The Li Lab
Assessing the performance of next-generation sequencing techniques in accurate genome/epigenome/transcriptome profiling and understanding the clinical and functional role of epigenome heterogeneity in the cancer evolution.
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Assessing the performance of next-generation sequencing techniques in accurate genome/epigenome/transcriptome profiling and understanding the clinical and functional role of epigenome heterogeneity in the cancer evolution.
The primary focus of the Li Lab is on assessing the performance of next-generation sequencing techniques in accurate genome/epigenome/transcriptome profiling and understanding the clinical and functional role of epigenome heterogeneity in the cancer evolution. The Li laboratory utilizes computational and sequencing methodologies to identify and characterize the essential epigenetic lesions that guide cancer cells to evolve and escape from therapy. Our research interest is to understand the inner workings of cancer cells – the genetic and epigenetic heterogeneity that drive cancer initiation and progression. Specifically, the research involves (1) determining the drivers of epigenetic heterogeneity; (2) evaluating the functional impact of the cross-talk among epigenetic modifications on transcriptome; (3) assessing epigenetic heterogeneity/subpopulations in treatment resistance.
Dr. Li has developed a series of computational methods and software for the epigenome sequencing data analysis, to comprehensively detect the significant DNA methylation aberration and epigenetic heterogeneity during disease progression. Dr. Li's work has helped to establish the first principles and metrics for examining changes in RNA splicing and expression profiling and set standards at the FDA for clinical-grade RNA-sequencing. Dr. Li further applied these approaches to study the epigenetic heterogeneity and dynamics using acute myeloid leukemia (AML) as a model. Dr. Li found that epigenetic allele burden was linked to inferior clinical outcome, and epigenetic dynamics was related to hypervariable transcriptional regulation and was divergent from the genetic burden.
The Li Lab has the current open positions.
Research Scientist – Computational Cancer Biology
About the position: Dr. Sheng Li’s lab at JAX-GM is seeking exceptional scientists who are interested in studying cancer epigenomics using large-scale genomics datasets. The Li Lab focuses on combining computational approaches and high throughput datasets to uncover novel mechanisms that contribute to drug resistance and cancer evolution. For additional information, visit the Li Lab online.
This is a senior position within the Li Lab, and candidates with substantial prior experience are encouraged to apply. JAX-GM offers a collegial, collaborative, interdisciplinary, and diverse research environment. We will provide a competitive salary commensurate with qualifications.
Li S, Garrett-Bakelman FE, Chung SS, Sanders MA, Hricik T, Rapaport F, Patel J, Dillon R, Vijay P, Brown AL, Perl AE, Cannon J, Bullinger L, Luger S, Becker M, Lewis ID, To LB, Delwel R, Löwenberg B, Döhner H, Döhner K, Guzman ML, Hassane DC, Roboz GJ, Grimwade D, Valk PJ, D'Andrea RJ, Carroll M, Park CY, Neuberg D, Levine R, Melnick AM, Mason CE. Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia. Nat Med. 22(7):792-9. 2016.
Li S, Mason CE, Melnick A. Genetic and epigenetic heterogeneity in acute myeloid leukemia. Current opinion in genetics & development. 36:100-6. 2016.
Li S, Łabaj PP, Zumbo P, Sykacek P, Shi W, Shi L, Phan J, Wu PY, Wang M, Wang C, Thierry-Mieg D, Thierry-Mieg J, Kreil DP, Mason CE. Detecting and correcting systematic variation in large-scale RNA sequencing data. Nat Biotechnol. 32(9):888-95. 2014.
A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium. Nat Biotechnol. 32(9):903-14. 2014.
Li S, Garrett-Bakelman F, Perl AE, Luger SM, Zhang C, To BL, Lewis ID, Brown AL, D'Andrea RJ, Ross ME, Levine R, Carroll M, Melnick A, Mason CE. Dynamic evolution of clonal epialleles revealed by methclone. Genome Biology. 15(9):472. 2014.
Li S, Tighe SW, Nicolet CM, Grove D, Levy S, Farmerie W, Viale A, Wright C, Schweitzer PA, Gao Y, Kim D, Boland J, Hicks B, Kim R, Chhangawala S, Jafari N, Raghavachari N, Gandara J, Garcia-Reyero N, Hendrickson C, Roberson D, Rosenfeld J, Smith T, Underwood JG, Wang M, Zumbo P, Baldwin DA, Grills GS, Mason CE. Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study. Nat Biotechnol. 32(9):915-25. 2014.
Ricarte-Filho JC*, Li S*, Garcia-Rendueles ME, Montero-Conde C, Voza F, Knauf JA, Heguy A, Viale A, Bogdanova T, Thomas GA, Mason CE, Fagin JA. Identification of kinase fusion oncogenes in post-Chernobyl radiation-induced thyroid cancers. J Clin Invest. 123(11):4935-44. 2013.