Biology subjects

Sanders, E.

Publications and source records attributed to Sanders, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Learning quality scores for chromatin accessibility bigWig tracks using Machine Learning

High-throughput chromatin accessibility assays such as bulk and single-cell ATAC-seq have generated large collections of processed signal tracks in bigWig format, which are widely used for visualisation, data integration, and Machine Learning (ML)-based analyses. Despite their central role, systematic quality control (QC) frameworks operating directly at the level of bigWig signal tracks remain underdeveloped. This gap limits the ability to assess data reliability and hampers robust downstream analyses. Here, we present a biologically grounded QC framework for chromatin accessibility bigWig files that integrates peak-level information, background noise estimation, and recovery of stable genomic reference features. Using an ML-based peak caller (LanceOtron), we derive complementary quality metrics capturing signal structure and signal-to-noise properties. We further define constant promoter and CTCF regions as internal biological controls and show that their recovery provides a sensitive measure of data quality across diverse cellular contexts. We apply this framework to a collection of 502 human chromatin accessibility bigWig tracks spanning a wide range of tissues and cell types. The proposed metrics capture related but non-redundant aspects of signal quality and motivate the use of constant promoter and CTCF recovery as biologically meaningful targets. An XGBoost model trained on LanceOtron-derived features accurately predicts recovery of these stable genomic elements on held-out data (R2 = 0.97), yielding a continuous and interpretable quality score. Feature importance analysis using SHAP values highlights that model decisions are driven by biologically relevant signal properties rather than arbitrary heuristics. Quantile-based stratification of the quality score is further supported by clear qualitative differences in genome browser visualisations. Together, this work provides a principled and extensible frame-work for assessing the quality of chromatin accessibility bigWig tracks, enabling more reliable data integration and supporting downstream ML applications in regulatory genomics.

bioinformatics↗

bioRxiv2025

GWAS SVatalog: a visualization tool to aid fine-mapping of GWAS loci with structural variations

BackgroundGenome-wide association studies (GWAS) have been successful in identifying single nucleotide polymorphisms (SNPs) associated with phenotypic traits. However, SNPs form an incomplete set of variation across the genome and since a large percentage of GWAS-significant SNPs lie in non-coding regions, their impact on a given trait is difficult to decipher. Recognizing whether these SNPs are tagging other polymorphisms, like structural variations (SV), is an important step towards understanding the putative causal variation at GWAS loci. ResultsHere, we develop GWAS SVatalog (https://svatalog.research.sickkids.ca/), a novel open-source web tool that computes and visualizes linkage disequilibrium (LD) between SVs and GWAS-associated SNPs throughout the human genome. The tool combines GWAS Catalogs SNP-trait association data across 14,479 phenotypes with LD statistics calculated between 35,732 SVs and 116,870 SNPs identified in 101 whole-genome long-read sequences. We use GWAS SVatalog to identify SVs that may explain GWAS loci for iron levels, refractive error, and Alzheimers disease, where previously SNPs were unable to provide a causal explanation. ConclusionsGWAS SVatalog advances the fine-mapping of GWAS loci with structural variations, enabling researchers to associate 35,732 common SVs with 14,479 phenotypes, accelerating the understanding of disease etiology.

bioinformatics↗

bioRxiv2025

REnformer, a single-cell ATAC-seq predicting model to investigate open chromatin sites

Genome regulatory elements are fundamental to cellular identity and cell type specific gene expression. Understanding how the underlying genetic code is differentially utilised by different cell types is central to understanding human health and disease. To better understand how DNA encodes genome regulatory elements such as promoters, enhancers, and boundary elements, we leverage the Enformer gene expression and epigenetic prediction model. We used transfer learning with high quality single cell ATAC datasets to develop REnformer, a model to predict chromatin accessibility. By introducing a bench-mark for comparing performances against Enformer model, REnformer significantly outperformed Enformer in terms of higher prediction outcomes and lower error rates in all extensive analyses shown; introducing these benchmarks allowed us, and possible future works, to fairly compare such models. We further tested REnformer by predicting the effects of a well characterised -thalassemia variant and found that the prediction aligned with the observed change in genome regulatory element, previously validated. We conclude that REnformer is and can be a state-of-the-art tool to predict cell type specific regulatory elements, and interrogate the effect of genome variation in health and disease.

bioinformatics↗

bioRxiv2024

RUVBL1 and RUVBL2 are druggable MYCN regulators in neuroblastoma.

High-risk neuroblastoma is characterized by MYCN amplification and high MYCN or MYC gene expression. These patients have a poor prognosis and there is an urgent need for more effective drugs. While strategies to develop inhibitors that directly target the MYC proteins have remained largely unsuccessful, recent preclinical studies have identified ATR, a key protein of the DNA damage response, as a promising alternative therapeutic target. Here we identified a strong RUVBL1 and RUVBL2 signature in transcriptomics data derived from different MYCN-driven mice tumors treated with ATR inhibitors. The RUVBL proteins form a complex with ATPase activity that has broad cellular functions and we demonstrate that pharmacological inhibition of this protein complex results in a strong reduction of MYC signaling, cell cycle arrest, DNA damage and apoptosis. We confirmed the association with MYCN and identified the RUVBL genes as independent prognosticators in human primary neuroblastoma data.

cancer biology↗

bioRxiv2024

5UTR translational inhibition of neuroblastoma dependency factors using the CR-1-31-B rocaglate

Current therapies for neuroblastoma are often ineffective and survivors suffer from severe long-term therapy related side-effects, underscoring the need for identification of novel drugging strategies. We performed an in-depth evaluation of phenotypic and molecular responses following exposure of neuroblastoma cells to the rocaglate CR-1-31-B, scrutinizing its mode-of-action through integrative ribosome footprinting and shotgun proteome profiling. We could show that CR-1-31-B significantly reduces tumor growth in vivo without apparent toxicity. By means of combined ribosome footprinting and transcriptome analysis we uncovered that CR-1-31-B treatment downregulates translation efficiencies of several major neuroblastoma dependencies including MYCN, CCND1 and ALK as well as factors involved in the G2/M checkpoint. Upregulated targets are enriched for oxidative phosphorylation pathway components and DNA repair. At the proteome level, CR-1-31-B imposed downregulation of a FOXM1 driven signature, including the FOXM1 target gene TPX2. We show that neuroblastoma cells are dependent on TPX2 for growth and DNA repair and further demonstrate enhanced CHK1 sensitivity upon TPX2 knockdown. Next, we also observed synergistic effects of CHK1 inhibition with CR-1-31-B. In conclusion, our data support CR-1-31-B as a potent novel therapeutic agent in neuroblastoma, in particular in combination with DNA damage or replication stress inducing agents.

cancer biology↗

bioRxiv2024

Deciphering cis-regulatory elements using REgulamentary

With the boom in Genome-Wide Association Studies (GWAS), it has become apparent that many disease-associated genetic variants lie in the non-coding regions of the genome. In order to prioritise these variants and disentangle their functional significance, it is important to be able to accurately classify cis-regulatory elements within these non-coding regions of the genome. Historically, the classification of cis-regulatory elements relied purely on the presence of characteristic histone marks, with recent advancements in their classification using more sophisticated Hidden Markov Model (HMM)-based approaches. The limitation of the HMM-based approaches is that the output of these models is an arbitrary chromatin state, which then requires the user to manually assign these states to a particular class of cis-regulatory elements. Here we present a new tool, REgulamentary, which enables de novo genome-wide annotation of cis-regulatory elements in a cell-type specific manner. We benchmarked REgulamentary against GenoSTAN, the most popular existing published chromatin annotation and regulatory element identification tool, to demonstrate the advancements REgulamentary can provide in assigning chromatin states. Finally, as an example of REgulamentarys utility in solving complex disease trait loci, we applied REgulamentary to published GWAS data to demonstrate how this tool can be used to prioritise likely causal variants.

bioinformatics↗

bioRxiv2023

The chromatin reader PHF6 at the crossroad of the replication stress and DNA damage responses in neuroblastoma through interaction with RRM2

The PHF6 protein is a presumed chromatin reader implicated in disease through germline loss-of-function mutations causing cognitive disability syndromes and somatic mutations are predominantly observed in acute T-cell leukemia. Previous reports support a role for PHF6 in DNA damage repair, replication fork restart as well as hematopoietic precursor cell self-renewal capacity and lineage commitment. To explore better how PHF6 mediates these functions, we mapped the PHF6 interactome and identified RRM2 as a consistent binding partner across different normal and malignant cell types. Next, PHF6 knockdown imposed increased replicative stress/DNA damage and suggested possible binding of PHF6 to H3K56ac, a marker for nascent DNA at sites of DNA damage repair. Genome-wide mapping of PHF6 chromatin binding indeed revealed overlap with sites of active DNA damage, binding sites of replication fork proteins and functional crosstalk with the neuroblastoma transcription core regulatory circuitry. Altogether, we show a canonical PHF6-RRM2 interaction enabling active transport of RRM2 to genomic sites of PHF6 mediated fork restart and PHF6 localization to H3K56ac at highly transcribed genes facilitating fork restart following replication-transcription conflicts.

cancer biology↗

bioRxiv2022

Secretoglobin family 1D member 2 (SCGB1D2) protein inhibits growth of Borrelia burgdorferi and affects susceptibility to Lyme disease

Lyme disease is a tick-borne disease caused by bacteria of the genus Borrelia. The disease can initially manifest as an erythema migrans rash and, if able to evade the host immune defenses, can progress into a secondary stage chronic disease with debilitating physical or neurological manifestations1,2. The host factors that modulate susceptibility for Lyme disease have remained mostly unknown. Here we show a novel host defense mechanism against Lyme disease in humans. Using epidemiological and genetic data from FinnGen, we identify a common missense variant at the gene encoding for Secretoglobin family 1D member 2 (SCGB1D2) protein that increases the susceptibility for Lyme disease. The genetic variant changes proline at position 53 to leucine and is predicted as deleterious. Consequently, we validate the dysfunction of this protein variant using live Borrelia burgdorferi (Bb). Recombinant reference SCGB1D2 protein inhibits the growth of Bb twice as effectively as the recombinant SCGB1D2 P53L deleterious missense variant. Together, these data suggest that SCGB1D2 is a host defense factor present in the skin, sweat, and other secretions which protects against Bb infection. This finding provides a novel therapeutic avenue for drug development to prevent and treat Lyme disease.

genetics↗

bioRxiv2022

resPAINT: Accelerating volumetric super-resolution localisation microscopy by active control of probe emission

Points for accumulation in nanoscale topography (PAINT) allows the acquisition of practically unlimited measurements in localisation microscopy. However, PAINT is inherently limited by unwanted background fluorescence at high probe concentrations, especially in large depth-of-field volumetric imaging techniques. Here we present reservoir-PAINT (resPAINT), in which we combine PAINT with active control of probe photophysics. In resPAINT, a reservoir of non-fluorescent activatable probes accumulate on the target, which makes it possible to drastically improve the localisation rate (by up to 50-fold) compared to conventional PAINT, without any compromise in contrast. By combining resPAINT with large depth-of-field microscopy, we demonstrate volumetric super-resolution imaging of entire cell surfaces. We then generalise the approach by implementing multiple switching strategies, including photoactivation and spontaneous blinking. We also implement alternative volumetric imaging modalities including the double-helix pointspread function, the tetrapod point-spread function and singlemolecule light field microscopy. Finally, we show that resPAINT can be used with a Fab to image membrane proteins, effectively extending the operating regime of conventional PAINT to encompass a larger range of biological interactions.

biophysics↗

bioRxiv2022

Novel Association of Lyme Disease, Age, and Atopic Dermatitis

Borrelia burgdorferi (B. burgdorferi) is a bacterial spirochete that can cause Lyme disease after infecting a susceptible host. Immune responses to the bacteria are highly variable and host specific. The murine substrain, C3H/HeJ, is a frequently utilized mouse model of Lyme disease. In this study, we sought to investigate the correlation of age with onset and severity of dermatitis, both in mice infected with B. burgdorferi as well as humans who have had a diagnosis of Lyme disease. Female C3H/HeJ mice aged 6-8 weeks, 1 year, or 2 years were infected intraperitoneally with 105 B. burgdorferi. Dermatitis of the tail was evaluated by gross examination and histology. Additional female C3H/HeJ and C57BL/6J mice aged 5 weeks were injected intradermally with 105 B. burgdorferi containing the luciferase reporter gene then analyzed under in vivo imaging. Human data via electronic health records of 342,499 Finnish individuals was tested and analyzed for associations between Lyme disease and atopic dermatitis. Dermatitis worsened over the course of untreated infection, with ulceration, hemorrhaging, flaking, hair loss, and dark lesions as well as spongiosis and acanthosis. These features of dermatitis were present in infected mice after 1 year of age. We further confirm the presence of B. burgdorferi in the tail through quantification of bioluminescence and immunohistochemistry of both C3H/HeJ and C57BL/6J mice. This relationship among Lyme disease, atopic dermatitis, and host age seen in the mouse model is consistent with a large pool (342,499) of human epidemiological data from Finland. We identified 5,248 individuals with Lyme disease and 17,233 with atopic dermatitis in FinnGen. Retrospective analysis shows Lyme disease is associated with atopic dermatitis (OR = 1.91 [1.68 -2.37], P < 2e-16). More visits due to Lyme disease complications (3 or more visits versus 1 visit) were associated with atopic dermatitis (OR = 2.19 [1.35-3.55], P = 0.0014) and risk of developing atopic dermatitis over time (HR=2.26 [1.54-3.95], P = 0.0017). Data from mice and humans reveal a novel relationship among Lyme disease, age, and atopic dermatitis. Through defined pathological scoring, we demonstrate the onset of murine atopic dermatitis with B. burgdorferi infection, which is further exacerbated by host age at time of infection. In humans, a diagnosis of Lyme disease in FinnGen was associated with atopic dermatitis and further research is warranted to establish causation.

immunology↗

bioRxiv2021

Deciphering the tumor-specific immunopeptidome in vivo with genetically engineered mouse models

Effective immunosurveillance of cancer requires the presentation of peptide antigens on major histocompatibility complex Class I (MHC-I). Recent developments in proteomics have improved the identification of peptides that are naturally presented by MHC-I, collectively known as the "immunopeptidome". Current approaches to profile tumor immunopeptidomes have been limited to in vitro investigation, which fails to capture the in vivo repertoire of MHC-I peptides, or bulk tumor lysates, which are obscured by the lack of tumor-specific MHC-I isolation. To overcome these limitations, we report here the engineering of a Cre recombinase-inducible affinity tag into the endogenous mouse MHC-I gene and targeting of this allele to the KrasLSL-G12D/+; p53fl/fl (KP) mouse model (KP; KbStrep). This novel approach has allowed us to isolate tumor-specific MHC-I peptides from autochthonous pancreatic ductal adenocarcinoma (PDAC) and lung adenocarcinoma (LUAD) in vivo. With this powerful analytical tool, we were able to profile the evolution of the LUAD immunopeptidome through tumor progression and show that in vivo MHC-I presentation is shaped by post-translational mechanisms. We also uncovered novel, putative LUAD tumor associated antigens (TAAs). Many peptides that were recurrently presented in vivo exhibited very low expression of the cognate mRNA, provoking reconsideration of antigen prediction pipelines that triage peptides according to transcript abundance. Beyond cancer, the KbStrep allele is compatible with a broad range of Cre-driver lines to explore antigen presentation in vivo in the pursuit of understanding basic immunology, infectious disease, and autoimmunity.

cancer biology↗

bioRxiv2020

RRM2 is a target for synthetic lethal interactions with replication stress checkpoint addiction in high-risk neuroblastoma

Neuroblastoma is a pediatric tumor originating from the sympathetic nervous system responsible for 10-15 percent of all childhood cancer deaths. Half of all neuroblastoma patients present with high-risk disease at diagnosis. Despite intensive multi-modal therapies nearly 50 percent of high-risk cases relapse and die of their disease. In contrast to the overall paucity of mutations, high-risk neuroblastoma nearly invariably present with recurrent somatic segmental chromosome copy number variants. For several focal aberrations (e.g. MYCN and LIN28B amplification), the direct role in tumor formation has been established. However, for recurrent aberrations, such as chromosome 2p and 17q gains, the identification of genes contributing to tumor initiation or progression has been challenging due to the scarcity of small segmental gains or amplifications. In this study, we identified and functionally evaluated the ribonucleotide reductase regulatory subunit 2 (RRM2) as a top-ranked 2p putative co-driver and therapeutic target in high-risk neuroblastoma enforcing replicative stress resistance. In vitro knock down and pharmacological RRM2 inhibition highlight RRM2 dependency in neuroblastoma cells, further supported by the finding that co-overexpression of RRM2 in a d{beta}h-MYCN transgenic zebrafish line increased tumor penetrance with 80% and accelerated tumor formation. Given the critical role of RRM2 in replication fork progression and regulation of RRM2 through ATR/CHK1 signaling, we tested combined RRM2 and ATR/CHK1 small molecule inhibition with triapine and BAY1895344/prexasertib respectively, and observed strong synergism, in particular for combined RRM2 and CHK1 inhibition. Transcriptome analysis following combinatorial drugging revealed HEXIM1 as one of the strongest upregulated genes. Using programmable DNA binding of dCas9 with a promiscuous biotin ligase, RRM2 promotor bound proteins were identified including HEXIM1 and NurRD complex members, supporting a cooperative role for HEXIM1 upregulation together with CHK1 inhibition in further attenuating RRM2 expression levels. We evaluated the impact of combined RRM2/CHK1 inhibition in vivo, with treatment of a murine xenograft model showing rapid and complete tumor regression, without tumor regrowth upon treatment arrest. In conclusion, we identified RRM2 as a novel dependency gene in neuroblastoma and promising target for synergistic drug combinations with small compounds targeting DNA checkpoint regulators.

cancer biology↗

bioRxiv2020

Building a virtual summer research experience in cancer for high school and early undergraduate students: lessons from the COVID-19 pandemic

BackgroundThe COVID-19 pandemic posed a unique challenge for summer research programs in 2020, particularly for programs aimed at hands-on experience for younger trainees. The Indiana University Melvin and Bren Simon Comprehensive Cancer Center supports two pipeline programs, which traditionally immerse high school juniors, seniors, and early undergraduate students from underrepresented populations in science in hands-on projects in cancer biology labs. However, due to social distancing policies during the pandemic and reduction of research operations, these students were not physically allowed on campus. Thus, the authors set out to strategically pivot to a wholly virtual curriculum and evaluate the Virtual Summer Research Experience in Cancer outcomes. MethodsThe virtual program included four components: 1. a core science and professional development curriculum led by high school teachers and senior undergraduates; 2. faculty-delivered didactic sessions on cancer science; 3. mentored, virtual research projects with research faculty; and 4. online networking events to encourage vertical mentoring. Outcomes data were measured using an 11-item Research Preparation scale, daily electronic feedback, and structured evaluation and feedback via Zoom weekly. ResultsOutcome data suggested high self-reported satisfaction with the virtual program. Outcome data also revealed the importance of coordination between multiple entities for seamless program implementation. This includes the active recruitment and participation of high school teachers and further investment in information technology capabilities of institutions. ConclusionsFindings reveal a path to educate and train high school and early undergraduate students in cancer research when hands-on, in-person training is not feasible. Virtual research experiences are not only useful to engage students during public health crises but can provide an avenue for cancer centers to expand their cancer education footprints to remotely located schools and universities with limited resources to provide such experiences to their students.

scientific communication and education↗

bioRxiv2020

Recurrent chromosomal imbalances provide selective advantage to human embryonic stem cells under enhanced replicative stress conditions

Human embryonic stem cells (hESCs) and embryonal tumors share a number of common features including a compromised G1/S checkpoint. Consequently, these rapidly dividing hESCs and cancer cells undergo elevated levels of replicative stress which is known to induce genomic instability causing chromosomal imbalances. In this context, it is of interest that long-term in vitro cultured hESCs exhibit a remarkable high incidence of segmental DNA copy number gains, some of which are also highly recurrent in certain malignancies such as 17q gain (17q+). The selective advantage of DNA copy number changes in these cells has been attributed to several underlying processes including enhanced proliferation. We hypothesized that these recurrent chromosomal imbalances become rapidly embedded in the cultured hESCs through a replicative stress driven Darwinian selection process. To this end, we compared the effect of hydroxyurea induced replicative stress versus normal growth conditions in an equally-mixed cell population of isogenic euploid and 17q+ hESCs. We could show that 17q+ hESCs rapidly overtook normal hESCs. Our data suggest that recurrent chromosomal segmental gains provide a proliferative advantage to hESCs under increased replicative stress, a process that may also explain the highly recurrent nature of certain imbalances in cancer.

cancer biology↗

bioRxiv2020

Comprehensive synthetic genetic array analysis of alleles that interact with mutation of the Saccharomyces cerevisiae RecQ helicases Hrq1 and Sgs1

Most eukaryotic genomes encode multiple RecQ family helicases, including five such enzymes in humans. For many years, the yeast Saccharomyces cerevisiae was considered unusual in that it only contained a single RecQ helicase, named Sgs1. However, it has recently been discovered that a second RecQ helicase, called Hrq1, resides in yeast. Both Hrq1 and Sgs1 are involved in genome integrity, functioning in processes such as DNA inter-strand crosslink repair, double-strand break repair, and telomere maintenance. However, it is unknown if these enzymes interact at a genetic, physical, or functional level as demonstrated for their human homologs. Thus, we performed synthetic genetic array (SGA) analyses of hrq1{Delta} and sgs1{Delta} mutants. As inactive alleles of helicases can demonstrate dominant phenotypes, we also performed SGA analyses on the hrq1-K318A and sgs1-K706A ATPase/helicase-null mutants, as well as all combinations of deletion and inactive double mutants. We crossed these eight query strains (hrq1{Delta}, sgs1{Delta}, hrq1-K318A, sgs1-K706A, hrq1{Delta} sgs1{Delta}, hrq1{Delta} sgs1-K706A, hrq1-K318A sgs1{Delta}, and hrq1-K318A sgsl-K706A) to the S. cerevisiae single gene deletion and temperature-sensitive allele collections to generate double and triple mutants and scored them for synthetic positive and negative genetic effects based on colony growth. These screens identified hundreds of synthetic interactions, supporting the known roles of Hrq1 and Sgs1 in DNA repair, as well as suggesting novel connections to rRNA processing, mitochondrial DNA maintenance, transcription, and lagging strand synthesis during DNA replication.

genetics↗

bioRxiv2020

The genetic and physical interactomes of the Saccharomyces cerevisiae Hrq1 helicase

The human genome encodes five RecQ helicases (RECQL1, BLM, WRN, RECQL4, and RECQL5) that participate in various processes underpinning genomic stability. Of these enzymes, the disease-associated RECQL4 is comparatively understudied due to a variety of technical challenges. However, Saccharomyces cerevisiae encodes a functional homolog of RECQL4 called Hrq1, which is more amenable to experimentation and has recently been shown to be involved in DNA inter-strand crosslink (ICL) repair and telomere maintenance. To expand our understanding of Hrq1 and the RecQ4 subfamily of helicases in general, we took a multi-omics approach to define the Hrq1 interactome in yeast. Using synthetic genetic array analysis, we found that mutations of genes involved in processes such as DNA repair, chromosome segregation, and transcription synthetically interact with deletion of HRQ1 and the catalytically inactive hrq1-K318A allele. Pull-down of tagged Hrq1 and mass spectrometry identification of interacting partners similarly underscored links to these processes and others. Focusing on transcription, we found that hrq1 mutant cells are sensitive to caffeine and that mutation of HRQ1 alters the expression levels of hundreds of genes. In the case of hrq1-K318A, several of the most highly upregulated genes encode proteins of unknown function whose expression levels are also increased by DNA ICL damage. Together, our results suggest a heretofore unrecognized role for Hrq1 in transcription, as well as novel members of the Hrq1 ICL repair pathway. These data expand our understanding of RecQ4 subfamily helicase biology and help to explain why mutations in human RECQL4 cause diseases of genomic instability.

genetics↗

bioRxiv2020

SOX11 is a lineage-dependency factor and master epigenetic regulator in neuroblastoma

The pediatric extra-cranial tumor neuroblastoma (NB) is characterised by a low mutation burden while copy number alterations are present in most high-risk cases. We identified SOX11 as a strong lineage dependency transcription factor in adrenergic NB based on recurrent chromosome 2p focal gains and amplifications, its specific expression in the normal sympatho-adrenal lineage and adrenergic NBs and its regulation by multiple adrenergic specific cis-interacting (super-)enhancers. Adrenergic NBs are strongly dependent on high SOX11 expression levels for growth and proliferation. Through genome-wide DNA-binding and transcriptome analysis, we identified and validated functional SOX11 target genes, several of which implicated in chromatin remodeling and epigenetic modification. SOX11 controls chromatin accessibility predominantly affecting distal adrenergic lineage-specific enhancers marked by binding sites of the adrenergic core regulatory circuitry. During normal sympathoblast differentiation we find expression of SOX11 prior to members of the adrenergic core regulatory circuitry. Given the broad control of SOX11 of multiple epigenetic regulatory complexes and its presumed pioneer factor function, we propose that adrenergic NB cells have co-opted the normal role of SOX11 as a crucial regulator of chromatin accessibility and cell identity.

cancer biology↗

bioRxiv2020

Anipose: a toolkit for robust markerless 3D pose estimation

AO_SCPLOWBSTRACTC_SCPLOWQuantifying movement is critical for understanding animal behavior. Advances in computer vision now enable markerless tracking from 2D video, but most animals live and move in 3D. Here, we introduce Anipose, a Python toolkit for robust markerless 3D pose estimation. Anipose is built on the popular 2D tracking method DeepLabCut, so users can easily expand their existing experimental setups to obtain accurate 3D tracking. It consists of four components: (1) a 3D calibration module, (2) filters to resolve 2D tracking errors, (3) a triangulation module that integrates temporal and spatial regularization, and (4) a pipeline to structure processing of large numbers of videos. We evaluate Anipose on four datasets: a moving calibration board, fruit flies walking on a treadmill, mice reaching for a pellet, and humans performing various actions. By analyzing 3D leg kinematics tracked with Anipose, we identify a key role for joint rotation in motor control of fly walking. We believe this open-source software and accompanying tutorials (anipose.org) will facilitate the analysis of 3D animal behavior and the biology that underlies it.

neuroscience↗