CD Genomics Blog

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RNA-Seq-Transcriptome-1

Recently, researchers form Netherlands announced that they developed a new algorithm named RaceID and conbined this RaceID with sequencing datas of transcriptome, then they found some rare cell types in intestine. This is meaningful for our understanding of tissue biology and the formation of cells in tissues.
Traditional methods of finding cells or isolating subpopulation are based on known gene-expression message RNA or protein. But for some rare cells, it’s still hard to identify their specific gene expressions. The researchers firstly chose hundred types of cells from all the intestinal cells and sequenced them. To find specific gene expressions in rare cells, they invented an algorithm, which is RaceID. By this RaceID they found a new rare marker gene named Reg4 in enteroendocrine cells.
RNA-Seq
Transcriptome is the collection of all RNA molecules, including mRNA, rRNA, tRNA, and other non-coding RNA transcribed. Transcriptome becomes a main method of research on gene expression because protein plays an important role in the functional process of cells. With the requirments of all kinds of research, RNA-seq is developed as an important method for transcriptomics studies. RNA-Seq now is a powerful tools for basic research, diagnose and medical research. Accurate and reliable RNA-Seq is necessary in this process, so choose a powerful sequencing company is needed for researchers. And since the foundation of CD Genomics in 2004, It has won the trust of customers for the high efficiency and comprehensive service. RNA-Seq is also one of the main services of it.
What is the significance?
The researchers said this new method may be used to identity rare cell types like stem cells, short-lived progenitors, cancer stem cells, or circulating tumour cells. And precious research has proved that stem cells can be applicated in many fields like organ transplantation, nephropathy treaement, and other diseases. Cancer stem cells are related to new cancer drug development. Knowing those cells more deeply means we can have the chance to cure them. This new algorithm provides more possibility for us to find unknown parts about those cells. But to find out if this algorithm is suitable for other types of cells, we still need time.

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