Biology subjects

Duarte, F. M.

Publications and source records attributed to Duarte, F. M..

11 recordsLinked to original sources

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↗

bioRxiv2023

Cell of origin epigenetic priming determines susceptibility to Tet2 mutation

Hematopoietic stem cell mutations can result in clonal hematopoiesis (CH) but the clinical outcomes are heterogeneous. The nature of the founder mutation and secondary mutations likely drive emergent neoplastic disease. We investigated how the state of the cell of origin where the Tet2 mutation occurs affects susceptibility to that commonly occurring CH mutation. Here, we provide evidence that risk is written in the epigenome of the cell of origin. By characterizing cell states that underlie myeloid differentiation and linking this information to an inducible system to assess myeloid progenitor clones, we provide evidence that epigenetic markers of the cell where Tet2 mutation occurs stratifies clonal behaviors. Specifically, Sox4 fosters a global cell state of high sensitization towards Tet2 KO. Using GMP and primary HSC models, we show that Sox4 promotes cell dedifferentiation, alters cell metabolism and increases the in vivo clonal output of mutant cells. Our results validate the hypothesis that epigenetic features can predispose specific clones for dominance and explain why an identical mutation can result in different outcomes.

cancer 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↗

bioRxiv2021

Kinetic networks identify key regulatory nodes and transcription factor functions in early adipogenesis

Adipocytes contribute to metabolic disorders such as obesity, diabetes, and atherosclerosis. Prior characterizations of the transcriptional network driving adipogenesis overlook transiently acting transcription factors (TFs), genes, and regulatory elements that are essential for proper differentiation. Moreover, traditional gene regulatory networks provide neither mechanistic details about individual RE-gene relationships nor temporal information needed to define a regulatory hierarchy that prioritizes key regulatory factors. To address these shortcomings, we integrate kinetic chromatin accessibility (ATAC-seq) and nascent transcription (PRO-seq) data to generate temporally resolved networks that describe TF binding events and resultant effects on target gene expression. Our data indicate which TF families cooperate with and antagonize each other to regulate adipogenesis. Compartment modeling of RNA polymerase density quantifies how individual TFs mechanistically contribute to distinct steps in transcription. Glucocorticoid receptor activates transcription by inducing RNA polymerase pause release while SP and AP1 factors affect RNA polymerase initiation. We identify Twist2 as a previously unappreciated effector of adipocyte differentiation. We find that TWIST2 acts as a negative regulator of 3T3-L1 and primary preadipocyte differentiation. We confirm that Twist2 knockout mice have compromised lipid storage within subcutaneous and brown adipose tissue. Previous phenotyping of Twist2 knockout mice and Setleis syndrome (Twist2-/-) patients noted deficiencies in subcutaneous adipose tissue. This network inference framework is a powerful and general approach for interpreting complex biological phenomena and can be applied to a wide range of cellular processes.

genomics↗

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

Pioneer factor GAF cooperates with PBAP and NURF to regulate transcription

Transcriptionally silent genes must be activated throughout development. This requires nucleosomes be removed from promoters and enhancers to allow transcription factor binding (TFs) and recruitment of coactivators and RNA Polymerase II (Pol II). Specialized pioneer TFs bind nucleosome-wrapped DNA to perform this chromatin opening by mechanisms that remain incompletely understood1-3. Here, we show that GAGA-factor (GAF), a Drosophila pioneer factor4, interacts with both SWI/SNF and ISWI family chromatin remodelers to allow recruitment of Pol II and entry to a promoter-proximal paused state, and also to promote Pol IIs transition to productive elongation. We found that GAF functions with PBAP (SWI/SNF) to open chromatin and allow Pol II to be recruited. Importantly this activity is not dependent on NURF as previously proposed5-7; however, GAF also functions with NURF downstream of this process to ensure efficient Pol II pause release and transition to productive elongation apparently through its role in precisely positioning the +1 nucleosome. These results demonstrate how a single sequence-specific pioneer TF can synergize with remodelers to activate sets of genes. Furthermore, this behavior of remodelers is consistent with findings in yeast8-10 and mice11-13, and likely represents general, conserved mechanisms found throughout Eukarya.

genomics↗

bioRxiv2019

AtacWorks: A deep convolutional neural network toolkit for epigenomics

We introduce AtacWorks (https://github.com/clara-genomics/AtacWorks), a method to denoise and identify accessible chromatin regions from low-coverage or low-quality ATAC-seq data. AtacWorks uses a deep neural network to learn a mapping between noisy ATAC-seq data and corresponding higher-coverage or higher-quality data. To demonstrate the utility of AtacWorks, we train a model on data from four human blood cell types and show that this model accurately denoises chromatin accessibility at base-pair resolution and identifies peaks from low-coverage bulk sequencing of unseen cell types and experimental conditions. We use the same framework to obtain high-quality results from as few as 50 aggregate single-cell ATAC-seq profiles, and also from data with a low signal-to-noise ratio. We further show that AtacWorks can be adapted for cross-modality prediction of transcription factor footprints and ChIP-seq peaks from low input ATAC-seq. Finally, we demonstrate the applications of our approach to single-cell genomics by using AtacWorks to identify regulatory regions that are differentially-accessible between rare lineage-primed subpopulations of hematopoietic stem cells.

genomics↗

bioRxiv2019

Defining data-driven primary transcript annotations with primaryTranscriptAnnotation in R

Nascent transcript measurements derived from run-on sequencing experiments are critical for the investigation of transcriptional mechanisms and regulatory networks. However, conventional gene annotations specify the boundaries of mRNAs, which significantly differ from the boundaries of primary transcripts. Moreover, transcript isoforms with distinct transcription start and end coordinates can vary between cell types. Therefore, new primary transcript annotations are needed to accurately interpret run-on data. We developed the primaryTranscriptAnnotation R package to infer the transcriptional start and termination sites of annotated genes from genomic run-on data. We then used these inferred co-ordinates to annotate transcriptional units identified de novo. Hence, this package provides the novel utility to integrate data-driven primary transcript annotations with transcriptional unit coordinates identified in an unbiased manner. Our analyses demonstrated that this new methodology increases the sensitivity for detecting differentially expressed transcripts and provides more accurate quantification of RNA polymerase pause indices, consistent with the importance of using accurate primary transcript coordinates for interpreting genomic nascent transcription data.\n\nAvailabilityhttps://github.com/WarrenDavidAnderson/genomicsRpackage/tree/master/primaryTranscriptAnnotation

genomics↗

bioRxiv2019

Droplet-based combinatorial indexing for massive scale single-cell epigenomics

While recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution, the throughput and quality of these methods have limited the widespread adoption of these technologies. Here, we describe a droplet microfluidics platform for single-cell assay for transposase accessible chromatin (scATAC-seq) for high-throughput single-cell profiling of chromatin accessibility. We use this approach for the unbiased discovery of cell types and regulatory elements within the mouse brain. Further, we extend the throughput of this approach by pairing combinatorial indexing with droplet microfluidics, enabling single-cell studies at a massive scale. With this approach, we measure chromatin accessibility across resting and stimulated human bone marrow derived cells to reveal changes in the cis- and trans- regulatory landscape across cell types and upon stimulation conditions at single-cell resolution. Altogether, we describe a total of 502,207 single-cell profiles, demonstrating the scalability and flexibility of this droplet-based platform.

genomics↗

bioRxiv2019

An improved auxin-inducible degron system preserves native protein levels and enables rapid and specific protein depletion

Rapid perturbation of protein function permits the ability to define primary molecular responses while avoiding down-stream cumulative effects of protein dysregulation. The auxin-inducible degron (AID) system was developed as a tool to achieve rapid and inducible protein degradation in non-plant systems. However, tagging proteins at their endogenous loci results in chronic, auxin-independent degradation by the proteasome. To correct this deficiency, we expressed the Auxin Response Transcription Factor (ARF) in an improved inducible degron system. ARF is absent from previously engineered AID systems, but ARF is a critical component of native auxin signaling. In plants, ARF directly interacts with AID in the absence of auxin and we found that expression of the ARF Phox and Bem1 (PB1) domain suppresses constitutive degradation of AID-tagged proteins. Moreover, the rate of auxin-induced AID degradation is substantially faster in the ARF-AID system. To test the ARF-AID system in a quantitative and sensitive manner, we measured genome-wide changes in nascent transcription after rapidly depleting the ZNF143 transcription factor. Transciptional profiling indicates that ZNF143 activates transcription in cis and ZNF143 regulates promoter-proximal paused RNA Polymerase density. Rapidly inducible degradation systems that preserve the target proteins native expression levels and patterns will revolutionize the study of biological systems by enabling specific and temporally defined protein dysregulation.

molecular biology↗

bioRxiv2017

Mitotic systemic genomic instability in yeast

Conventional models of genome evolution generally include the assumption that mutations accumulate gradually and independently over time. We characterized the occurrence of sudden spikes in the accumulation of genome-wide loss-of-heterozygosity (LOH) in Saccharomyces cerevisiae, suggesting the existence of a mitotic systemic genomic instability process (mitSGI). We characterized the emergence of a rough colony morphology phenotype resulting from an LOH event spanning a specific locus (ACE2/ace2-A7). Surprisingly, half of the clones analyzed also carried unselected secondary LOH tracts elsewhere in their genomes. The number of secondary LOH tracts detected was 20-fold higher than expected assuming independence between mutational events. Secondary LOH tracts were not detected in control clones without a primary selected LOH event. We then measured the rates of single and double LOH at different chromosome pairs and found that coincident LOH accumulated at rates 30-100 fold higher than expected if the two underlying single LOH events occurred independently. These results were consistent between two different strain backgrounds, and in mutant strains incapable of entering meiosis. Our results indicate that a subset of mitotic cells within a population experience systemic genomic instability episodes, resulting in multiple chromosomal rearrangements over one or few generations. They are reminiscent of early reports from the classic yeast genetics literature, as well as recent studies in humans, both in the cancer and genomic disorder contexts, all of which challenge the idea of gradual accumulation of structural genomic variation. Our experimental approach provides a model to further dissect the fundamental mechanisms responsible for mitSGI.\n\nSIGNIFICANCE STATEMENTPoint mutations and alterations in chromosome structure are generally thought to accumulate gradually and independently over many generations. Here, we combined complementary genetic approaches in budding yeast to track the appearance of chromosomal changes resulting in loss-of-heterozygosity (LOH). Contrary to expectations, our results provided evidence for the occurrence of non-independent accumulation of multiple LOH events over one or a few cell generations. These results are analogous to recent reports of bursts of chromosomal instability in humans. Our experimental approach provides a framework to further dissect the fundamental mechanisms underlying systemic chromosomal instability processes, including in the human cancer and genomic disorder contexts.

genetics↗