Beginner’s Guide to Single Cell RNA Sequencing: Wet Lab Essentials for Success 12.01.20265’ Single cell sequencing Single cell RNA sequencing (scRNA) is revolutionizing biology by allowing scientists to study gene expression at the level of individual cells. By analyzing gene expression at the level of individual cells, researchers can uncover hidden cell types, track how cells behave in disease, and explore complex tissues with unprecedented resolution.If you’re new to scRNA-seq, the wet lab might seem overwhelming. But don’t worry, this guide walks you through each step, from sample preparation to quality control, with practical tips from experienced scientists to help you succeed.If you’re most worried about data analysis, we also got that covered. Learn more on our upcoming bioinformatics course here.What Is scRNA Used For?scRNA is widely applied across oncology, immunology, developmental biology, and drug discovery. It enables researchers to identify novel cell types, map dynamic cell states, and understand disease mechanisms at a cellular level.Applications of scRNA:OncologyTumor vasculature at single-cell resolution – Nature, 10 July 2024Oncology/ImmunologyNeoadjuvant PARPi or chemotherapy in ovarian cancer informs targeting effector Treg cells for homologous-recombination-deficient tumors – Cell, 05 September 2024Aging/Reporductive healthSpatio-temporal landscape of mouse epididymal cells and specific mitochondria-rich segments defined by large-scale single-cell RNA-seq – Cell Discovery, 18 May 2021Machine learning in infectious diseasesRAIN: machine learning-based identification for HIV-1 bNAbs – Nature Communications, 24 June 2024More than just humans & miceA single-cell resolved genotype-phenotype map using genome-wide genetic and environmental perturbations – Nature Communications, 18 March 2025Sample Quality: The Foundation of Meaningful DataNo matter if you work with cell lines, organoids or tissues, the quality of your sample directly affects the quality of your data. Damaged, dead, or stressed cells can release RNA, which may skew your results and mask true biology. That’s why it’s critical to start with intact, viable cells.Sample Input RequirementsGood cell yield High viability ≥85%Low debrisSingle cell suspensions in PBSWhenever possible, process fresh samples quickly. If storage is unavoidable, use validated preservation techniques that maintain viability of all cell types, preserve transcriptional states and simultaneously minimize RNA degradation. Preservation buffers mimick physiological conditions for ~ 72h at 4°C. Use validated cryopreservation protocols tailored to your sample type.If you’re working with tissues, effective and gentle dissociation is essential to obtain clean, viable single cell suspensions. Check out our dedicated post on tissue dissociation. And if your samples are already flash-frozen, don’t worry, you may be able to switch to single nucleus RNA sequencing (snRNA).Choosing Between Single Cell and Single Nucleus RNA SequencingNot all samples are suitable for scRNA. Some tissues are difficult to dissociate, and others, such as frozen samples may no longer contain viable cells. In these cases, snRNA offers a powerful alternative by analyzing nuclear RNA instead of total cellular transcripts. Here is how the two methods compare: Choosing between these methods depends on your sample type and research goals. If you’re unsure, our team can help you evaluate the best approach.Further reading:Application Note scRNA-seq VS snRNA-seqPlanning Your Experiment: Cells, Replicates, and ControlsDesigning your experiment thoughtfully is just as important as the technical steps. The number of cells you sequence and the number of replicates you include will depend on your scientific question and budget. Generally, sequencing more cells increases resolution and statistical power. But it also raises costs. Equally important is including biological replicates to ensure your findings are reproducible and using appropriate controls to validate your results.Experimental Design Guidelines:Global transcriptome profiling: 3,000-10,000 cells/sample Detection of rare populations: 20,000+ cells/sample or consider enrichment of target cells3+ replicates per group recommendedInclude untreated, baseline, wild-type or healthy control groupsFurther reading Technical NoteStatistical power for single cell analysis More infoQuality Control: A Critical Step You Can’t SkipOnce you have prepared your single-cell suspension, the scRNA workflow begins: Cells are isolated, lysed and their mRNA is captured by polyA-selection and reverse transcribed into cDNA. mRNA is then reverse-transcribed into cDNA, which is amplified, purified and used to construct a sequencing library.Before moving forward with sequencing, it is essential to verify that your cDNA and libraries meet quality standards. Performing quality control at each step is not just best practice, it is a crucial step that can save you time, resources, and the frustration of failed sequencing runs.To ensure accurate quantification, fluorometric assays are recommended for both cDNA and library measurements. These assays provide reliable concentration data, which is critical for downstream steps. Additionally, capillary electrophoresis offers valuable insights into fragment size distribution, helping you assess the complexity and integrity of your samples.cDNA Quality Checks Main peak sizeExpect the largest cDNA peak around 1.5–2 kb, reflecting the majority of transcripts. Keep in mind that not every tissue looks the same; highly expressed transcripts in some tissues can produce unique peaks. Sample complexityA broader range of fragment sizes usually indicates a diverse sample. Very narrow peaks could suggest loss of complexity. YieldEnsure you have enough cDNA for downstream library prep. Typical yields vary by sample and number of input cells. Extremely low yield can indicate poor capture, RNA degradation, or issues during processing Primer artifactsAvoid peaks <150 bp, which usually represent leftover primers or adapter dimers. Signs of degradationA gradual increase of small fragments can indicate RNA degradation.Library Quality ChecksMain peak sizeMost libraries show a bell-shaped curve around 400-700 bp, reflecting proper amplification and diversity.YieldShould be sufficient to show that PCR amplification worked efficiently. Extremely low yield may indicate issues with input or amplification; very high yield can reflect over‑amplification, which may reduce library complexity.Primer artifactsAvoid fragments <150 bp, which usually indicate leftover primers or adapter dimers.Final Thoughts: Your Path to scRNA SuccessscRNA is an incredibly powerful tool that opens up new dimensions in biological discovery. With the right preparation and attention to detail, your first experiment will yield high-quality, insightful data that drives your research forward. Start by working with high-quality, well-preserved samples. Choose between scRNA and snRNA based on your sample type and research goals. Design your experiment with replicates and controls in mind and always verify cDNA and library quality before sequencing.By following these best practices, you are setting yourself up for a smooth and successful journey into single cell transcriptomics. With each step carefully planned and executed, you will be well on your way to generating impactful, publication-ready data.Success Checklist:Start with high-quality samplesChoose scRNA vs. snRNA based on your sample and research questionsPrepare clean single cell or nuclei suspensionInclude replicates and proper controlsConfirm cDNA and library quality before proceedingNeed Help Planning Your scRNA Experiment?Whether you’re comparing technologies, optimizing tissue prep, designing your experiment or interpreting fragment distributions, our team is here to support you every step of the way.Book a Free Consultation! A post by Melanie DostertMelanie Dostert, Ph.D. is a microbiologist specializing in biofilm-associated antibiotic resistance. She completed her doctorate at the University of British Columbia and has conducted research at the Max Planck Institute for Dynamics of Complex Technical Systems. Her work bridges microbiology, systems biology, and clinical applications, with a growing interest in single-cell technologies. Melanie is part of the Singleron team in Cologne, where she works as an Application Scientist.Check out our latest blog posts Learn more 25.07.08 What is Single Cell RNA Sequencing? The basics of single-cell RNA sequencing As biologists, we know biology is anything but uniform. Every tissue is a mosaic of diverse cell types, each… Read more 25.02.25 Dissecting Tumor–Microbiome Interactions: Introducing FocuSCOPE 16S for Single Cell Insight Intracellular bacteria are known to influence the development, progression, and treatment of cancer. However, studying these microbes in the tumour microenvironment has been challenging. Bulk… Read more 23.04.03 Linking two worlds: RNA and protein at single cell resolution High-throughput single cell analysis lets researchers see the functions of complex biological systems. Detecting key proteins at the cell surface together with gene expression adds an additional layer oinformation. Read more nuclei isolationsingle cell analysissingle cell sequencingsingle nucleus sequencing
25.07.08 What is Single Cell RNA Sequencing? The basics of single-cell RNA sequencing As biologists, we know biology is anything but uniform. Every tissue is a mosaic of diverse cell types, each… Read more
25.02.25 Dissecting Tumor–Microbiome Interactions: Introducing FocuSCOPE 16S for Single Cell Insight Intracellular bacteria are known to influence the development, progression, and treatment of cancer. However, studying these microbes in the tumour microenvironment has been challenging. Bulk… Read more
23.04.03 Linking two worlds: RNA and protein at single cell resolution High-throughput single cell analysis lets researchers see the functions of complex biological systems. Detecting key proteins at the cell surface together with gene expression adds an additional layer oinformation. Read more