Confirmation of linkage to chromosome 1q for spine bone mineral density in southern Chinese

Chromosome 1q has previously been linked to bone mineral density (BMD) variation in the general population in several genome-wide linkage studies in both humans and mouse model. The aim of present study is to replicate and fine map the QTL influencing BMD in chromosome 1q in southern Chinese. Twelve microsatellite markers were genotyped for a 57 cΜ region in the chromosome 1q in 306 southern Chinese families with 1,459 subjects. Each of these families was ascertained through a proband with BMD Z-scores less than −1.3 at the hip or spine. BMD (g/cm²) at the L1-4 lumbar spine, femoral neck (FN), trochanter and total hip was measured by dual-energy X-ray absortiometry. Linkage analyses were performed using the variance component linkage analysis method implemented in Merlin software. Four markers (D1S2878, D1S196, D1S452, and D1S218) achieved a LOD score greater than 1.0 with spine BMD, with the maximum multipoint LOD score of 2.36 at the marker D1S196. We did not detect a LOD score greater than 1.0 for BMD at the FN, trochanter, or total hip in multipoint linkage analyses. Our results present the first evidence for the presence of an osteoporosis susceptibility gene on chromosome 1q in non-Caucasian subjects. Further analyses of candidate genes are warranted to identify QTL genes and variants underlying the variations of BMD in this region.     

Linkage disequilibrium between alleles at highly polymorphic mini- and micro-satellite loci of Theileria parva isolated from cattle in three regions of Kenya

Theileria parva schizont-infected lymphocyte culture isolates from western, central and coastal Kenya were analysed for size polymorphism at 30 T. parva-specific variable number tandem repeat (VNTR) loci using a panel of mini- and micro-satellite markers. The mean number of alleles ranged from 3 to 11 at individual loci and 183 distinct alleles were observed in total, indicating high genetic diversity within the T. parva gene pool in Kenyan cattle. The frequency distribution of the length variation of specific alleles among isolates ranged from normal to markedly discontinuous. Genetic relationships between isolates were analysed using standard indices of genetic distance. Genetic distances and dendrograms derived from these using neighbour-joining algorithms did not indicate significant clustering on a geographical basis. Analysis of molecular variance demonstrated that the genetic variation between individual isolates was 72%, but only 2.3% when isolates from different regions were pooled. Both these observations suggest minimal genetic sub-structuring relative to geographical origin. Linkage disequilibrium was observed between pairs of loci within populations, as in certain Ugandan T. parva populations. A novel observation was that disequilibrium was also detected between alleles at three individual pairs of VNTR loci when isolates from the three regional meta-populations were pooled for analysis.     

Optimization of two-stage genetic designs where data are combined using an accurate and efficient approximation for Pearson's statistic

There is an increasing interest in the use of two-stage case-control studies to reduce genotyping costs in the search for genes underlying common disorders. Instead of analyzing the data from the second stage separately, a more powerful test can be performed by combining the data from both stages. However, standard tests cannot be used because only the markers that are significant in the first stage are selected for the second stage and the test statistics at both stages are dependent because they partly involve the same data. Theoretical approximations are not available for commonly used test statistics and in this specific context simulations can be problematic because of the computational burden. We therefore derived a cost-effective, that is, accurate but fast in terms of central processing unit (CPU) time, approximation for the distribution of Pearson's statistic on 2 xm contingency tables in two-stage design with combined data. We included this approximation in an iterative method for designing optimal two-stage studies. Simulations supported the accuracy of our approximation. Numerical results confirmed that the use of two-stage designs reduces the genotyping burden substantially. Compared to not combining data, combining the data decreases the required sample sizes on average by 15% and the genotyping burden by 5%.     

Addition of glycerol for improved methylation linkage analysis of polysaccharides

A presolubilization procedure with the use of glycerol is shown to be applicable for the structural analysis of polysaccharides. Neutral, acidic, high-molecular-weight and low-molecular-weight polysaccharides were solubilized in glycerol prior to methylation and subsequent linkage analysis by GC-MS. All four types of polysaccharides showed significant increases in derivatization following presolubilization as measured by recovery of partially methylated alditol acetates.     

A statistical framework for genetic association studies of power curves in bird flight

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution.     

Glycomic strategy for efficient linkage analysis of di-, oligo- and polysialic acids

Sialic acid polymers of glycoproteins and glycolipids are characterized by a high diversity in nature and are involved in distinct biological processes depending inter alia on the glycosidic linkages between the present sialic acid residues. Though suitable protocols are available for chain length and sialic acid determination, sensitive methods for linkage analysis of di-, oligo-, and polysialic acids (di/oligo/polySia) are still pending. In this study, we have established a highly sensitive glycomic strategy for this purpose which is based on permethylation of di/oligo/polySia after tagging their reducing ends with the fluorescent dye 1,2-diamino-4,5-methylenedioxybenzene (DMB). Using DMB-labeled sialic acid di/oligo/polymers glycosidic linkages could be efficiently determined and, optionally, the established working procedure can be combined with HPLC for in depth characterization of distinct di/oligo/polySia chains. Moreover, the outlined approach can be directly applied to mammalian tissue samples and linkage analysis of sialic acid polymers present in biopsy samples of neuroblastoma tissue demonstrating the usefulness of the outlined work flow to screen, for example, cancer tissue for the presence of distinct variants of di/oligo/polySia as potentially novel biomarkers. Hence, the described strategy offers a highly sensitive and efficient strategy for identification of glycosidic linkages in sialic acid di/oligo/polymers of glycoproteins and glycolipids.     

Allelic Combinations of Promoter and Exon 2 in <Emphasis Type="Italic">DQB1</Emphasis> in Dogs and Wolves

Polymorphism of PBRs of the major histocompatibility complex (MHC) genes is well recognized, but the polymorphism also extends to proximal promoter regions. Examining DQB1 variability in dogs and wolves, we identified 7 promoter variants and 13 exon 2 alleles among 89 dogs, including a previously unknown DQB1 exon 2 allele, and 8 promoter variants and 9 exon 2 alleles among 85 wolves. As expected from previous studies and from a close chromosomal location, strong linkage disequilibrium was demonstrated in both wolves and dogs by having significantly fewer promoter/exon 2 combinations than expected from simulations of randomized data sets. Interestingly, we noticed weaker haplotypic associations in dogs than in wolves. Dogs had twice as many promoter/exon 2 combinations as wolves and an almost 2-fold difference in the number of exon 2 alleles per promoter variant. This difference was not caused by an admixture of breeds in our group of dogs because the high ratio of observed to expected number of haplotypes persisted within a single dog breed, the German Shepherd. Ewens-Watterson tests indicated that both the promoter and exon 2 are under the balancing selection, and both regions appear to be more recently derived in the dog than in the wolf. Hence, although reasons for the differences are unknown, they may relate to altered selection pressure on patterns of expression. Deviations from normal MHC expression patterns have been associated with autoimmune diseases, which occur frequently in several dog breeds. Further knowledge about these deviations may help us understand the source of such diseases.     

Gametic models for multitrait selection schemes to study variance of response and drift under adverse genetic correlations

A major issue faced by breeders is how to effectively manage adverse correlations in breeding programs. We present results of a Monte Carlo allele-based simulation of the changes in response and variance of response under adverse genetic correlations by using the examples of two contrasting selection methods: the ‘Smith-Hazel’ selection index (SH) and independent culling (IC). We assumed several gene models, which included linkage and antagonistic pleiotropy as the primary drivers of adverse genetic correlations. The different behaviors of these selection methods allowed us to identify the mechanism behind the generation of uncertainty under antagonistic trait selection: IC had the properties of stabilizing selection, while SH behaved more similar to disruptive selection. Although SH outperformed IC in terms of genetic gain, this advantage happened at the cost of higher variance of response and loss of heterozygosity. Using an optimum selection algorithm (OS) to prevent the loss of heterozygosity through a constraint on inbreeding in SH/OS increased marginally the reliability, remaining still below that of IC under equal conditions. However, SH/OS had lower inbreeding (ΔF) than IC for equivalent levels of genetic gain, so a compromise between high selection reliability, low ΔF, and gain must be made by a breeder under antagonistic trait selection even with the use of optimization tools.     

Role of domestication in shaping <Emphasis Type="Italic">Castanea sativa</Emphasis> genetic variation in Europe

The genetic structure of sweet chestnut (Castanea sativa Mill.) across Europe was assessed using 73 inter-simple sequence repeat markers to screen 1,768 individuals from 68 stands distributed across 29 sites in five European countries (Italy, France, Spain, Greece, and UK). At each site, trees were sampled from three distinct management types (domestication levels): naturalized stands, managed coppice, and grafted fruit orchards. In more than a third of the orchards, nonlocal genetic material (grafted clones) were evident, showing (as predicted) large differences from the other two domestication levels for most of the within-population genetic diversity parameters estimated. Randomly generated linkage disequilibrium analysis revealed weak though significant differences in two-locus allelic correlations between naturalized stands and coppice, suggesting that long-term management techniques may influence the genetic makeup of the populations. Multivariate analysis revealed the existence of five distinct gene pools across the study area; three were located in Greece, one on the northwestern coast of the Iberian peninsula and a large gene pool covering the rest of the Mediterranean basin. The implications of the results are discussed in relation to developing conservation strategies for chestnut genetic resources in Europe.