Biology subjects

Buenrostro, J. D.

Publications and source records attributed to Buenrostro, J. D..

At least 19 recordsLinked to original sources

bioRxiv2026

Predicting cell-state-specific gene regulation from DNA across species

DNA encodes the cell's phenotype, but the same DNA sequence is interpreted differently in every cell type, developmental stage, and activity state. Existing deep-learning models solve only half of this puzzle: sequence-to-function models read DNA but treat cell state as a fixed label, while single-cell foundation models represent cell state but not sequence. We developed Bolero, a sequence-to-function model whose parameters condition on atlas-scale cell-state embeddings and additional biological variables to predict cell-state-specific chromatin accessibility and transcript abundance from DNA. Trained on 10.7 million cells from 33 datasets across six mammals, Bolero matched or exceeded specialised models and resolved regulatory differences between closely related cell states, including cortical regional and developmental gradients. Extrapolating cell-state embeddings extended Bolero's predictions to cell states that are absent from training. Cell-state conditioning facilitated tracing of the effects of non-coding variants to the cell types in which they act. Using an AP-1 activity score as a further continuous conditioning axis, Bolero predicted activity-regulated chromatin changes without requiring actual stimulation data. Across human cell types, we reconstructed the cooperative grammar of motif identity and spacing underlying predicted AP-1 responses. Bolero further predicted cell-type-specific chromatin accessibility and AP-1 responses in species excluded from training, extending comparative genomics from sequence conservation to predicted functional conservation. Across 84 mammals, we found that predicted AP-1 responses were less conserved than chromatin accessibility at cis-regulatory elements, driven by the human-specific sequence variants on AP-1 and cooperating motifs. By combining reference genomes with reference cell atlases, Bolero allowed genome sequences, either native or mutated, to be queried across cell states, perturbations, and different species for their chromatin and expression signatures.

genomics↗

bioRxiv2026

A single-nucleus multi-omic atlas of gene regulation across 21 adult human tissues

Diverse human cell types establish specialized functions through lineage- and context-specific regulatory programs. Interpreting non-coding genetic risk requires integrated multi-omic reference maps that directly connect regulatory DNA to cellular expression across human tissues. Here we present a single-nucleus multi-omic atlas comprising 459,856 transcriptomic and chromatin accessibility profiles from 21 adult human tissues and four donors, including paired measurements from 160,688 nuclei. The atlas resolves nine cell lineages, 61 broad cell types and 313 subclusters, and identifies 1,085,062 candidate cis-regulatory elements (cCREs), including 161,270 novel elements absent from ENCODE. Regulatory activity was dominated by cell identity but refined by tissue context. Joint profiling enabled 871,177 cCRE-gene associations and revealed lineage-specific regulatory architectures. Cross-tissue accessibility further identified lineage-restricted and constitutively inaccessible chromatin domains, the latter showing preferential hypomethylation across human cancers. Furthermore, we leverage this dataset to train sequence-to-function models to predict chromatin-accessibility effects for 548,656 fine-mapped variants, identifying 18,133 high-effect variants, including 1,120 broadly active variants. Models trained for eight endothelial subtypes further resolve predicted variant effects across vascular beds. Together, this atlas provides a comprehensive cellular and computational framework for interpreting regulatory sequence, context-dependent gene control, and complex trait genetics across the human body.

genomics↗

bioRxiv2026

Transcription factor collaboration enables precise T cell state engineering

Transcription factors (TFs) collaborate to regulate gene expression programs that define cell fate. In CD8+ T cells, this coordinated regulation underlies exhaustion, a dysfunctional state that constrains immunity in chronic infection and cancer. Here, we screen for cell state-specific TFs by performing pooled overexpression screens of 3,548 TF and TF isoforms in primary T cells across multiple CD8+ T cell states. We identify 82 regulators that collaborate with exhaustion-specific programs and profile their effects using perturb-SHARE-seq, connecting perturbations to changes in chromatin accessibility and gene expression across 702,314 single cells. We identify 38 reproducible regulatory programs and construct a map of 12,616 TF-program connections that shape CD8+ T cell states, nominating KLF2 as predictive of positive response to CAR-T therapy. Using seq2PRINT, a deep learning framework that predicts functional TF interactions, we identify RUNX as a "master collaborator", a TF that broadly collaborates with other factors, and uncover a RUNX2:KLF2 interaction that specifies exhaustion-associated programs. Mutation of the RUNX2:KLF2 protein interface attenuates KLF2-mediated repression of exhaustion, while synthetic tethering of RUNX2 to KLF2 leads to an amplification of the phenotype. More broadly, we identify the collaborative action of RUNX as a driver in CD8+ T cell states, and show that tethering TFs enables the rational engineering of cell state identity for cell and gene therapies.

genomics↗

bioRxiv2026

Transcriptomic atlas of premalignant oral squamous cell carcinoma in an aging mouse model reveals an enhanced immune response and dysregulation of head and neck tissue stem cells

Oral squamous cell carcinomas (OSCC) account for [~]90% of all oral malignancies and have devastating effects on overall health and quality of life. However, little is known about the early initiating events that drive the development of oral leukoplakia-like premalignant lesions (OPLs) and disease progression. Here, we create a mouse model of tobacco-related premalignant OSCC that takes into consideration its primary risk factors, including advancing age and male sex. This model notably recapitulates the age variant patterns of OSCC risk observed in humans, with a higher prevalence of oral premalignant lesions in older mice. In addition, by building a transcriptomic atlas with this system, we reveal genetic signatures associated with oncogenic progression in the tongue and buccal epithelium, and their resident somatic tissue stem cells. We also identify several novel transcriptomic signatures of premalignancy in OSCC, including enhanced immune response and expansion and dysregulation of head and neck tissue stem cells. These findings offer a new framework for investigating physiologically-relevant risk factors and drivers of OSCC and illuminate novel biological pathways underlying its pathology.

cancer biology↗

bioRxiv2025

Engineered histones reshape chromatin in human cells

Histone proteins and their variants have been found to play crucial and specialized roles in chromatin organization and the regulation of downstream gene expression; however, the relationship between histone sequence and its effect on chromatin organization remains poorly understood, limiting our functional understanding of sequence variation between distinct subtypes and across evolution and frustrating efforts to rationally design synthetic histones that can be used to engineer specified cell states. Here, we make the first advance towards engineered histone-driven chromatin organization. By expressing libraries of sequence variants of core histones in human cells, we identify variants that dominantly modulate chromatin structure. We further interrogate variants using a combination of imaging, proteomics, and genomics to reveal both cis and trans-acting mechanisms of effect. Functional screening with transcription factor libraries identifies transcriptional programs that are facilitated by engineered histone expression. Double mutation screens combined with protein language models allow us to learn sequence-to-function patterns and design synthetic histone proteins optimized to drive specific chromatin states. This work establishes a foundation for the high-throughput evaluation and engineering of chromatin-associated proteins and positions histones as tunable nodes for understanding and modulating mesoscale chromatin organization.

synthetic biology↗

bioRxiv2025

Reprogramming Factors Activate a Non-Canonical Oxidative Resilience Pathway That Can Rejuvenate RPEs and Restore Vision

Oct4, Sox2, and Klf4 (OSK) Yamanaka factors induce pluripotency and reverse age-related epigenetic changes, yet the mechanisms by which they promote rejuvenation remain poorly explored. Oxidative stress contributes to CNS aging and retinal pigmented epithelium (RPE) degeneration in age-related macular degeneration. We find that OSK expression in RPE restores retinal structure and visual function in aged mice and promotes oxidative resilience through a non-canonical, Tet2-independent pathway. Integrative functional genomics identifies GSTA4, a detoxifying enzyme that clears the lipid peroxidation byproduct 4-HNE, as a necessary and sufficient OSK effector. Dynamic GSTA4 regulation by OSK recapitulates a stem cell derived stress resilience program. GSTA4 overexpression alone enhances mitochondrial resilience, rejuvenates the aged RPE transcriptome, and reverses visual decline. GSTA4 is consistently upregulated across diverse lifespan-extending interventions suggesting a broader pro-longevity role. These findings uncover a previously unrecognized protective axis driven by Yamanaka factors that circumvents reprogramming, providing therapeutic insights for age-related diseases. HIGHLIGHTSO_LIOSK-GSTA4 provides a dynamic, Tet2-independent stress-resilience axis. C_LIO_LIFunctional genomics pinpoints GSTA4 as a direct downstream effector activated by OSK. C_LIO_LIRPE aging involves progressive accumulation of 4-HNE that can be detoxified by GSTA4. C_LIO_LIEnhancing GSTA4 rejuvenates RPE cells, restores vision and is associated with lifespan-extending interventions. C_LI

genetics↗

bioRxiv2025

Clonal memory of colitis accumulates and promotes tumor growth

Chronic inflammation is a well-established risk factor for cancer, but the underlying molecular mechanisms remain unclear. Using a mouse model of colitis, we demonstrate that colonic stem cells retain an epigenetic memory of inflammation following disease resolution, characterized by a cumulative gain of activator protein 1 (AP-1) transcription factor activity. Further, we develop SHARE-TRACE, a method that enables simultaneous profiling of gene expression, chromatin accessibility and clonal history in single cells, enabling high resolution tracking of epigenomic memory. This reveals that inflammatory memory is propagated cell-intrinsically and inherited through stem cell lineages, with certain clones demonstrating dramatically stronger memory than others. Finally, we show that colitis primes stem cells for amplified expression of regenerative gene programs following oncogenic mutation that accelerate tumor growth. This includes a subpopulation of tumors that have exceptionally high AP-1 activity and the additional upregulation of pro-oncogenic programs. Together, our findings provide a mechanistic link between chronic inflammation and malignancy, revealing how long-lived epigenetic alterations in regenerative tissues may contribute to disease susceptibility and suggesting potential therapeutic strategies to mitigate cancer risk in patients with chronic inflammatory conditions.

cancer biology↗

bioRxiv2024

Coupling CRISPR Scanning with Targeted Chromatin Accessibility Profiling using a Double-Stranded DNA Deaminase

Genome editing enables sequence-function profiling of endogenous cis-regulatory elements, driving understanding of their mechanisms and the development of gene therapies. However, these approaches cannot be combined with direct scalable readouts of chromatin structure and accessibility across long single-molecule chromatin fibers. Here we leverage a double-stranded DNA cytosine deaminase to profile chromatin accessibility at high depth and resolution at endogenous loci of interest through targeted PCR and long-read sequencing, a method we term targeted deaminase-accessible chromatin sequencing (TDAC-seq). Powered by high sequence coverage at targeted loci of interest, TDAC-seq can be uniquely integrated with CRISPR perturbations to enable the functional dissection of cis-regulatory elements, where genetic perturbations and their effects on chromatin accessibility are superimposed on the same single chromatin fiber and resolved at single-nucleotide resolution. We employed TDAC-seq to parse CRISPR edits that activate fetal hemoglobin in human CD34+ hematopoietic stem and progenitor cells during erythroid differentiation as well as in pooled CRISPR and base editing screens tiling an enhancer controlling the globin locus. Together, TDAC-seq enables high-resolution sequence-function mapping of single-molecule chromatin fibers by genome editing.

molecular biology↗

bioRxiv2024

Expansion in situ genome sequencing links nuclear abnormalities to hotspots of aberrant euchromatin repression

Microscopy and genomics are both used to characterize cell function, but approaches to connect the two types of information are lacking, particularly at subnuclear resolution. While emerging multiplexed imaging methods can simultaneously localize genomic regions and nuclear proteins, their ability to accurately measure DNA-protein interactions is constrained by the diffraction limit of optical microscopy. Here, we describe expansion in situ genome sequencing (ExIGS), a technology that enables sequencing of genomic DNA and superresolution localization of nuclear proteins in single cells. We applied ExIGS to fibroblast cells derived from an individual with Hutchinson-Gilford progeria syndrome to characterize how variation in nuclear morphology affects spatial chromatin organization. Using this data, we discovered that lamin abnormalities are linked to hotspots of aberrant euchromatin repression that may erode cell identity. Further, we show that lamin abnormalities heterogeneously increase the repressive environment of the nucleus in tissues and aged cells. These results demonstrate that ExIGS may serve as a generalizable platform for connecting nuclear abnormalities to changes in gene regulation across disease contexts.

genomics↗

bioRxiv2024

scooby: Modeling multi-modal genomic profiles from DNA sequence at single-cell resolution

Understanding how regulatory DNA elements shape gene expression across individual cells is a fundamental challenge in genomics. Joint RNA-seq and epigenomic profiling provides opportunities to build unifying models of gene regulation capturing sequence determinants across steps of gene expression. However, current models, developed primarily for bulk omics data, fail to capture the cellular heterogeneity and dynamic processes revealed by single-cell multi-modal technologies. Here, we introduce scooby, the first framework to model scRNA-seq coverage and scATAC-seq insertion profiles along the genome from sequence at single-cell resolution. For this, we leverage the pre-trained multi-omics profile predictor Borzoi as a foundation model, equip it with a cell-specific decoder, and fine-tune its sequence embeddings. Specifically, we condition the decoder on the cell position in a precomputed single-cell embedding resulting in strong generalization capability. Applied to a hematopoiesis dataset, scooby recapitulates cell-specific expression levels of held-out genes, and identifies regulators and their putative target genes through in silico motif deletion. Moreover, accurate variant effect prediction with scooby allows for breaking down bulk eQTL effects into single-cell effects and delineating their impact on chromatin accessibility and gene expression. We anticipate scooby to aid unraveling the complexities of gene regulation at the resolution of individual cells.

genomics↗

bioRxiv2023

Multi-locus CRISPRi targeting with a single truncated guide RNA

A critical goal in functional genomics is evaluating which non-coding elements contribute to gene expression, cellular function, and disease. Functional characterization remains a challenge due to the abundance and complexity of candidate elements. Here, we develop a CRISPRi- based approach for multi-locus screening of putative transcription factor binding sites with a single truncated guide. A truncated guide with hundreds of sequence match sites can reliably disrupt enhancer activity, which expands the targeting scope of CRISPRi while maintaining repressive efficacy. We screen over 13,000 possible CTCF binding sites with 24 guides at 10 nucleotides in spacer length. These truncated guides direct CRISPRi-mediated deposition of repressive H3K9me3 marks and disrupt transcription factor binding at most sequence match target sites. This approach is valuable for elucidating functional transcription factor binding motifs or other repeated genomic sequences and is easily implementable with existing tools.

molecular biology↗

bioRxiv2023

Single-cell multi-scale footprinting reveals the modular organization of DNA regulatory elements

Cis-regulatory elements control gene expression and are dynamic in their structure, reflecting changes to the composition of diverse effector proteins over time1-3. Here we sought to connect the structural changes at cis-regulatory elements to alterations in cellular fate and function. To do this we developed PRINT, a computational method that uses deep learning to correct sequence bias in chromatin accessibility data and identifies multi-scale footprints of DNA-protein interactions. We find that multi-scale footprints enable more accurate inference of TF and nucleosome binding. Using PRINT with single-cell multi-omics, we discover wide-spread changes to the structure and function of candidate cis-regulatory elements (cCREs) across hematopoiesis, wherein nucleosomes slide, expose DNA for TF binding, and promote gene expression. Activity segmentation using the co-variance across cell states identifies "sub-cCREs" as modular cCRE subunits of regulatory DNA. We apply this single-cell and PRINT approach to characterize the age-associated alterations to cCREs within hematopoietic stem cells (HSCs). Remarkably, we find a spectrum of aging alterations among HSCs corresponding to a global gain of sub-cCRE activity while preserving cCRE accessibility. Collectively, we reveal the functional importance of cCRE structure across cell states, highlighting changes to gene regulation at single-cell and single-base-pair resolution.

genomics↗

bioRxiv2022

Photoselective sequencing: microscopically-guided genomic measurements with subcellular resolution

In biological systems, spatial organization is interconnected with genome function and regulation. However, methods that couple high-throughput genomic and epigenomic profiling with spatial information are lacking. Here, we developed Photoselective Sequencing, a spatially-informed DNA sequencing method to assay collections of cells or subcellular regions that share a unifying morphological trait. In Photoselective Sequencing, we prepare a blocked fragment library within a fixed biological specimen. Guided by fluorescence imaging, we remove the block in specific regions of interest using targeted illumination with near-UV light, ultimately allowing high-throughput sequencing of the selected fragments. To validate Photoselective Sequencing, we profile chromatin openness in fluorescently-labeled cell types within the mouse brain and demonstrate strong agreement with published single-cell ATAC-seq data. Using Photoselective Sequencing, we characterize the accessibility profiles of oligodendrocyte-lineage cells within the cortex and corpus-callosum regions of the brain. We develop a new computational strategy for decomposing bulk accessibility profiles by individual cell types, and report a relative enrichment of oligodendrocyte-progenitor-like cells in the cortex. Finally, we leverage Photoselective Sequencing for unbiased profiling of DNA at the nuclear periphery, a key chromatin organizing region. We compare and contrast the Photoselective Sequencing profile with lamin ChIP-seq data, and identify features beyond lamin interaction that are correlated with positioning at the nuclear periphery. These results collectively demonstrate that Photoselective Sequencing is a flexible and generalizable platform for exploring the interplay of spatial structures with genomic and epigenomic properties.

genomics↗

bioRxiv2022

The chromatin landscape of Th17 cells reveals mechanisms of diversification of regulatory and pro-inflammatory states

Th17 cells are a heterogenous cell population consisting of non-pathogenic Th17 cells (npTh17) that contribute to tissue homeostasis and pathogenic Th17 cells (pTh17) that are potent mediators of tissue inflammation. To reveal regulatory mechanisms underlying Th17 heterogeneity, we performed combined ATAC-seq and RNA-seq and discovered substantial differences in the chromatin landscape of npTh17 and pTh17 cells both in vitro and in vivo. Compared to other CD4+ T cell subsets, npTh17 cells share accessible chromatin programs with Tregs, and pTh17 cells have an intermediate profile spanning features of npTh17 cells and Th1 cells. Integrating single-cell ATAC-seq and single-cell RNA-seq, we inferred self-reinforcing and mutually exclusive regulatory networks controlling the different cell states and predicted transcription factors (TFs) shaping the chromatin landscape of Th17 cell pathogenicity. We validated one novel TF, BACH2, which promotes immunomodulatory npTh17 programs and restrains pro-inflammatory Th1-like programs in Th17 cells and showed genetic evidence for protective variants in the human BACH2 locus associated with multiple sclerosis. Our work uncovered mechanisms that regulate Th17 heterogeneity, revealed shared regulatory programs with other CD4+ T cell subsets, and identified novel drivers of Th17 pathogenicity as potential targets to mitigate autoimmunity.

immunology↗

bioRxiv2021

Functional Inference of Gene Regulation using Single-Cell Multi-Omics

Cells require coordinated control over gene expression when responding to environmental stimuli. Here, we apply scATAC-seq and scRNA-seq in resting and stimulated human blood cells. Collectively, we generate [~]91,000 single-cell profiles, allowing us to probe the cis-regulatory landscape of immunological response across cell types, stimuli and time. Advancing tools to integrate multi-omic data, we develop FigR - a framework to computationally pair scATAC-seq with scRNA-seq cells, connect distal cis-regulatory elements to genes, and infer gene regulatory networks (GRNs) to identify candidate TF regulators. Utilizing these paired multi-omic data, we define Domains of Regulatory Chromatin (DORCs) of immune stimulation and find that cells alter chromatin accessibility prior to production of gene expression at time scales of minutes. Further, the construction of the stimulation GRN elucidates TF activity at disease-associated DORCs. Overall, FigR enables the elucidation of regulatory interactions across single-cell data, providing new opportunities to understand the function of cells within tissues.

genomics↗

bioRxiv2020

Deep learning and alignment of spatially-resolved whole transcriptomes of single cells in the mouse brain with Tangram

Charting a biological atlas of an organ, such as the brain, requires us to spatially-resolve whole transcriptomes of single cells, and to relate such cellular features to the histological and anatomical scales. Single-cell and single-nucleus RNA-Seq (sc/snRNA-seq) can map cells comprehensively5,6, but relating those to their histological and anatomical positions in the context of an organs common coordinate framework remains a major challenge and barrier to the construction of a cell atlas7-10. Conversely, Spatial Transcriptomics allows for in-situ measurements11-13 at the histological level, but at lower spatial resolution and with limited sensitivity. Targeted in situ technologies1-3 solve both issues, but are limited in gene throughput which impedes profiling of the entire transcriptome. Finally, as samples are collected for profiling, their registration to anatomical atlases often require human supervision, which is a major obstacle to build pipelines at scale. Here, we demonstrate spatial mapping of cells, histology, and anatomy in the somatomotor area and the visual area of the healthy adult mouse brain. We devise Tangram, a method that aligns snRNA-seq data to various forms of spatial data collected from the same brain region, including MERFISH1, STARmap2, smFISH3, and Spatial Transcriptomics4 (Visium), as well as histological images and public atlases. Tangram can map any type of sc/snRNA-seq data, including multi-modal data such as SHARE-seq data5, which we used to reveal spatial patterns of chromatin accessibility. We equipped Tangram with a deep learning computer vision pipeline, which allows for automatic identification of anatomical annotations on histological images of mouse brain. By doing so, Tangram reconstructs a genome-wide, anatomically-integrated, spatial map of the visual and somatomotor area with [~]30,000 genes at single-cell resolution, revealing spatial gene expression and chromatin accessibility patterning beyond current limitation of in-situ technologies.

genomics↗

bioRxiv2020

Temporally-Divergent Regulatory Mechanisms Govern Neuronal Development and Diversification in the Neocortex

Mammalian neocortical neurons span one of the most diverse cell type spectra of any tissue. The regulatory strategies that neurons use during progressive development and maturation remain unclear. We present an integrated single-cell epigenomic and transcriptional analysis of individual classes of neurons from both mouse and marmoset neocortex, sampled during both early postmitotic stages of identity acquisition and later stages of neuronal plasticity and circuit integration. We find that in both species, the regulatory strategies controlling these early and late stages diverge: early postmitotic neurons use molecular regulatory programs with broader tissue distribution and greater evolutionary conservation, while programs active during later neuronal maturation implement more brain- and neuron-specific mechanisms showing greater evolutionary divergence. The data uncovers a temporally-regulated shift in regulatory choices, likely reflecting unique evolutionary constraints on distinct events of neuronal development in the neocortex.

neuroscience↗

bioRxiv2020

Chromatin potential identified by shared single cell profiling of RNA and chromatin

Cell differentiation and function are regulated across multiple layers of gene regulation, including the modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of the regulatory events leading to cell fate commitment. Here, we developed SHARE-seq, a highly scalable approach for measurement of chromatin accessibility and gene expression within the same single cell. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define Domains of Regulatory Chromatin (DORCs), which significantly overlap with super-enhancers. We show that during lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting changes in chromatin accessibility may prime cells for lineage commitment. We therefore develop a computational strategy (chromatin potential) to quantify chromatin lineage-priming and predict cell fate outcomes. Together, SHARE-seq provides an extensible platform to study regulatory circuitry across diverse cells within tissues.

genomics↗