During the lifetime of a fermenter culture, the soil bacterium S. coelicolor undergoes a major metabolic switch from exponential growth to antibiotic production. We have studied gene expression patterns during this switch, using a specifically designed Affymetrix genechip and a high-resolution time-series of fermenter-grown samples. Surprisingly, we find that the metabolic switch actually consists of multiple finely orchestrated switching events. Strongly coherent clusters of genes show drastic changes in gene expression already many hours before the classically defined transition phase where the switch from primary to secondary metabolism was expected. The main switch in gene expression takes only 2 hours, and changes in antibiotic biosynthesis genes are delayed relative to the metabolic rearrangements. Furthermore, global variation in morphogenesis genes indicates an involvement of cell differentiation pathways in the decision phase leading up to the commitment to antibiotic biosynthesis. Our study provides the first detailed insights into the complex sequence of early regulatory events during and preceding the major metabolic switch in S. coelicolor, which will form the starting point for future attempts at engineering antibiotic production in a biotechnological setting.

Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmer's access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Mayday's functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files. Results: We have rewritten large parts of Mayday's core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved. Conclusions: We present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at http://microarray-analysis.org.

Current treatment outcome of patients with glioblastoma (GBM) remains poor. Following standard therapy, recurrence is universal with limited survival. Tumors from 173 GBM patients are analysed for somatic mutations to generate a personalized peptide vaccine targeting tumor-specific neoantigens. All patients were treated within the scope of an individual healing attempt. Among all vaccinated patients, including 70 treated prior to progression (primary) and 103 treated after progression (recurrent), the median overall survival from first diagnosis is 31.9 months (95% CI: 25.0–36.5). Adverse events are infrequent and are predominantly grade 1 or 2. A vaccine-induced immune response to at least one of the vaccinated peptides is detected in blood samples of 87 of 97 (90%) monitored patients. Vaccine-specific T-cell responses are durable in most patients. Significantly prolonged survival is observed for patients with multiple vaccine-induced T-cell responses (53 months) compared to those with no/low induced responses (27 months; P = 0.03). Altogether, our results highlight that the application of personalized neoantigen-targeting peptide vaccine is feasible and represents a promising potential treatment option for GBM patients.

Objective: About 3% of newborns show malformations, with about 20% of the affected having genetic causes. Clarification of genetic diseases in postnatal diagnostics was significantly improved with high‐throughput sequencing, in particular through whole exome sequencing covering all protein‐coding regions. Here, we aim to extend the use of this technology to prenatal diagnostics.Method: Between 07/2018 and 10/2020, 500 pregnancies with fetal ultrasound abnormalities were analyzed after genetic counseling as part of prenatal diagnostics using WES of the fetus and parents.Results: Molecular genetic findings could explain ultrasound abnormalities in 38% of affected fetuses. In 47% of these, disease‐causing de novo variants were found. Pathogenic variants in genes with autosomal recessive or X‐linked inheritance were detected in more than one‐third (70/189 = 37%). The latter are associated with increased probability of recurrence, making their detection important for further pregnancies. Average time from sample receipt to report was 12 days in the recent cases.Conclusion: Trio exome sequencing is a useful addition to prenatal diagnostics due to its high diagnostic yield and short processing time (comparable to chromosome analysis). It covers a wide spectrum of genetic changes. Comprehensive interdisciplinary counseling before and after diagnostics is indispensable.

We aimed to gain insight into frequencies of genetic variants in genes implicated in neurodevelopmental disorder with epilepsy (NDD+E) by investigating large cohorts of patients in a diagnostic setting. We analyzed variants in NDD+E using epilepsy gene panel sequencing performed between 2013 and 2017 by two large diagnostic companies. We compared variant frequencies in 6994 panels with another 8588 recently published panels as well as exome-wide de novo variants in 1942 individuals with NDD+E and 10,937 controls. Genes with highest frequencies of ultrarare variants in NDD+E comprised SCN1A, KCNQ2, SCN2A, CDKL5, SCN8A, and STXBP1, concordant with the two other epilepsy cohorts we investigated. In only 46% of the analyzed 262 dominant and X-linked panel genes ultrarare variants in patients were reported. Among genes with contradictory evidence of association with epilepsy, CACNB4, CLCN2, EFHC1, GABRD, MAGI2, and SRPX2 showed equal frequencies in cases and controls. We show that improvement of panel design increased diagnostic yield over time, but panels still display genes with low or no diagnostic yield. With our data, we hope to improve current diagnostic NDD+E panel design and provide a resource of ultrarare variants in individuals with NDD+E to the community.

Motivation: The number of completely sequenced genomes is continuously rising, allowing for comparative analyses of genomic variation. Such analyses are often based on whole-genome alignments to elucidate structural differences arising from insertions, deletions or from rearrangement events. Computational tools that can visualize genome alignments in a meaningful manner are needed to help researchers gain new insights into the underlying data. Such visualizations typically are either realized in a linear fashion as in genome browsers or by using a circular approach, where relationships between genomic regions are indicated by arcs. Both methods allow for the integration of additional information such as experimental data or annotations. However, providing a visualization that still allows for a quick and comprehensive interpretation of all important genomic variations together with various supplemental data, which may be highly heterogeneous, remains a challenge. Results: Here, we present two complementary approaches to tackle this problem. First, we propose the SuperGenome concept for the computation of a common coordinate system for all genomes in a multiple alignment. This coordinate system allows for the consistent placement of genome annotations in the presence of insertions, deletions and rearrangements. Second, we present the GenomeRing visualization that, based on the SuperGenome, creates an interactive overview visualization of the multiple genome alignment in a circular layout. We demonstrate our methods by applying them to an alignment of Campylobacter jejuni strains for the discovery of genomic islands as well as to an alignment of Helicobacter pylori, which we visualize in combination with gene expression data. Availability: GenomeRing and example data is available at http://it.inf.uni-tuebingen.de/software/genomering/ Contact:kay.nieselt@uni-tuebingen.de