Using Single-Cell Westerns to Validate Single-Cell RNA Sequencing Data
Single-cell gene expression analysis of heterogeneous cell populations such as those contributing to cancer and the immune response has begun to revolutionize our understanding of biology. The increased resolution provided by single-cell technologies allows researchers to identify rare cell subpopulations that play a key role in disease and profile variation in response to treatment across heterogeneous patient samples.
Single-cell RNA sequencing (RNA-Seq) allows researchers to measure transcript levels in thousands of individual cells in a single assay to measure RNA expression heterogeneity. However, cellular mRNA transcript levels do not always directly correlate with levels of functional protein. In fact, mRNA and protein levels can vary significantly due to translational and post-translational regulation. MicroRNAs can modulate gene expression by inhibiting translation of mRNA. Proteins may also be rapidly degraded after they are translated via proteases and the proteasome. Studies have demonstrated that only about 40% of cellular protein levels are directly proportional to mRNA concentration. It is therefore vital to validate any single-cell RNA expression studies with single-cell protein expression data to ensure accurate and complete conclusions about cellular function.
In this application note, learn how Milo was used in parallel with a single-cell RNA-Seq workflow at the Stanford Functional Genomics Facility to validate single-cell RNA expression studies with single-cell protein expression data and ensure accurate and complete conclusions about cellular function. Because it uses the large Western catalog of antibodies & can easily measure intracellular proteins, Milo is the only platform with the versatility to detect diverse targets that are discovered in a sequencing run.