Modal Logics of Topological Relations

Logical formalisms for reasoning about relations between spatial regions play a fundamental role in geographical information systems, spatial and constraint databases, and spatial reasoning in AI. In analogy with Halpern and Shoham's modal logic of time intervals based on the Allen relations, we introduce a family of modal logics equipped with eight modal operators that are interpreted by the Egenhofer-Franzosa (or RCC8) relations between regions in topological spaces such as the real plane. We investigate the expressive power and computational complexity of logics obtained in this way. It turns out that our modal logics have the same expressive power as the two-variable fragment of first-order logic, but are exponentially less succinct. The complexity ranges from (undecidable and) recursively enumerable to highly undecidable, where the recursively enumerable logics are obtained by considering substructures of structures induced by topological spaces. As our undecidability results also capture logics based on the real line, they improve upon undecidability results for interval temporal logics by Halpern and Shoham. We also analyze modal logics based on the five RCC5 relations, with similar results regarding the expressive power, but weaker results regarding the complexity

DNA Methylation of the ABO Promoter Underlies Loss of ABO Allelic Expression in a Significant Proportion of Leukemic Patients

Background: Loss of A, B and H antigens from the red blood cells of patients with myeloid malignancies is a frequent occurrence. Previously, we have reported alterations in ABH antigens on the red blood cells of 55% of patients with myeloid malignancies. Methodology/Principal Findings: To determine the underlying molecular mechanisms of this loss, we assessed ABO allelic expression in 21 patients with ABH antigen loss previously identified by flow cytometric analysis as well as an additional 7 patients detected with ABH antigen changes by serology. When assessing ABO mRNA allelic expression, 6/12 (50%) patients with ABH antigen loss detected by flow cytometry and 5/7 (71%) of the patients with ABH antigen loss detected by serology had a corresponding ABO mRNA allelic loss of expression. We examined the ABO locus for copy number and DNA methylation alterations in 21 patients, 11 with loss of expression of one or both ABO alleles, and 10 patients with no detectable allelic loss of ABO mRNA expression. No loss of heterozygosity (LOH) at the ABO locus was observed in these patients. However in 8/11 (73%) patients with loss of ABO allelic expression, the ABO promoter was methylated compared with 2/10 (20%) of patients with no ABO allelic expression loss (P = 0.03). Conclusions/Significance: We have found that loss of ABH antigens in patients with hematological malignancies is associated with a corresponding loss of ABO allelic expression in a significant proportion of patients. Loss of ABO allelic expression was strongly associated with DNA methylation of the ABO promoter.Tina Bianco-Miotto, Damian J. Hussey, Tanya K. Day, Denise S. O'Keefe and Alexander Dobrovi

Analysis of transcription factor binding at cis-regulatory elements during blood development and differentiation

The overall aim of this work is to understand how regulatory sequences (enhancers, promoters) are bound and interpreted by TFs during erythroid development and differentiation. This is becoming increasingly important as DNA sequence variants in enhancers may alter protein binding and consequently may contribute to changes in gene expression that affect susceptibility to common diseases. We hypothesised that by using high-resolution analysis of chromatin accessibility data, we would identify relevant differences in sequence usage at regulatory regions in erythroid cells at various stages of development and differentiation. To test this, we developed a robust and efficient method to isolate HS regions in erythroid cells by performing DNase-Seq and ATAC-Seq. When analysed at high resolution, open-chromatin assays, namely DNase-Seq, reveal a genome-wide profile of “footprints” - transcription factor bound sites at regulatory elements in different erythroid cell types. The two dynamic contexts, development and differentiation, in which we analysed the changes in HS regions share a common pattern: we identified approximately 10% cell specific HS regions. The differential open-chromatin regions correspond mainly to enhancers, but also promoters. Majority of these elements (&amp;Tilde;80%) occur in different genomic regions. These observations reinforce the fact that differentiation and development are driven by TF binding at distal elements. At the α-globin locus, the quantitative changes of HS regions are correlated with the activity of gene promoters. The level of HS enrichment refines the chromatin signature of functional enhancers. Novel analysis of HS genome-wide data, "average footprinting", provides a constrained set of transcription factor binding sites ranked by their usage in a specific cell type. We also adapted this approach to predict the effect of a variant in a sequence on altering affinity to TF and potentially causing changes in gene expression. This predicted damage score approach can be used to prioritise variants for functional analysis. Finally, we have identified families with unexplained anaemia, which have a SNP in a binding site of the major enhancer of the human α-globin cluster. This variant has a high damage score based on our prediction analysis. We are currently investigating if, and how, this non-coding SNP affects gene expression as an example of how regulatory SNPs in general may contribute to human genetic disease.</p

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome

The influence of HLA-matched sibling donor availability on treatment outcome for patients with AML: an analysis of the AML 8A study of the EORTC Leukaemia Cooperative Group and GIMEMA

To determine whether patients with a HLA-identical sibling donor have a better outcome than patients without a donor, an analysis on the basis of intention-to-treat principles was performed within the framework of the EORTC-GIMEMA randomized phase III AML 8A trial. Patients in complete remission (CR) received one intensive consolidation course. Patients with a histocompatible sibling donor were then allocated allogeneic bone marrow transplantation (alloBMT). the patients without a donor were randomized between autologous BMT (ABMT) and a second intensive consolidation (IC2). 831 patients 8 weeks from diagnosis were included. HLA typing was performed in 672 patients. AlloBMT was performed during CR1 in 180 (61%) out of 295 patients with a donor. Another 38 patients were allografted: ave in resistant disease, 14 during relapse and 19 in CR2, ABMT was performed in 130 (34%) out of 377 patients without a donor in CR1, in six: (2%) patients during relapse and in 38 (10%) patients during CR2. The disease-free survival (DFS) from CR for patients with a donor was significantly longer than for patients without a donor (46% v 33% at 6 years; P = 0.01, RR 0.78, 95% confidence interval 0.63-0.96). The overall survival from diagnosis for patients with a donor was longer, but not statistically significant, than for patients without a donor (48% v 40% at 6 years; logrank P= 0.24). When patients were stratified according to prognostic risk groups, the same trend in favour of patients with a donor was seen for survival duration and the DFS remained significantly longer for this group of patients