Inheritance of Adrenal Phenylethanolamine N-Methyltransferase Activity in the Rat

Phenylethanolamine N-methyltransferase (PNMT) is the enzyme that catalyzes the S-adenosyl-L-methionine-dependent methylation of (-)norepinephrine to (-)epinephrine in the adrenal medulla. Adrenal PNMT activity is markedly different in two highly inbred rat strains; enzyme activity in the F344 strain is more than fivefold greater than that in the Buf strain. Initial characterization of the enzyme in the two inbred strains reveals evidence for catalytic and structural differences, as reflected in dissimilar Km values for the cosubstrate (S-adenosyl-L-methionine) and prominent differences in thermal inactivation curves. To assess adrenal PNMT activity in an F344 X Buf pedigree, we employed a statistical procedure to test for one- and two-locus hypotheses in the presence of within-class correlations due to cage or litter effects. The PNMT data in the pedigree are best accounted for by segregation at a simple major locus superimposed upon a polygenic background; data obtained from the biochemical studies suggest that the major locus is a structural gene locus.     

The Elston-Stewart algorithm for continuous genotypes and environmental factors.

The Elston-Stewart algorithm for a normally distributed trait under a polygenic model is explained in detail and extended to allow for other continuous environmental variables. This formulation is especially useful for large pedigrees, as it avoids the need to invert matrices. Whereas it may not be feasible by this method to estimate all the various components of previously suggested models for polygenic inheritance, it can allow for a reasonably flexible pedigree correlational structure under which valid tests can be performed for fixed effects that may affect the phenotype.     

Hybridization modeling of oligonucleotide SNP arrays for accurate DNA copy number estimation

Affymetrix SNP arrays have been widely used for single-nucleotide polymorphism (SNP) genotype calling and DNA copy number variation inference. Although numerous methods have achieved high accuracy in these fields, most studies have paid little attention to the modeling of hybridization of probes to off-target allele sequences, which can affect the accuracy greatly. In this study, we address this issue and demonstrate that hybridization with mismatch nucleotides (HWMMN) occurs in all SNP probe-sets and has a critical effect on the estimation of allelic concentrations (ACs). We study sequence binding through binding free energy and then binding affinity, and develop a probe intensity composite representation (PICR) model. The PICR model allows the estimation of ACs at a given SNP through statistical regression. Furthermore, we demonstrate with cell-line data of known true copy numbers that the PICR model can achieve reasonable accuracy in copy number estimation at a single SNP locus, by using the ratio of the estimated AC of each sample to that of the reference sample, and can reveal subtle genotype structure of SNPs at abnormal loci. We also demonstrate with HapMap data that the PICR model yields accurate SNP genotype calls consistently across samples, laboratories and even across array platforms.     

An approximation to the likelihood for a pedigree with loops

This paper presents a new approximation to the likelihood for a pedigree with loops, based on cutting all loops and extending the pedigree at the cuts. An opimum loop-cutting strategy and an iterative extension technique are presented. The likelihood for a pedigree with loops is then approximated by the conditional likelihood for the entire cut-extended pedigree given the extended part. The approximate likelihoods are compared with the exact likelihoods obtained using the program MENDEL for several small pedigrees with loops. The approximation is efficient for large pedigrees with complex loops in terms of computing speed and memory requirements.