We are seeking an outstanding postdoctoral fellow or research scientist with strong computational skills and a keen interest in working across two laboratories to (1) understanding sources of genome instability that drive the development of cancer, particularly lymphoma and leukemia, and (2) develop new computational pipelines to analyze data mutational profiles from chemically modified RNAs.
The biological focus of this position is the mechanisms that lead to genome damage during the processes of somatic hypermutation and V(D)J recombination, which are mediated by the enzymes AID (activation induced deaminase) and RAG (recombination activating gene), respectively. The project will involve the analysis of diverse data types including NGS, epigenetic, Ig/TCR REP-seq, and chromatin architecture and looping data in order to identify the mechanisms that lead to mis-targeting of AID and RAG. There will also be opportunities to perform wet-bench experiments if desired.
The chemical biology focus of this position will include the development of efficient pipelines to accompany nucleotide recoding experiments---new RNA sequencing experiments that use metabolic labeling and mutational analysis to infer RNA structure, dynamics and small molecule-RNA interactions from sequencing data.
The successful applicant will develop novel computational approaches and pipelines while working closely with experimental immunologists and chemical biologists to formulate hypotheses, design experiments and refine models. Interested applicants should have a strong interest in biological mechanism and in developing their skills and independence in computational genomics, immunology and chemical biology.
This position will be sponsored and mentored by David Schatz immunobiology.yale.edu/people/david_schatz.profile in the Department of Immunobiology, and Matt Simon (www.simonlab.yale.edu) in the Chemical Biology Institute. The successful candidate will have access to the experimental resources of the Schatz and Simon labs including the rich immunology environment provided by the Department of Immunobiology, the computational expertise and resources available in Yale's Interdepartmental Program in Computational Biology and Bioinformatics (CBB) through long-time computational collaborator Steven Kleinstein (bbs.yale.edu/people/steven_kleinstein-2.profile), and the interdisciplinary resources of the Chemical Biology Institute.
The Schatz lab is a leader in the study of V(D)J recombination and somatic hypermutation, including biochemical mechanism, evolution, and regulation in vivo. This lab has a long history of collaboration with computational biologists and use of NGS approaches to study biological problems (Buerstedde et al., 2014; Duke et al., 2013; Liu et al., 2008; Maman et al., 2016; Teng et al., 2015). The Simon lab is a leader in the study of RNA biology through new chemical approaches, including the use of metabolic labeling and nucleotide recoding experiments to reveal RNA population dynamics (Duffy et al. 2015; Duffy et al. 2018; Schofield et al. 2018).
Buerstedde, J.M., Alinikula, J., Arakawa, H., McDonald, J.J., and Schatz, D.G. (2014). Targeting of somatic hypermutation by immunoglobulin enhancer and enhancer-like sequences. PLoS Biol 12, e1001831.
Duffy, E.E., Rutenberg-Schoenberg, M., Stark, C.D., Kitchen, R.R., Gerstein, M.B., and Simon M.D. (2015) Tracking distinct RNA populations using efficient and reversible covalent chemistry. Mol Cell, 59, 858-66.
Duffy, E.E., Canzio, D., Maniatis, T., and Simon, M.D. (2018) Solid phase chemistry to covalently and reversibly capture thiolated RNA. Nucl Acids Res 46, 6996-7005.
Duke, J.L., Liu, M., Yaari, G., Khalil, A.M., Tomayko, M.M., Shlomchik, M.J., Schatz, D.G., and Kleinstein, S.H. (2013). Multiple transcription factor binding sites predict AID targeting in non-Ig genes. J Immunol 190, 3878-3888.
Liu, M., Duke, J.L., Richter, D.J., Vinuesa, C.G., Goodnow, C.C., Kleinstein, S.H., and Schatz, D.G. (2008). Two levels of protection for the B cell genome during somatic hypermutation. Nature 451, 841-845.
Maman, Y., Teng, G., Seth, R., Kleinstein, S.H., and Schatz, D.G. (2016). RAG1 targeting in the genome is dominated by chromatin interactions mediated by the non-core regions of RAG1 and RAG2. Nucl Acids Res 44, 9624-9637.
Schofield, J.A., Duffy, E.E., Kiefer, L., Sullivan, M.C., and Simon, M.D. (2018) TimeLapse-seq: adding a temporal dimension to RNA sequencing through nucleoside recoding. Nature Methods 15, 221-225.
Teng, G., Maman, Y., Resch, W., Kim, M., Yamane, A., Qian, J., Kieffer-Kwon, K.R., Mandal, M., Ji, Y., Meffre, E., Clark, M.R., Cowell, L.G., Casellas, R., and Schatz, D.G. (2015). RAG Represents a Widespread Threat to the Lymphocyte Genome. Cell 162, 751-765.
We are recruiting creative and enthusiastic PhD graduates who are computational scientists with a strong interest in genomics and/or immunology or a biologist with extensive experience in computational analysis. The successful candidate will have some combination of experience with NGS data analysis, proficiency in R and at least one other programming language (Java, Python, Matlab, C++), familiarity with Bayesian inference, and knowledge of genomics or a strong desire to learn.