More frequent naps are associated with lower cognitive development in a cohort of 8–38‐month‐old children, during the Covid‐19 pandemic

Background How often a child naps, during infancy, is believed to reflect both intrinsic factors, that is, the need of an immature brain to consolidate information soon after it is acquired, and environmental factors. Difficulty accounting for important environmental factors that interfere with a child's sleep needs (e.g., attending daycare) has clouded our ability to understand the role of intrinsic drivers of napping frequency. Methods Here we investigate sleep patterns in association with two measures of cognitive ability, vocabulary size, measured with the Oxford-Communicative Development Inventory (N = 298) and cognitive executive functions (EF), measured with the Early EF Questionnaire (N = 463), in a cohort of 8–38-month-olds. Importantly, because of the social distancing measures imposed during the Covid-19 Spring 2020 lockdown, in the UK, measures of sleep were taken when children did not access daycare settings. Results We find that children with more frequent but shorter naps than expected for their age had lower concurrent receptive vocabularies, lower cognitive EF and a slower increase in expressive vocabulary from spring to winter 2020, when age, sex, and SES were accounted for. The negative association between vocabulary and frequency of naps became stronger with age. Conclusions These findings suggest that the structure of daytime sleep is an indicator of cognitive development and highlight the importance of considering environmental perturbations and age when investigating developmental correlates of sleep

Pulsed Gamma Rays from the Original Millisecond and Black Widow Pulsars: a case for Caustic Radio Emission?

We report the detection of pulsed gamma-ray emission from the fast millisecond pulsars (MSPs) B1937+21 (also known as J1939+2134) and B1957+20 (J1959+2048) using 18 months of survey data recorded by the \emph{Fermi} Large Area Telescope (LAT) and timing solutions based on radio observations conducted at the Westerbork and Nan\c{c}ay radio telescopes. In addition, we analyzed archival \emph{RXTE} and \emph{XMM-Newton} X-ray data for the two MSPs, confirming the X-ray emission properties of PSR B1937+21 and finding evidence ($\sim 4\sigma$) for pulsed emission from PSR B1957+20 for the first time. In both cases the gamma-ray emission profile is characterized by two peaks separated by half a rotation and are in close alignment with components observed in radio and X-rays. These two pulsars join PSRs J0034-0534 and J2214+3000 to form an emerging class of gamma-ray MSPs with phase-aligned peaks in different energy bands. The modeling of the radio and gamma-ray emission profiles suggests co-located emission regions in the outer magnetosphere.Comment: Accepted for publication in the Astrophysical Journa

Routes for breaching and protecting genetic privacy

We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.Comment: Draft for comment

Chemical Basis of Metabolic Network Organization

Although the metabolic networks of the three domains of life consist of different constituents and metabolic pathways, they exhibit the same scale-free organization. This phenomenon has been hypothetically explained by preferential attachment principle that the new-recruited metabolites attach preferentially to those that are already well connected. However, since metabolites are usually small molecules and metabolic processes are basically chemical reactions, we speculate that the metabolic network organization may have a chemical basis. In this paper, chemoinformatic analyses on metabolic networks of Kyoto Encyclopedia of Genes and Genomes (KEGG), Escherichia coli and Saccharomyces cerevisiae were performed. It was found that there exist qualitative and quantitative correlations between network topology and chemical properties of metabolites. The metabolites with larger degrees of connectivity (hubs) are of relatively stronger polarity. This suggests that metabolic networks are chemically organized to a certain extent, which was further elucidated in terms of high concentrations required by metabolic hubs to drive a variety of reactions. This finding not only provides a chemical explanation to the preferential attachment principle for metabolic network expansion, but also has important implications for metabolic network design and metabolite concentration prediction

Building pathway clusters from Random Forests classification using class votes

<p>Abstract</p> <p>Background</p> <p>Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bring biological insights into microarray studies. A variety of methods have been proposed to construct networks using gene expression data. Because individual pathways do not act in isolation, it is important to understand how different pathways coordinate to perform cellular functions. However, there are no published methods describing how to build pathway clusters that are closely related to traits of interest.</p> <p>Results</p> <p>We propose to build pathway clusters from pathway-based classification methods. The proposed methods allow researchers to identify clusters of pathways sharing similar functions. These pathways may or may not share genes. As an illustration, our approach is applied to three human breast cancer microarray data sets. We found that our methods yielded consistent and interpretable results for these three data sets. We further investigated one of the pathway clusters found using PubMatrix. We found that informative genes in the pathway clusters do have more publications with keywords, like estrogen receptor, compared with informative genes in other top pathways. In addition, using the shortest path analysis in GeneGo's MetaCore and Human Protein Reference Database, we were able to identify the links which connect the pathways without shared genes within the pathway cluster.</p> <p>Conclusion</p> <p>Our proposed pathway clustering methods allow bioinformaticians and biologists to investigate how informative genes within pathways are related to each other and understand possible crosstalk between pathways in a cluster. Therefore, building pathway clusters may lead to a better understanding of molecular mechanisms affecting a trait of interest, and help generate further biological hypotheses from gene expression data.</p

Targeted Development of Registries of Biological Parts

BACKGROUND: The design and construction of novel biological systems by combining basic building blocks represents a dominant paradigm in synthetic biology. Creating and maintaining a database of these building blocks is a way to streamline the fabrication of complex constructs. The Registry of Standard Biological Parts (Registry) is the most advanced implementation of this idea. METHODS/PRINCIPAL FINDINGS: By analyzing inclusion relationships between the sequences of the Registry entries, we build a network that can be related to the Registry abstraction hierarchy. The distribution of entry reuse and complexity was extracted from this network. The collection of clones associated with the database entries was also analyzed. The plasmid inserts were amplified and sequenced. The sequences of 162 inserts could be confirmed experimentally but unexpected discrepancies have also been identified. CONCLUSIONS/SIGNIFICANCE: Organizational guidelines are proposed to help design and manage this new type of scientific resources. In particular, it appears necessary to compare the cost of ensuring the integrity of database entries and associated biological samples with their value to the users. The initial strategy that permits including any combination of parts irrespective of its potential value leads to an exponential and economically unsustainable growth that may be detrimental to the quality and long-term value of the resource to its users

Quantitative proteomics analysis reveals important roles of N-glycosylation on ER quality control system for development and pathogenesis in Magnaporthe oryzae

The fungal pathogen Magnaporthe oryzae can cause rice blast and wheat blast diseases, which threatens worldwide food production. During infection, M. oryzae follows a sequence of distinct developmental stages adapted to survival and invasion of the host environment. M. oryzae attaches onto the host by the conidium, and then develops an appressorium to breach the host cuticle. After penetrating, it forms invasive hyphae to quickly spread in the host cells. Numerous genetic studies have focused on the mechanisms underlying each step in the infection process, but systemic approaches are needed for a broader, integrated understanding of regulatory events during M. oryzae pathogenesis. Many infection-related signaling events are regulated through post-translational protein modifications within the pathogen. N-linked glycosylation, in which a glycan moiety is added to the amide group of an asparagine residue, is an abundant modification known to be essential for M. oryzae infection. In this study, we employed a quantitative proteomics analysis to unravel the overall regulatory mechanisms of N-glycosylation at different developmental stages of M. oryzae. We detected changes in N-glycosylation levels at 559 glycosylated residues (N-glycosites) in 355 proteins during different stages, and determined that the ER quality control system is elaborately regulated by N-glycosylation. The insights gained will help us to better understand the regulatory mechanisms of infection in pathogenic fungi. These findings may be also important for developing novel strategies for fungal disease control. Genetic studies have shown essential functions of N-glycosylation during infection of the plant pathogenic fungi, however, systematic roles of N-glycosylation in fungi is still largely unknown. Biological analysis demonstrated N-glycosylated proteins were widely present at different development stages of Magnaporthe oryzae and especially increased in the appressorium and invasive hyphae. A large-scale quantitative proteomics analysis was then performed to explore the roles of N-glycosylation in M. oryzae. A total of 559 N-glycosites from 355 proteins were identified and quantified at different developmental stages. Functional classification to the N-glycosylated proteins revealed N-glycosylation can coordinate different cellular processes for mycelial growth, conidium formation, and appressorium formation. N-glycosylation can also modify key components in N-glycosylation, O-glycosylation and GPI anchor pathways, indicating intimate crosstalk between these pathways. Interestingly, we found nearly all key components of the endoplasmic reticulum quality control (ERQC) system were highly N-glycosylated in conidium and appressorium. Phenotypic analyses to the gene deletion mutants revealed four ERQC components, Gls1, Gls2, GTB1 and Cnx1, are important for mycelial growth, conidiation, and invasive hyphal growth in host cells. Subsequently, we identified the Gls1 N-glycosite N497 was important for invasive hyphal growth and partially required for conidiation, but didn't affect colony growth. Mutation of N497 resulted in reduction of Gls1 in protein level, and localization from ER into the vacuole, suggesting N497 is important for protein stability of Gls1. Our study showed a snapshot of the N-glycosylation landscape in plant pathogenic fungi, indicating functions of this modification in cellular processes, developments and pathogenesis

An integrated epigenomic analysis for type 2 diabetes susceptibility loci in monozygotic twins

DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Here we perform genome-wide methylated DNA immunoprecipitation sequencing (MeDIP-seq) in whole-blood-derived DNA from 27 monozygotic twin pairs and follow up results with replication and integrated omics analyses. We identify predominately hypermethylated T2D-related differentially methylated regions (DMRs) and replicate the top signals in 42 unrelated T2D cases and 221 controls. The strongest signal is in the promoter of the MALT1 gene, involved in insulin and glycaemic pathways, and related to taurocholate levels in blood. Integrating the DNA methylome findings with T2D GWAS meta-analysis results reveals a strong enrichment for DMRs in T2D-susceptibility loci. We also detect signals specific to T2D-discordant twins in the GPR61 and PRKCB genes. These replicated T2D associations reflect both likely causal and consequential pathways of the disease. The analysis indicates how an integrated genomics and epigenomics approach, utilizing an MZ twin design, can provide pathogenic insights as well as potential drug targets and biomarkers for T2D and other complex traits.Funding support for this project was obtained from the European Research Council (project number 250157) and BGI. The study was also supported by TwinsUK, which is funded by the Wellcome Trust; European Community’s Seventh Framework Programme (FP7/2007-2013); and also receives support from the National Institute for Health Research (NIHR) BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas' NHS Foundation Trust and King’s College London. SNP Genotyping was performed by The Wellcome Trust Sanger Institute and National Eye Institute via NIH/CIDR. M.M. is the holder of Wellcome Trust Senior Investigator Award (Wellcome 098381). T.D.S. is the holder of an ERC Advanced Principal Investigator award (ERC 250157). A.P.M. is a Wellcome Trust Senior Research Fellow in Basic Biomedical Science (grant number WT098017). Skeletal muscle 450k methylation project is supported by European Community's Seventh Framework Programme (FP7/2007-2013) under DEXLIFE project (grant agreement no. HEALTH-F2-2011-279228)