Biomedical subjects

I Hoeschele

Publications and source records attributed to I Hoeschele.

13 recordsLinked to original sources

PubMed1998

Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree.

Quantitative trait loci (QTL) affecting milk production and health of dairy cattle were mapped in a very large Holstein granddaughter design. The analysis included 1794 sons of 14 sires and 206 genetic markers distributed across all 29 autosomes and flanking an estimated 2497 autosomal cM using Kosambi's mapping function. All families were analyzed jointly with least-squares (LS) and variance components (VC) methods. A total of 6 QTL exceeding approximate experiment-wise significance thresholds, 24 QTL exceeding suggestive thresholds, and 34 QTL exceeding chromosome-wise thresholds were identified. Significance thresholds were determined via data permutation (for LS analysis) and chi-square distribution (for VC analysis). The average bootstrap confidence interval for the experiment-wise significant QTL was 48 cM. Some chromosomes harbored QTL affecting several traits, and these were always in coupling phase, defined by consistency with genetic correlations among traits. Chromosome 17 likely harbors 2 QTL affecting milk yield, and some other chromosomes showed some evidence for 2 linked QTL affecting the same trait. In each of these cases, the 2 QTL were in repulsion phase in those families appearing to be heterozygous for both QTL, a finding which supports the build-up of linkage disequilibrium due to selection.

Analysis of Variance↗

PubMed1997

Mapping-linked quantitative trait loci using Bayesian analysis and Markov chain Monte Carlo algorithms.

A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic markers is presented. Parameter estimation and hypothesis testing was implemented via Markov chain Monte Carlo (MCMC) algorithms. Parameters included were allele frequencies and substitution effects for two biallelic QTL, map positions of the QTL, and markers, allele frequencies of the markers, and polygenic and residual variances. Missing data were polygenic effects and multi-locus marker-QTL genotypes. Three different MCMC schemes for testing the presence of a single or two linked QTL on the chromosome were compared. The first approach includes a model indicator variable representing two unlinked QTL, affecting the trait, one linked and one unlinked QTL, or both QTL linked with the markers. The second approach incorporates an indicator variable for each QTL into the model for phenotype, allowing or not allowing for a substitution effect of a QTL, on phenotype, and the third approach is based on model determination by reversible jump MCMC. Methods were evaluated empirically by analyzing simulated granddaughter designs. All methods identified correctly a second, linked QTL and did not reject the one-QTL model when there was only a single QTL, and no additional or an unlinked QTL.

Algorithms↗

PubMed1997

Advances in statistical methods to map quantitative trait loci in outbred populations.

Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.

Bayes Theorem↗

PubMed1996

Maximum likelihood analysis of rare binary traits under different modes of inheritance.

Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary traits with data structures typical for swine populations. The genetic models considered included a monogenic, a digenic, a polygenic, and three mixed polygenic and major gene models. The main emphasis was on the detection of major genes acting on a polygenic background. Deterministic algorithms were employed to integrate and maximize likelihoods. A simulation study was conducted to evaluate model selection and parameter estimation. Three designs were simulated that differed in the number of sires/number of dams within sires (10/10, 30/30, 100/30). Major gene effects of at least one SD of the liability were detected with satisfactory power under the mixed model of inheritance, except for the smallest design. Parameter estimates were empirically unbiased with acceptable standard errors, except for the smallest design, and allowed to distinguish clearly between the genetic models. Distributions of the likelihood ratio statistic were evaluated empirically, because asymptotic theory did not hold. For each simulation model, the Average Information Criterion was computed for all models of analysis. The model with the smallest value was chosen as the best model and was equal to the true model in almost every case studied.

Algorithms↗

PubMed1996

The use of multiple markers in a Bayesian method for mapping quantitative trait loci.

Information on multiple linked genetic markers was used in a Bayesian method for the statistical mapping of quantitative trait loci (QTL). Bayesian parameter estimation and hypothesis testing were implemented via Markov chain Monte Carlo algorithms. Variables sampled were the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage or nonlinkage, and the parameters. The parameter vector included allele frequencies at the markers and the QTL, map distances of the markers and the QTL, QTL substitution effect, and polygenic and residual variances. The criterion for QTL detection was the marginal posterior probability of a QTL being located on the chromosome carrying the markers. The method was evaluated empirically by analyzing simulated granddaughter designs consisting of 2000 sons, 20 related sires, and their ancestors.

Algorithms↗

PubMed1995

Multiple-trait genetic evaluation for one polychotomous trait and several continuous traits with missing data and unequal models.

A method for multiple-trait genetic evaluation for categorical and continuous traits was generalized to a polychotomous rather than a binary trait and to several continuous traits rather than one. Any missing data pattern was allowed. Breeding values were estimated based on an animal model with fixed and random effects differing among traits. Equations in location parameters were solved iteratively within each Fisher scoring step. In each round of scoring, new solutions of the residual covariances among the categorical and the continuous traits were computed based on maximum likelihood estimation and used to reevaluate all partial regression coefficients of liability on the continuous traits for each missing data pattern. Simulation was used to assess the estimation of the residual covariances. The other dispersion parameters were treated as known because their estimation has been treated elsewhere and is analogous to restricted maximum likelihood.

Animals↗

PubMed1995

Multiple-trait prediction of transmitting abilities for herd life and estimation of economic weights using relative net income adjusted for opportunity cost.

Genetic and phenotypic (co)variances among linear type traits, final score, first lactation milk and fat yield, and 84-mo totals for longevity, relative net income, and relative net income adjusted for opportunity cost of postponed replacement were estimated with a multiple-trait sire model. Data were from 433,116 cows in herds participating in the classification program for conformation traits of the Holstein Association of America. Yield information from all cows in classified herds indicated that classified cows are not a random sample. Heritability of net income adjusted for opportunity cost was higher, .17, than unadjusted net income, .12, but the genetic correlation between the estimates of net income was high, .97. Adjusted net income also had high genetic correlations with first lactation milk yield, .80; fat yield, .60; and dairy form, .48. Heritability of longevity (months in milk to 84 mo) was .06. Adjustment of net income for opportunity cost lowered the genetic correlation with longevity from .84 to .70. Evaluation of lifetime merit using traits measured during first lactation with economic weights developed using adjusted net income was more accurate than indirect prediction of longevity; the approximate reliability of a first-crop AI sire for lifetime merit was .65 compared with .42 for longevity.

Animals↗

PubMed1994

Impact of different strategies and amounts of preferential treatment on various methods of bull-dam selection.

Three records of milk yield, fat yield, and type were simulated for each cow in 20 herds of 200 cows over 13 yr. Preferential treatment or bias was simulated by increasing milk and fat yields by an average of 0, 16, and 32% for separate copies of the simulation. The bias was given to a limited number of cows from the original herds based on four strategies. Five methods of bull-dam selection that used an index with a 2:2:1 ratio of milk to fat to type to select the top 2% of cows were compared: ETA using first lactation, using all lactations, after phenotypic minima were required, after preselection on three-generation pedigree index, and on pedigree index alone. Selection on ETA for first or all lactations gave the highest average of true breeding values at 0 and 16% for all strategies studied. In general, selection on pedigree index alone or after phenotypic minima were required gave poor results and should not be considered to be viable. Preselection of bull-dams on pedigree index proved to be extremely useful for biased and unbiased data. The optimal policy was to preselect the top 12% of the population before reranking and selecting on ETA for all lactations.

Animals↗

PubMed1992

Use of reproductive technology to estimate variances and predict effects of gene interactions.

Advanced reproductive techniques are creating the large numbers of close relatives needed to study gene interactions. Identical triplets, a set of 26 full sisters, a family of 4215 three-quarter sisters (same sire and maternal grandsire), a family of 76,698 half sisters, and 1.6 million granddaughters of Round Oak Rag Apple Elevation now have lactation records. Similarity of closest relatives might be explained by similar nonadditive as well as additive genetic merit. The 23,015 families of full sisters with mean family size of 3 provide nearly as much information about dominance variation as do the 55,779 families of three-quarter sisters with mean family size of 13; the 79 families of clones provide little information by comparison. Hypothetically, REML analysis of all US Holstein data could provide estimates of dominance and additive x additive variance with standard errors approximately 1% of phenotypic variance, but estimates of any higher order interactions would have standard errors greater than 10%. The tilde-hat approximation proved to be incompatible with animal models but was used for sire-maternal grandsire analysis of 765,868 first lactation records. Dominance variance was estimated as 3.5% of phenotypic variance for milk and 3.3% for fat with standard error of 4.2%. With constant data set size, variances are estimated most precisely if family sizes equal 1 plus ratio of within-family to between-family variance. An animal model evaluation including dominance relationships for 581,670 animals was computed, but gene interactions from distant ancestor pairs were ignored. Mating advice and improved additive predictions, especially for clones, could be obtained by including dominance in models.

Animals↗

PubMed1991

Rapid inversion of dominance relationship matrices for noninbred populations by including sire by dam subclass effects.

For estimation of dominance effects and dominance variance, the inverse of a dominance relationship matrix is required. Dominance effects can be partitioned into sire x dam or sire x maternal grandsire subclass effects that are inherited and residuals within subclass that are not inherited. The subclass effects have immediate use in predicting performance of offspring from prospective matings. A rapid method for directly computing the inverse relationship matrix of subclass effects is presented. The procedure is similar to Henderson's simple method of computing an inverse additive genetic relationship matrix. The inverse relationship matrix among subclass effects consists of a contribution from each subclass of coefficients of a matrix of maximum size 9 x 9. The algorithm can be modified to compute the inverse of the relationship matrix among sire x dam or sire x maternal grandsire subclasses and among individual dominance effects. Computing cost increases approximately linearly with dimensions of inverses. Dimensions could be several times the number of subclasses in the data because subclasses without records but providing relationship ties must be added. Computation of the inverse relationship matrix among 136,827 sire x maternal grandsire subclasses in a population of 765,868 animals required 163 central processing unit seconds on an IBM 3090 and less than 4 Mbytes of memory.

Algorithms↗

PubMed1991

Rapid inversion of additive by additive relationship matrices by including sire-dam combination effects.

Inverses of relationship matrices are useful for prediction of individual additive or nonadditive genetic merits and for estimation of variance components. An algorithm to form inverses of additive by additive relationship matrices rapidly from lists of individuals and their parents was developed. The algorithm uses simple recurrences among additive by additive and sire-dam combination effects to construct inverses for noninbred or inbred populations. Dimensions of matrices produced may be several times the number of individuals in the population because combination effects for sire-dam subclasses must be included in matrices. Rules of inheritance of sire-dam combination effects are the same as for dominance combination effects. Cost of forming inverses increases linearly with number of individuals. Each individual contributes 36 or fewer nonzero coefficients, and each sire-dam subclass contributes an additional 81 or fewer nonzero coefficients to the matrix. Computation of inverse of the relationship matrix due to 1003 sires and maternal grandsires of 765,868 cows required forming a matrix of order 137,830 and 4 Mbytes of memory.

Algorithms↗

PubMed1991

Additive and nonadditive genetic variance in female fertility of Holsteins.

Additive and nonadditive genetic variances were estimated for cow fertility of Holsteins. Measures of fertility were first lactation days open and service period as recorded and with upper bounds of 150 and 91 d, respectively. Six million inseminations from the Raleigh, North Carolina Processing Center were used to form fertility records of 379,009 cows. Data were analyzed with a model accounting for all additive, dominance, and additive by additive covariances traced through sires and maternal grandsires. Variance components were estimated by the tilde-hat approximation to REML. Heritability in the narrow sense was 2% for days open and .8% for service period. Dominance and additive by additive variance as a percentage of phenotypic variation strongly depended on imposition of upper bounds. Heritabilities in the broad sense ranged from 2.2 to 6.6% and were at least twice as large as heritabilities in the narrow sense. Effect of 25% inbreeding was only around an additional 3 d open. Specific combining abilities among bulls were estimated as sums of dominance and additive by additive interactions removing effect of inbreeding depression. Differences between maximum and minimum estimates were in the order of twice the estimated standard deviation, ranging from 1.5 to 6.7 d. Effects of inbreeding and specific combining ability could be jointly considered in mating programs following sire selection.

Animals↗

PubMed1990

Association of genetic defects with yield and type traits: the weaver locus effect on yield.

The association of recessive genetic disorders with yield and type traits was investigated. The frequency of a defective gene could be increased by selection if it is positively associated with selected traits, despite efforts to reduce it. Genetic defects considered were weaver in Brown Swiss and rectovaginal constriction and limber leg in Jerseys. Data sets for linkage analysis consisted of 245 sons of 9 carrier sires, 1036 sons of 16 carrier sires, and 557 sons of 10 carrier sires, respectively. Weaver carrier sons had higher producing daughters than noncarrier sons within all 9 sire families. Weaver carrier cows have an advantage of 673.6 kg milk and 26.0 kg fat and a disadvantage in rear legs score, indicating that the condition may not be completely recessive. Carriers of the other defect genes have no advantage for milk production, are scored lower for pelvic angle, and limber leg carriers have more desirable udders. Estimates of defect gene frequencies in 264,000 Jersey cows show a decrease over time for rectovaginal constriction and limber leg; in 97,723 Brown Swiss cows, frequency of the weaver gene increased over time. Gene frequencies in daughters of the youngest sires were 5.48, 2.13, and 8.89%, respectively. Consistently higher yield evaluations of weaver carrier sons within each sire family, large advantage in production of weaver carrier cows, and increasing gene frequency over time indicate that a chromosome segment with major effect on yield is tightly linked to weaver in Brown Swiss.

Animals↗