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.

The positive impact of conservation action.

Governments recently adopted new global targets to halt and reverse the loss of biodiversity. It is therefore crucial to understand the outcomes of conservation actions. We conducted a global meta-analysis of 186 studies (including 665 trials) that measured biodiversity over time and compared outcomes under conservation action with a suitable counterfactual of no action. We find that in two-thirds of cases, conservation either improved the state of biodiversity or at least slowed declines. Specifically, we find that interventions targeted at species and ecosystems, such as invasive species control, habitat loss reduction and restoration, protected areas, and sustainable management, are highly effective and have large effect sizes. This provides the strongest evidence to date that conservation actions are successful but require transformational scaling up to meet global targets.

Roles of the Red List of Ecosystems in the Kunming-Montreal Global Biodiversity Framework.

The Kunming-Montreal Global Biodiversity Framework (GBF) of the UN Convention on Biological Diversity set the agenda for global aspirations and action to reverse biodiversity loss. The GBF includes an explicit goal for maintaining and restoring biodiversity, encompassing ecosystems, species and genetic diversity (goal A), targets for ecosystem protection and restoration and headline indicators to track progress and guide action1. One of the headline indicators is the Red List of Ecosystems2, the global standard for ecosystem risk assessment. The Red List of Ecosystems provides a systematic framework for collating, analysing and synthesizing data on ecosystems, including their distribution, integrity and risk of collapse3. Here, we examine how it can contribute to implementing the GBF, as well as monitoring progress. We find that the Red List of Ecosystems provides common theory and practical data, while fostering collaboration, cross-sector cooperation and knowledge sharing, with important roles in 16 of the 23 targets. In particular, ecosystem maps, descriptions and risk categories are key to spatial planning for halting loss, restoration and protection (targets 1, 2 and 3). The Red List of Ecosystems is therefore well-placed to aid Parties to the GBF as they assess, plan and act to achieve the targets and goals. We outline future work to further strengthen this potential and improve biodiversity outcomes, including expanding spatial coverage of Red List of Ecosystems assessments and partnerships between practitioners, policy-makers and scientists.

Harnessing online digital data in biodiversity monitoring.

Online digital data from media platforms have the potential to complement biodiversity monitoring efforts. We propose a strategy for integrating these data into current biodiversity datasets in light of the Kunming-Montreal Global Biodiversity Framework.

Prognostic utility of rhythmic components in 24-h ambulatory blood pressure monitoring for the risk stratification of chronic kidney disease patients with cardiovascular co-morbidity.

Chronic kidney disease (CKD) represents a significant global burden. Hypertension is a modifiable risk factor for rapid progression of CKD. We extend the risk stratification by introducing the non-parametric determination of rhythmic components in 24-h profiles of ambulatory blood pressure monitoring (ABPM) in the Chronic Renal Insufficiency Cohort (CRIC) and the African American Study for Kidney Disease and Hypertension (AASK) cohort using Cox proportional hazards models. We find that rhythmic profiling of BP through JTK_CYCLE analysis identifies subgroups of CRIC participants that were more likely to die due to cardiovascular causes. While our fully adjusted model shows a trend towards a significant association between absent cyclic components and cardiovascular death in the full CRIC cohort (HR: 1.71,95% CI: 0.99-2.97, p = 0.056), CRIC participants with a history of cardiovascular disease (CVD) and absent cyclic components in their BP profile had at any time a 3.4-times higher risk of cardiovascular death than CVD patients with cyclic components present in their BP profile (HR: 3.37, 95% CI: 1.45-7.87, p = 0.005). This increased risk was not explained by the dipping or non-dipping pattern in ABPM. Due to the large differences in patient characteristics, the results do not replicate in the AASK cohort. This study suggests rhythmic blood pressure components as a potential novel biomarker to unmask excess risk among CKD patients with prior cardiovascular disease.

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.

Examining the Role of Mononormative Beliefs, Stigma, and Internalized Consensual Non-Monogamy Negativity for Dehumanization.

Interest in consensually non-monogamous (CNM) relationships has been increasing in the general population in recent years. However, given the cultural dominance of monogamy and the normative expectations often imposed through socialization (i.e., mononormativity), people in CNM relationships may experience negativity, which can become internalized and harm their individual and relationship health. The present study investigated if mononormativity beliefs and CNM relationship stigma were associated with more dehumanization and if internalized CNM negativity was an underlying mechanism for these associations. Results showed that participants who endorsed more mononormative beliefs and CNM relationship stigma also reported more internalized CNM negativity. In turn, participants who experienced more internalized CNM negativity attributed more negative (vs. positive) emotions to themselves and treated their partners as more immature, unrefined, exploitable, and emotionless. These results show that mononormativity and internalized negativity can shape the attitudes, perceptions, and behaviors of CNM individuals toward themselves and their partners.

Bottom-up global biodiversity metrics needed for businesses to assess and manage their impact.

Ensuring that companies can assess and manage their impacts on biodiversity will be crucial to solving the current biodiversity crisis, and regulatory and public pressure to disclose these impacts is increasing. Top-down intactness metrics (e.g., Mean Species Abundance) can be valuable for generating high-level or first-tier assessments of impact risk but do not provide sufficient precision or guidance for companies, regulators, or third-party assessors. New metrics based on bottom-up assessments of biodiversity (e.g., the Species Threat Abatement and Restoration metric) can accommodate spatial variation of biodiversity and provide more specific guidance for actions to avoid, reduce, remediate, and compensate for impacts and to identify positive opportunities.

Cuantificación vertical de la biodiversidad mundial necesarias para que las empresas evalúen y gestionen su impacto Resumen Para resolver la actual crisis de biodiversidad, es importante asegurar que las empresas puedan evaluar y gestionar su impacto sobre la biodiversidad. Además, cada vez es mayor la presión pública y legislativa para divulgar este impacto. La cuantificación vertical de la integridad (p. ej.: Abundancia Media de Especies) puede ser valiosa para producir evaluaciones de alto nivel o primera categoría del riesgo de impacto, pero no proporcionan suficiente precisión o guía para las empresas, los reguladores o los asesores de terceros. Las nuevas medidas basadas en evaluaciones verticales (p. ej.: la medida de Abatimiento y Restauración de Amenazas de Especies) pueden acomodar la variación espacial de la biodiversidad y proporcionar una guía más específica para las acciones necesarias para evitar, reducir, remediar y compensar los impactos e identificar las oportunidades positivas.

Correction: Batch-produced, GIS-informed range maps for birds based on provenanced, crowd-sourced data inform conservation assessments.

[This corrects the article DOI: 10.1371/journal.pone.0259299.].

A standard approach for including climate change responses in IUCN Red List assessments.

The International Union for Conservation of Nature (IUCN) Red List is a central tool for extinction risk monitoring and influences global biodiversity policy and action. But, to be effective, it is crucial that it consistently accounts for each driver of extinction. Climate change is rapidly becoming a key extinction driver, but consideration of climate change information remains challenging for the IUCN. Several methods can be used to predict species' future decline, but they often fail to provide estimates of the symptoms of endangerment used by IUCN. We devised a standardized method to measure climate change impact in terms of change in habitat quality to inform criterion A3 on future population reduction. Using terrestrial nonvolant tetrapods as a case study, we measured this impact as the difference between the current and the future species climatic niche, defined based on current and future bioclimatic variables under alternative model algorithms, dispersal scenarios, emission scenarios, and climate models. Our models identified 171 species (13% out of those analyzed) for which their current red-list category could worsen under criterion A3 if they cannot disperse beyond their current range in the future. Categories for 14 species (1.5%) could worsen if maximum dispersal is possible. Although ours is a simulation exercise and not a formal red-list assessment, our results suggest that considering climate change impacts may reduce misclassification and strengthen consistency and comprehensiveness of IUCN Red List assessments.

Una estrategia estándar para incluir las respuestas al cambio climático en las evaluaciones de la Lista Roja de la UICN Resumen La Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN) es una herramienta central para el monitoreo del riesgo de extinción e influye sobre las acciones y políticas para la biodiversidad. Para que esta herramienta sea efectiva, es crucial que tenga en cuenta de manera regular cada factor de extinción. El cambio climático se está convirtiendo rápidamente en un factor de extinción importante, pero considerar información sobre este factor todavía es un reto para la UICN. Se pueden usar varios métodos para predecir la declinación de una especie en el futuro, pero generalmente fallan en proporcionar estimaciones de los síntomas del peligro usados por la UICN. Diseñamos un método estandarizado para medir el impacto del cambio climático en términos del cambio en la calidad del hábitat para informar el criterio A3 sobre la reducción futura de las poblaciones. Usamos a los tetrápodos terrestres no voladores como estudio de caso para medir este impacto como la diferencia entre el nicho climático actual y futuro de las especies, definido con base en las variables bioclimáticas actuales y futuras con algoritmos de modelos alternativos, escenarios de dispersión y emisión y modelos climáticos. Nuestros modelos identificaron 171 especies (13% de las especies analizadas) para las que su categoría actual en la lista roja podría empeorar bajo el criterio A3 si no logran dispersarse más allá de su distribución actual en el futuro. Las categorías para 14 especies (1.5%) podrían empeorar si es posible la dispersión máxima. Aunque realizamos una simulación y no una evaluación formal para listas rojas, nuestros resultados sugieren que considerar los impactos del cambio climático podría reducir la clasificación incorrecta y fortalecer la coherencia y exhaustividad de las evaluaciones de la Lista Roja de la UICN.

Deep phenotyping of the lipidomic response in COVID-19 and non-COVID-19 sepsis.

BACKGROUND: Lipids may influence cellular penetrance by viral pathogens and the immune response that they evoke. We deeply phenotyped the lipidomic response to SARs-CoV-2 and compared that with infection with other pathogens in patients admitted with acute respiratory distress syndrome to an intensive care unit (ICU). METHODS: Mass spectrometry was used to characterise lipids and relate them to proteins, peripheral cell immunotypes and disease severity. RESULTS: Circulating phospholipases (sPLA2, cPLA2 (PLA2G4A) and PLA2G2D) were elevated on admission in all ICU groups. Cyclooxygenase, lipoxygenase and epoxygenase products of arachidonic acid (AA) were elevated in all ICU groups compared with controls. sPLA2 predicted severity in COVID-19 and correlated with TxA2, LTE4 and the isoprostane, iPF2α-III, while PLA2G2D correlated with LTE4. The elevation in PGD2, like PGI2 and 12-HETE, exhibited relative specificity for COVID-19 and correlated with sPLA2 and the interleukin-13 receptor to drive lymphopenia, a marker of disease severity. Pro-inflammatory eicosanoids remained correlated with severity in COVID-19 28 days after admission. Amongst non-COVID ICU patients, elevations in 5- and 15-HETE and 9- and 13-HODE reflected viral rather than bacterial disease. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflected disease severity in COVID-19. In healthy marines, these lipids rose with seroconversion. Eicosanoids linked variably to the peripheral cellular immune response. PGE2, TxA2 and LTE4 correlated with T cell activation, as did PGD2 with non-B non-T cell activation. In COVID-19, LPS stimulated peripheral blood mononuclear cell PGF2α correlated with memory T cells, dendritic and NK cells while LA and DiHOMEs correlated with exhausted T cells. Three high abundance lipids - ChoE 18:3, LPC-O-16:0 and PC-O-30:0 - were altered specifically in COVID. LPC-O-16:0 was strongly correlated with T helper follicular cell activation and all three negatively correlated with multi-omic inflammatory pathways and disease severity. CONCLUSIONS: A broad based lipidomic storm is a predictor of poor prognosis in ARDS. Alterations in sPLA2, PGD2 and 12-HETE and the high abundance lipids, ChoE 18:3, LPC-O-16:0 and PC-O-30:0 exhibit relative specificity for COVID-19 amongst such patients and correlate with the inflammatory response to link to disease severity.

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.

Deep Phenotyping of the Lipidomic Response in COVID and non-COVID Sepsis.

Lipids may influence cellular penetrance by pathogens and the immune response that they evoke. Here we find a broad based lipidomic storm driven predominantly by secretory (s) phospholipase A 2 (sPLA 2 ) dependent eicosanoid production occurs in patients with sepsis of viral and bacterial origin and relates to disease severity in COVID-19. Elevations in the cyclooxygenase (COX) products of arachidonic acid (AA), PGD 2 and PGI 2 , and the AA lipoxygenase (LOX) product, 12-HETE, and a reduction in the high abundance lipids, ChoE 18:3, LPC-O-16:0 and PC-O-30:0 exhibit relative specificity for COVID-19 amongst such patients, correlate with the inflammatory response and link to disease severity. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflect disease severity in COVID-19. AA and LA metabolites and LPC-O-16:0 linked variably to the immune response. These studies yield prognostic biomarkers and therapeutic targets for patients with sepsis, including COVID-19. An interactive purpose built interactive network analysis tool was developed, allowing the community to interrogate connections across these multiomic data and generate novel hypotheses.

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.

Prognostic utility of rhythmic components in 24-hour ambulatory blood pressure monitoring for the risk stratification of chronic kidney disease patients with cardiovascular co-morbidity.

Background: Chronic kidney disease (CKD) represents a significant global burden. Hypertension is a modifiable risk factor for rapid progression of CKD. Methods: We extend the risk stratification by introducing the non-parametric determination of rhythmic components in 24-hour profiles of ambulatory blood pressure monitoring (ABPM) in the African American Study for Kidney Disease and Hypertension (AASK) cohort and the Chronic Renal Insufficiency Cohort (CRIC) using Cox proportional hazards models. Results: We find that rhythmic profiling of BP through JTK_Cycle analysis identifies subgroups of CRIC participants at advanced risk of cardiovascular death. CRIC participants with a history of cardiovascular disease (CVD) and absent cyclic components in their BP profile had at any time a 3.4-times higher risk of cardiovascular death than CVD patients with cyclic components present in their BP profile (HR: 3.38, 95% CI: 1.45-7.88, p=0.005). This substantially increased risk was independent of whether ABPM followed a dipping or non-dipping pattern whereby non-dipping or reverse dipping were not significantly associated with cardiovascular death in patients with prior CVD (p>0.1). In the AASK cohort, unadjusted models demonstrate a higher risk in reaching end stage renal disease among participants without rhythmic ABPM components (HR:1.80, 95% CI: 1.10-2.96); however, full adjustment abolished this association. Conclusions: This study proposes rhythmic blood pressure components as a novel biomarker to unmask excess risk among CKD patients with prior cardiovascular disease.