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B.Sc. (Hons.) Physics, 1997, University of Delhi, Delhi, India
M.B.A., 2000, Indian Institute of Foreign Trade, New Delhi, India
Ph.D., 2007, Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY
Fellow, 2013-2014, Institute of Genomics and Systems Biology, University of Chicago, Chicago, IL
Postdoctoral Scholar, 2009-2013, Ecology and Evolution, University of Chicago, Chicago, IL
Instructor, 2002-2003, Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY
Management Trainee, 2000-2001, TATA International Limited, Chennai, India
I am interested in understanding how cell fate—the future identity of a cell—is specified during development. Many molecular processes, such as transcriptional regulation, intracellular signaling, chromatin modification, and RNA regulation, are known to be involved in cell-fate specification. In many developmental systems, such as Drosophila segmentation and mammalian hematopoiesis, cell-fate specification is largely governed by networks of cross-regulating transcription factors (TFs). This simplification makes the analysis of such developmental systems more tractable than others. Transcriptional networks controlling cell-fate specification can be quite large, sometimes involving hundreds of TFs, and contain an even larger number of interactions between the TFs. How such complex networks lead to the apparently simple and reliable phenomenon of cell-fate choice is an important problem in biology. The broad goal of my lab's research is to understand how the construction of transcriptional networks—including coarse features such as network topology and finer ones such as binding site arrangement within enhancers—determines the gene expression state of the network as a whole.
Our current work is focussed on cell-fate specification in mouse hematopoiesis. During hematopoiesis, the hematopoietic stem cell, through a series of intermediates with progressively restricted fate potential, gives rise to all the major types of cells found in blood. This process is largely governed by transcription factors that alter the genome-wide gene expression patterns in each lineage. Over the past decade genomic approaches such as RNA-seq and ChIP-seq have shown that hematopoietic transcriptional networks are large and highly interconnected.
Despite the availability of genome-wide gene expression and ChIP datasets for the past decade or so, the inference of cis regulation—the TFs binding an individual gene and how they control its gene expression—remains unknown for most hematopoietic genes. We are addressing this challenge with a new computational modeling-based approach—which takes into account biophysical and phenomenological rules of transcription factor binding and interaction—to infer cis-regulatory logic from genome-wide gene expression and reporter activity datasets.
I have used this approach, in collaboration with other investigators, to decode the cis regulation of three hematopoietic genes, Cebpa (C/EBPα), Egr1, and Egr2 during the differentiation of macrophages and neutrophils from progenitors in an inducible cell differentiation system. The model infers that Cebpa has a surprisingly complex regulatory makeup, with multiple activating and suppressing elements and regulatory inputs from several TFs.
We plan to broaden the scope of our reverse engineering efforts to other hematopoietic TFs and non-myeloid lineages. We expect that increasing the breadth and depth of cis-regulatory decoding will lead to insights about how hematopoietic gene networks are built and allow us to relate their construction to their function in both normal and perturbed development. This methodology is quite general and applicable to a wide variety of developmental and other biological contexts. We are actively exploring collaborations with other groups to apply such approaches in other systems.
I offer a course in Systems Biology (Biol 418) and team-teach General Biology II (Biol 151). Biol 418 introduces basic concepts and methods in the emerging field of systems biology with an emphasis on biological networks, gene regulation, intracellular signaling, development and pattern formation, metabolism, and the analysis of high-throughput “omics” data. Computer simulations are used heavily to gain deeper insight into system function.
"Modeling the processing of signaling cues by transcriptional networks during cell-fate choice", National Science Foundation, Division of Molecular and Cellular Biosciences Award 1615916, 2016-2019 ($659,279).
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E. Bertolino, J. Reinitz, and Manu (2016) The analysis of novel distal Cebpa enhancers and silencers using a transcriptional model reveals the complex regulatory logic of hematopoietic lineage specification. Developmental Biology, 413:128–141 [Full Text]
H. Wu, Manu , R. Jiao, and J. Ma (2015) Temporal and spatial dynamics of scaling-specific features of a gene regulatory network in Drosophila. Nature Communications, 6:10031 [Full Text]
Manu, M. Z. Ludwig, and M. Kreitman (2013) Sex-specific pattern formation during early Drosophila development. Genetics, 194(1):163–73
M. Z. Ludwig, Manu, R. Kittler, K. P. White, and M. Kreitman (2011) Consequences of eukaryotic enhancer architecture for gene expression dynamics, development, and fitness. PLoS Genetics, 7:e1002364
Manu, S. Surkova, A. V. Spirov, V. Gursky, H. Janssens, A. Kim, O. Radulescu, C. E. Vanario-Alonso, D. H. Sharp, M. Samsonova, and J. Reinitz (2009) Canalization of gene expression in the Drosophila blastoderm by gap gene cross regulation. PLoS Biology, 7:e1000049
Manu, S. Surkova, A. V. Spirov, V. Gursky, H. Janssens, A. Kim, O. Radulescu, C. E. Vanario-Alonso, D. H. Sharp, M. Samsonova, and J. Reinitz (2009) Canalization of gene expression and domain shifts in the Drosophila blastoderm by dynamical attractors. PLoS Computational Biology, 5:e1000303
J. Jaeger, S. Surkova, M. Blagov, H. Janssens, D. Kosman, K. N. Kozlov, Manu, E. Myasnikova, C. E. Vanario- Alonso, M. Samsonova, D. H. Sharp, and J. Reinitz (2004) Dynamic control of positional information in the early Drosophila embryo. Nature, 430:368–371