Linkage disequilibrium assessment via log-linear modeling of SNP haplotype frequencies

Analyses of high-density single-nucleotide polymorphism (SNP) data, such as genetic mapping and linkage disequilibrium (LD) studies, require phase-known haplotypes to allow for the correlation between tightly linked loci. However, current SNP genotyping technology cannot determine phase, which must be inferred statistically. In this paper, we present a new Bayesian Markov chain Monte Carlo (MCMC) algorithm for population haplotype frequency estimation, particulary in the context of LD assessment. The novel feature of the method is the incorporation of a log-linear prior model for population haplotype frequencies. We present simulations to suggest that 1) the log-linear prior model is more appropriate than the standard coalescent process in the presence of recombination (>0.02cM between adjacent loci), and 2) there is substantial inflation in measures of LD obtained by a "two-stage" approach to the analysis by treating the "best" haplotype configuration as correct, without regard to uncertainty in the recombination process. Genet Epidemiol 25:106-114, 2003. (C) 2003 Wiley-Liss, Inc.

In vitro fermentation of mixed linkage glucooligosaccharides produced by Gluconobacter oxydans NCIMB 4943 by the human colonic microflora

The aim of this study was to develop selectively fermented (prebiotic) carbohydrate molecules which would also result in the generation of butyric acid. Glucooligosaccharides produced by Gluconobacter oxydans NCIMB 4943 from various types of maltodextrins were evaluated for their fermentation by mixed cultures of human colonic microflora. The selectivity of growth of desirable bacteria (bifidobacteria, lactobacilli) was studied in stirred pH-controlled (6.8) batch cultures. Bacterial populations were enumerated using fluorescent in situ hybridization (FISH). Gluco-oligosaccharides resulted in significantly (P<0.05) increased numbers of bifidobacteria and lactobacilli within 24 hours. Bacteroides, clostridial and eubacterial populations were slightly decreased at 48 h. There was very little difference in selectivity between the maltodextrin substrates and the products, although maltodextrin displayed a slightly less selective fermentation than the gluco-oligosaccharide products, also stimulating the growth of bacteroides, clostridia and eubacteria. Gluco-oligosaccharides, produced from G19 maltodextrin, resulted in the best prebiotic effect with the highest prebiotic index (PI) of 5.90 at 48 hours. Acetate, propionate and butyrate were all produced from glucooligosaccharides, derived from G19 maltodextrin, at 48 hours but no lactate or formate were detected.

Effect of molecule branching and glycosidic linkage on the degradation of polydextrose by gut microbiota.

Polydextrose is a randomly linked complex glucose oligomer that is widely used as a sugar replacer, bulking agent, dietary fiber and prebiotic. Polydextrose is poorly utilized by the host and, during gastrointestinal transit, it is slowly degraded by intestinal microbes, although it is not known which parts of the complex molecule are preferred by the microbes. The microbial degradation of polydextrose was assessed by using a simulated model of colonic fermentation. The degradation products and their glycosidic linkages were measured by combined gas chromatography and mass spectrometry, and compared to those of intact polydextrose. Fermentation resulted in an increase in the relative abundance of non-branched molecules with a concomitant decrease in single-branched glucose molecules and a reduced total number of branching points. A detailed analysis showed a preponderance of 1,6 pyranose linkages. The results of this study demonstrate how intestinal microbes selectively degrade polydextrose, and provide an insight into the preferences of gut microbiota in the presence of different glycosidic linkages.

Measuring gametic disequilibrium from multilocus data

We describe a Bayesian approach to analyzing multilocus genotype or haplotype data to assess departures from gametic (linkage) equilibrium. Our approach employs a Markov chain Monte Carlo (MCMC) algorithm to approximate the posterior probability distributions of disequilibrium parameters. The distributions are computed exactly in some simple settings. Among other advantages, posterior distributions can be presented visually, which allows the uncertainties in parameter estimates to be readily assessed. In addition, background knowledge can be incorporated, where available, to improve the precision of inferences. The method is illustrated by application to previously published datasets; implications for multilocus forensic match probabilities and for simple association-based gene mapping are also discussed.

Modelling niches of arbitrary shape in genetic algorithms using Niche Linkage in the Dynamic Niche Clustering framework

We present some additions to a fuzzy variable radius niche technique called Dynamic Niche Clustering (DNC) (Gan and Warwick, 1999; 2000; 2001) that enable the identification and creation of niches of arbitrary shape through a mechanism called Niche Linkage. We show that by using this mechanism it is possible to attain better feature extraction from the underlying population.