened by the DNA test. The dominant group was young bulls entering the testing program (1171) and proven bulls (781). They represented all sires entering Polish breeding programs between 1999 and 2003. Also, 257 sire dams were included in the screening program. No DUMPS carrier has been found. Our results then indicate that the population of dairy cattle reared in Poland is free from DUMPS. Because of the economical significance of the DUMPS mutation and its recessive mode of inheritance, attention has to be paid to any case of a bull having in his origin any known DUMPS carrier. Such a bull should be tested and if positive eliminated from the active population. Also, young bulls (testing bulls) should be screened for DUMPS if in their progeny a high incidence of embryo mortality is observed and their genealogy cannot exclude their relatedness to any DUMPS carriers.
The covariance function approach with an iterative two-stage algorithm of Liu et al. (2000) was applied to estimate parameters for the Polish Black-and-White dairy population based on a sample of 338 808 test day records for milk, fat, and protein yields. A multiple trait sire model was used to estimate covariances of lactation stages. A third-order Legendre polynomial was subsequently fitted to the estimated (co)variances to derive (co)variances of random regression coefficients for both additive genetic and permanent environment effects. Daily and 305-day heritability estimates obtained are consistent with several studies which used both fixed and random regression test day models. Genetic correlations between any two days in milk (DIM) of the same lactation as well as genetic correlations between the same DIM of two lactations were within a biologically acceptable range. It was shown that the applied estimation procedure can utilise very large data sets and give plausible estimates of (co)variance components.
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