38 research outputs found

    Characterization of the linkage disequilibrium structure and identification of tagging-SNPs in five DNA repair genes

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    BACKGROUND: Characterization of the linkage disequilibrium (LD) structure of candidate genes is the basis for an effective association study of complex diseases such as cancer. In this study, we report the LD and haplotype architecture and tagging-single nucleotide polymorphisms (tSNPs) for five DNA repair genes: ATM, MRE11A, XRCC4, NBS1 and RAD50. METHODS: The genes ATM, MRE11A, and XRCC4 were characterized using a panel of 94 unrelated female subjects (47 breast cancer cases, 47 controls) obtained from high-risk breast cancer families. A similar LD structure and tSNP analysis was performed for NBS1 and RAD50, using publicly available genotyping data. We studied a total of 61 SNPs at an average marker density of 10 kb. Using a matrix decomposition algorithm, based on principal component analysis, we captured >90% of the intragenetic variation for each gene. RESULTS: Our results revealed that three of the five genes did not conform to a haplotype block structure (MRE11A, RAD50 and XRCC4). Instead, the data fit a more flexible LD group paradigm, where SNPs in high LD are not required to be contiguous. Traditional haplotype blocks assume recombination is the only dynamic at work. For ATM, MRE11A and XRCC4 we repeated the analysis in cases and controls separately to determine whether LD structure was consistent across breast cancer cases and controls. No substantial difference in LD structures was found. CONCLUSION: This study suggests that appropriate SNP selection for an association study involving candidate genes should allow for both mutation and recombination, which shape the population-level genomic structure. Furthermore, LD structure characterization in either breast cancer cases or controls appears to be sufficient for future cancer studies utilizing these genes

    HMMerThread: Detecting Remote, Functional Conserved Domains in Entire Genomes by Combining Relaxed Sequence-Database Searches with Fold Recognition

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    Conserved domains in proteins are one of the major sources of functional information for experimental design and genome-level annotation. Though search tools for conserved domain databases such as Hidden Markov Models (HMMs) are sensitive in detecting conserved domains in proteins when they share sufficient sequence similarity, they tend to miss more divergent family members, as they lack a reliable statistical framework for the detection of low sequence similarity. We have developed a greatly improved HMMerThread algorithm that can detect remotely conserved domains in highly divergent sequences. HMMerThread combines relaxed conserved domain searches with fold recognition to eliminate false positive, sequence-based identifications. With an accuracy of 90%, our software is able to automatically predict highly divergent members of conserved domain families with an associated 3-dimensional structure. We give additional confidence to our predictions by validation across species. We have run HMMerThread searches on eight proteomes including human and present a rich resource of remotely conserved domains, which adds significantly to the functional annotation of entire proteomes. We find ∼4500 cross-species validated, remotely conserved domain predictions in the human proteome alone. As an example, we find a DNA-binding domain in the C-terminal part of the A-kinase anchor protein 10 (AKAP10), a PKA adaptor that has been implicated in cardiac arrhythmias and premature cardiac death, which upon stress likely translocates from mitochondria to the nucleus/nucleolus. Based on our prediction, we propose that with this HLH-domain, AKAP10 is involved in the transcriptional control of stress response. Further remotely conserved domains we discuss are examples from areas such as sporulation, chromosome segregation and signalling during immune response. The HMMerThread algorithm is able to automatically detect the presence of remotely conserved domains in proteins based on weak sequence similarity. Our predictions open up new avenues for biological and medical studies. Genome-wide HMMerThread domains are available at http://vm1-hmmerthread.age.mpg.de

    Vampires in the village Žrnovo on the island of Korčula: following an archival document from the 18th century

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    Središnja tema rada usmjerena je na raščlambu spisa pohranjenog u Državnom arhivu u Mlecima (fond: Capi del Consiglio de’ Dieci: Lettere di Rettori e di altre cariche) koji se odnosi na događaj iz 1748. godine u korčulanskom selu Žrnovo, kada su mještani – vjerujući da su se pojavili vampiri – oskvrnuli nekoliko mjesnih grobova. U radu se podrobno iznose osnovni podaci iz spisa te rečeni događaj analizira u širem društvenom kontekstu i prate se lokalna vjerovanja.The main interest of this essay is the analysis of the document from the State Archive in Venice (file: Capi del Consiglio de’ Dieci: Lettere di Rettori e di altre cariche) which is connected with the episode from 1748 when the inhabitants of the village Žrnove on the island of Korčula in Croatia opened tombs on the local cemetery in the fear of the vampires treating. This essay try to show some social circumstances connected with this event as well as a local vernacular tradition concerning superstitions

    Superimposed holographic image—guided neurosurgery

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    FINDSITE LHM: A Threading-Based Approach to Ligand Homology Modeling

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    ©2009 Brylinski, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.DOI: 10.1371/journal.pcbi.1000405The characters LHM are superscript in the title.Ligand virtual screening is a widely used tool to assist in new pharmaceutical discovery. In practice, virtual screening approaches have a number of limitations, and the development of new methodologies is required. Previously, we showed that remotely related proteins identified by threading often share a common binding site occupied by chemically similar ligands. Here, we demonstrate that across an evolutionarily related, but distant family of proteins, the ligands that bind to the common binding site contain a set of strongly conserved anchor functional groups as well as a variable region that accounts for their binding specificity. Furthermore, the sequence and structure conservation of residues contacting the anchor functional groups is significantly higher than those contacting ligand variable regions. Exploiting these insights, we developed FINDSITELHM that employs structural information extracted from weakly related proteins to perform rapid ligand docking by homology modeling. In large scale benchmarking, using the predicted anchor-binding mode and the crystal structure of the receptor, FINDSITELHM outperforms classical docking approaches with an average ligand RMSD from native of ,2.5 A° . For weakly homologous receptor protein models, using FINDSITELHM, the fraction of recovered binding residues and specific contacts is 0.66 (0.55) and 0.49 (0.38) for highly confident (all) targets, respectively. Finally, in virtual screening for HIV-1 protease inhibitors, using similarity to the ligand anchor region yields significantly improved enrichment factors. Thus, the rather accurate, computationally inexpensive FINDSITELHM algorithm should be a useful approach to assist in the discovery of novel biopharmaceuticals
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