Exploring GRIA2 Sequence Variations Using Virtual Reality

The effective visualization and presentation of biological data is of critical importance to research scientists. The increasing rate at which experiments generate data has only exacerbated the problem. While bioinformatics datasets continue to increase in size and complexity, the shift to adopt new user interface (UI) paradigms has historically lagged. Consequently, a major bottleneck for analysis of next-generation sequencing data is the continued use of UIs primarily inspired from the 1990’s through the early 2000’s. This paper presents the novel use of virtual reality (VR) as a medium for visualizing genomic, transcriptomic and proteomic data. Using the Gria2 (GluR2 or GluA2) gene and its associated gene products as our main objects of interest, we present Gria2-Viewer, a proof of concept software tool for visualizing any gene variant within the Gria2 locus. For any given genomic or transcriptomic variant of Gria2, we can quickly visualize its position on the protein subunit, rendered as a secondary structure. We also present a design for an experimental case study which compares our software versus a “traditional” workstation for ascertaining the severity of any Gria2 variant and its location within a 3d representation of the protein

Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.

Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10(-12)), while Dnmt3a KO signature does not (P = 0.017)

Common susceptibility variants are shared between schizophrenia and psoriasis in the Han Chinese population

Previous studies have shown that individuals with schizophrenia have a greater risk for psoriasis than a typical person. This suggests that there might be a shared genetic etiology between the 2 conditions. We aimed to characterize the potential shared genetic susceptibility between schizophrenia and psoriasis using genome-wide marker genotype data

Common susceptibility variants are shared between schizophrenia and psoriasis in the Han Chinese population

Background Previous studies have shown that individuals with schizophrenia have a greater risk for psoriasis than a typical person. This suggests that there might be a shared genetic etiology between the 2 conditions. We aimed to characterize the potential shared genetic susceptibility between schizophrenia and psoriasis using genome-wide marker genotype data. Methods We obtained genetic data on individuals with psoriasis, schizophrenia and control individuals. We applied a marker-based coheritability estimation procedure, polygenic score analysis, a gene set enrichment test and a least absolute shrinkage and selection operator regression model to estimate the potential shared genetic etiology between the 2 diseases. We validated the results in independent schizophrenia and psoriasis cohorts from Singapore. Results We included 1139 individuals with psoriasis, 744 with schizophrenia and 1678 controls in our analysis, and we validated the results in independent cohorts, including 441 individuals with psoriasis (and 2420 controls) and 1630 with schizophrenia (and 1860 controls). We estimated that a large fraction of schizophrenia and psoriasis risk could be attributed to common variants (h(SNP)(2) = 29% 5.0%, p = 2.00 x 10(-8)), with a coheritability estimate between the traits of 21%. We identified 5 variants within the human leukocyte antigen (HLA) gene region, which were most likely to be associated with both diseases and collectively conferred a significant risk effect (odds ratio of highest risk quartile = 6.03, p < 2.00 x 10(-16)). We discovered that variants contributing most to the shared heritable component between psoriasis and schizophrenia were enriched in antigen processing and cell endoplasmic reticulum. Limitations Our sample size was relatively small. The findings of 5 HLA gene variants were complicated by the complex structure in the HLA region. Conclusion We found evidence for a shared genetic etiology between schizophrenia and psoriasis. The mechanism for this shared genetic basis likely involves immune and calcium signalling pathways.National Natural Science Foundation of China [81370044, 81000692, 81273301, 81072461, 81130031, 81222022, 81222017]; China Council of Scholarship [201208340003]; Youth Project of the Outstanding Talents of Organization Department of the CPC Central Committee Program [31200939]; Pre-National Basic Research Program of China (973 Plan) [2012CB722404]; Anhui Province Natural Science Foundation [1208085QH145]; Anhui High Education Young Talent; Anhui Medical University [XJ201429]; NIH [1UL1TR001114, U19 AG023122-09, R01 DA030976-05, R01 MH094483-03, R01 AG035020-05, R01 MH100351-02, R21 AG045789-01A1]; Human Longevity, Inc.; Johnson and Johnson; Tanner Foundation; Stand-Up-to-Cancer organization; National Research Foundation Singapore under the National Medical Research Council Translational and Clinical Research Flagship Program [NMRC/TCR/003/2008]SCI(E)[email protected]; [email protected]

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp