A simulation study on the accuracy of position and effect estimates of linked QTL and their asymptotic standard deviations using multiple interval mapping in an F2 scheme

Approaches like multiple interval mapping using a multiple-QTL model for simultaneously mapping QTL can aid the identification of multiple QTL, improve the precision of estimating QTL positions and effects, and are able to identify patterns and individual elements of QTL epistasis. Because of the statistical problems in analytically deriving the standard errors and the distributional form of the estimates and because the use of resampling techniques is not feasible for several linked QTL, there is the need to perform large-scale simulation studies in order to evaluate the accuracy of multiple interval mapping for linked QTL and to assess confidence intervals based on the standard statistical theory. From our simulation study it can be concluded that in comparison with a monogenetic background a reliable and accurate estimation of QTL positions and QTL effects of multiple QTL in a linkage group requires much more information from the data. The reduction of the marker interval size from 10 cM to 5 cM led to a higher power in QTL detection and to a remarkable improvement of the QTL position as well as the QTL effect estimates. This is different from the findings for (single) interval mapping. The empirical standard deviations of the genetic effect estimates were generally large and they were the largest for the epistatic effects. These of the dominance effects were larger than those of the additive effects. The asymptotic standard deviation of the position estimates was not a good criterion for the accuracy of the position estimates and confidence intervals based on the standard statistical theory had a clearly smaller empirical coverage probability as compared to the nominal probability. Furthermore the asymptotic standard deviation of the additive, dominance and epistatic effects did not reflect the empirical standard deviations of the estimates very well, when the relative QTL variance was smaller/equal to 0.5. The implications of the above findings are discussed

Effect of family relatedness on characteristics of estimated IBD probabilities in relation to precision of QTL estimates

<p>Abstract</p> <p>Background</p> <p>A random QTL effects model uses a function of probabilities that two alleles in the same or in different animals at a particular genomic position are identical by descent (IBD). Estimates of such IBD probabilities and therefore, modeling and estimating QTL variances, depend on marker polymorphism, strength of linkage and linkage disequilibrium of markers and QTL, and the relatedness of animals in the pedigree. The effect of relatedness of animals in a pedigree on IBD probabilities and their characteristics was examined in a simulation study.</p> <p>Results</p> <p>The study based on nine multi-generational family structures, similar to a pedigree structure of a real dairy population, distinguished by an increased level of inbreeding from zero to 28% across the studied population. Highest inbreeding level in the pedigree, connected with highest relatedness, was accompanied by highest IBD probabilities of two alleles at the same locus, and by lower relative variation coefficients. Profiles of correlation coefficients of IBD probabilities along the marked chromosomal segment with those at the true QTL position were steepest when the inbreeding coefficient in the pedigree was highest. Precision of estimated QTL location increased with increasing inbreeding and pedigree relatedness. A method to assess the optimum level of inbreeding for QTL detection is proposed, depending on population parameters.</p> <p>Conclusions</p> <p>An increased overall relationship in a QTL mapping design has positive effects on precision of QTL position estimates. But the relationship of inbreeding level and the capacity for QTL detection depending on the recombination rate of QTL and adjacent informative marker is not linear.</p

Maximum number of total born piglets in a parity and individual ranges in litter size expressed as specific characteristics of sows

Abstract Background The objective of this study was to underline that litter size as a key trait of sows needs new parameters to be evaluated and to target an individual optimum. Large individual variation in litter size affects both production and piglet’s survival and health negatively. Therefore, two new traits were suggested and analyzed. Two data sets on 5509 purebred German Landrace sows and 3926 Large White and crossing sows including at least two parental generations and at least five parities were subjected to variance components analysis. Results The new traits for evaluating litter size were derived from the individual numbers of total born piglets (TBP) per parity: In most cases, sows reach their maximum litter size in their fourth parity. Therefore, data from at least five parities were included. The first observable maximum and minimum of TBP, and the individual variation expressed by the range were targeted. Maximum of TBP being an observable trait in pig breeding and management yielded clearly higher heritability estimates (h 2 ~ 0.3) than those estimates predominantly reported so far. Maximum TBP gets closer to the genetic capacity for litter size than other litter traits. Minimum of TBP is positively correlated with the range of TBP (r p  = 0.48, r g  > 0.6). The correlation between maximum of TBP and its individually reached frequency was negative in both data sets (r p  = − 0.28 and − 0.22, respectively). Estimated heritability coefficients for the range of TBP comprised a span of h 2  = 0.06 to 0.10. Conclusion An optimum both for maximum and range of total born piglets in selecting sows is a way contributing to homogenous litters in order to improving the animal-related conditions both for piglets’ welfare and economic management in pig

A simulation study on the accuracy of position and effect estimates of linked QTL and their asymptotic standard deviations using multiple interval mapping in an F2_{2} scheme

Approaches like multiple interval mapping using a multiple-QTL model for simultaneously mapping QTL can aid the identification of multiple QTL, improve the precision of estimating QTL positions and effects, and are able to identify patterns and individual elements of QTL epistasis. Because of the statistical problems in analytically deriving the standard errors and the distributional form of the estimates and because the use of resampling techniques is not feasible for several linked QTL, there is the need to perform large-scale simulation studies in order to evaluate the accuracy of multiple interval mapping for linked QTL and to assess confidence intervals based on the standard statistical theory. From our simulation study it can be concluded that in comparison with a monogenetic background a reliable and accurate estimation of QTL positions and QTL effects of multiple QTL in a linkage group requires much more information from the data. The reduction of the marker interval size from 10 cM to 5 cM led to a higher power in QTL detection and to a remarkable improvement of the QTL position as well as the QTL effect estimates. This is different from the findings for (single) interval mapping. The empirical standard deviations of the genetic effect estimates were generally large and they were the largest for the epistatic effects. These of the dominance effects were larger than those of the additive effects. The asymptotic standard deviation of the position estimates was not a good criterion for the accuracy of the position estimates and confidence intervals based on the standard statistical theory had a clearly smaller empirical coverage probability as compared to the nominal probability. Furthermore the asymptotic standard deviation of the additive, dominance and epistatic effects did not reflect the empirical standard deviations of the estimates very well, when the relative QTL variance was smaller/equal to 0.5. The implications of the above findings are discussed

A note on inbreeding in dairy cattle breeding

Starting from the study at the beginning of the East German "Heterosisfeldversuch", where PANICKE et al. (1975) considered the possibilities of a targeted use of inbreeding and heterotic effects, we show and discuss results of inbreeding studies in the USA dairy cattle breeding. Several research groups worldwide presented effective tools for managing inbreeding in dairy cattle. Their efforts underline the need of inbreeding studies. Contemplating inbreeding is necessary for any breeding decision to avoid inbreeding depression and for improved genetic analyses, e.g. in QTL- estimation. A novel methodology (HERNANDEZ-SANCHEZ et al., 2004a and b) is suggested for estimating inbreeding at the three levels of population, individual and locus