consensusDE: an R package for assessing consensus of multiple RNA-seq algorithms with RUV correction

Extensive evaluation of RNA-seq methods have demonstrated that no single algorithm consistently outperforms all others. Removal of unwanted variation (RUV) has also been proposed as a method for stabilizing differential expression (DE) results. Despite this, it remains a challenge to run multiple RNA-seq algorithms to identify significant differences common to multiple algorithms, whilst also integrating and assessing the impact of RUV into all algorithms. consensusDE was developed to automate the process of identifying significant DE by combining the results from multiple algorithms with minimal user input and with the option to automatically integrate RUV. consensusDE only requires a table describing the sample groups, a directory containing BAM files or preprocessed count tables and an optional transcript database for annotation. It supports merging of technical replicates, paired analyses and outputs a compendium of plots to guide the user in subsequent analyses. Herein, we assess the ability of RUV to improve DE stability when combined with multiple algorithms and between algorithms, through application to real and simulated data. We find that, although RUV increased fold change stability between algorithms, it demonstrated improved FDR in a setting of low replication for the intersect, the effect was algorithm specific and diminished with increased replication, reinforcing increased replication for recovery of true DE genes. We finish by offering some rules and considerations for the application of RUV in a consensus-based setting. consensusDE is freely available, implemented in R and available as a Bioconductor package, under the GPL-3 license, along with a comprehensive vignette describing functionality: trup://bioconduaor.org/packagesi consensusDE/

consensusDE: an R package for assessing consensus of multiple RNA-seq algorithms with RUV correction

Extensive evaluation of RNA-seq methods have demonstrated that no single algorithm consistently outperforms all others. Removal of unwanted variation (RUV) has also been proposed as a method for stabilizing differential expression (DE) results. Despite this, it remains a challenge to run multiple RNA-seq algorithms to identify significant differences common to multiple algorithms, whilst also integrating and assessing the impact of RUV into all algorithms. consensusDE was developed to automate the process of identifying significant DE by combining the results from multiple algorithms with minimal user input and with the option to automatically integrate RUV. consensusDE only requires a table describing the sample groups, a directory containing BAM files or preprocessed count tables and an optional transcript database for annotation. It supports merging of technical replicates, paired analyses and outputs a compendium of plots to guide the user in subsequent analyses. Herein, we assess the ability of RUV to improve DE stability when combined with multiple algorithms and between algorithms, through application to real and simulated data. We find that, although RUV increased fold change stability between algorithms, it demonstrated improved FDR in a setting of low replication for the intersect, the effect was algorithm specific and diminished with increased replication, reinforcing increased replication for recovery of true DE genes. We finish by offering some rules and considerations for the application of RUV in a consensus-based setting. consensusDE is freely available, implemented in R and available as a Bioconductor package, under the GPL-3 license, along with a comprehensive vignette describing functionality: http://bioconductor.org/packages/ consensusDE/This work has been supported by the NHMRC fellowship APP113975

CompGO: an R package for comparing and visualizing gene ontology enrichment differences between DNA binding experiments

Background: Gene ontology (GO) enrichment is commonly used for inferring biological meaning from systems biology experiments. However, determining differential GO and pathway enrichment between DNA-binding experiments or using the GO structure to classify experiments has received little attention. Results: Herein, we present a bioinformatics tool, CompGO, for identifying Differentially Enriched Gene Ontologies, called DiEGOs, and pathways, through the use of a z-score derivation of log odds ratios, and visualizing these differences at GO and pathway level. Through public experimental data focused on the cardiac transcription factor NKX2-5, we illustrate the problems associated with comparing GO enrichments between experiments using a simple overlap approach. Conclusions: We have developed an R/Bioconductor package, CompGO, which implements a new statistic normally used in epidemiological studies for performing comparative GO analyses and visualizing comparisons from .BED data containing genomic coordinates as well as gene lists as inputs. We justify the statistic through inclusion of experimental data and compare to the commonly used overlap method. CompGO is freely available as a R/Bioconductor package enabling easy integration into existing pipelines and is available at: http://www.bioconductor.org/packages/release/bioc/html/CompGO.html packages/release/bioc/html/CompGO.htm

An analytically and diagnostically sensitive RNA extraction and RT-qPCR protocol for peripheral blood mononuclear cells

Reliable extraction and sensitive detection of RNA from human peripheral blood mononuclear cells (PBMCs) is critical for a broad spectrum of immunology research and clinical diagnostics. RNA analysis platforms are dependent upon high-quality and high-quantity RNA; however, sensitive detection of specific responses associated with high-quality RNA extractions from human samples with limited PBMCs can be challenging. Furthermore, the comparative sensitivity between RNA quantification and best-practice protein quantification is poorly defined. Therefore, we provide herein a critical evaluation of the wide variety of current generation of RNA-based kits for PBMCs, representative of several strategies designed to maximize sensitivity. We assess these kits with a reverse transcription quantitative PCR (RT-qPCR) assay optimized for both analytically and diagnostically sensitive cell-based RNA-based applications. Specifically, three RNA extraction kits, one post-extraction RNA purification/concentration kit, four SYBR master-mix kits, and four reverse transcription kits were tested. RNA extraction and RT-qPCR reaction efficiency were evaluated with commonly used reference and cytokine genes. Significant variation in RNA expression of reference genes was apparent, and absolute quantification based on cell number was established as an effective RT-qPCR normalization strategy. We defined an optimized RNA extraction and RT-qPCR protocol with an analytical sensitivity capable of single cell RNA detection. The diagnostic sensitivity of this assay was sufficient to show a CD8+ T cell peptide epitope hierarchy with as few as 1 × 104 cells. Finally, we compared our optimized RNA extraction and RT-qPCR protocol with current best-practice immune assays and demonstrated that our assay is a sensitive alternative to protein-based assays for peptide-specific responses, especially with limited PBMCs number. This protocol with high analytical and diagnostic sensitivity has broad applicability for both primary research and clinical practice

Progesterone signalling in broiler skeletal muscle is associated with divergent feed efficiency

Background: We contrast the pectoralis muscle transcriptomes of broilers selected from within a single genetic line expressing divergent feed efficiency (FE) in an effort to improve our understanding of the mechanistic basis of FE. Results: Application of a virtual muscle model to gene expression data pointed to a coordinated reduction in slow twitch muscle isoforms of the contractile apparatus (MYH15, TPM3, MYOZ2, TNNI1, MYL2, MYOM3, CSRP3, TNNT2), consistent with diminishment in associated slow machinery (myoglobin and phospholamban) in the high FE animals. These data are in line with the repeated transition from red slow to white fast muscle fibres observed in agricultural species selected on mass and FE. Surprisingly, we found that the expression of 699 genes encoding the broiler mitoproteome is modestly–but significantly–biased towards the high FE group, suggesting a slightly elevated mitochondrial content. This is contrary to expectation based on the slow muscle isoform data and theoretical physiological capacity arguments. Reassuringly, the extreme 40 most DE genes can successfully cluster the 12 individuals into the appropriate FE treatment group. Functional groups contained in this DE gene list include metabolic proteins (including opposing patterns of CA3 and CA4), mitochondrial proteins (CKMT1A), oxidative status (SEPP1, HIG2A) and cholesterol homeostasis (APOA1, INSIG1). We applied a differential network method (Regulatory Impact Factors) whose aim is to use patterns of differential co-expression to detect regulatory molecules transcriptionally rewired between the groups. This analysis clearly points to alterations in progesterone signalling (via the receptor PGR) as the major driver. We show the progesterone receptor localises to the mitochondria in a quail muscle cell line. Conclusions: Progesterone is sometimes used in the cattle industry in exogenous hormone mixes that lead to a ~20% increase in FE. Because the progesterone receptor can localise to avian mitochondria, our data continue to point to muscle mitochondrial metabolism as an important component of the phenotypic expression of variation in broiler FE

A systematic approach to simultaneously evaluate safety, immunogenicity, and efficacy of novel tuberculosis vaccination strategies

Tuberculosis (TB) is the deadliest infectious disease worldwide. Bacille-Calmette-Guerin (BCG), the only licensed TB vaccine, affords variable protection against TB but remains the gold standard. BCG improvement is focused around three strategies: recombinant BCG strains, heterologous routes of administration, and booster vaccination. It is currently unknown whether combining these strategies is beneficial. The preclinical evaluation for new TB vaccines is heavily skewed toward immunogenicity and efficacy; however, safety and efficacy are the dominant considerations in human use. To facilitate stage gating of TB vaccines, we developed a simple empirical model to systematically rank vaccination strategies by integrating multiple measurements of safety, immunogenicity, and efficacy. We assessed 24 vaccination regimens, composed of three BCG strains and eight combinations of delivery. The model presented here highlights that mucosal booster vaccination may cause adverse outcomes and provides a much needed strategy to evaluate and rank data obtained from TB vaccine studies using different routes, strains, or animal models

An Always Correlated gene expression landscape for ovine skeletal muscle, lessons learnt from comparison with an “equivalent” bovine landscape

BACKGROUND: We have recently described a method for the construction of an informative gene expression correlation landscape for a single tissue, longissimus muscle (LM) of cattle, using a small number (less than a hundred) of diverse samples. Does this approach facilitate interspecies comparison of networks? FINDINGS: Using gene expression datasets from LM samples from a single postnatal time point for high and low muscling sheep, and from a developmental time course (prenatal to postnatal) for normal sheep and sheep exhibiting the Callipyge muscling phenotype gene expression correlations were calculated across subsets of the data comparable to the bovine analysis. An “Always Correlated” gene expression landscape was constructed by integrating the correlations from the subsets of data and was compared to the equivalent landscape for bovine LM muscle. Whilst at the high level apparently equivalent modules were identified in the two species, at the detailed level overlap between genes in the equivalent modules was limited and generally not significant. Indeed, only 395 genes and 18 edges were in common between the two landscapes. CONCLUSIONS: Since it is unlikely that the equivalent muscles of two closely related species are as different as this analysis suggests, within tissue gene expression correlations appear to be very sensitive to the samples chosen for their construction, compounded by the different platforms used. Thus users need to be very cautious in interpretation of the differences. In future experiments, attention will be required to ensure equivalent experimental designs and use cross-species gene expression platform to enable the identification of true differences between different species

Small extracellular vesicles but not microvesicles from Opisthorchis viverrini promote cell proliferation in human cholangiocytes

Chronic infection with O. viverrini has been linked to the development of cholangiocarcinoma (CCA), which is a major public health burden in the Lower Mekong River Basin countries, including Thailand, Lao PDR, Vietnam and Cambodia. Despite its importance, the exact mechanisms by which O. viverrini promotes CCA are largely unknown. In this study, we characterized different extracellular vesicle populations released by O. viverrini (OvEVs) using proteomic and transcriptomic analyses and investigated their potential role in host-parasite interactions. While 120k OvEVs promoted cell proliferation in H69 cells at different concentrations, 15k OvEVs did not produce any effect compared to controls. The proteomic analysis of both populations showed differences in their composition that could contribute to this differential effect. Furthermore, the miRNAs present in 120k EVs were analysed and their potential interactions with human host genes was explored by computational target prediction. Different pathways involved in inflammation, immune response and apoptosis were identified as potentially targeted by the miRNAs present in this population of EVs. This is the first study showing specific roles for different EV populations in the pathogenesis of a parasitic helminth, and more importantly, an important advance towards deciphering the mechanisms used in establishment of opisthorchiasis and liver fluke infection-associated malignancy.This research was supported from a project grant from the National Health and Medical Research Council of Australia (NHMRC), grant identification number APP1085309, the National Cancer Institute, National Institutes of Health, award number R01CA164719, and the Fundamental Fund, Khon Kaen University. AL is supported by a Level Three NHMRC Investigator Grant APP2008450. JS is supported by a Ramon y Cajal fellowship (RYC2021-032443-I) from the Ministerio de Ciencia e Innovacion from Spain.N

A presynaptic phosphosignaling hub for lasting homeostatic plasticity

Stable function of networks requires that synapses adapt their strength to levels of neuronal activity, and failure to do so results in cognitive disorders. How such homeostatic regulation may be implemented in mammalian synapses remains poorly understood. Here we show that the phosphorylation status of several positions of the active-zone (AZ) protein RIM1 are relevant for synaptic glutamate release. Position RIMS1045 is necessary and sufficient for expression of silencing-induced homeostatic plasticity and is kept phosphorylated by serine arginine protein kinase 2 (SRPK2). SRPK2-induced upscaling of synaptic release leads to additional RIM1 nanoclusters and docked vesicles at the AZ and is not observed in the absence of RIM1 and occluded by RIMS1045E. Our data suggest that SRPK2 and RIM1 represent a presynaptic phosphosignaling hub that is involved in the homeostatic balance of synaptic coupling of neuronal networks

Using a 3D virtual muscle model to link gene expression changes during myogenesis to protein spatial location in muscle

Background: Myogenesis is an ordered process whereby mononucleated muscle precursor cells (myoblasts) fuse into multinucleated myotubes that eventually differentiate into myofibres, involving substantial changes in gene expression and the organisation of structural components of the cells. To gain further insight into the orchestration of these structural changes we have overlaid the spatial organisation of the protein components of a muscle cell with their gene expression changes during differentiation using a new 3D visualisation tool: the Virtual Muscle 3D (VMus3D)