Genetics of milking characteristics in dairy cows

Genetic selection for milking speed is feasible. The existence of a correlation structure between milking speed and milk yield, however, necessitates a selection strategy to increase milking speed with no repercussion on genetic merit for milk yield. Residual milking duration (RMD) and residual milking duration including somatic cell score (RMDS), defined as the residuals from a regression model of milking duration on milk yield or milk yield plus somatic cell score (SCS) have been advocated. The objective of this study was to undertake a first ever genetic analysis of these novel traits. Data on electronically recorded milking duration and other milking characteristics from 235 005 test-day records on 74 608 cows in 1075 Irish dairy herds were available. Variance components for the milking characteristic traits were estimated using animal linear mixed models and covariances with other performance traits, including udder-related type traits, were estimated using sire models. The heritability of milking duration, RMD and RMDS was 0.20, 0.22 and 0.18, respectively. There were little differences in the heritability of RMD or RMDS when defined using genetic regression. The genetic standard deviation of RMDS defined on the phenotypic or genetic level was 36.8 s and 37.6 s, respectively, clearly indicating considerable exploitable genetic variation in milking duration independent of both milk yield and SCS. The genetic correlation between phenotypically derived RMDS and milk yield was favourable (−0.43), but RMDS was unfavourably genetically correlated with SCS (−0.30); the genetic correlations with both traits when RMDS was defined at a genetic level were zero. RMDS defined at the phenotypic level was negatively (i.e. unfavourable) genetically correlated (−0.35; s.e. = 0.15) with mastitis; however, when defined using genetic regression, shorter RMDS was not associated with greater expected incidence of mastitis. RMDS, defined at the genetic level, is a useful heritable trait with ample genetic variation for inclusion in a national breeding strategy without influencing genetic gain in either milk yield or udder health.     

Bayesian segregation analysis of milk flow in Swiss dairy cattle using Gibbs sampling

Segregation analyses with Gibbs sampling were applied to investigate the mode of inheritance and to estimate the genetic parameters of milk flow of Swiss dairy cattle. The data consisted of 204 397, 655 989 and 40 242 lactation records of milk flow in Brown Swiss, Simmental and Holstein cattle, respectively (4 to 22 years). Separate genetic analyses of first and multiple lactations were carried out for each breed. The results show that genetic parameters especially polygenic variance and heritability of milk flow in the first lactation were very similar under both mixed inheritance (polygenes + major gene) and polygenic models. Segregation analyses yielded very low major gene variances which favour the polygenic determinism of milk flow. Heritabilities and repeatabilities of milk flow in both Brown Swiss and Simmental were high (0.44 to 0.48 and 0.54 to 0.59, respectively). The heritability of milk flow based on scores of milking ability in Holstein was intermediate (0.25). Variance components and heritabilities in the first lactation were slightly larger than those estimates for multiple lactations. The results suggest that milk flow (the quantity of milk per minute of milking) is a relevant measurement to characterise the cows milking ability which is a good candidate trait to be evaluated for a possible inclusion in the selection objectives in dairy cattle.     

Genetic relationship among somatic cell score and some milking traits in Holstein-Friesian primiparous cows milked by an automated milking system

The automated milking system provides breeders with a large amount of automatically collected information about each cow in herd that cannot be easily obtained in non-robotised systems. This knowledge can be used in breeding programs improving somatic cell count (SCC) level. The objective of this study was to estimate heritabilities and genetic correlations among test-day (TD) somatic cell score (SCS) and selected milking traits, such as daily milk yield (MY), milking frequency (MF), milking time (MT) and milking speed (MS), attachment time (AT) to single teat cups, electrical conductivity (EC) and milk temperature (MTEMP). Data were collected for 1 899 Polish Holstein-Friesian primiparous cows milked in an automatic milking system. Genetic parameters of the studied traits were estimated using Bayesian method via Gibbs sampling and two-trait random regression animal model with fixed effect of herd x TD, fixed regressions on days in milk (DIM) nested within age at calving by season of calving and RR for additive genetic and permanent environmental effects. Both fixed and RR were fitted with fourth-order Legendre polynomials on DIM. The estimated daily heritabilities were in the following ranges: MY – 0.162–0.338, MF – 0.156–0.444, MT – 0.090–0.320, MS – 0.252–0.665, AT – 0.105–0.394, EC – 0.269–0.466, MTEMP – 0.135–0.304 and SCS – 0.155–0.321. The heritabilities for traits expressed on a 305-d basis were moderate to high: 0.460 for MY, 0.514 for MF, 0.315 for MT, 0.431 for MS, 0.256 for AT, 0.386 for EC, 0.407 for MTEMP and 0.359 for SCS. Genetic correlations between traits on a 305-d basis showed that SCS was most strongly genetically correlated with MTEMP (0.572) and MS (0.480), whereas genetic relationships of SCS with MT (0.221) and EC (− 0.216) were moderate. Phenotypic correlations between traits on a 305-d basis were moderate or low. Somatic cell score was negatively phenotypically correlated with MY, MF and MT, with the highest relationship with MT (− 0.302). The largest positive phenotypic correlations were observed between SCS and MS (0.311) and with MTEMP (0.286). In summary, it is concluded that there is a chance to carry out effective selection for lower SCS and for some other traits, in particular MS and MTEMP. The obtained results are promising enough to conduct further research to evaluate how these traits can be used both to increase the accuracy of genetic evaluations of SCC and to improve udder health.     

Major recessive gene(s) with considerable residual polygenic effect regulating adult height: confirmation of genomewide scan results for chromosomes 6, 9, and 12

Segregation and linkage analyses were performed for adult height in a population of 200 Dutch families, each of which was ascertained through a proband with asthma. The best-fit model from the segregation analysis was a major recessive gene with a significant residual polygenic background. Models without a polygenic component were rejected. A genomewide scan was performed, and it confirmed previous linkage results for chromosomes 6q25 (LOD = 3.06, D6S2436), 9p1 (LOD = 2.09, D9S301), and 12q1 (LOD = 1.86, D12S375). Our results provide evidence that a combination of segregation and linkage approaches is valuable in understanding genetic determination of common complex traits.     

Evidence that a single gene with gender- and age-dependent effects influences systolic blood pressure determination in a population-based sample.

A biometrical study was carried out to evaluate the role of genetic variation in determining interindividual differences in systolic blood pressure (SBP) in the population at large. SBP was measured in 1,266 Caucasian individuals in 278 pedigrees ascertained through children enrolled in the Rochester, MN, school system. The sample included 646 males and 620 females 550 years of age and not taking antihypertensive medication or oral contraceptives. Complex segregation analysis was first applied to these data by using a regression model for age, in which the intercept was gender and ousiotype specific but in which the slope was only gender specific. When the slope was independent of ousiotype, neither variation at a single gene combined with polygenic effects (mixed genetic model) nor variation in a single environmental factor combined with polygenetic effects (mixed environmental model) explained the distribution of SBP in this sample. However, when the regression model for age allowed both the intercept and slope to be gender and ousiotype specific, the mixed environmental model was rejected whereas the mixed genetic model was not. These results suggest that variability in SBP may be influenced by major effects of allelic variation at a single gene that are both gender and age dependent. This study (1) suggests that particular genotypes determined by a single gene are associated with a steeper increase of SBP with age among males and females 550 years of age in the general population and (2) illustrates the need to consider models that more realistically represent the relationship between genotypic variability and phenotypic variability, to understand the genetics of human quantitative traits.     

Multifactorial genetic models for quantitative traits in humans.

Quantitative traits measured in human families can be analyzed to partition the total population variance into genetic and environmental components, or to elucidate the genetic mechanism involved. We review the estimation of variance components directly from human pedigree data, or in the form of path coefficients from correlations between pairs of relatives. To elucidate genetic mechanisms, a mixed model that allows for segregation at a major locus, a polygenic effect and a sibling environmental correlation is described for nuclear families. In each case appropriate likelihoods are derived as a basis, using numerical maximum likelihood methods, for parameter estimation and hypothesis testing. A general model is then described that allows for several familial sources of environmental variation, assortative mating, and both major gene and polygenic effects; and an algorithm for calculating the likelihood of a pedigree under this model is indicated. Finally, some of the remaining problems in this area of biometric analysis are pointed out.     

Genetic relationship between milk urea nitrogen and reproductive performance in Holstein dairy cows

The objective of this study was to describe the genetic and phenotypic relationship between milk urea nitrogen (MUN) and reproductive traits in Iranian Holstein dairy cows. Test-day MUN data obtained from 57 301 dairy cows on 20 large dairy herds in Iran between January 2005 and June 2009. Genetic parameters for MUN and reproductive traits were estimated with a five-trait model using ASREML program. Random regression test-day models were used to estimate heritabilities separately for MUN from first, second and third lactations. Regression curves were modeled using Legendre polynomials of order 3. Herd-year-season along with age at calving was included as fixed effects in all models for reproductive traits. Heritabilities for MUN and reproductive traits were estimated separately for first lactation, second lactation and third lactation. The estimated heritabilities for MUN varied from 0.18 to 0.22. The heritability estimate was low for reproductive traits, which ranged from 0.02 to 0.06 for different traits and across parities. Except for days open, phenotypic and genetic correlations of MUN with reproductive performance traits were close to zero. Genetic correlations between MUN and days open were 0.23, 0.35 and 0.45 in first, second and third lactation, respectively. However, the phenotypic correlation between MUN at different parities was moderate (0.28 to 0.35), but the genetic correlation between MUN at different parities was high and ranged from 0.84 to 0.97. This study shows a limited application of MUN for use in selection programs to improve reproductive performance.     

Investigation of major gene for milk yield, milking speed, dry matter intake, and body weight in dairy cattle

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.     

A common genetic mechanism determines plasma apolipoprotein B levels and dense LDL subfraction distribution in familial combined hyperlipidemia.

Familial combined hyperlipidemia (FCH) is a common lipid disorder characterized by elevations of plasma cholesterol and/or triglyceride in first-degree relatives. A predominance of small, dense LDL particles and elevated apolipoprotein B (apoB) levels is commonly found in members of FCH families. Many studies have investigated the genetic mechanisms determining individuals' lipid levels, in FCH families. Previously, we demonstrated a major gene effect on LDL particle size and codominant Mendelian inheritance involved in determination of apoB levels in a sample of 40 well-defined FCH families. An elevation of apoB levels is associated metabolically with a predominance of small, dense LDL particles in FCH. To establish whether a common gene regulates both traits, we conducted a bivariate genetic analysis to test the hypothesis of a common genetic mechanism. In this study, we found that 66% of the total phenotypic correlation is due to shared genetic components. Further bivariate segregation analysis suggested that both traits share a common major gene plus individual polygenic components. This common major gene explains 37% of the variance of adjusted LDL particle size and 23% of the variance of adjusted apoB levels. Our study suggests that a major gene that has pleiotropic effects on LDL particle size and apoB levels may be the gene underlying FCH in the families we studied.     

利用DH或RIL群体检测QTL体系并估计其遗传效应

利用ＤＨ和ＲＩＫＬ群体并结合重复内分组随机区组设计对和物产量等遗传率较低的数量性状进行分离分析可提高遗传分析的精度。根据混合分布理论菜了利用ＤＨ或ＲＩＬ群体重复实验数据鉴定数量性状混合遗传模型的分离分析法,特别是２对链锁主基因＋多基因模型。该方法可鉴定数量性状的遗传模型和主基因的作用方式,估计主基因、多基因的遗传疚和遗传方差,在两主基因存在连锁可可估计其重组率。下面通过应用举例说明该方法。     

A blocking Gibbs sampling method to detect major genes with phenotypic data from a diallel mating

Diallel mating is a frequently used design for estimating the additive and dominance genetic (polygenic) effects involved in quantitative traits observed in the half- and full-sib progenies generated in plant breeding programmes. Gibbs sampling has been used for making statistical inferences for a mixed-inheritance model (MIM) that includes both major genes and polygenes. However, using this approach it has not been possible to incorporate the genetic properties of major genes with the additive and dominance polygenic effects in a diallel mating population. A parent block Gibbs sampling method was developed in this study to make statistical inferences about the major gene and polygenic effects on quantitative traits for progenies derived from a half-diallel mating design. Using simulated data sets with different major and polygenic effects, the proposed method accurately estimated the major and polygenic effects of quantitative traits, and possible genotypes of parents and progenies. The impact of specifying different prior distributions was examined and was found to have little effect on inference on the posterior distribution. This approach was applied to an experimental data set of Loblolly pine (Pinus taeda L.) derived from a 6-parent half-diallel mating. The result indicated that there might be a recessive major gene affecting height growth in this diallel population.     

Incorporation of genotype effects into animal model evaluations when only a small fraction of the population has been genotyped

The method of Israel and Weller (Estimation of candidate gene effects in dairy cattle populations. Journal of Dairy Science 1998, 81, 1653-1662) to estimate quantitative trait locus (QTL) effects when only a small fraction of the population was genotyped was investigated by simulation. The QTL effect was underestimated in all cases, but bias was greater for extreme allelic frequencies, and increased with the number of generations included in the simulations. Apparently, as the fraction of animals with inferred genotypes increases, the genotype probabilities tend to 'mimic' the effect of relationships. Unbiased estimates of QTL effects were derived by a modified 'cow model' without the inclusion of the relationship matrix on simulated data, even though only a small fraction of the population was genotyped. This method yielded empirically unbiased estimates for the effects of the genes DGAT1 and ABCG2 on milk production traits in the Israeli Holstein population. Based on these results, an efficient algorithm for marker-assisted selection in dairy cattle was proposed. Quantitative trait loci effects are estimated and subtracted from the cows' records. Genetic evaluations are then computed for the adjusted records. Animals are then selected based on the sum of their polygenic genetic evaluations and QTL effects. This scheme differs from a traditional dairy cattle breeding scheme in that all bull calves were considered candidates for selection. At year 10, total genetic gain was 20% greater by the proposed algorithm as compared to the selection based on a standard animal model for a locus with a substitution effect of 0.5 phenotypic standard deviations. The proposed method is easy to apply, and all required software are 'on the shelf.' It is only necessary to genotype breeding males, which are a very small fraction of the entire population. The method is flexible with respect to the model used for routine genetic evaluation. Any number of genetic markers can be easily incorporated into the algorithm, and the reduction in genetic gain due to incorrect QTL determination is minimal.     

Genetic complexity and quantitative trait loci mapping of yeast morphological traits

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes.     

Genetic and phenotypic correlations among feed efficiency,production and selected conformation traits in dairy cows

The difficulties and costs of measuring individual feed intake in dairy cattle are the primary factors limiting the genetic study of feed intake and utilisation, and hence the potential of their subsequent industry-wide applications. However, indirect selection based on heritable, easily measurable, and genetically correlated traits, such as conformation traits, may be an alternative approach to improve feed efficiency. The aim of this study was to estimate genetic and phenotypic correlations among feed intake, production, and feed efficiency traits (particularly residual feed intake; RFI) with routinely recorded conformation traits. A total of 496 repeated records from 260 Holstein dairy cows in different lactations (260, 159 and 77 from first, second and third lactation, respectively) were considered in this study. Individual daily feed intake and monthly BW and body condition scores of these animals were recorded from 5 to 305 days in milk within each lactation from June 2007 to July 2013. Milk yield and composition data of all animals within each lactation were retrieved, and the first lactation conformation traits for primiparous animals were extracted from databases. Individual RFI over 301 days was estimated using linear regression of total 301 days actual energy intake on a total of 301 days estimated traits of metabolic BW, milk production energy requirement, and empty BW change. Pair-wise bivariate animal models were used to estimate genetic and phenotypic parameters among the studied traits. Estimated heritabilities of total intake and production traits ranged from 0.27±0.07 for lactation actual energy intake to 0.45±0.08 for average body condition score over 301 days of the lactation period. RFI showed a moderate heritability estimate (0.20±0.03) and non-significant phenotypic and genetic correlations with lactation 3.5 % fat-corrected milk and average BW over lactation. Among the conformation traits, dairy strength, stature, rear attachment width, chest width and pin width had significant (P<0.05) moderate to strong genetic correlations with RFI. Combinations of these conformation traits could be used as RFI indicators in the dairy genetic improvement programmes to increase the accuracy of the genetic evaluation of feed intake and utilisation included in the index.     

Fluctuating asymmetry as a possible measure of developmental homeostasis in humans: a review

We investigate three hypotheses related to fluctuating asymmetry (FA) of bilateral morphologic traits in humans: (1) the magnitude of FA in individual suffering from different levels of morbidity is significantly elevated compared with FA in healthy control subjects, (2) FA is negatively correlated with an individual's heterozygosity, and (3) phenotypic variance of FA may have a significant genetic component (or at least a family resemblance). Our experimental data and the literature support the first hypothesis and indicate that individuals who suffer from chromosomal or polygenic morbidity and from anomalies or conditions of development with still unknown genetic components demonstrate an elevated FA of various structures. The literature regarding the second hypothesis is sparse but is generally in agreement with it, although some exceptions exist. A study of correlations of phenotypic scores of FA between family members of nuclear families in two independent samples has shown that FA variance in individual traits probably does not have any significant genetic component. However, phenotypic variance of the mean estimate of FA over 8 traits showed significant additive and nonadditive (dominance) genetic components, each about 0.30.     

Robot utilisation of pasture-based dairy cows with varying levels of milking frequency

Achieving a consistent level of robot utilisation throughout 24 h maximises automatic milking system (AMS) utilisation. However, levels of robot utilisation in the early morning hours are typically low, caused by the diurnal feeding behaviour of cows, limiting the inherent capacity and total production of pasture-based AMS. Our objective was to determine robot utilisation throughout 24 h by dairy cows, based on milking frequency (MF; milking events per animal per day) in a pasture-based AMS. Milking data were collected from January and February 2013 across 56 days, from a single herd of 186 animals (Bos taurus) utilising three Lely A3 robotic milking units, located in Tasmania, Australia. The dairy herd was categorised into three equal sized groups (n=62 per group) according to the cow’s mean daily MF over the duration of the study. Robot utilisation was characterised by an interaction (P< 0.001) between the three MF groups and time of day, with peak milking time for high MF cows within one h of a fresh pasture allocation becoming available, followed by the medium MF and low MF cows 2 and 4 h later, respectively. Cows in the high MF group also presented for milking between 2400 and 0600 h more frequently (77% of nights), compared to the medium MF group (57%) and low MF group (50%). This study has shown the formation of three distinct groups of cows within a herd, based on their MF levels. Further work is required to determine if this finding is replicated across other pasture-based AMS farms.     

Pleiotropic Relationships between Cortisol Levels and Adiposity: The HERITAGE Family Study

Objective: To investigate familial basis for the relationship between cortisol adiposity at baseline and their training responses. Research Methods and Procedures: Bivariate correlation and segregation analyses were employed between cortisol and several adiposity measures [body mass index, fat mass (FM), fat-free mass, percentage of body fat (% BF), abdominal visceral fat (AVF), abdominal subcutaneous fat (ASF), and abdominal total fat (ATF)] from 99 white families and 105 black families. Results: In both races, significant inverse phenotypic correlations were generally observed between cortisol and adiposity measures at baseline but not for training responses. Significant cross-trait familial correlations were found for cortisol with abdominal fat (ASF, AVF, ATF) and overall body adiposity (FM, % BF) measures at baseline, which accounted for 14% to 20% of the phenotypic variance in whites. The cross-trait correlations were not significant for baseline phenotypes in blacks, perhaps because of the small sample size. A bivariate segregation analysis showed evidence of polygenic pleiotropy for cortisol with both abdominal fat and overall adiposity measures that accounted for 14% to 17% of the phenotypic covariance, but major gene pleiotropy was not suggested in whites. However, when ASF, AVF, and ATF were additionally adjusted for FM, no familial cross-trait correlations or polygenic pleiotropy between cortisol and the abdominal fat measures remained. Discussion: Evidence was found for polygenic pleiotropy but not for pleiotropic major gene effects between cortisol and overall adiposity in whites. However, the covariation of cortisol with abdominal fat phenotypes is dependent on concomitant polygenic factors for total-body fat.     

The construction of a genetic linkage map of red raspberry (Rubus idaeus subsp. idaeus) based on AFLPs, genomic-SSR and EST-SSR markers

Breeding in raspberry is time-consuming due to the highly heterozygous nature of this perennial fruit crop, coupled with relatively long periods of juvenility. The speed and precision of raspberry breeding can be improved by genetic linkage maps, thus facilitating the development of diagnostic markers for polygenic traits and the identification of genes controlling complex phenotypes. A genetic linkage map (789 cM) of the red raspberry Rubus idaeus has been constructed from a cross between two phenotypically different cultivars; the recent European cultivar Glen Moy and the older North American cultivar Latham. SSR markers were developed from both genomic and cDNA libraries from Glen Moy. These SSRs, together with AFLP markers, were utilised to create a linkage map. In order to test the utility of the genetic linkage map for QTL analysis, morphological data based on easily scoreable phenotypic traits were collected. The segregation of cane spininess, and the root sucker traits of density and spread from the mother plant, was quantified in two different environments. These traits were analysed for significant linkages to mapped markers using MapQTL and were found to be located on linkage group 2 for spines and group 8 for density and diameter. The availability of co-dominant markers allowed heterozygosities to be calculated for both cultivars.     

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P₁ and P₂), F₁, F₂, and both backcross generations (B₁ and B₂) derived from crossing the F₁ to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes. Received: 18 August 2000 / Accepted: 9 March 2001     

Major-locus contributions to variability of the craniofacial feature dystopia canthorum in Waardenburg syndrome.

We used segregation analysis to investigate the genetic basis of variation in dystopia canthorum, one of the key diagnostic features of Waardenburg syndrome type 1 (WS1). We sought to determine whether the W-index, a quantitative measure of this craniofacial feature, is influenced primarily either by allelic variation in the PAX3 disease gene or other major loci, by polygenic background effects, or by all of these potential sources of genetic variation. We studied both WS1-affected individuals and their WS1-unaffected relatives. After adjustment of the W-index for WS1 disease status, segregation analyses by the regression approach indicated major-locus control of this variation, although residual parent-offspring and sib-sib correlations are consistent with additional (possibly polygenic) effects. Separate analyses of WS1-affected and WS1-unaffected individuals suggest that epistatic interactions between disease alleles at the PAX3 WS1 locus and a second major locus influence variation in dystopia canthorum. Our approach should be applicable for assessing the genetic architecture of variation associated with other genetic diseases.