Understanding the Popularity of Single Cell RNA-seq Analysis
Single cell RNA sequencing, or scRNA-seq, has recently gained popularity as a to-go technique for studying gene expression at the single cell level. This method allows researchers to capture the complexity of multicellular organisms, providing valuable insights into the full heterogeneity of biological samples.
In contrast, traditional bulk RNA sequencing, or RNA-seq, is a widespread technique used to study gene expression by averaging transcript levels across all cells within a sample. While bulk RNA-seq provides useful snapshots of information, it can mask important biological differences between individual cells. Here, we’ll discuss some of the key benefits of using single cell RNA-seq (over bulk RNA-seq) that have contributed to its popularity.
Single Cell vs Bulk RNA-seq Analysis
Four Key Advantages of scRNA-seq over bulk RNA-seq:
- It captures cellular heterogeneity: Living organisms are composed of billions, if not trillions, of individual cells grouped in functional organs. Within each organ different cell types perform precise tasks that are defined by their transcriptional profile. With scRNA-Seq, researchers have the opportunity to profile this complexity and describe cellular pathways with previously unseen resolution.
- Rare cell populations can be isolated: At the correct granularity, scRNA-seq allows researchers to capture the status of rare cell populations, providing details that would not be possible to see using bulk RNA-seq.
- It captures cell-to-cell communication networks: Paracrine signaling allows cells to “talk” to each other via ligand-receptor signaling. By using scRNA-seq, researchers can identify the intracellular and paracrine pathways that allow cells to influence their environment, and consequently, cellular and organ phenotypes.
- Spatial transcriptomics is one of the newest and most exciting applications of scRNASeq analyses. The goal of spatial transcriptomics is to study the geographical organization of cells within a tissue, which is critical for understanding its function. For example, the organization of cells within the developing brain is essential for establishing proper neural connections.
Single cell RNA-seq is a powerful and increasingly popular technique for studying gene expression at the single cell level. By providing valuable insights into cellular heterogeneity, rare cell populations, spatial organization, and the effects of any disruptions to these systems, scRNA-seq can help researchers to better understand biological processes and describe cellular functions in health and disease.
Outsourcing Bioinformatics Analysis: How We Can Help
The applications of RNA-seq technologies are innumerable, and our clients are at the forefront of tackling these research questions with sophisticated bioinformatics approaches. However, choosing which methods to use and analyzing the resulting data is no small challenge.
As experts across data types from cutting-edge 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.
Dan Ryder, MPH, PhD
Dan is the founder and CEO of Bridge Informatics, a professional services firm helping pharmaceutical companies translate genomic data into medicine. Unlike any other data analytics firm, Bridge forges sustainable communication change between their client’s biological and computational scientists. Dan is particularly passionate about improving communication between people of different scientific backgrounds, enabling bioinformaticians and software engineers to collectively succeed.
Prior to forming Bridge Informatics, Dan served in a variety of roles helping pharmaceutical clients solve early phase drug discovery and development challenges.
Dan received both a PhD in Biochemistry and Molecular Biology and an MPH in Disease Control from the University of Texas Health Science Center at Houston (UTHealth Houston). He completed his postdoctoral studies in Molecular Pathways of Energy Metabolism at the University of Florida College of Medicine. Dan received his undergraduate degree in Microbiology from the University of Texas at Austin.
