Research

Understanding Gene Regulation

Transcription factors (TFs) orchestrate gene expression by recognizing and binding to specific DNA sequences that regulate gene transcription by RNA polymerase II. A mechanistic understanding of how TFs identify and bind such sequences in vivo has been elusive despite decades of work. Recently progress has been made using machine learning to predict binding and gene expression to DNA sequences in different cell types, but such algorithms do not generally yield insights into the biophysical principles that govern TF specificity. We believe that a fruitful approach is to generate specific mechanistic hypotheses from analyses of large scale in vivo and in vitro experiments (machine learning aided or otherwise) and then build biophysically motivated models to test them.

Relevant Publications

  1. Recio PS, Mitra NJ, Shively CA, Song D, Jaramillo G, Lewis KS, Chen X, Mitra RD. Zinc cluster transcription factors frequently activate target genes using a non-canonical half-site binding mode.  Nucleic Acids Res. 2023 doi: 10.1093/nar/gkad320.
  2. Liu J, Shively CA, Mitra RD. Quantitative analysis of transcription factor binding and expression using calling cards reporter arrays. Nucleic Acids Res. 2020 May 21;48(9):e50. doi: 10.1093/nar/gkaa141.PMID: 32133534
  3. Shively CA, Liu J, Chen X, Loell K, Mitra RD. Homotypic cooperativity and collective binding are determinants of bHLH specificity and function. Proc Natl Acad Sci USA. 2019 Aug 6; 116(32):16143-16152. doi:10.1073/PNAS.1818015116. PMID:31341088

Genomic Technology Development

We have a long-standing interest in genomic technology development, starting with some of the earliest work on next-generation sequencing technology and it’s applications to forays into single molecule protein sequencing. Recently our focus has been on developing methods to better understand gene expression including methods to map transcription factor (TF) binding and mRNA expression in single cells, using MPRAs to measure TF binding to, and gene expression output from, user-specified DNA sequences in parallel. We have also developed methods to measure gene expression from different tissues in vivo.

Relevant Publications

  1. Lalli M, Avey D, Dougherty JD, Milbrandt J, Mitra RD. High-throughput single-cell functional elucidation of neurodevelopmental disease-associated genes reveals convergent mechanisms altering neuronal differentiation. Genome Res. 2020 Sep;30(9):1317-1331. doi: 10.1101/gr.262295.120. Epub 2020 Sep 4.PMID: 32887689 
  2. Moudgil A, Wilkinson MN, Chen X, He J, Cammack AJ, Vasek MJ, Lagunas Jr. T, Qi Z, Morris SA, Dougherty JD, Mitra RD. Self-reporting transposons enable simultaneous readout of gene expression and transcription factor binding in single cells. Cell. 2020 Aug 20;182(4):992-1008.e21. doi: 10.1016/j.cell.2020.06.037. Epub 2020 Jul 24.PMID: 32710817
  3. Cammack AJ, Moudgil A, Lagunas T, Vasek MJ, Shabsovich M, He J, Chen X, Wilkinson MN, Miller TM, Mitra RD, Dougherty JD. A viral toolkit for recording transcription factor-DNA interactions in live mouse tissues. Proc Natl Acad Sci U S A. 2020 May 5;117(18):10003-10014. doi: 10.1073/pnas.1918241117. Epub 2020 Apr 16.PMID: 32300008

Misregulation of Gene Expression in Disease

We are interested in understanding how disease develops when transcriptional and post-transcriptional programs go awry. We are focused, in particular, on cancer, neurodevelopment, and neurodegeneration through collaborations with the Puram, Rubin Dougherty, Milbrandt, and DiAntonio labs. We are interested in the transcriptional basis of partial EMT and sex differences in cancer. We are also developing tools to analyze the response to TF perturbations at scale.

Relevant Publications

  1. Kfoury N, Qi Z, Prager BC, Wilkinson M, Broestl L, Berrett KC, Moudgil A, Sankararaman S,  Chen X,  Gertz J,  Rich JN, Mitra RD, and Rubin JB. Brd4-bound enhancers drive cell-intrinsic sex differences in glioblastoma. Proc Natl Acad Sci USA April 20, 2021 PMID:33850013
  2. Lalli M, Avey D, Dougherty JD, Milbrandt J, Mitra RD. High-throughput single-cell functional elucidation of neurodevelopmental disease-associated genes reveals convergent mechanisms altering neuronal differentiation. Genome Res. 2020 Sep;30(9):1317-1331. PMID: 32887689 
  3. Avey D, Sankararaman S, Yim A, Barve R, Milbrandt J†, Mitra RD†.Single-Cell RNA-Seq Uncovers a Robust Transcriptional Response to Morphine by Glia. Cell Rep. 2018 Sep 25;24(13):3619-3629.e4. PMID: 30257220
  4. Yim AKY, Wang PL, Bermingham JR Jr, Hackett A, Strickland A, Miller TM, Ly C, Mitra RD, Milbrandt J. Disentangling glial diversity in peripheral nerves at single-nuclei resolution. Nat Neurosci. 2022 Feb;25(2):238-251. PMID: 35115729