. Support is requested for the renewal of an integrated, multidisciplinary training program for pre-doctoral trainees in genomics, with the goal of providing future scientists with the quantitative and computational tools necessary for successful biological research. The genome-training program supports students in Princeton University?s Graduate Program in Quantitative and Computational Biology (QCB) and other partner departments, including Molecular Biology, Computer Science, Chemistry, Chemical and Biological Engineering, Physics, and Ecology and Evolutionary Biology and is administered by the Lewis-Sigler Institute for Integrative Genomics. Genomics trainees are able to do their lab rotations and thesis research with any of 24 affiliated faculty in seven departments united by common interests in quantitative and computational biology, across a wide range of research areas. We request 10 pre-doctoral positions (our current level) each year during the proposed grant period; trainees typically are appointed to the training grant for a total of two years. Trainees do experimental and computational research in: experimental functional genomics in a variety of model and mammalian systems; computational projects ranging from large-scale genomics data integration, analysis, and visualization to human origins and evolution; single-cell genomics and other genomics technology development; and systems biology projects ranging from microbial metabolism to the biophysics of transcriptional regulation. Trainees have individualized, efficient training plans, which span on average 4.9 years, for those who received their Ph.D. in the last ten years. Formal training includes courses in genomics and genomic analysis, a seminar series, a journal club / presentation course, responsible conduct in research training appropriate for both experimental and computational research, and other multidisciplinary activities centered in the Institute. Trainees have the opportunity to teach in an innovative multidisciplinary introductory program for undergraduates at Princeton. Finally, trainees and eligible faculty participate in a number of activities designed to recruit and teach individuals who are members of under-represented minority groups.

Public Health Relevance

Genomics technology and the computer have revolutionized biomedical science. To enable the success of future biomedical researchers, a paradigm shift in graduate education is required, one in which biology and the more quantitative sciences, especially computation, are given equal weight. The NHGRI training program at Princeton has been one of the pioneer programs fulfilling this role.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Institutional National Research Service Award (T32)
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Special Emphasis Panel (ZHG1)
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Gatlin, Tina L
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Princeton University
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Treen, Nicholas; Heist, Tyler; Wang, Wei et al. (2018) Depletion of Maternal Cyclin B3 Contributes to Zygotic Genome Activation in the Ciona Embryo. Curr Biol 28:1150-1156.e4
Brush, Eleanor R; Krakauer, David C; Flack, Jessica C (2018) Conflicts of interest improve collective computation of adaptive social structures. Sci Adv 4:e1603311
Kaletsky, Rachel; Yao, Victoria; Williams, April et al. (2018) Transcriptome analysis of adult Caenorhabditis elegans cells reveals tissue-specific gene and isoform expression. PLoS Genet 14:e1007559
Brush, Eleanor; Brännström, Åke; Dieckmann, Ulf (2018) Indirect reciprocity with negative assortment and limited information can promote cooperation. J Theor Biol 443:56-65
Liu, Mochi; Sharma, Anuj K; Shaevitz, Joshua W et al. (2018) Temporal processing and context dependency in Caenorhabditis elegans response to mechanosensation. Elife 7:
Lim, Bomyi; Fukaya, Takashi; Heist, Tyler et al. (2018) Temporal dynamics of pair-rule stripes in living Drosophila embryos. Proc Natl Acad Sci U S A 115:8376-8381
Klibaite, Ugne; Berman, Gordon J; Cande, Jessica et al. (2017) An unsupervised method for quantifying the behavior of paired animals. Phys Biol 14:015006
GTEx Consortium; Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group; Statistical Methods groups—Analysis Working Group et al. (2017) Genetic effects on gene expression across human tissues. Nature 550:204-213
Saha, Ashis; Kim, Yungil; Gewirtz, Ariel D H et al. (2017) Co-expression networks reveal the tissue-specific regulation of transcription and splicing. Genome Res 27:1843-1858
Cleard, Fabienne; Wolle, Daniel; Taverner, Andrew M et al. (2017) Different Evolutionary Strategies To Conserve Chromatin Boundary Function in the Bithorax Complex. Genetics 205:589-603

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