学术报告
题目：Single Cell Genomics: When Stochasticity Meets Precision
报告人：Xiaoliang Sunney Xie
时间：6月20日（周三）下午1：30pm--2：30pm
地点：金光生命科学大楼411会议室
摘要：
DNA exists as single molecules in individual cells. Consequently, genomic variations such as copy-number variations (CNVs) and single nucleotide variations (SNVs) in a single cell occur in a stochastic way, necessitating single-cell and single-molecule measurements. However, existing single-cell whole genome amplification (WGA) methods are limited by low accuracy of CNV and SNV detection. We have developed transposase-based methods for single-cell WGA, which have superseded previous methods. With the improved genome coverage, we were able to develop a high-resolution single-cell chromatin conformation capture method, which allows for the first 3D genome map of a human diploid cell.
Gene expression is also stochastic due to the fact that the DNA exists as single-molecules in an individual cell. The correlations among different types of mRNAs in a single-cell are masked within the stochastic gene expression noise. We have developed a method for measuring single-cell transcriptome with much improved detection efficiency and accuracy, revealing intrinsic correlations among each pair of mRNAs in a single-cell. For a particular human cell type, we uncovered ~150 Correlated Transcription modules (CTMs) from the gene expression data of ~700 individual cells under a steady state condition. We found that the CTMs are cell type dependent.
欢迎各位老师同学积极参加！