Single-cell epigenomics reveals mechanisms of human cortical development.

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.

A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex.

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.

Genome wide association joint analysis reveals 99 risk loci for pain susceptibility and pleiotropic relationships with psychiatric, metabolic, and immunological traits.

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 genome-wide association studies have been reported for specific pain-related traits, many of these studies were underpowered, and the genetic relationship among these traits remains poorly understood. Here, we conducted a joint analysis of genome-wide association study summary statistics from seventeen pain susceptibility traits in the UK Biobank. This analysis revealed 99 genome-wide significant risk loci, 65 of which overlap loci identified in earlier studies. The remaining 34 loci are novel. We applied leave-one-trait-out meta-analyses to evaluate the influence of each trait on the joint analysis, which suggested that loci fall into four categories: loci associated with nearly all pain-related traits; loci primarily associated with a single trait; loci associated with multiple forms of skeletomuscular pain; and loci associated with headache-related pain. Overall, 664 genes were mapped to the 99 loci by genomic proximity, eQTLs, and chromatin interaction and ~15% of these genes showed differential expression in individuals with acute or chronic pain compared to healthy controls. Risk loci were enriched for genes involved in neurological and inflammatory pathways. Genetic correlation and two-sample Mendelian randomization indicated that psychiatric, metabolic, and immunological traits mediate some of these effects.

The single-cell opioid responses in the context of HIV (SCORCH) consortium.

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

The Neuroscience Multi-Omic Archive: a BRAIN Initiative resource for single-cell transcriptomic and epigenomic data from the mammalian brain.

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).

Impaired Reorganization of Centrosome Structure Underlies Human Infantile Dilated Cardiomyopathy.

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.

Genome-wide significant risk loci for mood disorders in the Old Order Amish founder population.

Genome-wide association studies (GWAS) of mood disorders in large case-control cohorts have identified numerous risk loci, yet pathophysiological mechanisms remain elusive, primarily due to the very small effects of common variants. We sought to discover risk variants with larger effects by conducting a genome-wide association study of mood disorders in a founder population, the Old Order Amish (OOA, n = 1,672). Our analysis revealed four genome-wide significant risk loci, all of which were associated with >2-fold relative risk. Quantitative behavioral and neurocognitive assessments (n = 314) revealed effects of risk variants on sub-clinical depressive symptoms and information processing speed. Network analysis suggested that OOA-specific risk loci harbor novel risk-associated genes that interact with known neuropsychiatry-associated genes via gene interaction networks. Annotation of the variants at these risk loci revealed population-enriched, non-synonymous variants in two genes encoding neurodevelopmental transcription factors, CUX1 and CNOT1. Our findings provide insight into the genetic architecture of mood disorders and a substrate for mechanistic and clinical studies.

Transcriptional signatures of fentanyl use in the mouse ventral tegmental area.

Synthetic opioids such as fentanyl contribute to the vast majority of opioid-related overdose deaths, but fentanyl use remains broadly understudied. Like other substances with misuse potential, opioids cause lasting molecular adaptations to brain reward circuits, including neurons in the ventral tegmental area (VTA). The VTA contains numerous cell types that play diverse roles in opioid use and relapse; however, it is unknown how fentanyl experience alters the transcriptional landscape in specific subtypes. Here, we performed single nuclei RNA sequencing to study transcriptional programs in fentanyl-experienced mice. Male and female C57/BL6 mice self-administered intravenous fentanyl (1.5 µg/kg/infusion) or saline for 10 days. After 24 h abstinence, VTA nuclei were isolated and prepared for sequencing on the 10× platform. We identified different patterns of gene expression across cell types. In dopamine neurons, we found enrichment of genes involved in growth hormone signalling. In dopamine-glutamate-GABA combinatorial neurons, and some GABA neurons, we found enrichment of genes involved in Pi3k-Akt signalling. In glutamate neurons, we found enrichment of genes involved in cholinergic signalling. We identified transcriptional regulators for the differentially expressed genes in each neuron cluster, including downregulated transcriptional repressor Bcl6, and upregulated transcription factor Tcf4. We also compared the fentanyl-induced gene expression changes identified in mouse VTA with a published rat dataset in bulk VTA, and found overlap in genes related to GABAergic signalling and extracellular matrix interaction. Together, we provide a comprehensive picture of how fentanyl self-administration alters the transcriptional landscape of the mouse VTA that serves as the foundation for future mechanistic studies.

Rare variants implicate NMDA receptor signaling and cerebellar gene networks in risk for bipolar disorder.

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.

Identifying enhancer properties associated with genetic risk for complex traits using regulome-wide association studies.

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.

Biological insights from multi-omic analysis of 31 genomic risk loci for adult hearing difficulty.

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 330,759) and identified 31 genome-wide significant risk loci for self-reported hearing difficulty (p < 5x10-8), of which eight have not been reported previously in the peer-reviewed literature. 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 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 non-specific regulatory regions. Epigenomic and statistical fine-mapping most strongly supported 50 putative risk genes. Of these, 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.

Single-Nucleus RNA-Seq Reveals Dysregulation of Striatal Cell Identity Due to Huntington's Disease Mutations.

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, HttQ175/+, 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.

Genetic versus stress and mood determinants of sleep in the Amish.

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.

Rediscovering the value of families for psychiatric genetics research.

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.

High resolution time-course mapping of early transcriptomic, molecular and cellular phenotypes in Huntington's disease CAG knock-in mice across multiple genetic backgrounds.

Huntington's disease is a dominantly inherited neurodegenerative disease caused by the expansion of a CAG repeat in the HTT gene. In addition to the length of the CAG expansion, factors such as genetic background have been shown to contribute to the age at onset of neurological symptoms. A central challenge in understanding the disease progression that leads from the HD mutation to massive cell death in the striatum is the ability to characterize the subtle and early functional consequences of the CAG expansion longitudinally. We used dense time course sampling between 4 and 20 postnatal weeks to characterize early transcriptomic, molecular and cellular phenotypes in the striatum of six distinct knock-in mouse models of the HD mutation. We studied the effects of the HttQ111 allele on the C57BL/6J, CD-1, FVB/NCr1, and 129S2/SvPasCrl genetic backgrounds, and of two additional alleles, HttQ92 and HttQ50, on the C57BL/6J background. We describe the emergence of a transcriptomic signature in HttQ111/+ mice involving hundreds of differentially expressed genes and changes in diverse molecular pathways. We also show that this time course spanned the onset of mutant huntingtin nuclear localization phenotypes and somatic CAG-length instability in the striatum. Genetic background strongly influenced the magnitude and age at onset of these effects. This work provides a foundation for understanding the earliest transcriptional and molecular changes contributing to HD pathogenesis.

Transcriptional regulatory networks underlying gene expression changes in Huntington's disease.

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 transcription factors (TFs) in the mouse striatum by integrating a model of 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 CAG repeat length-dependent gene expression changes in Htt CAG knock-in mouse striatum and replicated many of these associations in independent transcriptomic and proteomic datasets. Thirteen of 48 of these predicted TF-target gene modules were also differentially expressed in striatal tissue from human disease. We experimentally validated a specific model prediction that SMAD3 regulates HD-related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP-seq) of mouse striatum. We found CAG repeat length-dependent changes in the genomic occupancy of SMAD3 and confirmed our model's prediction that many SMAD3 target genes are downregulated early in HD.

Rare variants in neuronal excitability genes influence risk for bipolar disorder.

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.

Cell type-specific genes show striking and distinct patterns of spatial expression in the mouse brain.

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.

Diet and endocrine effects on behavioral maturation-related gene expression in the pars intercerebralis of the honey bee brain.

Nervous and neuroendocrine systems mediate environmental conditions to control a variety of life history traits. Our goal was to provide mechanistic insights as to how neurosecretory signals mediate division of labor in the honey bee (Apis mellifera). Worker division of labor is based on a process of behavioral maturation by individual bees, which involves performing in-hive tasks early in adulthood, then transitioning to foraging for food outside the hive. Social and nutritional cues converge on endocrine factors to regulate behavioral maturation, but whether neurosecretory systems are central to this process is not known. To explore this, we performed transcriptomic profiling of a neurosecretory region of the brain, the pars intercerebralis (PI). We first compared PI transcriptional profiles for bees performing in-hive tasks and bees engaged in foraging. Using these results as a baseline, we then performed manipulative experiments to test whether the PI is responsive to dietary changes and/or changes in juvenile hormone (JH) levels. Results reveal a robust molecular signature of behavioral maturation in the PI, with a subset of gene expression changes consistent with changes elicited by JH treatment. In contrast, dietary changes did not induce transcriptomic changes in the PI consistent with behavioral maturation or JH treatment. Based on these results, we propose a new verbal model of the regulation of division of labor in honey bees in which the relationship between diet and nutritional physiology is attenuated, and in its place is a relationship between social signals and nutritional physiology that is mediated by JH.