TOX3 regulates neural progenitor identity

Using human genetics to understand the phenotypic association between chronotype and breast cancer

Little is known regarding the shared genetic influences underlying the observed phenotypic association between chronotype and breast cancer in women. Leveraging summary statistics from the hitherto largest genome-wide association study conducted in each trait, we investigated the genetic correlation, pleiotropic loci, and causal relationship of chronotype with overall breast cancer, and with its subtypes defined by the status of oestrogen receptor. We identified a negative genomic correlation between chronotype and overall breast cancer (r g  = -0.06, p = 3.00 × 10-4), consistent across oestrogen receptor-positive (r g  = -0.05, p = 3.30 × 10-3) and oestrogen receptor-negative subtypes (r g  = -0.05, p = 1.11 × 10-2). Five specific genomic regions were further identified as contributing a significant local genetic correlation. Cross-trait meta-analysis identified 78 loci shared between chronotype and breast cancer, of which 23 were novel. Transcriptome-wide association study revealed 13 shared genes, targeting tissues of the nervous, cardiovascular, digestive, and exocrine/endocrine systems. Mendelian randomisation demonstrated a significantly reduced risk of overall breast cancer (odds ratio 0.89, 95% confidence interval 0.83-0.94; p = 1.30 × 10-4) for genetically predicted morning chronotype. No reverse causality was found. Our work demonstrates an intrinsic link underlying chronotype and breast cancer, which may provide clues to inform management of sleep habits to improve female health.

In vitro generation of mouse morula-like cells

Generating cells with the molecular and functional properties of embryo cells and with full developmental potential is an aim with fundamental biological significance. Here we report the in vitro generation of mouse transient morula-like cells (MLCs) via the manipulation of signaling pathways. MLCs are molecularly distinct from embryonic stem cells (ESCs) and cluster instead with embryo 8- to 16-cell stage cells. A single MLC can generate a blastoid, and the efficiency increases to 80% when 8-10 MLCs are used. MLCs make embryoids directly, efficiently, and within 4 days. Transcriptomic analysis shows that day 4-5 MLC-derived embryoids contain the cell types found in natural embryos at early gastrulation. Furthermore, MLCs introduced into morulae segregate into epiblast (EPI), primitive endoderm (PrE), and trophectoderm (TE) fates in blastocyst chimeras and have a molecular signature indistinguishable from that of host embryo cells. These findings represent the generation of cells that are molecularly and functionally similar to the precursors of the first three cell lineages of the embryo.

DMRT1-mediated regulation of TOX3 modulates expansion of the gonadal steroidogenic cell lineage in the chicken embryo

During gonadal sex determination, the supporting cell lineage differentiates into Sertoli cells in males and pre-granulosa cells in females. Recently, single cell RNA-seq data have indicated that chicken steroidogenic cells are derived from differentiated supporting cells. This differentiation process is achieved by a sequential upregulation of steroidogenic genes and downregulation of supporting cell markers. The exact mechanism regulating this differentiation process remains unknown. We have identified TOX3 as a previously unreported transcription factor expressed in embryonic Sertoli cells of the chicken testis. TOX3 knockdown in males resulted in increased CYP17A1-positive Leydig cells. TOX3 overexpression in male and female gonads resulted in a significant decline in CYP17A1-positive steroidogenic cells. In ovo knockdown of the testis determinant DMRT1 in male gonads resulted in a downregulation of TOX3 expression. Conversely, DMRT1 overexpression caused an increase in TOX3 expression. Taken together, these data indicate that DMRT1-mediated regulation of TOX3 modulates expansion of the steroidogenic lineage, either directly, via cell lineage allocation, or indirectly, via signaling from the supporting to steroidogenic cell populations.

Decoding anterior-posterior axis emergence among mouse, monkey, and human embryos

Anterior-posterior axis formation regulated by the distal visceral endoderm (DVE) and anterior visceral endoderm (AVE) is essential for peri-implantation embryogenesis. However, the principles of the origin and specialization of DVE and AVE remain elusive. Here, with single-cell transcriptome analysis and pseudotime prediction, we show that DVE and AVE independently originate from the specialized primary endoderm in mouse blastocysts. Along distinct developmental paths, these two lineages, respectively, undergo four representative states with stage-specific transcriptional patterns around implantation. Further comparative analysis shows that AVE, but not DVE, is detected in human and non-human primate embryos, defining differences in polarity formation across species. Moreover, stem cell-assembled human blastoids lack DVE or AVE precursors, implying that additional induction of stem cells with DVE/AVE potential could promote the current embryo-like models and their post-implantation growth. Our work provides insight into understanding of embryonic polarity formation and early mammalian development.

Evolutionarily conservative and non-conservative regulatory networks during primate interneuron development revealed by single-cell RNA and ATAC sequencing

The differences in size and function between primate and rodent brains, and the association of disturbed excitatory/inhibitory balance with many neurodevelopmental disorders highlight the importance to study primate ganglionic eminences (GEs) development. Here we used single-cell RNA and ATAC sequencing to characterize the emergence of cell diversity in monkey and human GEs where most striatal and cortical interneurons are generated. We identified regional and temporal diversity among progenitor cells which give rise to a variety of interneurons. These cells are specified within the primate GEs by well conserved gene regulatory networks, similar to those identified in mice. However, we detected, in human, several novel regulatory pathways or factors involved in the specification and migration of interneurons. Importantly, comparison of progenitors between our human and published mouse GE datasets led to the discovery and confirmation of outer radial glial cells in GEs in human cortex. Our findings reveal both evolutionarily conservative and nonconservative regulatory networks in primate GEs, which may contribute to their larger brain sizes and more complex neural networks compared with mouse.

MOUSSE: Multi-Omics Using Subject-Specific SignaturEs

Simple Summary

Modern profiling technologies have led to relevant progress toward precision medicine and disease management. A new trend in patient classification is to integrate multiple data types for the same subjects to increase the chance of identifying meaningful phenotype groups. However, these methodologies are still in their infancy, with their performance varying widely depending on the biological conditions analyzed. We developed MOUSSE, a new unsupervised and normalization-free tool for multi-omics integration able to maintain good clustering performance across a wide range of omics data. We verified its efficiency in clustering patients based on survival for ten different cancer types. The results we obtained show a higher average score in classification performance than ten other state-of-the-art algorithms. We have further validated the method by identifying a list of biological features potentially involved in patient survival, finding a high degree of concordance with the literature.

Abstract

High-throughput technologies make it possible to produce a large amount of data representing different biological layers, examples of which are genomics, proteomics, metabolomics and transcriptomics. Omics data have been individually investigated to understand the molecular bases of various diseases, but this may not be sufficient to fully capture the molecular mechanisms and the multilayer regulatory processes underlying complex diseases, especially cancer. To overcome this problem, several multi-omics integration methods have been introduced but a commonly agreed standard of analysis is still lacking. In this paper, we present MOUSSE, a novel normalization-free pipeline for unsupervised multi-omics integration. The main innovations are the use of rank-based subject-specific signatures and the use of such signatures to derive subject similarity networks. A separate similarity network was derived for each omics, and the resulting networks were then carefully merged in a way that considered their informative content. We applied it to analyze survival in ten different types of cancer. We produced a meaningful clusterization of the subjects and obtained a higher average classification score than ten state-of-the-art algorithms tested on the same data. As further validation, we extracted from the subject-specific signatures a list of relevant features used for the clusterization and investigated their biological role in survival. We were able to verify that, according to the literature, these features are highly involved in cancer progression and differential survival.

Multimodal single-cell analysis reveals distinct radioresistant stem-like and progenitor cell populations in murine glioma

Radiation therapy is part of the standard of care for gliomas and kills a subset of tumor cells, while also altering the tumor microenvironment. Tumor cells with stem-like properties preferentially survive radiation and give rise to glioma recurrence. Various techniques for enriching and quantifying cells with stem-like properties have been used, including the fluorescence activated cell sorting (FACS)-based side population (SP) assay, which is a functional assay that enriches for stem-like tumor cells. In these analyses, mouse models of glioma have been used to understand the biology of this disease and therapeutic responses, including the radiation response. We present combined SP analysis and single-cell RNA sequencing of genetically-engineered mouse models of glioma to show a time course of cellular response to radiation. We identify and characterize two distinct tumor cell populations that are inherently radioresistant and also distinct effects of radiation on immune cell populations within the tumor microenvironment.

TOX3 Promotes Ovarian Estrogen Synthesis: An RNA-Sequencing and Network Study

BACKGROUND

Women who undergo chronic exposure to excessive estrogen are at a high risk of developing breast cancer. TOX3 has been reported to be highly expressed in breast tumors and is closely related to estrogen receptors. However, the effect of TOX3 on estrogen synthesis remains poorly understood.

METHODS

Using lentiviruses as a vector, we stably overexpressed TOX3 in the ovarian granulosa cell line KGN, the cells where estradiol is primarily produced, to investigate its role in estrogen production as well as cell viability and apoptosis. RNA-Sequencing was applied to uncover the global gene expression upon TOX3 overexpression.

RESULTS

We observed an increased level of cell viability and a reduced cell apoptosis rate after TOX3 overexpression, and the level of estradiol in the cell culture supernatant also increased significantly. Gene set enrichment analysis of the transcriptome showed that the ovarian steroidogenesis pathway was significantly enriched. Similarly, pathway mapping using the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses also showed that TOX3 overexpression affects the ovarian steroidogenesis pathway. Further experiments showed that upregulated FSHR, CYP19A1, and BMP6 accounted for the enhanced estrogen synthesis.

CONCLUSION

Our study demonstrated that TOX3 quantitatively and qualitatively stimulates estrogen synthesis by enhancing estrogen signaling pathway-related gene expression in ovarian granulosa cells. These findings suggest that TOX3 may play a vital role in the pathogenesis of breast cancer.

Caenorhabditis elegans and its applicability to studies on restless legs syndrome

Restless legs syndrome (RLS) is a common neurological disorder in the United States. This disorder is characterized by an irresistible urge to move the legs, although the symptoms vary in a wide range. The pathobiology of RLS has been linked to iron (Fe) deficiency and dopaminergic (DAergic) dysfunction. Several genetic factors have been reported to increase the risk of RLS. Caenorhabditis elegans (C. elegans) is a well-established animal model with a fully sequenced genome, which is highly conserved with mammals. Given the detailed knowledge of its genomic architecture, ease of genetic manipulation and conserved biosynthetic and metabolic pathways, as well as its small size, ease of maintenance, speedy generation time and large brood size, C. elegans provides numerous advantages in studying RLS-associated gene-environment interactions. Here we will review current knowledge about RLS symptoms, pathology and treatments, and discuss the application of C. elegans in RLS study, including the worm homologous genes and methods that could be performed to advance the pathophysiology RLS.

Lack of Association Between Shape and Volume of Subcortical Brain Structures and Restless Legs Syndrome

Objective

Previous studies on patients with restless legs syndrome (RLS) yielded inconclusive results in the magnetic resonance imaging (MRI)-based analyses of alterations of subcortical structures in the brain. The aim of this study was to compare volumes as well as shapes of subcortical structures and the hippocampus between RLS cases and controls. Additionally, the associations between the genetic risks for RLS and subcortical volumes were investigated.

Methods

We compared volumetric as well as shape differences assessed by 3 T MRI in the caudate nucleus, hippocampus, globus pallidus, putamen, and thalamus in 39 RLS cases versus 117 controls, nested within a population-based sample. In a subsample, we explored associations between known genetic risk markers for RLS and the volumes of the subcortical structures and the hippocampus.

Results

No significant differences between RLS cases and controls in subcortical and hippocampal shapes and volumes were observed. Furthermore, the genetic risk for RLS was unrelated to any alterations of subcortical and hippocampal gray matter volume.

Interpretation

We conclude that neither RLS nor the genetic risk for the disease give rise to changes in hippocampal and subcortical shapes and gray matter volumes.

Identification of novel risk loci for restless legs syndrome in genome-wide association studies in individuals of European ancestry: a meta-analysis

BACKGROUND

Restless legs syndrome is a prevalent chronic neurological disorder with potentially severe mental and physical health consequences. Clearer understanding of the underlying pathophysiology is needed to improve treatment options. We did a meta-analysis of genome-wide association studies (GWASs) to identify potential molecular targets.

METHODS

In the discovery stage, we combined three GWAS datasets (EU-RLS GENE, INTERVAL, and 23andMe) with diagnosis data collected from 2003 to 2017, in face-to-face interviews or via questionnaires, and involving 15 126 cases and 95 725 controls of European ancestry. We identified common variants by fixed-effect inverse-variance meta-analysis. Significant genome-wide signals (p≤5 × 10-8) were tested for replication in an independent GWAS of 30 770 cases and 286 913 controls, followed by a joint analysis of the discovery and replication stages. We did gene annotation, pathway, and gene-set-enrichment analyses and studied the genetic correlations between restless legs syndrome and traits of interest.

FINDINGS

We identified and replicated 13 new risk loci for restless legs syndrome and confirmed the previously identified six risk loci. MEIS1 was confirmed as the strongest genetic risk factor for restless legs syndrome (odds ratio 1·92, 95% CI 1·85-1·99). Gene prioritisation, enrichment, and genetic correlation analyses showed that identified pathways were related to neurodevelopment and highlighted genes linked to axon guidance (associated with SEMA6D), synapse formation (NTNG1), and neuronal specification (HOXB cluster family and MYT1).

INTERPRETATION

Identification of new candidate genes and associated pathways will inform future functional research. Advances in understanding of the molecular mechanisms that underlie restless legs syndrome could lead to new treatment options. We focused on common variants; thus, additional studies are needed to dissect the roles of rare and structural variations.

FUNDING

Deutsche Forschungsgemeinschaft, Helmholtz Zentrum München-Deutsches Forschungszentrum für Gesundheit und Umwelt, National Research Institutions, NHS Blood and Transplant, National Institute for Health Research, British Heart Foundation, European Commission, European Research Council, National Institutes of Health, National Institute of Neurological Disorders and Stroke, NIH Research Cambridge Biomedical Research Centre, and UK Medical Research Council.