Each typical human cell contains about 6 billion base pairs of DNA, known as the genome. This genome is expressed differently in each human cell. Different levels of gene expression give each cell its specific characteristics and function through the production of different proteins. The expression of genes can be measured by analyzing the RNA, molecules that are transcribed from the DNA and convey genetic information to the ribosome. This is where protein production takes place.
To understand and analyze the regulation of gene expression patterns, we use quantitative RNA sequencing. To determine expression levels, in traditional sequencing methods a mix of millions of cells is used. But because that information is pooled, it lacks a high enough resolution to draw conclusions about individual cells.
Using single-cell sequencing, we can investigate the expression patterns of independent cells by examining their own sequence information. This provides a higher resolution. Also, by pooling this information from multiple independent cells, we can understand the function of cells within their context. For instance, by sequencing single cells from a tumor, we can assess the heterogeneity of the cancer. In a larger scale, we could make an atlas of all common and rare cell types, encompassing information about their expression profiles and their abundance within an organ. One of the projects contributing to this is the Human Cell Atlas (link). This way, single cell analysis could lead to a better understanding of human health, diagnosing and monitoring, and the development of personalized treatments.
At the Hubrecht Institute, we conduct single-cell sequencing by sorting individual cells in wells of a 384-well plate and lysing (breaking) them, so the RNA and DNA are released. Each single well contains a different barcode primer that binds to the RNA. This way, when the material is pooled afterwards, we can still trace it back to each original cell. Subsequently, the transcriptome material is processed using the SORTseq protocol [link Hashimshony et al., 2016]. After evaluation, we send the resulting transcriptome libraries out for sequencing to the Utrecht Sequencing Facility (USF, www.useq.nl). Once they return the data, we can map them against the reference transcriptome to determine which transcripts were present in the cell. The resulting data is then ready for in-depth analysis.
As a response to the growing demand for single cell sequencing projects, in July 2016, the Single Cell Facility [link naar tekst hieronder] at the Hubrecht Institute was founded. This facility enables labs within and outside of the Hubrecht Institute that lack the know-how and equipment to support their research with single cell transcriptome data.
The Single Cell Sequencing Facility uses the SORTseq pipeline. In this pipeline, single cells are sorted into 384 well plates that contain barcoded CELseq2 primers. These plates are provided by the facility. The FACS sort has to be arranged by the client. Besides the plates, preferably some bulk samples (for example 500-1000 cells) are sorted for a RNA-quality check. The plates and bulk samples are returned to the facility, where the plates are processed using the CELseq2 protocol [link Hashimshony et al., 2016].
The processing and sequencing take quite some time, and it is expected that after returning the plates to the facility, it will take at least 2 months until the data returns. Every 384 plate single cell experiment costs approximately €1000 (excluding VAT). Sequencing costs and reagents are included in this price.
When you want to make use of the facility, please contact Judith Vivié via j.vivie[at]hubrecht.eu to make an appointment.