Biology subjects

Mulqueen, R. M.

Publications and source records attributed to Mulqueen, R. M..

5 recordsLinked to original sources

bioRxiv2023

txci-ATAC-seq, a massive-scale single-cell technique to profile chromatin accessibility

Measuring chromatin accessibility is a powerful method to identify cell types and states. Performed at single-cell resolution, this assay has generated catalogs of genome-wide DNA regulatory sites, whole-organism cell atlases, and dynamic chromatin reorganization through development. However, the limited throughput of current single-cell approaches poses a challenge for implementing proper study designs, population-scale profiling, and/or very deep profiling of complex samples. To this end, we developed a 10X-compatible combinatorial indexing ATAC sequencing ("txci-ATAC-seq"), which is a combinatorial indexing framework that initially indexes ("pre-indexes") chromatin within nuclei with barcoded transposases followed by encapsulation and further barcoding using a commercialized droplet-based microfluidics platform (10X Genomics). Leveraging this molecular hashing strategy, we demonstrate that txci-ATAC-seq enables the indexing of up to 200,000 nuclei across multiple samples in a single emulsion reaction, representing a [~]22-fold increase in throughput compared to the standard workflow at the same collision rate. To improve the efficiency of this new technique, we further developed a faster version of the protocol ("Fast-txci-ATAC-seq") that separates sample pre-processing from library generation and has the potential to profile up to 96 samples simultaneously. We initially benchmarked our assay by generating chromatin accessibility profiles for 230,018 cells from five native tissues across three experiments, including human cortex (28,513 cells), mouse brain (48,997 cells), human lung (15,799 cells), mouse lung (73,280 cells), and mouse liver (63,429 cells). We also applied our method to a club cell secretory protein knockout (CC16-/-) mouse model to examine the biological and technical limitations of the mouse line. By characterizing DNA regulatory landscapes in 76,498 wild-type and 77,638 CC16-/- murine lung nuclei, our investigations uncovered previously unappreciated residual genetic deviations from the reference strain that resulted from the method of gene targeting, which employed embryonic stem cells from the 129 strain. We found that these genetic remnants from the 129 strain led to profound cell-type-specific changes in chromatin accessibility in regulatory elements near a host of genes. Collectively, we defined single-cell chromatin signatures in 384,154 nuclei from 13 primary samples across different species, organs, biological replicates, and genetic backgrounds, establishing txci-ATAC-seq as a robust, high-quality, and highly multiplexable single-cell assay for large-scale chromatin studies.

genomics↗

bioRxiv2021

High-content single-cell combinatorial indexing

Single-cell genomics assays have emerged as a dominant platform for interrogating complex biological systems. Methods to capture various properties at the single-cell level typically suffer a tradeoff between cell count and information content, which is defined by the number of unique and usable reads acquired per cell. We and others have described workflows that utilize single-cell combinatorial indexing (sci)1, leveraging transposase-based library construction2 to assess a variety of genomic properties in high throughput; however, these techniques often produce sparse coverage for the property of interest. Here, we describe a novel adaptor-switching strategy, s3, capable of producing one-to-two order-of-magnitude improvements in usable reads obtained per cell for chromatin accessibility (s3-ATAC), whole genome sequencing (s3-WGS), and whole genome plus chromatin conformation (s3-GCC), while retaining the same high-throughput capabilities of predecessor sci technologies. We apply s3 to produce high-coverage single-cell ATAC-seq profiles of mouse brain and human cortex tissue; and whole genome and chromatin contact maps for two low-passage patient-derived cell lines from a primary pancreatic tumor.

genetics↗

bioRxiv2019

Spatially-mapped single-cell chromatin accessibility

High-throughput single-cell epigenomic assays can resolve the heterogeneity of cell types and states in complex tissues, however, spatial orientation within the network of interconnected cells is lost. Here, we present a novel method for highly scalable, spatially resolved, single-cell profiling of chromatin states. We use high-density multiregional sampling to perform single-cell combinatorial indexing on Microbiopsies Assigned to Positions for the Assay for Transposase Accessible Chromatin (sciMAP-ATAC) to produce single-cell data of an equivalent quality to non-spatially resolved single-cell ATAC-seq, where each cell is localized to a three-dimensional position within the tissue. A typical experiment comprises between 96 and 384 spatially mapped tissue positions, each producing 10s to over 100 individual single-cell ATAC-seq profiles, and a typical resolution of 214 cubic microns; with the ability to tune the resolution and cell throughput to suit each target application. We apply sciMAP-ATAC to the adult mouse primary somatosensory cortex, where we profile cortical lamination and demonstrate the ability to analyze data from a single tissue position or compare a single cell type in adjacent positions. We also profile the human primary visual cortex, where we produce spatial trajectories through the cortex. Finally, we characterize the spatially progressive nature of cerebral ischemic infarct in the mouse brain using a model of transient middle cerebral artery occlusion. We leverage the spatial information to identify novel and known transcription factor activities that vary by proximity to the ischemic infarction core with cell type specificity.

genetics↗

bioRxiv2019

Improved single-cell ATAC-seq reveals chromatin dynamics of in vitro corticogenesis

Development is a complex process that requires the precise modulation of regulatory gene networks controlled through dynamic changes in the epigenome. Single-cell-omic technologies provide an avenue for understanding the mechanisms of these processes by capturing the progression of epigenetic cell states during the course of cellular differentiation using in vitro or in vivo models1. However, current single-cell epigenomic methods are limited in the information garnered per individual cell, which in turn limits their ability to measure chromatin dynamics and state shifts. Single-cell combinatorial indexing (sci-) has been applied as a strategy for identifying single-cell-omic originating libraries and removes the necessity of single-cell, single-compartment chemistry2. Here, we report an improved sci-assay for transposase accessible chromatin by sequencing (ATAC-seq), which utilizes the small molecule inhibitor Pitstop 2 (scip-ATAC-seq)3. We demonstrate that these improvements, which theoretically could be applied to any in situ transposition method for single-cell library preparation, significantly increase the ability of transposase to enter the nucleus and generate highly complex single-cell libraries, without altering biological signal. We applied sci-ATAC-seq and scip-ATAC-seq to characterize the chromatin dynamics of developing forebrain-like organoids, an in vitro model of human corticogenesis4. Using these data, we characterized novel putative regulatory elements, compared the epigenome of the organoid model to human cortex data, generated a high-resolution pseudotemporal map of chromatin accessibility through differentiation, and measured epigenomic changes coinciding with a neurogenic fate decision point. Finally, we combined transcription factor motif accessibility with gene activity (GA) scores to directly observe the dynamics of complex regulatory programs that regulate neurogenesis through developmental pseudotime. Overall, scip-ATAC-seq increases information content per cell and bolsters the potential for future single-cell studies into complex developmental processes.

genomics↗

bioRxiv2017

Scalable and efficient single-cell DNA methylation sequencing by combinatorial indexing.

Here we present a novel method: single-cell combinatorial indexing for methylation analysis (sci-MET), which is the first highly scalable assay for whole genome methylation profiling of single cells. We use sci-MET to produce 2,697 total single-cell bisulfite sequencing libraries and achieve read alignment rates of 69 {+/-} 7%, comparable to those of bulk cell methods. As a proof of concept, we applied sci-MET to successfully deconvolve the cellular identity of a mixture of three human cell lines.

genomics↗