Progeny group size for evaluating natural service bulls using AI reference sires

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Power of the 2-locus TDT for testing the interaction of two susceptibility genes

We recently proposed a new strategy: 2-locus TDT for detecting two susceptibility genes through their interaction in trio families. We apply our method to two candidate genes, A and C, on the Genetic Analysis Workshop 15 (GAW15) simulated rheumatoid arthritis data and study the power to identify an interactive effect of these genes

On the choice of linkage statistics

Three LOD score statistics are often used for genome-wide linkage analysis: the maximum LOD score, the LOD score statistic proposed by Kong and Cox, both based on the allele-sharing between affected sib pairs, and the maximization of the LOD score function of Morton on two genetic models and an heterogeneity parameter

An ordered subset approach to including covariates in the transmission disequilibrium test

Clinical heterogeneity of a disease may reflect an underlying genetic heterogeneity, which may hinder the detection of trait loci. Consequently, many statistical methods have been developed that allow for the detection of linkage and/or association signals in the presence of heterogeneity

Modeling the effect of a genetic factor for a complex trait in a simulated population

Genetic Analysis Workshop 14 simulated data have been analyzed with MASC(marker association segregation chi-squares) in which we implemented a bootstrap procedure to provide the variation intervals of parameter estimates. We model here the effect of a genetic factor, S, for Kofendrerd Personality Disorder in the region of the marker C03R0281 for the Aipotu population. The goodness of fit of several genetic models with two alleles for one locus has been tested. The data are not compatible with a direct effect of a single-nucleotide polymorphism (SNP) (SNP 16, 17, 18, 19 of pack 153) in the region. Therefore, we can conclude that the functional polymorphism has not been typed and is in linkage disequilibrium with the four studied SNPs. We obtained very large variation intervals both of the disease allele frequency and the degree of dominance. The uncertainty of the model parameters can be explained first, by the method used, which models marginal effects when the disease is due to complex interactions, second, by the presence of different sub-criteria used for the diagnosis that are not determined by S in the same way, and third, by the fact that the segregation of the disease in the families was not taken into account. However, we could not find any model that could explain the familial segregation of the trait, namely the higher proportion of affected parents than affected sibs

Validation of the reshaped shared epitope HLA-DRB1 classification in rheumatoid arthritis

Recently, we proposed a classification of HLA-DRB1 alleles that reshapes the shared epitope hypothesis in rheumatoid arthritis (RA); according to this model, RA is associated with the RAA shared epitope sequence (72–74 positions) and the association is modulated by the amino acids at positions 70 and 71, resulting in six genotypes with different RA risks. This was the first model to take into account the association between the HLA-DRB1 gene and RA, and linkage data for that gene. In the present study we tested this classification for validity in an independent sample. A new sample of the same size and population (100 RA French Caucasian families) was genotyped for the HLA-DRB1 gene. The alleles were grouped as proposed in the new classification: S(1 )alleles for the sequences A-RAA or E-RAA; S(2 )for Q or D-K-RAA; S(3D )for D-R-RAA; S(3P )for Q or R-R-RAA; and X alleles for no RAA sequence. Transmission of the alleles was investigated. Genotype odds ratio (OR) calculations were performed through conditional logistic regression, and we tested the homogeneity of these ORs with those of the 100 first trio families (one case and both parents) previously reported. As previously observed, the S(2 )and S(3P )alleles were significantly over-transmitted and the S(1), S(3D )and X alleles were under-transmitted. The latter were grouped as L alleles, resulting in the same three-allele classification. The risk hierarchy of the six derived genotypes was the same: (by decreasing OR and with L/L being the reference genotype) S(2)/S(3P), S(2)/S(2), S(3P)/S(3P), S(2)/L and S(3P)/L. The homogeneity test between the ORs of the initial and the replication samples revealed no significant differences. The new classification was therefore considered validated, and both samples were pooled to provide improved estimates of RA risk genotypes from the highest (S(2)/S(3P )[OR 22.2, 95% confidence interval 9.9–49.7]) to the lowest (S(3P)/L [OR 4.4, 95% confidence interval 2.3–8.4])

Handling linkage disequilibrium in qualitative trait linkage analysis using dense SNPs: a two-step strategy

<p>Abstract</p> <p>Background</p> <p>In affected sibling pair linkage analysis, the presence of linkage disequilibrium (LD) has been shown to lead to overestimation of the number of alleles shared identity-by-descent (IBD) among sibling pairs when parents are ungenotyped. This inflation results in spurious evidence for linkage even when the markers and the disease locus are not linked. In our study, we first theoretically evaluate how inflation in IBD probabilities leads to overestimation of a nonparametric linkage (NPL) statistic under the assumption of linkage equilibrium. Next, we propose a two-step processing strategy in order to systematically evaluate approaches to handle LD. Based on the observed inflation of expected logarithm of the odds ratio (LOD) from our theoretical exploration, we implemented our proposed two-step processing strategy. Step 1 involves three techniques to filter a dense set of markers. In step 2, we use the selected subset of markers from step 1 and apply four different methods of handling LD among dense markers: 1) marker thinning (MT); 2) recursive elimination; 3) SNPLINK; and 4) LD modeling approach in MERLIN. We evaluate relative performance of each method through simulation.</p> <p>Results</p> <p>We observed LOD score inflation only when the parents were ungenotyped. For a given number of markers, all approaches evaluated for each type of LD threshold performed similarly; however, RE approach was the only one that eliminated the LOD score bias. Our simulation results indicate a reduction of approximately 75% to complete elimination of the LOD score inflation while maintaining the information content (IC) when setting a tolerable squared correlation coefficient LD threshold (r²) above 0.3 for or 2 SNPs per cM using MT.</p> <p>Conclusion</p> <p>We have established a theoretical basis of how inflated IBD information among dense markers overestimates a NPL statistic. The two-step processing strategy serves as a useful framework to systematically evaluate relative performance of different methods to handle LD.</p

Partitioning of copy-number genotypes in pedigrees

<p>Abstract</p> <p>Background</p> <p>Copy number variations (CNVs) and polymorphisms (CNPs) have only recently gained the genetic community's attention. Conservative estimates have shown that CNVs and CNPs might affect more than 10% of the genome and that they may be at least as important as single nucleotide polymorphisms in assessing human variability. Widely used tools for CNP analysis have been implemented in <it>Birdsuite </it>and <it>PLINK </it>for the purpose of conducting genetic association studies based on the unpartitioned total number of CNP copies provided by the intensities from Affymetrix's Genome-Wide Human SNP Array. Here, we are interested in partitioning copy number variations and polymorphisms in extended pedigrees for the purpose of linkage analysis on familial data.</p> <p>Results</p> <p>We have developed <it>CNGen</it>, a new software for the partitioning of copy number polymorphism using the integrated genotypes from <it>Birdsuite </it>with the Affymetrix platform. The algorithm applied to familial trios or extended pedigrees can produce partitioned copy number genotypes with distinct parental alleles. We have validated the algorithm using simulations on a complex pedigree structure using frequencies calculated from a real dataset of 300 genotyped samples from 42 pedigrees segregating a congenital heart defect phenotype.</p> <p>Conclusions</p> <p><it>CNGen </it>is the first published software for the partitioning of copy number genotypes in pedigrees, making possible the use CNPs and CNVs for linkage analysis. It was implemented with the <it>Python </it>interpreter version 2.5.2. It was successfully tested on current Linux, Windows and Mac OS workstations.</p