Haplotype inference based on Hidden Markov Models in the QTL-MAS 2010 multi-generational dataset

<p>Abstract</p> <p>Background</p> <p>We have previously demonstrated an approach for efficient computation of genotype probabilities, and more generally probabilities of allele inheritance in inbred as well as outbred populations. That work also included an extension for haplotype inference, or phasing, using Hidden Markov Models. Computational phasing of multi-thousand marker datasets has not become common as of yet. In this communication, we further investigate the method presented earlier for such problems, in a multi-generational dataset simulated for QTL detection.</p> <p>Results</p> <p>When analyzing the dataset simulated for the 14th QTLMAS workshop, the phasing produced showed zero deviations compared to original simulated phase in the founder generation. In total, 99.93% of all markers were correctly phased. 97.68% of the individuals were correct in all markers over all 5 simulated chromosomes. Results were produced over a weekend on a small computational cluster. The specific algorithmic adaptations needed for the Markov model training approach in order to reach convergence are described.</p> <p>Conclusions</p> <p>Our method provides efficient, near-perfect haplotype inference allowing the determination of completely phased genomes in dense pedigrees. These developments are of special value for applications where marker alleles are not corresponding directly to QTL alleles, thus necessitating tracking of allele origin, and in complex multi-generational crosses. The cnF2freq codebase, which is in a current state of active development, is available under a BSD-style license.</p

Extended homozygosity is not usually due to cytogenetic abnormality

<p>Abstract</p> <p>Background</p> <p>Previous studies have reported frequent stretches of homozygosity in human subjects but have failed to clarify whether these are due to cytogenetic abnormalities or to autozygosity.</p> <p>Methods</p> <p>Trios which had been typed for closely spaced SNPs spanning the genome were studied. Stretches of extended homozygosity were identified in the child members, as were occasions on which the child had been genotyped as not inheriting one parental allele. The number of times such transmission errors occurred within regions of extended homozygosity was compared with the chance expectation.</p> <p>Results</p> <p>Transmission errors occurred more rarely in regions of extended homozygosity than would be expected by chance.</p> <p>Discussion</p> <p>Regions of extended homozygosity are not generally due to cytogenetic abnormalities such as uniparental isodisomy. They reflect the Mendelian inheritance of haplotypes from a common ancestor. This may have implications for mapping disease genes.</p

qtl.outbred: Interfacing outbred line cross data with the R/qtl mapping software

<p>Abstract</p> <p>Background</p> <p><b>qtl.outbred </b>is an extendible interface in the statistical environment, R, for combining quantitative trait loci (QTL) mapping tools. It is built as an umbrella package that enables outbred genotype probabilities to be calculated and/or imported into the software package R/<b>qtl</b>.</p> <p>Findings</p> <p>Using <b>qtl.outbred</b>, the genotype probabilities from outbred line cross data can be calculated by interfacing with a new and efficient algorithm developed for analyzing arbitrarily large datasets (included in the package) or imported from other sources such as the web-based tool, GridQTL.</p> <p>Conclusion</p> <p><b>qtl.outbred </b>will improve the speed for calculating probabilities and the ability to analyse large future datasets. This package enables the user to analyse outbred line cross data accurately, but with similar effort than inbred line cross data.</p

Broad-Scale Recombination Patterns Underlying Proper Disjunction in Humans

Although recombination is essential to the successful completion of human meiosis, it remains unclear how tightly the process is regulated and over what scale. To assess the nature and stringency of constraints on human recombination, we examined crossover patterns in transmissions to viable, non-trisomic offspring, using dense genotyping data collected in a large set of pedigrees. Our analysis supports a requirement for one chiasma per chromosome rather than per arm to ensure proper disjunction, with additional chiasmata occurring in proportion to physical length. The requirement is not absolute, however, as chromosome 21 seems to be frequently transmitted properly in the absence of a chiasma in females, a finding that raises the possibility of a back-up mechanism aiding in its correct segregation. We also found a set of double crossovers in surprisingly close proximity, as expected from a second pathway that is not subject to crossover interference. These findings point to multiple mechanisms that shape the distribution of crossovers, influencing proper disjunction in humans

Mapping genetic determinants of host susceptibility to Pseudomonas aeruginosa lung infection in mice.

Background: P. aeruginosa is one of the top three causes of opportunistic human bacterial infections. The remarkable variability in the clinical outcomes of this infection is thought to be associated with genetic predisposition. However, the genes underlying host susceptibility to P. aeruginosa infection are still largely unknown. Results: As a step towards mapping these genes, we applied a genome wide linkage analysis approach to a mouse model. A large F2 intercross population, obtained by mating P. aeruginosa-resistant C3H/HeOuJ, and susceptible A/J mice, was used for quantitative trait locus (QTL) mapping. The F2 progenies were challenged with a P. aeruginosa clinical strain and monitored for the survival time up to 7 days post-infection, as a disease phenotype associated trait. Selected phenotypic extremes of the F2 distribution were genotyped with high-density single nucleotide polymorphic (SNP) markers, and subsequently QTL analysis was performed. A significant locus was mapped on chromosome 6 and was named P. aeruginosa infection resistance locus 1 (Pairl1). The most promising candidate genes, including Dok1, Tacr1, Cd207, Clec4f, Gp9, Gata2, Foxp1, are related to pathogen sensing, neutrophils and macrophages recruitment and inflammatory processes. Conclusions: We propose a set of genes involved in the pathogenesis of P. aeruginosa infection that may be explored to complement human studie

Qxpak.5: Old mixed model solutions for new genomics problems

Mixed models have a long and fruitful history in statistics. They are pertinent to genomics problems because they are highly versatile, accommodating a wide variety of situations within the same theoretical and algorithmic framework. Qxpak is a package for versatile statistical genomics, specifically designed for sophisticated quantitative trait loci and association analyses. Multiple loci, multiple trait, infinitesimal genetic effects, imprinting, epistasis or sex linked loci can be fitted. The new version (v. 5) allows us, among other new features, to include either relationship matrices obtained with molecular information or user defined matrices that can be read from an input file. This feature can be used for genome selection or - more importantly - to correct for population structure in association studies. In crosses, two parental lines, not necessarily inbred, can be accommodated. This software aims at simplifying statistical genetic analyses implementing a coherent and unified approach by mixed models. It provides a tool that can be used in a wide variety of situations with ample genetic and statistical modeling flexibility. The software, a complete manual and examples are available at http://www.icrea.cat/Web/OtherSectionViewer.aspx?key=485&titol=Software:Qxpak.

A Simple Method for Combining Genetic Mapping Data from Multiple Crosses and Experimental Designs

Over the past decade many linkage studies have defined chromosomal intervals containing polymorphisms that modulate a variety of traits. Many phenotypes are now associated with enough mapping data that meta-analysis could help refine locations of known QTLs and detect many novel QTLs.We describe a simple approach to combining QTL mapping results for multiple studies and demonstrate its utility using two hippocampus weight loci. Using data taken from two populations, a recombinant inbred strain set and an advanced intercross population we demonstrate considerable improvements in significance and resolution for both loci. 1-LOD support intervals were improved 51% for Hipp1a and 37% for Hipp9a. We first generate locus-wise permuted P-values for association with the phenotype from multiple maps, which can be done using a permutation method appropriate to each population. These results are then assigned to defined physical positions by interpolation between markers with known physical and genetic positions. We then use Fisher's combination test to combine position-by-position probabilities among experiments. Finally, we calculate genome-wide combined P-values by generating locus-specific P-values for each permuted map for each experiment. These permuted maps are then sampled with replacement and combined. The distribution of best locus-specific P-values for each combined map is the null distribution of genome-wide adjusted P-values.Our approach is applicable to a wide variety of segregating and non-segregating mapping populations, facilitates rapid refinement of physical QTL position, is complementary to other QTL fine mapping methods, and provides an appropriate genome-wide criterion of significance for combined mapping results

Strain-dependent host transcriptional responses to toxoplasma infection are largely conserved in mammalian and avian hosts

Toxoplasma gondii has a remarkable ability to infect an enormous variety of mammalian and avian species. Given this, it is surprising that three strains (Types I/II/III) account for the majority of isolates from Europe/North America. The selective pressures that have driven the emergence of these particular strains, however, remain enigmatic. We hypothesized that strain selection might be partially driven by adaptation of strains for mammalian versus avian hosts. To test this, we examine in vitro, strain-dependent host responses in fibroblasts of a representative avian host, the chicken (Gallus gallus). Using gene expression profiling of infected chicken embryonic fibroblasts and pathway analysis to assess host response, we show here that chicken cells respond with distinct transcriptional profiles upon infection with Type II versus III strains that are reminiscent of profiles observed in mammalian cells. To identify the parasite drivers of these differences, chicken fibroblasts were infected with individual F1 progeny of a Type II x III cross and host gene expression was assessed for each by microarray. QTL mapping of transcriptional differences suggested, and deletion strains confirmed, that, as in mammalian cells, the polymorphic rhoptry kinase ROP16 is the major driver of strain-specific responses. We originally hypothesized that comparing avian versus mammalian host response might reveal an inversion in parasite strain-dependent phenotypes; specifically, for polymorphic effectors like ROP16, we hypothesized that the allele with most activity in mammalian cells might be less active in avian cells. Instead, we found that activity of ROP16 alleles appears to be conserved across host species; moreover, additional parasite loci that were previously mapped for strain-specific effects on mammalian response showed similar strain-specific effects in chicken cells. These results indicate that if different hosts select for different parasite genotypes, the selection operates downstream of the signaling occurring during the beginning of the host's immune response. © 2011 Ong et al

Genetic Analysis of Genome-Scale Recombination Rate Evolution in House Mice

The rate of meiotic recombination varies markedly between species and among individuals. Classical genetic experiments demonstrated a heritable component to population variation in recombination rate, and specific sequence variants that contribute to recombination rate differences between individuals have recently been identified. Despite these advances, the genetic basis of species divergence in recombination rate remains unexplored. Using a cytological assay that allows direct in situ imaging of recombination events in spermatocytes, we report a large (∼30%) difference in global recombination rate between males of two closely related house mouse subspecies (Mus musculus musculus and M. m. castaneus). To characterize the genetic basis of this recombination rate divergence, we generated an F2 panel of inter-subspecific hybrid males (n = 276) from an intercross between wild-derived inbred strains CAST/EiJ (M. m. castaneus) and PWD/PhJ (M. m. musculus). We uncover considerable heritable variation for recombination rate among males from this mapping population. Much of the F2 variance for recombination rate and a substantial portion of the difference in recombination rate between the parental strains is explained by eight moderate- to large-effect quantitative trait loci, including two transgressive loci on the X chromosome. In contrast to the rapid evolution observed in males, female CAST/EiJ and PWD/PhJ animals show minimal divergence in recombination rate (∼5%). The existence of loci on the X chromosome suggests a genetic mechanism to explain this male-biased evolution. Our results provide an initial map of the genetic changes underlying subspecies differences in genome-scale recombination rate and underscore the power of the house mouse system for understanding the evolution of this trait