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A list of single cell sequencing applications and research results (Part One)

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A list of single cell sequencing applications and research results (Part One)

Here is a list of researches related to single cell sequencing:
1. Cell: topographic single-cell sequencing technology to help reveal the mystery of early breast cancer invasiveness
In a new study, researchers from the University of Texas MD Anderson Cancer Center reported that a new genetic model may explain how a common early stage breast progresses to more invasive breast cancer, ductal carcinoma in situ (DCIS or DCI). The relevant research results were published online in the Cell Journal on January 4, 2018, and the title of the paper is "Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing."
This study provides new insights into how DCI progresses to invasive ductal carcinoma (IDC) and provides a clearer understanding of why some of these cancers have not been detected. This discovery was achieved thanks to the researchers developing a new analytical method called topographic single cell sequencing (TSCS).
Dr. Nicholas Navin, associate professor of genetics at the MD Anderson Cancer Center at the University of Texas, said that although DCIS is the most common form of early breast cancer and can often be detected by mammography, 10% of this cancer up to 30% will progress to IDC. Given the technical challenges of organizational analysis, how DCIS accurately produces invasiveness is still not well understood in the genome."
[Original doi:10.1016/j.cell.2017.12.007]
2. Cell: Identification of olfactory neuron types using single-cell RNA sequencing
The human nervous system is like a complex circuit board. Diseases such as schizophrenia or bipolar disorder can occur when the wires cross or the circuit fails.
Scientists have long struggled to identify how brain circuits are formed so that they can understand the reconnection of neurons in question.
Now, in a new study, Liqun Luo, a professor of biology at Stanford University, and Stephen Quake, a professor of bioengineering and applied physics at the University of Stanford, and his team, constructed a detailed genetic blueprint for Drosophila olfactory neurons on a cell-by-cell basis, which is an important step in this direction. The results of the study were published in the November 16, 2017 issue of Cell, entitled "Classifying Drosophila Olfactory Projection Neuron Subtypes by Single-Cell RNA Sequencing."
The underlying idea of ​​this research is to understand the relatively simple types of neurons in the Drosophila brain and to identify molecules that direct the formation of connections between different types of neurons in the Drosophila brain. Over time, people want to use a similar approach to study the much more complex cell composition in the human brain, and may even one day fix the wrong connections in brain diseases.
[Original doi:10.1016/j.cell.2017.10.019]
3. How to make single cell sequencing simple?
Single-cell biology research has been a hot topic today, and the most advanced area is single-cell RNA sequencing (scRNA-seq). Conventional RNA sequencing methods can process and sequence tens of thousands of cells at a time, and give average differences, but no two cells are exactly the same, and the new scRNA-seq method can reveal each of them. Small changes in specificity, even this technique can clarify the complete new cell type.
For example, when Aviv Regev and others from the Baldur Institute used scRNA-seq to probe 2400 immune system cells, they inadvertently discovered some dendritic cells with potential T cell activation activity, Regev said. A vaccine that stimulates these cells or can potentially enhance the body's immune system and protect the body against cancer. Of course, these findings are hard-won. It is difficult for researchers to operate on single cells compared to a large number of cells, because each cell produces only a small amount of RNA, leaving no room for researchers to make mistakes. Another problem is how to analyze large amounts of data, and most importantly, the tools used by researchers may not be intuitive.
4. Cell Res: Chinese scientists publish the latest research results of single-cell super-spectral sequencing technology
On June 16, 2017, Tang Fufu, a biodynamic optical imaging center of the School of Life Sciences, Peking University, published a study entitled "Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells" in Cell Research. Internationally, it has pioneered the development of a single-cell simultaneous chromatin state, DNA methylation, genomic copy number variation, and ploidy genome-wide sequencing technology (single-cell COOL-seq), and the use of this technology Single-cell resolution systematically and in-depth analysis of the key features of epigenome reprogramming during mouse preimplantation embryo development, and the interaction between chromatin status and DNA methylation.
Existing research methods based on high-throughput sequencing to analyze whole-genome chromatin status typically require large numbers of cells (eg, ATAC-seq, DNase-seq, FAIRE-seq, MNase-seq, etc.). Even if these methods can achieve single-cell resolution, it is impossible to study the interaction between multiple omics at single-cell resolution. The Tang Fuhui team skillfully combined NOMe-seq (full genome nucleosome localization and whole genome DNA methylation sequencing) technology with PBAT-seq technology (whole genome bisulfite sequencing, WGBS) and performed the system. The optimization and improvement of the genomic and epigenome features of up to five levels of the same single cell was achieved.
To be continued in Part Two…

 


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