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Ecophysiologists have reported a range of relationships, including intrinsic trade-offs across and within species between plant relative growth rate in high resource conditions (RGR) vs adaptation to tolerate cold or arid climates, arising from trait-based mechanisms. Few studies have considered ecotypes within a species, in which the lack of a trade-off would contribute to a wide species range and resilience to climate change. For 15 ecotypes of Arabidopsis thaliana in a common garden we tested for associations between RGR vs adaptation to cold or dry native climates and assessed hypotheses for its mediation by 15 functional traits. Ecotypes native to warmer, drier climates had higher leaf density, leaf mass per area, root mass fraction, nitrogen per leaf area and carbon isotope ratio, and lower osmotic potential at full turgor. Relative growth rate was statistically independent of the climate of the ecotype native range and of individual functional traits. The decoupling of RGR and cold or drought adaptation in Arabidopsis is consistent with multiple stress resistance and avoidance mechanisms for ecotypic climate adaptation and would contribute to the species' wide geographic range and resilience as the climate changes.

Transgenic T-cell receptor (TCR) adoptive cell therapies recognizing tumor antigens are associated with robust initial response rates, but frequent disease relapse. This usually occurs in the setting of poor long-term persistence of cells expressing the transgenic TCR, generated using murine stem cell virus (MSCV) γ-retroviral vectors. Analysis of clinical transgenic adoptive cell therapy products in vivo revealed that despite strong persistence of the transgenic TCR DNA sequence over time, its expression was profoundly decreased over time at the RNA and protein levels. Patients with the greatest degrees of expression suppression displayed significant increases in DNA methylation over time within the MSCV promoter region, as well as progressive increases in DNA methylation within the entire MSCV vector over time. These increases in vector methylation occurred independently of its integration site within the host genomes. These results have significant implications for the design of future viral vector gene–engineered adoptive cell transfer therapies.Significance:Cellular immunotherapies' reliance on retroviral vectors encoding foreign genetic material can be vulnerable to progressive acquisition of DNA methylation and subsequent epigenetic suppression of the transgenic product in TCR adoptive cell therapy. This must be considered in the design of future generations of cellular immunotherapies for cancer.This article is highlighted in the In This Issue feature, p. 1611

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Unlike genomes, which are static throughout the lifespan of an organism, DNA methylomes are dynamic. To study these dynamics, we developed quantitative models that measure the effect of multiple factors on DNA methylomes including, age, sex, weight, and genetics. We conducted our study in canids, which prove to be an ideal species to assess epigenetic moderators due to their extreme variability in size and well-characterized genetic structure. We collected buccal swabs from 217 canids (207 domestic dogs and 10 grey wolves) and used targeted bisulphite sequencing to measure methylomes. We also measured genotypes at over one thousand single nucleotide polymorphisms (SNPs). As expected, we found that DNA methylomes are strongly associated with age, enabling the construction of epigenetic clocks. However, we also identify novel associations between methylomes and sex, weight, and sterilization status, leading to accurate models that predict these factors. Methylomes are also affected by genetics, and we observe multiple associations between SNP loci and methylated CpGs. Finally, we show that several factors moderate the relationship between epigenetic ages and real ages, such as body weight, which increases epigenetic ageing. In conclusion, we demonstrate that the plasticity of DNA methylomes is impacted by myriad genetics and physiological factors, and that DNA methylation biomarkers are accurate predictors of age, sex and sterilization status.

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single- cell RNA-sequencing (scRNA-seq) dataset of ∼7 million cells profiled, and a spatially resolved transcriptomic dataset of ∼4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.

The detection of novel stimuli is critical to learn and survive in a dynamic environment. Though novel stimuli powerfully affect brain activity, their impact on specific cell types and circuits is not well understood. Disinhibition is one candidate mechanism for novelty-induced enhancements in activity. Here we characterize the impact of stimulus novelty on disinhibitory circuit components using longitudinal 2-photon calcium imaging of Vip, Sst, and excitatory populations in the mouse visual cortex. Mice learn a behavioral task with stimuli that become highly familiar, then are tested on both familiar and novel stimuli. Mice consistently perform the task with novel stimuli, yet responses to stimulus presentations and stimulus omissions are dramatically altered. Further, we find that novelty modifies coding of visual as well as behavioral and task information. At the population level, the direction of these changes is consistent with engagement of the Vip-Sst disinhibitory circuit. At the single cell level, we identify separate clusters of Vip, Sst, and excitatory cells with unique patterns of novelty-induced coding changes. This study and the accompanying open-access dataset reveals the impact of novelty on sensory and behavioral representations in visual cortical circuits and establishes novelty as a key driver of cellular functional diversity.

Epigenetic clocks, DNA methylation based predictive models of chronological age, are often utilized to study aging associated biology. Despite their widespread use, these methods do not account for other factors that also contribute to the variability of DNA methylation data. For example, many CpG sites show strong sex-specific or cell type specific patterns that likely impact the predictions of epigenetic age. To overcome these limitations, we developed a multidimensional extension of the Epigenetic Pacemaker, the Multi-State Epigenetic Pacemaker (MSEPM). We show that the MSEPM is capable of accurately modeling multiple methylation associated factors simultaneously, while also providing site specific models that describe the per site relationship between methylation and these factors. We utilized the MSEPM with a large aggregate cohort of blood methylation data to construct models of the effects of age, sex and cell type heterogeneity on DNA methylation. We found that these models capture a large faction of the variability at thousands of DNA methylation sites. Moreover, we found modeled sites that are primarily affected by aging and no other factors. Among these, those that lose methylation over time are enriched for CTCF transcription factor chip peaks, while those that gain methylation over time are enriched for REST transcription factor chip peaks. Both transcription factors are associated with transcriptional maintenance and suggest a general dysregulation of transcription with age that is not impacted by sex or cell type heterogeneity. In conclusion, the MSEPM is capable of accurately modeling multiple methylation associated factors and the models produced can illuminate site specific combinations of factors that affect methylation dynamics.

Species that hibernate generally live longer than would be expected based solely on their body size. Hibernation is characterized by long periods of metabolic suppression (torpor) interspersed by short periods of increased metabolism (arousal). The torpor–arousal cycles occur multiple times during hibernation, and it has been suggested that processes controlling the transition between torpor and arousal states cause ageing suppression. Metabolic rate is also a known correlate of longevity; we thus proposed the ‘hibernation–ageing hypothesis’ whereby ageing is suspended during hibernation. We tested this hypothesis in a well-studied population of yellow-bellied marmots (Marmota flaviventer), which spend 7–8 months per year hibernating. We used two approaches to estimate epigenetic age: the epigenetic clock and the epigenetic pacemaker. Variation in epigenetic age of 149 samples collected throughout the life of 73 females was modelled using generalized additive mixed models (GAMM), where season (cyclic cubic spline) and chronological age (cubic spline) were fixed effects. As expected, the GAMM using epigenetic ages calculated from the epigenetic pacemaker was better able to detect nonlinear patterns in epigenetic ageing over time. We observed a logarithmic curve of epigenetic age with time, where the epigenetic age increased at a higher rate until females reached sexual maturity (two years old). With respect to circannual patterns, the epigenetic age increased during the active season and essentially stalled during the hibernation period. Taken together, our results are consistent with the hibernation–ageing hypothesis and may explain the enhanced longevity in hibernators.

Introduction: Breast tissue age, measured with DNA methylation-based estimates, is accelerated in healthy women compared with matched peripheral blood samples. While we have shown that the degree of acceleration in breast epigenetic age is related to hormonal factors including elevated body mass index and earlier age at menarche, no prior work has examined alterations in gene expression that accompany breast epigenetic aging. In this study, we examine gene expression patterns associated with epigenetic age acceleration in healthy breast using six epigenetic clocks. Methods: Using the AllPrep (Qiagen) DNA/RNA Kit, we extracted DNA and RNA from the same breast tissue specimens from 192 healthy women aged 19-90 years who donated breast tissue to the Susan G. Komen Tissue Bank at the Indiana University Simon Comprehensive Cancer Center. Transcriptome analysis was performed using the QuantSeq 3’MRNA-SeqFWD kit to generate RNA sequencing libraries. DNA methylation was quantified using the Illumina EPIC 850K array platform, and methylation age was estimated using beta-values from these experiments. Age acceleration is defined using the residuals of a linear regression of methylation age on chronologic age, and samples with positive residuals were characterized as exhibiting epigenetic age acceleration. Differential gene expression analysis was performed using DESeq2 bioconductor software to estimate variance-mean dependence in count data and using a negative binomial distribution model to test for differential gene expression in samples with accelerated epigenetic age in 6 epigenetic clocks: the Horvath pan-tissue clock, Hannum Age, Phenotypic Age, Grim Age, Skin and Blood clock, and the Epigenetic Pacemaker clock (EPM) , a newly developed clock that accounts for curvilinearity in methylation-based estimates of age over time. Results: Principal components analysis revealed that a large proportion of the variance in gene expression was explained by the first two components (PC1 8.6%, PC2 8.2%). Using a false discovery rate cutoff of 0.05, we found 17 (pan-tissue), 909 (Hannum), 3573 (Phenotypic), 1459 (Grim), 3081 (Skin and Blood), and 227 (EPM) genes differentially expressed with the presence of epigenetic age acceleration for each clock. Examining overlap of these genes revealed distinct groups of genes differentially expressed with acceleration in each clock, with no genes in common for all clocks, Phenotypic and Skin and Blood clocks sharing 1137 genes; Phenotypic, Grim, and Skin and Blood clocks sharing 726 genes; and few genes shared by 5 out of 6 clocks (41 genes in all clocks except pan-tissue, 5 genes in all clocks except EPM). Gene set enrichment analysis revealed activation of pathways involved in cellular respiration, oxidative phosphorylation, energy derivation, organic acid metabolic processes, and immune response, and suppression of genes involved in embryonic epithelial morphogenesis, epidermal cell differentiation, chromatin organization, and lipoprotein transport. Conclusion: We identified significant alterations in gene expression patterns that accompany breast epigenetic acceleration in healthy female breast, with distinct patterns observed for six epigenetic clocks examined. Pathways involved include epithelial morphogenesis and differentiation, potentially representing a mechanistic link between breast accelerated aging and carcinogenesis. Citation Format: Mary Elizabeth Sehl, Wenbin Guo, Colin Farrell, Natascia Marino, Jill E. Henry, Anna Maria Storniolo, Jeannette Papp, Jingyi Jessica Li, Matteo Pellegrini, Steve Horvath, Patricia A. Ganz. Differential gene expression patterns in healthy breast tissue exhibiting epigenetic age acceleration [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-11-06.

DNA methylation modulates telomere function. In Arabidopsis thaliana, telomeric regions have a bimodal chromatin organization with unmethylated telomeres and methylated subtelomeres. To gain insight into this organization we have generated TAIR10-Tel, a modified version of the Arabidopsis reference genome with additional sequences at most chromosome ends. TAIR10-Tel has allowed us to analyse DNA methylation at nucleotide resolution level in telomeric regions. We have analysed the wild-type strain and mutants that encode inactive versions of all currently known relevant methyltransferases involved in cytosine methylation. These analyses have revealed that subtelomeric DNA methylation extends 1 to 2 kbp from Interstitial Telomeric Sequences (ITSs) that abut or are very near to telomeres. However, DNA methylation drops at the telomeric side of the telomere-subtelomere boundaries and disappears at the inner part of telomeres. We present a comprehensive and integrative model for subtelomeric DNA methylation that should help to decipher the mechanisms that govern the epigenetic regulation of telomeres. This model involves a complex network of interactions between methyltransferases and subtelomeric DNA sequences.

The neocortex is disproportionately expanded in human compared with mouse1,2, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers composed of neurons that selectively make connections within the neocortex and with other telencephalic structures. Single-cell transcriptomic analyses of human and mouse neocortex show an increased diversity of glutamatergic neuron types in supragranular layers in human neocortex and pronounced gradients as a function of cortical depth3. Here, to probe the functional and anatomical correlates of this transcriptomic diversity, we developed a robust platform combining patch clamp recording, biocytin staining and single-cell RNA-sequencing (Patch-seq) to examine neurosurgically resected human tissues. We demonstrate a strong correspondence between morphological, physiological and transcriptomic phenotypes of five human glutamatergic supragranular neuron types. These were enriched in but not restricted to layers, with one type varying continuously in all phenotypes across layers 2 and 3. The deep portion of layer 3 contained highly distinctive cell types, two of which express a neurofilament protein that labels long-range projection neurons in primates that are selectively depleted in Alzheimer’s disease4,5. Together, these results demonstrate the explanatory power of transcriptomic cell-type classification, provide a structural underpinning for increased complexity of cortical function in humans, and implicate discrete transcriptomic neuron types as selectively vulnerable in disease., Combined patch clamp recording, biocytin staining and single-cell RNA-sequencing of human neurocortical neurons shows an expansion of glutamatergic neuron types relative to mouse that characterizes the greater complexity of the human neocortex.

Immune cell-type composition changes with age, potentially weakening the response to infectious diseases. Profiling epigenetics marks of immune cells can help us understand the relationship with disease severity. We therefore leveraged a targeted DNA methylation method to study the differences in a cohort of pneumonia patients (both COVID-19 positive and negative) and unaffected individuals from peripheral blood. This approach allowed us to predict the pneumonia diagnosis with high accuracy (AUC = 0.92), and the PCR positivity to the SARS-CoV-2 viral genome with moderate, albeit lower, accuracy (AUC = 0.77). We were also able to predict the severity of pneumonia (PORT score) with an R2 = 0.69. By estimating immune cellular frequency from DNA methylation data, patients under the age of 65 positive to the SARS-CoV-2 genome (as revealed by PCR) showed an increase in T cells, and specifically in CD8+ cells, compared to the negative control group. Conversely, we observed a decreased frequency of neutrophils in the positive compared to the negative group. No significant difference was found in patients over the age of 65. The results suggest that this DNA methylation-based approach can be used as a cost-effective and clinically useful biomarker platform for predicting pneumonias and their severity. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

The anatomy of the mammalian visual system, from the retina to the neocortex, is organized hierarchically1. However, direct observation of cellular-level functional interactions across this hierarchy is lacking due to the challenge of simultaneously recording activity across numerous regions. Here we describe a large, open dataset-part of the Allen Brain Observatory2-that surveys spiking from tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli. Using cross-correlation analysis, we reveal that the organization of inter-area functional connectivity during visual stimulation mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas3. We find that four classical hierarchical measures-response latency, receptive-field size, phase-locking to drifting gratings and response decay timescale-are all correlated with the hierarchy. Moreover, recordings obtained during a visual task reveal that the correlation between neural activity and behavioural choice also increases along the hierarchy. Our study provides a foundation for understanding coding and signal propagation across hierarchically organized cortical and thalamic visual areas.

We present a unique, extensive, and open synaptic physiology analysis platform and dataset. Through its application, we reveal principles that relate cell type to synaptic properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Synaptic properties are heterogeneous in most subclass-to-subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, whereas the strength axis accounts for substantial heterogeneity within the subclass. In the human cortex, excitatory-to-excitatory synaptic dynamics are distinct from those in the mouse cortex and vary with depth across layers 2 and 3.

The epigenetic trajectory of DNA methylation profiles has a nonlinear relationship with time, reflecting rapid changes in DNA methylation early in life that progressively slow with age. In this study, we use pseudotime analysis to determine the functional form of these trajectories. Unlike epigenetic clocks that constrain the functional form of methylation changes with time, pseudotime analysis orders samples along a path, based on similarities in a latent dimension, to provide an unbiased trajectory. We show that pseudotime analysis can be applied to DNA methylation in human blood and brain tissue and find that it is highly correlated with the epigenetic states described by the Epigenetic Pacemaker. Moreover, we show that the pseudotime trajectory can be modeled with respect to time, using a sum of two exponentials, with coefficients that are close to the timescales of human age-associated mortality. Thus, for the first time, we can identify age-associated molecular changes that appear to track the exponential dynamics of mortality risk.

Purpose Data collected by the American Speech-Language-Hearing Association (ASHA) consistently show that over 50% of ASHA-certified speech-language pathologists (SLPs) are employed in a school-based setting. In such a setting, SLPs address a wide range of disorder areas. Key components of preparation for school-based practice are focused academic coursework, the clinical practicum in a school setting, and practicum supervisors who serve as key figures in training graduate students. This survey focused on the experiences and opinions of three groups: (a) graduate student clinicians who have completed a school-based practicum, (b) supervisors in the schools, and (c) new school-based SLPs. Method Convenience sampling was used to survey newly practicing school-based SLPs and school-based supervisors as well as graduate student clinicians at universities in the mid-south who have completed a school-based practicum. Surveys were posted to two ASHA Special Interest Groups and disseminated by selected graduate program directors to graduate student clinicians. Results were analyzed to measure satisfaction with preparation for school-based service. Surveys were completed electronically and analyzed both qualitatively and quantitatively for consistent themes and trends in responses. Results A total of 252 respondents completed the survey, the majority being school-based supervisors. Graduate clinicians and speech-language pathology supervisors shared similar attitudes regarding graduate clinician preparation for a school-based practicum, with most students indicating they received good or extensive preparation and, similarly, supervisors indicating that graduate students were adequately or well prepared. Differences were found in expectations between groups of what graduate students should know, skills identified as needing better development, and what is important for successful practice in the schools. Conclusions Many factors contribute to the success of a clinical practicum. While students, supervisors, and new employees share beliefs in what is important and have similar confidence in preparedness, there are differences in expectations between groups as well. Communication between university training programs, school-based supervisors, and dedicated coursework to school-based practice are key factors in the successful preparation of school-based clinicians.

To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes the cortical activity of nearly 60,000 neurons from six visual areas, four layers, and 12 transgenic mouse lines in a total of 243 adult mice, in response to a systematic set of visual stimuli. We classify neurons on the basis of joint reliabilities to multiple stimuli and validate this functional classification with models of visual responses. While most classes are characterized by responses to specific subsets of the stimuli, the largest class is not reliably responsive to any of the stimuli and becomes progressively larger in higher visual areas. These classes reveal a functional organization wherein putative dorsal areas show specialization for visual motion signals.

Effective conservation and management of threatened wildlife populations require an accurate assessment of age structure to estimate demographic trends and population viability. Epigenetic aging models are promising developments because they estimate individual age with high accuracy, accurately predict age in related species, and do not require invasive sampling or intensive long-term studies. Using blood and biopsy samples from known age plains zebras (Equus quagga), we model epigenetic aging using two approaches: the epigenetic clock (EC) and the epigenetic pacemaker (EPM). The plains zebra EC has the potential for broad application within the genus Equus given that five of the seven extant wild species of the genus are threatened. We test the EC’s ability to predict age in sister taxa, including two endangered species and the more distantly related domestic horse, demonstrating high accuracy in all cases. By comparing chronological and estimated age in plains zebras, we investigate age acceleration as a proxy of health status. An interaction between chronological age and inbreeding is associated with age acceleration estimated by the EPM, suggesting a cumulative effect of inbreeding on biological aging throughout life., Larison et al. report epigenetic aging models in plains zebras (Equus quagga) using the epigenetic clock and epigenetic pacemaker approaches. Their epigenetic clock allows age to be accurately estimated in endangered sister species, and the pacemaker model identifies an association between inbreeding and accelerating aging.

Epigenetic clocks, DNA methylation based chronological age prediction models, are commonly employed to study age related biology. The error between the predicted and observed age is often interpreted as a form of biological age acceleration and many studies have measured the impact of environmental and other factors on epigenetic age. Epigenetic clocks are fit using approaches that minimize the error between the predicted and observed chronological age and as a result they reduce the impact of factors that may moderate the relationship between actual and epigenetic age. Here we compare the standard methods used to construct epigenetic clocks to an evolutionary framework of epigenetic aging, the epigenetic pacemaker (EPM) that directly models DNA methylation as a function of a time dependent epigenetic state. We show that the EPM is more sensitive than epigenetic clocks for the detection of factors that moderate the relationship between actual age and epigenetic state (ie epigenetic age). Specifically, we show that the EPM is more sensitive at detecting sex and cell type effects in a large aggregate data set and in an example case study is more sensitive sensitive at detecting age related methylation changes associated with polybrominated biphenyl exposure. Thus we find that the pacemaker provides a more robust framework for the study of factors that impact epigenetic age acceleration than traditional clocks based on linear regression models.

Species that hibernate live longer than would be expected based solely on their body size. Hibernation is characterized by long periods of metabolic suppression (torpor) interspersed by short periods of increased metabolism (arousal). The torpor-arousal cycles occur multiple times during hibernation, and it has been suggested that processes controlling the transition between torpor and arousal states cause aging suppression. Metabolic rate is also a known correlate of longevity, we thus proposed the ‘hibernation-aging hypothesis’ whereby aging is suspended during hibernation. We tested this hypothesis in a well-studied population of yellow-bellied marmots (Marmota flaviventer), which spend 7-8 months per year hibernating. We used two approaches to estimate epigenetic age: the epigenetic clock and the epigenetic pacemaker. Variation in epigenetic age of 149 samples collected throughout the life of 73 females was modeled using generalized additive mixed models (GAMM), where season (cyclic cubic spline) and chronological age (cubic spline) were fixed effects. As expected, the GAMM using epigenetic ages calculated from the epigenetic pacemaker was better able to detect nonlinear patterns in epigenetic age change over time. We observed a logarithmic curve of epigenetic age with time, where the epigenetic age increased at a higher rate until females reached sexual maturity (2-years old). With respect to circannual patterns, the epigenetic age increased during the summer and essentially stalled during the winter. Our enrichment analysis of age-related CpG sites revealed pathways related to development and cell differentiation, while the season-related CpGs enriched pathways related to central carbon metabolism, immune system, and circadian clock. Taken together, our results are consistent with the hibernation-aging hypothesis and may explain the enhanced longevity in hibernators.

Species that hibernate generally live longer than would be expected based solely on their body size. Hibernation is characterized by long periods of metabolic suppression (torpor) interspersed by short periods of increased metabolism (arousal). The torpor-arousal cycles occur multiple times during hibernation, and it has been suggested that processes controlling the transition between torpor and arousal states cause ageing suppression. Metabolic rate is also a known correlate of longevity; we thus proposed the 'hibernation-ageing hypothesis' whereby ageing is suspended during hibernation. We tested this hypothesis in a well-studied population of yellow-bellied marmots (Marmota flaviventer), which spend 7-8 months per year hibernating. We used two approaches to estimate epigenetic age: the epigenetic clock and the epigenetic pacemaker. Variation in epigenetic age of 149 samples collected throughout the life of 73 females was modelled using generalized additive mixed models (GAMM), where season (cyclic cubic spline) and chronological age (cubic spline) were fixed effects. As expected, the GAMM using epigenetic ages calculated from the epigenetic pacemaker was better able to detect nonlinear patterns in epigenetic ageing over time. We observed a logarithmic curve of epigenetic age with time, where the epigenetic age increased at a higher rate until females reached sexual maturity (two years old). With respect to circannual patterns, the epigenetic age increased during the active season and essentially stalled during the hibernation period. Taken together, our results are consistent with the hibernation-ageing hypothesis and may explain the enhanced longevity in hibernators.

Background Bisulfite sequencing is commonly used to measure DNA methylation. Processing bisulfite sequencing data is often challenging owing to the computational demands of mapping a low-complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis-ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt), a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries. Findings We evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy. Conclusion BSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a Python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.

To elucidate cortical microcircuit structure and synaptic properties we present a unique, extensive, and public synaptic physiology dataset and analysis platform. Through its application, we reveal principles that relate cell type to synapse properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Despite these associations, synaptic properties are heterogeneous in most subclass to subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, while the strength axis accounts for significant heterogeneity within the subclass. In human cortex, excitatory to excitatory synapse dynamics are distinct from those in mouse and short-term plasticity varies with depth across layers 2 and 3. With a novel connectivity analysis that enables fair comparisons between circuit elements, we find that intralaminar connection probability among cell subclasses exhibits a strong layer dependence.These and other findings combined with the analysis platform create new opportunities for the neuroscience community to advance our understanding of cortical microcircuits.

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.

Epigenetic changes during ageing have been characterized by multiple epigenetic clocks that allow the prediction of chronological age based on methylation status. Despite their accuracy and utility, epigenetic age biomarkers leave many questions about epigenetic ageing unanswered. Specifically, they do not permit the unbiased characterization of non-linear epigenetic ageing trends across entire life spans, a critical question underlying this field of research. Here we provide an integrated framework to address this question. Our model, inspired from evolutionary models, is able to account for acceleration/deceleration in epigenetic changes by fitting an individual's model age, the epigenetic age, which is related to chronological age in a non-linear fashion. Application of this model to DNA methylation data measured across broad age ranges, from before birth to old age, and from two tissue types, suggests a universal logarithmic trend characterizes epigenetic ageing across entire lifespans.

Five of the seven extant wild species of the genus Equus are species of significant conservation concern. Effective conservation and management of such threatened wildlife populations depends on the ability to estimate demographic trends and population viability and therefore requires accurate assessment of age structure. However, reliably aging wildlife is challenging as many methods are highly invasive, inaccurate, or both. Epigenetic aging models, which estimate individual age with high accuracy based on genomic methylation patterns, are promising developments in this regard. Importantly, epigenetic aging models developed for one species can potentially predict age with high accuracy in sister taxa. Using blood and biopsy samples from known age plains zebras (Equus quagga), we developed epigenetic clocks (ECs) to predict chronological age, and epigenetic pacemaker (EPM) models to predict biological age. We tested the ability of our blood-based EC to predict ages of Grevy’s zebras, Somali asses and domestic horses, from blood samples. Because our samples came from a population with a complex pedigree, we also leveraged information from a previous sequencing effort to measure the association between levels of inbreeding (F and ROH) and the age acceleration as measured by DNA methylation. The resulting models describe the trajectory of epigenetic aging in plains zebras and accurately predict the ages of plains zebras and other equids. We found moderate support for a slight acceleration of aging with increased inbreeding.

Species that hibernate live longer than would be expected based solely on their body size. Hibernation is characterized by long periods of metabolic suppression (torpor) interspersed by short periods of increased metabolism (arousal). The torpor-arousal cycles occur multiple times during hibernation, and it has been suggested that processes controlling the transition between torpor and arousal states cause aging suppression. Metabolic rate is also a known correlate of longevity, we thus proposed the ‘hibernation-aging hypothesis’ whereby aging is suspended during hibernation. We tested this hypothesis in a well-studied population of yellow-bellied marmots (Marmota flaviventer), which spend 7-8 months per year hibernating. We used two approaches to estimate epigenetic age: the epigenetic clock and the epigenetic pacemaker. Variation in epigenetic age of 149 samples collected throughout the life of 73 females were modeled using generalized additive mixed models (GAMM), where season (cyclic cubic spline) and chronological age (cubic spline) were fixed effects. As expected, the GAMM using epigenetic ages calculated from the epigenetic pacemaker was better able to detect nonlinear patterns in epigenetic age change over time. We observed a logarithmic curve of epigenetic age with time, where the epigenetic age increased at a higher rate until females reached sexual maturity (2-years old). With respect to circannual patterns, the epigenetic age increased during the summer and essentially stalled during the winter. Our enrichment analysis of age-related CpG sites revealed pathways related to development and cell differentiation, while the season-related CpGs enriched pathways related to central carbon metabolism, immune system, and circadian clock. Taken together, our results are consistent with the hibernation-aging hypothesis and may explain the enhanced longevity in hibernators.

Cytosine methylation is one of the best studied epigenetic modifications. In mammals, DNA methylation patterns vary among cells and is mainly found in the CpG context. DNA methylation is involved in important processes during development and differentiation and its dysregulation can lead to or is associated with diseases, such as cancer, loss-of-imprinting syndromes and neurological disorders. It has been also shown that DNA methylation at the cellular, tissue and organism level varies with age. To overcome the costs of Whole-Genome Bisulfite Sequencing, the gold standard method to detect 5-methylcytosines at a single base resolution, DNA methylation arrays have been developed and extensively used. This method allows one to assess the status of a fraction of the CpG sites present in the genome of an organism. In order to combine the relatively low cost of Methylation Arrays and digital signals of bisulfite sequencing, we developed a Targeted Bisulfite Sequencing method that can be applied to biomarker discovery for virtually any phenotype. Here we describe a comprehensive step-by-step protocol to build a DNA methylation-based epigenetic clock.

Extrapulmonary manifestations of COVID-19 are associated with a much higher mortality rate than pulmonary manifestations. However, little is known about the pathogenesis of systemic complications of COVID-19. Here, we create a murine model of SARS-CoV-2-induced severe systemic toxicity and multiorgan involvement by expressing the human ACE2 transgene in multiple tissues via viral delivery, followed by systemic administration of SARS-CoV-2. The animals develop a profound phenotype within 7 days with severe weight loss, morbidity, and failure to thrive. We demonstrate that there is metabolic suppression of oxidative phosphorylation and the tricarboxylic acid (TCA) cycle in multiple organs with neutrophilia, lymphopenia, and splenic atrophy, mirroring human COVID-19 phenotypes. Animals had a significantly lower heart rate, and electron microscopy demonstrated myofibrillar disarray and myocardial edema, a common pathogenic cardiac phenotype in human COVID-19. We performed metabolomic profiling of peripheral blood and identified a panel of TCA cycle metabolites that served as biomarkers of depressed oxidative phosphorylation. Finally, we observed that SARS-CoV-2 induces epigenetic changes of DNA methylation, which affects expression of immune response genes and could, in part, contribute to COVID-19 pathogenesis. Our model suggests that SARS-CoV-2-induced metabolic reprogramming and epigenetic changes in internal organs could contribute to systemic toxicity and lethality in COVID-19.

Cardiac fibrosis is a pathophysiologic hallmark of the aging heart, but little is known about how fibroblast proliferation and transcriptional programs change throughout the life span of the organism. Using EdU pulse labeling, we demonstrated that more than 50% of cardiac fibroblasts were actively proliferating in the first day of postnatal life. However, by 4 weeks, only 10% of cardiac fibroblasts were proliferating. By early adulthood, the fraction of proliferating cardiac fibroblasts further decreased to approximately 2%, where it remained throughout the rest of the organism's life. We observed that maximal changes in cardiac fibroblast transcriptional programs and, in particular, collagen and ECM gene expression both in the heart and cardiac fibroblast were maximal in the newly born and juvenile animal and decreased with organismal aging. Examination of DNA methylation changes both in the heart and in cardiac fibroblasts did not demonstrate significant changes in differentially methylated regions between young and old mice. Our observations demonstrate that cardiac fibroblasts attain a stable proliferation rate and transcriptional program early in the life span of the organism and suggest that phenotypic changes in the aging heart are not directly attributable to changes in proliferation rate or altered collagen expression in cardiac fibroblasts.

Transgenic T-cell receptor (TCR) adoptive cell therapies recognizing tumor antigens are associated with robust initial response rates, but frequent disease relapse. This usually occurs in the setting of poor long-term persistence of cells expressing the transgenic TCR, generated using murine stem cell virus (MSCV) γ-retroviral vectors. Analysis of clinical transgenic adoptive cell therapy products in vivo revealed that despite strong persistence of the transgenic TCR DNA sequence over time, its expression was profoundly decreased over time at the RNA and protein levels. Patients with the greatest degrees of expression suppression displayed significant increases in DNA methylation over time within the MSCV promoter region, as well as progressive increases in DNA methylation within the entire MSCV vector over time. These increases in vector methylation occurred independently of its integration site within the host genomes. These results have significant implications for the design of future viral vector gene–engineered adoptive cell transfer therapies. Significance: Cellular immunotherapies' reliance on retroviral vectors encoding foreign genetic material can be vulnerable to progressive acquisition of DNA methylation and subsequent epigenetic suppression of the transgenic product in TCR adoptive cell therapy. This must be considered in the design of future generations of cellular immunotherapies for cancer. This article is highlighted in the In This Issue feature, p. 1611

Robust biomarkers of aging have been developed from DNA methylation in humans and more recently, in mice. This study aimed to generate a novel epigenetic clock in rats—a model with unique physical, physiological, and biochemical advantages—by incorporating behavioral data, unsupervised machine learning, and network analysis to identify epigenetic signals that not only track with age, but also relates to phenotypic aging. Reduced representation bisulfite sequencing (RRBS) data was used to train an epigenetic age (DNAmAge) measure in Fischer 344 CDF (F344) rats. This measure correlated with age at (r = 0.93) in an independent sample, and related to physical functioning (p=5.9e-3), after adjusting for age and cell counts. DNAmAge was also found to correlate with age in male C57BL/6 mice (r = 0.79), and was decreased in response to caloric restriction. Our signatures driven by CpGs in intergenic regions that showed substantial overlap with H3K9me3, H3K27me3, and E2F1 transcriptional factor binding.

Aging has been shown to be a strong driver of DNA methylation changes, leading to the development of robust biomarkers in humans and more recently, in mice. This study aimed to generate a novel epigenetic clock in rats—a model with unique physical, physiological, and biochemical advantages for studying mammalian aging. Additionally, we incorporated behavioral data, unsupervised machine learning, and network analysis to identify epigenetic signals that not only track with age, but also relate to phenotypic aging and reflect higher-order molecular aging changes. We used DNAm data from reduced representation bisulfite sequencing (RRBS) to train an epigenetic age (DNAmAge) measure in Fischer 344 CDF (F344) rats. In an independent sample of n=32 F344 rats, we found that this measure correlated with age at (r=0.93), and related to physical functioning (5.9e-3), after adjusting for age and differential cell counts. DNAmAge was also found to correlate with age in C57BL/6 mice (r=0.79), and was decreased in response to caloric restriction (CR), such that the longer the animal was on a CR diet, the greater the decrease in DNAm. We also observed resetting of DNAm when kidney and lung fibroblasts when converted to induced pluripotent stem cells (iPSCs). Using weighted gene correlation network analysis (WGCNA) we identified two modules that appeared to drive our DNAmAge measure. These two modules contained CpGs in intergenic regions that showed substantial overlap with histone marks H3K9me3, H3K27me3, and E2F1 transcriptional factor binding. In moving forward, our ability to unravel the complex signals linking DNA methylation changes to functional aging would require experimental studies in model systems in which longitudinal epigenetic changes can be related to other molecular and physiological hallmarks of aging.

The neocortex is disproportionately expanded in human compared to mouse, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers that selectively make connections within the cortex and other telencephalic structures. Single-cell transcriptomic analyses of human and mouse cortex show an increased diversity of glutamatergic neuron types in supragranular cortex in human and pronounced gradients as a function of cortical depth. To probe the functional and anatomical correlates of this transcriptomic diversity, we describe a robust Patch-seq platform using neurosurgically-resected human tissues. We characterize the morphological and physiological properties of five transcriptomically defined human glutamatergic supragranular neuron types. Three of these types have properties that are specialized compared to the more homogeneous properties of transcriptomically defined homologous mouse neuron types. The two remaining supragranular neuron types, located exclusively in deep layer 3, do not have clear mouse homologues in supragranular cortex but are transcriptionally most similar to deep layer mouse intratelencephalic-projecting neuron types. Furthermore, we reveal the transcriptomic types in deep layer 3 that express high levels of non-phosphorylated heavy chain neurofilament protein that label long-range neurons known to be selectively depleted in Alzheimer’s disease. Together, these results demonstrate the power of transcriptomic cell type classification, provide a mechanistic underpinning for increased complexity of cortical function in human cortical evolution, and implicate discrete transcriptomic cell types as selectively vulnerable in disease.

Summary Epigenetic rates of change, much as evolutionary mutation rate along a lineage, vary during lifetime. Accurate estimation of the epigenetic state has vast medical and biological implications. To account for these non-linear epigenetic changes with age, we recently developed a formalism inspired by the Pacemaker model of evolution that accounts for varying rates of mutations with time. Here, we present a python implementation of the Epigenetic Pacemaker (EPM), a conditional expectation maximization algorithm that estimates epigenetic landscapes and the state of individuals and may be used to study non-linear epigenetic aging. Availability and Implementation The EPM is available at https://pypi.org/project/EpigeneticPacemaker/ under the MIT license. The EPM is compatible with python version 3.6 and above.

Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 3,700 GABAergic mouse visual cortical neurons and reconstructed the local morphologies of 350 of those neurons. We found that most transcriptomic types (t-types) occupy specific laminar positions within mouse visual cortex, and many of those t-types exhibit consistent electrophysiological and morphological features. We observed that these properties could vary continuously between t-types, which limited the ability to predict specific t-types from other data modalities. Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.HighlightsPatch-seq data obtained from >3,700 GABAergic cortical interneuronsComprehensive characterization of morpho-electric features of transcriptomic types20 interneuron met-types that have congruent properties across data modalitiesDifferent Sst met-types preferentially innervate different cortical layers

BACKGROUNDThe Allen Institute recently built a set of high-throughput experimental pipelines to collect comprehensive in vivo surveys of physiological activity in the visual cortex of awake, head-fixed mice. Developing these large-scale, industrial-like pipelines posed many scientific, operational, and engineering challenges.NEW METHODOur strategies for creating a cross-platform reference space to which all pipeline datasets were mapped required development of 1) a robust headframe, 2) a reproducible clamping system, and 3) data-collection systems that are built, and maintained, around precise alignment with a reference artifact.RESULTSWhen paired with our pipeline clamping system, our headframe exceeded deflection and reproducibility requirements. By leveraging our headframe and clamping system we were able to create a cross-platform reference space to which multi-modal imaging datasets could be mapped.COMPARISON WITH EXISTING METHODSTogether, the Allen Brain Observatory headframe, surgical tooling, clamping system, and system registration strategy create a unique system for collecting large amounts of standardized in vivo datasets over long periods of time. Moreover, the integrated approach to cross-platform registration allows for multi-modal datasets to be collected within a shared reference space.CONCLUSIONSHere we report the engineering strategies that we implemented when creating the Allen Brain Observatory physiology pipelines. All of the documentation related to headframe, surgical tooling, and clamp design has been made freely available and can be readily manufactured or procured. The engineering strategy, or components of the strategy, described in this report can be tailored and applied by external researchers to improve data standardization and stability.

Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 3,700 GABAergic mouse visual cortical neurons and reconstructed the local morphologies of 350 of those neurons. We found that most transcriptomic types (t-types) occupy specific laminar positions within mouse visual cortex, and many of those t-types exhibit consistent electrophysiological and morphological features. We observed that these properties could vary continuously between t- types, which limited the ability to predict specific t-types from other data modalities. Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.

The anatomy of the mammalian visual system, from the retina to the neocortex, is organized hierarchically

The mammalian visual system, from retina to neocortex, has been extensively studied at both anatomical and functional levels. Anatomy indicates the cortico-thalamic system is hierarchical, but characterization of cellular-level functional interactions across multiple levels of this hierarchy is lacking, partially due to the challenge of simultaneously recording activity across numerous regions. Here, we describe a large, open dataset (part of theAllen Brain Observatory) that surveys spiking from units in six cortical and two thalamic regions responding to a battery of visual stimuli. Using spike cross-correlation analysis, we find that inter-area functional connectivity mirrors the anatomical hierarchy from theAllen Mouse Brain Connectivity Atlas. Classical functional measures of hierarchy, including visual response latency, receptive field size, phase-locking to a drifting grating stimulus, and autocorrelation timescale are all correlated with the anatomical hierarchy. Moreover, recordings during a visual task support the behavioral relevance of hierarchical processing. Overall, this dataset and the hierarchy we describe provide a foundation for understanding coding and dynamics in the mouse cortico-thalamic visual system.

Serial-section electron microscopy is the method of choice for studying cellular structure and network connectivity in the brain. We have built a pipeline of parallel imaging using transmission electron automated microscopes (piTEAM) that scales this technology and enables the acquisition of petascale datasets containing local cortical microcircuits. The distributed platform is composed of multiple transmission electron microscopes that image, in parallel, different sections from the same block of tissue, all under control of a custom acquisition software (pyTEM) that implements 24/7 continuous autonomous imaging. The suitability of this architecture for large scale electron microscopy imaging was demonstrated by acquiring a volume of more than 1 mm3 of mouse neocortex spanning four different visual areas. Over 26,500 ultrathin tissue sections were imaged, yielding a dataset of more than 2 petabytes. Our current burst imaging rate is 500 Mpixel/s (image capture only) per microscope and net imaging rate is 100 Mpixel/s (including stage movement, image capture, quality control, and post processing). This brings the combined burst acquisition rate of the pipeline to 3 Gpixel/s and the net rate to 600 Mpixel/s with six microscopes running acquisition in parallel, which allowed imaging a cubic millimeter of mouse visual cortex at synaptic resolution in less than 6 months.

Visual cortex is organized into discrete sub-regions or areas that are arranged into a hierarchy and serve different functions in the processing of visual information. In our previous work, we noted that retinotopic maps of cortical visual areas differed between mice, but did not quantify these differences or determine the relative contributions of biological variation and measurement noise. Here we quantify the biological variation in the size, shape and locations of 11 visual areas in the mouse. We find that there is substantial biological variation in the sizes of visual areas, with some visual areas varying in size by two-fold across the population of mice.

We report a novel two-photon fluorescence microscope based on a fast-switching liquid crystal spatial light modulator and a pair of galvo-resonant scanners for large-scale recording of neural activity from the mammalian brain. The utilized imaging technique is capable of monitoring large populations of neurons spread across different layers of the neocortex in awake and behaving mice. During each imaging session, all visual stimulus driven somatic activity could be recorded in the same behavior state. We observed heterogeneous response to different types of visual stimuli from ~ 3,300 excitatory neurons reaching from layer II/III to V of the striate cortex.

IMPACT: This work may provide new targets for vaccine and immunotherapeutic development against MRSA infections. OBJECTIVES/GOALS: Staphylococcus aureus is the leading cause of skin and skin structure infection (SSSI), a primary portal of entry for invasive infection. Patients with SA SSSI have a high 1-year recurrence. We have shown innate memory protects mice against SA SSSI. The goal of this project is to determine epigenetic mechanisms of protective memory against SA SSSI. METHODS/STUDY POPULATION: We have shown macrophages (Mf) afford protective memory against recurrent SA SSSI in mice. Priming by prior infection reduced skin lesion size and MRSA burden, which correlated with increased Mf in abscesses and lymph nodes. Priming potentiated the opsonophagocytic killing of SA by bone-marrow derived Mf (BMDM) in vitro, and their adoptive transfer into naive skin afforded protective efficacy in vivo. Here, we investigated epigenetic mechanisms of anti-SA efficacy in BMDMs. BMDM from naive (uninfected) or primed (SA SSSI) wild-type C57Bl/6 mice were cultured ex vivo. DNA from BMDM groups were isolated and analyzed for methylation changes using reduced representation bisulfite sequencing (RRBS). Pathway analyses of methylation changes were determined with Panther. RESULTS/ANTICIPATED RESULTS: Present findings indicate the protective memory afforded by BMDM was mediated by epigenetic modifications of the DNA. Using RRBS, we profiled differentially methylated regions (DMR) in DNA from naive vs. primed BMDM. Primed BMDM exhibited significantly different DMRs as compared to naive BMDM. Proximity to known genes were mapped using GREAT. Pathway analyses revealed DMRs predominant in genes integral to immune modulation, such as integrin signaling, cytokine/chemokine networks, and growth regulation. For example, SA-primed BMDM were hypermethylated proximate to GIMAP8 versus naive BMDM, suggesting repression of this protein. Gimap family ligands are small GTPase immune-associated proteins expressed in immune cells known to regulate macrophage lysosomal fusion during parasite infection. DISCUSSION/SIGNIFICANCE OF FINDINGS: These findings reveal epigenetic mechanisms of macrophage innate memory against recurrent MRSA infection. Functional testing of these genes in response to SA infection is needed to confirm their protective role. These insights may provide new targets for vaccine and immunotherapeutic development against MRSA.

Background The Allen Institute recently built a set of high-throughput experimental pipelines to collect comprehensive in vivo surveys of physiological activity in the visual cortex of awake, head-fixed mice. Developing these large-scale, industrial-like pipelines posed many scientific, operational, and engineering challenges. New method Our strategies for creating a cross-platform reference space to which all pipeline datasets were mapped required development of 1) a robust headframe, 2) a reproducible clamping system, and 3) data-collection systems that are built, and maintained, around precise alignment with a reference artifact. Results When paired with our pipeline clamping system, our headframe exceeded deflection and reproducibility requirements. By leveraging our headframe and clamping system we were able to create a cross-platform reference space to which multi-modal imaging datasets could be mapped. Comparison with existing methods Together, the Allen Brain Observatory headframe, surgical tooling, clamping system, and system registration strategy create a unique system for collecting large amounts of standardized in vivo datasets over long periods of time. Moreover, the integrated approach to cross-platform registration allows for multi-modal datasets to be collected within a shared reference space. Conclusions Here we report the engineering strategies that we implemented when creating the Allen Brain Observatory physiology pipelines. All of the documentation related to headframe, surgical tooling, and clamp design has been made freely available and can be readily manufactured or procured. The engineering strategy, or components of the strategy, described in this report can be tailored and applied by external researchers to improve data standardization and stability.

Neurons are frequently classified into distinct types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 4,200 mouse visual cortical GABAergic interneurons and reconstructed the local morphologies of 517 of those neurons. We find that most transcriptomic types (t-types) occupy specific laminar positions within visual cortex, and, for most types, the cells mapping to a t-type exhibit consistent electrophysiological and morphological properties. These properties display both discrete and continuous variation among t-types. Through multimodal integrated analysis, we define 28 met-types that have congruent morphological, electrophysiological, and transcriptomic properties and robust mutual predictability. We identify layer-specific axon innervation pattern as a defining feature distinguishing different met-types. These met-types represent a unified definition of cortical GABAergic interneuron types, providing a systematic framework to capture existing knowledge and bridge future analyses across different modalities.

Introduction: Gamblers' enduring illusions of control (IOC) may be one reason why they continue to gamble in the face of sustained losses. If gamblers persist in the belief that they have special skills, knowledge and other advantages when gambling, they may be able to convince themselves it is worth doing again. Maintaining an IOC requires selective attention of the illusion supporting moments during the construction of an evaluation of a gambling session.Objective: Test the hypothesis that selected moments, specifically the moment of the highest win and the last moment of the gaming session, explain the retrospective evaluation of the session for gamblers high in the illusion of control.Method: A total of 102 and 35 experienced gamblers were recruited from gambling venues and participated in two studies by gambling on 20 occasions on coin toss outcomes. Participants were asked to evaluate their enjoyment of the gambling experience they had just completed, and completed an IOC Beliefs Questionnaire designed to measure the extent to which they believe they are good at influencing gambling outcomes.Results: Gamblers with a high IOC use the largest win in their evaluation when they lose. This is consistent with the motivated selective attention hypothesis. Non-threatened gamblers, those with a low IOC or winners, use the final outcome as the determinant of their evaluation of the gaming session.Conclusion: The results suggest that instead of altering an important characteristic of self, gamblers instead reflect on the moment of a gambling episode that does not threaten, and in fact supports, their ability to find patterns in random events. Indicators of the illusion could be used to assist gamblers in controlling their own behavior.