Author Correction: Approaches and advances in the genetic causes of autoimmune disease and their implications.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher Correction: Approaches and advances in the genetic causes of autoimmune disease and their implications.

In the version of this article initially published, the bibliographic information for reference 2 was incorrect in the reference list, and reference 2 was cited incorrectly at the end of the second sentence in the second paragraph ("...were identified2."). The correct reference 2 is as follows: "Kong, A. et al. The nature of nurture: Effects of parental genotypes. Science 359, 424-428 (2018)." The reference that should be cited at the end of the aforementioned sentence, which should be numbered '5' ("...were identified5."), is as follows: "Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376-381 (2014)." All subsequent references (5-161) should be renumbered accordingly (6-162) in the list and text. Also, several of the gene symbols in Table 2 were formatted incorrectly (without commas); the correct gene symbols are as follows: column 3 row 13, RBM17, IL2RA; column 3 row 30, DEXI, CLEC16A; column 3 row 39, UBASH3A, ICOSLG; column 4 row 15, PTEN, KLLN; column 4 row 21, CLEC7A, CLEC9A; and column 5 rows 7-9, AL391559.1, ENSG00000238747, RP11-63K6.7, RP3-512E2.2. The errors have been corrected in the HTML and PDF version of the article.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

Approaches and advances in the genetic causes of autoimmune disease and their implications.

Genome-wide association studies are transformative in revealing the polygenetic basis of common diseases, with autoimmune diseases leading the charge. Although the field is just over 10 years old, advances in understanding the underlying mechanistic pathways of these conditions, which result from a dense multifactorial blend of genetic, developmental and environmental factors, have already been informative, including insights into therapeutic possibilities. Nevertheless, the challenge of identifying the actual causal genes and pathways and their biological effects on altering disease risk remains for many identified susceptibility regions. It is this fundamental knowledge that will underpin the revolution in patient stratification, the discovery of therapeutic targets and clinical trial design in the next 20 years. Here we outline recent advances in analytical and phenotyping approaches and the emergence of large cohorts with standardized gene-expression data and other phenotypic data that are fueling a bounty of discovery and improved understanding of human physiology.

Tracking chromatin state changes using nanoscale photo-proximity labelling.

Interactions between biomolecules underlie all cellular processes and ultimately control cell fate. Perturbation of native interactions through mutation, changes in expression levels or external stimuli leads to altered cellular physiology and can result in either disease or therapeutic effects1,2. Mapping these interactions and determining how they respond to stimulus is the genesis of many drug development efforts, leading to new therapeutic targets and improvements in human health1. However, in the complex environment of the nucleus, it is challenging to determine protein-protein interactions owing to low abundance, transient or multivalent binding and a lack of technologies that are able to interrogate these interactions without disrupting the protein-binding surface under study3. Here, we describe a method for the traceless incorporation of iridium-photosensitizers into the nuclear micro-environment using engineered split inteins. These Ir-catalysts can activate diazirine warheads through Dexter energy transfer to form reactive carbenes within an approximately 10 nm radius, cross-linking with proteins in the immediate micro-environment (a process termed µMap) for analysis using quantitative chemoproteomics4. We show that this nanoscale proximity-labelling method can reveal the critical changes in interactomes in the presence of cancer-associated mutations, as well as treatment with small-molecule inhibitors. µMap improves our fundamental understanding of nuclear protein-protein interactions and, in doing so, is expected to have a significant effect on the field of epigenetic drug discovery in both academia and industry.

Projected land ice contributions to twenty-first-century sea level rise.

The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2-8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.

Whole-genome sequencing of a sporadic primary immunodeficiency cohort.

Primary immunodeficiency (PID) is characterized by recurrent and often life-threatening infections, autoimmunity and cancer, and it poses major diagnostic and therapeutic challenges. Although the most severe forms of PID are identified in early childhood, most patients present in adulthood, typically with no apparent family history and a variable clinical phenotype of widespread immune dysregulation: about 25% of patients have autoimmune disease, allergy is prevalent and up to 10% develop lymphoid malignancies1-3. Consequently, in sporadic (or non-familial) PID genetic diagnosis is difficult and the role of genetics is not well defined. Here we address these challenges by performing whole-genome sequencing in a large PID cohort of 1,318 participants. An analysis of the coding regions of the genome in 886 index cases of PID found that disease-causing mutations in known genes that are implicated in monogenic PID occurred in 10.3% of these patients, and a Bayesian approach (BeviMed4) identified multiple new candidate PID-associated genes, including IVNS1ABP. We also examined the noncoding genome, and found deletions in regulatory regions that contribute to disease causation. In addition, we used a genome-wide association study to identify loci that are associated with PID, and found evidence for the colocalization of-and interplay between-novel high-penetrance monogenic variants and common variants (at the PTPN2 and SOCS1 loci). This begins to explain the contribution of common variants to the variable penetrance and phenotypic complexity that are observed in PID. Thus, using a cohort-based whole-genome-sequencing approach in the diagnosis of PID can increase diagnostic yield and further our understanding of the key pathways that influence immune responsiveness in humans.

Publisher Correction: Whole-genome sequencing of a sporadic primary immunodeficiency cohort.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Functional overlap and regulatory links shape genetic interactions between signaling pathways.

To understand relationships between phosphorylation-based signaling pathways, we analyzed 150 deletion mutants of protein kinases and phosphatases in S. cerevisiae using DNA microarrays. Downstream changes in gene expression were treated as a phenotypic readout. Double mutants with synthetic genetic interactions were included to investigate genetic buffering relationships such as redundancy. Three types of genetic buffering relationships are identified: mixed epistasis, complete redundancy, and quantitative redundancy. In mixed epistasis, the most common buffering relationship, different gene sets respond in different epistatic ways. Mixed epistasis arises from pairs of regulators that have only partial overlap in function and that are coupled by additional regulatory links such as repression of one by the other. Such regulatory modules confer the ability to control different combinations of processes depending on condition or context. These properties likely contribute to the evolutionary maintenance of paralogs and indicate a way in which signaling pathways connect for multiprocess control.

Revisiting Antarctic ice loss due to marine ice-cliff instability.

Predictions for sea-level rise this century due to melt from Antarctica range from zero to more than one metre. The highest predictions are driven by the controversial marine ice-cliff instability (MICI) hypothesis, which assumes that coastal ice cliffs can rapidly collapse after ice shelves disintegrate, as a result of surface and sub-shelf melting caused by global warming. But MICI has not been observed in the modern era and it remains unclear whether it is required to reproduce sea-level variations in the geological past. Here we quantify ice-sheet modelling uncertainties for the original MICI study and show that the probability distributions are skewed towards lower values (under very high greenhouse gas concentrations, the most likely value is 45 centimetres). However, MICI is not required to reproduce sea-level changes due to Antarctic ice loss in the mid-Pliocene epoch, the last interglacial period or 1992-2017; without it we find that the projections agree with previous studies (all 95th percentiles are less than 43 centimetres). We conclude that previous interpretations of these MICI projections over-estimate sea-level rise this century; because the MICI hypothesis is not well constrained, confidence in projections with MICI would require a greater range of observationally constrained models of ice-shelf vulnerability and ice-cliff collapse.

Online and Offline Prioritization of Chemicals of Interest in Suspect Screening and Non-targeted Screening with High-Resolution Mass Spectrometry.

Recent advances in high-resolution mass spectrometry (HRMS) have enabled the detection of thousands of chemicals from a single sample, while computational methods have improved the identification and quantification of these chemicals in the absence of reference standards typically required in targeted analysis. However, to determine the presence of chemicals of interest that may pose an overall impact on ecological and human health, prioritization strategies must be used to effectively and efficiently highlight chemicals for further investigation. Prioritization can be based on a chemical's physicochemical properties, structure, exposure, and toxicity, in addition to its regulatory status. This Perspective aims to provide a framework for the strategies used for chemical prioritization that can be implemented to facilitate high-quality research and communication of results. These strategies are categorized as either "online" or "offline" prioritization techniques. Online prioritization techniques trigger the isolation and fragmentation of ions from the low-energy mass spectra in real time, with user-defined parameters. Offline prioritization techniques, in contrast, highlight chemicals of interest after the data has been acquired; detected features can be filtered and ranked based on the relative abundance or the predicted structure, toxicity, and concentration imputed from the tandem mass spectrum (MS2). Here we provide an overview of these prioritization techniques and how they have been successfully implemented and reported in the literature to find chemicals of elevated risk to human and ecological environments. A complete list of software and tools is available from https://nontargetedanalysis.org/.

Combining Nontargeted Analysis with Computer-Based Hazard Comparison Approaches to Support Prioritization of Unregulated Organic Contaminants in Biosolids.

Biosolids are a byproduct of wastewater treatment that can be beneficially applied to agricultural land as a fertilizer. While U.S. regulations limit metals and pathogens in biosolids intended for land applications, no organic contaminants are currently regulated. Novel techniques can aid in detection, evaluation, and prioritization of biosolid-associated organic contaminants (BOCs). For example, nontargeted analysis (NTA) can detect a broad range of chemicals, producing data sets representing thousands of measured analytes that can be combined with computational toxicological tools to support human and ecological hazard assessment and prioritization. We combined NTA with a computer-based tool from the U.S. EPA, the Cheminformatics Hazard Comparison Module (HCM), to identify and prioritize BOCs present in U.S. and Canadian biosolids (n = 16). Four-hundred fifty-one features were detected in at least 80% of samples, with identities of 92 compounds confirmed or assigned probable structures. These compounds were primarily categorized as endogenous compounds, pharmaceuticals, industrial chemicals, and fragrances. Examples of top prioritized compounds were p-cresol and chlorophene, based on human health end points, and fludioxonil and triclocarban, based on ecological health end points. Combining NTA results with hazard comparison data allowed us to prioritize compounds to be included in future studies of the environmental fate and transport of BOCs.

(Non)targeted Chemical Analysis and Risk Assessment of Organic Contaminants in Darkibor Kale Grown at Rural and Urban Farms.

This study investigated the presence and human hazards associated with pesticides and other anthropogenic chemicals identified in kale grown in urban and rural environments. Pesticides and related compounds (i.e., surfactants and metabolites) in kale samples were evaluated using a nontargeted data acquisition for targeted analysis method which utilized a pesticide mixture containing >1,000 compounds for suspect screening and quantification. We modeled population-level exposures and assessed noncancer hazards to DEET, piperonyl butoxide, prometon, secbumeton, terbumeton, and spinosyn A using nationally representative estimates of kale consumption across life stages in the US. Our findings indicate even sensitive populations (e.g., pregnant women and children) are not likely to experience hazards from these select compounds were they to consume kale from this study. However, a strictly nontargeted chemical analytical approach identified a total of 1,822 features across all samples, and principal component analysis revealed that the kale chemical composition may have been impacted by agricultural growing practices and environmental factors. Confidence level 2 compounds that were ≥5 times more abundant in the urban samples than in rural samples (p < 0.05) included chemicals categorized as "flavoring and nutrients" and "surfactants" in the EPA's Chemicals and Products Database. Using the US-EPA's Cheminformatics Hazard Module, we identified that many of the nontarget compounds have predicted toxicity scores of "very high" for several end points related to human health. These aspects would have been overlooked using traditional targeted analysis methods, although more information is needed to ascertain whether the compounds identified through nontargeted analysis are of environmental or human health concern. As such, our approach enabled the identification of potentially hazardous compounds that, based on their hazard assessment score, merit follow-up investigations.

Improving predictions of compound amenability for liquid chromatography-mass spectrometry to enhance non-targeted analysis.

Mass-spectrometry-based non-targeted analysis (NTA), in which mass spectrometric signals are assigned chemical identities based on a systematic collation of evidence, is a growing area of interest for toxicological risk assessment. Successful NTA results in better identification of potentially hazardous pollutants within the environment, facilitating the development of targeted analytical strategies to best characterize risks to human and ecological health. A supporting component of the NTA process involves assessing whether suspected chemicals are amenable to the mass spectrometric method, which is necessary in order to assign an observed signal to the chemical structure. Prior work from this group involved the development of a random forest model for predicting the amenability of 5517 unique chemical structures to liquid chromatography-mass spectrometry (LC-MS). This work improves the interpretability of the group's prior model of the same endpoint, as well as integrating 1348 more data points across negative and positive ionization modes. We enhance interpretability by feature engineering, a machine learning practice that reduces the input dimensionality while attempting to preserve performance statistics. We emphasize the importance of interpretable machine learning models within the context of building confidence in NTA identification. The novel data were curated by the labeling of compounds as amenable or unamenable by expert curators, resulting in an enhanced set of chemical compounds to expand the applicability domain of the prior model. The balanced accuracy benchmark of the newly developed model is comparable to performance previously reported (mean CV BA is 0.84 vs. 0.82 in positive mode, and 0.85 vs. 0.82 in negative mode), while on a novel external set, derived from this work's data, the Matthews correlation coefficients (MCC) for the novel models are 0.66 and 0.68 for positive and negative mode, respectively. Our group's prior published models scored MCC of 0.55 and 0.54 on the same external sets. This demonstrates appreciable improvement over the chemical space captured by the expanded dataset. This work forms part of our ongoing efforts to develop models with higher interpretability and higher performance to support NTA efforts.

ASPiRATION: Australian observational cohort study of comprehensive genomic profiling in metastatic lung cancer tissue.

ASPiRATION is a national prospective observational cohort study assessing the feasibility, clinical and economic value of up-front tissue-based comprehensive genomic profiling (CGP) to identify actionable genomic alterations in participants with newly diagnosed metastatic non-squamous non-small-cell lung cancer in Australia. This study will enrol 1000 participants with tumor available for CGP and standard of care molecular testing (EGFR/ALK/ROS1). Participants with actionable variants may receive novel targeted treatments through ASPiRATION-specific substudies, other trials/programs. Clinical outcome data will be collected for a minimum of 2 years. Study outcomes are descriptive, including the ability of CGP to identify additional actionable variants, leading to personalized treatment recommendations, and will describe the feasibility, efficiency, cost and utility of implementation of CGP nationally.

Lung cancer is the most common cause of cancer death in Australia and worldwide. This disease often happens due to alterations in specific genes that allow cancer cells to develop and spread. Scientists have designed targeted drugs that are better at attacking cancer cells that have specific 'actionable' gene alterations and have less effect on other cells in the body. The result is often more benefit from treatment and fewer side effects than other standard treatments (chemotherapy or immunotherapy). The targeted drugs are well established as the best initial treatments for some gene alterations, but more research is needed to know if this is true for some of the less common or recently identified gene alterations, and where the targeted drugs are very new. Comprehensive genomic profiling is a new way of testing lung cancer cells for all the gene alterations (the well-known ones as well as the rare ones) in a single test. It is expected that this test will find many more of these gene alterations, which will allow more people to have safer and more effective targeted treatments leading to potentially better outcomes, and will allow some people to join clinical trials testing newer targeted treatments. The ASPiRATION study will help work out whether comprehensive genomic profiling is better than the current way of testing for gene alterations in Australia, and if it is feasible to use in all people diagnosed with advanced lung cancer in Australia. Clinical Trial Registration: ACTRN12621000221853 (ANZCTR).

The many possible climates from the Paris Agreement's aim of 1.5 °C warming.

The United Nations' Paris Agreement includes the aim of pursuing efforts to limit global warming to only 1.5 °C above pre-industrial levels. However, it is not clear what the resulting climate would look like across the globe and over time. Here we show that trajectories towards a '1.5 °C warmer world' may result in vastly different outcomes at regional scales, owing to variations in the pace and location of climate change and their interactions with society's mitigation, adaptation and vulnerabilities to climate change. Pursuing policies that are considered to be consistent with the 1.5 °C aim will not completely remove the risk of global temperatures being much higher or of some regional extremes reaching dangerous levels for ecosystems and societies over the coming decades.

A new method for regionalization of the vertebral column in salmonids based on radiographic hallmarks.

Current procedures to establish vertebral column regionalization (e.g., histology) in fish are time consuming and difficult to apply. The aim of this study was to develop a more rapid and accurate radiology-based method for Atlantic salmon (Salmo salar). A detailed analysis of 90 animals (4 kg) led to the establishment of region-specific radiographic hallmarks. To elucidate its transferability to other salmonid species, radiography was carried out in brown trout (Salmo trutta), Arctic char (Salvelinus alpinus), rainbow trout (Oncorhynchus mykiss), pink salmon (Oncorhynchus gorbuscha), and Chinook salmon (Oncorhynchus tshawytscha). This method was also evaluated for whole ungutted fish. The vertebral column of Atlantic salmon can be subdivided into five regions (R1-R5) based on anatomy: postcranial (R1, V1, and V2), abdominal (R2, V3-V26), transitional (R3, V27-V36), caudal (R4, V37-V53), and ural (R5, V54-V59). The following specific radiographic hallmarks allow the identification of regions: (i) lack of ribs in R1, (ii) modified parapophysis of the first vertebra of R3, (iii) prominent hemal spine of the first vertebra of R4, and (iv) the separated hemal spine of the most cranial pre-ural vertebra of R5. These hallmarks were all transferable to the other salmonid species assessed. The results include a further description of various region-specific characteristics in Atlantic salmon. The method was found applicable for sedated/whole ungutted fish, verifying it as quick and easy compared to other regionalization methods. The regions defined by radiology in this study agree with the vertebral column regions recently defined for Chinook salmon (O. tshawytscha). Thus, and considering the results of this study on various salmonid species, the currently developed regionalization protocol can be generally used for salmonids.

Does the small conductance Ca2+-activated K+ current ISK flow under physiological conditions in rabbit and human atrial isolated cardiomyocytes?

BACKGROUND: The small conductance Ca2+-activated K+ current (ISK) is a potential therapeutic target for treating atrial fibrillation. AIM: To clarify, in rabbit and human atrial cardiomyocytes, the intracellular [Ca2+]-sensitivity of ISK, and its contribution to action potential (AP) repolarisation, under physiological conditions. METHODS: Whole-cell-patch clamp, fluorescence microscopy: to record ion currents, APs and [Ca2+]i; 35-37°C. RESULTS: In rabbit atrial myocytes, 0.5 mM Ba2+ (positive control) significantly decreased whole-cell current, from -12.8 to -4.9 pA/pF (P < 0.05, n = 17 cells, 8 rabbits). By contrast, the ISK blocker apamin (100 nM) had no effect on whole-cell current, at any set [Ca2+]i (∼100-450 nM). The ISK blocker ICAGEN (1 µM: ≥2 x IC50) also had no effect on current over this [Ca2+]i range. In human atrial myocytes, neither 1 µM ICAGEN (at [Ca2+]i âˆ¼ 100-450 nM), nor 100 nM apamin ([Ca2+]i âˆ¼ 250 nM) affected whole-cell current (5-10 cells, 3-5 patients/group). APs were significantly prolonged (at APD30 and APD70) by 2 mM 4-aminopyridine (positive control) in rabbit atrial myocytes, but 1 µM ICAGEN had no effect on APDs, versus either pre-ICAGEN or time-matched controls. High concentration (10 µM) ICAGEN (potentially ISK-non-selective) moderately increased APD70 and APD90, by 5 and 26 ms, respectively. In human atrial myocytes, 1 µM ICAGEN had no effect on APD30-90, whether stimulated at 1, 2 or 3 Hz (6-9 cells, 2-4 patients/rate). CONCLUSION: ISK does not flow in human or rabbit atrial cardiomyocytes with [Ca2+]i set within the global average diastolic-systolic range, nor during APs stimulated at physiological or supra-physiological (≤3 Hz) rates.

Lysosomal Targeting of ß-Cyclodextrin.

ß-Cyclodextrin (ß-CD) and derivatives are approved therapeutics in >30 clinical settings. ß-CDs have also shown promise as therapeutics for treatment of some lysosomal storage disorders, such as Niemann-Pick disease type C, and other disease states which involve metabolite accumulation in the lysosome. In these cases, ß-CD activity relies on transport to the lysosome, wherein it can bind hydrophobic substrate and effect extraction. The post-translational attachment of N-glycans terminated in mannose-6-phosphate (M6P) residues is the predominant method by which lysosomal enzymes are targeted to the lysosome. In this work we covalently attach a synthetic biantennary bis-M6P-terminated N-glycan to ß-CD and study the effect of the added glycans in a mammalian cell line. The formation of a host guest complex with a Cy5 fluorophore allows study of both cellular internalisation and transport to the lysosome by fluorescence microscopy. Results indicate that the rates of both internalisation and lysosomal transport are increased by the attachment of M6P-glycans to ß-CD, indicating that M6P-glycan conjugation may improve the therapeutic effectiveness of ß-CD for the treatment of disorders involving hydrophobic metabolite accumulation in the lysosome.

Transparency in Modeling through Careful Application of OECD's QSAR/QSPR Principles via a Curated Water Solubility Data Set.

The need for careful assembly, training, and validation of quantitative structure-activity/property models (QSAR/QSPR) is more significant than ever as data sets become larger and sophisticated machine learning tools become increasingly ubiquitous and accessible to the scientific community. Regulatory agencies such as the United States Environmental Protection Agency must carefully scrutinize each aspect of a resulting QSAR/QSPR model to determine its potential use in environmental exposure and hazard assessment. Herein, we revisit the goals of the Organisation for Economic Cooperation and Development (OECD) in our application and discuss the validation principles for structure-activity models. We apply these principles to a model for predicting water solubility of organic compounds derived using random forest regression, a common machine learning approach in the QSA/PR literature. Using public sources, we carefully assembled and curated a data set consisting of 10,200 unique chemical structures with associated water solubility measurements. This data set was then used as a focal narrative to methodically consider the OECD's QSA/PR principles and how they can be applied to random forests. Despite some expert, mechanistically informed supervision of descriptor selection to enhance model interpretability, we achieved a model of water solubility with comparable performance to previously published models (5-fold cross validated performance 0.81 R2 and 0.98 RMSE). We hope this work will catalyze a necessary conversation around the importance of cautiously modernizing and explicitly leveraging OECD principles while pursuing state-of-the-art machine learning approaches to derive QSA/PR models suitable for regulatory consideration.