In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html
 .

/pdf/moderated-estimation-of-fold-change-and-dispersion-for-rna-3ywnbkcan0.pdf

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

/pdf/gene-set-enrichment-analysis-a-knowledge-based-approach-for-mbpti6qljw.pdf

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).

http://dmrocke.ucdavis.edu/Class/BST226.2014.Winter/edgeR%20bioinformatics%202010.pdf

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

/pdf/limma-powers-differential-expression-analyses-for-rna-4yl7ae3arh.pdf

limma powers differential expression analyses for RNA-sequencing and microarray studies

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-Seq data, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data. DESeq2 uses shrinkage estimation for dispersions and fold changes to improve stability and interpretability of the estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression and facilitates downstream tasks such as gene ranking and visualization. DESeq2 is available as an R/Bioconductor package.

/pdf/moderated-estimation-of-fold-change-and-dispersion-for-rna-59glcgpwlk.pdf

The trans-luminal LINC (Linker of Nucleoskeleton and Cytoskeleton) complex plays a central role in nuclear mechanotransduction by coupling the nucleus with cytoskeleton. High spatial density and active dynamics of LINC complex have hindered its precise characterization for the understanding of underlying mechanisms how the linkages sense and respond to mechanical stimuli. In this study, we focus on SUN2, a core component of LINC complex interconnecting the nuclear lamina and actin cytoskeleton and apply single molecule super-resolution imaging to reveal how SUN2 responds to actomyosin contractility. Using stochastic optical reconstruction microscopy (STORM), we quantitated the distribution pattern and density of SUN2 on the basal nuclear membrane. We found that SUN2 undergoes bidirectional translocation between ER and nuclear membrane in response to actomyosin contractility, suggesting that dynamic constrained force on SUN2 is required for its proper distribution. Furthermore, single molecule imaging unveils interesting dynamics of SUN2 molecules that are regulated by both actomyosin contractility and laminA/C network, whereas SUN2 oligomeric states are not affected by actomyosin contractility. Lastly, the mechanical response of SUN2 to actomyosin contractility was found to regulate expression of mechano-sensitive genes located in lamina-associated domains (LADs) and perinuclear heterochromatin. Taken together, our results reveal how SUN2 responds to mechanical cues at the single-molecule level, providing new insights into the mechanism of nuclear mechanotransduction.

Perinuclear force regulates SUN2 dynamics and distribution on the nuclear envelope for proper nuclear mechanotransduction

Activity of Human T Lymphocytes and NK Regulation of Phenotype and Functional Heat Shock Protein 90 Is Critical for

Motivated by the unique experience of creating three-dimensional artworks in virtual reality (VR) and the need for teletherapy due to the global pandemic, we conducted this pilot case study to explore the feasibility and effectiveness of using a custom-designed collaborative virtual environment (CVE) to enable remote arts therapy. Three participants (two females and one male) experiencing moderate to high stress as measured by the Perceived Stress Scale (PSS) joined this study. Each participant had eight 45-minute one-on-one sessions with the therapist for eight consecutive weeks. These eight sessions covered eight art creation themes and were delivered following pre-designed protocols. The CVE was the only medium to facilitate the sessions, during which the therapist and the participants were physically separated into two rooms. The quantitative and qualitative results suggested that the CVE-enabled approach was generally feasible and was welcomed by both the participants and the therapist. However, more evidence of the approach’s effectiveness in enhancing the participants’ mental wellbeing is needed because the results of the pilot case study were affected by the pandemic. The advantages and disadvantages of this approach and the CVE were investigated from practicality and technological affordance perspectives. Potential improvements to the CVE are also proposed to better facilitate the practice of remote arts therapy in CVE. We encourage future studies to cautiously investigate CVE-enabled remote arts therapy in clinical settings and collect more evidence regarding its effectiveness in addressing clinically diagnosed mental disorders and other complications.

/pdf/remote-arts-therapy-in-collaborative-virtual-environment-a-25ez3eh0.pdf

Remote arts therapy in collaborative virtual environment: A pilot case study

Here we report the generation and characterization of a novel Huntington9s disease (HD) mouse model BAC226Q by using a bacterial artificial chromosome (BAC) system, expressing full length human HTT with ~226 CAG-CAA repeats and containing endogenous human HTT promoter and regulatory elements. BAC226Q recapitulated a full-spectrum of age-dependent and progressive HD-like phenotypes without unwanted and erroneous phenotypes. BAC226Q mice developed normally, and gradually exhibited HD-like mood and cognitive phenotypes at 2 months. From 3-4 months, BAC226Q mice showed robust progressive motor deficits. At 11 months, BAC226Q mice showed significant reduced life span, gradual weight loss and exhibit neuropathology including significant brain atrophy specific to striatum and cortex, striatal neuronal death, widespread huntingtin inclusions and reactive pathology. Therefore, the novel BAC226Q mouse accurately recapitulating robust, age-dependent, progressive HD-like phenotypes will be a valuable tool for studying disease mechanisms, identifying biomarkers and testing gene-targeting therapeutic approaches for HD.

https://biorxiv.org/content/10.1101/2021.06.14.448318v1.full.pdf

Cheng Li

Papers

Perinuclear force regulates SUN2 dynamics and distribution on the nuclear envelope for proper nuclear mechanotransduction

Activity of Human T Lymphocytes and NK Regulation of Phenotype and Functional Heat Shock Protein 90 Is Critical for

Remote arts therapy in collaborative virtual environment: A pilot case study

A novel and accurate full-length HTT mouse model for Huntington's disease

In vivo G-CSF treatment activates the GR-SOCS1 axis to suppress IFN-γ secretion by natural killer cells.