SNPFile – A software library and file format for large scale association mapping and population genetics studies

<p>Abstract</p> <p>Background</p> <p>High-throughput genotyping technology has enabled cost effective typing of thousands of individuals in hundred of thousands of markers for use in genome wide studies. This vast improvement in data acquisition technology makes it an informatics challenge to efficiently store and manipulate the data. While spreadsheets and at text files were adequate solutions earlier, the increased data size mandates more efficient solutions.</p> <p>Results</p> <p>We describe a new binary file format for SNP data, together with a software library for file manipulation. The file format stores genotype data together with any kind of additional data, using a flexible serialisation mechanism. The format is designed to be IO efficient for the access patterns of most multi-locus analysis methods.</p> <p>Conclusion</p> <p>The new file format has been very useful for our own studies where it has significantly reduced the informatics burden in keeping track of various secondary data, and where the memory and IO efficiency has greatly simplified analysis runs. A main limitation with the file format is that it is only supported by the very limited set of analysis tools developed in our own lab. This is somewhat alleviated by a scripting interfaces that makes it easy to write converters to and from the format.</p

A fast algorithm for genome-wide haplotype pattern mining

<p>Abstract</p> <p>Background</p> <p>Identifying the genetic components of common diseases has long been an important area of research. Recently, genotyping technology has reached the level where it is cost effective to genotype single nucleotide polymorphism (SNP) markers covering the entire genome, in thousands of individuals, and analyse such data for markers associated with a diseases. The statistical power to detect association, however, is limited when markers are analysed one at a time. This can be alleviated by considering multiple markers simultaneously. The <it>Haplotype Pattern Mining </it>(HPM) method is a machine learning approach to do exactly this.</p> <p>Results</p> <p>We present a new, faster algorithm for the HPM method. The new approach use patterns of haplotype diversity in the genome: locally in the genome, the number of observed haplotypes is much smaller than the total number of possible haplotypes. We show that the new approach speeds up the HPM method with a factor of 2 on a genome-wide dataset with 5009 individuals typed in 491208 markers using default parameters and more if the pattern length is increased.</p> <p>Conclusion</p> <p>The new algorithm speeds up the HPM method and we show that it is feasible to apply HPM to whole genome association mapping with thousands of individuals and hundreds of thousands of markers.</p

SLEPR: A Sample-Level Enrichment-Based Pathway Ranking Method — Seeking Biological Themes through Pathway-Level Consistency

Analysis of microarray and other high throughput data often involves identification of genes consistently up or down-regulated across samples as the first step in extraction of biological meaning. This gene-level paradigm can be limited as a result of valid sample fluctuations and biological complexities. In this report, we describe a novel method, SLEPR, which eliminates this limitation by relying on pathway-level consistencies. Our method first selects the sample-level differentiated genes from each individual sample, capturing genes missed by other analysis methods, ascertains the enrichment levels of associated pathways from each of those lists, and then ranks annotated pathways based on the consistency of enrichment levels of individual samples from both sample classes. As a proof of concept, we have used this method to analyze three public microarray datasets with a direct comparison with the GSEA method, one of the most popular pathway-level analysis methods in the field. We found that our method was able to reproduce the earlier observations with significant improvements in depth of coverage for validated or expected biological themes, but also produced additional insights that make biological sense. This new method extends existing analyses approaches and facilitates integration of different types of HTP data

Tissue distribution of the laminin β1 and β2 chain during embryonic and fetal human development

Laminins are the major glycoproteins present in all basement membranes. Previously, we showed that perlecan is present during human development. Although an overview of mRNA-expression of the laminin β1 and β2 chains in various developing fetal organs is already available, a systematic localization of the laminin β1 and β2 chains on the protein level during embryonic and fetal human development is missing. Therefore, we studied the immunohistochemical expression and tissue distribution of the laminin β1 and β2 chains in various developing embryonic and fetal human organs between gestational weeks 8 and 12. The laminin β1 chain was ubiquitously expressed in the basement membrane zones of the brain, ganglia, blood vessels, liver, kidney, skin, pancreas, intestine, heart and skeletal system. Furthermore, the laminin β2 chain was present in the basement membrane zones of the brain, ganglia, skin, heart and skeletal system. The findings of this study support and expand upon the theory that these two laminin chains are important during human development

A telephone survey of parental attitudes and behaviours regarding teenage drinking

<p>Abstract</p> <p>Background</p> <p>Irish teenagers demonstrate high rates of drunkenness and there has been a progressive fall in age of first drinking in recent decades. International research indicates that parents exert substantial influence over their teenager's drinking. We sought to determine the attitudes and behaviours of Irish parents towards drinking by their adolescent children.</p> <p>Methods</p> <p>We conducted a telephone survey of a representative sample of of 234 parents who had a teenager aged between 13 and 17 years.</p> <p>Results</p> <p>Six per cent reported that they would be unconcerned if their son or daughter was to binge drink once per month. On the issue of introducing children to alcohol in the home, 27% viewed this as a good idea while 63% disagreed with this practice. Eleven per cent of parents reported that they had given a drink to their teenager at home. Parents who drank regularly themselves, who were from higher socio-demographic groups and who lived in the east of Ireland demonstrated more permissive attitudes to teenage drinking.</p> <p>Conclusions</p> <p>We found no evidence of widespread permissive attitudes and behaviours among Irish parents. Given that parental influences have been demonstrated to exert substantial impact on teenage drinking, it may be possible to harness the concerns of Irish parents more effectively to reverse the trends of escalating alcohol related harm in Ireland.</p

Whole genome association mapping by incompatibilities and local perfect phylogenies

BACKGROUND: With current technology, vast amounts of data can be cheaply and efficiently produced in association studies, and to prevent data analysis to become the bottleneck of studies, fast and efficient analysis methods that scale to such data set sizes must be developed. RESULTS: We present a fast method for accurate localisation of disease causing variants in high density case-control association mapping experiments with large numbers of cases and controls. The method searches for significant clustering of case chromosomes in the "perfect" phylogenetic tree defined by the largest region around each marker that is compatible with a single phylogenetic tree. This perfect phylogenetic tree is treated as a decision tree for determining disease status, and scored by its accuracy as a decision tree. The rationale for this is that the perfect phylogeny near a disease affecting mutation should provide more information about the affected/unaffected classification than random trees. If regions of compatibility contain few markers, due to e.g. large marker spacing, the algorithm can allow the inclusion of incompatibility markers in order to enlarge the regions prior to estimating their phylogeny. Haplotype data and phased genotype data can be analysed. The power and efficiency of the method is investigated on 1) simulated genotype data under different models of disease determination 2) artificial data sets created from the HapMap ressource, and 3) data sets used for testing of other methods in order to compare with these. Our method has the same accuracy as single marker association (SMA) in the simplest case of a single disease causing mutation and a constant recombination rate. However, when it comes to more complex scenarios of mutation heterogeneity and more complex haplotype structure such as found in the HapMap data our method outperforms SMA as well as other fast, data mining approaches such as HapMiner and Haplotype Pattern Mining (HPM) despite being significantly faster. For unphased genotype data, an initial step of estimating the phase only slightly decreases the power of the method. The method was also found to accurately localise the known susceptibility variants in an empirical data set – the ΔF508 mutation for cystic fibrosis – where the susceptibility variant is already known – and to find significant signals for association between the CYP2D6 gene and poor drug metabolism, although for this dataset the highest association score is about 60 kb from the CYP2D6 gene. CONCLUSION: Our method has been implemented in the Blossoc (BLOck aSSOCiation) software. Using Blossoc, genome wide chip-based surveys of 3 million SNPs in 1000 cases and 1000 controls can be analysed in less than two CPU hours

Hox10 Genes Function in Kidney Development in the Differentiation and Integration of the Cortical Stroma

Organogenesis requires the differentiation and integration of distinct populations of cells to form a functional organ. In the kidney, reciprocal interactions between the ureter and the nephrogenic mesenchyme are required for organ formation. Additionally, the differentiation and integration of stromal cells are also necessary for the proper development of this organ. Much remains to be understood regarding the origin of cortical stromal cells and the pathways involved in their formation and function. By generating triple mutants in the Hox10 paralogous group genes, we demonstrate that Hox10 genes play a critical role in the developing kidney. Careful examination of control kidneys show that Foxd1-expressing stromal precursor cells are first observed in a cap-like pattern anterior to the metanephric mesenchyme and these cells subsequently integrate posteriorly into the kidney periphery as development proceeds. While the initial cap-like pattern of Foxd1-expressing cortical stromal cells is unaffected in Hox10 mutants, these cells fail to become properly integrated into the kidney, and do not differentiate to form the kidney capsule. Consistent with loss of cortical stromal cell function, Hox10 mutant kidneys display reduced and aberrant ureter branching, decreased nephrogenesis. These data therefore provide critical novel insights into the cellular and genetic mechanisms governing cortical cell development during kidney organogenesis. These results, combined with previous evidence demonstrating that Hox11 genes are necessary for patterning the metanephric mesenchyme, support a model whereby distinct populations in the nephrogenic cord are regulated by unique Hox codes, and that differential Hox function along the AP axis of the nephrogenic cord is critical for the differentiation and integration of these cell types during kidney organogenesis

T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection.

The clinical course of autoimmune and infectious disease varies greatly, even between individuals with the same condition. An understanding of the molecular basis for this heterogeneity could lead to significant improvements in both monitoring and treatment. During chronic infection the process of T-cell exhaustion inhibits the immune response, facilitating viral persistence. Here we show that a transcriptional signature reflecting CD8 T-cell exhaustion is associated with poor clearance of chronic viral infection, but conversely predicts better prognosis in multiple autoimmune diseases. The development of CD8 T-cell exhaustion during chronic infection is driven both by persistence of antigen and by a lack of accessory 'help' signals. In autoimmunity, we find that where evidence of CD4 T-cell co-stimulation is pronounced, that of CD8 T-cell exhaustion is reduced. We can reproduce the exhaustion signature by modifying the balance of persistent stimulation of T-cell antigen receptors and specific CD2-induced co-stimulation provided to human CD8 T cells in vitro, suggesting that each process plays a role in dictating outcome in autoimmune disease. The 'non-exhausted' T-cell state driven by CD2-induced co-stimulation is reduced by signals through the exhaustion-associated inhibitory receptor PD-1, suggesting that induction of exhaustion may be a therapeutic strategy in autoimmune and inflammatory disease. Using expression of optimal surrogate markers of co-stimulation/exhaustion signatures in independent data sets, we confirm an association with good clinical outcome or response to therapy in infection (hepatitis C virus) and vaccination (yellow fever, malaria, influenza), but poor outcome in autoimmune and inflammatory disease (type 1 diabetes, anti-neutrophil cytoplasmic antibody-associated vasculitis, systemic lupus erythematosus, idiopathic pulmonary fibrosis and dengue haemorrhagic fever). Thus, T-cell exhaustion plays a central role in determining outcome in autoimmune disease and targeted manipulation of this process could lead to new therapeutic opportunities

Assessment of motor functioning in the preschool period

The assessment of motor functioning in young children has become increasingly important in recent years with the acknowledgement that motor impairment is linked with cognitive, language, social and emotional difficulties. However, there is no one gold standard assessment tool to investigate motor ability in children. The aim of the current paper was to discuss the issues related to the assessment of motor ability in young pre-school children and to provide guidelines on the best approach for motor assessment. The paper discusses the maturational changes in brain development at the preschool level in relation to motor ability. Other issues include sex differences in motor ability at this young age, and evidence for this in relation to sociological versus biological influences. From the previous literature it is unclear what needs to be assessed in relation to motor functioning. Should the focus be underlying motor processes or movement skill assessment? Several key assessment tools are discussed that produce a general measure of motor performance followed by a description of tools that assess specific skills, such as fine and gross motor, ball and graphomotor skills. The paper concludes with recommendations on the best approach in assessing motor function in pre-school children