Background The fast-moving progress of the third-generation long-read sequencing technologies will soon bring the biological and medical sciences to a new era of research. Altogether, the technique and experimental procedures are becoming more straightforward and available to biologists from diverse fields, even without any profound experience in DNA sequencing. Thus, the introduction of the MinION device by Oxford Nanopore Technologies promises to “bring sequencing technology to the masses” and also allows quick and operative analysis in field studies. However, the convenience of this sequencing technology dramatically contrasts with the available analysis tools, which may significantly reduce enthusiasm of a “regular” user. To really bring the sequencing technology to every biologist, we need a set of user-friendly tools that can perform a powerful analysis in an automatic manner. Findings NanoPipe was developed in consideration of the specifics of the MinION sequencing technologies, providing accordingly adjusted alignment parameters. The range of the target species/sequences for the alignment is not limited, and the descriptive usage page of NanoPipe helps a user to succeed with NanoPipe analysis. The results contain alignment statistics, consensus sequence, polymorphisms data, and visualization of the alignment. Several test cases are used to demonstrate the efficiency of the tool. Conclusions Freely available NanoPipe software allows effortless and reliable analysis of MinION sequencing data for experienced bioinformaticians, as well for wet-lab biologists with minimum bioinformatics knowledge. Moreover, for the latter group, we describe the basic algorithm necessary for MinION sequencing analysis from the first to last step.

Upstream open reading frame (uORF)-mediated translational control has emerged as an important regulatory mechanism in human health and disease. However, a systematic search for cancer-associated somatic uORF mutations has not been performed. Here, we analyzed the genetic variability at canonical (uAUG) and alternative translational initiation sites (aTISs), as well as the associated upstream termination codons (uStops) in 3394 whole-exome-sequencing datasets from patient samples of breast, colon, lung, prostate, and skin cancer and of acute myeloid leukemia, provided by The Cancer Genome Atlas research network. We found that 66.5% of patient samples were affected by at least one of 5277 recurrent uORF-associated somatic single nucleotide variants altering 446 uAUG, 347 uStop, and 4733 aTIS codons. While twelve uORF variants were detected in all entities, 17 variants occurred in all five types of solid cancer analyzed here. Highest frequencies of individual somatic variants in the TLSs of NBPF20 and CHCHD2 reached 10.1% among LAML and 8.1% among skin cancer patients, respectively. Functional evaluation by dual luciferase reporter assays identified 19 uORF variants causing significant translational deregulation of the associated main coding sequence, ranging from 1.73-fold induction for an AUG.1 > UUG variant in SETD4 to 0.006-fold repression for a CUG.6 > GUG variant in HLA-DRB1. These data suggest that somatic uORF mutations are highly prevalent in human malignancies and that defective translational regulation of protein expression may contribute to the onset or progression of cancer.

Upstream open reading frames (uORFs) are initiated by AUG or near-cognate start codons and have been identified in the transcript leader sequences of the majority of eukaryotic transcripts. Functionally, uORFs are implicated in downstream translational regulation of the main protein coding sequence and may serve as a source of non-canonical peptides. Genetic defects in uORF sequences have been linked to the development of various diseases, including cancer. To simplify uORF-related research, the initial release of uORFdb in 2014 provided a comprehensive and manually curated collection of uORF-related literature. Here, we present an updated sequence-based version of uORFdb, accessible at https://www.bioinformatics.uni-muenster.de/tools/uorfdb. The new uORFdb enables users to directly access sequence information, graphical displays, and genetic variation data for over 2.4 million human uORFs. It also includes sequence data of >4.2 million uORFs in 12 additional species. Multiple uORFs can be displayed in transcript- and reading-frame-specific models to visualize the translational context. A variety of filters, sequence-related information, and links to external resources (UCSC Genome Browser, dbSNP, ClinVar) facilitate immediate in-depth analysis of individual uORFs. The database also contains uORF-related somatic variation data obtained from whole-genome sequencing (WGS) analyses of 677 cancer samples collected by the TCGA consortium.

Identifying single organisms in environmental samples is one of the key tasks of metagenomics.During the last few years, third generation sequencing technologies have enabled researchers to sequence much longer molecules, but at the expense of sequencing accuracy. Thus, new algorithms needed to be developed to cope with this new type of data. With this in mind, we developed a tool called MetaG. An intuitive web interface makes the software accessible to a vast range of users, including those without extensive bioinformatic expertise. Evaluation of MetaG's performance showed that it makes nearly perfect classifications of viral isolates using simulated short and long reads.MetaG also outperformed current state-of-the-art algorithms on data from targeted sequencing of the 16S and 28S rRNA genes. Since MetaG's output is also supplemented with information about hosts and antibiotic resistances of pathogens, we expect it to be especially useful to the healthcare sector.Moreover, the outstanding accuracy of the taxonomic assignments will make MetaG a serious alternative for anyone working with metagenomic sequences. MetaG can be accessed at

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