欢迎参加南校区7月26日学术报告

主讲人：

Jingjing Li, PhD

Instructor, Stanford Pediatrics

Banting Fellow, Stanford Genetics

Stanford Center for Genomics and Personalized Medicine

Stanford School of Medicine

主持人：张锐教授

时间：2016年7月26号（星期二）上午10:00-11:00

地点：南校区生物楼205会议室

Dr Li 从事的领域包括复杂疾病的多组学研究、RNA生物学、分子进化和计算生物学。在Nature、Science、Cell Systems、Genome research、PNAS 等相关领域的顶级杂志上发表SCI论文超过25篇。

Seminar Abstract

Mutational heterogeneity is common among many complex human diseases, where even for the same disease, different patients tend to carry different sets of mutations. Using autism spectrum disorders as an example, all professionals in this field know the truth of the saying “If you’ve seen one individual with autism, you’ve seen one individual with autism”. Given such extreme locus heterogeneity, it is often challenging to apply the traditional statistical techniques to identify the genetic architecture underlying complex human diseases.

In this talk I will discuss our systems frameworks to unveil the hidden genetic architecture in complex human diseases. Focusing on autism spectrum disorders, we integrated multi-omics profiling approaches with molecular network analysis, and identified modules of highly interacting proteins that are strongly involved in autism. Combining high-throughput sequencing with immunostaining, cell-type-specific transcriptome analysis, and data from mouse knockout experiments, our study established the role of oligodendrocytes in this disease. To gain a finer grained picture for the genetic architecture in autism, we performed proteome-wide affinity purification screens in neuronal cells, followed by mass spectrometry profiling, and exhaustively identified the neuronal protein complexes harboring autism-associated subunits. These identified neuronal protein complexes exhibited increased deleterious mutations in autism cases and are commonly regulated by FMRP and MECP2, which are causal for fragile X and Rett syndromes, respectively. Our systems analysis has made it possible to directly reveal the physical architecture in autism in a cellular context, and demonstrated that the seemingly heterogeneous mutations converge onto a common set of pathways. In the last part of my talk, I will discuss my ongoing and future studies on characterizing the non-coding regulatory landscape in autism.

Overall, complementary to standard mutation analysis for complex human diseases, an integrative framework built on omics-profiling strategies will allow capturing genetic abnormalities and consequences across genomic, epigenomic, transcriptomic, and proteomic dimensions. It will not only reveal the “action in context” for disease-associated genes, but will also provide additional power to uncover novel genetic components in complex human diseases.