Refphase: Multi-sample phasing reveals haplotype-specific copy number heterogeneity.

Most computational methods that infer somatic copy number alterations (SCNAs) from bulk sequencing of DNA analyse tumour samples individually. However, the sequencing of multiple tumour samples from a patient's disease is an increasingly common practice. We introduce Refphase, an algorithm that leverages this multi-sampling approach to infer haplotype-specific copy numbers through multi-sample phasing. We demonstrate Refphase's ability to infer haplotype-specific SCNAs and characterise their intra-tumour heterogeneity, to uncover previously undetected allelic imbalance in low purity samples, and to identify parallel evolution in the context of whole genome doubling in a pan-cancer cohort of 336 samples from 99 tumours.

RNA Sequencing of Human Peripheral Blood Cells Indicates Upregulation of Immune-Related Genes in Huntington's Disease.

Huntington's disease (HD) is an autosomal dominantly inherited neurodegenerative disorder caused by a trinucleotide repeat expansion in the Huntingtin gene. As disease-modifying therapies for HD are being developed, peripheral blood cells may be used to indicate disease progression and to monitor treatment response. In order to investigate whether gene expression changes can be found in the blood of individuals with HD that distinguish them from healthy controls, we performed transcriptome analysis by next-generation sequencing (RNA-seq). We detected a gene expression signature consistent with dysregulation of immune-related functions and inflammatory response in peripheral blood from HD cases vs. controls, including induction of the interferon response genes, IFITM3, IFI6 and IRF7. Our results suggest that it is possible to detect gene expression changes in blood samples from individuals with HD, which may reflect the immune pathology associated with the disease.

Genomic basis for RNA alterations in cancer.

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

The Anti-amyloid Compound DO1 Decreases Plaque Pathology and Neuroinflammation-Related Expression Changes in 5xFAD Transgenic Mice.

Self-propagating amyloid-ß (Aß) aggregates or seeds possibly drive pathogenesis of Alzheimer's disease (AD). Small molecules targeting such structures might act therapeutically in vivo. Here, a fluorescence polarization assay was established that enables the detection of compound effects on both seeded and spontaneous Aß42 aggregation. In a focused screen of anti-amyloid compounds, we identified Disperse Orange 1 (DO1) ([4-((4-nitrophenyl)diazenyl)-N-phenylaniline]), a small molecule that potently delays both seeded and non-seeded Aß42 polymerization at substoichiometric concentrations. Mechanistic studies revealed that DO1 disrupts preformed fibrillar assemblies of synthetic Aß42 peptides and decreases the seeding activity of Aß aggregates from brain extracts of AD transgenic mice. DO1 also reduced the size and abundance of diffuse Aß plaques and decreased neuroinflammation-related gene expression changes in brains of 5xFAD transgenic mice. Finally, improved nesting behavior was observed upon treatment with the compound. Together, our evidence supports targeting of self-propagating Aß structures with small molecules as a valid therapeutic strategy.

Role of the chromatin landscape and sequence in determining cell type-specific genomic glucocorticoid receptor binding and gene regulation.

The genomic loci bound by the glucocorticoid receptor (GR), a hormone-activated transcription factor, show little overlap between cell types. To study the role of chromatin and sequence in specifying where GR binds, we used Bayesian modeling within the universe of accessible chromatin. Taken together, our results uncovered that although GR preferentially binds accessible chromatin, its binding is biased against accessible chromatin located at promoter regions. This bias can only be explained partially by the presence of fewer GR recognition sequences, arguing for the existence of additional mechanisms that interfere with GR binding at promoters. Therefore, we tested the role of H3K9ac, the chromatin feature with the strongest negative association with GR binding, but found that this correlation does not reflect a causative link. Finally, we find a higher percentage of promoter-proximal GR binding for genes regulated by GR across cell types than for cell type-specific target genes. Given that GR almost exclusively binds accessible chromatin, we propose that cell type-specific regulation by GR preferentially occurs via distal enhancers, whose chromatin accessibility is typically cell type-specific, whereas ubiquitous target gene regulation is more likely to result from binding to promoter regions, which are often accessible regardless of cell type examined.

Concerted down-regulation of immune-system related genes predicts metastasis in colorectal carcinoma.

BACKGROUND: This study aimed at the identification of prognostic gene expression markers in early primary colorectal carcinomas without metastasis at the time point of surgery by analyzing genome-wide gene expression profiles using oligonucleotide microarrays. METHODS: Cryo-conserved tumor specimens from 45 patients with early colorectal cancers were examined, with the majority of them being UICC stage II or earlier and with a follow-up time of 41-115 months. Gene expression profiling was performed using Whole Human Genome 4x44K Oligonucleotide Microarrays. Validation of microarray data was performed on five of the genes in a smaller cohort. RESULTS: Using a novel algorithm based on the recursive application of support vector machines (SVMs), we selected a signature of 44 probes that discriminated between patients developing later metastasis and patients with a good prognosis. Interestingly, almost half of the genes was related to the patients' immune response and showed reduced expression in the metastatic cases. CONCLUSIONS: Whereas up to now gene signatures containing genes with various biological functions have been described for prediction of metastasis in CRC, in this study metastasis could be well predicted by a set of gene expression markers consisting exclusively of genes related to the MHC class II complex involved in immune response. Thus, our data emphasize that the proper function of a comprehensive network of immune response genes is of vital importance for the survival of colorectal cancer patients.

PROmiRNA: a new miRNA promoter recognition method uncovers the complex regulation of intronic miRNAs.

The regulation of intragenic miRNAs by their own intronic promoters is one of the open problems of miRNA biogenesis. Here, we describe PROmiRNA, a new approach for miRNA promoter annotation based on a semi-supervised statistical model trained on deepCAGE data and sequence features. We validate our results with existing annotation, PolII occupancy data and read coverage from RNA-seq data. Compared to previous methods PROmiRNA increases the detection rate of intronic promoters by 30%, allowing us to perform a large-scale analysis of their genomic features, as well as elucidate their contribution to tissue-specific regulation. PROmiRNA can be downloaded from http://promirna.molgen.mpg.de.

The soluble intracellular domain of megalin does not affect renal proximal tubular function in vivo.

Megalin-mediated endocytic uptake constitutes the main pathway for clearance of plasma proteins from the glomerular filtrate in proximal tubules. Little is known, however, about mechanisms that control megalin expression and activity in the kidney. A widely discussed hypothesis states that upon ligand binding a regulated intramembrane proteolysis releases the cytosolic domain of megalin and this fragment subsequently modulates megalin gene transcription. Here, we tested this by generating a mouse model that co-expressed both the soluble intracellular domain and full-length megalin. Despite pronounced synthesis in the proximal tubules, the soluble intracellular domain failed to exert distinct effects on renal proximal tubular function, including megalin expression, endocytic retrieval of proteins, or global renal gene transcription. Hence, our study argues that the soluble intracellular domain does not have a role in regulating the activity of megalin in the kidney.

DNA methylation protects hematopoietic stem cell multipotency from myeloerythroid restriction.

DNA methylation is a dynamic epigenetic mark that undergoes extensive changes during differentiation of self-renewing stem cells. However, whether these changes are the cause or consequence of stem cell fate remains unknown. Here, we show that alternative functional programs of hematopoietic stem cells (HSCs) are governed by gradual differences in methylation levels. Constitutive methylation is essential for HSC self-renewal but dispensable for homing, cell cycle control and suppression of apoptosis. Notably, HSCs from mice with reduced DNA methyltransferase 1 activity cannot suppress key myeloerythroid regulators and thus can differentiate into myeloerythroid, but not lymphoid, progeny. A similar methylation dosage effect controls stem cell function in leukemia. These data identify DNA methylation as an essential epigenetic mechanism to protect stem cells from premature activation of predominant differentiation programs and suggest that methylation dynamics determine stem cell functions in tissue homeostasis and cancer.

MedlineRanker: flexible ranking of biomedical literature.

The biomedical literature is represented by millions of abstracts available in the Medline database. These abstracts can be queried with the PubMed interface, which provides a keyword-based Boolean search engine. This approach shows limitations in the retrieval of abstracts related to very specific topics, as it is difficult for a non-expert user to find all of the most relevant keywords related to a biomedical topic. Additionally, when searching for more general topics, the same approach may return hundreds of unranked references. To address these issues, text mining tools have been developed to help scientists focus on relevant abstracts. We have implemented the MedlineRanker webserver, which allows a flexible ranking of Medline for a topic of interest without expert knowledge. Given some abstracts related to a topic, the program deduces automatically the most discriminative words in comparison to a random selection. These words are used to score other abstracts, including those from not yet annotated recent publications, which can be then ranked by relevance. We show that our tool can be highly accurate and that it is able to process millions of abstracts in a practical amount of time. MedlineRanker is free for use and is available at http://cbdm.mdc-berlin.de/tools/medlineranker.

Detection of alpha-rod protein repeats using a neural network and application to huntingtin.

A growing number of solved protein structures display an elongated structural domain, denoted here as alpha-rod, composed of stacked pairs of anti-parallel alpha-helices. Alpha-rods are flexible and expose a large surface, which makes them suitable for protein interaction. Although most likely originating by tandem duplication of a two-helix unit, their detection using sequence similarity between repeats is poor. Here, we show that alpha-rod repeats can be detected using a neural network. The network detects more repeats than are identified by domain databases using multiple profiles, with a low level of false positives (<10%). We identify alpha-rod repeats in approximately 0.4% of proteins in eukaryotic genomes. We then investigate the results for all human proteins, identifying alpha-rod repeats for the first time in six protein families, including proteins STAG1-3, SERAC1, and PSMD1-2 & 5. We also characterize a short version of these repeats in eight protein families of Archaeal, Bacterial, and Fungal species. Finally, we demonstrate the utility of these predictions in directing experimental work to demarcate three alpha-rods in huntingtin, a protein mutated in Huntington's disease. Using yeast two hybrid analysis and an immunoprecipitation technique, we show that the huntingtin fragments containing alpha-rods associate with each other. This is the first definition of domains in huntingtin and the first validation of predicted interactions between fragments of huntingtin, which sets up directions toward functional characterization of this protein. An implementation of the repeat detection algorithm is available as a Web server with a simple graphical output: http://www.ogic.ca/projects/ard. This can be further visualized using BiasViz, a graphic tool for representation of multiple sequence alignments.

Recent developments in StemBase: a tool to study gene expression in human and murine stem cells.

BACKGROUND: Currently one of the largest online repositories for human and mouse stem cell gene expression data, StemBase was first designed as a simple web-interface to DNA microarray data generated by the Canadian Stem Cell Network to facilitate the discovery of gene functions relevant to stem cell control and differentiation. FINDINGS: Since its creation, StemBase has grown in both size and scope into a system with analysis tools that examine either the whole database at once, or slices of data, based on tissue type, cell type or gene of interest. As of September 1, 2008, StemBase contains gene expression data (microarray and Serial Analysis of Gene Expression) from 210 stem cell samples in 60 different experiments. CONCLUSION: StemBase can be used to study gene expression in human and murine stem cells and is available at http://www.stembase.ca.

BiasViz: visualization of amino acid biased regions in protein alignments.

About a third of all protein sequences have at least one composition biased region (CBR). Such regions might act as linkers between protein domains but often confer specific binding to various molecules; therefore, their characterization in terms of their boundaries and over-represented residues is important. Analysis of CBRs in a particular sequence can be time consuming if several types of biases have to be explored and their position visualized. Assessment of the significance of the detected CBRs can be approached by comparison to homologous protein sequences. To assist this procedure, we have developed BiasViz, a tool that allows to graphically studying local amino acid composition in protein sequences of a multiple sequence alignment.

Study of stem cell function using microarray experiments.

DNA Microarrays are used to simultaneously measure the levels of thousands of mRNAs in a sample. We illustrate here that a collection of such measurements in different cell types and states is a sound source of functional predictions, provided the microarray experiments are analogous and the cell samples are appropriately diverse. We have used this approach to study stem cells, whose identity and mechanisms of control are not well understood, generating Affymetrix microarray data from more than 200 samples, including stem cells and their derivatives, from human and mouse. The data can be accessed online (StemBase; http://www.scgp.ca:8080/StemBase/).