ALBERT

Beschreibung: Background: Blood--brain barrier (BBB) disruption is an integral feature of numerous neurological disorders. However, there is a relative lack of knowledge regarding the underlying molecular mechanisms of immune-mediated BBB disruption. We have previously shown that CD8 T cells and perforin play critical roles in initiating altered permeability of the BBB in the peptide-induced fatal syndrome (PIFS) model developed by our laboratory. Additionally, despite having indistinguishable CD8 T cell responses, C57BL/6J (B6) mice are highly susceptible to PIFS, exhibiting functional motor deficits, increased astrocyte activation, and severe CNS vascular permeability, while 129S1/SvImJ (129S1) mice remain resistant. Therefore, to investigate the potential role of genetic factors, we performed a comprehensive genetic analysis of (B6 x 129S1) F2 progeny to define quantitative trait loci (QTL) linked to the phenotypic characteristics stated above that mediate CD8 T cell-initiated BBB disruption. Results: Using single nucleotide polymorphism (SNP) markers and a 95% confidence interval, we identified one QTL (PIFS1) on chromosome 12 linked to deficits in motor function (SNP markers rs6292954, rs13481303, rs3655057, and rs13481324, LOD score = 3.3). In addition we identified a second QTL (PIFS2) on chromosome 17 linked to changes in CNS vascular permeability (SNP markers rs6196216 and rs3672065, LOD score = 3.7). Conclusions: The QTL critical intervals discovered have allowed for compilation of a list of candidate genes implicated in regulating functional deficit and CNS vascular permeability. These genes encode for factors that may be potential targets for therapeutic approaches to treat disorders characterized by CD8 T cell-mediated BBB disruption.

Beschreibung: Background: MAP is a suspected zoonotic pathogen and the causative agent of Johne's Disease in cattle and other ruminant animals. With over $1 billion dollars in loss to the dairy industry due to Johne's Disease, efforts to eliminate or reduce MAP from cattle are of importance. The purpose of this study was to determine if daily intake of probiotics could eliminate or reduce Johne's Disease associated symptoms and pathogenesis by MAP. Post infection, animals are often asymptomatic carriers with limited shedding of the pathogen, proving early detection to be difficult. Disease and symptoms often appear 3--4 years after infection with antibiotic treatment proving ineffective. Symptoms include chronic gastrointestinal inflammation leading to severe weight-loss from poor feed and water intake cause a wasting disease. These symptoms are similar to those found in individuals with Crohn's Disease (CD); MAP has been implicated by not proven to be the causative agent of CD. Probiotics administered to livestock animals, including dairy and beef cattle have demonstrated improvements in cattle performance and health. Our objectives included determining the benefits of Lactobacillus animalis (strain name: NP-51) in MAP infected BALB/c mice by evaluating systemic and gastrointestinal response by the host and gut microbiota. Male and female animals were fed 1x106CFU/g probiotics in sterile, powdered mouse chow daily and infected with 1 x 107 CFU/ml MAP and compared to controls. Animals were evaluated for 180 days to assess acute and chronic stages of disease, with sample collection from animals every 45 days. MAP concentrations from liver and intestinal tissues were examined using real time-PCR methods and the expression of key inflammatory markers were measured during MAP infection (interferon-gamma [IFN-Upsilon], Interleukin-1alpha, IL-12, IL-10, IL-6, and Tumor necrosis factor alpha [TNF-alpha]) Results: Our results demonstrate administration of probiotics reduces production of IFN-Upsilon and IL-6 while increasing TNF-alpha and IL-17 in chronic disease; healthful immune responses that reduce chronic inflammation associated to MAP infection. Conclusions: We observed that the immune system's response in the presence of probiotics to MAP contributes towards host health by influencing the activity of the immune system and gut microbial populations.

Beschreibung: Background: Population stratification is a systematic difference in allele frequencies between subpopulations. This can lead to spurious association findings in the case--control genome wide association studies (GWASs) used to identify single nucleotide polymorphisms (SNPs) associated with disease-linked phenotypes. Methods such as self-declared ancestry, ancestry informative markers, genomic control, structured association, and principal component analysis are used to assess and correct population stratification but each has limitations. We provide an alternative technique to address population stratification. Results: We propose a novel machine learning method, ETHNOPRED, which uses the genotype and ethnicity data from the HapMap project to learn ensembles of disjoint decision trees, capable of accurately predicting an individual's continental and sub-continental ancestry. To predict an individual's continental ancestry, ETHNOPRED produced an ensemble of 3 decision trees involving a total of 10 SNPs, with 10-fold cross validation accuracy of 100% using HapMap II dataset. We extended this model to involve 29 disjoint decision trees over 149 SNPs, and showed that this ensemble has an accuracy of 〉= 99.9%, even if some of those 149 SNP values were missing. On an independent dataset, predominantly of Caucasian origin, our continental classifier showed 96.8% accuracy and improved genomic control's lamda from 1.22 to 1.11. We next used the HapMap III dataset to learn classifiers to distinguish European subpopulations (North-Western vs. Southern), East Asian subpopulations (Chinese vs. Japanese), African subpopulations (Eastern vs. Western), North American subpopulations (European vs. Chinese vs. African vs. Mexican vs. Indian), and Kenyan subpopulations (Luhya vs. Maasai). In these cases, ETHNOPRED produced ensembles of 3, 39, 21, 11, and 25 disjoint decision trees, respectively involving 31, 502, 526, 242 and 271 SNPs, with 10-fold cross validation accuracy of 86.5% +/- 2.4%, 95.6% +/- 3.9%, 95.6% +/- 2.1%, 98.3% +/- 2.0%, and 95.9% +/- 1.5%. However, ETHNOPRED was unable to produce a classifier that can accurately distinguish Chinese in Beijing vs. Chinese in Denver. Conclusions: ETHNOPRED is a novel technique for producing classifiers that can identify an individual's continental and sub-continental heritage, based on a small number of SNPs. We show that its learned classifiers are simple, cost-efficient, accurate, transparent, flexible, fast, applicable to large scale GWASs, and robust to missing values.

Beschreibung: Background: Characterising genetic diversity through the analysis of massively parallel sequencing (MPS) data offers enormous potential to significantly improve our understanding of the genetic basis for observed phenotypes, including predisposition to and progression of complex human disease. Great challenges remain in resolving which genetic variants are genuinely associated with disease from the millions of 'bystanders' and artefactual signals. Results: FAVR is a suite of new methods designed to work with commonly used MPS analysis pipelines to assist in the resolution of some of these issues with a focus on relatively rare genetic variants. To the best of our knowledge, no equivalent has previously been described. The most important and novel aspect of FAVR is the use of signatures in comparator sequence alignment files during variant filtering, and annotation of variants potentially shared between individuals. The FAVR methods use these signatures to facilitate filtering of (i) platform-specific artefacts, (ii) common genetic variants, and, where relevant, (iii) artefacts derived from imbalanced paired-end sequencing, as well as annotation of genetic variants based on evidence of co-occurrence in individuals. By comparing conventional variant calling with or without downstream processing by FAVR methods applied to whole-exome sequencing datasets, we demonstrate a 3-fold smaller rare single nucleotide variant shortlist with no detected reduction in sensitivity. This analysis included Sanger sequencing of rare variant signals not evident in dbSNP131, assessment of known variant signal preservation, and comparison of observed and expected rare variant numbers across a range of first cousin pairs. The principles described herein were applied in our recent publication identifying XRCC2 as a new breast cancer risk gene and have been made publically available as a suite of software tools. Conclusions: FAVR is a platform-agnostic suite of methods that significantly enhances the analysis of large volumes of sequencing data for the study of rare genetic variants and their influence on phenotypes.

Beschreibung: Background: Studies of normal human mammary gland development and function have mostly relied on cell culture, limited surgical specimens, and rodent models. Although RNA extracted from human milk has been used to assay the mammary transcriptome non-invasively, this assay has not been adequately validated in primates. Thus, the objectives of the current study were to assess the suitability of lactating rhesus macaques as a model for lactating humans and to determine whether RNA extracted from milk fractions is representative of RNA extracted from mammary tissue for the purpose of studying the transcriptome of milk-producing cells. Results: We confirmed that macaque milk contains cytoplasmic crescents and that ample high-quality RNA can be obtained for sequencing. Using RNA sequencing, RNA extracted from macaque milk fat and milk cell fractions more accurately represented RNA from mammary epithelial cells (cells that produce milk) than did RNA from whole mammary tissue. Mammary epithelium-specific transcripts were more abundant in macaque milk fat, whereas adipose or stroma-specific transcripts were more abundant in mammary tissue. Functional analyses confirmed the validity of milk as a source of RNA from milk-producing mammary epithelial cells. Conclusions: RNA extracted from the milk fat during lactation accurately portrayed the RNA profile of milk-producing mammary epithelial cells in a non-human primate. However, this sample type clearly requires protocols that minimize RNA degradation. Overall, we validated the use of RNA extracted from human and macaque milk and provided evidence to support the use of lactating macaques as a model for human lactation.

Beschreibung: Background: Group B Sox domain transcription factors play conserved roles in the specification and development of the nervous system in higher metazoans. However, we know comparatively little about how these transcription factors regulate gene expression, and the analysis of Sox gene function in vertebrates is confounded by functional compensation between three closely related family members. In Drosophila, only two group B Sox genes, Dichaete and SoxN, have been shown to function during embryonic CNS development, providing a simpler system for understanding the functions of this important class of regulators. Results: Using a combination of transcriptional profiling and genome-wide binding analysis we conservatively identify over 1000 high confidence direct Dichaete target genes in the Drosophila genome. We show that Dichaete plays key roles in CNS development, regulating aspects of the temporal transcription factor sequence that confer neuroblast identity. Dichaete also shows a complex interaction with Prospero in the pathway controlling the switch from stem cell self-renewal to neural differentiation. Dichaete potentially regulates many more genes in the Drosophila genome and was found to be associated with over 2000 mapped regulatory elements. Conclusions: Our analysis suggests that Dichaete acts as a transcriptional hub, controlling multiple regulatory pathways during CNS development. These include a set of core CNS expressed genes that are also bound by the related Sox2 gene during mammalian CNS development. Furthermore, we identify Dichaete as one of the transcription factors involved in the neural stem cell transcriptional network, with evidence supporting the view that Dichaete is involved in controlling the temporal series of divisions regulating neuroblast identity.

Beschreibung: Background: The next big challenge in human genetics is understanding the 98% of the genome that comprises non-coding DNA. Hidden in this DNA are sequences critical for gene regulation, and new experimental strategies are needed to understand the functional role of gene-regulation sequences in health and disease. In this study, we build upon our HuGX (High-throughput Human Genes on the X Chromosome) strategy to expand our understanding of human gene regulation in vivo. Results: Ten human genes known to express in therapeutically important brain regions were chosen for study. For eight of these genes; human bacterial artificial chromosome clones were identified, retrofitted with a reporter, knocked single-copy into the Hprt locus in mouse embryonic stem cells, and mouse strains derived. Five of these human genes expressed in mouse, and all expressed in the adult brain region for which they were chosen. This defined the boundaries of the genomic DNA sufficient for brain expression, and refined our knowledge regarding the complexity of gene regulation. We also characterized for the first time the expression of human MAOA and NR2F2, two genes for which the mouse homologs have been extensively studied in the central nervous system (CNS), and AMOTL1 and NOV for which roles in CNS have been unclear. Conclusions: We have demonstrated the use of the HuGX strategy to functionally delineate non-coding-regulatory regions of therapeutically important human brain genes. Our results also show that a careful investigation, using publicly available resources and bioinformatics, can lead to accurate prediction of gene expression.

Beschreibung: Background: Phenomena such as incomplete lineage sorting, horizontal gene transfer, gene duplication and subsequent sub- and neo-functionalisation can result in distinct local phylogenetic relationships that are discordant with species phylogeny. In order to assess the possible biological roles for these subdivisions, they must first be identified and characterised, preferably on a large scale and in an automated fashion. Results: We developed Saguaro, a combination of a Hidden Markov Model (HMM) and a Self Organising Map (SOM), to characterise local phylogenetic relationships among aligned sequences using cacti, matrices of pair-wise distance measures. While the HMM determines the genomic boundaries from aligned sequences, the SOM hypothesises new cacti in an unsupervised and iterative fashion based on the regions that were modelled least well by existing cacti. After testing the software on simulated data, we demonstrate the utility of Saguaro by testing two different data sets: (i) 181 Dengue virus strains, and (ii) 5 primate genomes. Saguaro identifies regions under lineage-specific constraint for the first set, and genomic segments that we attribute to incomplete lineage sorting in the second dataset. Intriguingly for the primate data, Saguaro also classified an additional ~3% of the genome as most incompatible with the expected species phylogeny. A substantial fraction of these regions was found to overlap genes associated with both the innate and adaptive immune systems. Conclusions: Saguaro detects distinct cacti describing local phylogenetic relationships without requiring any a priori hypotheses. We have successfully demonstrated Saguaro's utility with two contrasting data sets, one containing many members with short sequences (Dengue viral strains: n = 181, genome size = 10,700 nt), and the other with few members but complex genomes (related primate species: n = 5, genome size = 3 Gb), suggesting that the software is applicable to a wide variety of experimental populations. Saguaro is written in C++, runs on the Linux operating system, and can be downloaded from http://saguarogw.sourceforge.net/.

Beschreibung: Background: Stoichiometric models provide a structural framework for analyzing steady-state cellular behavior. Models are developed either through augmentations of existing models or more recently through automatic reconstruction tools. There is currently no standardized practice or method for validating the properties of a model before placing it in the public domain. Considerable effort is often required to understand a model's inconsistencies before its reuse within new research efforts. Results: We present a review of common issues in stoichiometric models typically uncovered during pathway analysis and constraint-based optimization, and we detail succinct and efficient ways to find them. We present MC3, Model and Constraint Consistency Checker, a computational tool that can be used for two purposes: (a) identifying potential connectivity and topological issues for a given stoichiometric matrix, S, and (b) flagging issues that arise during constraint-based optimization. The MC3 tool includes three distinct checking components. The first examines the results of computing the basis for the null space for Sv = 0; the second uses connectivity analysis; and the third utilizes Flux Variability Analysis. MC3 takes as input a stoichiometric matrix and flux constraints, and generates a report summarizing issues. Conclusions: We report the results of applying MC3 to published models for several systems including Escherichia coli, an adipocyte cell, a Chinese Hamster Ovary cell, and Leishmania major. Several issues with no prior documentation are identified. MC3 provides a standalone MATLAB-based comprehensive tool for model validation, a task currently performed either ad hoc or implemented in part within other computational tools.