Protocol for immunophenotyping out-of-hospital cardiac arrest patients.

Immunophenotyping of out-of-hospital cardiac arrest (OHCA) patients is of increasing interest but has challenges. Here, we describe steps for the design of the clinical cohort, planning patient enrollment and sample collection, and ethical review of the study protocol. We detail procedures for blood sample collection and cryopreservation of peripheral blood mononuclear cells (PBMCs). We detail steps to modulate immune checkpoints in OHCA PBMC ex vivo. This protocol also has relevance for immunophenotyping other types of critical illness. For complete details on the use and execution of this protocol, please refer to Tamura et al. (2023).1.

Genetic and epigenetic features of bilateral Wilms tumor predisposition in patients from the Children's Oncology Group AREN18B5-Q.

Developing synchronous bilateral Wilms tumor suggests an underlying (epi)genetic predisposition. Here, we evaluate this predisposition in 68 patients using whole exome or genome sequencing (n = 85 tumors from 61 patients with matched germline blood DNA), RNA-seq (n = 99 tumors), and DNA methylation analysis (n = 61 peripheral blood, n = 29 non-diseased kidney, n = 99 tumors). We determine the predominant events for bilateral Wilms tumor predisposition: 1)pre-zygotic germline genetic variants readily detectable in blood DNA [WT1 (14.8%), NYNRIN (6.6%), TRIM28 (5%), and BRCA-related genes (5%)] or 2)post-zygotic epigenetic hypermethylation at 11p15.5 H19/ICR1 that may require analysis of multiple tissue types for diagnosis. Of 99 total tumor specimens, 16 (16.1%) have 11p15.5 normal retention of imprinting, 25 (25.2%) have 11p15.5 copy neutral loss of heterozygosity, and 58 (58.6%) have 11p15.5 H19/ICR1 epigenetic hypermethylation (loss of imprinting). Here, we ascertain the epigenetic and genetic modes of bilateral Wilms tumor predisposition.

A Review of Single-Cell RNA-Seq Annotation, Integration, and Cell-Cell Communication.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular biology at an unprecedented resolution, enabling the characterization of cellular heterogeneity, identification of rare but significant cell types, and exploration of cell-cell communications and interactions. Its broad applications span both basic and clinical research domains. In this comprehensive review, we survey the current landscape of scRNA-seq analysis methods and tools, focusing on count modeling, cell-type annotation, data integration, including spatial transcriptomics, and the inference of cell-cell communication. We review the challenges encountered in scRNA-seq analysis, including issues of sparsity or low expression, reliability of cell annotation, and assumptions in data integration, and discuss the potential impact of suboptimal clustering and differential expression analysis tools on downstream analyses, particularly in identifying cell subpopulations. Finally, we discuss recent advancements and future directions for enhancing scRNA-seq analysis. Specifically, we highlight the development of novel tools for annotating single-cell data, integrating and interpreting multimodal datasets covering transcriptomics, epigenomics, and proteomics, and inferring cellular communication networks. By elucidating the latest progress and innovation, we provide a comprehensive overview of the rapidly advancing field of scRNA-seq analysis.

Genome-wide mapping of cancer dependency genes and genetic modifiers of chemotherapy in high-risk hepatoblastoma.

A lack of relevant genetic models and cell lines hampers our understanding of hepatoblastoma pathogenesis and the development of new therapies for this neoplasm. Here, we report an improved MYC-driven hepatoblastoma-like murine model that recapitulates the pathological features of embryonal type of hepatoblastoma, with transcriptomics resembling the high-risk gene signatures of the human disease. Single-cell RNA-sequencing and spatial transcriptomics identify distinct subpopulations of hepatoblastoma cells. After deriving cell lines from the mouse model, we map cancer dependency genes using CRISPR-Cas9 screening and identify druggable targets shared with human hepatoblastoma (e.g., CDK7, CDK9, PRMT1, PRMT5). Our screen also reveals oncogenes and tumor suppressor genes in hepatoblastoma that engage multiple, druggable cancer signaling pathways. Chemotherapy is critical for human hepatoblastoma treatment. A genetic mapping of doxorubicin response by CRISPR-Cas9 screening identifies modifiers whose loss-of-function synergizes with (e.g., PRKDC) or antagonizes (e.g., apoptosis genes) the effect of chemotherapy. The combination of PRKDC inhibition and doxorubicin-based chemotherapy greatly enhances therapeutic efficacy. These studies provide a set of resources including disease models suitable for identifying and validating potential therapeutic targets in human high-risk hepatoblastoma.

Single-cell transcriptomics reveal a hyperacute cytokine and immune checkpoint axis after cardiac arrest in patients with poor neurological outcome.

BACKGROUND: Most patients hospitalized after cardiac arrest (CA) die because of neurological injury. The systemic inflammatory response after CA is associated with neurological injury and mortality but remains poorly defined. METHODS: We determine the innate immune network induced by clinical CA at single-cell resolution. FINDINGS: Immune cell states diverge as early as 6 h post-CA between patients with good or poor neurological outcomes 30 days after CA. Nectin-2+ monocyte and Tim-3+ natural killer (NK) cell subpopulations are associated with poor outcomes, and interactome analysis highlights their crosstalk via cytokines and immune checkpoints. Ex vivo studies of peripheral blood cells from CA patients demonstrate that immune checkpoints are a compensatory mechanism against inflammation after CA. Interferon γ (IFNγ)/interleukin-10 (IL-10) induced Nectin-2 on monocytes; in a negative feedback loop, Nectin-2 suppresses IFNγ production by NK cells. CONCLUSIONS: The initial hours after CA may represent a window for therapeutic intervention in the resolution of inflammation via immune checkpoints. FUNDING: This work was supported by funding from the American Heart Association, Brigham and Women's Hospital Department of Medicine, the Evergreen Innovation Fund, and the National Institutes of Health.

The Genetic and Epigenetic Features of Bilateral Wilms Tumor Predisposition: A Report from the Children's Oncology Group AREN18B5-Q Study.

This study comprehensively evaluated the landscape of genetic and epigenetic events that predispose to synchronous bilateral Wilms tumor (BWT). We performed whole exome or whole genome sequencing, total-strand RNA-seq, and DNA methylation analysis using germline and/or tumor samples from 68 patients with BWT from St. Jude Children's Research Hospital and the Children's Oncology Group. We found that 25/61 (41%) of patients evaluated harbored pathogenic or likely pathogenic germline variants, with WT1 (14.8%), NYNRIN (6.6%), TRIM28 (5%) and the BRCA-related genes (5%) BRCA1, BRCA2, and PALB2 being most common. Germline WT1 variants were strongly associated with somatic paternal uniparental disomy encompassing the 11p15.5 and 11p13/WT1 loci and subsequent acquired pathogenic CTNNB1 variants. Somatic coding variants or genome-wide copy number alterations were almost never shared between paired synchronous BWT, suggesting that the acquisition of independent somatic variants leads to tumor formation in the context of germline or early embryonic, post-zygotic initiating events. In contrast, 11p15.5 status (loss of heterozygosity, loss or retention of imprinting) was shared among paired synchronous BWT in all but one case. The predominant molecular events for BWT predisposition include pathogenic germline variants or post-zygotic epigenetic hypermethylation at the 11p15.5 H19/ICR1 locus (loss of imprinting). This study demonstrates that post-zygotic somatic mosaicism for 11p15.5 hypermethylation/loss of imprinting is the single most common initiating molecular event predisposing to BWT. Evidence of somatic mosaicism for 11p15.5 loss of imprinting was detected in leukocytes of a cohort of BWT patients and long-term survivors, but not in unilateral Wilms tumor patients and long-term survivors or controls, further supporting the hypothesis that post-zygotic 11p15.5 alterations occurred in the mesoderm of patients who go on to develop BWT. Due to the preponderance of BWT patients with demonstrable germline or early embryonic tumor predisposition, BWT exhibits a unique biology when compared to unilateral Wilms tumor and therefore warrants continued refinement of its own treatment-relevant biomarkers which in turn may inform directed treatment strategies in the future.

Identification and targeting of a HES1-YAP1-CDKN1C functional interaction in fusion-negative rhabdomyosarcoma.

Rhabdomyosarcoma (RMS), a cancer characterized by features of skeletal muscle, is the most common soft-tissue sarcoma of childhood. With 5-year survival rates among high-risk groups at < 30%, new therapeutics are desperately needed. Previously, using a myoblast-based model of fusion-negative RMS (FN-RMS), we found that expression of the Hippo pathway effector transcriptional coactivator YAP1 (YAP1) permitted senescence bypass and subsequent transformation to malignant cells, mimicking FN-RMS. We also found that YAP1 engages in a positive feedback loop with Notch signaling to promote FN-RMS tumorigenesis. However, we could not identify an immediate downstream impact of this Hippo-Notch relationship. Here, we identify a HES1-YAP1-CDKN1C functional interaction, and show that knockdown of the Notch effector HES1 (Hes family BHLH transcription factor 1) impairs growth of multiple FN-RMS cell lines, with knockdown resulting in decreased YAP1 and increased CDKN1C expression. In silico mining of published proteomic and transcriptomic profiles of human RMS patient-derived xenografts revealed the same pattern of HES1-YAP1-CDKN1C expression. Treatment of FN-RMS cells in vitro with the recently described HES1 small-molecule inhibitor, JI130, limited FN-RMS cell growth. Inhibition of HES1 in vivo via conditional expression of a HES1-directed shRNA or JI130 dosing impaired FN-RMS tumor xenograft growth. Lastly, targeted transcriptomic profiling of FN-RMS xenografts in the context of HES1 suppression identified associations between HES1 and RAS-MAPK signaling. In summary, these in vitro and in vivo preclinical studies support the further investigation of HES1 as a therapeutic target in FN-RMS.

Molecular evolution and the decline of purifying selection with age.

Life history theory predicts that the intensity of selection declines with age, and this trend should impact how genes expressed at different ages evolve. Here we find consistent relationships between a gene's age of expression and patterns of molecular evolution in two mammals (the human Homo sapiens and the mouse Mus musculus) and two insects (the malaria mosquito Anopheles gambiae and the fruit fly Drosophila melanogaster). When expressed later in life, genes fix nonsynonymous mutations more frequently, are more polymorphic for nonsynonymous mutations, and have shorter evolutionary lifespans, relative to those expressed early. The latter pattern is explained by a simple evolutionary model. Further, early-expressed genes tend to be enriched in similar gene ontology terms across species, while late-expressed genes show no such consistency. In humans, late-expressed genes are more likely to be linked to cancer and to segregate for dominant disease-causing mutations. Last, the effective strength of selection (Ne s) decreases and the fraction of beneficial mutations increases with a gene's age of expression. These results are consistent with the diminishing efficacy of purifying selection with age, as proposed by Medawar's classic hypothesis for the evolution of senescence, and provide links between life history theory and molecular evolution.

Predicting the Evolution of Sexual Dimorphism in Gene Expression.

Sexual dimorphism in gene expression is likely to be the underlying source of dimorphism in a variety of traits. Many analyses implicitly make the assumption that dimorphism only evolves when selection favors different phenotypes in the two sexes, although theory makes clear that it can also evolve as an indirect response to other kinds of selection. Furthermore, previous analyses consider the evolution of a single transcript or trait at a time, ignoring the genetic covariance with other transcripts and traits. We first show which aspects of the genetic-variance-covariance matrix, G, affect dimorphism when these assumptions about selection are relaxed. We then reanalyze gene expression data from Drosophila melanogaster with these predictions in mind. Dimorphism of gene expression for individual transcripts shows the signature of both direct selection for dimorphism and indirect responses to selection. To account for the effect of measurement error on evolutionary predictions, we estimated a G matrix for eight linear combinations of expression traits. Sex-specific genetic variances in female- and male-biased transcription, as well as one relatively unbiased combination, were quite unequal, ensuring that most forms of selection on these traits will have large effects on dimorphism. Predictions of response to selection based on the whole G matrix showed that sexually concordant and antagonistic selection are equally capable of changing sexual dimorphism. In addition, the indirect responses of dimorphism due to cross-trait covariances were quite substantial. The assumption that sexual dimorphism in transcription is an adaptation could be incorrect in many specific cases.

Latent cellular analysis robustly reveals subtle diversity in large-scale single-cell RNA-seq data.

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing the cell-to-cell variation and cellular dynamics in populations which appear homogeneous otherwise in basic and translational biological research. However, significant challenges arise in the analysis of scRNA-seq data, including the low signal-to-noise ratio with high data sparsity, potential batch effects, scalability problems when hundreds of thousands of cells are to be analyzed among others. The inherent complexities of scRNA-seq data and dynamic nature of cellular processes lead to suboptimal performance of many currently available algorithms, even for basic tasks such as identifying biologically meaningful heterogeneous subpopulations. In this study, we developed the Latent Cellular Analysis (LCA), a machine learning-based analytical pipeline that combines cosine-similarity measurement by latent cellular states with a graph-based clustering algorithm. LCA provides heuristic solutions for population number inference, dimension reduction, feature selection, and control of technical variations without explicit gene filtering. We show that LCA is robust, accurate, and powerful by comparison with multiple state-of-the-art computational methods when applied to large-scale real and simulated scRNA-seq data. Importantly, the ability of LCA to learn from representative subsets of the data provides scalability, thereby addressing a significant challenge posed by growing sample sizes in scRNA-seq data analysis.

Complex interactions between day length and diurnal patterns of gene expression drive photoperiodic responses in a perennial C4 grass.

Photoperiod is a key environmental cue affecting flowering and biomass traits in plants. Key components of the photoperiodic flowering pathway have been identified in many species, but surprisingly few studies have globally examined the diurnal rhythm of gene expression with changes in day length. Using a cost-effective 3'-Tag RNA sequencing strategy, we characterize 9,010 photoperiod responsive genes with strict statistical testing across a diurnal time series in the C4 perennial grass, Panicum hallii. We show that the vast majority of photoperiod responses are driven by complex interactions between day length and sampling periods. A fine-scale contrast analysis at each sampling time revealed a detailed picture of the temporal reprogramming of cis-regulatory elements and biological processes under short- and long-day conditions. Phase shift analysis reveals quantitative variation among genes with photoperiod-dependent diurnal patterns. In addition, we identify three photoperiod enriched transcription factor families with key genes involved in photoperiod flowering regulatory networks. Finally, coexpression networks analysis of GIGANTEA homolog predicted 1,668 potential coincidence partners, including five well-known GI-interacting proteins. Our results not only provide a resource for understanding the mechanisms of photoperiod regulation in perennial grasses but also lay a foundation to increase biomass yield in biofuel crops.

Inversions are bigger on the X chromosome.

In many insects, X-linked inversions fix at a higher rate and are much less polymorphic than autosomal inversions. Here, we report that in Drosophila, X-linked inversions also capture 67% more genes. We estimated the number of genes captured through an approximate Bayesian computational analysis of gene orders in nine species of Drosophila. X-linked inversions fixed with a significantly larger gene content. Further, X-linked inversions of intermediate size enjoy highest fixation rate, while the fixation rate of autosomal inversions decreases with size. A less detailed analysis in Anopheles suggests a similar pattern holds in mosquitoes. We develop a population genetic model that assumes the fitness effects of inversions scale with the number of genes captured. We show that the same conditions that lead to a higher fixation rate also produce a larger size for inversions on the X.

Systems genetic analysis of inversion polymorphisms in the malaria mosquito Anopheles gambiae.

Inversion polymorphisms in the African malaria vector Anopheles gambiae segregate along climatic gradients of aridity. Despite indirect evidence of their adaptive significance, little is known of the phenotypic targets of selection or the underlying genetic mechanisms. Here we adopt a systems genetics approach to explore the interaction of two inversions on opposite arms of chromosome 2 with gender, climatic conditions, and one another. We measure organismal traits and transcriptional profiles in 8-d-old adults of both sexes and four alternative homokaryotypic classes reared under two alternative climatic regimes. We show that karyotype strongly influences both organismal traits and transcriptional profiles but that the strength and direction of the effects depend upon complex interactions with gender and environmental conditions and between inversions on independent arms. Our data support the suppressed recombination model for the role of inversions in local adaptation, and-supported by transcriptional and physiological measurements following perturbation with the drug rapamycin-suggest that one mechanism underlying their adaptive role may be the maintenance of energy homeostasis.

Metabolic signaling directs the reciprocal lineage decisions of αß and γδ T cells.

The interaction between extrinsic factors and intrinsic signal strength governs thymocyte development, but the mechanisms linking them remain elusive. We report that mechanistic target of rapamycin complex 1 (mTORC1) couples microenvironmental cues with metabolic programs to orchestrate the reciprocal development of two fundamentally distinct T cell lineages, the αß and γδ T cells. Developing thymocytes dynamically engage metabolic programs including glycolysis and oxidative phosphorylation, as well as mTORC1 signaling. Loss of RAPTOR-mediated mTORC1 activity impairs the development of αß T cells but promotes γδ T cell generation, associated with disrupted metabolic remodeling of oxidative and glycolytic metabolism. Mechanistically, we identify mTORC1-dependent control of reactive oxygen species production as a key metabolic signal in mediating αß and γδ T cell development, and perturbation of redox homeostasis impinges upon thymocyte fate decisions and mTORC1-associated phenotypes. Furthermore, single-cell RNA sequencing and genetic dissection reveal that mTORC1 links developmental signals from T cell receptors and NOTCH to coordinate metabolic activity and signal strength. Our results establish mTORC1-driven metabolic signaling as a decisive factor for reciprocal αß and γδ T cell development and provide insight into metabolic control of cell signaling and fate decisions.

Sex Differences in Recombination in Sticklebacks.

Recombination often differs markedly between males and females. Here we present the first analysis of sex-specific recombination in Gasterosteus sticklebacks. Using whole-genome sequencing of 15 crosses between G. aculeatus and G. nipponicus, we localized 698 crossovers with a median resolution of 2.3 kb. We also used a bioinformatic approach to infer historical sex-averaged recombination patterns for both species. Recombination is greater in females than males on all chromosomes, and overall map length is 1.64 times longer in females. The locations of crossovers differ strikingly between sexes. Crossovers cluster toward chromosome ends in males, but are distributed more evenly across chromosomes in females. Suppression of recombination near the centromeres in males causes crossovers to cluster at the ends of long arms in acrocentric chromosomes, and greatly reduces crossing over on short arms. The effect of centromeres on recombination is much weaker in females. Genomic differentiation between G. aculeatus and G. nipponicus is strongly correlated with recombination rate, and patterns of differentiation along chromosomes are strongly influenced by male-specific telomere and centromere effects. We found no evidence for fine-scale correlations between recombination and local gene content in either sex. We discuss hypotheses for the origin of sexual dimorphism in recombination and its consequences for sexually antagonistic selection and sex chromosome evolution.

Environmental Plasticity in the Intersexual Correlation and Sex Bias of Gene Expression.

Intersexual genetic correlations are expected to constrain the evolution of sexual dimorphic traits, including the degree of sex-biased gene expression. Consistent with that expectation, studies in fruit flies and birds have reported that genes whose expression has a strong intersexual genetic correlation (rMF) show a lower level of sex-biased expression (SBE). However, it is known that both rMF and SBE can be affected by the environment. It is therefore unclear whether there is a consistent relationship between these 2 quantities across multiple environments. In this paper, we study this relationship in the African malaria mosquito Anopheles gambiae. We show that both rMF and SBE change between environments. The change in SBE across environments is significantly correlated with dN/dS: greater changes in SBE are associated with higher values of dN/dS. Furthermore, the relationship between rMF and SBE is sensitive to the environment. We conclude that this relationship is sufficiently plastic that environmental effects should be considered in future studies.

Extensive Genetic Differentiation between Homomorphic Sex Chromosomes in the Mosquito Vector, Aedes aegypti.

Mechanisms and evolutionary dynamics of sex-determination systems are of particular interest in insect vectors of human pathogens like mosquitoes because novel control strategies aim to convert pathogen-transmitting females into nonbiting males, or rely on accurate sexing for the release of sterile males. In Aedes aegypti, the main vector of dengue and Zika viruses, sex determination is governed by a dominant male-determining locus, previously thought to reside within a small, nonrecombining, sex-determining region (SDR) of an otherwise homomorphic sex chromosome. Here, we provide evidence that sex chromosomes in Ae. aegypti are genetically differentiated between males and females over a region much larger than the SDR. Our linkage mapping intercrosses failed to detect recombination between X and Y chromosomes over a 123-Mbp region (40% of their physical length) containing the SDR. This region of reduced male recombination overlapped with a smaller 63-Mbp region (20% of the physical length of the sex chromosomes) displaying high male-female genetic differentiation in unrelated wild populations from Brazil and Australia and in a reference laboratory strain originating from Africa. In addition, the sex-differentiated genomic region was associated with a significant excess of male-to-female heterozygosity and contained a small cluster of loci consistent with Y-specific null alleles. We demonstrate that genetic differentiation between sex chromosomes is sufficient to assign individuals to their correct sex with high accuracy. We also show how data on allele frequency differences between sexes can be used to estimate linkage disequilibrium between loci and the sex-determining locus. Our discovery of large-scale genetic differentiation between sex chromosomes in Ae. aegypti lays a new foundation for mapping and population genomic studies, as well as for mosquito control strategies targeting the sex-determination pathway.

Sex-Specific Selection and Sex-Biased Gene Expression in Humans and Flies.

Sexual dimorphism results from sex-biased gene expression, which evolves when selection acts differently on males and females. While there is an intimate connection between sex-biased gene expression and sex-specific selection, few empirical studies have studied this relationship directly. Here we compare the two on a genome-wide scale in humans and flies. We find a distinctive "Twin Peaks" pattern in humans that relates the strength of sex-specific selection, quantified by genetic divergence between male and female adults at autosomal loci, to the degree of sex-biased expression. Genes with intermediate degrees of sex-biased expression show evidence of ongoing sex-specific selection, while genes with either little or completely sex-biased expression do not. This pattern apparently results from differential viability selection in males and females acting in the current generation. The Twin Peaks pattern is also found in Drosophila using a different measure of sex-specific selection acting on fertility. We develop a simple model that successfully recapitulates the Twin Peaks. Our results suggest that many genes with intermediate sex-biased expression experience ongoing sex-specific selection in humans and flies.

Radical remodeling of the Y chromosome in a recent radiation of malaria mosquitoes.

Y chromosomes control essential male functions in many species, including sex determination and fertility. However, because of obstacles posed by repeat-rich heterochromatin, knowledge of Y chromosome sequences is limited to a handful of model organisms, constraining our understanding of Y biology across the tree of life. Here, we leverage long single-molecule sequencing to determine the content and structure of the nonrecombining Y chromosome of the primary African malaria mosquito, Anopheles gambiae We find that the An. gambiae Y consists almost entirely of a few massively amplified, tandemly arrayed repeats, some of which can recombine with similar repeats on the X chromosome. Sex-specific genome resequencing in a recent species radiation, the An. gambiae complex, revealed rapid sequence turnover within An. gambiae and among species. Exploiting 52 sex-specific An. gambiae RNA-Seq datasets representing all developmental stages, we identified a small repertoire of Y-linked genes that lack X gametologs and are not Y-linked in any other species except An. gambiae, with the notable exception of YG2, a candidate male-determining gene. YG2 is the only gene conserved and exclusive to the Y in all species examined, yet sequence similarity to YG2 is not detectable in the genome of a more distant mosquito relative, suggesting rapid evolution of Y chromosome genes in this highly dynamic genus of malaria vectors. The extensive characterization of the An. gambiae Y provides a long-awaited foundation for studying male mosquito biology, and will inform novel mosquito control strategies based on the manipulation of Y chromosomes.