Single Cell Genomic DNA Analysis

The genomic era makes it possible to measure high-throughput quantitative biological data. These technologies, ranging from fluorescence microscopy and polymerase chain reaction (PCR) to microarrays and sequencing, have successfully been applied to bulk samples containing many thousands of cells. The ability of single cells to resolve anatomical heterogeneity has become a powerful approach to study complex phenomena.

Fig.1 Timeline of Milestones in Single-Cell Sequencing. (Wang, 2015)

Single-Cell Genomic Technologies

• Microscopy-based methods

With the development of gene-encoded fluorescent proteins, cell imaging has undergone revolutionary changes, which makes it possible to analyze protein localization and transport in living cells at a single-cell level. For example, Livet et al. tagged neurons with a variety of different colored genes through random Cre/lox recombination of fluorescent proteins and were able to visualize hundreds of neighboring axons and synaptic contacts in the brains of transgenic mice.

Microscopy approaches are also used to directly observe nucleic acids. RNA fluorescent in situ hybridization (FISH) uses fluorescently tagged oligonucleotide probes to label mRNA molecules expressed in fixed cells. Topalidou et al. used single-cell mRNA counting to show that the gene alr-1 in Caenorhabditis elegans is important to control the cell-cell variability of the gene mec-3, a key regulator of neuronal differentiation of nematode touch receptor.

• Fluorescence-activated cell sorting (FACS)

FACS machines can process tens of thousands of cells per hour, measuring about 18 surface markers at a time. FACS has become a core technology tool in biomedicine especially in characterizing different types of cells in the blood and immune systems. Using DNA binding dyes, FACS can study the DNA content of single cells.

• Single-cell quantitative polymerase chain reaction

PCR has been used to amplify DNA and mRNA from single cells for purposes of genetic testing, immunology studies, and gene expression. Microfluidic chips can perform thousands of reactions in parallel on a single chip by mixing samples and gene detectors. Bontoux et al. used a similar microfluidic chip to profile single neuronal progenitors using on-chip RT followed by template-switching PCR (TS-PCR) amplification. Recently, White et al. designed a microfluidic device capable of performing single-cell capture, cell lysis, reverse transcription, and qPCR for hundreds of individual cells per run. Using this device, they were able to measure mRNA levels, and miRNA levels, and perform single nucleotide variant detection in thousands of single cells.

• Single-cell microarrays and RNA sequencing analysis

Microarrays enable the measurement of thousands of genes at once by hybridization of a fluorescently labeled biological sample to an array consisting of thousands of synthetic oligonucleotide probes.

• Single-cell genomic sequencing

Single-cell sequencing is useful not only to access the genomes of uncultivated organisms but also for comparing the genetic sequences of individual cells sequenced from a population.

Fig.2 Single-cell genome sequencing using microfluidics. (Paolillo, 2019)

Applications of Single-Cell Sequencing (SCS) in Neurobiology

Neurons represent one of the most morphologically diverse populations of cells. Traditional classification has relied mainly on morphological features; however, single-cell RNA sequencing provides a powerful unbiased approach to classify neurons based on their transcriptional profiles. In a study by Qiu et al., single neuron RNA sequencing was combined with electrophysiology to obtain transcriptional profiles from embryonic mouse hippocampus and neocortical neurons. In another study, single-cell RNA-seq was performed in situ in spatially defined neuronal regions, which identified cell-to-cell transcriptional variation in hippocampal neurons.

Several studies have also begun to investigate DNA heterogeneity in neurons. SCS was recently used to study LINE-1 retrotransposition in the cerebral cortex and found that each cortex neuron had an average of 0.6 somatic insertions events. In another study, SCS using microwells identified copy number changes in a normal postmortem brain and a patient with Down syndrome. These initial studies show that SCS provides a novel approach to classify neuronal cell types and identify an unexpected amount of DNA diversity in neuronal populations.

Genetic and phenotypic heterogeneity among cells is the rule, not the exception, in tissues and natural populations of microbes, and single-cell techniques are the most powerful methods for resolving such cell-to-cell variation. Creative Biolabs has a very strong technical force in the field of neuroscience research, focusing on single-cell level analysis in recent years. We can develop customized single-cell genomic methods for customer’s neuroscience research projects to make the greatest breakthrough in your project. Contact us for more information.

References

1. Wang, Y.; Navin, N.E. Advances and applications of single-cell sequencing technologies. Mol Cell. 2015 May 21;58(4): 598-609.
2. Paolillo, C.; Single-Cell Genomics. Clin Chem. 2019 Aug;65(8): 972-985.