Many of the molecular mechanisms underlying well-characterized robust and rapidly inducible transcriptional responses are shared among other systems, so we use the transcriptional response to hormone treatment as a model to study gene regulation. We use rapid kinetic regulation and perturbation of transcription cascades, transcription factors, and cofactors to identify key mechanisms, genes, and regulatory elements that are critical for hormone signaling. Transcription factors act as activators or repressors and interface with a constellation of accessory cofactors to regulate distinct steps in the transcription to coordinate gene expression, but the molecular functions of the vast majority of transcription factors remain uncharacterized. We use molecular genomics and computational methods to classify transcription factors by their molecular function, as opposed to broad activator and repressor classes, in order to understand the context specificity of gene regulation. The genes and regulatory elements that are downstream of the first wave of transcriptional response are critical for propagating regulatory cascades. We generated high temporal resolution time course data and implement modeling approaches to identify effector genes and regulatory elements that are critical for hormone signaling. Our research continues to reveal basic principles and rules that govern transcription factor specificity in order to understand how genetics, nutrition, and environmental factors contribute to variation in transcriptional programs that can lead to disease states or ineffective therapies.

Recent seminar:

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Publications


fragment_distribution_comparisonSmith JP, Dutta AB, Sathyan KM, Guertin MJ, Sheffield NC, Quality control and processing of nascent RNA profiling data. bioRχiv https://doi.org/10.1101/2020.02.27.956110, 2020.
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Figure 1

Sathyan KM, Scott TG, Guertin MJ. The ARF-AID system: Methods that preserve endogenous protein levels and facilitate rapidly inducible protein degradation. arXiv https://arxiv.org/abs/2002.12883, 2020. PDF


Fig1newAnderson WD, Duarte FM, Civelek M, Guertin MJ. Defining data-driven primary transcript annotations with primaryTranscriptAnnotation in R. Bioinformatics, btaa011 https://doi.org/10.1093/bioinformatics/btaa011 2020. PDF


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Sathyan KM, McKenna BD, Anderson WD, Duarte FM, Core L, Guertin MJ. An improved auxin-inducible degron system preserves native protein levels and enables rapid and specific protein depletion. Genes & Development, 33: 1441-1455,2019. PDF


Screen Shot 2018-02-05 at 11.46.32 AMGuertin MJ, Cullen AE, Markowetz F, Holding AN. Parallel Factor ChIP Provides Essential Internal Control for Quantitative Differential ChIP-seq. Nucleic Acids Research, 46(12), e75, 2018. PDF


Screen Shot 2018-03-12 at 6.39.24 PMWang Z, Civelek M, Miller CL, Sheffield NC, Guertin MJ, Zang C. BART: a transcription factor prediction tool with query gene sets or epigenetic profiles. Bioinformatics, bty194, 2018. PDF


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Martins AL, Walavalkar NM, Anderson WD, Zang C, Guertin MJ. Universal correction of enzymatic sequence bias reveals molecular signatures of protein/DNA interactions. Nucleic Acids Research, Volume 46, Issue 2, 25, Pages e9, 2018. PDF


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Liu Y, Walavalkar NM, Dozmorov MG, Rich SS, Civelek M, Guertin MJ. Identification of breast cancer associated variants that modulate transcription factor binding. PLOS Genetics 13(9): e1006761, 2017. PDF


F6.large-3                                                                                                               Duarte FM, Fuda NJ, Mahat DB, Core LJ, Guertin MJ, Lis JT. Transcription factors GAF and HSF act at distinct regulatory steps to modulate stress-induced gene activation. Genes and Development 30(15):1731-46, 2016. PDF



Fuda NJ, Guertin MJ, Sharma S, Danko CG, Martins AL, Siepel A, Lis JT. GAGA Factor Maintains Nucleosome-Free Regions and Has a Role in RNA Polymerase II Recruitment to Promoters. PLOS Genetics 11(3): e1005108, 2015. PDF


Figure 4
Guertin MJ, Zhang X, Anguish L, Kim S, Varticovshi L, Lis JT, Hager GL, Coonrod SA. Targeted H3R26 deimination specifically facilitates ER binding by modifying nucleosome structure: PLOS Genetics 10 (9), e1004613, 2014. PDF


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Sung M, Guertin MJ, Baek S, Hager GL. DNase footprint signatures are dictated by factor dynamics and DNA sequence: Molecular Cell 56(2): 275-285, 2014. PDF


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Guertin MJ, Zhang X, Coonrod SA, Hager GL. Transient ER binding and p300 redistribution support a squelching mechanism for E2-repressed genes: Molecular Endocrinology 28(9): 1522-33, 2014. PDF


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Guertin MJ, Lis JT. Mechanisms by which transcription factors gain access to target sequence elements in chromatin. Current Opinion in Genetics and Development 23(2): 116-123, 2013. PDF

 



Guertin MJ, Martins AL, Siepel A, Lis JT. Accurate predictions of inducible transcription factor binding intensities in vivo. PLoS Genetics 8(3): e1002610, 2012. PDF

 


Zhang X, Bolt M, Guertin MJ, Chen W, Zhang S, Cherrington BD, Slade DJ, Dreyton CJ,Subramanian V, Bicker KL, Thompson PR, Mancini MA, Lis JT, Coonrod SA. Peptidylarginine deiminase 2-catalyzed histone H3 arginine 26 citrullination facilitates estrogen receptor α target gene activation. Proc Natl Acad Sci 109(33):13331-13336, 2012. PDF



Guertin MJ, Petesch SJ, Zobeck KL, Min IM, Lis JT. Drosophila heat shock system as a general model to investigate transcriptional regulation. Cold Spring Harb Symp Quant Biol. 75:1-9, 2011. PDF


 

Guertin MJ, Lis JT. Chromatin landscape dictates HSF binding to target DNA elements. PLoS Genetics 6(9):e1001114, 2010. PDF

 



Carmon A, Guertin MJ, Grushko O, Marshall B, MacIntyre R. A molecular analysis of mutations at the complex dumpy locus in Drosophila melanogaster. PLoS ONE 5(8):e12319, 2010. PDF