Cinteny: flexible analysis and visualization of synteny and genome rearrangements in multiple organisms

BACKGROUND: Identifying syntenic regions, i.e., blocks of genes or other markers with evolutionary conserved order, and quantifying evolutionary relatedness between genomes in terms of chromosomal rearrangements is one of the central goals in comparative genomics. However, the analysis of synteny and the resulting assessment of genome rearrangements are sensitive to the choice of a number of arbitrary parameters that affect the detection of synteny blocks. In particular, the choice of a set of markers and the effect of different aggregation strategies, which enable coarse graining of synteny blocks and exclusion of micro-rearrangements, need to be assessed. Therefore, existing tools and resources that facilitate identification, visualization and analysis of synteny need to be further improved to provide a flexible platform for such analysis, especially in the context of multiple genomes. RESULTS: We present a new tool, Cinteny, for fast identification and analysis of synteny with different sets of markers and various levels of coarse graining of syntenic blocks. Using Hannenhalli-Pevzner approach and its extensions, Cinteny also enables interactive determination of evolutionary relationships between genomes in terms of the number of rearrangements (the reversal distance). In particular, Cinteny provides: i) integration of synteny browsing with assessment of evolutionary distances for multiple genomes; ii) flexibility to adjust the parameters and re-compute the results on-the-fly; iii) ability to work with user provided data, such as orthologous genes, sequence tags or other conserved markers. In addition, Cinteny provides many annotated mammalian, invertebrate and fungal genomes that are pre-loaded and available for analysis at . CONCLUSION: Cinteny allows one to automatically compare multiple genomes and perform sensitivity analysis for synteny block detection and for the subsequent computation of reversal distances. Cinteny can also be used to interactively browse syntenic blocks conserved in multiple genomes, to facilitate genome annotation and validation of assemblies for newly sequenced genomes, and to construct and assess phylogenomic trees

Partitioning of copy-number genotypes in pedigrees

<p>Abstract</p> <p>Background</p> <p>Copy number variations (CNVs) and polymorphisms (CNPs) have only recently gained the genetic community's attention. Conservative estimates have shown that CNVs and CNPs might affect more than 10% of the genome and that they may be at least as important as single nucleotide polymorphisms in assessing human variability. Widely used tools for CNP analysis have been implemented in <it>Birdsuite </it>and <it>PLINK </it>for the purpose of conducting genetic association studies based on the unpartitioned total number of CNP copies provided by the intensities from Affymetrix's Genome-Wide Human SNP Array. Here, we are interested in partitioning copy number variations and polymorphisms in extended pedigrees for the purpose of linkage analysis on familial data.</p> <p>Results</p> <p>We have developed <it>CNGen</it>, a new software for the partitioning of copy number polymorphism using the integrated genotypes from <it>Birdsuite </it>with the Affymetrix platform. The algorithm applied to familial trios or extended pedigrees can produce partitioned copy number genotypes with distinct parental alleles. We have validated the algorithm using simulations on a complex pedigree structure using frequencies calculated from a real dataset of 300 genotyped samples from 42 pedigrees segregating a congenital heart defect phenotype.</p> <p>Conclusions</p> <p><it>CNGen </it>is the first published software for the partitioning of copy number genotypes in pedigrees, making possible the use CNPs and CNVs for linkage analysis. It was implemented with the <it>Python </it>interpreter version 2.5.2. It was successfully tested on current Linux, Windows and Mac OS workstations.</p

Congenital and childhood atrioventricular blocks: pathophysiology and contemporary management

Atrioventricular block is classified as congeni- tal if diagnosed in utero, at birth, or within the first month of life. The pathophysiological process is believed to be due to immune-mediated injury of the conduction system, which occurs as a result of transplacental pas- sage of maternal anti-SSA/Ro-SSB/La antibodies. Childhood atrioventricular block is therefore diagnosed between the first month and the 18th year of life. Genetic variants in multiple genes have been described to date in the pathogenesis of inherited progressive car- diac conduction disorders. Indications and techniques of cardiac pacing have also evolved to allow safe perma- nent cardiac pacing in almost all patients, including those with structural heart abnormalities

Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease

Congenital Heart Disease (CHD) affects approximately 7-9 children per 1000 live births. Numerous genetic studies have established a role for rare genomic variants at the copy number variation (CNV) and single nucleotide variant level. In particular, the role of de novo mutations (DNM) has been highlighted in syndromic and non-syndromic CHD. To identify novel haploinsufficient CHD disease genes we performed an integrative analysis of CNVs and DNMs identified in probands with CHD including cases with sporadic thoracic aortic aneurysm (TAA). We assembled CNV data from 7,958 cases and 14,082 controls and performed a gene-wise analysis of the burden of rare genomic deletions in cases versus controls. In addition, we performed mutation rate testing for DNMs identified in 2,489 parent-offspring trios. Our combined analysis revealed 21 genes which were significantly affected by rare genomic deletions and/or constrained non-synonymous de novo mutations in probands. Fourteen of these genes have previously been associated with CHD while the remaining genes (FEZ1, MYO16, ARID1B, NALCN, WAC, KDM5B and WHSC1) have only been associated in singletons and small cases series, or show new associations with CHD. In addition, a systems level analysis revealed shared contribution of CNV deletions and DNMs in CHD probands, affecting protein-protein interaction networks involved in Notch signaling pathway, heart morphogenesis, DNA repair and cilia/centrosome function. Taken together, this approach highlights the importance of re-analyzing existing datasets to strengthen disease association and identify novel disease genes

Untersuchungen zur Zuverlaessigkeit hybrid-gemischter Finiter Elemente fuer Flaechentragwerke

SIGLEAvailable from TIB Hannover: RN 3694(13) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman