Childhood cancer data initiative: Status report.

In March 2023, over 800 researchers, clinicians, patients, survivors, and advocates from the pediatric oncology community met to discuss the progress of the National Cancer Institute's Childhood Cancer Data Initiative. We present here the status of the initiative's efforts in building its data ecosystem and updates on key programs, especially the Molecular Characterization Initiative and the planned Coordinated National Initiative for Rare Cancers in Children and Young Adults. These activities aim to improve access to childhood cancer data, foster collaborations, facilitate integrative data analysis, and expand access to molecular characterization, ultimately leading to the development of innovative therapeutic approaches.

New Drinking Water Genome Catalog Identifies a Globally Distributed Bacterial Genus Adapted to Disinfected Drinking Water Systems.

Genome-resolved insights into the structure and function of the drinking water microbiome can advance the effective management of drinking water quality. To enable this, we constructed and curated thousands of metagenome-assembled and isolate genomes from drinking water distribution systems globally to develop a Drinking Water Genome Catalog (DWGC). The current DWGC disproportionately represents disinfected drinking water systems due to a paucity of metagenomes from nondisinfected systems. Using the DWGC, we identify core genera of the drinking water microbiome including a genus (UBA4765) within the order Rhizobiales that is frequently detected and highly abundant in disinfected drinking water systems. We demonstrate that this genus has been widely detected but incorrectly classified in previous amplicon sequencing-based investigations of the drinking water microbiome. Further, we show that a single genome variant (genomovar) within this genus is detected in 75% of drinking water systems included in this study. We propose a name for this uncultured bacterium as "Raskinella chloraquaticus" and describe the genus as "Raskinella" (endorsed by SeqCode). Metabolic annotation and modeling-based predictions indicate that this bacterium is capable of necrotrophic growth, is able to metabolize halogenated compounds, proliferates in a biofilm-based environment, and shows clear indications of disinfection-mediated selection.

The Allele Catalog Tool: a web-based interactive tool for allele discovery and analysis.

BACKGROUND: The advancement of sequencing technologies today has made a plethora of whole-genome re-sequenced (WGRS) data publicly available. However, research utilizing the WGRS data without further configuration is nearly impossible. To solve this problem, our research group has developed an interactive Allele Catalog Tool to enable researchers to explore the coding region allelic variation present in over 1,000 re-sequenced accessions each for soybean, Arabidopsis, and maize. RESULTS: The Allele Catalog Tool was designed originally with soybean genomic data and resources. The Allele Catalog datasets were generated using our variant calling pipeline (SnakyVC) and the Allele Catalog pipeline (AlleleCatalog). The variant calling pipeline is developed to parallelly process raw sequencing reads to generate the Variant Call Format (VCF) files, and the Allele Catalog pipeline takes VCF files to perform imputations, functional effect predictions, and assemble alleles for each gene to generate curated Allele Catalog datasets. Both pipelines were utilized to generate the data panels (VCF files and Allele Catalog files) in which the accessions of the WGRS datasets were collected from various sources, currently representing over 1,000 diverse accessions for soybean, Arabidopsis, and maize individually. The main features of the Allele Catalog Tool include data query, visualization of results, categorical filtering, and download functions. Queries are performed from user input, and results are a tabular format of summary results by categorical description and genotype results of the alleles for each gene. The categorical information is specific to each species; additionally, available detailed meta-information is provided in modal popups. The genotypic information contains the variant positions, reference or alternate genotypes, the functional effect classes, and the amino-acid changes of each accession. Besides that, the results can also be downloaded for other research purposes. CONCLUSIONS: The Allele Catalog Tool is a web-based tool that currently supports three species: soybean, Arabidopsis, and maize. The Soybean Allele Catalog Tool is hosted on the SoyKB website ( https://soykb.org/SoybeanAlleleCatalogTool/ ), while the Allele Catalog Tool for Arabidopsis and maize is hosted on the KBCommons website ( https://kbcommons.org/system/tools/AlleleCatalogTool/Zmays and https://kbcommons.org/system/tools/AlleleCatalogTool/Athaliana ). Researchers can use this tool to connect variant alleles of genes with meta-information of species.

GenoPheno: cataloging large-scale phenotypic and next-generation sequencing data within human datasets.

Precision medicine promises to revolutionize treatment, shifting therapeutic approaches from the classical one-size-fits-all to those more tailored to the patient's individual genomic profile, lifestyle and environmental exposures. Yet, to advance precision medicine's main objective-ensuring the optimum diagnosis, treatment and prognosis for each individual-investigators need access to large-scale clinical and genomic data repositories. Despite the vast proliferation of these datasets, locating and obtaining access to many remains a challenge. We sought to provide an overview of available patient-level datasets that contain both genotypic data, obtained by next-generation sequencing, and phenotypic data-and to create a dynamic, online catalog for consultation, contribution and revision by the research community. Datasets included in this review conform to six specific inclusion parameters that are: (i) contain data from more than 500 human subjects; (ii) contain both genotypic and phenotypic data from the same subjects; (iii) include whole genome sequencing or whole exome sequencing data; (iv) include at least 100 recorded phenotypic variables per subject; (v) accessible through a website or collaboration with investigators and (vi) make access information available in English. Using these criteria, we identified 30 datasets, reviewed them and provided results in the release version of a catalog, which is publicly available through a dynamic Web application and on GitHub. Users can review as well as contribute new datasets for inclusion (Web: https://avillachlab.shinyapps.io/genophenocatalog/; GitHub: https://github.com/hms-dbmi/GenoPheno-CatalogShiny).

Three alginate lyases provide a new gut Bacteroides ovatus isolate with the ability to grow on alginate.

Humans consume alginate in the form of seaweed, food hydrocolloids, and encapsulations, making the digestion of this mannuronic acid (M) and guluronic acid (G) polymer of key interest for human health. To increase knowledge on alginate degradation in the gut, a gene catalog from human feces was mined for potential alginate lyases (ALs). The predicted ALs were present in nine species of the Bacteroidetes phylum, of which two required supplementation of an endo-acting AL, expected to mimic cross-feeding in the gut. However, only a new isolate grew on alginate. Whole-genome sequencing of this alginate-utilizing isolate suggested that it is a new Bacteroides ovatus strain harboring a polysaccharide utilization locus (PUL) containing three ALs of families: PL6, PL17, and PL38. The BoPL6 degraded polyG to oligosaccharides of DP 1-3, and BoPL17 released 4,5-unsaturated monouronate from polyM. BoPL38 degraded both alginates, polyM, polyG, and polyMG, in endo-mode; hence, it was assumed to deliver oligosaccharide substrates for BoPL6 and BoPL17, corresponding well with synergistic action on alginate. BoPL17 and BoPL38 crystal structures, determined at 1.61 and 2.11 Å, respectively, showed (α/α)6-barrel + anti-parallel ß-sheet and (α/α)7-barrel folds, distinctive for these PL families. BoPL17 had a more open active site than the two homologous structures. BoPL38 was very similar to the structure of an uncharacterized PL38, albeit with a different triad of residues possibly interacting with substrate in the presumed active site tunnel. Altogether, the study provides unique functional and structural insights into alginate-degrading lyases of a PUL in a human gut bacterium.IMPORTANCEHuman ingestion of sustainable biopolymers calls for insight into their utilization in our gut. Seaweed is one such resource with alginate, a major cell wall component, used as a food hydrocolloid and for encapsulation of pharmaceuticals and probiotics. Knowledge is sparse on the molecular basis for alginate utilization in the gut. We identified a new Bacteroides ovatus strain from human feces that grew on alginate and encoded three alginate lyases in a gene cluster. BoPL6 and BoPL17 show complementary specificity toward guluronate (G) and mannuronate (M) residues, releasing unsaturated oligosaccharides and monouronic acids. BoPL38 produces oligosaccharides degraded by BoPL6 and BoPL17 from both alginates, G-, M-, and MG-substrates. Enzymatic and structural characterization discloses the mode of action and synergistic degradation of alginate by these alginate lyases. Other bacteria were cross-feeding on alginate oligosaccharides produced by an endo-acting alginate lyase. Hence, there is an interdependent community in our guts that can utilize alginate.

Time trade-off health state utility values for depression: a systematic review and meta-analysis.

PURPOSE: This study aims to systematically review the literature on health utility in depression generated by time trade-off (TTO) method and to compare health state vignettes. METHODS: Systematic literature search was conducted following PRISMA guideline in 2020 November (updated in 2022 March) in Pubmed, Web of Science, PsycInfo, and Cochrane Database of Systematic Reviews. Random effect meta-analysis was conducted to pool vignette-based utility values of mild, moderate, and severe depression and to compare the preferences of depressed and nondepressed population. RESULTS: Overall, 264 records were found, 143 screened by title and abstract after removing duplicates, 18 assessed full text, and 14 original publications included. Majority of the studies (n = 9) used conventional TTO method, and most of the studies (n = 8) applied 10-year timeframe. Eight studies evaluated self-experienced health (own-current depression). Six studies assessed vignette-based health states of remitted, mild, moderate, and severe depression, half of them applied McSad measure based health description. Altogether, 61 different utility values have been cataloged, mean utility of self-experienced depression states (n = 33) ranged between 0.89 (current-own depression) and 0.24 (worst experienced depression). Pooled utility estimates for vignette-based mild, moderate, and severe depression was 0.75, 0.66 and 0.50, respectively. Meta-regression showed that severe depression (ß = -0.16) and depressed sample populations (ß = -0.13) significantly decrease vignette-based utility scores. CONCLUSION: Our review revealed extent heterogeneity both in TTO methodology and health state vignette development. Patient's perception of depression health states was worse than healthy respondents.

Construction of the Guide Star Catalog for Double Fine Guidance Sensors Based on SSBK Clustering.

In the Chinese Survey Space Telescope (CSST), the Fine Guidance Sensor (FGS) is required to provide high-precision attitude information of the space telescope. The fine star guide catalog is an essential part of the FGS. It is not only the basis for star identification and attitude determination but also the key to determining the absolute attitude of the space telescope. However, the capacity and uniformity of the fine guide star catalog will affect the performance of the FGS. To build a guide star catalog with uniform distribution of guide stars and catalog capacity that is as small as possible, and to effectively improve the speed of star identification and the accuracy of attitude determination, the spherical spiral binary K-means clustering algorithm (SSBK) is proposed. Based on the selection criteria, firstly, the spherical spiral reference point method is used for global uniform division, and then, the K-means clustering algorithm in machine learning is introduced to divide the stars into several disjoint subsets through the use of angular distance and dichotomy so that the guide stars are uniformly distributed. We assume that the field of view (FOV) is 0.2° × 0.2°, the magnitude range is 9∼15 mag, and the threshold for the number of stars (NOS) in the FOV is 9. The simulation shows that compared with the magnitude filtering method (MFM) and the spherical spiral reference point brightness optimization algorithm (SSRP), the guide star catalog based on the SSBK algorithm has the lowest standard deviation of the NOS in the FOV, and the probability of 5∼15 stars is the highest (over 99.4%), which can ensure a higher identification probability and attitude determination accuracy.

The Politics of Sources Meets the Practices of the Librarian: An Interview with Esther Chen.

[I] want to single out one phenomenon that could be called the 'politics of sources'. It points to the extent to which the histories that both scientists and historians can write are artifacts of the available sources. The Rockefeller Foundation not only opened its archives very early on for historical work but also invested a lot in making the archives readily available for historical exploration. During the 1980s, many young historians took advantage of this opportunity. Thus, in a relatively early phase of the professional historiography of molecular biology, one could have gained the impression that the development of the new biology as a whole was a bio-politically directed enterprise of the Rockefeller Foundation sustained by the vision that social processes could ultimately be controlled by biological processes.

Estimating colocalization probability from limited summary statistics.

BACKGROUND: Colocalization is a statistical method used in genetics to determine whether the same variant is causal for multiple phenotypes, for example, complex traits and gene expression. It provides stronger mechanistic evidence than shared significance, which can be produced through separate causal variants in linkage disequilibrium. Current colocalization methods require full summary statistics for both traits, limiting their use with the majority of reported GWAS associations (e.g. GWAS Catalog). We propose a new approximation to the popular coloc method that can be applied when limited summary statistics are available. Our method (POint EstiMation of Colocalization, POEMColoc) imputes missing summary statistics for one or both traits using LD structure in a reference panel, and performs colocalization using the imputed summary statistics. RESULTS: We evaluate the performance of POEMColoc using real (UK Biobank phenotypes and GTEx eQTL) and simulated datasets. We show good correlation between posterior probabilities of colocalization computed from imputed and observed datasets and similar accuracy in simulation. We evaluate scenarios that might reduce performance and show that multiple independent causal variants in a region and imputation from a limited subset of typed variants have a larger effect while mismatched ancestry in the reference panel has a modest effect. Further, we find that POEMColoc is a better approximation of coloc when the imputed association statistics are from a well powered study (e.g., relatively larger sample size or effect size). Applying POEMColoc to estimate colocalization of GWAS Catalog entries and GTEx eQTL, we find evidence for colocalization of 150,000 trait-gene-tissue triplets. CONCLUSIONS: We find that colocalization analysis performed with full summary statistics can be closely approximated when only the summary statistics of the top SNP are available for one or both traits. When applied to the full GWAS Catalog and GTEx eQTL, we find that colocalized trait-gene pairs are enriched in tissues relevant to disease etiology and for matches to approved drug mechanisms. POEMColoc R package is available at https://github.com/AbbVie-ComputationalGenomics/POEMColoc .

Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics.

BACKGROUND: Genome-wide association studies (GWAS) have significantly contributed to the association of many clinical conditions and phenotypic characteristics with genomic variants. The majority of these genomic findings have been deposited to the GWAS catalog. So far, findings uncovering associations of single nucleotide polymorphisms (SNPs) with treatment efficacy in mood disorders are encouraging, but not adequate. METHODS: Statistical, genomic, and literature information was retrieved from EBI's GWAS catalog, while we also searched for potential clinical information/clinical guidelines in well-established pharmacogenomics databases regarding the assessed drug-SNP correlations of the present study. RESULTS: Here, we provide an overview of significant genome-wide associations of SNPs with the response to commonly prescribed antipsychotics and antidepressants. Up to date, this is the first study providing novel insight in previously reported pharmacogenomics associations for antipsychotic/antidepressant treatment. We also show that although there are published CPIC guidelines for antidepressant agents, as well as the FDA labels include genome-based drug prescription information for both antipsychotic and antidepressant treatments, there are no specific clinical guidelines for the assessed drug-SNP correlations of this study. CONCLUSIONS: Our present findings suggest that more effort should be implemented towards identifying GWA-significant antipsychotic and antidepressant pharmacogenomics correlations. Moreover, additional functional studies are required in order to characterise the potential role of the assessed SNPs as biomarkers for the response of patients to antipsychotic/antidepressant treatment.

Rare Occurrences of Non-cascading Foreshock Activity in Southern California.

Earthquakes preceding large events are commonly referred to as foreshocks. They are often considered as precursory phenomena reflecting the nucleation process of the main rupture. Such foreshock sequences may also be explained by cascades of triggered events. Recent advances in earthquake detection motivates a reevaluation of seismicity variations prior to mainshocks. Based on a highly complete earthquake catalog, previous studies suggested that mainshocks in Southern California are often preceded by anomalously elevated seismicity. In this study, we test the same catalog against the Epidemic Type Aftershock Sequence model that accounts for temporal clustering due to earthquake interactions. We find that 10/53 mainshocks are preceded by a significantly elevated seismic activity compared with our model. This shows that anomalous foreshock activity is relatively uncommon when tested against a model of earthquake interactions. Accounting for the recurrence of anomalies over time, only 3/10 mainshocks present a mainshock-specific anomaly with a high predictive power.

Global peatland initiation driven by regionally asynchronous warming.

Widespread establishment of peatlands since the Last Glacial Maximum represents the activation of a globally important carbon sink, but the drivers of peat initiation are unclear. The role of climate in peat initiation is particularly poorly understood. We used a general circulation model to simulate local changes in climate during the initiation of 1,097 peatlands around the world. We find that peat initiation in deglaciated landscapes in both hemispheres was driven primarily by warming growing seasons, likely through enhanced plant productivity, rather than by any increase in effective precipitation. In Western Siberia, which remained ice-free throughout the last glacial period, the initiation of the world's largest peatland complex was globally unique in that it was triggered by an increase in effective precipitation that inhibited soil respiration and allowed wetland plant communities to establish. Peat initiation in the tropics was only weakly related to climate change, and appears to have been driven primarily by nonclimatic mechanisms such as waterlogging due to tectonic subsidence. Our findings shed light on the genesis and Holocene climate space of one of the world's most carbon-dense ecosystem types, with implications for understanding trajectories of ecological change under changing future climates.

Breast cancer risk factors and their effects on survival: a Mendelian randomisation study.

BACKGROUND: Observational studies have investigated the association of risk factors with breast cancer prognosis. However, the results have been conflicting and it has been challenging to establish causality due to potential residual confounding. Using a Mendelian randomisation (MR) approach, we aimed to examine the potential causal association between breast cancer-specific survival and nine established risk factors for breast cancer: alcohol consumption, body mass index, height, physical activity, mammographic density, age at menarche or menopause, smoking, and type 2 diabetes mellitus (T2DM). METHODS: We conducted a two-sample MR analysis on data from the Breast Cancer Association Consortium (BCAC) and risk factor summary estimates from the GWAS Catalog. The BCAC data included 86,627 female patients of European ancestry with 7054 breast cancer-specific deaths during 15 years of follow-up. Of these, 59,378 were estrogen receptor (ER)-positive and 13,692 were ER-negative breast cancer patients. For the significant association, we used sensitivity analyses and a multivariable MR model. All risk factor associations were also examined in a model adjusted by other prognostic factors. RESULTS: Increased genetic liability to T2DM was significantly associated with worse breast cancer-specific survival (hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.03-1.17, P value [P] = 0.003). There were no significant associations after multiple testing correction for any of the risk factors in the ER-status subtypes. For the reported significant association with T2DM, the sensitivity analyses did not show evidence for violation of the MR assumptions nor that the association was due to increased BMI. The association remained significant when adjusting by other prognostic factors. CONCLUSIONS: This extensive MR analysis suggests that T2DM may be causally associated with worse breast cancer-specific survival and therefore that treating T2DM may improve prognosis.

Detection of Low RCS Supersonic Flying Targets with a High-Resolution MMW Radar.

In this study, the detection of a low radar cross-section (RCS) target moving at a very high speed using a high-resolution millimeter-wave radar is presented. This real-time detection is based on the transmission of a continuous wave and heterodyning of the received signal reflected from the moving target. This type of detection enables one to extract the object's movement characteristics, such as velocity and position, while in motion and also to extract its physical characteristics. In this paper, we describe the detection of a fired bullet using a radar operating at an extremely high-frequency band. This allowed us to employ a low sampling rate which enabled the use of inexpensive and straightforward equipment, including the use of small antennas that allow velocity detection at high resolution and with low atmospheric absorption.

Time-Frequency Spectral Signature of Limb Movements and Height Estimation Using Micro-Doppler Millimeter-Wave Radar.

We present a technique for the identification of human and animal movement and height using a low power millimeter-wave radar. The detection was based on the transmission of a continuous wave and heterodyning the received signal reflected from the target to obtain micro-Doppler shifts associated with the target structure and motion. The algorithm enabled the extraction of target signatures from typical gestures and differentiated between humans, animals, and other 'still' objects. Analytical expressions were derived using a pendulum model to characterize the micro-Doppler frequency shifts due to the periodic motion of the human and animal limbs. The algorithm was demonstrated using millimeter-wave radar operating in the W-band. We employed a time-frequency distribution to analyze the detected signal and classify the type of targets.

One Thousand and One Software for Proteomics: Tales of the Toolmakers of Science.

Proteomics is a highly dynamic field driven by frequent introduction of new technological approaches, leading to high demand for new software tools and the concurrent development of many methods for data analysis, processing, and storage. The rapidly changing landscape of proteomics software makes finding a tool fit for a particular purpose a significant challenge. The comparison of software and the selection of tools capable to perform a certain operation on a given type of data rely on their detailed annotation using well-defined descriptors. However, finding accurate information including tool input/output capabilities can be challenging and often heavily depends on manual curation efforts. This is further hampered by a rather low half-life of most of the tools, thus demanding the maintenance of a resource with updated information about the tools. We present here our approach to curate a collection of 189 software tools with detailed information about their functional capabilities. We furthermore describe our efforts to reach out to the proteomics community for their engagement, which further increased the catalog to >750 tools being about 70% of the estimated number of 1097 tools existing for proteomics data analysis. Descriptions of all annotated tools are available at  https://proteomics.bio.tools.

Gene characteristics predicting missense, nonsense and frameshift mutations in tumor samples.

BACKGROUND: Because driver mutations provide selective advantage to the mutant clone, they tend to occur at a higher frequency in tumor samples compared to selectively neutral (passenger) mutations. However, mutation frequency alone is insufficient to identify cancer genes because mutability is influenced by many gene characteristics, such as size, nucleotide composition, etc. The goal of this study was to identify gene characteristics associated with the frequency of somatic mutations in the gene in tumor samples. RESULTS: We used data on somatic mutations detected by genome wide screens from the Catalog of Somatic Mutations in Cancer (COSMIC). Gene size, nucleotide composition, expression level of the gene, relative replication time in the cell cycle, level of evolutionary conservation and other gene characteristics (totaling 11) were used as predictors of the number of somatic mutations. We applied stepwise multiple linear regression to predict the number of mutations per gene. Because missense, nonsense, and frameshift mutations are associated with different sets of gene characteristics, they were modeled separately. Gene characteristics explain 88% of the variation in the number of missense, 40% of nonsense, and 23% of frameshift mutations. Comparisons of the observed and expected numbers of mutations identified genes with a higher than expected number of mutations- positive outliers. Many of these are known driver genes. A number of novel candidate driver genes was also identified. CONCLUSIONS: By comparing the observed and predicted number of mutations in a gene, we have identified known cancer-associated genes as well as 111 novel cancer associated genes. We also showed that adding the number of silent mutations per gene reported by genome/exome wide screens across all cancer type (COSMIC data) as a predictor substantially exceeds predicting accuracy of the most popular cancer gene predicting tool - MutsigCV.

Straightforward hit identification approach in fragment-based discovery of bromodomain-containing protein 4 (BRD4) inhibitors.

A combination approach of a fragment screening and "SAR by catalog" was used for the discovery of bromodomain-containing protein 4 (BRD4) inhibitors. Initial screening of 3695-fragment library against bromodomain 1 of BRD4 using thermal shift assay (TSA), followed by initial hit validation, resulted in 73 fragment hits, which were used to construct a follow-up library selected from available screening collection. Additionally, analogs of inactive fragments, as well as a set of randomly selected compounds were also prepared (3 × 3200 compounds in total). Screening of the resulting sets using TSA, followed by re-testing at several concentrations, counter-screen, and TR-FRET assay resulted in 18 confirmed hits. Compounds derived from the initial fragment set showed better hit rate as compared to the other two sets. Finally, building dose-response curves revealed three compounds with IC50 = 1.9-7.4 µM. For these compounds, binding sites and conformations in the BRD4 (4UYD) have been determined by docking.

Regional Seismic Information Entropy to Detect Earthquake Activation Precursors.

A method is presented to detect earthquake precursors from time series data on earthquakes in a target region. The Regional Entropy of Seismic Information (RESI) is an index that represents the average influence of an earthquake in a target region on the diversity of clusters to which earthquake foci are distributed. Based on a simple qualitative model of the dynamics of land crust, it is hypothesized that the saturation that occurs after an increase in RESI precedes the activation of earthquakes. This hypothesis is validated by the earthquake catalog. This temporal change was found to correlate with the activation of earthquakes in Japanese regions one to two years ahead of the real activation, more reliably than the compared baseline methods.

Cell line donor genotype and its influence on experimental phenotype: Toll-like receptor SNPs and potential variability in innate immunity.

Cell lines are used to model a disease and provide valuable information regarding phenotype, mechanism, and response to novel therapies. Derived from individuals of diverse genetic backgrounds, the cell's genetic complement predicts the phenotype, and although some lines have been sequenced, little emphasis has been placed on genotyping. Toll-like receptors (TLRs) are essential in initiating the inflammatory cascade in response to infection. TLR single nucleotide polymorphism (SNP) alleles may predict an altered innate immune response: a SNP can affect TLR-dependent pathways and may alter experimental results. Thus, genotype variation may have far-reaching implications when using cell lines to model phenotypes. We recommend that cell lines be genotyped and cataloged in a fashion similar to that used for bacteria, with cumulative information being archived in an accessible central database to facilitate the understanding of SNP cell phenotypes reported in the literature.