SAN DIEGO, July 7, 2016 /PRNewswire/ -- A collaborative effort from the University of California San Diego, The Scripps Research Institute (TSRI), and Illumina has led to the classification of neuronal single-nuclei transcriptomes from the cerebral cortex of the human brain. The new findings were published on June 23rd in the Journal of Science. http://science.sciencemag.org/content/352/6293/1586.full
Classification of single neurons into subtypes has often posed a challenge because of the lower signal-to-noise ratio in cell subtypes than other typical single-cell datasets. Dr. Rizi Ai (Wang Lab at University of California, San Diego), the leading researcher and co-first author in the new Journal of Science paper, developed a new bioinformatics algorithm to iteratively classify 3,227 single-cell transcriptome datasets across the six brain regions. Dr. Ai's algorithm called "Clustering-and-Classification" is able to sensitively measure the most variant gene expressions at each splitting level and determine the cell subtypes based on the active/inactive genes iteratively. The algorithm successfully revealed a lot more diverse in human brain than previously thought by dividing 3,227 individual neurons into 16 neuronal subtypes that are correlated with functions. Besides, Dr. Ai also developed an automatic analysis pipeline to automatically process and analyze large volumes of high-throughput sequencing data such as RNA sequencing data of neuronal cells.
Dr. Rizi Ai had this to say when contacted through email:
"Our research is beyond classifying cells into cell types, we wanted to look more deeply and classify single neurons into cell subtypes. This process is important in further understanding how different brain regions could function differently. With the shortfalls of traditional clustering methods I worked around the clock to create the novel bioinformatics algorithm, Clustering-and-Classification. This new algorithm is sensitive enough to reveal heterogeneity in cell subtypes and capturing transcription variation signals from different neuronal subtypes. "
The Journal of Science article that Dr. Rizi Ai co-first authored is a huge step forward in understanding neuronal subtypes in the human cerebral cortex and provides a framework for comparing individual neurons. This data can also be useful for further research into neurological disorders like dementia, Alzheimer's, Parkinson's, schizophrenia, depression and seeing if changes in heterogeneity of neuronal subtypes plays a role in these diseases.
To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/novel-approach-reveals-more-diversity-in-the-human-brain-300295168.html
SOURCE Wei Wang's Lab