SEAweb: the small RNA Expression Atlas web application.

We present the Small RNA Expression Atlas (SEAweb), a web application that allows for the interactive querying, visualization and analysis of known and novel small RNAs across 10 organisms. It contains sRNA and pathogen expression information for over 4200 published samples with standardized search terms and ontologies. In addition, SEAweb allows for the interactive visualization and re-analysis of 879 differential expression and 514 classification comparisons. SEAweb's user model enables sRNA researchers to compare and re-analyze user-specific and published datasets, highlighting common and distinct sRNA expression patterns. We provide evidence for SEAweb's fidelity by (i) generating a set of 591 tissue specific miRNAs across 29 tissues, (ii) finding known and novel bacterial and viral infections across diseases and (iii) determining a Parkinson's disease-specific blood biomarker signature using novel data. We believe that SEAweb's simple semantic search interface, the flexible interactive reports and the user model with rich analysis capabilities will enable researchers to better understand the potential function and diagnostic value of sRNAs or pathogens across tissues, diseases and organisms.

Oasis 2: improved online analysis of small RNA-seq data.

BACKGROUND: Small RNA molecules play important roles in many biological processes and their dysregulation or dysfunction can cause disease. The current method of choice for genome-wide sRNA expression profiling is deep sequencing. RESULTS: Here we present Oasis 2, which is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module. CONCLUSIONS: Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment. AVAILABILITY AND IMPLEMENTATION: Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at https://oasis.dzne.de.

The genetics of Crohn's disease and ulcerative colitis--status quo and beyond.

The two major subtypes of inflammatory bowel disease (IBD), ulcerative colitis (UC, MIM#191390) and Crohn's disease (CD, MIM#266600), are chronic relapsing-remitting inflammatory disorders affecting primarily the gastrointestinal tract. Prevalence rates in North America and Europe range from 21 to 246 per 100,000 for UC and 8 to 214 per 100,000 for CD. Although CD and UC share some clinical and pathological features, they can be distinguished by localization, endoscopic appearance, histology and behavior, which suggest differences in the underlying pathophysiology. The importance of genetic risk factors in disease etiology is high and has been documented more clearly for CD than for UC (relative sibling risks λ(s): 15-35 for CD, 6-9 for UC). The most recent and largest genetic association study for IBD, which employed genome-wide association data for over 75,000 patients and controls, established the association of 163 susceptibility loci with IBD. Although the disease variance explained by the 163 loci only amounts to 13.6% for CD and 7.5% for UC, the identified loci and the candidate genes within yielded valuable insights into the pathogenesis of IBD and the relevant disease pathways. We here review the current research on the genetics of IBD and provide insights into on current efforts as well as suggest topics for future research.

A method to build extended sequence context models of point mutations and indels.

The mutation rate of a specific position in the human genome depends on the sequence context surrounding it. Modeling the mutation rate by estimating a rate for each possible k-mer, however, only works for small values of k since the data becomes too sparse for larger values of k. Here we propose a new method that solves this problem by grouping similar k-mers. We refer to the method as k-mer pattern partition and have implemented it in a software package called kmerPaPa. We use a large set of human de novo mutations to show that this new method leads to improved prediction of mutation rates and makes it possible to create models using wider sequence contexts than previous studies. As the first method of its kind, it does not only predict rates for point mutations but also insertions and deletions. We have additionally created a software package called Genovo that, given a k-mer pattern partition model, predicts the expected number of synonymous, missense, and other functional mutation types for each gene. Using this software, we show that the created mutation rate models increase the statistical power to detect genes containing disease-causing variants and to identify genes under strong selective constraint.

NGS-based methylation profiling differentiates TCF3-HLF and TCF3-PBX1 positive B-cell acute lymphoblastic leukemia.

AIM: To determine whether methylation differences between mostly fatal TCF3-HLF and curable TCF3-PBX1 pediatric acute lymphoblastic leukemia subtypes can be associated with differential gene expression and remission. MATERIALS & METHODS: Five (extremely rare) TCF3-HLF versus five (very similar) TCF3-PBX1 patients were sampled before and after remission and analyzed using reduced representation bisulfite sequencing and RNA-sequencing. RESULTS: We identified 7000 differentially methylated CpG sites between subtypes, of which 78% had lower methylation levels in TCF3-HLF. Gene expression was negatively correlated with CpG sites in 23 genes. KBTBD11 clearly differed in methylation and expression between subtypes and before and after remission in TCF3-HLF samples. CONCLUSION: KBTBD11 hypomethylation may be a promising potential target for further experimental validation especially for the TCF3-HLF subtype.

LitDB - Keeping Track of Research Papers From Your Institute Made Simple.

BACKGROUND: In science peer-reviewed publications serve as an important indicator of scientific excellence and productivity. Therefore, every scientist and institution must carefully maintain and update records of their scientific publications. However, in most institutions and universities articles are often managed in a redundant file-based and non-central way. Whereas excellent reference management software packages such as Zotero, Endnote or Mendeley exist to manage bibliographies and references when writing scientific articles, we are not aware of any open source database solution keeping track of publication records from large scientific groups, entire institutions and/or universities. RESULTS: We here describe LitDB, a novel open source literature database solution for easy maintenance of publication lists assigned to various topics. In the last 2 years more than 50 users have been using LitDB at our research institute. The LitDB system is accessed via a web browser. Publications can be uploaded through direct exports from reference manager libraries or by entering PubMed IDs. Single users or user groups can track their citation counts, h-index and impact factor statistics and gain insights into the publication records of other users. It offers various visualization functions like coauthor networks and provides ways to organize publications from dedicated projects and user groups. The latter is in particular beneficial to manage publication lists of large research groups and research initiatives through a "crowd-sourcing" effort. CONCLUSIONS: Keeping track of papers authored and published by a research group, institute or university is an important and non-trivial task. By using a centralized web-based platform for publication management such as LitDB the compilation of project- and group-related publication lists becomes easily manageable and it is less likely that papers are forgotten along the way.

Genome-wide association analysis identifies variation in vitamin D receptor and other host factors influencing the gut microbiota.

Human gut microbiota is an important determinant for health and disease, and recent studies emphasize the numerous factors shaping its diversity. Here we performed a genome-wide association study (GWAS) of the gut microbiota using two cohorts from northern Germany totaling 1,812 individuals. Comprehensively controlling for diet and non-genetic parameters, we identify genome-wide significant associations for overall microbial variation and individual taxa at multiple genetic loci, including the VDR gene (encoding vitamin D receptor). We observe significant shifts in the microbiota of Vdr-/- mice relative to control mice and correlations between the microbiota and serum measurements of selected bile and fatty acids in humans, including known ligands and downstream metabolites of VDR. Genome-wide significant (P < 5 × 10-8) associations at multiple additional loci identify other important points of host-microbe intersection, notably several disease susceptibility genes and sterol metabolism pathway components. Non-genetic and genetic factors each account for approximately 10% of the variation in gut microbiota, whereby individual effects are relatively small.

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci.

We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn's disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European ancestry, we identified 244 independent multidisease signals, including 27 new genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multidisease signals with expression data sets from human, rat and mouse together with epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases genetically identical to those with another disease, possibly owing to diagnostic misclassification, molecular subtypes or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes.