Genetic parameters for blood oxygen saturation, body weight and breast conformation in 4 meat-type chicken lines

1. The objective of the study was to explore the genetic architecture of blood oxygen saturation (SaO) (an indicator trait, negatively correlated with ascites susceptibility), body weight (Weight) and fleshing score (Flesh, a measure of breast conformation) for 4 meat-type chicken lines reared in commercial conditions. 2. Genetic components, including heritabilities and genetic correlations, were estimated by Restricted Maximum likelihood for these traits measured at 6 weeks of age. 3. Data were collected over eight generations of selection and pedigrees comprised in excess of 130,000 birds. 4. Univariate analyses were performed to allow model definition and to obtain starting values for trivariate analyses. The basic model included a random animal effect and, in further models explored, a maternal environmental effect or a genetic maternal effect or both were fitted. Models were compared using likelihood ratio tests. 5. Estimated heritabilities for SaO ranged from 0.1 to 0.2, and there was no evidence of genetic maternal effects for SaO. The environmental maternal component was significant for one of the populations only. Estimated heritabilities for both Weight and Flesh were between 0.2 and 0.4, and there was evidence of environmental and genetic maternal effects for these traits in all populations. 6. Genetic correlations between SaO and Weight and between SaO and Flesh were low and negative. This suggests that, in principle, genetic selection to simultaneously increase SaO, and therefore decrease ascites susceptibility, and WEight and Flesh could be performed using traditional (marker-free) selection methods. We discuss how a putative interaction between ascites and production traits could jeopardise the success of such methods.

Joint multi-population analysis for genetic linkage of bipolar disorder or "wellness" to chromosome 4p

To test the hypothesis that the same genetic loci confer susceptibility to, or protection from, disease in different populations, and that a combined analysis would improve the map resolution of a common susceptibility locus, we analyzed data from three studies that had reported linkage to bipolar disorder in a small region on chromosome 4p. Data sets comprised phenotypic information and genetic marker data on Scottish, Danish, and USA extended pedigrees. Across the three data sets, 913 individuals appeared in the pedigrees, 462 were classified, either as unaffected (323) or affected (139) with unipolar or bipolar disorder. A consensus linkage map was created from 14 microsatellite markers in a 33 cM region. Phenotypic and genetic data were analyzed using a variance component (VC) and allele sharing method. All previously reported elevated test statistics in the region were confirmed with one or both analysis methods, indicating the presence of one or more susceptibility genes to bipolar disorder in the three populations in the studied chromosome segment. When the results from both the VC and allele sharing method were considered, there was strong evidence for a susceptibility locus in the data from Scotland, some evidence in the data from Denmark and relatively less evidence in the data from the USA. The test statistics from the Scottish data set dominated the test statistics from the other studies, and no improved map resolution for a putative genetic locus underlying susceptibility in all three studies was obtained. Studies reporting linkage to the same region require careful scrutiny and preferably joint or meta analysis on the same basis in order to ensure that the results are truly comparable.

A genome scan and follow-up study identify a bipolar disorder susceptibility locus on chromosome 1q42

In this study, we report a genome scan for psychiatric disease susceptibility loci in 13 Scottish families. We follow up one of the linkage peaks on chromosome 1q in a substantially larger sample of 22 families affected by schizophrenia (SCZ) or bipolar affective disorder (BPAD). To minimise the effect of genetic heterogeneity, we collected mainly large extended families (average family size >18). The families collected were Scottish, carried no chromosomal abnormalities and were unrelated to the large family previously reported as segregating a balanced (1:11) translocation with major psychiatric disease. In the genome scan, we found linkage peaks with logarithm of odds (LOD) scores >1.5 on chromosomes 1q (BPAD), 3p (SCZ), 8p (SCZ), 8q (BPAD), 9q (BPAD) and 19q (SCZ). In the follow-up sample, we obtained most evidence for linkage to 1q42 in bipolar families, with a maximum (parametric) LOD of 2.63 at D1S103. Multipoint variance components linkage gave a maximum LOD of 2.77 (overall maximum LOD 2.47 after correction for multiple tests), 12 cM from the previously identified SCZ susceptibility locus DISC1. Interestingly, there was negligible evidence for linkage to 1q42 in the SCZ families. These results, together with results from a number of other recent studies, stress the importance of the 1q42 region in susceptibility to both BPAD and SCZ.

Power of linkage disequilibrium mapping to detect a quantitative trait locus (QTL) in selected samples of unrelated individuals

We considered a strategy to map quantitative trait loci (QTLs) using linkage disequilibrium (LD) when the QTL and marker locus were multiallelic. The strategy involved phenotyping a large number of unrelated individuals and genotyping only selected individuals from the two tails of the trait distribution. Power to detect trait-marker association was assessed as a function of the number of QTL and marker alleles. Two patterns of LD were used to study their influence on power. When the frequency of the QTL allele with the largest effect and that of the marker allele linked in coupling were equal, power was maximum. In this case, increasing the number of QTL alleles reduced the power. The maximum difference in power between the two LD patterns studied was approximately 30%. For low QTL heritabilities (h2QTL<0.1) and single trait studies we recommend selecting around 5% of the upper and lower tails of the trait distribution.

Mapping of quantitative trait loci for growth and carcass traits in commercial sheep populations1

Quantitative trait loci analyses were applied to data from Suffolk and Texel commercial sheep flocks in the United Kingdom. The populations comprised 489 Suffolk animals in three half-sib families and 903 Texel animals in nine half-sib families. Phenotypic data comprised measurements of live weight at 8 and 20 wk of age and ultrasonically measured fat and muscle depth at 20 wk. Lambs and their sires were genotyped across candidate regions on chromosomes 1, 2, 3, 4, 5, 6, 11, 18, and 20. Data were analyzed at the breed level, at the family level, and across extended families when families were genetically related. The breed-level analyses revealed a suggestive QTL on chromosome 1 in the Suffolk breed, between markers BM8246 and McM130, affecting muscle depth, although the effect was only significant in one of the three Suffolk families. A two-QTL analysis suggested that this effect may be due to two adjacent QTL acting in coupling. In total, 24 suggestive QTL were identified from individual family analyses. The most significant QTL affected fat depth and was segregating in a Texel family on chromosome 2, with an effect of 0.62 mm. The QTL was located around marker ILSTS030, 26 cM distal to myostatin. Two of the Suffolk and two of the Texel sires were related, and a three-generation analysis was applied across these two extended families. Seven suggestive QTL were identified in this analysis, including one that had not been detected in the individual family analysis. The most significant QTL, which affected muscle depth, was located on chromosome 18 near the callipyge and Carwell loci. Based on the phenotypic effect and location of the QTL, the data suggest that a locus similar to the Carwell locus may be segregating in the United Kingdom Texel population.

Twin study of genetic and environmental influences on adult body size, shape, and composition

OBJECTIVE

To investigate the genetic and environmental influences on adult body size, shape, and composition in women and men, and to assess the impact of age.

MATERIALS AND METHODS

In this cross-sectional study of 325 female and 299 male like-sex healthy twin pairs, on average 38 y old (18-67 y), we determined zygosity by DNA similarity, and performed anthropometry and bioelectrical impedance analysis of body composition. The contribution to the total phenotypic variance of genetic, common environment, and individual environment was estimated in multivariate analysis using the FISHER program. Further, these variance components were analysed as linear functions of age.

RESULTS

In both women and men genetic contributions were significant for all phenotypes. Heritability for body mass index was 0.58 and 0.63; for body fat%, 0.59 and 0.63; for total skinfolds, 0.61 and 0.65; for extremity skinfolds 0.65 and 0.62; for truncal skinfolds, 0.50 and 0.69; for suprailiac skinfolds, 0.49 and 0.48; for waist circumference, 0.48 and 0.61; for hip, 0.52 and 0.58; for lean body mass/height2, 0.61 and 0.56; and for height, 0.81 and 0.69, respectively. There was no strong evidence of common environmental effects under the assumptions of no nonadditive effect. The pattern of age trends was inconsistent. However, when significant there was a decrease in heritability with advancing age.

DISCUSSION

These findings suggest that adult body size, shape, and composition are highly heritable in both women and men, although a decreasing tendency is seen with advancing age.

Extent of linkage disequilibrium in a Sardinian sub-isolate: sampling and methodological considerations

The extent of linkage disequilibrium (LD) is an important factor when designing experiments for mapping disease or trait loci using LD mapping methods. It depends on the population history and hence is a characteristic of each population. Here, we have assessed the extent of LD in a sub-isolate of the general Sardinian population (775 members of one village) using 22 polymorphic markers on chromosome 19. We found high levels of disequilibrium that extended to 8 cM, when based on D', and 11 cM when based on the significance level of the allelic association. The fact that conclusions based on both methods are similar suggests that the estimates are quite robust. We have also shown, through a simple resampling technique, that small sample sizes can overestimate both the mean value of D' and its variance up to a factor of about 2 and 16, respectively, when the number of diplotypes (the pair of haplotypes that compose the genotype) decreased from 186 to 26. We evaluated the effect on D' of the depth of the pedigree available when using phased founders, and compared the estimates with those obtained when using unphased founders, and also the effect of grouping alleles on the value of D' and the significance level. Owing to the high sampling variance of LD, we recommend the use of at least 200 unrelated individuals when characterizing the extent of LD.

Twin study of genetic and environmental influences on glucose tolerance and indices of insulin sensitivity and secretion

AIMS/HYPOTHESIS

Family and twin studies have reported different estimates of the relative contribution of genetic and environmental factors to the quantitative traits glucose tolerance, insulin secretion, and insulin sensitivity. Our aims were to estimate these relative influences in a large sample of twins from the population and to assess the effect of age.

METHODS

In this population-based, cross-sectional study we gave an oral glucose tolerance test to 317 women and 290 men who were same-sex healthy twin pairs between 18 to 67 years of age. The genetic, common environmental and individual environmental variance components for fasting and 120-min glucose and for fasting and 30-min insulin as well as the linear effects of age on these components were estimated by multivariate analysis (using the software FISHER).

RESULTS

In women and men the heritability for fasting glucose was 12 and 38%, for 120-min glucose it was 38 and 43%, for fasting insulin it was 54 and 37%, and for 30-min insulin it was 57 and 47%, respectively. Under the assumption of no non-additive genetic effects (no intra- or inter-gene interaction) there was no strong evidence for common environmental effects, barring significant effects for fasting glucose in women. Heritability decreased with age for 120-min glucose in women and fasting insulin in men, whereas it increased for 120-min glucose in men.

CONCLUSION/INTERPRETATION

This study indicates a limited additive genetic influence on the result of an OGTT, possibly with sex-specific age effects, and generally little or no influence of the common environment. Accordingly, there is a considerable individual environmental variation.

Analyses for the presence of a major gene affecting uterine capacity in unilaterally ovariectomized rabbits

The presence of a major gene for uterine capacity (UC), ovulation rate (OR), number of implanted embryos (IE), embryo survival (ES), fetal survival (FS), and prenatal survival (PS) was investigated in a population of rabbits divergently selected for UC for 10 generations. Selection was performed on estimated breeding values for UC up to four parities. UC was estimated as litter size in the remaining overcrowded horn of unilaterally ovariectomized does. OR and IE were counted by means of laparoscopy. Bartlett's test, Fain's test, and a complex segregation analysis using Bayesian methods were used to test for the presence of a major gene. All three tests showed that the data appeared consistent with the presence of a major gene affecting UC and IE. The results of the complex segregation analysis suggested the presence of a major gene with large effect on IE and ES (a > 1sigma(p)), at high frequency (p = 0.70 and 0.68, respectively), and with a large contribution to the total variance (R(g) = 0.39 and 0.47, respectively); and the presence of a major gene with moderate effect on each of OR, FS, PS, and UC. The results suggest that the studied reproductive traits are determined genetically by at least one gene of large effect.

Estimation of linkage disequilibrium in a sample of the United Kingdom dairy cattle population using unphased genotypes

The association between genetic marker alleles was estimated for two regions of the bovine genome from a random sample of 50 young dairy bulls born in the United Kingdom between 1988 and 1995. Microsatellite marker genotypes were obtained for six markers on chromosome 2 and seven markers on chromosome 6, spanning 38 and 20 cM, respectively. Two different methods, which do not require family information, were used to estimate population haplotype frequencies. Haplotype frequencies were estimated for pairs of loci using the expectation-maximization algorithm and for all linked loci using a Bayesian approach via a Markov chain-Monte Carlo algorithm. Significant (P = 0.0007) linkage disequilibrium was detected between pairs of loci in syntenic groups (that is, loci in the same linkage group), extending to about 10 cM. No significant linkage disequilibrium was detected between markers in nonsyntenic regions. Given the observed level of linkage disequilibrium, mapping methods based on population-wide association might provide a better resolution than traditional quantitative trait loci mapping methods in the U.K. dairy cattle population and may reduce the required sample sizes of the experiments.

A genome scan for quantitative trait loci in a wild population of red deer (Cervus elaphus)

Recent empirical evidence indicates that although fitness and fitness components tend to have low heritability in natural populations, they may nonetheless have relatively large components of additive genetic variance. The molecular basis of additive genetic variation has been investigated in model organisms but never in the wild. In this article we describe an attempt to map quantitative trait loci (QTL) for birth weight (a trait positively associated with overall fitness) in an unmanipulated, wild population of red deer (Cervus elaphus). Two approaches were used: interval mapping by linear regression within half-sib families and a variance components analysis of a six-generation pedigree of >350 animals. Evidence for segregating QTL was found on three linkage groups, one of which was significant at the genome-wide suggestive linkage threshold. To our knowledge this is the first time that a QTL for any trait has been mapped in a wild mammal population. It is hoped that this study will stimulate further investigations of the genetic architecture of fitness traits in the wild.

Simple deterministic identity-by-descent coefficients and estimation of QTL allelic effects in full and half sibs

Accurate and rapid methods for the detection of quantitative trait loci (QTLs) and evaluation of consequent allelic effects are required to implement marker-assisted selection in outbred populations. In this study, we present a simple deterministic method for estimating identity-by-descent (IBD) coefficients in full- and half-sib families that can be used for the detection of QTLs via a variance-component approach. In a simulated dataset, IBD coefficients among sibs estimated by the simple deterministic and Markov chain Monte Carlo (MCMC) methods with three or four alleles at each marker locus exhibited a correlation of greater than 0.99. This high correlation was also found in QTL analyses of data from an outbred pig population. Variance component analysis used both the simple deterministic and MCMC methods to estimate IBD coefficients. Both procedures detected a QTL at the same position and gave similar test statistics and heritabilities. The MCMC method, however, required much longer computation than the simple method. The conversion of estimated QTL genotypic effects into allelic effects for use in marker-assisted selection is also demonstrated.

Estimation of pedigree errors in the UK dairy population using microsatellite markers and the impact on selection

The proportion of cows in the UK dairy herd whose sires were misidentified was estimated using DNA markers. Genetic marker genotypes were determined on 568 cows (from 168 milk samples and 400 hair samples) and 96 putative sires (from semen samples). The estimated pedigree error rate from the hair samples was 8.8%, and from the milk samples, 13.1%, giving an overall estimate of the error rate of 10%. This level of pedigree errors will have a relatively large impact on the efficiency of progeny testing and the accuracy of cow predicted breeding values. We predict a loss of response to selection of approximately 2 to 3% given this error rate.

Heritability, reliability of genetic evaluations and response to selection in proportional hazard models

The purposes of this study were 1) to investigate the heritability, reliability, and selection response for survival traits following a Weibull frailty proportional hazard model; and 2) to examine the relationship between genetic parameters from a Weibull model, a discrete proportional hazard model, and a binary data analysis using a linear model. Both analytical methods and Monte Carlo simulations were used to achieve these aims. Data were simulated using the Weibull frailty model with two different shapes of the Weibull distribution. Breeding values of 100 unrelated sires with 50 to 100 progeny (with different levels of censoring) were generated from a normal distribution and two different sire variances. For analysis of longevity data on the discrete scale, simulated data were transformed to a discrete scale using arbitrary ends of discrete intervals of 400, 800, or 1200 d. For binary data analysis, an individual's longevity was either 0 (when longevity was less than the end of interval) or 1 (when longevity was equal or greater than the end of interval). Three different statistical models were investigated in this study: a Weibull model, a discrete-time model (a proportional hazard model assuming that the survival data are measured on a discrete scale with few classes), and a linear model based upon binary data. An alternative derivation using basic expressions of reliabilities in sire models suggests a simple equation for the heritability on the original scale (effective heritability) that is not dependent on the Weibull parameters. The predictions of reliabilities using the proposed formulae in this study are in very good agreement with reliabilities observed from simulations. In general, the estimates of reliability from either the discrete model or the binary data analysis were close to estimates from the Weibull model for a given number of uncensored records in this simplified case of a balanced design. Although selection response from the binary data analysis depends on the end of interval point, there is a relatively good agreement between selection responses in the Weibull model and the binary data analysis. In general, when the underlying survival data is from a Weibull distribution, it appears that the method of analyzing data does not greatly affect the results in terms of sire ranking or response to selection, at least for the simplified context considered in this study.

Contrasting models for lactation curve analysis

Several statistical models have been proposed for the genetic evaluation of production traits in dairy cattle based on test-day records. Three main approaches have been put forward in the literature: random regression, orthogonal polynomials, and, more recently, character process models. The aim of this paper is to show how these different approaches are related, to compare their performance for the genetic analysis of lactation curves, and to assess equivalence between sire and animal models for repeated measures analyses. It was found that, with an animal model, a character process model with 11 parameters performed better, regarding the likelihood criterion, than a quartic random regression model (with 31 parameters). However, although the likelihood was higher, the genetic variance was very different with the character process model from the unstructured model, which raises important issues concerning model selection criteria. There are advantages in combining methodologies. A quadratic random regression model for the environmental part, combined with a character process model for the residual, performed better than the quartic random regression model and had fewer parameters. A character process structure allowing for a correlation pattern modeled the residual better than a simple quadratic variance, and had only one extra parameter.

Parental assignment in fish using microsatellite genetic markers with finite numbers of parents and offspring

Deterministic predictions for the proportion of offspring assigned to different numbers of parent-pairs are developed in order to investigate the power of microsatellite loci for parental assignment in fish species. Comparisons with stochastic simulation results show that predictions based on exclusion probabilities are accurate, provided that the number of parents involved in the crosses is large. Accounting for sampling of parents gave very accurate predictions for a small number of parents and a single biallelic locus. For large numbers of loci or large numbers of alleles per locus stochastic simulations are, however, the only available method to predict the power of assignment of a particular set of loci when the number of parents is small. Nine 5-allele loci or six 10-allele loci with equifrequent alleles, are sufficient for assigning, with certainty, parents to 99% of the fish resulting from either 100 or 400 crosses. Results simulating a set of highly polymorphic microsatellites developed for Atlantic salmon show that the four most informative loci are sufficient to assign at least 99% of the offspring to the correct pair with 100 crosses involving 100 males and 100 females. An additional locus is required for correctly assigning 99% of the offspring when the 100 crosses are produced with 10 males and 10 females.

Power of regression and maximum likelihood methods to map QTL from sib-pair and DZ twin data

A common study design to map quantitative trait loci (QTL) is to compare the phenotypes and marker genotypes of two or more siblings in a sample of unrelated sib groups, and to test for linkage between chromosome location and quantitative trait values. The simplest case is sib pairs only, in particular dizygotic twin pairs, and a simple and elegant regression method was proposed by Haseman & Elston in 1972 to test for linkage. Since then, several other methods have been proposed to test for linkage. In this study, we derived the statistical power of linear regression and maximum likelihood methods to map QTL from sib pair data analytically, and determined which methods are superior under which set of population parameters. In particular, we considered four regression-based and three maximum likelihood-based approaches, and derived asymptotic approximations of the mean test statistic and statistical power for each method. It was found, both analytically and by computer simulation, that the revisited or new Haseman-Elston method (based upon the mean-corrected crossproduct of the observations on sib-pairs) is less powerful than a full maximum likelihood approach and is also inferior to the Haseman-Elston method under a realistic range of values for the population parameters. We found that a simple regression method, based upon both the squared difference and the mean-corrected squared sum of the observations on sib-pairs, is as powerful as a full maximum likelihood approach. Our derivations of statistical power for regression and maximum likelihood methods provide a simple way to compare alternative methods and obviate the need to perform elaborate computer simulations. DZ twin pairs are likely to be more powerful for linkage analysis than ordinary siblings because they may share more common environmental effects, thereby increasing the proportion of within-family variance that is explained by a QTL.

Genetic survival analysis of age-at-onset of bipolar disorder: evidence for anticipation or cohort effect in families

Age-at-onset (AAO) in a number of extended families ascertained for bipolar disorder was analysed using survival analysis techniques, fitting proportional hazards models to estimate the fixed effects of sex, year of birth, and generation, and a random polygenic genetic effect. Data comprised the AAO (for 171 affecteds) or age when last seen (ALS) for 327 unaffecteds, on 498 individuals in 27 families. ALS was treated as the censored time in the statistical analyses. The majority of individuals classified as affected were diagnosed with bipolar I and II (n = 103) or recurrent major depressive disorder (n = 68). In addition to the significant effects of sex and year of birth, a fitted 'generation' effect was highly significant, which could be interpreted as evidence for an anticipation effect. The risk of developing bipolar or unipolar disorder increased twofold with each generation descended from the oldest founder. However, although information from both affected and unaffected individuals was used to estimate the relative risk of subsequent generations, it is possible that the results are biased because of the 'Penrose effect'. Females had a twofold increased risk in developing depressive disorder relative to males. The risk of developing bipolar or unipolar disorder increased by approximately 4% per year of birth. A polygenic component of variance was estimated, resulting in a 'heritability' of AAO of approximately 0.52. In a family showing strong evidence of linkage to chromosome 4p (family 22), the 'affected haplotype' increased the relative risk of being affected by a factor of 46. In this family, there was strong evidence of a time trend in the AAO. When either year of birth or generation was fitted in the model, these effects were highly significant, but neither was significant in the presence of the other. For this family, there was no increase in trinucleotide repeats measured by the repeat expansion detection method in affected individuals compared with control subjects. Proportional hazard models appear appropriate to analyse AAO data, and the methodology will be extended to map quantitative trait loci (QTL) for AAO.

Genetic studies of bipolar affective disorder in large families

BACKGROUND

Genetic factors are known to be important in the aetiology of bipolar disorder.

AIMS

To review linkage studies in extended families multiply affected with bipolar disorder.

METHOD

Selective review of linkage studies of bipolar disorder emphasising the gains and drawbacks of studying large multiply-affected families and comparing the statistical methods used for data analysis.

RESULTS

Linkage of bipolar disorder to several chromosome regions including 4p, 4q, 10p, 12q, 16p, 18q, 21q and Xq has first been reported in extended families. In other families chromosomal rearrangements associated with affective illnesses provide signposts to the location of disease-related genes. Statistical analyses using variance component methods can be applied to extended families, require no prior knowledge of the disease inheritance, and can test multilocus models.

CONCLUSION

Studying single large pedigrees combined with variance component analysis is an efficient and effective strategy likely to lead to further insights into the genetic basis of bipolar disorders.

Genetic studies of bipolar affective disorder in large families

Background Genetic factors are known to be important in the aetiology of bipolar disorder. Aims To review linkage studies in extended families multiply affected with bipolar disorder. Method Selective review of linkage studies of bipolar disorder emphasising the gains and drawbacks of studying large multiply-affected families and comparing the statistical methods used for data analysis. Results Linkage of bipolar disorder to several chromosome regions including 4p, 4q, 10p, 12q, 16p, 18q, 21q and Xq has first been reported in extended families. In other families chromosomal rearrangements associated with affective illnesses provide signposts to the location of disease-related genes. Statistical analyses using variance component methods can be applied to extended families, require no prior knowledge of the disease inheritance, and can test multilocus models. Conclusion Studying single large pedigrees combined with variance component analysis is an efficient and effective strategy likely to lead to further insights into the genetic basis of bipolar disorders.

Bias and Power in the Estimation of a Maternal Family Variance Component in the Presence of Incomplete and Incorrect Pedigree Information

Several studies over the last 15 yr have estimated the magnitude of cytoplasmic inheritance of production and type traits in dairy cattle. Pedigree information can be used to assign maternal lineages, and the between-maternal lineage variance is then assumed to be an estimate of cytoplasmic inheritance. Two potential sources of bias and reduction of the power of estimation of cytoplasmic inheritance using such a method are 1) incomplete and 2) incorrect pedigree information being used in the assignment of maternal lineages. The theoretical bias introduced by these two sources of error is investigated and the results of a simulation study varying the number of families, the percentage of pedigree errors, and the level of incomplete lineage assignment are presented. Pedigree errors were found to have the biggest impact. A pedigree error rate of 8% per generation would result in a 75% reduction in the estimable magnitude of a 5% true component of variance after nine generations. The effect that these mechanisms have on the power of estimation are discussed and investigated by simulation. It was concluded that using historical pedigree, with incomplete and incorrect maternal family information, to assign maternal lineage would cause a downward bias in the magnitude of the cytoplasmic effect estimated. In the future, it will be possible to overcome pedigree problems by using molecular information to directly assign cytoplasmic lineage groups.

Mapping quantitative trait loci in complex pedigrees: a two-step variance component approach

There is a growing need for the development of statistical techniques capable of mapping quantitative trait loci (QTL) in general outbred animal populations. Presently used variance component methods, which correctly account for the complex relationships that may exist between individuals, are challenged by the difficulties incurred through unknown marker genotypes, inbred individuals, partially or unknown marker phases, and multigenerational data. In this article, a two-step variance component approach that enables practitioners to routinely map QTL in populations with the aforementioned difficulties is explored. The performance of the QTL mapping methodology is assessed via its application to simulated data. The capacity of the technique to accurately estimate parameters is examined for a range of scenarios.

Combined analyses of data from quantitative trait loci mapping studies. Chromosome 4 effects on porcine growth and fatness

For many species several similar QTL mapping populations have been produced and analyzed independently. Joint analysis of such data could be used to increase power to detect QTL and evaluate population differences. In this study, data were collated on almost 3000 pigs from seven different F(2) crosses between Western commercial breeds and either the European wild boar or the Chinese Meishan breed. Genotypes were available for 31 markers on chromosome 4 (on average 8.3 markers per population). Data from three traits common to all populations (birth weight, mean backfat depth at slaughter or end of test, and growth rate from birth to slaughter or end of test) were analyzed for individual populations and jointly. A QTL influencing birth weight was detected in one individual population and in the combined data, with no significant interaction of the QTL effect with population. A QTL affecting backfat that had a significantly greater effect in wild boar than in Meishan crosses was detected. Some evidence for a QTL affecting growth rate was detected in all populations, with no significant differences between populations. This study is the largest F(2) QTL analysis achieved in a livestock species and demonstrates the potential of joint analysis.