Biology subjects

Miller, J. A.

Publications and source records attributed to Miller, J. A..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Reference-based cell type matching of spatial transcriptomics data

With the advent of multiplex fluorescence in situ hybridization (FISH) and in situ RNA sequencing technologies, spatial transcriptomics analysis is advancing rapidly. Spatial transcriptomics provides spatial location and pattern information about cells in tissue sections at single cell resolution. Cell type classification of spatially-resolved cells can also be inferred by matching the spatial transcriptomics data to reference single cell RNA-sequencing (scRNA-seq) data with cell types determined by their gene expression profiles. However, robust cell type matching of the spatial cells is challenging due to the intrinsic differences in resolution between the spatial and scRNA-seq data. In this study, we systematically evaluated six computational algorithms for cell type matching across four spatial transcriptomics experimental protocols (MERFISH, smFISH, BaristaSeq, and ExSeq) conducted on the same mouse primary visual cortex (VISp) brain region. We find that while matching results of individual algorithms vary to some degree, they also show agreement to some extent. We present two ensembl meta-analysis strategies to combine the individual matching results and share the consensus matching results in the Cytosplore Viewer (https://viewer.cytosplore.org) for interactive visualization and data exploration. The consensus matching can also guide spot-based spatial data analysis using SSAM, allowing segmentation-free cell type assignment.

bioinformatics↗

bioRxiv2022

Hominoid-specific sulcal variability is related to face perception ability

Human perception requires complex cortical networks that function at neuroanatomical scales of microns and temporal scales of milliseconds. Despite this complexity, what if just one morphological feature of the brain could predict perceptual ability? Here, we tested this hypothesis with pre-registered analyses of neuroanatomy and face perception in neurotypical controls (NTs) and individuals with developmental prosopagnosia (DPs). Results show that the length of the mid-fusiform sulcus (MFS), a hominoid-specific tertiary sulcus in ventral temporal cortex (VTC), was shorter in DPs than NTs. Furthermore, individual differences in MFS length in the right, but not left, hemisphere predicted individual differences in face perception. These results support theories linking brain structure and function to perception, as well as indicate that one feature - variability in MFS length - can predict face perception. Finally, these findings add to growing evidence supporting a role of morphological variability of late developing, tertiary sulci and individual differences in cognition.

neuroscience↗

bioRxiv2021

Sulcal depth in prefrontal cortex: A novel predictor of working memory performance

The neuroanatomical changes that underpin cognitive development is of major interest in neuroscience. Of the many aspects of neuroanatomy to consider, tertiary sulci are particularly appealing as they emerge last in gestation, show a protracted development after birth, and are either human- or hominoid-specific. Thus, they are ideal targets for exploring morphological-cognitive relationships with cognitive skills, such as verbal working memory (WM), that also show protracted development. Yet, the relationship between sulcal morphology and verbal WM is unknown, either in development or more generally. To fill this gap, we adopted a data-driven approach with cross-validation to examine the relationship between sulcal depth in lateral prefrontal cortex (LPFC) and verbal WM in 60 participants ages 6-18. These analyses identified nine left, but not right, LPFC sulci (of which six were tertiary) whose depth predicted verbal WM performance. Most of these sulci are located within and around contours of functionally defined parcellations of LPFC proposed previously. This sulcal depth model out-performed models with age or cortical thickness. Taken together, these findings contribute to building empirical support for a classic theory that tertiary sulci serve as landmarks in association cortices that contribute to aspects of human behavior that show a protracted development.

neuroscience↗

bioRxiv2021

A new tripartite landmark in posterior cingulate cortex

Understanding brain structure-function relationships, and their development and evolution, is central to neuroscience research. Here, we show that morphological differences in posterior cingulate cortex (PCC), a hub of functional brain networks, predict individual differences in macroanatomical, microstructural, and functional features of PCC. Manually labeling 4,319 sulci in 552 hemispheres, we discovered a consistently localized shallow cortical indentation (termed the inframarginal sulcus; ifrms) within PCC that is absent from neuroanatomical atlases, yet co-localized with a region within the cognitive control, but not default mode, network. Morphological analyses in humans and chimpanzees showed that unique properties of the ifrms differ across the lifespan and between hominoid species. Intriguingly, the consistency of the ifrms also debunks the uniqueness of the morphology of Einsteins PCC. These findings support a classic theory that shallow, tertiary sulci serve as landmarks in association cortices. They also beg the question: how many other cortical indentations have we missed?

neuroscience↗

bioRxiv2021

Brain Data Standards Ontology: A data-driven ontology of transcriptomically defined cell types in the primary motor cortex

Large-scale single-cell omics profiling is revolutionising our understanding of cell types in complex organs like the brain, where it is being used to define a complete catalogue of cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem. How do we organise such a catalogue - providing a standard way to refer to the cell types discovered, linking their classification and properties to supporting data? Cell ontologies provide a solution to recording definitions, classifications, and properties of cell types and provide standard identifiers for annotation, but they currently do not support the data driven cell type definitions and classifications needed for multi-modal single cell omics profiling. Here we describe the construction and application of a semi-automated, data-linked extension to the Cell Ontology that represents cell types in the Primary Motor Cortex of humans, mice and marmosets. The methods and resulting ontology are designed to be scalable and applicable to similar whole brain atlases currently in preparation.

neuroscience↗

bioRxiv2021

Anatomical Structures, Cell Types, and Biomarkers Tables Plus 3D Reference Organs in Support of a Human Reference Atlas

1.This paper reviews efforts across 16 international consortia to construct human anatomical structures, cell types, and biomarkers (ASCT+B) tables and three-dimensional reference organs in support of a Human Reference Atlas. We detail the ontological descriptions and spatial three-dimensional anatomical representations together with user interfaces that support the registration and exploration of human tissue data. Four use cases are presented to demonstrate the utility of ASCT+B tables for advancing biomedical research and improving health.

cell biology↗

bioRxiv2021

Structural and cellular transcriptome foundations of human brain disease

Genes associated with risk for brain disease exhibit characteristic expression patterns that reflect both anatomical and cell type relationships. Brain-wide transcriptomic patterns of disease risk genes provide a molecular based signature for identifying disease association, often differing from common phenotypic classification. Analysis of adult brain-wide transcriptomic patterns associated with 40 human brain diseases identified five major transcriptional patterns, represented by tumor-related, neurodegenerative, psychiatric and substance abuse, and two mixed groups of diseases. Brain disease risk genes exhibit unique anatomic transcriptomic signatures, based on differential co-expression, that often uniquely identify the disease. For cortical expressing diseases, single nucleus data in the middle temporal gyrus reveals cell type expression gradients separating neurodegenerative, psychiatric, and substance abuse diseases. By homology mapping of cell types across mouse and human, transcriptomic disease signatures are found largely conserved, but with psychiatric and substance abuse related diseases showing important specific species differences. These results describe the structural and cellular transcriptomic landscape of disease in the adult brain, highlighting significant homology with the mouse yet indicating where human data is needed to further refine our understanding of disease-associated genes.

neuroscience↗

bioRxiv2021

The type 2 diabetes factor methylglyoxal mediates axon initial segment shortening and neuronal network activity changes

Recent evidence suggests that alteration of axon initial segment (AIS) geometry (i.e., length or position along the axon) contributes to CNS dysfunction in neurological diseases. For example, AIS length is shorter in the prefrontal cortex of type 2 diabetic mice with cognitive impairment. The key type 2 diabetes-related factor that alters AIS geometry is unknown. Here, we tested whether modifying the levels of insulin, glucose, or methylglyoxal, a reactive carbonyl species that is a metabolite of glucose, changes AIS geometry in mature cultures of dissociated postnatal mouse cortex using immunofluorescent imaging of the AIS proteins AnkyrinG and {beta}IV spectrin. Neither insulin nor glucose modification appreciably altered AIS length. Elevation of methylglyoxal produced reversible AIS shortening without cell death. Multi-electrode array recordings revealed a biphasic effect of methylglyoxal on neuronal network activity: an immediate, transient [~]300% increase in spiking and bursting rates was followed by a [~]20% reduction from baseline at 3 h. AIS length was unchanged at 0.5 h or 3 h after adding methylglyoxal, whereas development of AIS shortening at 24 h was associated with restoration of spiking to baseline levels. Immunostaining for the excitatory neuron marker Ca2+/calmodulin-dependent protein kinase II alpha revealed AIS shortening in both excitatory and inhibitory neuron populations. This suggests that complex mechanisms maintain neuronal network operation after acute exposure to the disease metabolite methylglyoxal. Importantly, our results indicate that methylglyoxal could be a key mediator of AIS shortening during type 2 diabetes. Significance StatementSmall changes in the structure of the axon initial segment affect neuronal function and may be a key mediator of neurological complications in various disease states. However, the specific disease factors that mediate structural changes at the axon initial segment are relatively unknown. This is the first study to show that increase of methylglyoxal is sufficient to reduce axon initial segment length and modulate neuronal network function. Methylglyoxal is a disease factor implicated in a wide variety of conditions including type 2 diabetes, Alzheimers disease, and aging. Thus, these findings could significantly impact the understanding of neurological complications in several disease states and are of broad pathophysiological relevance.

neuroscience↗

bioRxiv2021

Comprehensive in situ mapping of human cortical transcriptomic cell types

The ability to spatially resolve the cellular architecture of human cortical cell types over informative areas is essential to understanding brain function. We combined in situ sequencing gene expression data and single-nucleus RNA-sequencing cell type definitions to spatially map cells in sections of the human cortex via probabilistic cell typing. We mapped and classified a total of 59,816 cells into all 75 previously defined subtypes to create a first spatial atlas of human cortical cells in their native position, their abundances and genetic signatures.

neuroscience↗

bioRxiv2020

Cognitive insights from evolutionarily new brain structures in prefrontal cortex

While the disproportionate expansion of lateral prefrontal cortex (LPFC) in humans compared to non-human primates is accepted, the relationship between evolutionarily new LPFC brain structures and uniquely human cognitive skills is largely unknown. Here, we tested the relationship between variability in evolutionarily new LPFC tertiary sulci and reasoning skills in a pediatric cohort. A novel data-driven approach in independent discovery and replication samples revealed that the depth of specific LPFC tertiary sulci predicts individual differences in reasoning skills beyond age. These findings support a classic, yet untested, theory linking the protracted development of tertiary sulci to late-developing cognitive processes. We suggest that deeper LPFC tertiary sulci reflect reduced short-range connections in white matter, which in turn, improve the efficiency of local neural signals underlying cognitive skills such as reasoning that are central to human cognitive development. To expedite discoveries in future neuroanatomical-behavioural studies, we share sulcal definitions with the field.

neuroscience↗

bioRxiv2020

High fidelity electrophysiological, morphological, and transcriptomic cell characterization using a refined Patch-seq protocol

The Patch-seq approach is a powerful variation of the standard patch clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at a scale and quality that can be integrated with high-throughput dissociated cell transcriptomic data, we have optimized the technique by identifying and refining key factors that contribute to the efficient collection of high-quality data. To rapidly generate high-quality electrophysiology data, we developed patch clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized a substantial improvement in transcriptomic data quality when the nucleus was extracted following the recording. For morphology success, the importance of maximizing the neurons membrane integrity during the extraction of the nucleus was much more critical to success than varying the duration of the electrophysiology recording. We compiled the lab protocol with the analysis and acquisition software at https://github.com/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate Patch-seq data across diverse mammalian species and that is compatible with recent large-scale publicly available Allen Institute Patch-seq datasets.

neuroscience↗

bioRxiv2020

NS-Forest: A machine learning method for the objective identification of minimum marker gene combinations for cell type determination from single cell RNA sequencing

Single cell genomics is rapidly advancing our knowledge of cell phenotypic types and states. Driven by single cell/nucleus RNA sequencing (scRNA-seq) data, comprehensive atlas projects covering a wide range of organisms and tissues are currently underway. As a result, it is critical that the cell transcriptional phenotypes discovered are defined and disseminated in a consistent and concise manner. Molecular biomarkers have historically played an important role in biological research, from defining immune cell-types by surface protein expression to defining diseases by molecular drivers. Here we describe a machine learning-based marker gene selection algorithm, NS-Forest version 2.0, which leverages the non-linear attributes of random forest feature selection and a binary expression scoring approach to discover the minimal marker gene expression combinations that precisely captures the cell type identity represented in the complete scRNA-seq transcriptional profiles. The marker genes selected provide a barcode of the necessary and sufficient characteristics for semantic cell type definition and serve as useful tools for downstream biological investigation. The use of NS-Forest to identify marker genes for human brain middle temporal gyrus cell types reveals the importance of cell signaling and non-coding RNAs in neuronal cell type identity.

bioinformatics↗

bioRxiv2020

Consistent cross-modal identification of cortical neurons with coupled autoencoders

Consistent identification of neurons in different experimental modalities is a key problem in neuroscience. While methods to perform multimodal measurements in the same set of single neurons have become available, parsing complex relationships across different modalities to uncover neuronal identity is a growing challenge. Here, we present an optimization framework to learn coordinated representations of multimodal data, and apply it to a large multimodal dataset profiling mouse cortical interneurons. Our approach reveals strong alignment between transcriptomic and electrophysiological characterizations, enables accurate cross-modal data prediction, and identifies cell types that are consistent across modalities. HighlightsCoupled autoencoders for multimodal assignment, Analysis of Patch-seq data consisting of more than 3000 cells

neuroscience↗

bioRxiv2020

Parallel RNA and DNA analysis after Deep-sequencing (PRDD-seq) reveals cell type-specific lineage patterns in human brain

Elucidating the lineage relationships among different cell types is key to understanding human brain development. Here we developed Parallel RNA and DNA analysis after Deep-sequencing (PRDD-seq), which combines RNA analysis of neuronal cell types with analysis of nested spontaneous DNA somatic mutations as cell lineage markers, identified from joint analysis of single cell and bulk DNA sequencing by single-cell MosaicHunter (scMH). PRDD-seq enables the first-ever simultaneous reconstruction of neuronal cell type, cell lineage, and sequential neuronal formation ("birthdate") in postmortem human cerebral cortex. Analysis of two human brains showed remarkable quantitative details that relate mutation mosaic frequency to clonal patterns, confirming an early divergence of precursors for excitatory and inhibitory neurons, and an "inside-out" layer formation of excitatory neurons as seen in other species. In addition our analysis allows the first estimate of excitatory neuron-restricted precursors (about 10) that generate the excitatory neurons within a cortical column. Inhibitory neurons showed complex, subtype-specific patterns of neurogenesis, including some patterns of development conserved relative to mouse, but also some aspects of primate cortical interneuron development not seen in mouse. PRDD-seq can be broadly applied to characterize cell identity and lineage from diverse archival samples with single-cell resolution and in potentially any developmental or disease condition. Significance StatementStem cells and progenitors undergo a series of cell divisions to generate the neurons of the brain, and understanding this sequence is critical to studying the mechanisms that control cell division and migration in developing brain. Mutations that occur as cells divide are known as the basis of cancer, but have more recently been shown to occur with normal cell divisions, creating a permanent, forensic map of the clonal patterns that define the brain. Here we develop new technology to analyze both DNA mutations and RNA gene expression patterns in single cells from human postmortem brain, allowing us to define clonal patterns among different types of human brain neurons, gaining the first direct insight into how they form.

neuroscience↗

bioRxiv2020

Human cortical expansion involves diversification and specialization of supragranular intratelencephalic-projecting neurons

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 Alzheimers 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.

neuroscience↗

bioRxiv2020

Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse

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

neuroscience↗

bioRxiv2020

A new sulcal landmark identifying anatomical and functional gradients in human lateral prefrontal cortex

Understanding the relationship between neuroanatomy and function in portions of human cortex that are expanded compared to other mammals such as lateral prefrontal cortex (LPFC) is of major interest in systems and cognitive neuroscience. When considering neuroanatomical-functional relationships in LPFC, shallow indentations in cortex known as tertiary sulci have been largely ignored. Here, by implementing a multi-modal approach and manually defining 936 neuroanatomical structures in 72 hemispheres (males and females), we show that a subset of these overlooked tertiary sulci serve as a meso-scale link between microstructural (myelin content) and functional (network connectivity) properties of human LPFC in individuals. For example, the posterior middle frontal sulcus (pmfs) is a tertiary sulcus with three components that differ in their myelin content, resting state connectivity profiles, and engagement across meta-analyses of 83 cognitive tasks. Further, generating microstructural profiles of myelin content across cortical depths for each pmfs component and the surrounding middle frontal gyrus (MFG) shows that both gyral and sulcal components of the MFG have greater myelin content in deeper compared to superficial layers and that the myelin content in superficial layers of the gyral components is greater than sulcal components. These findings support a classic, yet largely unconsidered theory that tertiary sulci may serve as landmarks in association cortices, as well as a modern cognitive neuroscience theory proposing a functional hierarchy in LPFC. As there is a growing need for computational tools that automatically define tertiary sulci throughout cortex, we share pmfs probabilistic sulcal maps with the field. Significance statementLateral prefrontal cortex (LPFC) is critical for higher-order cognitive control and goal-directed behavior and is disproportionately expanded in the human brain. However, relationships between fine-scale neuroanatomical structures largely specific to hominoid cortex and functional properties of LPFC remain elusive. Here, we show that these structures, which have been largely neglected throughout history, surprisingly serve as markers for anatomical and functional organization in human LPFC. These findings have theoretical, methodological, developmental, and evolutionary implications for improved understanding of neuroanatomical-functional relationships not only in LPFC, but also in association cortices more broadly. Finally, these findings ignite new questions regarding how morphological features of these neglected neuroanatomical structures contribute to functions of association cortices that are critical for human-specific aspects of cognition.

neuroscience↗

bioRxiv2019

Testing Hormone-specific Antibody Probes for Presumptive Detection and Separation of Contributor Cell Populations in Trace DNA Mixtures

"Touch" or trace DNA evidence represent a significant proportion of samples analyzed by forensic science laboratories. Because these samples frequently contain multiple contributors and are often challenging to analyze due to low DNA concentrations and frequent degradation, front end techniques to simplify the mixture prior to DNA profiling could significantly impact case processing and enhance success rates. The goal of this study was to investigate whether targeting hormone molecules within the cell with antibody probes could be used to selectively label and then physically isolate contributor cell populations in trace biological samples. The separation of male and female cells into distinct fractions could reduce the complexity of the mixture prior to DNA profiling. To accomplish this, we first tested the specificity of fluorescently labelled anti-testosterone and anti-dihydrotestosterone antibody probes to epidermal cells from both male and female individuals. Results show that male and female cell populations can be effectively labeled using anti-testosterone and anti-dihydrotestosterone antibody probes and that distinct differences in binding efficiency and resulting median fluorescence of cell populations were observed between several individuals. These differences were then used to design sorting criteria for physically isolating each cell population in two-person epidermal cell mixtures using fluorescence activated cell sorting (FACS). DNA profiling of separated fractions in combination with probabilistic modeling demonstrated that some cell mixtures could be enriched for one contributor in separated cell fractions and yielded statistically more discriminating profiles compared to those generated from the original mixtures. Other mixtures tested showed less evidence of effective cell separation possibly due to a number of factors including imbalance of contributor DNA ratio, intra-sex variation of antibody binding efficiency, and contributions of extracellular or cell-free DNA in the mixture sample. Screening and separation of trace DNA samples with this approach may be presumptive and ultimately constrained by specific parameters of the original mixture, however, antibody binding optimization may mitigate some of these influences.

molecular biology↗