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Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

Mouse models are a critical tool for studying human diseases, particularly developmental disorders1. However, conventional approaches for phenotyping may fail to detect subtle defects throughout the developing mouse2. Here we set out to establish single-cell RNA sequencing of the whole embryo as a scalable platform for the systematic phenotyping of mouse genetic models. We applied combinatorial indexing-based single-cell RNA sequencing3 to profile 101 embryos of 22 mutant and 4 wild-type genotypes at embryonic day 13.5, altogether profiling more than 1.6 million nuclei. The 22 mutants represent a range of anticipated phenotypic severities, from established multisystem disorders to deletions of individual regulatory regions4,5. We developed and applied several analytical frameworks for detecting differences in composition and/or gene expression across 52 cell types or trajectories. Some mutants exhibit changes in dozens of trajectories whereas others exhibit changes in only a few cell types. We also identify differences between widely used wild-type strains, compare phenotyping of gain- versus loss-of-function mutants and characterize deletions of topological associating domain boundaries. Notably, some changes are shared among mutants, suggesting that developmental pleiotropy might be 'decomposable' through further scaling of this approach. Overall, our findings show how single-cell profiling of whole embryos can enable the systematic molecular and cellular phenotypic characterization of mouse mutants with unprecedented breadth and resolution.

Mammalian embryogenesis is characterized by rapid cellular proliferation and diversification. Within a few weeks, a single-cell zygote gives rise to millions of cells expressing a panoply of molecular programs. Although intensively studied, a comprehensive delineation of the major cellular trajectories that comprise mammalian development in vivo remains elusive. Here, we set out to integrate several single-cell RNA-sequencing (scRNA-seq) datasets that collectively span mouse gastrulation and organogenesis, supplemented with new profiling of ~150,000 nuclei from approximately embryonic day 8.5 (E8.5) embryos staged in one-somite increments. Overall, we define cell states at each of 19 successive stages spanning E3.5 to E13.5 and heuristically connect them to their pseudoancestors and pseudodescendants. Although constructed through automated procedures, the resulting directed acyclic graph (TOME (trajectories of mammalian embryogenesis)) is largely consistent with our contemporary understanding of mammalian development. We leverage TOME to systematically nominate transcription factors (TFs) as candidate regulators of each cell types specification, as well as cell-type homologs across vertebrate evolution.

Poor metabolic control and host genetic predisposition are critical for diabetic kidney disease (DKD) development. The epigenome integrates information from sequence variations and metabolic alterations. Here, we performed a genome-wide methylome association analysis in 500 subjects with DKD from the Chronic Renal Insufficiency Cohort for DKD phenotypes, including glycemic control, albuminuria, kidney function, and kidney function decline. We show distinct methylation patterns associated with each phenotype. We define methylation variations that are associated with underlying nucleotide variations (methylation quantitative trait loci) and show that underlying genetic variations are important drivers of methylation changes. We implemented Bayesian multitrait colocalization analysis (moloc) and summary data-based Mendelian randomization to systematically annotate genomic regions that show association with kidney function, methylation, and gene expression. We prioritized 40 loci, where methylation and gene-expression changes likely mediate the genotype effect on kidney disease development. Functional annotation suggested the role of inflammation, specifically, apoptotic cell clearance and complement activation in kidney disease development. Our study defines methylation changes associated with DKD phenotypes, the key role of underlying genetic variations driving methylation variations, and prioritizes methylome and gene-expression changes that likely mediate the genotype effect on kidney disease pathogenesis.

Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria.

Genome-wide association studies (GWAS) for kidney function identified hundreds of risk regions; however, the causal variants, target genes, cell types, and disease mechanisms remain poorly understood. Here, we performed transcriptome- wide association studies (TWAS), summary Mendelian randomization, and MetaXcan to identify genes whose expression mediates the genotype effect on the phenotype. Our analyses identified Dachshund homolog 1 (DACH1), a cell-fate determination factor. GWAS risk variant was associated with lower DACH1 expression in human kidney tubules. Human and mouse kidney single- cell open chromatin data (snATAC-Seq) prioritized estimated glomerular filtration rate (eGFR) GWAS variants located on an intronic regulatory region in distal convoluted tubule cells. CRISPR-Cas9-mediated gene editing confirmed the role of risk variants in regulating DACH1 expression. Mice with tubule-specific Dach1 deletion developed more severe renal fibrosis both in folic acid and diabetic kidney injury models. Mice with tubule-specific Dach1 overexpression were protected from folic acid nephropathy. Single-cell RNA sequencing, chromatin immunoprecipitation, and functional analysis indicated that DACH1 controls the expression of cell cycle and myeloid chemotactic factors, contributing to macrophage infiltration and fibrosis development. In summary, integration of GWAS, TWAS, single-cell epigenome, expression analyses, gene editing, and functional validation in different mouse kidney disease models identified DACH1 as a kidney disease risk gene., Introduction More than 1 in 10 people in the US suffers from chronic kidney disease (CKD). CKD is one of the strongest risk factors for cardiovascular death. The annual mortality [...]

Sclerotinia sclerotiorum is a yield-limiting pathogen of several economically important crops, and it reproduces sexually by self-fertilization. Based on the presence of an inversion in the mating type locus, S. sclerotiorum can be grouped as inversion negative (Inv- MAT) and inversion positive (Inv+ MAT) isolates. This study was conducted to determine the prevalence of Inv- and Inv+ MAT S. sclerotiorum isolates across the United States. In total, 164 isolates from 16 hosts and 22 states were evaluated, including 87 isolates from North Dakota and northern Minnesota and 47 isolates from soybean. PCR screening was performed separately for Inv- and Inv+ MAT with specific primers. Of the two kinds of MAT homokaryons, Inv- MAT isolates were the most frequent (31.7%) and were identified in 15 states. Another 12.8% of isolates were Inv+ MAT, and were identified in 8 states. The majority (55.5%) of isolates screened were MAT heterokaryons, and these were identified from 18 states and 11 hosts. The implications of MAT heterokaryons for the biology and management of S. sclerotiorum are discussed. Key words: fungi, Sclerotinia sclerotiorum, mating type (MAT) alleles, MAT heterokaryon. Sclerotinia sclerotiorum est un pathogene qui limite le rendement de recoltes d'importance economique, et il se reproduit de maniere sexuee par autogamie. Selon la presence d'une inversion dans le locus du type sexuel, S. sclerotiorum peut se grouper en isolats negatifs pour l'inversion (Inv- MAT) et positifs pour l'inversion (Inv+ MAT). Cette etude a ete menee afin de determiner la prevalence des isolats de S. sclerotiorum Inv- MAT et Inv+ MAT a travers les Etats-Unis. Au total, 164 isolats provenant de 16 hotes et 22 etats ont ete evalues, y compris 87 isolats du Dakota du Nord et de la region nord du Minnesota, et 47 isolats provenant de la feve de soja. Un criblage par PCR a ete realise separement pour Inv- MAT et Inv+ MAT a l'aide d'amorces specifiques. Des deux types d'homocaryons MAT, les isolats Inv- MAT etaient les plus frequents (31,7 %) et ils ont ete identifies dans 15 etats. Les isolats Inv+ MAT formaient 12,8% de la population et ils ont ete identifies dans 8 etats. La majorite (55,5 %) des isolats cribles etaient des heterocaryons MAT et ils ont ete identifies dans 18 etats et sur 11 hotes. Les implications des heterocaryons MAT dans la biologie et la gestion de S. sclerotiorum sont discutees. [Traduit par la Redaction] Mots-cles : champignons, Sclerotinia sclerotiorum, alleles du type sexuel (MAT), heterocaryon MAT., Introduction Sclerotinia sclerotiorum is an ascomycete phytopathogen which attacks more than 400 plant species, including numerous economically important crops worldwide (Boland and Hall 1994). Sunflower, soybean, oilseed rape, dry bean, [...]