Jun Yin PhD

Research Experience

Amgen Inc., USA 2015-present

• Co-lead the target discovery platform for cardiovascular and metabolic diseases using integrative genomics knowledge including transcriptomics, proteomics, signaling pathway, and human genetics annotations.
• Develop computational pipelines and infrastructure to automate comprehensive analysis of RNA-seq data sets, including gene differential expression, alternative splicing, and expression and splicing QTL (eQTL and sQTL) analyses.
• Apply NGS technologies to investigate drug toxicity burden and toxicogenomics.
• Develop and apply machine learning technologies for omics data and patient electronical record for target discovery and biomarker identification.
• Lead bioinformatician for target discovery and biomarker identification for cardiovascular diseases
• Computational supports for target discovery and profiling in cancer immunotherapies and neuroscience.
• Extensive collaboration with business development, regulation and legal departments, and provide consultation on drug profiles, one of the projects led to a recently FDA/EU approved drug, IMLYGIC.

Yale University, USA 2012-2015

• Lead bioinformatician in the meningioma genomics project, the most common brain cancer (Science 2013). Developed computational pipeline to investigate and integrate high dimensional meningioma data sets on microarray gene expression, ChIP-seq epigenomic regulation, Exome somatic mutations from sequencing, and chromosome Copy Number Aberrations from CGH Microarray. Identified meningioma subtypes based on the integrated data. Built signaling networks for tumor subtype specific genes. Identified subtype specific biomarkers.
• Developed a computational pipeline to perform comparative analysis of ChIP-seq signals in multiple species in a parallel computing manner. Identified human specific regulatory elements based on large scale ChIP-seq maps on histone modifications in human, rhesus and mouse (Cell 2013). Identified sequence contributors to these regulatory elements from transposable elements, segmental duplications and self-chains. Calculated the evolutionary ages of the elements.
• Led a project studying human specific regulatory signatures on cortical development (Science 2015). Identified human specific regulatory elements in corticogenesis by comparing high dimensional ChIP-seq maps generated in multiple species. Constructed gene co-expression networks using high-resolution RNA-seq data on cortical development. Implemented permutation tests, and identified several gene co-expression modules significantly enriched with human specific promoters or enhancers. Uncovered modules of highly correlated genes on neuronal proliferation, migration, and cortical patterning significantly associated with human specific regulatory signatures. Provided extremely valuable roadmap to study brain development and associated diseases. A follow-up study was performed on mammalian specific regulatory elements (PNAS 2016). European Bioinformatics Institute, UK 2011
• Explored sequence features and chromosome locations of deeply conserved sequences, and discovered significant enrichment of the conserved sequences near development related genes. Google Inc. 2010
• Open Source Software Developer for BioPerl to develop and improve BioPerl packages on manipulation of multiple sequence alignment, and created several new packages on retrieving online alignment sequences.

University College Dublin, Ireland 2008-2012

• Developed a novel microarray annotation protocol to improve interpretation of gene expression microarrays by integrating multiple genome annotation databases (BMC Genomics 2010).
• Analyzed microarray and RNA-seq data sets on zebrafish developmental and functional genomics. Applied and analyzed functional assays to study drug treatment effects in zebrafish (PLoS One 2012). CapitalBio Corporation, China 2006-2007
• Developed computational packages and data mining pipelines for our service department and customers.
• Designed microarrays to identify plant virus and viroid infections (Plos One 2013, JVM 2010, and Seven Invention Patents) Uppsala University, Sweden 2005-2006
• Annotated the genome of Orientia tsutsugamushi, the pathogen of scrub typhus, which has the largest percentage (~40%) of repetitive sequences in bacteria (PNAS 2007).

Publications

(9 out of 18, #Authors contributed equally, Google Scholar)

1. Loss of function in R47H TREM2 risk-variant linked to Alzheimer’s disease can be rescued by a TREM2 agonist antibody. Cheng Q, J Danao, S Talreja, P Wen, Yin J, et al., Sambashivan S. Journal of Biological Chemistry. 2018 Jun 1;13(1):29.
2. Origin and evolution of developmental enhancers in the mammalian neocortex. Emera D#, Yin J#, Reilly SK, Gockley J, Noonan JP. Proc Natl Acad Sci U S A. 2016 May 10;113(19):E2617-26.
3. Evolutionary genomics. Evolutionary changes in promoter and enhancer activity during human corticogenesis. Reilly SK#, Yin J#, Ayoub AE, Emera D, Leng J, et al. Science. 2015 Mar 6;347(6226):1155-9.
4. The autism- associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment. Cotney J, Muhle RA, Sanders SJ, Liu L, Willsey AJ, Niu W, Liu W, Klei L, Lei J, Yin J, Reilly SK, Tebbenkamp AT, Bichsel C, Pletikos M, Sestan N, Roeder K, State MW, Devlin B, Noonan JP. Nat Commun. 2015 Mar 10;6:6404.
5. Universal oligonucleotide microarray with a minimal number of probes for the detection and identification of viroids at the genus level. Zhang Y#, Yin J#, Jiang D, Xin Y, Ding F, Deng Z, Wang G, Ma X, Li F, Li G, Li M, Li S, Zhu S. PLoS One. 2013 May 29;8(5):e64474.
6. The evolution of lineage-specific regulatory functions in the human embryonic limb. Cotney J#, Leng J#, Yin J, Reilly S, DeMare LE, Emera D, Ayoub AE, Rakic P, Noonan JP. T Cell. 2013 Jul 3;154(1):185-96.
7. Genomic analysis of non-NF2 meningiomas reveals mutations in TRAF7, KLF4, AKT1, and SMO. Clark VE, Erson-Omay EZ, Serin A, Yin J, Cotney J, Ozduman K, … and 35 authors …, Lifton RP, Noonan JP, Yasuno K, Gunel M. Science. 2013 Mar 1;339(6123):1077-80.
8. Integrating multiple genome annotation databases improves the interpretation of microarray gene expression data. Yin J, McLoughlin S, Jeffery IB, Glaviano A, Kennedy B, Higgins DG. BMC Genomics. 2010 Jan 20;11:50.
9. The Orientia tsutsugamushi genome reveals massive proliferation of conjugative type IV secretion system and host–cell interaction genes. Cho NH, Kim HR, Lee JH, Kim SY, Kim J, Cha S, Kim SY, Darby AC, Yin J, etc. Proc Natl Acad Sci U S A.2007 May 8;104(19):7981-6.