Single-cell sequencing examines the nucleic acid sequence information from individual cells with optimized next-generation sequencing technologies, providing a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment. For example, in cancer, sequencing the DNA of individual cells can give information about mutations carried by small populations of cells. In development, sequencing the RNAs expressed by individual cells can give insight into the existence and behavior of different cell types. In microbial systems, a population of the same species can appear genetically clonal. Still, single-cell sequencing of RNA or epigenetic modifications can reveal cell-to-cell variability that may help populations rapidly adapt to survive in changing environments.

A typical human cell consists of about 2 x 3.3 billion base pairs of DNA and 600 million mRNA bases. Usually, a mix of millions of cells is used in sequencing the DNA or RNA using traditional methods like Sanger sequencing or next generation sequencing. By deep sequencing of DNA and RNA from a single cell, cellular functions can be investigated extensively. Like typical next-generation sequencing experiments, single-cell sequencing protocols generally contain the following steps: isolation of a single cell, nucleic acid extraction and amplification, sequencing library preparation, sequencing, and bioinformatic data analysis. It is more challenging to perform single-cell sequencing than sequencing from cells in bulk. The minimal amount of starting materials from a single cell makes degradation, sample loss, and contamination exert pronounced effects on the quality of sequencing data. In addition, due to the picogram level of the number of nucleic acids used, heavy amplification is often needed during sample preparation of single-cell sequencing, resulting in uneven coverage, noise, and inaccurate quantification of sequencing data.

Recent technical improvements make single-cell sequencing a promising tool for approaching a set of seemingly inaccessible problems. For example, heterogeneous samples, rare cell types, cell lineage relationships, mosaicism of somatic tissues, analyses of microbes that cannot be cultured, and disease evolution can all be elucidated through single-cell sequencing. Single-cell sequencing was selected as the method of the year 2013 by Nature Publishing Group.

Single-cell DNA genome sequencing involves isolating a single cell, amplifying the whole genome or region of interest, constructing sequencing libraries, and then applying next-generation DNA sequencing (for example Illumina, Ion Torrent). Single-cell DNA sequencing has been widely applied in mammalian systems to study normal physiology and disease. Single-cell resolution can uncover the roles of genetic mosaicism or intra-tumor genetic heterogeneity in cancer development or treatment response. In the context of microbiomes, a genome from a single unicellular organism is referred to as a single amplified genome (SAG). Advancements in single-cell DNA sequencing have enabled collecting of genomic data from uncultivated prokaryotic species present in complex microbiomes.  Although SAGs are characterized by low completeness and significant bias, recent computational advances have achieved the assembly of near-complete genomes from composite SAGs. Data obtained from microorganisms might establish processes for culturing in the future. Some of the genome assembly tools used in single cell single-cell sequencing include SPAdes, IDBA-UD, Cortex, and HyDA.

A list of more than 100 different single-cell omics methods has been published.

Multiple displacement amplification (MDA) is a widely used technique, enabling amplifying femtograms of DNA from bacterium to micrograms for sequencing. Reagents required for MDA reactions include: random primers and DNA polymerase from bacteriophage phi29. In 30 degree isothermal reaction, DNA is amplified with included reagents. As the polymerases manufacture new strands, a strand displacement reaction takes place, synthesizing multiple copies from each template DNA. At the same time, the strands that were extended antecedently will be displaced. MDA products result in a length of about 12 kb and ranges up to around 100 kb, enabling its use in DNA sequencing. In 2017, a major improvement to this technique, called WGA-X, was introduced by taking advantage of a thermostable mutant of the phi29 polymerase, leading to better genome recovery from individual cells, in particular those with high G+C content. MDA has also been implemented in a microfluidic droplet-based system to achieve a highly parallelized single-cell whole genome amplification. By encapsulating single-cells in droplets for DNA capture and amplification, this method offers reduced bias and enhanced throughput compared to conventional MDA.

Another common method is MALBAC. As done in MDA, this method begins with isothermal amplification, but the primers are flanked with a "common" sequence for downstream PCR amplification. As the preliminary amplicons are generated, the common sequence promotes self-ligation and the formation of "loops" to prevent further amplification. In contrast with MDA, the highly branched DNA network is not formed. Instead, the loops are denatured in another temperature cycle allowing the fragments to be amplified with PCR. MALBAC has also been implemented in a microfluidic device, but the amplification performance was not significantly improved by encapsulation in nanoliter droplets.

Comparing MDA and MALBAC, MDA results in better genome coverage, but MALBAC provides more even coverage across the genome. MDA could be more effective for identifying SNPs, whereas MALBAC is preferred for detecting copy number variants. While performing MDA with a microfluidic device markedly reduces bias and contamination, the chemistry involved in MALBAC does not demonstrate the same potential for improved efficiency.