Michael Snyder
Academic Appointments
- Professor, Genetics
- Member, Stanford Cancer Institute
- Member, Child Health Research Institute
- Member, Bio-X
Key Documents
Contact Information
- Academic Offices
Personal Information Email Tel (650) 723-4668Alternate Contact Sarah Chirico Executive Assistant Email Tel Work 650-723-4668
Professional Overview
Postdoctoral Advisees
Carlos Araya, Alan Boyle, Sean Boyle, Can Cenik, Rui Chen, Yong Cheng, Kevin Pierre Francis Contrepois, Jijuan Gu, Nastaran Heidari, Maya Kasowski, Jingjing Li, Jennifer Li Pook Than, George Mias, Robert Nichols, Hwee Ling Dian Widyarini Oei, Cuiping Pan, Doug Phanstiel, Varsha Rao, Jason Reuter, Wei Jia Soon, Hagen Tilgner, Linfeng Wu, Dan Xie, Zhixin Zhao, Wenyu Zhou
Internet Links
Industry Relationships
Stanford is committed to ethical and transparent interactions with our industrial and other commercial partners. It is our policy to disclose payments (exclusive of travel support) from, and/or equity in, companies or other commercial entities to Stanford faculty of $5,000 or more in total value, as well as any equity in a privately held company, when the faculty member also has institutional responsibilities related to his or her interactions with the company. View Full Information
Scientific Focus
Current Research Interests
We are presently in an omics revolution in which genomes and other omes can be readily characterized. Our laboratory uses a variety of approaches to analyze genomes and regulatory networks. Our research focuses on yeast, an ideal model organism ideally suited to genetic analysis, and humans.
1) Transcriptomes
To annotate genomes, we developed RNA sequencing for annotation the yeast and human transcriptomes. We discovered that the eukaryotic transcriptome is much more complex than previously appreciated and that embryonic stem cells have more transcript isoforms than differentiated cells.
2) Transcription Factor Binding Networks
We have also developed methods for mapping transcription factor binding sites through the genome. We used this to develop regulatory maps and have been using this to help decipher the combinatorial regulatory code which factors work together to regulate which genes. Using this approach we have mapped out pathways crucial for metabolism and inflammation.
3) Integrated Regulatory Networks
In addition to transcriptional factor binding networks we have also been mapping phosphorylation and metabolite-protein interaction networks. These studies have revealed novel global regulators and key points in integrated regulatory networks.
4) Variation
We have been analyzing differences between individuals and species at two levels: DNA sequence variation and regulatory information variations. We developed paired end sequencing for humans and found that humans have extensive structural variation (SV), i.e. deletions, insertions and inversions. This is likely to be a major cause of phenotypic variation and human disease. In addition, by mapping binding sites difference among different yeast strains and humans, we have found that individuals differ much more in their regulatory information than in coding sequence differences. We can correlate these differences with those in SNPS and SVs, thereby associating noncoding DNA differences with regulatory information.
5) Human Disease
Finally, we are applying omics approaches of genome sequencing, transcriptomics, and proteomics to the analysis of human disease. These integrative omics approaches are being applied to help understand the molecular basis of disease and the development of diagnostics and therapeutics.
Publications
- Promise of personalized omics to precision medicine. Wiley Interdiscip Rev Syst Biol Med. 2013 Jan-Feb; (1): 73-82
- Accurate identification and analysis of human mRNA isoforms using deep long read sequencing. G3 (Bethesda). 2013; (3): 387-97
- Comparative annotation of functional regions in the human genome using epigenomic data. Nucleic Acids Res. 2013; (8): 4423-4432
- Exome sequencing by targeted enrichment. Curr Protoc Mol Biol. 2013: Unit7.12
- Extensive transcript diversity and novel upstream open reading frame regulation in yeast. G3 (Bethesda). 2013; (2): 343-52
- High-throughput sequencing for biology and medicine. Mol Syst Biol. 2013: 640
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