TBUSA to Supply Single-Cell RNA-Seq Kit for the Allen Cell Types Database
Complete the form below to unlock access to ALL audio articles.
Takara Bio USA Inc has announced that its SMART-Seq® v4 Ultra® Low Input RNA Kit for Sequencing has been selected for the development of gene expression profiles of individual brain cells as part of the Allen Cell Types Database, a public resource available from the Allen Institute for Brain Science. This database will extend knowledge about the various cell types in the brain, which in turn may shed light on how the healthy brain functions and what goes wrong in diseases such as autism, Alzheimer's and Parkinson's.
"We are excited to provide the SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing to the Allen Institute, to support their efforts to develop the Allen Cell Types Database of brain cell morphology, signaling, and gene expression. This publicly-accessible database will be a great step toward understanding healthy brain function and developing cures for serious brain diseases," commented Carol Lou, President of Takara Bio USA, Inc. "Understanding the gene expression that is correlated to specific cell morphologies and signaling events is essential to a fuller understanding of brain activity."
Andrew Farmer, Vice President of Research and Development at TBUSA, stated that, "The SMART-Seq v4 Ultra Low kit shows the highest performance of any technology currently available, producing the highest number of identified full-length genes with the smoothest library construction process. This kit will fully support the Allen Institute's project to generate full transcriptome maps of over 100,000 individual mouse and human neocortex cells."
The SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing is an immensely powerful tool for studying the full transcriptome, including splice junctions and alternative splicing events in cells, and provides full-length gene coverage. LNA technology incorporated into the kit improves the efficiency of template switching, which in turn increases the number of genes identified to higher levels than any other technology.