i-ADHoRe 3.0—fast and sensitive detection of genomic homology in extremely large data sets

Comparative genomics is a powerful means to gain insight into the evolutionary processes that shape the genomes of related species. As the number of sequenced genomes increases, the development of software to perform accurate cross-species analyses becomes indispensable. However, many implementations that have the ability to compare multiple genomes exhibit unfavorable computational and memory requirements, limiting the number of genomes that can be analyzed in one run. Here, we present a software package to unveil genomic homology based on the identification of conservation of gene content and gene order (collinearity), i-ADHoRe 3.0, and its application to eukaryotic genomes. The use of efficient algorithms and support for parallel computing enable the analysis of large-scale data sets. Unlike other tools, i-ADHoRe can process the Ensembl data set, containing 49 species, in 1 h. Furthermore, the profile search is more sensitive to detect degenerate genomic homology than chaining pairwise collinearity information based on transitive homology. From ultra-conserved collinear regions between mammals and birds, by integrating coexpression information and protein–protein interactions, we identified more than 400 regions in the human genome showing significant functional coherence. The different algorithmical improvements ensure that i-ADHoRe 3.0 will remain a powerful tool to study genome evolution

BLSSpeller : exhaustive comparative discovery of conserved cis-regulatory elements

Motivation: The accurate discovery and annotation of regulatory elements remains a challenging problem. The growing number of sequenced genomes creates new opportunities for comparative approaches to motif discovery. Putative binding sites are then considered to be functional if they are conserved in orthologous promoter sequences of multiple related species. Existing methods for comparative motif discovery usually rely on pregenerated multiple sequence alignments, which are difficult to obtain for more diverged species such as plants. As a consequence, misaligned regulatory elements often remain undetected. Results: We present a novel algorithm that supports both alignment-free and alignment-based motif discovery in the promoter sequences of related species. Putative motifs are exhaustively enumerated as words over the IUPAC alphabet and screened for conservation using the branch length score. Additionally, a confidence score is established in a genome-wide fashion. In order to take advantage of a cloud computing infrastructure, the MapReduce programming model is adopted. The method is applied to four monocotyledon plant species and it is shown that high-scoring motifs are significantly enriched for open chromatin regions in Oryza sativa and for transcription factor binding sites inferred through protein-binding microarrays in O. sativa and Zea mays. Furthermore, the method is shown to recover experimentally profiled ga2ox1-like KN1 binding sites in Z. mays

Losartan therapy in adults with Marfan syndrome: study protocol of the multi-center randomized controlled COMPARE trial

Contains fulltext : 87305.pdf (publisher's version ) (Open Access

Inflammation Aggravates Disease Severity in Marfan Syndrome Patients

BACKGROUND: Marfan syndrome (MFS) is a pleiotropic genetic disorder with major features in cardiovascular, ocular and skeletal systems, associated with large clinical variability. Numerous studies reveal an involvement of TGF-beta signaling. However, the contribution of tissue inflammation is not addressed so far. METHODOLOGY/PRINCIPAL FINDINGS: Here we showed that both TGF-beta and inflammation are up-regulated in patients with MFS. We analyzed transcriptome-wide gene expression in 55 MFS patients using Affymetrix Human Exon 1.0 ST Array and levels of TGF-beta and various cytokines in their plasma. Within our MFS population, increased plasma levels of TGF-beta were found especially in MFS patients with aortic root dilatation (124 pg/ml), when compared to MFS patients with normal aorta (10 pg/ml; p = 8x10(-6), 95% CI: 70-159 pg/ml). Interestingly, our microarray data show that increased expression of inflammatory genes was associated with major clinical features within the MFS patients group; namely severity of the aortic root dilatation (HLA-DRB1 and HLA-DRB5 genes; r = 0.56 for both; False Discovery Rate(FDR) = 0%), ocular lens dislocation (RAET1L, CCL19 and HLA-DQB2; Fold Change (FC) = 1.8; 1.4; 1.5, FDR = 0%) and specific skeletal features (HLA-DRB1, HLA-DRB5, GZMK; FC = 8.8, 7.1, 1.3; FDR = 0%). Patients with progressive aortic disease had higher levels of Macrophage Colony Stimulating Factor (M-CSF) in blood. When comparing MFS aortic root vessel wall with non-MFS aortic root, increased numbers of CD4+ T-cells were found in the media (p = 0.02) and increased number of CD8+ T-cells (p = 0.003) in the adventitia of the MFS patients. CONCLUSION/SIGNIFICANCE: In conclusion, our results imply a modifying role of inflammation in MFS. Inflammation might be a novel therapeutic target in these patients

Genome-wide association of major depression: description of samples for the GAIN Major Depressive Disorder Study: NTR and NESDA biobank projects.

To identify the genomic regions that confer risk and protection for major depressive disorder (MDD) in humans, large-scale studies are needed. Such studies should collect multiple phenotypes, DNA, and ideally, biological material that allows gene expression analysis, transcriptomic, proteomic, and metabolomic studies. In this paper, we briefly review linkage studies of MDD and then describe the large-scale nationwide biological sample collection in Dutch twin families from the Netherlands Twin Register (NTR) and in participants in the Netherlands Study of Depression and Anxiety (NESDA). Within these studies, 1862 participants with a diagnosis of MDD and 1857 controls at low liability for MDD have been selected for genome-wide genotyping by the US Foundation for the National Institutes of Health Genetic Association Information Network. Stage 1 genome-wide association results are scheduled to be accessible before the end of 2007. Genome-wide association results are open-access and can be viewed at the dbGAP web portal (http://www.ncbi.nlm.nih.gov). Approved users can download the genotype and phenotype data, which have been made available as of 9 October 2007