Selecting single cell clustering parameter values using subsampling-based robustness metrics

Background Generating and analysing single-cell data has become a widespread approach to examine tissue heterogeneity, and numerous algorithms exist for clustering these datasets to identify putative cell types with shared transcriptomic signatures. However, many of these clustering workflows rely on user-tuned parameter values, tailored to each dataset, to identify a set of biologically relevant clusters. Whereas users often develop their own intuition as to the optimal range of parameters for clustering on each data set, the lack of systematic approaches to identify this range can be daunting to new users of any given workflow. In addition, an optimal parameter set does not guarantee that all clusters are equally well-resolved, given the heterogeneity in transcriptomic signatures in most biological systems. Results Here, we illustrate a subsampling-based approach (chooseR) that simultaneously guides parameter selection and characterizes cluster robustness. Through bootstrapped iterative clustering across a range of parameters, chooseR was used to select parameter values for two distinct clustering workflows (Seurat and scVI). In each case, chooseR identified parameters that produced biologically relevant clusters from both well-characterized (human PBMC) and complex (mouse spinal cord) datasets. Moreover, it provided a simple “robustness score” for each of these clusters, facilitating the assessment of cluster quality. Conclusion chooseR is a simple, conceptually understandable tool that can be used flexibly across clustering algorithms, workflows, and datasets to guide clustering parameter selection and characterize cluster robustness

Genome engineering of isogenic human ES cells to model autism disorders.

Isogenic pluripotent stem cells are critical tools for studying human neurological diseases by allowing one to study the effects of a mutation in a fixed genetic background. Of particular interest are the spectrum of autism disorders, some of which are monogenic such as Timothy syndrome (TS); others are multigenic such as the microdeletion and microduplication syndromes of the 16p11.2 chromosomal locus. Here, we report engineered human embryonic stem cell (hESC) lines for modeling these two disorders using locus-specific endonucleases to increase the efficiency of homology-directed repair (HDR). We developed a system to: (1) computationally identify unique transcription activator-like effector nuclease (TALEN) binding sites in the genome using a new software program, TALENSeek, (2) assemble the TALEN genes by combining golden gate cloning with modified constructs from the FLASH protocol, and (3) test the TALEN pairs in an amplification-based HDR assay that is more sensitive than the typical non-homologous end joining assay. We applied these methods to identify, construct, and test TALENs that were used with HDR donors in hESCs to generate an isogenic TS cell line in a scarless manner and to model the 16p11.2 copy number disorder without modifying genomic loci with high sequence similarity

Translational approaches to understanding resilience to Alzheimer\u27s disease.

Individuals who maintain cognitive function despite high levels of Alzheimer\u27s disease (AD)-associated pathology are said to be \u27resilient\u27 to AD. Identifying mechanisms underlying resilience represents an exciting therapeutic opportunity. Human studies have identified a number of molecular and genetic factors associated with resilience, but the complexity of these cohorts prohibits a complete understanding of which factors are causal or simply correlated with resilience. Genetically and phenotypically diverse mouse models of AD provide new and translationally relevant opportunities to identify and prioritize new resilience mechanisms for further cross-species investigation. This review will discuss insights into resilience gained from both human and animal studies and highlight future approaches that may help translate these insights into therapeutics designed to prevent or delay AD-related dementia

Molecular Logic of Spinocerebellar Tract Neuron Diversity and Connectivity

Coordinated motor behaviors depend on feedback communication between peripheral sensory systems and central circuits in the brain and spinal cord. Relay of muscle- and tendon-derived sensory information to the CNS is facilitated by functionally and anatomically diverse groups of spinocerebellar tract neurons (SCTNs), but the molecular logic by which SCTN diversity and connectivity is achieved is poorly understood. We used single-cell RNA sequencing and genetic manipulations to define the mechanisms governing the molecular profile and organization of SCTN subtypes. We found that SCTNs relaying proprioceptive sensory information from limb and axial muscles are generated through segmentally restricted actions of specific Hox genes. Loss of Hox function disrupts SCTN-subtype-specific transcriptional programs, leading to defects in the connections between proprioceptive sensory neurons, SCTNs, and the cerebellum. These results indicate that Hox-dependent genetic programs play essential roles in the assembly of neural circuits necessary for communication between the brain and spinal cord. © 2019 The Author(s)Baek et al. show that Hox-transcription-factor-dependent programs govern the specification and connectivity of spinal interneurons that relay muscle-derived sensory information to the cerebellum. These findings shed light on the development of neural circuits required for proprioception—the perception of body position. © 2019 The Author(s)1

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development. DOI: http://dx.doi.org/10.7554/eLife.20487.00

NOS1AP is a novel molecular target and critical factor in TDP-43 pathology

Cappelli et al. reported that Nitric Oxide Synthase 1 Adaptor Protein is a co-regulated transcript of the TAR DNA-binding protein 43 kDa, reduced in amyotrophic lateral sclerosis and frontotemporal lobar degeneration patients with TAR DNA-binding protein 43 kDa pathology. Overall, their results highlight Nitric Oxide Synthase 1 Adaptor Protein as a novel druggable disease-relevant gene in TAR DNA-binding protein 43 kDa-related proteinopathies.Many lines of evidence have highlighted the role played by heterogeneous nuclear ribonucleoproteins in amyotrophic lateral sclerosis. In this study, we have aimed to identify transcripts co-regulated by TAR DNA-binding protein 43 kDa and highly conserved heterogeneous nuclear ribonucleoproteins which have been previously shown to regulate TAR DNA-binding protein 43 kDa toxicity (deleted in azoospermia-associated protein 1, heterogeneous nuclear ribonucleoprotein -Q, -D, -K and -U). Using the transcriptome analyses, we have uncovered that Nitric Oxide Synthase 1 Adaptor Protein mRNA is a direct TAR DNA-binding protein 43 kDa target, and in flies, its modulation alone can rescue TAR DNA-binding protein 43 kDa pathology. In primary mouse cortical neurons, we show that TAR DNA-binding protein 43 kDa mediated downregulation of Nitric Oxide Synthase 1 Adaptor Protein expression strongly affects the NMDA-receptor signalling pathway. In human patients, the downregulation of Nitric Oxide Synthase 1 Adaptor Protein mRNA strongly correlates with TAR DNA-binding protein 43 kDa proteinopathy as measured by cryptic Stathmin-2 and Unc-13 homolog A cryptic exon inclusion. Overall, our results demonstrate that Nitric Oxide Synthase 1 Adaptor Protein may represent a novel disease-relevant gene, potentially suitable for the development of new therapeutic strategies

Genome-wide structural variant analysis identifies risk loci for non-Alzheimer’s dementias

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer’s dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Discovering sparse transcription factor codes for cell states and state transitions during development

Computational analysis of gene expression to determine both the sequence of lineage choices made by multipotent cells and to identify the genes influencing these decisions is challenging. Here we discover a pattern in the expression levels of a sparse subset of genes among cell types in B- and T-cell developmental lineages that correlates with developmental topologies. We develop a statistical framework using this pattern to simultaneously infer lineage transitions and the genes that determine these relationships. We use this technique to reconstruct the early hematopoietic and intestinal developmental trees. We extend this framework to analyze single-cell RNA-seq data from early human cortical development, inferring a neocortical-hindbrain split in early progenitor cells and the key genes that could control this lineage decision. Our work allows us to simultaneously infer both the identity and lineage of cell types as well as a small set of key genes whose expression patterns reflect these relationships. DOI: http://dx.doi.org/10.7554/eLife.20488.00

Focused Ultrasound-Mediated Blood–Brain Barrier Opening Best Promotes Neuroimmunomodulation through Brain Macrophage Redistribution

Neuroimmunomodulation is a promising form of drug-free treatment for neurological diseases ranging from Alzheimer’s disease to depression. The evidence supporting the efficacy of focused ultrasound (FUS) neuroimmunomodulation is encouraging; however, the method has yet to be standardized, and its mechanism remains poorly understood. Methods of FUS neuroimmunomodulation can be categorized into three paradigms based on the parameters used. In the first paradigm, focused ultrasound blood–brain barrier opening (FUS-BBBO) combines FUS with microbubbles (MB) to transiently and safely induce BBB opening. In the second paradigm, focused ultrasound neuromodulation (FUS-N) harnesses the acoustic effects of FUS alone (without MB). In the third paradigm, focused ultrasound with microbubbles without BBBO (FUS + MB) combines MB with FUS below the BBBO pressure threshold—harnessing the mechanical effects of FUS without opening the barrier. Due to the recent evidence of brain macrophage modulation in response to FUS-BBBO, we provide the first direct comparison of brain macrophage modulation between all three paradigms both in the presence and absence of Alzheimer’s disease (AD) pathology. Flow cytometry and single-cell sequencing are employed to identify FUS-BBBO as the FUS paradigm, which maximizes brain macrophage modulation, including an increase in the population of neuroprotective, disease-associated microglia and direct correlation between treatment cavitation dose and brain macrophage phagocytosis. Next, we combine spatial and single-cell transcriptomics with immunohistochemical validation to provide the first characterization of brain macrophage distribution in response to FUS-BBBO. Given their relevance within neurodegeneration and perturbation response, we emphasize the analysis of three brain macrophage populations—disease- and interferon-associated microglia and central-nervous-system-associated macrophages. We find and validate the redistribution of each population with an overall trend toward increased interaction with the brain–cerebrospinal fluid barrier (BCSFB) after FUS-BBBO, an effect that is found to be more pronounced in the presence of disease pathology. This study addresses the prior lack of FUS neuroimmunomodulation paradigm optimization and mechanism characterization, identifying that FUS-BBBO best modulates brain macrophage response via complex redistribution