hGSuite HyperBrowser: A web-based toolkit for hierarchical metadata-informed analysis of genomic tracks.

Many high-throughput sequencing datasets can be represented as objects with coordinates along a reference genome. Currently, biological investigations often involve a large number of such datasets, for example representing different cell types or epigenetic factors. Drawing overall conclusions from a large collection of results for individual datasets may be challenging and time-consuming. Meaningful interpretation often requires the results to be aggregated according to metadata that represents biological characteristics of interest. In this light, we here propose the hierarchical Genomic Suite HyperBrowser (hGSuite), an open-source extension to the GSuite HyperBrowser platform, which aims to provide a means for extracting key results from an aggregated collection of high-throughput DNA sequencing data. The hGSuite utilizes a metadata-informed data cube to calculate various statistics across the multiple dimensions of the datasets. With this work, we show that the hGSuite and its associated data cube methodology offers a quick and accessible way for exploratory analysis of large genomic datasets. The web-based toolkit named hGsuite Hyperbrowser is available at https://hyperbrowser.uio.no/hgsuite under a GPLv3 license.

Longitudinal whole blood transcriptomic analysis characterizes neutrophil activation and interferon signaling in moderate and severe COVID-19.

A maladaptive inflammatory response has been implicated in the pathogenesis of severe COVID-19. This study aimed to characterize the temporal dynamics of this response and investigate whether severe disease is associated with distinct gene expression patterns. We performed microarray analysis of serial whole blood RNA samples from 17 patients with severe COVID-19, 15 patients with moderate disease and 11 healthy controls. All study subjects were unvaccinated. We assessed whole blood gene expression patterns by differential gene expression analysis, gene set enrichment, two clustering methods and estimated relative leukocyte abundance using CIBERSORT. Neutrophils, platelets, cytokine signaling, and the coagulation system were activated in COVID-19, and this broad immune activation was more pronounced in severe vs. moderate disease. We observed two different trajectories of neutrophil-associated genes, indicating the emergence of a more immature neutrophil phenotype over time. Interferon-associated genes were strongly enriched in early COVID-19 before falling markedly, with modest severity-associated differences in trajectory. In conclusion, COVID-19 necessitating hospitalization is associated with a broad inflammatory response, which is more pronounced in severe disease. Our data suggest a progressively more immature circulating neutrophil phenotype over time. Interferon signaling is enriched in COVID-19 but does not seem to drive severe disease.

TiSA: TimeSeriesAnalysis-a pipeline for the analysis of longitudinal transcriptomics data.

Improved transcriptomic sequencing technologies now make it possible to perform longitudinal experiments, thus generating a large amount of data. Currently, there are no dedicated or comprehensive methods for the analysis of these experiments. In this article, we describe our TimeSeries Analysis pipeline (TiSA) which combines differential gene expression, clustering based on recursive thresholding, and a functional enrichment analysis. Differential gene expression is performed for both the temporal and conditional axes. Clustering is performed on the identified differentially expressed genes, with each cluster being evaluated using a functional enrichment analysis. We show that TiSA can be used to analyse longitudinal transcriptomic data from both microarrays and RNA-seq, as well as small, large, and/or datasets with missing data points. The tested datasets ranged in complexity, some originating from cell lines while another was from a longitudinal experiment of severity in COVID-19 patients. We have also included custom figures to aid with the biological interpretation of the data, these plots include Principal Component Analyses, Multi Dimensional Scaling plots, functional enrichment dotplots, trajectory plots, and complex heatmaps showing the broad overview of results. To date, TiSA is the first pipeline to provide an easy solution to the analysis of longitudinal transcriptomics experiments.

Krill oil protects dopaminergic neurons from age-related degeneration through temporal transcriptome rewiring and suppression of several hallmarks of aging.

There is accumulating evidence that interfering with the basic aging mechanisms can enhance healthy longevity. The interventional/therapeutic strategies targeting multiple aging hallmarks could be more effective than targeting one hallmark. While health-promoting qualities of marine oils have been extensively studied, the underlying molecular mechanisms are not fully understood. Lipid extracts from Antarctic krill are rich in long-chain omega-3 fatty acids choline, and astaxanthin. Here, we used C. elegans and human cells to investigate whether krill oil promotes healthy aging. In a C. elegans model of Parkinson´s disease, we show that krill oil protects dopaminergic neurons from aging-related degeneration, decreases alpha-synuclein aggregation, and improves dopamine-dependent behavior and cognition. Krill oil rewires distinct gene expression programs that contribute to attenuating several aging hallmarks, including oxidative stress, proteotoxic stress, senescence, genomic instability, and mitochondrial dysfunction. Mechanistically, krill oil increases neuronal resilience through temporal transcriptome rewiring to promote anti-oxidative stress and anti-inflammation via healthspan regulating transcription factors such as SNK-1. Moreover, krill oil promotes dopaminergic neuron survival through regulation of synaptic transmission and neuronal functions via PBO-2 and RIM-1. Collectively, krill oil rewires global gene expression programs and promotes healthy aging via abrogating multiple aging hallmarks, suggesting directions for further pre-clinical and clinical explorations.