Single-cell genome sequencing: Challenges and applications

Mike Yee

High-throughput sequencing has contributed to the identification of new species and efforts in understanding disease factors, such as mosquito vectors. But as described by Dr. Stephen Quake, it is a rather “bulk tissue analysis.” In contrast, applications of single-cell genome sequencing are nearing breakthroughs in biomedical research. There is another level of diversity and complexity—as demonstrated by variations on the cellular level between individual cells—and that is where single-cell genome sequencing comes in, allowing for the analysis of the genome on an individual cell-to-cell basis.

But what are the challenges of single-cell genome sequencing, and how do advancements in this area provide new insights? This article addresses these obstacles and research directions. There are four major factors and challenges to consider:

  1. Isolation of DNA from a single cell can be done via laser-capture microdissection, fluorescence-activated cell sorting (FACS), or other methods.
  2. The genome for that single cell has to be amplified to have enough material to analyze. The main techniques for whole-genome amplification (WGA) include pure PCR-based, isothermal, and mixed methods of amplification.
  3. The method of querying such data sets. Do you query specific loci < 1 Mb (megabase) long, protein-coding regions 30-60 Mb, or entire genome of 3 Gb (gigabases)?
  4. The development of tools to analyze such data sets for biases and errors, and determination of true variants involves analyses of copy number variants (CNV) or single nucleotide variants (SNV).

Those are technical challenges being addressed, where new approaches are introduced for continual improvement. But what about the applications? Interesting applications of single-cell genome sequencing are discussed in this article. These include microbial dark matter, identification of new phyla and viruses, mosaicism within multicellular organisms, and cancer. Another application for single-cell genome sequencing is the study of human mosaicism, where SNVs and mutations may accumulate over time, as with aging and so many rounds of cell division.

The Human Cell Atlas project is another large-scale, ambitious project with potential applications for single-cell genome sequencing. Dr. Chris Walsh is also using this method to understand neurogenesis and diverse mutations found in different neurons in the human brain. Dr. Wolf Reik and his lab are finding ways to set up experiments using single-cell genome sequencing in combination with other techniques, such as RNA sequencing, to analyze topics in embryology, aging, and epigenetics. Furthermore, they are considering using this technique to analyze live cells over time. How fascinating and how much data could be had from such experiments? Thus, we return to the aforementioned major challenges—requiring even newer, improved tools to analyze even bigger data sets—and further development ensues.

Single-cell genome sequencing is a powerful technique that allows us to understand organisms, diseases, and individual cells with greater resolution. With each cell having its own characteristics, perhaps they can all be assigned unique profiles—similar to Facebook, LinkedIn, or (dare I say?) Tinder. Tinder for cell genomes: That might be a fun way of engaging and learning about developments in single-cell biology! Does this cell interest you? Swipe right. Would you rather move on to other single cells in your area? Just swipe left!

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Mike has a Ph.D. in Biomedical Sciences from the University of California, Riverside, a M.S. in Cell and Molecular Biology from San Francisco State University, and a B.A. in English from the University of California, Berkeley.

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