Creative Biolabs-Immuno-oncology

Single-cell Assays for Transposase-accessible Chromatin (scATAC-seq) Lineage Tracing Service

As a leader in the field of human oncology imaging development, Creative Biolabs has built a team of experienced scientists with facilities and processes designed specifically to provide the best-customized scATAC-seq lineage tracing services. We have established an advanced Tumor Single Cell lineage tracing technology platform that enables us to help build and establish a long-term vision with commercialization in mind.

Introduction to Single-cell ATAC (scATAC-seq) Sequencing

In Creative Biolabs, our staff have been exploring complex tumor cell tracing techniques based on transcriptome data for a long time. Over the past few decades, the inherent heterogeneity of samples and cell-to-cell differences in gene expression have prompted us to move from bulk cell assays to single-cell RNA sequencing for more accurately characterizing complex biological systems. However, the transcriptome data alone cannot reveal the full tumor cell fate. If you want to understand changes in gene expression patterns, determine heterogeneity within tumors, and identify tumor cell subpopulations that drive drug resistance, metastasis, and relapse in various tumor cells, then single-cell ATAC-seq (scATAC-seq) may be the ideal solution for you.

Our scATAC-seq platform has been considered a powerful tool for studying the physical structure of the genome by identifying open chromatin regions. Normally, our technique uses a highly active transposition enzyme that can cleave the region while inserting the sequencing linker. Our scATAC-seq data provides information on chromatin accessibility and reveals areas in a Tumor Single Cell where gene transcription is active.

Steps of single-cell ATAC-seq assays.1Fig.1 An ATAC-seq protocol.1

In addition, we can offer high-resolution scATAC-seq cell annotation analysis services. The open promoter region is generally used as a signal of transcriptional activity and is analyzed using a feature set specific to different tumor cell types. For example, a novel 10x Genomics scATAC-seq system has been developed for at least 10,000 bone marrow monocytes and CD34+ sorting cells analysis. Our scATAC-seq data can reveal the whole development process, from stem cells, B cells, and monocytes, to erythroid cells, and identify transcription factor motifs and enhancers that change in different differentiation states.

Features

Sample Delivery

scATAC-seq Lineage Tracing Services

Currently, single-cell ATAC-seq combined with single-cell RNA-seq has been broadly used for analyzing the regulatory sequences of all active transcripts in the genome. Based on microfluidic and barcode labeling technologies, Creative Biolabs can capture nearly 100,000 cells, obtain a large amount of epigenetic information, and map the chromatin accessibility of thousands of single cells.

In our labs, we attempted to capture mitochondrial DNA mutations from several tumor cells using the scATAC-seq system to evaluate tumor clonal heterogeneity through a series of lineage tracing analyses. we synthesized a multiplex cell label library containing approximately 30,000 unique barcodes for conducting large-scale lineage tracing testings. Labels were detected in 66% (RNA) and 46% (ATAC) of cells at mean MOI of 2.5 (RNA) and 3 (ATAC). Till now, we have successfully achieved simultaneous measurement of tumor cell lineage and cell fate. We found that somatic mutations in mitochondrial DNA can be used for reconstructing cell lineage relationships with high sensitivity and specificity at the single-cell level.

Service Process

With the commitment to being your best tumor lineage tracing partner, Creative Biolabs is capable of providing our clients with a variety of customized services in scATAC-seq lineage tracing analysis. Equipped with a team of professional scientists, we have won a good reputation among our worldwide customers for accomplishing numerous challenging projects in this field. If you are interested in our services, please contact us for more details. Let us know what you need and we will accommodate you. We look forward to working with you in the future.

Reference

  1. Chen, Huidong, et al. "Assessment of computational methods for the analysis of single-cell ATAC-seq data." Genome biology 20 (2019): 1-25. Distributed under Open Access license CC BY 4.0, without modification.

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