A hallmark of inflammatory diseases is the excessive recruitment and influx of monocytes to sites of tissue damage and their ensuing differentiation into macrophages. Numerous stimuli are known to induce transcriptional changes associated with macrophage phenotype, but posttranscriptional control of human macrophage differentiation is less well understood. Here we show that expression levels of the RNA-binding protein Quaking (QKI) are low in monocytes and early human atherosclerotic lesions, but are abundant in macrophages of advanced plaques. Depletion of QKI protein impairs monocyte adhesion, migration, differentiation into macrophages and foam cell formation in vitro and in vivo. RNA-seq and microarray analysis of human monocyte and macrophage transcriptomes, including those of a unique QKI haploinsufficient patient, reveal striking changes in QKI-dependent messenger RNA levels and splicing of RNA transcripts. The biological importance of these transcripts and requirement for QKI during differentiation illustrates a central role for QKI in posttranscriptionally guiding macrophage identity and function.

Rhabdomyosarcoma (RMS) is the most common soft-tissue sarcoma in children and adolescents, being characterized by expression of genes and morphological and ultrastructural features of sarcomeric differentiation. The spindle cell variant of rhabdomyosarcoma (spindle cell RMS) in adults has been defined as an entity, separated from embryonal rhabdomyosarcoma (ERMS), with unfavourable clinical outcome. So far, no recurrent genetic alteration has been identified in the adult form of spindle cell RMS. We studied a case of adult spindle cell RMS using next-generation sequencing (NGS) after exome capture. Using this approach, we identified 31 tumour-specific somatic alterations and selected four genes with predicted functional relevance to muscle differentiation and growth. MYOD1, KIF18A, NOTCH1, and EML5 were further tested for mutations using Sanger sequencing on DNA from FFPE samples from 16 additional, adult spindle cell RMS samples. The highly conserved sequence homology of MYOD1 with other myogenic transcription factors prompted us to screen the basic DNA-binding domains of MYF5, MYF6 and MYOG for mutations. From the investigated 17 samples, seven (41%) showed homozygous mutation of MYOD1, indicating a critical role in this rare subtype of adult spindle cell RMS, while no mutations were found in any of the other genes involved in myogenic differentiation. The p.L122R mutation occurs in the conserved DNA binding domain in MYOD1 and leads to transactivation and MYC-like functions. MYOD1 homozygous mutations are frequent, recurrent and pathognomonic events in adult-type spindle cell RMS.

BackgroundClostridium difficile strain 630Δerm is a spontaneous erythromycin sensitive derivative of the reference strain 630 obtained by serial passaging in antibiotic-free media. It is widely used as a defined and tractable C. difficile strain. Though largely similar to the ancestral strain, it demonstrates phenotypic differences that might be the result of underlying genetic changes. Here, we performed a de novo assembly based on single-molecule real-time sequencing and an analysis of major methylation patterns.ResultsIn addition to single nucleotide polymorphisms and various indels, we found that the mobile element CTn5 is present in the gene encoding the methyltransferase rumA rather than adhesin CD1844 where it is located in the reference strain.ConclusionsTogether, the genetic features identified in this study may help to explain at least part of the phenotypic differences. The annotated genome sequence of this lab strain, including the first analysis of major methylation patterns, will be a valuable resource for genetic research on C. difficile.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1252-7) contains supplementary material, which is available to authorized users.

Aberrant expression of microRNAs is widely accepted to be pathogenetically involved in nodal diffuse large B-cell lymphomas (DLBCLs). However, the microRNAs profiles of primary cutaneous large B-cell lymphomas (PCLBCLs) are not yet described. Its two main subtypes, i.e., primary cutaneous diffuse large B-cell lymphoma, leg type (PCLBCL-LT) and primary cutaneous follicle center lymphoma (PCFCL) are characterized by an activated B-cell (ABC)-genotype and a germinal center B-cell (GCB)-genotype, respectively. We performed high-throughput sequencing analysis on frozen tumor biopsies from 19 cases of PCFCL and PCLBCL-LT to establish microRNA profiles. Cluster analysis of the complete microRNome could not distinguish between the two subtypes, but 16 single microRNAs were found to be differentially expressed. Single microRNA RT-qPCR was conducted on formalin-fixed paraffin-embedded tumor biopsies of 20 additional cases, confirming higher expression of miR-9-5p, miR-31-5p, miR-129-2-3p and miR-214-3p in PCFCL as compared to PCLBCL-LT. MicroRNAs previously described to be higher expressed in ABC-type as compared to GCB-type nodal DLBCL were not differentially expressed between PCFCL and PCLBCL-LT. In conclusion, PCFCL and PCLBCL-LT differ in their microRNA profiles. In contrast to their gene expression profile, they only show slight resemblance with the microRNA profiles found in GCB- and ABC-type nodal DLBCL.

BackgroundMany tools exist to predict structural variants (SVs), utilizing a variety of algorithms. However, they have largely been developed and tested on human germline or somatic (e.g. cancer) variation. It seems appropriate to exploit this wealth of technology available for humans also for other species. Objectives of this work included:Creating an automated, standardized pipeline for SV prediction.Identifying the best tool(s) for SV prediction through benchmarking.Providing a statistically sound method for merging SV calls.ResultsThe SV-AUTOPILOT meta-tool platform is an automated pipeline for standardization of SV prediction and SV tool development in paired-end next-generation sequencing (NGS) analysis. SV-AUTOPILOT comes in the form of a virtual machine, which includes all datasets, tools and algorithms presented here. The virtual machine easily allows one to add, replace and update genomes, SV callers and post-processing routines and therefore provides an easy, out-of-the-box environment for complex SV discovery tasks. SV-AUTOPILOT was used to make a direct comparison between 7 popular SV tools on the Arabidopsis thaliana genome using the Landsberg (Ler) ecotype as a standardized dataset. Recall and precision measurements suggest that Pindel and Clever were the most adaptable to this dataset across all size ranges while Delly performed well for SVs larger than 250 nucleotides. A novel, statistically-sound merging process, which can control the false discovery rate, reduced the false positive rate on the Arabidopsis benchmark dataset used here by >60%.ConclusionSV-AUTOPILOT provides a meta-tool platform for future SV tool development and the benchmarking of tools on other genomes using a standardized pipeline. It optimizes detection of SVs in non-human genomes using statistically robust merging. The benchmarking in this study has demonstrated the power of 7 different SV tools for analyzing different size classes and types of structural variants. The optional merge feature enriches the call set and reduces false positives providing added benefit to researchers planning to validate SVs. SV-AUTOPILOT is a powerful, new meta-tool for biologists as well as SV tool developers.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1376-9) contains supplementary material, which is available to authorized users.