Advantages and Limitations of Single Cell -Omics
The use of single-cell genomics has significantly improved our ability to dissect cellular heterogeneity and enabled a better understanding of mechanisms behind drug resistance, the clonal structure of tissues, and the evolutionary trajectory of normal cells to diseased states. Since both genomic and transcriptional changes contribute to disease pathology, these features need to be combined. However, the integration of multiple high throughput technologies, or single-cell “multi-omics,” has been challenging.
In recent years, several technologies have become readily available for single-cell DNA and RNA sequencing simultaneously, but they can be plagued by significant limitations. These technologies, grouped under the umbrella of single-cell whole genome and RNA sequencing (scWGS/RNAseq), are technically demanding, time-consuming, and either require fresh tissue or cell samples or suffer from reduced sensitivity when employed on frozen tissues. However, since frozen bio-banked tissues are the most readily available source of biological material, the requirement of fresh tissues for high sensitivity is a significant drawback of current scWGS-RNAseq multi-omic technologies.
In a recent paper published in Science Advances, Yu et. al. introduced a new scWGS-RNAseq technique called scONE-seq. scONE-seq is a novel technique that paves the way for multi-omics on biobank tissues without compromising sensitivity or accuracy.
What is scONE-seq?
In scONE-seq, single cells or nuclei from frozen biobanked tissues are sorted into PCR plates and lysed. The DNA from lysed cells is fragmented in a process called segmentation, which introduces a “DNA barcode” or tag and a unique molecular identifier (UMI) to all DNA fragments. Meanwhile, the mRNA undergoes cDNA conversion using primers that add an “RNA barcode” and UMIs. Subsequently, the DNA and RNA undergo amplification cycles in the same reaction mixture to produce sequencing libraries. Unlike other scWGS-RNAseq multi-omic technologies, scONE-seq is less technically challenging, and therefore scalable due to this combined workflow for library construction.
Benchmarking of scONE-seq against scRNAseq (Smart-Seq and 10X Genomics), as well as pseudo-bulk WGS techniques, demonstrated its ability to capture copy number variations (CNV’s) and transcriptional changes in cells, without compromising on accuracy or sensitivity. The cross-contamination of DNA and RNA barcodes was minimal and the RNA-seq component displayed a high correlation in gene expression with whole-cell techniques.
Importantly, scONE-seq data was able to classify distinct cell types within a population of cells clustered based on their transcriptional profile alone by incorporating their CNV status. Using this extra layer of information, the authors were able to classify unique tumor clones in biobank astrocytoma tumors that were otherwise considered normal based on their transcriptomic phenotype. This demonstrates the superiority of scONEseq multi-omics approach in cancer studies which permits capturing of important layers of tumor heterogeneity, that are otherwise undetected by scRNA-seq alone. The ability to accurately and sensitively sequence biobank tissues will allow for a flood of useful new data to inform disease research.
Outsourcing Bioinformatics Analysis: How Bridge Informatics Can Help
Many of our clients at Bridge Informatics are at the cutting edge of research, applying novel bioinformatics tools to tackle their research questions. From pipeline development and software engineering to deploying existing bioinformatics tools, Bridge Informatics can help you on every step of your research journey.
As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing, and interpreting genomic and transcriptomic data. Bridge Informatics’ bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. Click here to schedule a free introductory call with a member of our team.
Outsourcing Biobanking: How Sampled Can Help
Sampled is a company that offers custom biobanking services, which are becoming increasingly important in the field of bioinformatics. As research becomes more advanced, the need for storing, managing, analyzing, researching, and transporting biological samples becomes more pressing. Sampled’s team of experts deals with many data types and works with leading sequencing platforms. This allows them to provide the best service possible and help our clients stay at the cutting edge of research. If you have a sample, Sampled SMART Labs are here to Store it, Manage it, Analyze it, Research it, and Transport it. If you’d like to learn more, please contact Dennis Young at [email protected].
Haider M. Hassan, Data Scientist, Bridge Informatics
Haider is one of our premier data scientists. He provides bioinformatic services to clients, including high throughput sequencing, data pre-processing, analysis, and custom pipeline development. Drawing on his rich experience with a variety of high-throughput sequencing technologies, Haider analyzes transcriptional (spatial and single-cell), epigenetic, and genetic landscapes.
Before joining Bridge Informatics, Haider was a Postdoctoral Associate at the London Regional Cancer Centre in Ontario, Canada. During his postdoc, he investigated the epigenetics of late-onset liver cancer using murine and human models. Haider holds a Ph.D. in biochemistry from Western University, where he studied the molecular mechanisms behind oncogenesis. Haider still lives in Ontario and enjoys spending his spare time visiting local parks. If you’re interested in reaching out, please email [email protected] or [email protected]