Poster
Overview
Single cell analysis is a critical approach to tease out nuanced information in any biological system. Combinatorial barcoding is an extremely efficient method for scRNA-seq at larger scale, achieving both sensitivity in gene detection and flexibility for sample input. However, this approach has historically been challenging when starting with small sample inputs of less than 100,000 cells. To address this, we have developed a modified combinatorial barcoding approach that allows researchers working with low sample inputs to fix, store, and barcode their cells efficiently without the need for costly or specialized instruments. This approach can be used to fix and profile up to 96 samples in parallel, results in a shorter workflow, and enables consistent handling which minimizes both experimental error and burden on scaling. As a proof-of-concept, we have generated a screen of 96-cell culture samples with input amounts starting at 10,000-20,000 cells. We present a method for fixing and isolating cells and nuclei at high capture efficiency (>65%). The capture efficiency remains high even at the lowest input values. This method maintains the stability of the fixed sample for extended storage at -80℃‚ and is compatible with the combinatorial barcoding process. The design of this workflow maximizes sample recovery while eliminating batch effects to provide accurate and comprehensive results on the transcriptional effect of experimental perturbations. This low-input fixation and capture method will be critical for the research community to expand their investigative scope to include precious samples at a larger scale, and to unlock new insights in biology for years to come.