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New shuffling trick, researchers can measure gene activity in a single cells


Biologist have said that single cells have a mind of their own, they can decide to be part of a tissue, or take another more interesting route towards a disease to fight. Although that is all interesting, scientists are still trying to figure out, exactly how many different types of cells are in tissues. Researchers from University of Washington and Allen Institute for brain Science, have developed a method that can classify and track the many cells in a simple tissue sample.
Just a few short weeks ago, a journal article posted about this method called “SPLIT-seq” this reliably tracts gene activity in a level of single cells. (Urton, James)
SPLIT-seq translates to meaning, “Split Pool Ligation-based Transcriptome Sequencing”. (Urton, James) This has a traditional approach with adding a bit of flare, or new twist. According to author Greg Seelig, “Cells differ from each other based on the activity of their genes”. You could think of this as genes either switching on or switching off.  Gene expression has been measured in tissues by the old fashioned way of sequencing letters of RNA to the DNA molecule, which is the first step of gene expression. (Urton, James) Another approach is called RNA-sequencing, this profiles RNA across the whole tissue. Unfortunately, these approaches do not help the researchers know how many cells are within the tissue, and if they differ from one another. It can be done as stated in the article, but it is very costly, and does not scale well.
            SPLIT-seq is able to perform single cell RNA-sequencing without isolating individual cells. These cells go through four rounds of “shuffling” which means they are getting split into separate pools and then mixing them back together. At each shifting stage they do label the RNA in each pool with its own DNA barcode. The end of the four rounds of shuffling and labeling, RNA from each cell contains a unique combination of barcodes. (Urton, James)
            Per George Seelig, “this new method can solve a big problem in means to measuring gene expression. By identifying what RNA molecules came from, and which cell in the original sample”. This theory was tested on mice, using the brain and spinal cord tissue samples. SPLIT-seq could measure the gene activity of over 156,000 cells. Based on the patterns of gene activity, it was estimated that more than 100 different types of cells are present in those tissue samples. They also included neurons and glial cells at various stages of development. (Urton, James) This is all evidence per the team of researchers from University of Washington and Allen Institute for brain science.
            SPLIT-seq also cost way less than the other two discussed methods and provides more accurate results. This article says, it cost about a penny per cell, which is much lower than other single cell RNA sequencing approaches. (Seelig, George) The researchers have claimed that this new method SPLIT-seq can answer important questions, and help identify actual minute changes in gene expression that can start unwanted disease like Parkinson’s or cancer. (Urton, James)
This article is very intriguing, I am interested in seeing how much further this new method can go. This could be a huge breakthrough in regards to helping with Parkinson's or cancer, this would be fantastic if it opened the door to cures, or at least the prevention of attracting the disease. 
https://www.nsf.gov/news/news_summ.jsp?cntn_id=244852&org=NSF&from=news

Melanie Tiedemann

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