Differential Impact In Vivo of Pf4-ΔCre-Mediated and Gp1ba-ΔCre-Mediated Depletion of Cyclooxygenase-1 in Platelets in Mice.

BACKGROUND: Low-dose aspirin is widely used for the secondary prevention of cardiovascular disease. The beneficial effects of low-dose aspirin are attributable to its inhibition of platelet Cox (cyclooxygenase)-1-derived thromboxane A2. Until recently, the use of the Pf4 (platelet factor 4) Cre has been the only genetic approach to generating megakaryocyte/platelet ablation of Cox-1 in mice. However, Pf4-ΔCre displays ectopic expression outside the megakaryocyte/platelet lineage, especially during inflammation. The use of the Gp1ba (glycoprotein 1bα) Cre promises a more specific, targeted approach. METHODS: To evaluate the role of Cox-1 in platelets, we crossed Pf4-ΔCre or Gp1ba-ΔCre mice with Cox-1flox/flox mice to generate platelet Cox-1-/- mice on normolipidemic and hyperlipidemic (Ldlr-/-) backgrounds. RESULTS: Ex vivo platelet aggregation induced by arachidonic acid or adenosine diphosphate in platelet-rich plasma was inhibited to a similar extent in Pf4-ΔCre Cox-1-/-/Ldlr-/- and Gp1ba-ΔCre Cox-1-/-/Ldlr-/- mice. In a mouse model of tail injury, Pf4-ΔCre-mediated and Gp1ba-ΔCre-mediated deletions of Cox-1 were similarly efficient in suppressing platelet prostanoid biosynthesis. Experimental thrombogenesis and attendant blood loss were similar in both models. However, the impact on atherogenesis was divergent, being accelerated in the Pf4-ΔCre mice while restrained in the Gp1ba-ΔCres. In the former, accelerated atherogenesis was associated with greater suppression of PGI2 biosynthesis, a reduction in the lipopolysaccharide-evoked capacity to produce PGE2 and PGD2, activation of the inflammasome, elevated plasma levels of IL-1ß, reduced plasma levels of HDL-C, and a reduction in the capacity for reverse cholesterol transport. By contrast, in the latter, plasma HDL-C and α-tocopherol were elevated, and MIP-1α (macrophage inflammatory protein-1α) and MCP-1 (monocyte chemoattractant protein 1) were reduced. CONCLUSIONS: Both approaches to Cox-1 deletion similarly restrain thrombogenesis, but a differential impact on Cox-1-dependent prostanoid formation by the vasculature may contribute to an inflammatory phenotype and accelerated atherogenesis in Pf4-ΔCre mice.

BEERS2: RNA-Seq simulation through high fidelity in silico modeling.

Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully length messenger RNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in polymerase chain reaction (PCR) amplification, barcode read errors and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm.

Challenges and best practices in omics benchmarking.

Technological advances enabling massively parallel measurement of biological features - such as microarrays, high-throughput sequencing and mass spectrometry - have ushered in the omics era, now in its third decade. The resulting complex landscape of analytical methods has naturally fostered the growth of an omics benchmarking industry. Benchmarking refers to the process of objectively comparing and evaluating the performance of different computational or analytical techniques when processing and analysing large-scale biological data sets, such as transcriptomics, proteomics and metabolomics. With thousands of omics benchmarking studies published over the past 25 years, the field has matured to the point where the foundations of benchmarking have been established and well described. However, generating meaningful benchmarking data and properly evaluating performance in this complex domain remains challenging. In this Review, we highlight some common oversights and pitfalls in omics benchmarking. We also establish a methodology to bring the issues that can be addressed into focus and to be transparent about those that cannot: this takes the form of a spreadsheet template of guidelines for comprehensive reporting, intended to accompany publications. In addition, a survey of recent developments in benchmarking is provided as well as specific guidance for commonly encountered difficulties.

Diurnal rhythms of wrist temperature are associated with future disease risk in the UK Biobank.

Many chronic disease symptomatologies involve desynchronized sleep-wake cycles, indicative of disrupted biorhythms. This can be interrogated using body temperature rhythms, which have circadian as well as sleep-wake behavior/environmental evoked components. Here, we investigated the association of wrist temperature amplitudes with a future onset of disease in the UK Biobank one year after actigraphy. Among 425 disease conditions (range n = 200-6728) compared to controls (range n = 62,107-91,134), a total of 73 (17%) disease phenotypes were significantly associated with decreased amplitudes of wrist temperature (Benjamini-Hochberg FDR q < 0.05) and 26 (6.1%) PheCODEs passed a more stringent significance level (Bonferroni-correction α < 0.05). A two-standard deviation (1.8° Celsius) lower wrist temperature amplitude corresponded to hazard ratios of 1.91 (1.58-2.31 95% CI) for NAFLD, 1.69 (1.53-1.88) for type 2 diabetes, 1.25 (1.14-1.37) for renal failure, 1.23 (1.17-1.3) for hypertension, and 1.22 (1.11-1.33) for pneumonia (phenome-wide atlas available at http://bioinf.itmat.upenn.edu/biorhythm_atlas/ ). This work suggests peripheral thermoregulation as a digital biomarker.

Circadian regulation of lung repair and regeneration.

Optimal lung repair and regeneration are essential for recovery from viral infections, including influenza A virus (IAV). We have previously demonstrated that acute inflammation and mortality induced by IAV is under circadian control. However, it is not known whether the influence of the circadian clock persists beyond the acute outcomes. Here, we utilize the UK Biobank to demonstrate an association between poor circadian rhythms and morbidity from lower respiratory tract infections, including the need for hospitalization and mortality after discharge; this persists even after adjusting for common confounding factors. Furthermore, we use a combination of lung organoid assays, single-cell RNA sequencing, and IAV infection in different models of clock disruption to investigate the role of the circadian clock in lung repair and regeneration. We show that lung organoids have a functional circadian clock and the disruption of this clock impairs regenerative capacity. Finally, we find that the circadian clock acts through distinct pathways in mediating lung regeneration - in tracheal cells via the Wnt/ß-catenin pathway and through IL-1ß in alveolar epithelial cells. We speculate that adding a circadian dimension to the critical process of lung repair and regeneration will lead to novel therapies and improve outcomes.

Meta-analysis of Diurnal Transcriptomics in Mouse Liver Reveals Low Repeatability of Rhythm Analyses.

To assess the consistency of biological rhythms across studies, 57 public mouse liver tissue timeseries totaling 1096 RNA-seq samples were obtained and analyzed. Only the control groups of each study were included, to create comparable data. Technical factors in RNA-seq library preparation were the largest contributors to transcriptome-level differences, beyond biological or experiment-specific factors such as lighting conditions. Core clock genes were remarkably consistent in phase across all studies. Overlap of genes identified as rhythmic across studies was generally low, with no pair of studies having over 60% overlap. Distributions of phases of significant genes were remarkably inconsistent across studies, but the genes that consistently identified as rhythmic had acrophase clustering near ZT0 and ZT12. Despite the discrepancies between single-study analyses, cross-study analyses found substantial consistency. Running compareRhythms on each pair of studies identified a median of only 11% of the identified rhythmic genes as rhythmic in only 1 of the 2 studies. Data were integrated across studies in a joint and individual variance estimate (JIVE) analysis, which showed that the top 2 components of joint within-study variation are determined by time of day. A shape-invariant model with random effects was fit to the genes to identify the underlying shape of the rhythms, consistent across all studies, including identifying 72 genes with consistently multiple peaks.

BEERS2: RNA-Seq simulation through high fidelity in silico modeling.

Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking, and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully-length mRNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM, or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in PCR amplification, barcode read errors, and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm.

Sexual dimorphism in the response to chronic circadian misalignment on a high-fat diet.

Longitudinal studies associate shiftwork with cardiometabolic disorders but do not establish causation or elucidate mechanisms of disease. We developed a mouse model based on shiftwork schedules to study circadian misalignment in both sexes. Behavioral and transcriptional rhythmicity were preserved in female mice despite exposure to misalignment. Females were protected from the cardiometabolic impact of circadian misalignment on a high-fat diet seen in males. The liver transcriptome and proteome revealed discordant pathway perturbations between the sexes. Tissue-level changes were accompanied by gut microbiome dysbiosis only in male mice, biasing toward increased potential for diabetogenic branched chain amino acid production. Antibiotic ablation of the gut microbiota diminished the impact of misalignment. In the United Kingdom Biobank, females showed stronger circadian rhythmicity in activity and a lower incidence of metabolic syndrome than males among job-matched shiftworkers. Thus, we show that female mice are more resilient than males to chronic circadian misalignment and that these differences are conserved in humans.

Modulation of the Immune Response to Severe Acute Respiratory Syndrome Coronavirus 2 Vaccination by Nonsteroidal Anti-Inflammatory Drugs.

Evidence is scarce to guide the use of nonsteroidal anti-inflammatory drugs (NSAIDs) to mitigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine-related adverse effects, given the possibility of blunting the desired immune response. In this pilot study, we deeply phenotyped a small number of volunteers who did or did not take NSAIDs concomitant with SARS-CoV-2 immunizations to seek initial information on the immune response. A SARS-CoV-2 vaccine-specific receptor binding domain (RBD) IgG antibody response and efficacy in the evoked neutralization titers were evident irrespective of concomitant NSAID consumption. Given the sample size, only a large and consistent signal of immunomodulation would have been detectable, and this was not apparent. However, the information gathered may inform the design of a definitive clinical trial. Here we report a series of divergent omics signals that invites additional hypotheses testing. SIGNIFICANCE STATEMENT: The impact of nonsteroidal anti-inflammatory drugs (NSAIDs) on the immune response elicited by repeat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunizations was profiled by immunophenotypic, proteomic, and metabolomic approaches in a clinical pilot study of small sample size. A SARS-CoV-2 vaccine-specific immune response was evident irrespective of concomitant NSAID consumption. The information gathered may inform the design of a definitive clinical trial.

RNA splicing analysis using heterogeneous and large RNA-seq datasets.

The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity. We describe here a suite of algorithms and tools implemented in the MAJIQ v2 package to address challenges in detection, quantification, and visualization of splicing variations from such datasets. Using both large scale synthetic data and GTEx v8 as benchmark datasets, we assess the advantages of MAJIQ v2 compared to existing methods. We then apply MAJIQ v2 package to analyze differential splicing across 2,335 samples from 13 brain subregions, demonstrating its ability to offer insights into brain subregion-specific splicing regulation.

The genetic and evolutionary basis of gene expression variation in East Africans.

BACKGROUND: Mapping of quantitative trait loci (QTL) associated with molecular phenotypes is a powerful approach for identifying the genes and molecular mechanisms underlying human traits and diseases, though most studies have focused on individuals of European descent. While important progress has been made to study a greater diversity of human populations, many groups remain unstudied, particularly among indigenous populations within Africa. To better understand the genetics of gene regulation in East Africans, we perform expression and splicing QTL mapping in whole blood from a cohort of 162 diverse Africans from Ethiopia and Tanzania. We assess replication of these QTLs in cohorts of predominantly European ancestry and identify candidate genes under selection in human populations. RESULTS: We find the gene regulatory architecture of African and non-African populations is broadly shared, though there is a considerable amount of variation at individual loci across populations. Comparing our analyses to an equivalently sized cohort of European Americans, we find that QTL mapping in Africans improves the detection of expression QTLs and fine-mapping of causal variation. Integrating our QTL scans with signatures of natural selection, we find several genes related to immunity and metabolism that are highly differentiated between Africans and non-Africans, as well as a gene associated with pigmentation. CONCLUSION: Extending QTL mapping studies beyond European ancestry, particularly to diverse indigenous populations, is vital for a complete understanding of the genetic architecture of human traits and can reveal novel functional variation underlying human traits and disease.

Time-specific associations of wearable sensor-based cardiovascular and behavioral readouts with disease phenotypes in the outpatient setting of the Chronic Renal Insufficiency Cohort.

Patients with chronic kidney disease are at risk of developing cardiovascular disease. To facilitate out-of-clinic evaluation, we piloted wearable device-based analysis of heart rate variability and behavioral readouts in patients with chronic kidney disease from the Chronic Renal Insufficiency Cohort and controls (n = 49). Time-specific partitioning of heart rate variability readouts confirm higher parasympathetic nervous activity during the night (mean RR at night 14.4 ± 1.9 ms vs. 12.8 ± 2.1 ms during active hours; n = 47, analysis of variance (ANOVA) q = 0.001). The α2 long-term fluctuations in the detrended fluctuation analysis, a parameter predictive of cardiovascular mortality, significantly differentiated between diabetic and nondiabetic patients (prominent at night with 0.58 ± 0.2 vs. 0.45 ± 0.12, respectively, adj. p = 0.004). Both diabetic and nondiabetic chronic kidney disease patients showed loss of rhythmic organization compared to controls, with diabetic chronic kidney disease patients exhibiting deconsolidation of peak phases between their activity and standard deviation of interbeat intervals rhythms (mean phase difference chronic kidney disease 8.3 h, chronic kidney disease/type 2 diabetes mellitus 4 h, controls 6.8 h). This work provides a roadmap toward deriving actionable clinical insights from the data collected by wearable devices outside of highly controlled clinical environments.

Nitecap: An Exploratory Circadian Analysis Web Application.

Circadian omics analyses present investigators with large amounts of data to consider and many choices for methods of analysis. Visualization is crucial as rhythmicity can take many forms and p-values offer an incomplete picture. Yet statically viewing the entirety of high-throughput datasets is impractical, and there is often limited ability to assess the impact of choices, such as significance threshold cutoffs. Nitecap provides an intuitive and unified web-based solution to these problems. Through highly responsive visualizations, Nitecap enables investigators to see dataset-wide behavior. It supports deep analyses, including comparisons of two conditions. Moreover, it focuses upon ease-of-use and enables collaboration through dataset sharing. As an application, we investigated cross talk between peripheral clocks in adipose and liver tissues and determined that adipocyte clock disruption does not substantially modulate the transcriptional rhythmicity of liver but does advance the phase of core clock gene Bmal1 (Arntl) expression in the liver. Nitecap is available at nitecap.org and is free-to-use.

CAMPAREE: a robust and configurable RNA expression simulator.

BACKGROUND: The accurate interpretation of RNA-Seq data presents a moving target as scientists continue to introduce new experimental techniques and analysis algorithms. Simulated datasets are an invaluable tool to accurately assess the performance of RNA-Seq analysis methods. However, existing RNA-Seq simulators focus on modeling the technical biases and artifacts of sequencing, rather than on simulating the original RNA samples. A first step in simulating RNA-Seq is to simulate RNA. RESULTS: To fill this need, we developed the Configurable And Modular Program Allowing RNA Expression Emulation (CAMPAREE), a simulator using empirical data to simulate diploid RNA samples at the level of individual molecules. We demonstrated CAMPAREE's use for generating idealized coverage plots from real data, and for adding the ability to generate allele-specific data to existing RNA-Seq simulators that do not natively support this feature. CONCLUSIONS: Separating input sample modeling from library preparation/sequencing offers added flexibility for both users and developers to mix-and-match different sample and sequencing simulators to suit their specific needs. Furthermore, the ability to maintain sample and sequencing simulators independently provides greater agility to incorporate new biological findings about transcriptomics and new developments in sequencing technologies. Additionally, by simulating at the level of individual molecules, CAMPAREE has the potential to model molecules transcribed from the same genes as a heterogeneous population of transcripts with different states of degradation and processing (splicing, editing, etc.). CAMPAREE was developed in Python, is open source, and freely available at https://github.com/itmat/CAMPAREE .

MOCCASIN: a method for correcting for known and unknown confounders in RNA splicing analysis.

The effects of confounding factors on gene expression analysis have been extensively studied following the introduction of high-throughput microarrays and subsequently RNA sequencing. In contrast, there is a lack of equivalent analysis and tools for RNA splicing. Here we first assess the effect of confounders on both expression and splicing quantifications in two large public RNA-Seq datasets (TARGET, ENCODE). We show quantification of splicing variations are affected at least as much as those of gene expression, revealing unwanted sources of variations in both datasets. Next, we develop MOCCASIN, a method to correct the effect of both known and unknown confounders on RNA splicing quantification and demonstrate MOCCASIN's effectiveness on both synthetic and real data. Code, synthetic and corrected datasets are all made available as resources.

Sex-dependent compensatory mechanisms preserve blood pressure homeostasis in prostacyclin receptor-deficient mice.

Inhibitors of microsomal prostaglandin E synthase 1 (mPGES-1) are in the early phase of clinical development. Deletion of mPges-1 in mice confers analgesia, restrains atherogenesis, and fails to accelerate thrombogenesis, while suppressing prostaglandin E2 (PGE2), but increasing the biosynthesis of prostacyclin (PGI2). In low-density lipoprotein receptor-deficient (Ldlr-/-) mice, this last effect represents the dominant mechanism by which mPges-1 deletion restrains thrombogenesis, while suppression of PGE2 accounts for its antiatherogenic effect. However, the effect of mPges-1 depletion on blood pressure (BP) in this setting remains unknown. Here, we show that mPges-1 depletion significantly increased the BP response to salt loading in male Ldlr-/- mice, whereas, despite the direct vasodilator properties of PGI2, deletion of the I prostanoid receptor (Ipr) suppressed this response. Furthermore, combined deletion of the Ipr abrogated the exaggerated BP response in male mPges-1-/- mice. Interestingly, these unexpected BP phenotypes were not observed in female mice fed a high-salt diet (HSD). This is attributable to the protective effect of estrogen in Ldlr-/- mice and in Ipr-/- Ldlr-/- mice. Thus, estrogen compensates for a deficiency in PGI2 to maintain BP homeostasis in response to high salt in hyperlipidemic female mice. In male mice, by contrast, the augmented formation of atrial natriuretic peptide (ANP) plays a similar compensatory role, restraining hypertension and oxidant stress in the setting of Ipr depletion. Hence, men with hyperlipidemia on a HSD might be at risk of a hypertensive response to mPGES-1 inhibitors.

Comparative evaluation of full-length isoform quantification from RNA-Seq.

BACKGROUND: Full-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and has been an area of active development since the beginning. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are short. RESULTS: Here we use simulated benchmarking data that reflects many properties of real data, including polymorphisms, intron signal and non-uniform coverage, allowing for systematic comparative analyses of isoform quantification accuracy and its impact on differential expression analysis. Genome, transcriptome and pseudo alignment-based methods are included; and a simple approach is included as a baseline control. CONCLUSIONS: Salmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.

Accounting for Time: Circadian Rhythms in the Time of COVID-19.

The COVID-19 pandemic has necessitated novel approaches and collaborative efforts across multiple disciplines. It is known that various aspects of our physiology and response to pathogens are under tight clock control. However, the assimilation of circadian biology into our clinical and research practices is still evolving. Using a focused review of the literature and original analyses of the UK Biobank, we discuss how circadian biology may inform our diagnostic and therapeutic strategies in this pandemic.

RNA-seq analysis of galaninergic neurons from ventrolateral preoptic nucleus identifies expression changes between sleep and wake.

BACKGROUND: Previous studies show that galanin neurons in ventrolateral preoptic nucleus (VLPO-Gal) are essential for sleep regulation. Here, we explored the transcriptional regulation of the VLPO-Gal neurons in sleep by comparing their transcriptional responses between sleeping mice and those kept awake, sacrificed at the same diurnal time. RESULTS: RNA-sequencing (RNA-seq) analysis was performed on eGFP(+) galanin neurons isolated using laser captured microdissection (LCM) from VLPO. Expression of Gal was assessed in our LCM eGFP(+) neurons via real time qPCR and showed marked enrichment when compared to LCM eGFP(-) cells and to bulk VLPO samples. Gene set enrichment analysis utilizing data from a recent single-cell RNA-seq study of the preoptic area demonstrated that our VLPO-Gal samples were highly enriched with galanin-expressing inhibitory neurons, but not galanin-expressing excitatory neurons. A total of 263 genes were differentially expressed between sleep and wake in VLPO-Gal neurons. When comparing differentially expressed genes in VLPO-Gal neurons to differentially expressed genes in a wake-active neuronal region (the medial prefrontal cortex), evidence indicates that both systemic and cell-specific mechanisms contribute to the transcriptional regulation in VLPO-Gal neurons. In both wake-active and sleep-active neurons, ER stress pathways are activated by wake and cold-inducible RNA-binding proteins are activated by sleep. In contrast, expression of DNA repair genes is increased in VLPO-Gal during wakefulness, but increased in wake-active cells during sleep. CONCLUSION: Our study identified transcriptomic responses of the galanin neurons in the ventrolateral preoptic nucleus during sleep and sleep deprivation. Data indicate that VLPO contains mainly sleep-active inhibitory galaninergic neurons. The VLPO galanin neurons show responses to sleep and wake similar to wake-active regions, indicating these responses, such as ER stress and cold-inducible RNA-binding proteins, are systemic affecting all neuronal populations. Region-specific differences in sleep/wake responses were also identified, in particular DNA repair. Our study expands knowledge about the transcriptional response of a distinct group of neurons essential for sleep.