Dark triad personality traits are associated with decreased grey matter volumes in 'social brain' structures.

Introduction: Personality traits and the degree of their prominence determine various aspects of social interactions. Some of the most socially relevant traits constitute the Dark Triad - narcissism, psychopathy, and Machiavellianism - associated with antisocial behaviour, disregard for moral norms, and a tendency to manipulation. Sufficient data point at the existence of Dark Triad 'profiles' distinguished by trait prominence. Currently, neuroimaging studies have mainly concentrated on the neuroanatomy of individual dark traits, while the Dark Triad profile structure has been mostly overlooked. Methods: We performed a clustering analysis of the Dirty Dozen Dark Triad questionnaire scores of 129 healthy subjects using the k-means method. The variance ratio criterion (VRC) was used to determine the optimal number of clusters for the current data. The two-sample t-test within the framework of voxel-based morphometry (VBM) was performed to test the hypothesised differences in grey matter volume (GMV) for the obtained groups. Results: Clustering analysis revealed 2 groups of subjects, both with low-to-mid and mid-to-high levels of Dark Triad traits prominence. A further VBM analysis of these groups showed that a higher level of Dark Triad traits may manifest itself in decreased grey matter volumes in the areas related to emotional regulation (the dorsolateral prefrontal cortex, the cingulate cortex), as well as those included in the reward system (the ventral striatum, the orbitofrontal cortex). Discussion: The obtained results shed light on the neurobiological basis underlying social interactions associated with the Dark Triad and its profiles.

Single-cell roadmap of human gonadal development.

Gonadal development is a complex process that involves sex determination followed by divergent maturation into either testes or ovaries1. Historically, limited tissue accessibility, a lack of reliable in vitro models and critical differences between humans and mice have hampered our knowledge of human gonadogenesis, despite its importance in gonadal conditions and infertility. Here, we generated a comprehensive map of first- and second-trimester human gonads using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays and fluorescent microscopy. We extracted human-specific regulatory programmes that control the development of germline and somatic cell lineages by profiling equivalent developmental stages in mice. In both species, we define the somatic cell states present at the time of sex specification, including the bipotent early supporting population that, in males, upregulates the testis-determining factor SRY and sPAX8s, a gonadal lineage located at the gonadal-mesonephric interface. In females, we resolve the cellular and molecular events that give rise to the first and second waves of granulosa cells that compartmentalize the developing ovary to modulate germ cell differentiation. In males, we identify human SIGLEC15+ and TREM2+ fetal testicular macrophages, which signal to somatic cells outside and inside the developing testis cords, respectively. This study provides a comprehensive spatiotemporal map of human and mouse gonadal differentiation, which can guide in vitro gonadogenesis.

Single-cell Atlas of common variable immunodeficiency shows germinal center-associated epigenetic dysregulation in B-cell responses.

Common variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, displays impaired terminal B-cell differentiation and defective antibody responses. Incomplete genetic penetrance and ample phenotypic expressivity in CVID suggest the participation of additional pathogenic mechanisms. Monozygotic (MZ) twins discordant for CVID are uniquely valuable for studying the contribution of epigenetics to the disease. Here, we generate a single-cell epigenomics and transcriptomics census of naïve-to-memory B cell differentiation in a CVID-discordant MZ twin pair. Our analysis identifies DNA methylation, chromatin accessibility and transcriptional defects in memory B-cells mirroring defective cell-cell communication upon activation. These findings are validated in a cohort of CVID patients and healthy donors. Our findings provide a comprehensive multi-omics map of alterations in naïve-to-memory B-cell transition in CVID and indicate links between the epigenome and immune cell cross-talk. Our resource, publicly available at the Human Cell Atlas, gives insight into future diagnosis and treatments of CVID patients.

Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro.

The endometrium, the mucosal lining of the uterus, undergoes dynamic changes throughout the menstrual cycle in response to ovarian hormones. We have generated dense single-cell and spatial reference maps of the human uterus and three-dimensional endometrial organoid cultures. We dissect the signaling pathways that determine cell fate of the epithelial lineages in the lumenal and glandular microenvironments. Our benchmark of the endometrial organoids reveals the pathways and cell states regulating differentiation of the secretory and ciliated lineages both in vivo and in vitro. In vitro downregulation of WNT or NOTCH pathways increases the differentiation efficiency along the secretory and ciliated lineages, respectively. We utilize our cellular maps to deconvolute bulk data from endometrial cancers and endometriotic lesions, illuminating the cell types dominating in each of these disorders. These mechanistic insights provide a platform for future development of treatments for common conditions including endometriosis and endometrial carcinoma.

Fast searches of large collections of single-cell data using scfind.

Single-cell technologies have made it possible to profile millions of cells, but for these resources to be useful they must be easy to query and access. To facilitate interactive and intuitive access to single-cell data we have developed scfind, a single-cell analysis tool that facilitates fast search of biologically or clinically relevant marker genes in cell atlases. Using transcriptome data from six mouse cell atlases, we show how scfind can be used to evaluate marker genes, perform in silico gating, and identify both cell-type-specific and housekeeping genes. Moreover, we have developed a subquery optimization routine to ensure that long and complex queries return meaningful results. To make scfind more user friendly, we use indices of PubMed abstracts and techniques from natural language processing to allow for arbitrary queries. Finally, we show how scfind can be used for multi-omics analyses by combining single-cell ATAC-seq data with transcriptome data.

Flexible comparison of batch correction methods for single-cell RNA-seq using BatchBench.

As the cost of single-cell RNA-seq experiments has decreased, an increasing number of datasets are now available. Combining newly generated and publicly accessible datasets is challenging due to non-biological signals, commonly known as batch effects. Although there are several computational methods available that can remove batch effects, evaluating which method performs best is not straightforward. Here, we present BatchBench (https://github.com/cellgeni/batchbench), a modular and flexible pipeline for comparing batch correction methods for single-cell RNA-seq data. We apply BatchBench to eight methods, highlighting their methodological differences and assess their performance and computational requirements through a compendium of well-studied datasets. This systematic comparison guides users in the choice of batch correction tool, and the pipeline makes it easy to evaluate other datasets.

Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data.

Single-cell RNA sequencing (scRNA-seq) is a popular and powerful technology that allows you to profile the whole transcriptome of a large number of individual cells. However, the analysis of the large volumes of data generated from these experiments requires specialized statistical and computational methods. Here we present an overview of the computational workflow involved in processing scRNA-seq data. We discuss some of the most common tasks and the tools available for addressing central biological questions. In this article and our companion website ( https://scrnaseq-course.cog.sanger.ac.uk/website/index.html ), we provide guidelines regarding best practices for performing computational analyses. This tutorial provides a hands-on guide for experimentalists interested in analyzing their data as well as an overview for bioinformaticians seeking to develop new computational methods.

Comparison of visualization tools for single-cell RNAseq data.

In the last decade, single cell RNAseq (scRNAseq) datasets have grown in size from a single cell to millions of cells. Due to its high dimensionality, it is not always feasible to visualize scRNAseq data and share it in a scientific report or an article publication format. Recently, many interactive analysis and visualization tools have been developed to address this issue and facilitate knowledge transfer in the scientific community. In this study, we review several of the currently available scRNAseq visualization tools and benchmark the subset that allows to visualize the data on the web and share it with others. We consider the memory and time required to prepare datasets for sharing as the number of cells increases, and additionally review the user experience and features available in the web interface. To address the problem of format compatibility we have also developed a user-friendly R package, sceasy, which allows users to convert their own scRNAseq datasets into a specific data format for visualization.

Challenges in unsupervised clustering of single-cell RNA-seq data.

Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues detailing the transcriptomes of individual cells. Unsupervised clustering is of central importance for the analysis of these data, as it is used to identify putative cell types. However, there are many challenges involved. We discuss why clustering is a challenging problem from a computational point of view and what aspects of the data make it challenging. We also consider the difficulties related to the biological interpretation and annotation of the identified clusters.

Publisher Correction: Challenges in unsupervised clustering of single-cell RNA-seq data.

During typesetting of this article, errors were inadvertently introduced to the hyperlinked URLs of some of the clustering tools in table 1 (Seurat, CIDR, pcaReduce and mpath), as well as to the numbering of the bold-text annotations in the reference list. The article has now been corrected online. The editors apologize for this error.

Predicting the mutations generated by repair of Cas9-induced double-strand breaks.

The DNA mutation produced by cellular repair of a CRISPR-Cas9-generated double-strand break determines its phenotypic effect. It is known that the mutational outcomes are not random, but depend on DNA sequence at the targeted location. Here we systematically study the influence of flanking DNA sequence on repair outcome by measuring the edits generated by >40,000 guide RNAs (gRNAs) in synthetic constructs. We performed the experiments in a range of genetic backgrounds and using alternative CRISPR-Cas9 reagents. In total, we gathered data for >109 mutational outcomes. The majority of reproducible mutations are insertions of a single base, short deletions or longer microhomology-mediated deletions. Each gRNA has an individual cell-line-dependent bias toward particular outcomes. We uncover sequence determinants of the mutations produced and use these to derive a predictor of Cas9 editing outcomes. Improved understanding of sequence repair will allow better design of gene editing experiments.

scmap: projection of single-cell RNA-seq data across data sets.

Single-cell RNA-seq (scRNA-seq) allows researchers to define cell types on the basis of unsupervised clustering of the transcriptome. However, differences in experimental methods and computational analyses make it challenging to compare data across experiments. Here we present scmap (http://bioconductor.org/packages/scmap; web version at http://www.sanger.ac.uk/science/tools/scmap), a method for projecting cells from an scRNA-seq data set onto cell types or individual cells from other experiments.

PTEN Regulates PI(3,4)P2 Signaling Downstream of Class I PI3K.

The PI3K signaling pathway regulates cell growth and movement and is heavily mutated in cancer. Class I PI3Ks synthesize the lipid messenger PI(3,4,5)P3. PI(3,4,5)P3 can be dephosphorylated by 3- or 5-phosphatases, the latter producing PI(3,4)P2. The PTEN tumor suppressor is thought to function primarily as a PI(3,4,5)P3 3-phosphatase, limiting activation of this pathway. Here we show that PTEN also functions as a PI(3,4)P2 3-phosphatase, both in vitro and in vivo. PTEN is a major PI(3,4)P2 phosphatase in Mcf10a cytosol, and loss of PTEN and INPP4B, a known PI(3,4)P2 4-phosphatase, leads to synergistic accumulation of PI(3,4)P2, which correlated with increased invadopodia in epidermal growth factor (EGF)-stimulated cells. PTEN deletion increased PI(3,4)P2 levels in a mouse model of prostate cancer, and it inversely correlated with PI(3,4)P2 levels across several EGF-stimulated prostate and breast cancer lines. These results point to a role for PI(3,4)P2 in the phenotype caused by loss-of-function mutations or deletions in PTEN.

Tia1 dependent regulation of mRNA subcellular location and translation controls p53 expression in B cells.

Post-transcriptional regulation of cellular mRNA is essential for protein synthesis. Here we describe the importance of mRNA translational repression and mRNA subcellular location for protein expression during B lymphocyte activation and the DNA damage response. Cytoplasmic RNA granules are formed upon cell activation with mitogens, including stress granules that contain the RNA binding protein Tia1. Tia1 binds to a subset of transcripts involved in cell stress, including p53 mRNA, and controls translational silencing and RNA granule localization. DNA damage promotes mRNA relocation and translation in part due to dissociation of Tia1 from its mRNA targets. Upon DNA damage, p53 mRNA is released from stress granules and associates with polyribosomes to increase protein synthesis in a CAP-independent manner. Global analysis of cellular mRNA abundance and translation indicates that this is an extended ATM-dependent mechanism to increase protein expression of key modulators of the DNA damage response.Sequestering mRNA in cytoplasmic stress granules is a mechanism for translational repression. Here the authors find that p53 mRNA, present in stress granules in activated B lymphocytes, is released upon DNA damage and is translated in a CAP-independent manner.

Proliferation Drives Aging-Related Functional Decline in a Subpopulation of the Hematopoietic Stem Cell Compartment.

Aging of the hematopoietic stem cell (HSC) compartment is characterized by lineage bias and reduced stem cell function, the molecular basis of which is largely unknown. Using single-cell transcriptomics, we identified a distinct subpopulation of old HSCs carrying a p53 signature indicative of stem cell decline alongside pro-proliferative JAK/STAT signaling. To investigate the relationship between JAK/STAT and p53 signaling, we challenged HSCs with a constitutively active form of JAK2 (V617F) and observed an expansion of the p53-positive subpopulation in old mice. Our results reveal cellular heterogeneity in the onset of HSC aging and implicate a role for JAK2V617F-driven proliferation in the p53-mediated functional decline of old HSCs.

SC3: consensus clustering of single-cell RNA-seq data.

Single-cell RNA-seq enables the quantitative characterization of cell types based on global transcriptome profiles. We present single-cell consensus clustering (SC3), a user-friendly tool for unsupervised clustering, which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach (http://bioconductor.org/packages/SC3). We demonstrate that SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients.

Perturbations of PIP3 signalling trigger a global remodelling of mRNA landscape and reveal a transcriptional feedback loop.

PIP3 is synthesized by the Class I PI3Ks and regulates complex cell responses, such as growth and migration. Signals that drive long-term reshaping of cell phenotypes are difficult to resolve because of complex feedback networks that operate over extended times. PIP3-dependent modulation of mRNA accumulation is clearly important in this process but is poorly understood. We have quantified the genome-wide mRNA-landscape of non-transformed, breast epithelium-derived MCF10a cells and its response to acute regulation by EGF, in the presence or absence of a PI3Kα inhibitor, compare it to chronic activation of PI3K signalling by cancer-relevant mutations (isogenic cells expressing an oncomutant PI3Kα allele or lacking the PIP3-phosphatase/tumour-suppressor, PTEN). Our results show that whilst many mRNAs are changed by long-term genetic perturbation of PIP3 signalling ('butterfly effect'), a much smaller number do so in a coherent fashion with the different PIP3 perturbations. This suggests a subset of more directly regulated mRNAs. We show that mRNAs respond differently to given aspects of PIP3 regulation. Some PIP3-sensitive mRNAs encode PI3K pathway components, thus suggesting a transcriptional feedback loop. We identify the transcription factor binding motifs SRF and PRDM1 as important regulators of PIP3-sensitive mRNAs involved in cell movement.

Lead removal in rats using calcium alginate.

Lead (Pb) exposure, even at low levels, causes a variety of health problems. The aims of this study were to investigate the tissue distribution of lead in the bodies of rats, to evaluate lead removal from the internal organs and bones using calcium alginate in doses of 500, 200 and 100 mg/kg per day for 28 days and to assess the impact of calcium alginate on the level of essential elements. Lead (Pb), calcium (Ca), manganese (Mn), iron (Fe), copper (Cu) and zinc (Zn) levels in the blood, hearts, kidneys, livers and femurs of the experimental animals were measured using mass spectrometry with inductively coupled plasma. The results revealed that lead acetate exposure increased the levels of Pb in the blood and organs of the animals and significantly reduced contents of Ca, Mn, Fe, Cu and Zn. Treatment with calcium alginate in dose 500 mg/kg contributed to significant decreases in the amount of lead in the kidney, heart and bones of animals and a slight increase in the content of essential elements in the liver, kidneys and heart, although these changes were not significant. Decreasing of lead was not significant in the internal organs, bones and blood of animals treated with calcium alginate 200 and 100 mg/kg. Consequently, calcium alginate dose of 500 mg/kg more efficiently removes lead accumulated in the body. Calcium alginate does not have negative effect on level of essential elements quite the contrary; reducing the levels of lead, calcium alginate helps normalize imbalances of Ca, Mn, Fe, Cu and Zn. The results of this study suggest that calcium alginate may potentially be useful for the treatment and prevention of heavy metal intoxications.

Changes in permittivity and density of molecular liquids under high pressure.

We collected and analyzed the density and permittivity of 57 nonpolar and dipolar molecular liquids at different temperatures (143 sets) and pressures (555 sets). No equation was found that could accurately predict the change to polar liquid permittivity by the change of its density in the range of the pressures and temperatures tested. Consequently, the influence of high hydrostatic pressure and temperature on liquid permittivity may be a more complicated process compared to density changes. The pressure and temperature coefficients of permittivity can be drastically larger than the pressure and temperature coefficients of density, indicating that pressure and particularly temperature significantly affect the structure of molecular liquids. These changes have less influence on the density change but can strongly affect the permittivity change. The clear relationship between the tangent and secant moduli of the permittivity curvatures under pressure for various molecular liquids at different temperatures was obtained, from which one can calculate the Tait equation coefficients from the experimental values of the pressure influence on the permittivity at ambient pressure.