Alternative splicing: An important mechanism in stem cell biology
Abstract
Alternative splicing (AS) is an essential mechanism in post-transcriptional regulation and leads to protein diversity. It has been shown that AS is prevalent in metazoan genomes, and the splicing pattern is dynamically regulated in different tissues and cell types, including embryonic stem cells. These observations suggest that AS may play critical roles in stem cell biology. Since embryonic stem cells and induced pluripotent stem cells have the ability to give rise to all types of cells and tissues, they hold the promise of future cell-based therapy. Many efforts have been devoted to understanding the mechanisms underlying stem cell self-renewal and differentiation. However, most of the studies focused on the expression of a core set of transcription factors and regulatory RNAs. The role of AS in stem cell differentiation was not clear. Recent advances in high-throughput technologies have allowed the profiling of dynamic splicing patterns and cis-motifs that are responsible for AS at a genome-wide scale, and provided novel insights in a number of studies. In this review, we discuss some recent findings involving AS and stem cells. An emerging picture from these findings is that AS is integrated in the transcriptional and post-transcriptional networks and together they control pluripotency maintenance and differentiation of stem cells.
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Xiaojing Dai 戴晓婧
Sr. Research Scientist
Xiaojing Dai is a Research Scientist at the University of Texas MD Anderson Cancer Center, under the pioneer department of Advanced Genomic Technology Core. She led the SOP, developing laboratory information management systems for advanced genomics sequencing and cell-based assays. She also worked as a research scientist at the University of Texas Health Science Center before her latest role. Before joining UT at MD Anderson, she earned her Ph.D. in the Neuroscience Program at The University of Tokyo and an M.D. from Ningxia Medical University in China. She is also jointly pursuing the Online Master of Science in Computer Science (OMSCS) at Georgia Institute of Technology (GaTech). Her research interests lie in AI for digital pathology, code structure learning, single-cell sequencing in software engineering in health, and medical imaging.