Algebraic Comparison of Partial Lists in Bioinformatics

The outcome of a functional genomics pipeline is usually a partial list of genomic features, ranked by their relevance in modelling biological phenotype in terms of a classification or regression model. Due to resampling protocols or just within a meta-analysis comparison, instead of one list it is often the case that sets of alternative feature lists (possibly of different lengths) are obtained. Here we introduce a method, based on the algebraic theory of symmetric groups, for studying the variability between lists ("list stability") in the case of lists of unequal length. We provide algorithms evaluating stability for lists embedded in the full feature set or just limited to the features occurring in the partial lists. The method is demonstrated first on synthetic data in a gene filtering task and then for finding gene profiles on a recent prostate cancer dataset

MICA: desktop software for comprehensive searching of DNA databases

BACKGROUND: Molecular biologists work with DNA databases that often include entire genomes. A common requirement is to search a DNA database to find exact matches for a nondegenerate or partially degenerate query. The software programs available for such purposes are normally designed to run on remote servers, but an appealing alternative is to work with DNA databases stored on local computers. We describe a desktop software program termed MICA (K-Mer Indexing with Compact Arrays) that allows large DNA databases to be searched efficiently using very little memory. RESULTS: MICA rapidly indexes a DNA database. On a Macintosh G5 computer, the complete human genome could be indexed in about 5 minutes. The indexing algorithm recognizes all 15 characters of the DNA alphabet and fully captures the information in any DNA sequence, yet for a typical sequence of length L, the index occupies only about 2L bytes. The index can be searched to return a complete list of exact matches for a nondegenerate or partially degenerate query of any length. A typical search of a long DNA sequence involves reading only a small fraction of the index into memory. As a result, searches are fast even when the available RAM is limited. CONCLUSION: MICA is suitable as a search engine for desktop DNA analysis software

FISH as an effective diagnostic tool for the management of challenging melanocytic lesions

<p>Abstract</p> <p>Background</p> <p>The accuracy of melanoma diagnosis continues to challenge the pathology community, even today with sophisticated histopathologic techniques. Melanocytic lesions exhibit significant morphological heterogeneity. While the majority of biopsies can be classified as benign (nevus) or malignant (melanoma) using well-established histopathologic criteria, there exists a cohort for which the prediction of clinical behaviour and invasive or metastatic potential is difficult if not impossible to ascertain on the basis of morphological features alone. Multiple studies have shown that there is significant disagreement between pathologists and even expert dermatopathologists in the diagnosis of this subgroup of difficult melanocytic lesions.</p> <p>Methods</p> <p>A four probe FISH assay was utilized to analyse a cohort of 500 samples including 157 nevus, 176 dysplastic nevus and 167 melanoma specimens.</p> <p>Results</p> <p>Review of the lesions determined the assay identified genetic abnormalities in a total of 83.8% of melanomas, and 1.9% of nevus without atypia, while genetic abnormalities were identified in 6.3%, 6.7%, and 10.3% of nevus identified with mild, moderate and severe atypia, respectively.</p> <p>Conclusions</p> <p>Based on this study, inheritable genetic damage/instability identified by FISH testing is a hallmark of a progressive malignant process, and a valuable diagnostic tool for the identification of high risk lesions.</p

A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

© 2014 Haider et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options

Genome-scale CRISPR-Cas9 knockout and transcriptional activation screening

Forward genetic screens are powerful tools for the unbiased discovery and functional characterization of specific genetic elements associated with a phenotype of interest. Recently, the RNA-guided endonuclease Cas9 from the microbial CRISPR (clustered regularly interspaced short palindromic repeats) immune system has been adapted for genome-scale screening by combining Cas9 with pooled guide RNA libraries. Here we describe a protocol for genome-scale knockout and transcriptional activation screening using the CRISPR-Cas9 system. Custom- or ready-made guide RNA libraries are constructed and packaged into lentiviral vectors for delivery into cells for screening. As each screen is unique, we provide guidelines for determining screening parameters and maintaining sufficient coverage. To validate candidate genes identified by the screen, we further describe strategies for confirming the screening phenotype, as well as genetic perturbation, through analysis of indel rate and transcriptional activation. Beginning with library design, a genome-scale screen can be completed in 9-15 weeks, followed by 4-5 weeks of validation.Paul & Daisy Soros Fellowships for New Americans (New York, N.Y.)McGovern Institute for Brain Research at MIT (Friends of McGovern Institute Fellowship)Massachusetts Institute of Technology. Poitras Center for Affective Disorders ResearchUnited States. Department of Energy (Computational Science Graduate Fellowship)National Institute of Mental Health (U.S.) (5DP1-MH100706)National Institute of Mental Health (U.S.) (1R01-MH110049)New York Stem Cell FoundationPoitras FoundationSimons FoundationPaul G. Allen Family FoundationVallee FoundationTom HarrimanB. Metcalf

siRNA Off-Target Effects Can Be Reduced at Concentrations That Match Their Individual Potency

Small interfering RNAs (siRNAs) are routinely used to reduce mRNA levels for a specific gene with the goal of studying its function. Several studies have demonstrated that siRNAs are not always specific and can have many off-target effects. The 3′ UTRs of off-target mRNAs are often enriched in sequences that are complementary to the seed-region of the siRNA. We demonstrate that siRNA off-targets can be significantly reduced when cells are treated with a dose of siRNA that is relatively low (e.g. 1 nM), but sufficient to effectively silence the intended target. The reduction in off-targets was demonstrated for both modified and unmodified siRNAs that targeted either STAT3 or hexokinase II. Low concentrations reduced silencing of transcripts with complementarity to the seed region of the siRNA. Similarly, off-targets that were not complementary to the siRNA were reduced at lower doses, including up-regulated genes that are involved in immune response. Importantly, the unintended induction of caspase activity following treatment with a siRNA that targeted hexokinase II was also shown to be a concentration-dependent off-target effect. We conclude that off-targets and their related phenotypic effects can be reduced for certain siRNA that potently silence their intended target at low concentrations

Sex differences in oncogenic mutational processes

Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research

Frizzled 7 and PIP₂ binding by syntenin PDZ₂ domain supports Frizzled 7 trafficking and signalling

PDZ domain-containing proteins work as intracellular scaffolds to control spatio-temporal aspects of cell signalling. This function is supported by the ability of their PDZ domains to bind other proteins such as receptors, but also phosphoinositide lipids important for membrane trafficking. Here we report a crystal structure of the syntenin PDZ tandem in complex with the carboxy-terminal fragment of Frizzled 7 and phosphatidylinositol 4,5-bisphosphate (PIP₂). The crystal structure reveals a tripartite interaction formed via the second PDZ domain of syntenin. Biophysical and biochemical experiments establish co-operative binding of the tripartite complex and identify residues crucial for membrane PIP₂-specific recognition. Experiments with cells support the importance of the syntenin–PIP₂ interaction for plasma membrane targeting of Frizzled 7 and c-jun phosphorylation. This study contributes to our understanding of the biology of PDZ proteins as key players in membrane compartmentalization and dynamics

A Simple but Highly Effective Approach to Evaluate the Prognostic Performance of Gene Expression Signatures

BACKGROUND: Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification. Once a signature is generated, traditional statistical testing is used to evaluate its prognostic performance. However, due to the dimensionality of microarrays, this can lead to false interpretation of these signatures. PRINCIPAL FINDINGS: A method was developed to test batches of a user-specified number of randomly chosen signatures in patient microarray datasets. The percentage of random generated signatures yielding prognostic value was assessed using ROC analysis by calculating the area under the curve (AUC) in six public available cancer patient microarray datasets. We found that a signature consisting of randomly selected genes has an average 10% chance of reaching significance when assessed in a single dataset, but can range from 1% to ∼40% depending on the dataset in question. Increasing the number of validation datasets markedly reduces this number. CONCLUSIONS: We have shown that the use of an arbitrary cut-off value for evaluation of signature significance is not suitable for this type of research, but should be defined for each dataset separately. Our method can be used to establish and evaluate signature performance of any derived gene signature in a dataset by comparing its performance to thousands of randomly generated signatures. It will be of most interest for cases where few data are available and testing in multiple datasets is limited

Identification of Mammalian Protein Quality Control Factors by High-Throughput Cellular Imaging

Protein Quality Control (PQC) pathways are essential to maintain the equilibrium between protein folding and the clearance of misfolded proteins. In order to discover novel human PQC factors, we developed a high-content, high-throughput cell-based assay to assess PQC activity. The assay is based on a fluorescently tagged, temperature sensitive PQC substrate and measures its degradation relative to a temperature insensitive internal control. In a targeted screen of 1591 siRNA genes involved in the Ubiquitin-Proteasome System (UPS) we identified 25 of the 33 genes encoding for 26S proteasome subunits and discovered several novel PQC factors. An unbiased genome-wide siRNA screen revealed the protein translation machinery, and in particular the EIF3 translation initiation complex, as a novel key modulator of misfolded protein stability. These results represent a comprehensive unbiased survey of human PQC components and establish an experimental tool for the discovery of genes that are required for the degradation of misfolded proteins under conditions of proteotoxic stress