Linkage and heritability analysis of migraine symptom groupings: a comparison of three different clustering methods on twin data

Migraine is a painful disorder for which the etiology remains obscure. Diagnosis is largely based on International Headache Society criteria. However, no feature occurs in all patients who meet these criteria, and no single symptom is required for diagnosis. Consequently, this definition may not accurately reflect the phenotypic heterogeneity or genetic basis of the disorder. Such phenotypic uncertainty is typical for complex genetic disorders and has encouraged interest in multivariate statistical methods for classifying disease phenotypes. We applied three popular statistical phenotyping methods—latent class analysis, grade of membership and grade of membership “fuzzy” clustering (Fanny)—to migraine symptom data, and compared heritability and genome-wide linkage results obtained using each approach. Our results demonstrate that different methodologies produce different clustering structures and non-negligible differences in subsequent analyses. We therefore urge caution in the use of any single approach and suggest that multiple phenotyping methods be used.     

Genomic prediction based on data from three layer lines: a comparison between linear methods

Background

The prediction accuracy of several linear genomic prediction models, which have previously been used for within-line genomic prediction, was evaluated for multi-line genomic prediction.

Methods

Compared to a conventional BLUP (best linear unbiased prediction) model using pedigree data, we evaluated the following genomic prediction models: genome-enabled BLUP (GBLUP), ridge regression BLUP (RRBLUP), principal component analysis followed by ridge regression (RRPCA), BayesC and Bayesian stochastic search variable selection. Prediction accuracy was measured as the correlation between predicted breeding values and observed phenotypes divided by the square root of the heritability. The data used concerned laying hens with phenotypes for number of eggs in the first production period and known genotypes. The hens were from two closely-related brown layer lines (B1 and B2), and a third distantly-related white layer line (W1). Lines had 1004 to 1023 training animals and 238 to 240 validation animals. Training datasets consisted of animals of either single lines, or a combination of two or all three lines, and had 30 508 to 45 974 segregating single nucleotide polymorphisms.

Results

Genomic prediction models yielded 0.13 to 0.16 higher accuracies than pedigree-based BLUP. When excluding the line itself from the training dataset, genomic predictions were generally inaccurate. Use of multiple lines marginally improved prediction accuracy for B2 but did not affect or slightly decreased prediction accuracy for B1 and W1. Differences between models were generally small except for RRPCA which gave considerably higher accuracies for B2. Correlations between genomic predictions from different methods were higher than 0.96 for W1 and higher than 0.88 for B1 and B2. The greater differences between methods for B1 and B2 were probably due to the lower accuracy of predictions for B1 (~0.45) and B2 (~0.40) compared to W1 (~0.76).

Conclusions

Multi-line genomic prediction did not affect or slightly improved prediction accuracy for closely-related lines. For distantly-related lines, multi-line genomic prediction yielded similar or slightly lower accuracies than single-line genomic prediction. Bayesian variable selection and GBLUP generally gave similar accuracies. Overall, RRPCA yielded the greatest accuracies for two lines, suggesting that using PCA helps to alleviate the “n ≪ p” problem in genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0057-5) contains supplementary material, which is available to authorized users.     

A simple method for estimating recombination percentages and linkage intensities from F2 data: examples from Triticum monococcum and other self-fertilizing diploid plant species

Summary We offer an alternative approach to the extensively used maximum likelihood and product methods for calculating recombination values and linkage intensities from F₂ data. This new method which we designate as the square root approach is simpler than the ones in current use in that it obviates the need for formulae and tables. It can be applied to autosomal F₂ data from F₁'s heterozygous in both the coupling and repulsion phases. It has greater applicability than the product method in that it can be used in all cases involving 2-, 3-, 4-, 6- and 9-class segregations regardless whether gene interaction occurs or not, provided the double recessive and other specific phenotypes are each determined by one particular genotype. The proposed method is based on the same well established genetic facts as the other two approaches. Percent recombinant gametes and therefore percent recombination are calculated by deriving the square root of the proportion of the F₂ population that expresses the double recessive or equivalent phenotype. The recombination values obtained by our method are compared with those derived by product method for 17 crosses in 7 different species and were found to be insignificantly different from the latter. The advantages and disadvantages of the square root method compared with the two most used ones are discussed.     

The evolution of alternative reproductive strategies: fitness differential, heritability, and genetic correlation between the sexes

Paternity analyses using molecular markers have become standard in studies of mating systems, parentage, and kinship. In systems where individuals exhibit alternative mating strategies, molecular analyses have been productively used to estimate the reproductive success of each behavioral type and hence the fitness consequences to each individual. Here we review the fitness results in a system of five alternative mating strategies present in one population of side-blotched lizards (Uta stansburiana). Males in this population adopt one of three behavioral strategies that differ in their degree of territoriality and mate guarding. In contrast, females adopt one of two strategies that differ in offspring quantity and quality. We use paternity analyses to estimate the fitness of each morph, the heritability of reproductive strategy, and the correlation in strategy between the sexes and discuss the implications of our findings for the evolution and maintenance of reproductive polymorphism in this and other systems.     

Extracting aquatic mites from stream substrates: a comparison of three methods

Aquatic mites (Hydrachnida, Oribatida, Halacaroidea) are diverse, and can reach high densities in the substrates of streams and rivers. Although they are a ubiquitous component of these habitats, their small size means that they are often overlooked. Using substrate samples from streams in tropical Queensland, I compared the thoroughness and time-based efficiency of three methods of extraction: sorting live samples without magnification (live-picking); exhaustive sorting of preserved samples using a dissecting microscope (microscope-picking); and kerosene-flotation of preserved samples followed by sorting with a dissecting microscope (kero-float). Live-picked samples yielded significantly fewer individuals and species than other methods, and were biased towards larger species. Oribatids and halacarids were not found when live-picking was used. Live-picking and kero-float methods provided similar numbers of mites per minute of sampling effort, whereas microscope-picking had a lower efficiency than kero-float. A combination of live-picking and kerosene-floatation is recommended for thorough surveys of stream acarofauna.     

Estimating repertoire size in a songbird: a comparison of three techniques

Many animals produce multiple types of breeding vocalizations that, together, constitute a vocal repertoire. In some species, the size of an individual’s repertoire is important because it correlates with brain size, territory size or social behaviour. Quantifying repertoire size is challenging because the long recordings needed to sample a repertoire comprehensively are difficult to obtain and analyse. The most basic quantification technique is simple enumeration, where one counts unique vocalization types until no new types are detected. Alternative techniques estimate repertoire size from subsamples, but these techniques are useful only if they are accurate. Using 12 years of acoustic data from a population of rufous-and-white wrens in Costa Rica, we used simple enumeration to measure the repertoire size for 40 males. We then compared these to the estimates generated by three estimation techniques: curve fitting, capture–recapture and a new technique based on the coupon collector’s problem. To understand how sampling effort affects the accuracy and precision of estimates, we applied each technique to six different-sized subsets of data per male. When averaged across subset sizes, the capture–recapture and coupon collector techniques showed the highest accuracy, whereas the curve fitting technique underestimated repertoire size. Precision (the average absolute difference between the estimated and true repertoire size) was significantly better for the capture–recapture technique than the coupon collector and curve fitting techniques. Both accuracy and precision improved as subset size increased. We conclude that capture–recapture is the best technique for estimating the sizes of small repertoires.     

Heritable variation and genetic correlation of quantitative traits within and between ecotypes of Avena barbata

We examined heritable variation for quantitative traits within and between naturally occurring mesic and xeric ecotypes of the slender wild oat (Avena barbata), and in 188 recombinant inbred lines derived from a cross between the ecotypes. We measured a suite of seedling and adult traits in the greenhouse, as well as performance-related traits in field sites native to the two ecotypes. Although the ecotypes were genetically diverged for most traits, few traits showed significant heritable variation within either ecotype. In contrast, considerable heritable variation was released in the recombinant progeny of the cross, and transgressive segregation was apparent in all traits. Heritabilities were substantially greater in the greenhouse than in the field, and this was associated with an increase in environmental variance in the field, rather than a decrease in genetic variance. Strong genetic correlations were evident among the recombinants, such that 22 measured traits could be well represented by only seven underlying factors, which accounted for 80% of the total variation. The primary axis of variation in the greenhouse described a trade-off between vegetative and reproductive allocation, mediated by the date of first flowering, and fitness was strongly correlated with this trade-off. Other factors in the greenhouse described variation in size and in seedling traits. Lack of correlation among these factors represents the release of multivariate trait variation through recombination. In the field, a separate axis of variation in overall performance was found for each year/site combination. Performance was significantly correlated across field environments, but not significantly correlated between greenhouse and field.     

MHC evolution in three salmonid species: a comparison between class II alpha and beta genes

The genes of the major histocompatibility complex (MHC) are amongst the most variable in vertebrates and represent some of the best candidates to study processes of adaptive evolution. However, despite the number of studies available, most of the information on the structure and function of these genes come from studies in mammals and birds in which the MHC class I and II genes are tightly linked and class II alpha exhibits low variability in many cases. Teleost fishes are among the most primitive vertebrates with MHC and represent good organisms for the study of MHC evolution because their class I and class II loci are not physically linked, allowing for independent evolution of both classes of genes. We have compared the diversity and molecular mechanisms of evolution of classical MH class II α and class II β loci in farm populations of three salmonid species: Oncorhynchus kisutch, Oncorhynchus mykiss and Salmo salar. We found single classical class II loci and high polymorphism at both class II α and β genes in the three species. Mechanisms of evolution were common for both class II genes, with recombination and point mutation involved in generating diversity and positive selection acting on the peptide-binding residues. These results suggest that the maintenance of variability at the class IIα gene could be a mechanism to increase diversity in the MHC class II in salmonids in order to compensate for the expression of one single classical locus and to respond to a wider array of parasites.     

Screening and genetic counseling for beta-thalassemia trait in a population unselected for interest: comparison of three counseling methods

We have assessed the effects of screening and genetic counseling for beta-thalassemia trait on knowledge, attitudes, and behavior in a prospective, controlled study of randomly selected adult members of a health maintenance organization. We report here that knowledge of manifestations and of inheritance of thalassemia, previously reported to be high immediately after counseling, were well maintained at 2 and 10 months following counseling. There was no detectable impairment of self-concept. Marital adjustment improved, and sexual activity increased significantly. Mood, assessed immediately before and after counseling, showed no undesirable changes. A patient-structured counseling method, designed to minimize negative psychological effects via discussion of feelings, was not superior to conventional and programmed methods, described in our previous reports, in terms of learning or attitude change.     

Estimating human long bone cross-sectional geometric properties: a comparison of noninvasive methods

Cross-sectional properties (areas, second moments of area) have been used extensively for reconstructing the mechanical loading history of long bone shafts. In the absence of a fortuitous break or available computed tomography (CT) facilities, the endosteal and/or periosteal boundaries of a bone may be approximated using alternative noninvasive methods. The present study tests whether cross-sectional geometric properties of human lower limb bones can be adequately estimated using two such techniques: the ellipse model method (EMM), which uses biplanar radiography alone, and the latex cast method (LCM), which involves molding of the subperiosteal contour in combination with biplanar radiography to estimate the contour of the medullary canal. Results of both methods are compared with "true" cross-sectional properties calculated by direct sectioning. The study sample includes matched femora and tibiae of 50 Pecos Pueblo Amerindians. Bone areas and second moments of area were calculated for the midshaft femur and tibia and proximal femoral diaphysis in each individual. Percent differences between methods were derived to evaluate directional (systematic) and absolute (random) error. Multiple regression was also used to investigate the sources of error associated with each method. The results indicate that while the LCM shows generally good correspondence to the true cross-sectional properties, the EMM generally overestimates true parameters. Regression equations are provided to correct this overestimation, and, when applied to another sample, are shown to significantly improve estimates for the femoral midshaft, although corrections are less successful for the other section locations. Our results suggest that the LCM is an adequate substitute for estimating cross-sectional properties when direct sectioning and CT are not feasible. The EMM is a reasonable alternative, although the bias inherent in the method should be corrected if possible, especially when the results of the study are to be compared with data collected using different methods.     

Modeling relationships between calving traits: a comparison between standard and recursive mixed models

Background

The use of structural equation models for the analysis of recursive and simultaneous relationships between phenotypes has become more popular recently. The aim of this paper is to illustrate how these models can be applied in animal breeding to achieve parameterizations of different levels of complexity and, more specifically, to model phenotypic recursion between three calving traits: gestation length (GL), calving difficulty (CD) and stillbirth (SB). All recursive models considered here postulate heterogeneous recursive relationships between GL and liabilities to CD and SB, and between liability to CD and liability to SB, depending on categories of GL phenotype.

Methods

Four models were compared in terms of goodness of fit and predictive ability: 1) standard mixed model (SMM), a model with unstructured (co)variance matrices; 2) recursive mixed model 1 (RMM1), assuming that residual correlations are due to the recursive relationships between phenotypes; 3) RMM2, assuming that correlations between residuals and contemporary groups are due to recursive relationships between phenotypes; and 4) RMM3, postulating that the correlations between genetic effects, contemporary groups and residuals are due to recursive relationships between phenotypes.

Results

For all the RMM considered, the estimates of the structural coefficients were similar. Results revealed a nonlinear relationship between GL and the liabilities both to CD and to SB, and a linear relationship between the liabilities to CD and SB.Differences in terms of goodness of fit and predictive ability of the models considered were negligible, suggesting that RMM3 is plausible.

Conclusions

The applications examined in this study suggest the plausibility of a nonlinear recursive effect from GL onto CD and SB. Also, the fact that the most restrictive model RMM3, which assumes that the only cause of correlation is phenotypic recursion, performs as well as the others indicates that the phenotypic recursion may be an important cause of the observed patterns of genetic and environmental correlations.     

Plasma clearance and half-life of prostaglandin F2alpha: a comparison between mares and heifers

Horses are about five times more sensitive to the luteolytic effect of prostaglandin F2alpha (PGF) than cattle, as indicated by a recommended clinical dose of 5 mg in horses and 25 mg in cattle. Novel evaluations of the PGF plasma disappearance curves were made in mares and in heifers, and the two species were compared. Mares and heifers (n = 5) of similar body weight were injected (Min 0) intravenously with PGF (5 mg per animal). Blood was sampled every 10 sec until Min 3, every 30 sec until Min 5, every 10 min until Min 60, and every 30 min until Min 240. The mean PGF concentration was greater (P < 0.05) in mares than in heifers at Min 1 through Min 60 and at Mins 180 and 240. The mean time to maximum PGF concentration was not different between mares (42.0 ± 8.6 sec) and heifers (35.0 ± 2.9 sec). The apparent plasma clearance, distribution half-life, elimination half-life, and maximum plasma PGF concentration were 3.3 ± 0.5 L h(-1) kg(-1), 94.2 ± 15.9 sec, 25.9 ± 5.0 min, and 249.1 ± 36.8 ng/ml, respectively, in mares and 15.4 ± 2.3 L h(-1) kg(-1), 29.2 ± 3.9 sec, 9.0 ± 0.9 min, and 51.4 ± 22.6 ng/ml, respectively, in heifers. Plasma clearance was about five times less (P < 0.0005), maximum plasma PGF concentration was five times greater (P < 0.002), and the distribution half-life and elimination half-life were about three times longer (P < 0.005) in mares than in heifers. The fivefold greater plasma clearance of PGF in heifers than in mares corresponds to the recommended fivefold greater clinical dose of PGF in cattle and supported the hypothesis that the metabolic clearance of PGF is slower in mares than heifers.     

Identification of genetic factors controlling domestication-related traits of rice using an F2 population of a cross between Oryza sativa and O. rufipogon

 Domesticated rice differs from the wild progenitor in large arrays of morphological and physiological traits. The present study was conducted to identify the genetic factors controlling the differences between cultivated rice and its wild progenitor, with the intention to assess the genetic basis of the changes associated with the processes of rice domestication. A total of 19 traits, including seven qualitative and 12 quantitative traits, that are related to domestication were scored in an F₂ population from a cross between a variety of the Asian cultivated rice (Oryza sativa) and an accession of the common wild rice (O. rufipogon). Loci controlling the inheritance of these traits were determined by making use of a molecular linkage map consisting of 348 molecular-marker loci (313 RFLPs, 12 SSRs and 23 AFLPs) based on this F₂ population. All seven qualitative traits were each controlled by a single Mendelian locus. Analysis of the 12 quantitative traits resolved a total of 44 putative QTLs with an average of 3.7 QTLs per trait. The amount of variation explained by individual QTLs ranged from a low of 6.9% to a high of 59.8%, and many of the QTLs accounted for more than 20% of the variation. Thus, genes of both major and minor effect were involved in the differences between wild and cultivated rice. The results also showed that most of the genetic factors (qualitative or QTLs) controlling the domestication-related traits were concentrated in a few chromosomal blocks. Such a clustered distribution of the genes may provide explanations for the genetic basis of the “domestication syndrome” observed in evolutionary studies and also for the “linkage drag” that occurs in many breeding programs. The information on the genetic basis of some desirable traits possessed by the wild parent may also be useful for facilitating the utilization of these traits in rice-breeding programs. Received: 1 June 1998 / Accepted: 28 July 1998