Multifunctional genes

In this paper a sensor fusion for pose estimation using optical and inertial data is presented. The proposed algorithm is based on extended Kalman filtering and fuses data from an optical tracking system and an inertial measurement unit. These two redundant sensor systems complement each other well, with the tracking providing absolute position accuracy and the inertial measurements giving low latency information of derivatives. Models for both sensors are given respecting the different sampling times and latencies. Another key issue is to use information about every landmark, i.e. marker, visible for the tracking system, by coupling the two sensor systems tightly together. The algorithms are evaluated in simulation and tested with an experimental hardware platform. The combined sensor system provides robust pose estimation in case of short time marker occlusion and effectively compensates for latencies the pose measurements

GeneSeeker: extraction and integration of human disease-related information from web-based genetic databases

The identification of genes underlying human genetic disorders requires the combination of data related to cytogenetic localization, phenotypes and expression patterns, to generate a list of candidate genes. In the field of human genetics, it is normal to perform this combination analysis by hand. We report on GeneSeeker (), a web server that gathers and combines data from a series of databases. All database searches are performed via the web interfaces provided with the original databases, guaranteeing that the most recent data are queried, and obviating data warehousing. GeneSeeker makes the same selection of candidate genes as the human geneticists would have performed, and thus reducing the time-consuming process to a few minutes. GeneSeeker is particularly well suited for syndromes in which the disease gene displays altered expression patterns in the affected tissue(s)

Molecular mechanisms that distinguish TFIID housekeeping from regulatable SAGA promoters

An important distinction is frequently made between constitutively expressed housekeeping genes versus regulated genes. Although generally characterized by different DNA elements, chromatin architecture and cofactors, it is not known to what degree promoter classes strictly follow regulatability rules and which molecular mechanisms dictate such differences. We show that SAGA-dominated/wTATA-box promoters are more responsive to changes in the amount of activator, even compared to TFIID/TATA-like promoters that depend on the same activator Hsf1. Regulatability is therefore an inherent property of promoter class. Further analyses show that SAGA/TATA-box promoters are more dynamic because TATA-binding protein recruitment through SAGA is susceptible to removal by Mot1. In addition, the nucleosome configuration upon activator depletion shifts on SAGA/TATA-box promoters and seems less amenable to preinitiation complex formation. The results explain the fundamental difference between housekeeping and regulatable genes, revealing an additional facet of combinatorial control: an activator can elicit a different response dependent on core promoter class

The genomic landscape of compensatory evolution.

Adaptive evolution is generally assumed to progress through the accumulation of beneficial mutations. However, as deleterious mutations are common in natural populations, they generate a strong selection pressure to mitigate their detrimental effects through compensatory genetic changes. This process can potentially influence directions of adaptive evolution by enabling evolutionary routes that are otherwise inaccessible. Therefore, the extent to which compensatory mutations shape genomic evolution is of central importance. Here, we studied the capacity of the baker's yeast genome to compensate the complete loss of genes during evolution, and explored the long-term consequences of this process. We initiated laboratory evolutionary experiments with over 180 haploid baker's yeast genotypes, all of which initially displayed slow growth owing to the deletion of a single gene. Compensatory evolution following gene loss was rapid and pervasive: 68% of the genotypes reached near wild-type fitness through accumulation of adaptive mutations elsewhere in the genome. As compensatory mutations have associated fitness costs, genotypes with especially low fitnesses were more likely to be subjects of compensatory evolution. Genomic analysis revealed that as compensatory mutations were generally specific to the functional defect incurred, convergent evolution at the molecular level was extremely rare. Moreover, the majority of the gene expression changes due to gene deletion remained unrestored. Accordingly, compensatory evolution promoted genomic divergence of parallel evolving populations. However, these different evolutionary outcomes are not phenotypically equivalent, as they generated diverse growth phenotypes across environments. Taken together, these results indicate that gene loss initiates adaptive genomic changes that rapidly restores fitness, but this process has substantial pleiotropic effects on cellular physiology and evolvability upon environmental change. Our work also implies that gene content variation across species could be partly due to the action of compensatory evolution rather than the passive loss of genes

Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks

The idea of 'date' and 'party' hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. Thus, we suggest that a date/party dichotomy is not meaningful and it might be more useful to conceive of roles for protein-protein interactions rather than individual proteins. We find significant correlations between interaction centrality and the functional similarity of the interacting proteins.Comment: 27 pages, 5 main figures, 4 supplementary figure

Is self-guided internet-based cognitive behavioural therapy (iCBT) harmful? : An individual participant data meta-analysis

BACKGROUND: Little is known about potential harmful effects as a consequence of self-guided internet-based cognitive behaviour therapy (iCBT), such as symptom deterioration rates. Thus, safety concerns remain and hamper the implementation of self-guided iCBT into clinical practice. We aimed to conduct an individual participant data (IPD) meta-analysis to determine the prevalence of clinically significant deterioration (symptom worsening) in adults with depressive symptoms who received self-guided iCBT compared with control conditions. Several socio-demographic, clinical and study-level variables were tested as potential moderators of deterioration. METHODS: Randomised controlled trials that reported results of self-guided iCBT compared with control conditions in adults with symptoms of depression were selected. Mixed effects models with participants nested within studies were used to examine possible clinically significant deterioration rates. RESULTS: Thirteen out of 16 eligible trials were included in the present IPD meta-analysis. Of the 3805 participants analysed, 7.2% showed clinically significant deterioration (5.8% and 9.1% of participants in the intervention and control groups, respectively). Participants in self-guided iCBT were less likely to deteriorate (OR 0.62, p < 0.001) compared with control conditions. None of the examined participant- and study-level moderators were significantly associated with deterioration rates. CONCLUSIONS: Self-guided iCBT has a lower rate of negative outcomes on symptoms than control conditions and could be a first step treatment approach for adult depression as well as an alternative to watchful waiting in general practice

Identifying protein complexes directly from high-throughput TAP data with Markov random fields

<p>Abstract</p> <p>Background</p> <p>Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms to reconstruct the complexes typically rely on a two-step process. First, they construct an interaction graph from the data, predominantly using heuristics, and subsequently cluster its vertices to identify protein complexes.</p> <p>Results</p> <p>We propose a model-based identification of protein complexes directly from the experimental observations. Our model of protein complexes based on Markov random fields explicitly incorporates false negative and false positive errors and exhibits a high robustness to noise. A model-based quality score for the resulting clusters allows us to identify reliable predictions in the complete data set. Comparisons with prior work on reference data sets shows favorable results, particularly for larger unfiltered data sets. Additional information on predictions, including the source code under the GNU Public License can be found at http://algorithmics.molgen.mpg.de/Static/Supplements/ProteinComplexes.</p> <p>Conclusion</p> <p>We can identify complexes in the data obtained from high-throughput experiments without prior elimination of proteins or weak interactions. The few parameters of our model, which does not rely on heuristics, can be estimated using maximum likelihood without a reference data set. This is particularly important for protein complex studies in organisms that do not have an established reference frame of known protein complexes.</p

An organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity

Kidney tumours are among the most common solid tumours in children, comprising distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first paediatric cancer organoid biobank. It contains tumour and matching normal kidney organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumours, malignant rhabdoid tumours, renal cell carcinomas, and congenital mesoblastic nephromas. Paediatric kidney tumour organoids retain key properties of native tumours, useful for revealing patient-specific drug sensitivities. Using single cell RNA-sequencing and high resolution 3D imaging, we further demonstrate that organoid cultures derived from Wilms tumours consist of multiple different cell types, including epithelial, stromal and blastemal-like cells. Our organoid biobank captures the heterogeneity of paediatric kidney tumours, providing a representative collection of well-characterised models for basic cancer research, drug-screening and personalised medicine

Mesenchymal tumor organoid models recapitulate rhabdomyosarcoma subtypes

Rhabdomyosarcomas (RMS) are mesenchyme-derived tumors and the most common childhood soft tissue sarcomas. Treatment is intense, with a nevertheless poor prognosis for high-risk patients. Discovery of new therapies would benefit from additional preclinical models. Here, we describe the generation of a collection of 19 pediatric RMS tumor organoid (tumoroid) models (success rate of 41%) comprising all major subtypes. For aggressive tumors, tumoroid models can often be established within 4-8 weeks, indicating the feasibility of personalized drug screening. Molecular, genetic, and histological characterization show that the models closely resemble the original tumors, with genetic stability over extended culture periods of up to 6 months. Importantly, drug screening reflects established sensitivities and the models can be modified by CRISPR/Cas9 with TP53 knockout in an embryonal RMS model resulting in replicative stress drug sensitivity. Tumors of mesenchymal origin can therefore be used to generate organoid models, relevant for a variety of preclinical and clinical research questions