| Lab members
The laboratory's overall goal is to elucidate mechanisms of gene regulation. In particular,
we are interested in understanding how transcription regulators and epigenetic modifications regulate gene expression
programs during cellular development and differentiation. We use a combination of systems biology and functional
genomics approaches to map and characterize regulatory elements and epigenomes in embryonic and hematopoietic stem cells,
and immune and cancer cells.
Role of Tet1 and 5-hydroxymethylcytosine in regulation of embryonic stem cell identity
The TET family of FE(II) and 2-oxoglutarate-dependent enzymes
(Tet1/2/3) promote DNA demethylation by converting 5-methylcytosine to
5-hydroxymethylcytosine (5hmC), which they further oxidize into
5-formylcytosine and 5-carboxylcytosine. Tet1 is robustly expressed in
mouse embryonic stem cells (mESCs) and has been implicated in mESC
maintenance. We demonstrated that, unlike genetic deletion,
RNAi-mediated depletion of Tet1 in mESCs leads to a significant
reduction in 5hmC and loss of mESC identity. The differentiation
phenotype due to Tet1 depletion positively correlates with the extent of
5hmC loss. Meta-analyses of genomic datasets suggest interaction
between Tet1 and leukemia inhibitory factor (LIF) signaling. LIF
signaling is known to promote self-renewal and pluripotency in mESCs
partly by opposing MAPK/ERK mediated differentiation. Withdrawal of LIF
leads to differentiation of mESCs. We discovered that Tet1 depletion
impaired LIF-dependent Stat3-mediated gene activation by affecting
Stat3's ability to bind to its target sites on chromatin. Nanog
overexpression or inhibition of MAPK/ERK signaling, both known to
maintain mESCs in the absence of LIF, rescues Tet1 depletion, which
further supports the dependence of LIF/Stat3 signaling on Tet1. These
data support the conclusion that analysis of mESCs in the hours/days
immediately following efficient Tet1 depletion reveals Tet1's normal
physiological role in maintaining the pluripotent state that may be
subject to homeostatic compensation in genetic models.
Chromatin remodeling and embryonic stem cell self-renewal and pluripotency
Signaling by the cytokine LIF and its downstream transcription
factor, STAT3, prevents differentiation of pluripotent embryonic stem
cells (ESCs). This contrasts with most cell types where STAT3 signaling
induces differentiation. In a collaborative effort with Gerald
Crabtree's lab (HHMI, Stanford), we found that STAT3 binding across the
pluripotent genome is dependent on Brg1, the ATPase subunit of a
specialized chromatin remodeling complex (esBAF) found in ESCs. We
showed that esBAF is an essential component of the core pluripotency
transcription network, and that esBAF is required to establish chromatin
accessibility at STAT3 binding targets, preparing these sites to
respond to LIF signalling. Brg1 deletion leads to rapid polycomb (PcG)
occupancy and H3K27me3-mediated silencing of many Brg1-activated targets
genome wide, including the target genes of the LIF signaling pathway.
This led to the conclusion that one crucial role of Brg1-containing
esBAF in ESCs involves its ability to potentiate LIF signaling by
opposing PcG. Contrary to expectations, esBAF also facilitates PcG
function at classical PcG targets, including all four Hox loci,
reinforcing their repression in ESCs. Taken together, it became evident
that esBAF does not simply antagonize PcG. Rather, the two chromatin
regulators act both antagonistically and synergistically with the common
goal of supporting pluripotency.
Gene expression noise, regulatory network architecture, and differential cell fate Outcome
To understand differential cell-fate outcome in response to the same uniform
stimulus, we continue to explore the link between regulatory network architecture and the genome-scale dynamics
of the underlying entities (genes, mRNAs, and proteins). Recently, we found that at the protein level, the
top-layer TFs (which trigger/initiate regulatory cascades) are relatively abundant, long-lived, and showed more
cell-to-cell variability (noise) compared to the downstream (core- and bottom-layer) TFs. This and other results
led us to conclude that the variability in expression of top-layer TFs might confer a selective advantage, as
this may permit at least some members in a clonal cell population to initiate an effective response to
fluctuating environments, whereas the tight regulation of the core- and bottom-layer TFs may minimize noise
propagation and ensure fidelity in regulation. The dynamic variability in expression level of key regulatory
proteins could permit differential sampling (i.e.,the survival network or the apoptotic network) of the same
underlying regulatory network (governing all cells) by different members in a clonal population, which might
result in divergent cell-fate outcomes among different individuals in an otherwise identical cell population.
This result is critical to understanding phenotypic variability in fluctuating environments, e.g., fractional survival
or cell-death in clonal cell populations upon drug treatment in diseases such as cancer. Our current research in
this area is focused on identifying additional evidence support this notion, and understanding how cells adapt
to changing environments, how different phenotypic outcomes are mediated in clonal cell populations, and how
mutations that disrupt the dynamics of key regulatory proteins may influence disease conditions.
Gene regulatory networks,
Embryonic stem cells
Current Lab Members
- Senthilkumar Cinghu, Ph.D. (University of Madras)
Postdoctoral Fellow (2011 - )
- Andrew J Oldfield, Ph.D. (Universite Paris VI Pierre & Marie Curie)
Postdoctoral Fellow (2012 - )
- Pengyi Yang, Ph.D. (University of Sydney)
Postdoctoral Fellow (2013 - )
- Amanda E Conway, Ph.D. (Duke University)
Postdoctoral Fellow (2013 - )
- Justin Kosak, M.S. (University of Pennsylvania)
Biologist (2013 - )
Past Lab Members
- Sailu Yellaboina, Ph.D. (University of Hyderabad)
Next Position: Associate Professor, CR Rao Institute, Hyderabad, India
- Johannes Freudenberg, Ph.D. (University of Cincinnati)
Next Position: Scientific Investigator, GlaxoSmithKline, USA
- Swati Ghosh, Ph.D. (Banaras Hindu University)
Next Position:Postdoctoral Fellow, NIEHS
- Viju Mathew, Enloe High School (Summer Intern)
Next Position: Undergraduate student, Duke University, USA
[ Complete List ]
[ Pubmed ]
[ DBLP ]
- * indicates corresponding author
Ldb1-nucleated transcription complexes function as primary mediators of global erythroid gene activation
Li L1, Freudenberg J1, Cui K, Dale R, Song SH, Dean A, Zhao K, Jothi R*, Love PE*.
Blood, 121(22):4575-85, 2013. (*Co-corresponding authors; 1Co-first authors)
Diverse stresses dramatically alter genome-wide p53 binding and transactivation landscape in human cancer cells
Menendez D1, Nguyen TA1, Freudenberg JM1, Mathew VJ, Anderson CW, Jothi R*, Resnick MA*.
Nucleic Acids Research, 2013 [Epub ahead of print]. (*Co-corresponding authors; 1Co-first authors)
Genome-wide characterization of menin-dependent H3K4me3 reveals a specific role for
menin in the regulation of genes implicated in MEN1-like tumors
Agarwal SK, Jothi R.
PLoS ONE, 7(5): e37952, 2012.
Interplay between gene expression noise and regulatory network architecture
Chalancon G, Ravarani R, Santhanam B, Martinez-Arias A, Aravind L, Jothi J, Babu MM.
Trends in Genetics, 2012 (to appear).
of Tet1-dependent 5-hydroxymethylcytosine levels impairs LIF/Stat3
signaling and results in loss of embryonic stem cell identity
Freudenberg JM1, Ghosh S1, Lackford BL1, Yellaboina S, Zheng X, Li R, Cuddapah S, Wade PA, Hu G, Jothi R.
Nucleic Acids Research, 2011. (*Co-corresponding authors; 1Co-first authors)
esBAF facilitates pluripotency by conditioning the genome for LIF/STAT3 signaling and by regulating Polycomb function
Ho L, Miller EL, Ronan JL, Ho WQ, Jothi R*, Crabtree GR*
Nature Cell Biology, 13(8):903-913, 2011. (*Co-corresponding authors)
Genome-wide analyses of GATA3-mediated gene regulation in distinct T cell types
Wei G1, Abraham BJ1, Yagi R1, Jothi R1, Cui K, Sharma S, Narlikar L, Northrup DL, Tang Q, Paul WE, Zhu J, Zhao K.
Immunity, 35(2):299-311, 2011. (1Co-first authors)
Nuclear adaptor Ldb1 regulates a transcriptional program essential for the maintenance of hematopoietic stem cells
Li L, Jothi R, Cui K, Lee JY, Cohen T, Gorivodsky M, Tzchori I, Zhao Y, Hayes SM, Bresnick EH, Zhao K, Westphal H, Love PE.
Nature Immunology, 12(2):129-136, 2011.
DOMINE: a comprehensive collection of known and predicted domain-domain interactions
Yellaboina S, Tasneem A, Zaykin DV, Raghavachari B, Jothi R.
Nucleic Acids Research, 39(Database issue):D730-735, 2011.
Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture
Jothi R*, Balaji S, Wuster A, Grochow JA, Gsponer J, Przytycka TM, Aravind L, Babu MM*.
Molecular Systems Biology, 5:294, 2009. (*Co-corresponding authors)
An embryonic stem cell chromatin remodeling complex,
esBAF, is an essential component of the core pluripotency transcriptional
Ho L1, Jothi R1, Ronan JL, Cui K, Zhao K, Crabtree GR.
Proc Natl Acad Sci (PNAS), 106(13):5187-5191, 2009.
Global analysis of the insulator binding protein
CTCF in chromatin barrier regions reveals demarcation of active and repressive
Cuddapah S1, Jothi R1, Schones DE, Roh TY, Cui K, Zhao K
Genome Research, 19(1):24-32, 2009. (1Co-first authors)
of in vivo protein-DNA binding sites from ChIP-Seq data
Jothi R, Cuddapah S, Barski A, Cui K, Zhao K
Nucleic Acids Research, 36(16):5221-31, 2008.
- Genome-wide identification of in vivo
protein-DNA interactions from ChIP-Seq data
- A database of protein domain interactions
- Performs co-evolutionary analysis of domains
in interacting proteins to predict domain pair(s) that is most likely
mediating a given protein-protein interaction
Identifies orthologous set of genes. Can also be used to perform
hierarchical clustering of orthologous (or homologous) genes to identify
out-paralogs from automatically generated set of ortholgous genes (eg:
MORPH - Predicts
protein interaction partners between members of two protein families
that are known to interact (for example: Ligands and Receptors).
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This file was last updated on Dec 10, 2013.