Biology subjects

Phan, B. N.

Publications and source records attributed to Phan, B. N..

At least 19 recordsLinked to original sources

bioRxiv2026

An Epigenetic Signature of Vulnerable Neurons is Under Selective Pressure Associated with Longevity Across Placental Mammals.

Age is the primary risk factor for neurodegenerative diseases, which are characterized by cell-type-specific vulnerability. Yet brain-aging mechanisms remain unclear given the complex, interacting age-associated pathways across diverse neural cell types. Here, we dissect cell type- cell state-specific aging gene regulatory programs and their contribution to cellular vulnerability by leveraging epigenomics, AI methodology, and natural lifespan diversity across placental mammals. Applying the TACIT method, we associated lifespans of 240 placental mammals to the predicted open chromatin levels of over 3 million orthologous loci across 18 cortical cell types. We identified thousands of lifespan-associated open chromatin regions, enriched near genes associated with hallmarks of aging, which stratified greatly by cell type. For example, regions near mitochondrial genes showed differential selective pressure in long-lived species in energetically-demanding layer V ET neurons, while regions near inflammatory response genes were under selective pressure in glial populations. We next asked whether regions linked to vulnerable or resilient neurons in the human brain were under differential selective pressure in longer lived species. Using an adaptive representation learning approach, we decompose intrinsic aging programs from systemic effects in the prefrontal cortex and define an aging signature predictive of cell-type-specific vulnerability. In Alzheimer's disease, this intrinsic aging signature more strongly predicts vulnerability than systemic effects. Active regions in vulnerable neurons showed lower predicted activity in species with longer lifespans, suggesting selective pressure to down-regulate the vulnerability-associated networks. Overall, our findings argue against a single master regulator of aging, instead implicating different hallmarks across different cell types.

genomics↗

bioRxiv2026

Fine-mapping candidate neuropsychiatric regulatory variants using cell type-aware comparative genomics

AbstractMeasures of nucleotide sequence conservation across species are useful for identifying functional genomic loci, but can fail when regulatory function is maintained, often in a cell type-specific manner, even when sequence is not. We introduce CTACIT, the Cell Type-Aware Conservation Inference Toolkit, to identify trait-associated regulatory variants. CTACIT integrates sequence conservation scores with cell type-specific open chromatin data collected from a few mammalian species to impute function for hundreds more. Applying CTACIT to neuropsychiatric trait loci identifies higher heritability enrichment and more fine-mapped variants than nucleotide conservation and human chromatin data alone. Our in vivo reporter assays validate predictions for enhancers with risk variants near the DRD2 schizophrenia risk locus. By integrating genome conservation and multi-species open chromatin data, CTACIT prioritizes variants within regions of conserved regulatory function for in vivo characterization and addresses a major challenge in translating disease associations to mechanistic understanding. One-Sentence SummaryRegulatory functions conserved across mammals underlying caudate cell type evolution reveal functions of human risk variants.

genomics↗

bioRxiv2026

Local control of dopamine release in nucleus accumbens gates opioid withdrawal aversion

The opioid crisis has emphasized the need for more effective treatments for opioid use disorder (OUD)1-3, which is characterized by habitual opioid use to avoid withdrawal symptoms4,5. Both physical and affective symptoms contribute to opioid withdrawal yet whether different neural mechanisms mediate these different symptom domains and contribute distinctly to opioid relapse is unknown. While neurons expressing mu opioid receptors (MORs) gate opioids reinforcing effects6-8 by increasing dopamine (DA) release in nucleus accumbens (NAc), sharp decreases in NAc DA release are associated with withdrawal9-11, the cellular and circuit mechanisms of which are unknown. Here we describe an unusual population of evolutionarily-conserved MOR+ neurons in the NAc expressing the transcription factor Tshz1. Increased activity in these neurons is required for withdrawal aversion learning. Deletion of MORs in Tshz1 neurons prevented withdrawal-induced decreases in DA release and affective aversion, but not physical symptoms associated with withdrawal. Pharmacological activation of mGluR8, which is preferentially expressed in Tshz1 neurons, reduced withdrawal aversion. Thus, by dissociating the circuit mechanisms contributing to the physical and affective components of opioid withdrawal focusing on the critical role of Tshz1 neurons, we have identified a novel druggable target with therapeutic potential for treating key OUD withdrawal symptoms.

neuroscience↗

bioRxiv2025

A molecular and spinal circuit basis for the functional segregation of itch and pain

Recent advances reveal an extensive cellular diversity within the dorsal horn. How this complexity processes distinct sensations, like itch and pain, remains a fundamental question. We discovered hidden within a population of neurons expressing the gastrin-releasing peptide receptor (Grpr+), thought to be itch-specific, are highly homologous yet functionally distinct subtypes distinguished by expression of Tachykinin-1 (Tac1). While the Tac1- subtype mediates itch, the Tac1+ subtype mediates mechanical allodynia across diverse pain states. Inhibitory populations and differential sensitivities to GRP serve as key modulators of the Grpr+ neuron subtypes, shaping modality specific output. Leveraging computationally designed genomic enhancers to silence the Tac1- population reverses itch while silencing the Tac1+ subtype reverses mechanical allodynia broadly. The work demonstrates the nuance of differential sensory modality coding within the dorsal horn and the power of genomic enhancer-based strategies for modality-specific targeting.

neuroscience↗

bioRxiv2025

Context-dependent regulatory variants in Alzheimer's disease

Noncoding genetic variants underlie many complex diseases, yet identifying and interpreting their functional impacts remains challenging. Late-onset Alzheimers disease (LOAD), a polygenic neurodegenerative disorder, exemplifies this challenge. The disease is strongly associated with noncoding variation, including common variants enriched in microglial enhancers and rare variants nominated at loci implicated in neurodevelopment and synaptic function. These variants may perturb regulatory sequences by disrupting transcription factor (TF) motifs or altering local regulatory sequence context, with potential consequences for gene expression and chromatin accessibility. However, assessing their impact is complicated by the context-dependent functions of regulatory sequences, underscoring the need to systematically examine variant effects across diverse tissues, cell types, and cellular states. Here, we combined in vitro and in vivo massively parallel reporter assays (MPRAs) with interpretable machine-learning models to systematically characterize common and rare variants across myeloid and neuron-enriched neural contexts. Parallel profiling of variants in four immune states in vitro and three mouse brain regions in vivo revealed that individual variants can differentially and even oppositely modulate reporter activity across cellular contexts, while a subset showed immune-state-dependent effects. Within the assayed candidate set, the relative effect sizes of common and rare variants reversed between contexts, with common variants showing larger effects in THP-1 macrophages and rare variants in brain tissue. Interpretable sequence-to-function models prioritized context-biased variants and generated motif-level hypotheses, including predicted transcription-factor motif disruption and subtler changes in local motif context. To probe endogenous consequences at a prioritized locus, we used CRISPR interference to perturb a rare-variant-containing enhancer at the SEC63-OSTM1 locus, revealing metabolic and biosynthetic transcriptional programs resembling those induced by SEC63 promoter perturbation, together with a stimulation-specific interferon response. These findings show that LOAD-associated noncoding variants exhibit context-dependent effects on reporter activity and predicted chromatin accessibility, and provide a framework for linking genetic association to regulatory activity, sequence grammar and endogenous transcriptional state.

genomics↗

bioRxiv2025

Combining Machine Learning and Multiplexed, In Situ Profiling to Engineer Cell Type and Behavioral Specificity

A promising strategy for the precise control of neural circuits is to use cis-regulatory enhancers to drive transgene expression in specific cells. However, enhancer discovery faces key challenges: low in vivo success rates, species-specific differences in activity, challenges with multiplexing adeno-associated viruses (AAVs), and the lack of spatial detail from single-cell sequencing. In order to accelerate enhancer discovery for the dorsal spinal cord--a region critical for pain and itch processing--we developed an end-to-end platform, ESCargoT (Engineered Specificity of Cargo Transcription), combining machine learning (ML)-guided enhancer prioritization, modular AAV assembly, and multiplexed, in situ screening. Using cross-species chromatin accessibility data, we trained ML models to predict enhancer activity in oligodendrocytes and in 15 dorsal horn neuronal subtypes. We first demonstrated that an initial enhancer, Excit-1, targeted excitatory dorsal horn neurons and drove reversal of mechanical allodynia in an inflammatory pain model. To enable parallel profiling of a 27-enhancer-AAV library delivered intraspinally in mice, we developed a Spatial Parallel Reporter Assay (SPRA) by integrating a novel Golden-Gate assembly pipeline with multiplexed, in situ screening. Regression adjustment for spatial confounding enabled specificity comparisons between enhancers, demonstrating the ability to screen enhancers targeting diverse cell types (oligodendrocytes, motoneurons, dorsal neuron subtypes) in one experiment. We then validated two candidates, targeting Exc-LMO3 and Exc-SKOR2 neurons, respectively. In a companion paper by Noh et al, our colleagues show that the functional specificity of the Exc-SKOR2-targeting enhancer, unlike Excit-1, is capable of blocking the sensation of chemical itch in mice. These enhancers were derived from the macaque genome but displayed functional sensitivity in mice. This platform enables spatially resolved, multiplexed in vivo enhancer profiling to accelerate discovery of cell-targeting tools and gene therapy development.

neuroscience↗

bioRxiv2024

Cell Type Specific Enhancers for Dorsolateral Prefrontal Cortex.

The dorsolateral prefrontal cortex (DLPFC) is crucial to primate cognitive functions, but a paucity of cell type specific tools limits studies of DLPFC neurocomputational principles. Therefore, we set out to identify enhancers that fit inside Adeno-Associated Virus (AAV) vectors and that elicited functional, cell type specific gene expression in the non-human primate (NHP) DLPFC. We used single nucleus RNA-Seq and ATAC-Seq from rhesus macaque tissue samples to define DLPFC cell types and their associated open chromatin regions (OCRs). We trained machine learning (ML) models to recognize the unique regulatory grammar associated with each DLPFC neuron type, performed in silico screening of all OCRs, and identified candidate enhancers most likely to elicit cell type specific transgene expression in each neuron type. For layer 3 pyramidal neurons (L3PNs) and layer 5 extratelencephalic neurons (L5ETs), we cloned the top twelve identified candidates into AAVs and injected them into NHP DLPFC. In situ observation of enhancer-driven expression revealed the best performers, RMacL3-01 and RMacL5ET-01. We validated RMacL3-01 and RMacL5ET-01 using one-at-a-time injections in NHP DLPFC. RMacL3-01 restricted GFP expression to pyramidal neurons in layers 2 and 3, whereas RMacL5ET-01 restricted expression to POU3F1+ neurons in layer 5. RMacL3-01 elicited functional levels of channelrhodopsin expression that enabled optical activation of single- and multi-unit activity in NHP DLFPC. Together, these results and resources establish a solid foundation to study cell type specific principles of primate cognitive functions.

neuroscience↗

bioRxiv2023

Single nucleus transcriptomics of human and monkey striatum implicates DNA damage, neuroinflammation, and neurodegeneration signaling in opioid use disorder

The striatum in the brain is involved in various behavioral functions, including reward, and disease processes, such as opioid use disorder (OUD). Further understanding of the role of striatal subregions in reward behaviors and their potential associations with OUD requires molecular identification of specific striatal cell types in human brain. The human striatum contains subregions based on different anatomical, functional, and physiological properties, with the dorsal striatum further divided into caudate and putamen. Both caudate and putamen are involved in altered reward processing, formation of habits, and development of negative affect states associated with OUD. Using single nuclei RNA-sequencing of human postmortem caudate and putamen, we identified canonical neuronal cell types in striatum (e.g., dopamine receptor 1 or 2 expressing neurons, D1 or D2) and less abundant subpopulations, including D1/D2-hybrid neurons and multiple classes of interneurons. By comparing unaffected subjects to subjects with OUD, we found neuronal-specific differences in pathways related to neurodegeneration, interferon response, and DNA damage. DNA damage markers were also elevated in striatal neurons of rhesus macaques following chronic opioid administration. We also identified sex-dependent differences in the expression of stress-induced transcripts among astrocytes and oligodendrocytes from female subjects with OUD. Thus, we describe striatal cell types and leverage these data to gain insights into molecular alterations in human striatum associated with opioid addiction.

neuroscience↗

bioRxiv2023

Title: Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease

Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

genomics↗

bioRxiv2022

An in vivo massively parallel platform for deciphering tissue-specific regulatory function

Genetic studies are rapidly identifying non-protein-coding human disease-associated loci. Understanding the regulatory mechanisms underlying these loci remains a challenge because the causal variants and the tissues in which they act are often unclear. Massively parallel reporter assays (MPRAs) have the potential to link differences in genome sequence, including genetic variants, to tissue-specific regulatory function. Although MPRA and similar technologies have been widely adopted in cell culture, there have been several barriers to widespread use in animals. We overcome these challenges with a new whole-animal MPRA (WhAMPRA), where systemic intravenous AAV effectively transduces the plasmid MPRA library to mouse tissues. Our WhAMPRA approach revealed models of tissue-specific regulation that generally match machine learning model predictions. In addition, we measured the regulatory effects of disrupting MEF2C transcription factor binding sites and impacts of late onset Alzheimers disease-associated genetic variations. Overall, our WhAMPRA technology simultaneously determines the transcriptional functions of hundreds of enhancers in vivo across multiple tissues.

genomics↗

bioRxiv2022

Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

Protein-coding differences between mammals often fail to explain phenotypic diversity, suggesting involvement of enhancers, often rapidly evolving regions that regulate gene expression. Identifying associations between enhancers and phenotypes is challenging because enhancer activity is context-dependent and may be conserved without much sequence conservation. We developed TACIT (Tissue-Aware Conservation Inference Toolkit) to associate open chromatin regions (OCRs) with phenotypes using predictions in hundreds of mammalian genomes from machine learning models trained to learn tissue-specific regulatory codes. Applying TACIT for motor cortex and parvalbumin-positive interneurons to neurological phenotypes revealed dozens of new OCR-phenotype associations. Many associated OCRs were near relevant genes, including brain size-associated OCRs near genes mutated in microcephaly or macrocephaly. Our work creates a forward genomics foundation for identifying candidate enhancers associated with phenotype evolution. One Sentence SummaryA new machine learning-based approach associates enhancers with the evolution of brain size and behavior across mammals.

genomics↗

bioRxiv2021

Molecular rhythm alterations in prefrontal cortex and nucleus accumbens associated with opioid use disorder

Severe and persistent disruptions to sleep and circadian rhythms are common features of people with opioid use disorder (OUD). Preclinical findings suggest altered molecular rhythms in the brain are involved in opioid reward and dependence. However, whether molecular rhythms are disrupted in brains of people with OUD remained an open question, critical to understanding the role of circadian rhythms in opioid addiction. We previously used subjects times of death (TOD) as a marker of time of day to investigate transcriptional rhythm alterations in psychiatric disorders. Using TOD and RNA sequencing, we discovered rhythmic transcripts in both the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc), key brain areas involved in opioid addiction, were largely distinct between OUD and unaffected comparison subjects. Further, fewer rhythmic transcripts were identified in DLPFC of OUD subjects compared to unaffected subjects, but nearly double the number of rhythmic transcripts were found in the NAc of OUD subjects. In OUD, rhythmic transcripts in the NAc peaked either in the evening or near sunrise, and were associated with dopamine, opioid, and GABAergic neurotransmission. Co-expression network analysis identified several OUD-specific modules in the NAc, enriched for transcripts involved in the modulation of dopamine and GABA synapses, including glutamatergic signaling and extracellular matrices. Integrative analyses with human GWAS revealed that rhythmic transcripts in DLPFC and NAc were enriched for genomic loci associated with sleep duration and insomnia. Overall, our results connect transcriptional rhythm changes in dopamine, opioid, and GABAergic synaptic signaling in human brain to sleep-related phenotypes and OUD.

neuroscience↗

bioRxiv2021

Induction of Bdnf from promoter I following electroconvulsive seizures contributes to structural plasticity in neurons of the piriform cortex

The efficacy of electroconvulsive therapy (ECT) as a treatment for psychiatric disorders, including major depressive disorder (MDD) is hypothesized to depend on induction of molecular and cellular events that trigger structural plasticity in neurons. Electroconvulsive seizures (ECS) in animal models can help to inform our understanding of how electroconvulsive therapy (ECT) impacts the brain. ECS induces structural plasticity in neuronal dendrites in many brain regions, including the piriform cortex, a highly epileptogenic region that has also been implicated in depression. ECS-induced structural plasticity is associated with differential expression of unique isoforms encoding the neurotrophin, brain-derived neurotrophic factor (BDNF), but the functional significance of these transcripts in dendritic plasticity is not clear. Here, we demonstrate that different Bdnf isoforms are expressed non-stochastically across neurons of the piriform cortex following ECS. Specifically, cells expressing Bdnf exon 1-containing transcripts show a unique spatial recruitment pattern in response to ECS. We further demonstrate that Bdnf Ex1 expression in these cells is necessary for ECS-induced dendritic spine plasticity.

neuroscience↗

bioRxiv2020

SPEAQeasy: a Scalable Pipeline for Expression Analysis and Quantification for R/Bioconductor-powered RNA-seq analyses

RNA sequencing (RNA-seq) is a common and widespread biological assay, and an increasing amount of data is generated with it. In practice, there are a large number of individual steps a researcher must perform before raw RNA-seq reads yield directly valuable information, such as differential gene expression data. Existing software tools are typically specialized, only performing one step-- such as alignment of reads to a reference genome-- of a larger workflow. The demand for a more comprehensive and reproducible workflow has led to the production of a number of publicly available RNA-seq pipelines. However, we have found that most require computational expertise to set up or share among several users, are not actively maintained, or lack features we have found to be important in our own analyses. In response to these concerns, we have developed a Scalable Pipeline for Expression Analysis and Quantification (SPEAQeasy), which is easy to install and share, and provides a bridge towards R/Bioconductor downstream analysis solutions. SPEAQeasy is user-friendly and lowers the computational-domain entry barrier for biologists and clinicians to RNA-seq data processing as the main input file is a table with sample names and their corresponding FASTQ files. SPEAQeasy is portable across computational frameworks (SGE, SLURM, local, docker integration) and different configuration files are provided.

bioinformatics↗

bioRxiv2020

The Regulatory Evolution of the Primate Fine-Motor System

In mammals, fine motor control is essential for skilled behavior, and is subserved by specialized subdivisions of the primary motor cortex (M1) and other components of the brains motor circuitry. We profiled the epigenomic state of several components of the Rhesus macaque motor system, including subdivisions of M1 corresponding to hand and orofacial control. We compared this to open chromatin data from M1 in rat, mouse, and human. We found broad similarities as well as unique specializations in open chromatin regions (OCRs) between M1 subdivisions and other brain regions, as well as species- and lineage-specific differences reflecting their evolutionary histories. By distinguishing shared mammalian M1 OCRs from primate- and human-specific specializations, we highlight gene regulatory programs that could subserve the evolution of skilled motor behaviors such as speech and tool use.

neuroscience↗

bioRxiv2020

Addiction-associated genetic variants implicate brain cell type- and region-specific cis-regulatory elements in addiction neurobiology

Recent large genome-wide association studies (GWAS) have identified multiple confident risk loci linked to addiction-associated behavioral traits. Genetic variants linked to addiction-associated traits lie largely in non-coding regions of the genome, likely disrupting cis-regulatory element (CRE) function. CREs tend to be highly cell type-specific and may contribute to the functional development of the neural circuits underlying addiction. Yet, a systematic approach for predicting the impact of risk variants on the CREs of specific cell populations is lacking. To dissect the cell types and brain regions underlying addiction-associated traits, we applied LD score regression to compare GWAS to genomic regions collected from human and mouse assays for open chromatin, which is associated with CRE activity. We found enrichment of addiction-associated variants in putative CREs marked by open chromatin in neuronal (NeuN+) nuclei collected from multiple prefrontal cortical areas and striatal regions known to play major roles in reward and addiction. To further dissect the cell type-specific basis of addiction-associated traits, we also identified enrichments in human orthologs of open chromatin regions of mouse neuronal subtypes: cortical excitatory, D1, D2, and PV. Lastly, we developed machine learning models from mouse cell type-specific regions of open chromatin to further dissect human NeuN+ open chromatin regions into cortical excitatory or striatal D1 and D2 neurons and predict the functional impact of addiction-associated genetic variants. Our results suggest that different neuronal subtypes within the reward system play distinct roles in the variety of traits that contribute to addiction. Significance StatementWe combine statistical genetic and machine learning techniques to find that the predisposition to for nicotine, alcohol, and cannabis use behaviors can be partially explained by genetic variants in conserved regulatory elements within specific brain regions and neuronal subtypes of the reward system. This computational framework can flexibly integrate open chromatin data across species to screen for putative causal variants in a cell type-and tissue-specific manner across numerous complex traits.

genomics↗

bioRxiv2019

dotdotdot: an automated approach to quantify multiplex single molecule fluorescent in situ hybridization (smFISH) images in complex tissues

Multiplex single-molecule fluorescent in situ hybridization (smFISH) is a powerful method for validating RNA sequencing and emerging spatial transcriptomic data, but quantification remains a computational challenge. We present a framework for generating and analyzing smFISH data in complex tissues while overcoming autofluorescence and increasing multiplexing capacity. We developed dotdotdot (https://github.com/LieberInstitute/dotdotdot) as a corresponding software package to quantify RNA transcripts in single nuclei and perform differential expression analysis. We first demonstrate robustness of our platform in single mouse neurons by quantifying differential expression of activity-regulated genes. We then quantify spatial gene expression in human dorsolateral prefrontal cortex (DLPFC) using spectral imaging and dotdotdot to mask lipofuscin autofluorescence. We lastly apply machine learning to predict cell types and perform downstream cell type-specific expression analysis. In summary, we provide experimental workflows, imaging acquisition and analytic strategies for quantification and biological interpretation of smFISH data in complex tissues.

neuroscience↗

bioRxiv2018

Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs

Human induced pluripotent stem cells (hiPSCs) are a powerful model of neural differentiation and maturation. We present a hiPSC transcriptomics resource on corticogenesis from 5 iPSC donor and 13 subclonal lines across nine time points over 5 broad conditions: self-renewal, early neuronal differentiation, neural precursor cells (NPCs), assembled rosettes, and differentiated neuronal cells that were validated using electrophysiology. We identified widespread changes in the expression of individual transcript features and their splice variants, gene networks, and global patterns of transcription. We next demonstrated that co-culturing human NPCs with rodent astrocytes resulted in mutually synergistic maturation, and that cell type-specific expression data can be extracted using only sequencing read alignments without potentially disruptive cell sorting. We lastly developed and validated a computational tool to estimate the relative neuronal maturity of iPSC-derived neuronal cultures and human brain tissue, which were maturationally heterogeneous but contained subsets of cells most akin to adult human neurons.

genomics↗