Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data

Background: MicroRNAs (miRNAs) are short, non-coding RNA regulators of protein coding genes. miRNAs play a very important role in diverse biological processes and various diseases. Many algorithms are able to predict miRNA genes and their targets, but their transcription regulation is still under investigation. It is generally believed that intragenic miRNAs (located in introns or exons of protein coding genes) are co-transcribed with their host genes and most intergenic miRNAs transcribed from their own RNA polymerase II (Pol II) promoter. However, the length of the primary transcripts and promoter organization is currently unknown. Methodology: We performed Pol II chromatin immunoprecipitation (ChIP)-chip using a custom array surrounding regions of known miRNA genes. To identify the true core transcription start sites of the miRNA genes we developed a new tool (CPPP). We showed that miRNA genes can be transcribed from promoters located several kilobases away and that their promoters share the same general features as those of protein coding genes. Finally, we found evidence that as many as 26% of the intragenic miRNAs may be transcribed from their own unique promoters. Conclusion: miRNA promoters have similar features to those of protein coding genes, but miRNA transcript organization is more complex. © 2009 Corcoran et al

Male gender, Charnley class C, and severity of bone defects predict the risk for aseptic loosening in the cup of ABG I hip arthroplasty

<p>Abstract</p> <p>Background</p> <p>We studied which factor could predict aseptic loosening in ABG I hip prosthesis with hydroxyapatite coating. Aseptic loosening and periprosthetic osteolysis are believed to be caused, at least in part, by increased polyethylene (PE) wear rate via particle disease. Based on it, increased PE wear rate should be associated with aseptic loosening regardless of the type of implant.</p> <p>Methods</p> <p>We analyzed data from 155 revisions of ABG I hip prostheses to examine the influence of patient, implant, surgery, and wear related factors on the rate of aseptic loosening at the site of the cup. This was calculated by stepwise logistic regression analysis. The stability of the implant and severity of bone defects were evaluated intraoperatively.</p> <p>Results</p> <p>We found that men (odds ratio, OR = 5.6; <it>p </it>= 0.004), patients with Charnley class C (OR = 6.71; <it>p </it>= 0.013), those having more severe acetabular bone defects (OR = 4 for each degree of severity; <it>p </it>= 0.002), and longer time to revision surgery (OR = 1.51 for each additional year; <it>p </it>= 0.012) had a greater chance of aseptic loosening of the cup. However, aseptic loosening was not directly predicted by polyethylene wear rate in our patients.</p> <p>Conclusion</p> <p>Severity of bone defects predicts the risk for aseptic loosening in ABG I cup. Factors potentially associated with the quality of bone bed and biomechanics of the hip might influence on the risk of aseptic loosening in this implant.</p

Three Ways of Combining Genotyping and Resequencing in Case-Control Association Studies

We describe three statistical results that we have found to be useful in case-control genetic association testing. All three involve combining the discovery of novel genetic variants, usually by sequencing, with genotyping methods that recognize previously discovered variants. We first consider expanding the list of known variants by concentrating variant-discovery in cases. Although the naive inclusion of cases-only sequencing data would create a bias, we show that some sequencing data may be retained, even if controls are not sequenced. Furthermore, for alleles of intermediate frequency, cases-only sequencing with bias-correction entails little if any loss of power, compared to dividing the same sequencing effort among cases and controls. Secondly, we investigate more strongly focused variant discovery to obtain a greater enrichment for disease-related variants. We show how case status, family history, and marker sharing enrich the discovery set by increments that are multiplicative with penetrance, enabling the preferential discovery of high-penetrance variants. A third result applies when sequencing is the primary means of counting alleles in both cases and controls, but a supplementary pooled genotyping sample is used to identify the variants that are very rare. We show that this raises no validity issues, and we evaluate a less expensive and more adaptive approach to judging rarity, based on group-specific variants. We demonstrate the important and unusual caveat that this method requires equal sample sizes for validity. These three results can be used to more efficiently detect the association of rare genetic variants with disease

Part 1: CT characterisation of pancreatic neoplasms: a pictorial essay

The pancreas is a site of origin of a diverse range of benign and malignant tumours, and these are frequently detected, diagnosed and staged with computed tomography (CT). Knowledge of the typical appearance of these neoplasms as well as the features of locoregional invasion is fundamental for all general and abdominal radiologists. This pictorial essay aims to outline the characteristic CT appearances of the spectrum of pancreatic neoplasms, as well as important demographic and clinical information that aids diagnosis. The second article in this series addresses common mimics of pancreatic neoplasia

Oblique decision trees for spatial pattern detection: optimal algorithm and application to malaria risk

BACKGROUND: In order to detect potential disease clusters where a putative source cannot be specified, classical procedures scan the geographical area with circular windows through a specified grid imposed to the map. However, the choice of the windows' shapes, sizes and centers is critical and different choices may not provide exactly the same results. The aim of our work was to use an Oblique Decision Tree model (ODT) which provides potential clusters without pre-specifying shapes, sizes or centers. For this purpose, we have developed an ODT-algorithm to find an oblique partition of the space defined by the geographic coordinates. METHODS: ODT is based on the classification and regression tree (CART). As CART finds out rectangular partitions of the covariate space, ODT provides oblique partitions maximizing the interclass variance of the independent variable. Since it is a NP-Hard problem in R(N), classical ODT-algorithms use evolutionary procedures or heuristics. We have developed an optimal ODT-algorithm in R(2), based on the directions defined by each couple of point locations. This partition provided potential clusters which can be tested with Monte-Carlo inference. We applied the ODT-model to a dataset in order to identify potential high risk clusters of malaria in a village in Western Africa during the dry season. The ODT results were compared with those of the Kulldorff' s SaTScan™. RESULTS: The ODT procedure provided four classes of risk of infection. In the first high risk class 60%, 95% confidence interval (CI95%) [52.22–67.55], of the children was infected. Monte-Carlo inference showed that the spatial pattern issued from the ODT-model was significant (p < 0.0001). Satscan results yielded one significant cluster where the risk of disease was high with an infectious rate of 54.21%, CI95% [47.51–60.75]. Obviously, his center was located within the first high risk ODT class. Both procedures provided similar results identifying a high risk cluster in the western part of the village where a mosquito breeding point was located. CONCLUSION: ODT-models improve the classical scanning procedures by detecting potential disease clusters independently of any specification of the shapes, sizes or centers of the clusters

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

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

The small-nucleolar RNAs commonly used for microRNA normalisation correlate with tumour pathology and prognosis

Background:To investigate small-nucleolar RNAs (snoRNAs) as reference genes when measuring miRNA expression in tumour samples, given emerging evidence for their role in cancer.Methods:Four snoRNAs, commonly used for normalisation, RNU44, RNU48, RNU43 and RNU6B, and miRNA known to be associated with pathological factors, were measured by real-time polymerase chain reaction in two patient series: 219 breast cancer and 46 head and neck squamous cell carcinoma (HNSCC). SnoRNA and miRNA were then correlated with clinicopathological features and prognosis.Results:Small-nucleolar RNA expression was as variable as miRNA expression (miR-21, miR-210, miR-10b). Normalising miRNA PCR expression data to these recommended snoRNAs introduced bias in associations between miRNA and pathology or outcome. Low snoRNA expression correlated with markers of aggressive pathology. Low levels of RNU44 were associated with a poor prognosis. RNU44 is an intronic gene in a cluster of highly conserved snoRNAs in the growth arrest specific 5 (GAS5) transcript, which is normally upregulated to arrest cell growth under stress. Low-tumour GAS5 expression was associated with a poor prognosis. RNU48 and RNU43 were also identified as intronic snoRNAs within genes that are dysregulated in cancer.Conclusion:Small-nucleolar RNAs are important in cancer prognosis, and their use as reference genes can introduce bias when determining miRNA expression. © 2011 Cancer Research UK All rights reserved

An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology

<p>Abstract</p> <p>Background</p> <p>Semantic similarity measures are useful to assess the physiological relevance of protein-protein interactions (PPIs). They quantify similarity between proteins based on their function using annotation systems like the Gene Ontology (GO). Proteins that interact in the cell are likely to be in similar locations or involved in similar biological processes compared to proteins that do not interact. Thus the more semantically similar the gene function annotations are among the interacting proteins, more likely the interaction is physiologically relevant. However, most semantic similarity measures used for PPI confidence assessment do not consider the unequal depth of term hierarchies in different classes of cellular location, molecular function, and biological process ontologies of GO and thus may over-or under-estimate similarity.</p> <p>Results</p> <p>We describe an improved algorithm, Topological Clustering Semantic Similarity (TCSS), to compute semantic similarity between GO terms annotated to proteins in interaction datasets. Our algorithm, considers unequal depth of biological knowledge representation in different branches of the GO graph. The central idea is to divide the GO graph into sub-graphs and score PPIs higher if participating proteins belong to the same sub-graph as compared to if they belong to different sub-graphs.</p> <p>Conclusions</p> <p>The TCSS algorithm performs better than other semantic similarity measurement techniques that we evaluated in terms of their performance on distinguishing true from false protein interactions, and correlation with gene expression and protein families. We show an average improvement of 4.6 times the <it>F</it>₁score over Resnik, the next best method, on our <it>Saccharomyces cerevisiae </it>PPI dataset and 2 times on our <it>Homo sapiens </it>PPI dataset using cellular component, biological process and molecular function GO annotations.</p

Genome Evolution of a Tertiary Dinoflagellate Plastid

The dinoflagellates have repeatedly replaced their ancestral peridinin-plastid by plastids derived from a variety of algal lineages ranging from green algae to diatoms. Here, we have characterized the genome of a dinoflagellate plastid of tertiary origin in order to understand the evolutionary processes that have shaped the organelle since it was acquired as a symbiont cell. To address this, the genome of the haptophyte-derived plastid in Karlodinium veneficum was analyzed by Sanger sequencing of library clones and 454 pyrosequencing of plastid enriched DNA fractions. The sequences were assembled into a single contig of 143 kb, encoding 70 proteins, 3 rRNAs and a nearly full set of tRNAs. Comparative genomics revealed massive rearrangements and gene losses compared to the haptophyte plastid; only a small fraction of the gene clusters usually found in haptophytes as well as other types of plastids are present in K. veneficum. Despite the reduced number of genes, the K. veneficum plastid genome has retained a large size due to expanded intergenic regions. Some of the plastid genes are highly diverged and may be pseudogenes or subject to RNA editing. Gene losses and rearrangements are also features of the genomes of the peridinin-containing plastids, apicomplexa and Chromera, suggesting that the evolutionary processes that once shaped these plastids have occurred at multiple independent occasions over the history of the Alveolata