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Background: During cardiomyocyte maturation, the centrosome, which functions as a microtubule organizing center in cardiomyocytes, undergoes dramatic structural reorganization where its components reorganize from being localized at the centriole to the nuclear envelope. This developmentally programmed process, referred to as centrosome reduction, has been previously associated with cell cycle exit. However, understanding of how this process influences cardiomyocyte cell biology, and whether its disruption results in human cardiac disease, remains unknown. We studied this phenomenon in an infant with a rare case of infantile dilated cardiomyopathy (iDCM) who presented with left ventricular ejection fraction of 18% and disrupted sarcomere and mitochondria structure. Methods: We performed an analysis beginning with an infant who presented with a rare case of iDCM. We derived induced pluripotent stem cells from the patient to model iDCM in vitro. We performed whole exome sequencing on the patient and his parents for causal gene analysis. CRISPR/Cas9-mediated gene knockout and correction in vitro were used to confirm whole exome sequencing results. Zebrafish and Drosophila models were used for in vivo validation of the causal gene. Matrigel mattress technology and single-cell RNA sequencing were used to characterize iDCM cardiomyocytes further. Results: Whole exome sequencing and CRISPR/Cas9 gene knockout/correction identified RTTN , the gene encoding the centrosomal protein RTTN (rotatin), as the causal gene underlying the patient’s condition, representing the first time a centrosome defect has been implicated in a nonsyndromic dilated cardiomyopathy. Genetic knockdowns in zebrafish and Drosophila confirmed an evolutionarily conserved requirement of RTTN for cardiac structure and function. Single-cell RNA sequencing of iDCM cardiomyocytes showed impaired maturation of iDCM cardiomyocytes, which underlie the observed cardiomyocyte structural and functional deficits. We also observed persistent localization of the centrosome at the centriole, contrasting with expected programmed perinuclear reorganization, which led to subsequent global microtubule network defects. In addition, we identified a small molecule that restored centrosome reorganization and improved the structure and contractility of iDCM cardiomyocytes. Conclusions: This study is the first to demonstrate a case of human disease caused by a defect in centrosome reduction. We also uncovered a novel role for RTTN in perinatal cardiac development and identified a potential therapeutic strategy for centrosome-related iDCM. Future study aimed at identifying variants in centrosome components may uncover additional contributors to human cardiac disease.

Bipolar disorder is an often-severe mental health condition characterized by alternation between extreme mood states of mania and depression. Despite strong heritability and the recent identification of 64 common variant risk loci of small effect, pathophysiological mechanisms remain unknown. Here, we analyzed genome sequences from 41 multiply-affected pedigrees and identified variants in 741 genes with nominally significant linkage or association with bipolar disorder. These 741 genes overlapped known risk genes for neurodevelopmental disorders and clustered within gene networks enriched for synaptic and nuclear functions. The top variant in this analysis - prioritized by statistical association, predicted deleteriousness, and network centrality - was a missense variant in the gene encoding D-amino acid oxidase (DAOG131V). Heterologous expression of DAOG131V in human cells resulted in decreased DAO protein abundance and enzymatic activity. In a knock-in mouse model of DAOG131, DaoG130V/+, we similarly found decreased DAO protein abundance in hindbrain regions, as well as enhanced stress susceptibility and blunted behavioral responses to pharmacological inhibition of N-methyl-D-aspartate receptors (NMDARs). RNA sequencing of cerebellar tissue revealed that DaoG130V resulted in decreased expression of two gene networks that are enriched for synaptic functions and for genes expressed, respectively, in Purkinje neurons or granule neurons. These gene networks were also down-regulated in the cerebellum of patients with bipolar disorder compared to healthy controls and were enriched for additional rare variants associated with bipolar disorder risk. These findings implicate dysregulation of NMDAR signaling and of gene expression in cerebellar neurons in bipolar disorder pathophysiology and provide insight into its genetic architecture.

During mammalian development, differences in chromatin state coincide with cellular differentiation and reflect changes in the gene regulatory landscape1. In the developing brain, cell fate specification and topographic identity are important for defining cell identity2 and confer selective vulnerabilities to neurodevelopmental disorders3. Here, to identify cell-type-specific chromatin accessibility patterns in the developing human brain, we used a single-cell assay for transposase accessibility by sequencing (scATAC-seq) in primary tissue samples from the human forebrain. We applied unbiased analyses to identify genomic loci that undergo extensive cell-type- and brain-region-specific changes in accessibility during neurogenesis, and an integrative analysis to predict cell-type-specific candidate regulatory elements. We found that cerebral organoids recapitulate most putative cell-type-specific enhancer accessibility patterns but lack many cell-type-specific open chromatin regions that are found in vivo. Systematic comparison of chromatin accessibility across brain regions revealed unexpected diversity among neural progenitor cells in the cerebral cortex and implicated retinoic acid signalling in the specification of neuronal lineage identity in the prefrontal cortex. Together, our results reveal the important contribution of chromatin state to the emerging patterns of cell type diversity and cell fate specification and provide a blueprint for evaluating the fidelity and robustness of cerebral organoids as a model for cortical development., Analysis of chromatin state at a single-cell level in samples of developing human forebrain demonstrate both cell-type-specific and region-specific changes during neurogenesis.

Scalable technologies to sequence the transcriptomes and epigenomes of single cells are transforming our understanding of cell types and cell states. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative Cell Census Network (BICCN) is applying these technologies at unprecedented scale to map the cell types in the mammalian brain. In an effort to increase data FAIRness (Findable, Accessible, Interoperable, Reusable), the NIH has established repositories to make data generated by the BICCN and related BRAIN Initiative projects accessible to the broader research community. Here, we describe the Neuroscience Multi-Omic Archive (NeMO Archive; nemoarchive.org), which serves as the primary repository for genomics data from the BRAIN Initiative. Working closely with other BRAIN Initiative researchers, we have organized these data into a continually expanding, curated repository, which contains transcriptomic and epigenomic data from over 50 million brain cells, including single-cell genomic data from all of the major regions of the adult and prenatal human and mouse brains, as well as substantial single-cell genomic data from non-human primates. We make available several tools for accessing these data, including a searchable web portal, a cloud-computing interface for large-scale data processing (implemented on Terra, terra.bio), and a visualization and analysis platform, NeMO Analytics (nemoanalytics.org).

Huntington's disease (HD) is a dominantly inherited neurodegenerative disorder caused by a trinucleotide expansion in exon 1 of the huntingtin (HTT) gene. Cell death in HD occurs primarily in striatal medium spiny neurons (MSNs), but the involvement of specific MSN subtypes and of other striatal cell types remains poorly understood. To gain insight into cell type-specific disease processes, we studied the nuclear transcriptomes of 4524 cells from the striatum of a genetically precise knock-in mouse model of the HD mutation, Htt(Q175/+), and from wild-type controls. We used 14- to 15-month-old male mice, a time point at which multiple behavioral, neuroanatomical, and neurophysiological changes are present but at which there is no known cell death. Thousands of differentially expressed genes (DEGs) were distributed across most striatal cell types, including transcriptional changes in glial populations that are not apparent from RNA-seq of bulk tissue. Reconstruction of cell type-specific transcriptional networks revealed a striking pattern of bidirectional dysregulation for many cell type-specific genes. Typically, these genes were repressed in their primary cell type, yet de-repressed in other striatal cell types. Integration with existing epigenomic and transcriptomic data suggest that partial loss-of-function of the polycomb repressive complex 2 (PRC2) may underlie many of these transcriptional changes, leading to deficits in the maintenance of cell identity across virtually all cell types in the adult striatum. SIGNIFICANCE STATEMENT Huntington's disease (HD) is a dominantly inherited neurodegenerative disorder characterized by specific loss of medium spiny neurons (MSNs) in the striatum, accompanied by more subtle changes in many other cell types. It is thought that changes in transcriptional regulation are an important underlying mechanism, but cell type-specific gene expression changes are not well understood, particularly at time points relevant to the onset of disease-related symptoms. Single-nucleus (sn)RNA-seq in a genetically precise mouse model enabled us to identify novel patterns of transcriptional dysregulation because of HD mutations, including bidirectional dysregulation of many cell type identity genes that may be driven by partial loss-of-function of the polycomb repressive complex (PRC). Identifying these regulators of transcriptional dysregulation in HD can be leveraged to design novel disease-modifying therapeutics.

Extracellular vesicles (EVs) are a unique mode of intercellular communication capable of incredible specificity in transmitting signals involved in cellular function, including germ cell maturation. Spermatogenesis occurs in the testes, behind a protective barrier to ensure safeguarding of germline DNA from environmental insults. Following DNA compaction, further sperm maturation occurs in the epididymis. Here, we report reproductive tract EVs transmit information regarding stress in the paternal environment to sperm, potentially altering fetal development. Using intracytoplasmic sperm injection, we found that sperm incubated with EVs collected from stress-treated epididymal epithelial cells produced offspring with altered neurodevelopment and adult stress reactivity. Proteomic and transcriptomic assessment of these EVs showed dramatic changes in protein and miRNA content long after stress treatment had ended, supporting a lasting programmatic change in response to chronic stress. Thus, EVs as a normal process in sperm maturation, can also perform roles in intergenerational transmission of paternal environmental experience.

The ventral pallidum (VP) is central to reward seeking and withdrawal from drugs of abuse. A characteristic of the VP is the diversity of its projection targets. Yet, it remains unknown whether different VP projections also differ in other aspects, such as their transcriptome, physiology and relevance to drug reward. In this study we perform a multimodal dissection of four major projections of the VP – to the lateral hypothalamus (VP→LH), ventral tegmental area (VP→VTA), lateral habenula (VP→LHb) and mediodorsal thalamus (VP→MDT) – with physiological, anatomical, genetic and behavioral tools and show significant differences between projections in all aspects. Specifically, the VP→LHand VP→VTAprojections show minimal overlap and stand out as having opposite properties – VP→LHneurons show higher excitability compared to VP→VTAneurons, different pattern of inputs and differentially expressed genes. Moreover, inhibition of VP→LHprojections diminishes, while inhibition of VP→VTAenhances cocaine preference after cocaine withdrawal. This demonstrates that VP projections are heterogenous neuron populations with different roles in cocaine withdrawal.

Altered activity of the ventral pallidum (VP) underlies disrupted motivation in stress and drug exposure. The VP is a very heterogeneous structure comprised of many neuron types with distinct physiological properties and projections. Neuronal PAS 1-positive (Npas1+) VP neurons are thought to send projections to brain regions critical for motivational behavior. While Npas1+ neurons have been characterized in the globus pallidus external, there is limited information on these neurons in the VP. To address this limitation, we evaluated the projection targets of the VP Npas1+ neurons and performed RNA-seq on ribosome-associated mRNA from VP Npas1+ neurons to determine their molecular identity. Finally, we used a chemogenetic approach to manipulate VP Npas1+ neurons during social defeat stress (SDS) and behavioral tasks related to anxiety and motivation in Npas1-Cre mice. We employed a similar approach in females using the chronic witness defeat stress (CWDS). We identified VP Npas1+ projections to the nucleus accumbens, ventral tegmental area, medial and lateral habenula, lateral hypothalamus, thalamus, medial and lateral septum, and periaqueductal gray area. VP Npas1+ neurons displayed distinct transcriptomes representing distinct biological processes. Chemogenetic activation of VP Npas1+ neurons increased susceptibility to a subthreshold (S)SDS and anxiety-like behavior in the elevated plus maze and open field while the inhibition of VP Npas1+ neurons enhanced resilience to chronic (C)SDS and CWDS. Thus, the activity of VP Npas1+ neurons modulates susceptibility to social stressors and anxiety-like behavior. Our studies provide new information into VP Npas1+ neuron circuitry, molecular identity, and their role in stress response.

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations., An examination of motor cortex in humans, marmosets and mice reveals a generally conserved cellular makeup that is likely to extend to many mammalian species, but also differences in gene expression, DNA methylation and chromatin state that lead to species-dependent specializations.

We explored the transcriptional and epigenetic programs underlying the differentiation of hair cells from postnatal progenitor cells in cochlear organoids. Heterogeneity in the cells including cells with the transcriptional signatures of mature hair cells allowed a full picture of possible cell fates. Construction of trajectories identified Lgr5+ cells as progenitors for hair cells and the genomic data revealed gene regulatory networks leading to hair cells. We validated these networks, demonstrating dynamic changes both in expression and predicted binding sites of these transcription factors during organoid differentiation. We identified known regulators of hair cell development, Atoh1, Pou4f3, and Gfi1, and predicted novel regulatory factors, Tcf4, an E-protein and heterodimerization partner of Atoh1, and Ddit3, a CCAAT/enhancer-binding protein (C/EBP) that represses Hes1 and activates transcription of Wnt signaling-related genes. Deciphering the signals for hair cell regeneration from mammalian cochlear supporting cells reveals candidates for HC regeneration which is limited in the adult.

Research has yet to provide a comprehensive understanding of the genetic basis of bipolar disorder (BP). In genetic studies, defining the phenotype by diagnosis may miss risk-allele carriers without BP. The authors aimed to test whether quantitatively detected subclinical symptoms of bipolarity identifies a heritable trait that infers risk for BP. The Quantitative Bipolarity Scale (QBS) was administered to 310 Old Order Amish or Mennonite individuals from multigenerational pedigrees; 110 individuals had psychiatric diagnoses (20 BP, 61 major depressive disorders (MDD), 3 psychotic disorders, 26 other psychiatric disorders). Familial aggregation of QBS was calculated using the variance components method to derive heritability and shared household effects. The QBS score was significantly higher in BP subjects (31.5 ± 3.6) compared to MDD (16.7 ± 2.0), other psychiatric diagnoses (7.0 ± 1.9), and no psychiatric diagnosis (6.0 ± 0.65) (all p 2 = 0.46 ± 0.15, p p = 0.073). When subjects with psychiatric illness were removed, the QBS heritability was similar (h2 = 0.59 ± 0.18, p

Chronic pain is at epidemic proportions in the United States, represents a significant burden on our public health system and is coincident with a growing opioid crisis. While numerous genetic risk factors have been identified, its genetic basis remains poorly understood. Here, we conducted a meta-analysis of genome-wide association study (GWAS) summary statistics from seventeen pain susceptibility traits in the UK Biobank. This analysis revealed 99 genome-wide significant risk loci, of which 62 have not been previously associated with a pain-related trait. Risk loci were enriched for genes involved in neurological and inflammatory pathways. Two-sample Mendelian randomization indicated that depression, neuroticism, and immunological traits mediate many of these effects. These analyses double the number of known risk loci for pain susceptibility and support dual causation from neuronal and immunological genes, providing leads toward targets for novel pain medications.

The development and diversity of neuronal subtypes in the human hypothalamus has been insufficiently characterized. We sequenced the transcriptomes of 40,927 cells from the prenatal human hypothalamus spanning from 6 to 25 gestational weeks and 25,424 mature neurons in regions of the adult human hypothalamus, revealing a temporal trajectory from proliferative stem cell populations to mature neurons and glia. Developing hypothalamic neurons followed branching trajectories leading to 170 transcriptionally distinct neuronal subtypes in ten hypothalamic nuclei in the adult. The uniqueness of hypothalamic neuronal lineages was examined developmentally by comparing excitatory lineages present in cortex and inhibitory lineages in ganglionic eminence from the same individuals, revealing both distinct and shared drivers of neuronal maturation across the human forebrain. Cross-species comparisons to the mouse hypothalamus identified human-specificPOMCpopulations expressing unique combinations of transcription factors and neuropeptides. These results provide the first comprehensive transcriptomic view of human hypothalamus development at cellular resolution.One-Sentence SummaryUsing single-cell genomics, we reconstructed the developmental lineages by which precursor populations give rise to 170 distinct neuronal subtypes in the human hypothalamus.

Genetic risk for complex traits is strongly enriched in non-coding genomic regions involved in gene regulation, especially enhancers. However, we lack adequate tools to connect the characteristics of these disruptions to genetic risk. Here, we propose RWAS (Regulome Wide Association Study), a new application of the MAGMA software package to identify the characteristics of enhancers that contribute to genetic risk for disease. RWAS involves three steps: (i) assign genotyped SNPs to cell type- or tissue-specific regulatory features (e.g., enhancers); (ii) test associations of each regulatory feature with a trait of interest for which genome-wide association study (GWAS) summary statistics are available; (iii) perform enhancer-set enrichment analyses to identify quantitative or categorical features of regulatory elements that are associated with the trait. These steps are implemented as a novel application of MAGMA, a tool originally developed for gene-based GWAS analyses. Applying RWAS to interrogate genetic risk for schizophrenia, we discovered a class of risk-associated AT-rich enhancers that are active in the developing brain and harbor binding sites for multiple transcription factors with neurodevelopmental functions. RWAS utilizes open-source software, and we provide a comprehensive collection of annotations for tissue-specific enhancer locations and features, including their evolutionary conservation, AT content, and co-localization with binding sites for hundreds of TFs. RWAS will enable researchers to characterize properties of regulatory elements associated with any trait of interest for which GWAS summary statistics are available.

Genetic risk for complex traits is strongly enriched in non-coding genomic regions involved in gene regulation, especially enhancers. However, we lack adequate tools to connect the characteristics of these disruptions to genetic risk. Here, we propose RWAS (Regulome Wide Association Study), a new framework to identify the characteristics of enhancers that contribute to genetic risk for disease. Applying our technique to interrogate genetic risk for schizophrenia, we found that risk-associated enhancers in this disease are predominantly active in the brain, evolutionarily conserved, and AT-rich. The association between AT percentage and risk corresponds to an overrepresentation in risk-associated enhancers for the binding sites of transcription factors that recognize AT-rich cis-regulatory motifs. Several of the TFs identified in our model as being overrepresented in risk-associated enhancers, including MEF2C, are master regulators of neuronal development. The genes that encode several of these TFs are themselves located at genetic risk loci for schizophrenia. This list also includes brain-expressed TFs that have not previously been linked to schizophrenia. In summary, we developed a generalizable approach that integrates GWAS summary statistics with enhancer characteristics to identify risk factors in tissue-specific regulatory regions.AUTHOR SUMMARYEnhancers are regulatory regions that influence gene expression via the binding of transcription factors. Risk for many heritable diseases is enriched in regulatory regions, including enhancers. In this study, we introduce a novel method of testing for association between enhancer attributes and risk and use this method to determine the enhancer characteristics that are associated with risk for schizophrenia. We found that enhancers associated with schizophrenia risk are both evolutionarily conserved and in physical contact with mutation-intolerant genes, many of which have neurodevelopmental functions. Risk-associated enhancers are also AT-rich and contain binding sites for neurodevelopmental transcription factors.

Bipolar disorder is an often-severe mental health disorder characterized by alternation between extreme mood states of mania and depression. Despite strong heritability and the recent identification of 64 loci of small effect, pathophysiological mechanisms and much of the genetic risk remain unknown. Here, through genome sequencing and linkage and association analyses, we found that rare variants co-segregating with bipolar disorder in large multiply affected families cluster within gene networks enriched for synaptic and nuclear functions. The top variant in this analysis prioritized by statistical association, predicted deleteriousness, and network centrality was a missense variant in the gene encoding D-amino acid oxidase (DAOG131V). Heterologous expression of DAOG131V in human cells resulted in decreased DAO protein abundance and enzymatic activity. In a knock-in mouse harboring this human DAOG131V variant, DaoG130V/+, we similarly found decreased DAO protein abundance, as well as enhanced stress susceptibility and blunted behavioral responses to pharmacological inhibition of N-methyl-D-aspartate receptors (NMDARs). RNA sequencing of cerebellar tissue revealed that DaoG130V resulted in decreased expression of two gene networks that are enriched for synaptic functions and for genes expressed specifically in Purkinje cells and granule neurons. Similar expression changes in both of these gene networks were also identified in the cerebellum of bipolar disorder cases vs. controls. These findings implicate dysregulation of NMDAR signaling and of gene expression in cerebellar neurons in bipolar disorder pathophysiology and provide insight into its genetic architecture.One Sentence SummaryFunctional studies of a rare hypofunctional variant in the D-amino acid oxidase gene implicate stress susceptibility, NMDA receptor signaling, and cerebellar circuits in risk for bipolar disorder.

Many psychiatric disorders including depression involve complex interactions of genetics and environmental stressors. Environmental influence is challenging to measure objectively and account for in genetic studies because the necessary large population samples in these studies involve individuals with varying cultures and life experiences, clouding genetic findings. In a unique population with relative sociocultural homogeneity and a narrower range of types of stress experiences, we quantitatively assessed multiple stress dimensions and measured their potential influence in biasing the heritability estimate of depression. We quantified depressive symptoms, major lifetime stressors, current perceived stress, and a culturally specific community stress measure in individuals with depression-related diagnoses and community controls in Old Order Amish and Mennonite populations. Results showed that lifetime stressors measured by lifetime stressor inventory (R2 = 0.06, p = 2 × 10−5) and current stress measured by Perceived Stress Scale (R2 = 0.13, p −6) were both associated with current depressive symptoms quantified by Beck Depression Inventory in community controls, but current stress was the only measure associated with current depressive symptoms in individuals with a depression diagnosis, and to a greater degree (R2 = 0.41, p −6). A novel, culturally specific community stress measure demonstrated internal reliability and was associated with current stress but was not significantly related to depression. Heritability (h2) for depression diagnosis (0.46 ± 0.14) and quantitative depression severity as measured by Beck Depression Inventory (0.45 ± 0.12) were significant, but h2 for depression diagnosis decreased to 0.25 ± 0.14 once stressors were accounted for in the model. This quantifies and demonstrates the importance of accounting for environmental influence in reducing phenotypic heterogeneity of depression and improving the power and replicability of genetic association findings that can be better translated to patient groups.

Sleep is essential to the human brain and is regulated by genetics with many features conserved across species. Sleep is also influenced by health and environmental factors; identifying replicable genetic variants contributing to sleep may require accounting for these factors. We examined how stress and mood disorder contribute to sleep and impact its heritability. Our sample included 326 Amish/Mennonite individuals with a lifestyle with limited technological interferences with sleep. Sleep measures included Pittsburgh Sleep Quality Index (PSQI), bedtime, wake time, and time to sleep onset. Current stress level, cumulative life stressors, and mood disorder were also evaluated. We estimated the heritability of sleep features and examined the impact of current stress, lifetime stress, mood diagnosis on sleep quality. The results showed current stress, lifetime stress, and mood disorder were independently associated with PSQI score (p < .05). Heritability of PSQI was low (0-0.23) before and after accounting for stress and mood. Bedtime, wake time, and minutes to sleep time did show significant heritability at 0.44, 0.42, and 0.29. However, after adjusting for shared environment, only heritability of wake time remained significant. Sleep is affected by environmental stress and mental health factors even in a society with limited technological interference with sleep. Wake time may be a more biological marker of sleep as compared to the evening measures which are more influenced by other household members. Accounting for nongenetic and partially genetic determinants of sleep particularly stress and mood disorder is likely important for improving the precision of genetic studies of sleep.

SummaryProgressive striatal gene expression changes and epigenetic alterations are a prominent feature of Huntington’s disease (HD), but direct relationships between the huntingtin (HTT) protein and chromatin remain poorly described. Here, using chromatin immunoprecipitation and sequencing (ChIP-seq), we show that HTT reproducibly occupies specific locations in the mouse genome, including thousands of genomic loci that are differentially occupied in striatal tissue from a knock-in mouse model of HD (B6.HttQ111/+) versus wildtype controls. ChIP-seq of histone modifications, generated in parallel, revealed genotype-specific colocalization of HTT with trimethylation of histone 3 lysine 27 (H3K27me3), a repressive chromatin mark. Near genes that are differentially regulated in HD, greater HTT occupancy in HttQ111/+ vs. wildtype mice predicted increased H3K27me3, reduced histone 3 lysine 4 (H3K4me3), a marker of poised and active promoters, and down-regulated gene expression. Altered huntingtin-chromatin interactions may therefore play a direct role in driving transcriptional dysregulation in HD.

Epidemiological studies from the last century have drawn strong associations between paternal life experiences and offspring health and disease outcomes. Recent studies have demonstrated sperm small non-coding RNA (sncRNA) populations vary in response to diverse paternal insults. However, for studies in retrospective or prospective human cohorts to identify changes in paternal germ cell epigenetics in association with offspring disease risk, a framework must first be built with insight into the expected biological variation inherent in human populations. In other words, how will we know what to look for if we don’t first know what is stable and what is dynamic, and what is consistent within and between men over time? From sperm samples from a ‘normative’ cohort of healthy human subjects collected repeatedly from each subject over 6 months, 17 healthy male participants met inclusion criteria and completed donations and psychological evaluations of perceived stress monthly. sncRNAs (including miRNA, piRNA, and tRNA) isolated from mature sperm from these samples were subjected to Illumina small RNA sequencing, aligned to subtype-specific reference transcriptomes, and quantified. The repeated measures design allowed us to define both within- and between-subject variation in the expression of 254 miRNA, 194 tRNA, and 937 piRNA in sperm over time. We developed screening criteria to identify a subset of potential environmentally responsive ‘dynamic’ sperm sncRNA. Implementing complex modeling of the relationships between individual dynamic sncRNA and perceived stress states in these data, we identified 5 miRNA (including let-7f-5p and miR-181a-5p) and 4 tRNA that are responsive to the dynamics of prior stress experience and fit our established mouse model. In the current study, we aligned repeated sampling of human sperm sncRNA expression data with concurrent measures of perceived stress as a novel framework that can now be applied across a range of studies focused on diverse environmental factors able to influence germ cell programming and potentially impact offspring development.

The primary motor cortex (M1) is essential for voluntary fine motor control and is functionally conserved across mammals. Using high-throughput transcriptomic and epigenomic profiling of over 450,000 single nuclei in human, marmoset monkey, and mouse, we demonstrate a broadly conserved cellular makeup of this region, whose similarity mirrors evolutionary distance and is consistent between the transcriptome and epigenome. The core conserved molecular identity of neuronal and non-neuronal types allowed the generation of a cross-species consensus cell type classification and inference of conserved cell type properties across species. Despite overall conservation, many species specializations were apparent, including differences in cell type proportions, gene expression, DNA methylation, and chromatin state. Few cell type marker genes were conserved across species, providing a short list of candidate genes and regulatory mechanisms responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allowed the Patch-seq identification of layer 5 (L5) corticospinal Betz cells in non-human primate and human and characterization of their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell type diversity in M1 across mammals and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1–3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas—containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities—is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis., The authors describe an integrated atlas of the diverse cell types in the mouse primary motor cortex.

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans., Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

As it is likely that both common and rare genetic variation are important for complex disease risk, studies that examine the full range of the allelic frequency distribution should be utilized to dissect the genetic influences on mental illness. The rate limiting factor for inferring an association between a variant and a phenotype is inevitably the total number of copies of the minor allele captured in the studied sample. For rare variation, with minor allele frequencies of 0.5% or less, very large samples of unrelated individuals are necessary to unambiguously associate a locus with an illness. Unfortunately, such large samples are often cost prohibitive. However, by using alternative analytic strategies and studying related individuals, particularly those from large multiplex families, it is possible to reduce the required sample size while maintaining statistical power. We contend that using whole genome sequence (WGS) in extended pedigrees provides a cost-effective strategy for psychiatric gene mapping that complements common variant approaches and WGS in unrelated individuals. This was our impetus for forming the “Pedigree-Based Whole Genome Sequencing of Affective and Psychotic Disorders” consortium. In this review, we provide a rationale for the use of WGS with pedigrees in modern psychiatric genetics research. We begin with a focused review of the current literature, followed by a short history of family-based research in psychiatry. Next, we describe several advantages of pedigrees for WGS research, including power estimates, methods for studying the environment, and endophenotypes. We conclude with a brief description of our consortium and its goals. This research was supported by National Institute of Mental Health grants U01 MH105630 (DCG), U01 MH105634 (REG), U01 MH105632 (JB), R01 MH078143 (DCG), R01 MH083824 (DCG & JB), R01 MH078111 (JB), R01 MH061622 (LA), R01 MH042191 (REG), and R01 MH063480 (VLN). UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Biología Celular y Molecular (CIBCM) UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Biología

The gEAR portal (gene Expression Analysis Resource, umgear.org) is an open access community-driven tool for multi-omic and multi-species data visualization, analysis and sharing. The gEAR supports visualization of multiple RNA-seq data types (bulk, sorted, single cell/nucleus) and epigenomics data, from multiple species, time points and tissues in a single-page, user-friendly browsable format. An integrated scRNA-seq workbench provides access to raw data of scRNA-seq datasets for de novo analysis, as well as marker-gene and cluster comparisons of pre-assigned clusters. Users can upload, view, analyze and privately share their own data in the context of previously published datasets. Short, permanent URLs can be generated for dissemination of individual or collections of datasets in published manuscripts. While the gEAR is currently curated for auditory research with over 90 high-value datasets organized in thematic profiles, the gEAR also supports the BRAIN initiative (via nemoanalytics.org) and is easily adaptable for other research domains.

Objective To assess the association between peripheral lipid/fat profiles and cerebral gray matter (GM) and white matter (WM) in healthy Old Order Amish (OOA). Methods Blood lipids, abdominal adiposity, liver lipid contents, and cerebral microstructure were assessed in OOA (N = 64, 31 males/33 females, ages 18-77). Orthogonal factors were extracted from lipid and imaging adiposity measures. GM assessment used the Human Connectome Project protocol to measure whole-brain average cortical thickness. Diffusion-weighted imaging was used to derive WM fractional anisotropy and kurtosis anisotropy measurements. Results Lipid/fat measures were captured by three orthogonal factors explaining 80% of the variance. Factor one loaded on cholesterol and/or low-density lipoprotein cholesterol measurements; factor two loaded on triglyceride/liver measurements; and factor three loaded on abdominal fat measurements. A two-stage regression including age/sex (first stage) and the three factors (second stage) examined the peripheral lipid/fat effects. Factors two and three significantly contributed to WM measures after Bonferroni corrections (P

Patients with schizophrenia show decreased processing speed on neuropsychological testing and decreased white matter integrity as measured by diffusion tensor imaging, two traits shown to be both heritable and genetically associated indicating that there may be genes that influence both traits as well as schizophrenia disease risk. The potassium channel gene family is a reasonable candidate to harbor such a gene given the prominent role potassium channels play in the central nervous system in signal transduction, particularly in myelinated axons. We genotyped members of the large potassium channel gene family focusing on putatively functional single nucleotide polymorphisms (SNPs) in a population of 363 controls, 194 patients with schizophrenia spectrum disorder (SSD) and 28 patients with affective disorders with psychotic features who completed imaging and neuropsychological testing. We then performed three association analyses using three phenotypes - processing speed, whole-brain white matter fractional anisotropy (FA) and schizophrenia spectrum diagnosis. We extracted SNPs showing an association at a nominal P value of

Dynamic changes in chromatin accessibility coincide with important aspects of neuronal differentiation, such as fate specification and arealization and confer cell type-specific associations to neurodevelopmental disorders. However, studies of the epigenomic landscape of the developing human brain have yet to be performed at single-cell resolution. Here, we profiled chromatin accessibility of >75,000 cells from eight distinct areas of developing human forebrain using single cell ATAC-seq (scATACseq). We identified thousands of loci that undergo extensive cell type-specific changes in accessibility during corticogenesis. Chromatin state profiling also reveals novel distinctions between neural progenitor cells from different cortical areas not seen in transcriptomic profiles and suggests a role for retinoic acid signaling in cortical arealization. Comparison of the cell type-specific chromatin landscape of cerebral organoids to primary developing cortex found that organoids establish broad cell type-specific enhancer accessibility patterns similar to the developing cortex, but lack many putative regulatory elements identified in homologous primary cell types. Together, our results reveal the important contribution of chromatin state to the emerging patterns of cell type diversity and cell fate specification and provide a blueprint for evaluating the fidelity and robustness of cerebral organoids as a model for cortical development.

Age-related hearing impairment (ARHI), one of the most common medical conditions, is strongly heritable, yet its genetic causes remain largely unknown. We conducted a meta-analysis of GWAS summary statistics from multiple hearing-related traits in the UK Biobank (n = up to 323,978) and identified 31 genome-wide significant risk loci for self-reported hearing difficulty (p < 5e-8), of which 30 have not been reported previously in the peer-reviewed literature at genome-wide significance. We investigated the regulatory and cell specific expression for these loci by generating mRNA-seq, ATAC-seq, and single-cell RNA-seq from cells in the mouse cochlea. Risk-associated genes were most strongly enriched for expression in cochlear epithelial cells, as well as for genes related to sensory perception and known Mendelian deafness genes, supporting their relevance to auditory function. Regions of the human genome homologous to open chromatin in sensory epithelial cells from the mouse were strongly enriched for heritable risk for hearing difficulty, even after adjusting for baseline effects of evolutionary conservation and cell-type nonspecific regulatory regions. Epigenomic and statistical fine-mapping most strongly supported 50 putative risk genes. Of these, at least 39 were expressed robustly in mouse cochlea and 16 were enriched specifically in sensory hair cells. These results reveal new risk loci and risk genes for hearing difficulty and suggest an important role for altered gene regulation in the cochlear sensory epithelium.

There is intense interest in mapping the tissue-specific binding sites of transcription factors in the human genome to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting provides a means to predict genome-wide binding sites for hundreds of transcription factors (TFs) simultaneously. However, despite the public availability of DNase-seq data for hundreds of samples, there is neither a unified analytical workflow nor a publicly accessible database providing the locations of footprints across all available samples. Here, we implemented a workflow for uniform processing of footprints using two state-of-the-art footprinting algorithms: Wellington and HINT. Our workflow scans the footprints generated by these algorithms for 1,530 sequence motifs to predict binding sites for 1,515 human transcription factors. We applied our workflow to detect footprints in 192 DNase-seq experiments from ENCODE spanning 27 human tissues. This collection of footprints describes an expansive landscape of potential TF occupancy. At thresholds optimized through machine learning, we report high-quality footprints covering 9.8% of the human genome. These footprints were enriched for true positive TF binding sites as defined by ChIP-seq peaks, as well as for genetic variants associated with changes in gene expression. Integrating our footprint atlas with summary statistics from genome-wide association studies revealed that risk for neuropsychiatric traits was enriched specifically at highly-scoring footprints in human brain, while risk for immune traits was enriched specifically at highly-scoring footprints in human lymphoblasts. Our cloud-based workflow is available at github.com/globusgenomics/genomics-footprint and a database with all footprints and TF binding site predictions are publicly available at http://data.nemoarchive.org/other/grant/sament/sament/footprint_atlas.

Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 - 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 - rs2086256 - rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data. peerReviewed

Summary Transcriptional regulatory changes in the developing and adult brain are prominent features of brain diseases, but the involvement of specific transcription factors (TFs) remains poorly understood. We integrated brain-specific DNase footprinting and TF-gene co-expression to reconstruct a transcriptional regulatory network (TRN) model for the human brain. We identified key regulator TFs whose predicted target genes were enriched for differentially expressed genes in the prefrontal cortex of individuals with psychiatric and neurodegenerative diseases. Many of these TFs were further implicated in the same diseases through disruption of their binding sites by disease-associated SNPs and associations of TF loci with disease risk. Using primary human neural stem cells, we validated network predictions that link the TF POU3F2 to schizophrenia and bipolar disorder via both cis- and trans-acting mechanisms. Our models of brain-specific TF binding sites and target genes provide a resource for network analysis of brain diseases.

We sequenced the genomes of 200 individuals from 41 families multiply affected with bipolar disorder (BD) to identify contributions of rare variants to genetic risk. We initially focused on 3,087 candidate genes with known synaptic functions or prior evidence from genome-wide association studies. BD pedigrees had an increased burden of rare variants in genes encoding neuronal ion channels, including subunits of GABAA receptors and voltage-gated calcium channels. Four uncommon coding and regulatory variants also showed significant association, including a missense variant in GABRA6. Targeted sequencing of 26 of these candidate genes in an additional 3,014 cases and 1,717 controls confirmed rare variant associations in ANK3, CACNA1B, CACNA1C, CACNA1D, CACNG2, CAMK2A, and NGF. Variants in promoters and 5' and 3' UTRs contributed more strongly than coding variants to risk for BD, both in pedigrees and in the case-control cohort. The genes and pathways identified in this study regulate diverse aspects of neuronal excitability. We conclude that rare variants in neuronal excitability genes contribute to risk for BD.

Genetic and genomic studies suggest an important role for transcriptional regulatory changes in brain diseases, but roles for specific transcription factors (TFs) remain poorly understood. We integrated human brain-specific DNase I footprinting and TF-gene co-expression to reconstruct a transcriptional regulatory network (TRN) model for the human brain, predicting the brain-specific binding sites and target genes for 741 TFs. We used this model to predict core TFs involved in psychiatric and neurodegenerative diseases. Our results suggest that disease-related transcriptomic and genetic changes converge on small sets of disease-specific regulators, with distinct networks underlying neurodegenerative vs. psychiatric diseases. Core TFs were frequently implicated in a disease through multiple mechanisms, including differential expression of their target genes, disruption of their binding sites by disease-associated SNPs, and associations of the genetic loci encoding these TFs with disease risk. We validated our model’s predictions through systematic comparison to publicly available ChIP-seq and TF perturbation studies and through experimental studies in primary human neural stem cells. Combined genetic and transcriptional evidence supports roles for neuronal and microglia-enriched, MEF2C-regulated networks in Alzheimer’s disease; an oligodendrocyte-enriched, SREBF1-regulated network in schizophrenia; and a neural stem cell and astrocyte-enriched, POU3F2-regulated network in bipolar disorder. We provide our models of brain-specific TF binding sites and target genes as a resource for network analysis of brain diseases.

Scientific Reports 7: Article number: 41570; published online: 08 February 2017; updated: 28 March 2017 This Article contains a typographical error in the Methods section, under the subheading “Library construction, RNA Sequencing and RNASeq analysis”, where: “The fastq files were aligned using the default parameters of SNAPR50 (https://github.

To characterize gene expression patterns in the regional subdivisions of the mammalian brain, we integrated spatial gene expression patterns from the Allen Brain Atlas for the adult mouse with panels of cell type-specific genes for neurons, astrocytes, and oligodendrocytes from previously published transcriptome profiling experiments. We found that the combined spatial expression patterns of 170 neuron-specific transcripts revealed strikingly clear and symmetrical signatures for most of the brain’s major subdivisions. Moreover, the brain expression spatial signatures correspond to anatomical structures and may even reflect developmental ontogeny. Spatial expression profiles of astrocyte- and oligodendrocyte-specific genes also revealed regional differences; these defined fewer regions and were less distinct but still symmetrical in the coronal plane. Follow-up analysis suggested that region-based clustering of neuron-specific genes was related to ( i ) a combination of individual genes with restricted expression patterns, ( ii ) region-specific differences in the relative expression of functional groups of genes, and ( iii ) regional differences in neuronal density. Products from some of these neuron-specific genes are present in peripheral blood, raising the possibility that they could reflect the activities of disease- or injury-perturbed networks and collectively function as biomarkers for clinical disease diagnostics.

Huntington’s disease (HD) is an autosomal dominant neurodegenerative disease whose neuropathological signature is a selective loss of medium spiny neurons in the striatum. Despite this selective neuropathology, the mutant protein (huntingtin) is found in virtually every cell so far studied, and, consequently, phenotypes are observed in a wide range of organ systems both inside and outside the central nervous system. We, and others, have suggested that peripheral dysfunction could contribute to the rate of progression of striatal phenotypes of HD. To test this hypothesis, we lowered levels of huntingtin by treating mice with antisense oligonucleotides (ASOs) targeting the murineHuntingtingene. To study the relationship between peripheral huntingtin levels and striatal HD phenotypes, we utilized a knock-in model of the human HD mutation (the B6.HttQ111/+mouse). We treated mice with ASOs from 2-10 months of age, a time period over which significant HD-relevant signs progressively develop in the brains ofHttQ111+mice. Peripheral treatment with ASOs led to persistent reduction of huntingtin protein in peripheral organs, including liver, brown and white adipose tissues. This reduction was not associated with alterations in the severity of HD-relevant signs in the striatum ofHttQ111/+mice at the end of the study, including transcriptional dysregulation, the accumulation of neuronal intranuclear inclusions, and behavioral changes such as subtle hypoactivity and reduced exploratory drive. These results suggest that the amount of peripheral reduction achieved in the current study does not significantly impact the progression of HD-relevant signs in the central nervous system.

Transcriptional changes occur presymptomatically and throughout Huntington’s Disease (HD), motivating the study of transcriptional regulatory networks (TRNs) in HD. We reconstructed a genome-scale model for the target genes of 718 TFs in the mouse striatum by integrating a model of the genomic binding sites with transcriptome profiling of striatal tissue from HD mouse models. We identified 48 differentially expressed TF-target gene modules associated with age‐ and Htt allele-dependent gene expression changes in the mouse striatum, and replicated many of these associations in independent transcriptomic and proteomic datasets. Strikingly, many of these predicted target genes were also differentially expressed in striatal tissue from human disease. We experimentally validated a key model prediction that SMAD3 regulates HD-related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP-seq) of mouse striatum. We found Htt allele-dependent changes in the genomic occupancy of SMAD3 and confirmed our model’s prediction that many SMAD3 target genes are down-regulated early in HD. Importantly, our study provides a mouse and human striatal-specific TRN and prioritizes a hierarchy of transcription factor drivers in HD.