Biology subjects

Lipson, D.

Publications and source records attributed to Lipson, D..

9 recordsLinked to original sources

bioRxiv2025

An automated ATAC-seq method reveals sequence determinants of transcription factor dose response in the open chromatin

Transcription factor (TF) dosage is a critical determinant of cellular identity. However, the quantitative relationship between TF dosage and its regulation of chromatin accessibility and gene expression remains poorly understood. To address this, we developed RoboATAC, a scalable, automated ATAC-seq platform for high-throughput accessibility profiling. We then systematically profiled genome-wide chromatin accessibility and gene expression changes induced by graded overexpression of 22 TFs in HEK293T cells (246 total samples), observing dose-dependent changes in accessibility and aggregate TF footprints. Modeling accessibility as a function of sequence and chromatin states revealed that DNA sequence alone accurately predicts dosage sensitivity at elements that become accessible, with low-affinity motifs requiring higher TF levels to induce accessibility. Interpretable deep learning models revealed contributions of motif orientation, spacing, and flanking bases to accessibility, both recapitulating known motifs and nominating novel dosage-sensitive motif arrangements. Nucleosome positioning analysis uncovered two distinct, TF identity dependent patterns by which accessibility is established by changing nucleosome position and occupancy.

genomics↗

bioRxiv2024

Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens

Recent advancements in functional genomics have provided an unprecedented ability to measure diverse molecular modalities, but learning causal regulatory relationships from observational data remains challenging. Here, we leverage pooled genetic screens and single cell sequencing (i.e. Perturb-seq) to systematically identify the targets of signaling regulators in diverse biological contexts. We demonstrate how Perturb-seq is compatible with recent and commercially available advances in combinatorial indexing and next-generation sequencing, and perform more than 1,500 perturbations split across six cell lines and five biological signaling contexts. We introduce an improved computational framework (Mixscale) to address cellular variation in perturbation efficiency, alongside optimized statistical methods to learn differentially expressed gene lists and conserved molecular signatures. Finally, we demonstrate how our Perturb-seq derived gene lists can be used to precisely infer changes in signaling pathway activation for in-vivo and in-situ samples. Our work enhances our understanding of signaling regulators and their targets, and lays a computational framework towards the data-driven inference of an atlas of perturbation signatures.

genomics↗

bioRxiv2023

Natural and age-related variation in circulating human hematopoietic stem cells

Hematopoietic stem and progenitor cells (HSPCs) deliver life-long multi-lineage output. However, with aging, we exhibit certain characteristic blood count changes and accumulation of clonal disorders. Better understanding of inter-individual variation in HSPC behavior is needed to understand these age-related phenomena and the transition from health to chronic and acute hematological malignancies. Here we study 627K single circulating CD34+ HSPCs (cHSPCs) from 148 healthy individuals, along with their clinical information and clonal hematopoiesis (CH) profiles, to characterize population-wide and age-related hematopoietic variability. Individuals with CH were linked with reduced frequencies of lymphocyte progenitors and higher RDW. An age-related decrease in lymphoid progenitors was observed, predominantly in males. Inter-individual transcriptional variation in expression of a Lamin-A signature and stemness gene programs were linked with aging and presence of macrocytic anemia. Based on our model for healthy cHSPC variation we construct the normal reference for cHSPC subtype frequencies. We show how compositional and expression deviations from this normal reference can robustly identify myeloid malignancies and pre-malignant states. Together, our data and methodologies present a novel resource, shedding light on various age-related hematopoietic processes, and a comprehensive normal cHSPC reference, which can serve as a tool for diagnosing and characterizing hematological disorders.

molecular biology↗

bioRxiv2023

Single-cell analysis of the nervous system at small and large scales with instant partitions

Single-cell RNA sequencing is a new frontier across all biology, particularly in neuroscience. While powerful for answering numerous neuroscience questions, limitations in sample input size, and initial capital outlay can exclude some researchers from its application. Here, we tested a recently introduced method for scRNAseq across diverse scales and neuroscience experiments. We benchmarked against a major current scRNAseq technology and found that PIPseq performed similarly, in line with earlier benchmarking data. Across dozens of samples, PIPseq recovered many brain cell types at small and large scales (1,000-100,000 cells/sample) and was able to detect differentially expressed genes in an inflammation paradigm. Similarly, PIPseq could detect expected and new differentially expressed genes in a brain single cell suspension from a knockout mouse model; it could also detect rare, virally-la-belled cells following lentiviral targeting and gene knockdown. Finally, we used PIPseq to investigate gene expression in a nontraditional model species, the little skate (Leucoraja erinacea). In total, PIPSeq was able to detect single-cell gene expression changes across models and species, with an added benefit of large scale capture and sequencing of each sample.

neuroscience↗

bioRxiv2022

Whole genome error-corrected sequencing for sensitive circulating tumor DNA cancer monitoring

Circulating cell-free DNA (ccfDNA) sequencing for low-burden cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), the abundance of genomic material within a plasma sample, and pre-analytical error rates due to library preparation, and sequencing errors. Sequencing costs have historically favored the development of deep targeted sequencing approaches for overcoming sparsity in ctDNA detection, but these techniques are limited by the abundance of ccfDNA in samples, which imposes a ceiling on the maximal depth of coverage in targeted panels. Whole genome sequencing (WGS) is an orthogonal approach to ctDNA detection that can overcome the low abundance of ccfDNA by supplanting sequencing depth with breadth, integrating signal across the entire tumor mutation landscape. However, the higher cost of WGS limits the practical depth of coverage and hinders broad adoption. Lower sequencing costs may thus allow for enhanced ctDNA cancer monitoring via WGS. We therefore applied emerging lower-cost WGS (Ultima Genomics, 1USD/Gb) to plasma samples at [~]120x coverage. Copy number and single nucleotide variation profiles were comparable between matched Ultima and Illumina datasets, and the deeper WGS coverage enabled ctDNA detection at the parts per million range. We further harnessed these lower sequencing costs to implement duplex error-corrected sequencing at the scale of the entire genome, demonstrating a [~]1,500x decrease in errors in the plasma of patient-derived xenograft mouse models, and error rates of [~]10-7 in patient plasma samples. We leveraged this highly de-noised plasma WGS to undertake cancer monitoring in the more challenging context of resectable melanoma without matched tumor sequencing. In this context, duplex-corrected WGS allowed us to harness known mutational signature patterns for disease monitoring without matched tumors, paving the way for de novo cancer monitoring.

genomics↗

bioRxiv2022

Global loss of fine-scale chromatin architecture and rebalancing of gene expression during early colorectal cancer development

Although 3D genome architecture can be essential for gene regulation, the biological implications of long-range chromatin interactions in disease remain elusive. In this study, we traced the early evolution and malignant transformation of colorectal cancer by generating high-resolution chromatin conformation maps of 33 colon samples spanning different stages of early neoplastic growth from polyps of Familial Adenomatous Polyposis (FAP) patients. Our analysis reveals a substantial progressive loss of genome-wide cis-regulatory connectivity at early stages of malignancy, which correlates with a non-linear effect on gene regulation. Genes with high promoter-enhancer (P-E) connectivity in unaffected mucosa are not correlated with elevated baseline expression, but instead tend to be up-regulated at advanced stages. Inhibition of highly connected promoters preferentially represses gene expression in colorectal cancer cells relative to normal colonic epithelial cells. Our results suggest a two-phase model whereby neoplastic transformation reduces P-E connectivity from a redundant state to a rate-limiting one for transcriptional levels. Overall, our study illuminates the intricate interplay between 3D genome architecture and gene regulation during early colorectal cancer progression, and provides valuable insights for potential therapeutic interventions targeting the connectivity of cis-regulatory elements.

genomics↗

bioRxiv2022

Cost-efficient whole genome-sequencing using novel mostly natural sequencing-by-synthesis chemistry and open fluidics platform

We introduce a massively parallel novel sequencing platform that combines an open flow cell design on a circular wafer with a large surface area and mostly natural nucleotides that allow optical end-point detection without reversible terminators. This platform enables sequencing billions of reads with longer read length ([~]300bp) and fast runs times (<20hrs) with high base accuracy (Q30 > 85%), at a low cost of $1/Gb. We establish system performance by whole-genome sequencing of the Genome-In-A-Bottle reference samples HG001-7, demonstrating high accuracy for SNPs (99.6%) and Indels in homopolymers up to length 10 (96.4%) across the vast majority (>98%) of the defined high-confidence regions of these samples. We demonstrate scalability of the whole-genome sequencing workflow by sequencing an additional 224 selected samples from the 1000 Genomes project achieving high concordance with reference data.

genomics↗

bioRxiv2022

Ultra high-throughput whole-genome methylation sequencing reveals trajectories in precancerous polyps to early colorectal adenocarcinoma

Aberrant shifts in DNA methylation have long been regarded as an early marker for cancer onset and progression. To chart DNA methylation changes that occur during the transformation from normal healthy colon tissue to malignant colorectal cancer (CRC), we collected over 50 samples from 15 familial adenomatous polyposis (FAP) and non-FAP colorectal cancer patients, and generated 30-70x whole-genome methylation sequencing (WGMS) runs via the novel Ultima Genomics ultra high-throughput sequencing platform. We observed changes in DNA methylation that occur early in the malignant transformation process, in gene promoters and in distal regulatory elements. Among these changes are events of hyper-methylation which are associated with a bivalent "poised" chromatin state at promoters and are CRC-specific. Distal enhancers show nonlinear dynamics, lose methylation in the progression from normal mucosa to dysplastic polyps but regain methylation in the adenocarcinoma state. Enhancers that gain chromatin accessibility in the adenocarcinoma state and are enriched with HOX transcription factor binding sites, a marker of developmental genes. This work demonstrates the feasibility of generating large high quality WGMS data using the Ultima Genomics platform and provides the first detailed view of methylation dynamics during CRC formation and progression in a model case.

genomics↗

bioRxiv2022

Single cell RNA-seq by mostly-natural sequencing by synthesis

Massively parallel single cell RNA-seq (scRNA-seq) for diverse applications, from cell atlases to functional screens, is increasingly limited by sequencing costs, and large-scale low-cost sequencing can open many additional applications, including patient diagnostics and drug screens. Here, we adapted and systematically benchmarked a newly developed, mostly-natural sequencing by synthesis method for scRNA-seq. We demonstrate successful application in four scRNA-seq case studies of different technical and biological types, including 5 and 3 scRNA-seq, human peripheral blood mononuclear cells from a single individual and in multiplex, as well as Perturb-Seq. Our data show comparable results to existing technology, including compatibility with state-of-the-art scRNA-seq libraries independent of the sequencing technology used - thus providing an enhanced cost-effective path for large scale scRNA-seq.

genomics↗