Molecular Cell, Volume 46

Supplemental Information

Integrative Genomics Identifies the Corepressor

SMRT as a Gatekeeper of Adipogenesis

through the Transcription Factors C/EBPand KAISO

Sunil K. Raghav, Sebastian M. Waszak, Irina Krier, Carine Gubelmann, Alina Isakova, Tarjei S. Mikkelsen, and Bart

Deplancke

Figure S1. SMRT KD Enhances Adipogenesis in 3T3-L1 Cells

Figure S1, Related to Figure 6 and 7. SMRT KD Enhances Adipogenesis in 3T3-L1

Cells

(A) Fold-change of SMRT mRNA expression in SMRT KD as compared to shRNA

control cells as measured by qPCR. Error bars represent the standard deviation

observed in three replicate experiments.

(B) Western blot to determine SMRT protein levels in the nuclear extracts of SMRT KD

compared to shRNA control cells. The figure constitutes a representative western

blot of three replicate experiments.

(C) Densitometric analysis of SMRT protein bands as observed in the western blot.

(D) Oil red-O staining of SMRT KD and shRNA control cells at D6. We observed

significantly enhanced differentiation in control versus SMRT KD cells, consistent

with previous results (Yu et al., 2005) and confirming the efficacy of the SMRT KD.

Figure S2. ChIP-qPCR Validation of Randomly Selected SMRT Peaks Derived from

ChIP-Seq Data

Figure S2, Related to Figure 1. ChIP-qPCR Validation of Randomly Selected SMRT

Peaks Derived from ChIP-Seq Data

(A) ChIP-qPCR for 15 randomly selected SMRT peak regions using SMRT KD and

shRNA control 3T3-L1 pre-adipocytes. The results shown are representative of two

ChIP-qPCR replicate experiments. Isotype match rabbit antibody and two genomic

regions not bound by SMRT were used to determine the non-specific ChIP

enrichment (see Supplemental Experimental Procedures for more experimental

detail and the list of primers used for qPCR).

(B) ChIP-qPCR for 25 randomly selected SMRT peak regions to validate the decrease in

SMRT binding after differentiation induction at D1. Isotype match rabbit antibody is

used to estimate the non-specific enrichment by beads used for ChIP and the

average enrichment (or lack thereof) of two genomic regions not bound by SMRT in

ChIP-Seq is used to subtract the non-specific ChIP enrichment by the SMRT

antibody (see Supplemental Experimental Procedures for more experimental detail

and the list of primers used for qPCR).

Figure S3. Position of De Novo Identified Motifs with Respect to SMRT Peak

Maxima and Further Validation of KAISO DNA Binding at SMRT Promoter-

Proximal Sites in 3T3-L1 Cells

Figure S3, Related to Figures 2 and 3. Position of De Novo Identified Motifs with

Respect to SMRT Peak Maxima and Further Validation of KAISO DNA Binding at

SMRT Promoter-Proximal Sites in 3T3-L1 Cells

(A) Positional distribution of de novo motifs with respect to SMRT peak maxima (see

Figure 2A for more details on motif statistics).

(B) SMRT tag density at regions bound by C/EBPβ at D0 and occupied by pro-

adipogenic TFs at 4h.

(C) Graph showing linear regression lines fitted to MITOMI data points corresponding to

each tested KAISO target probe sequence (Table S4D; see Supplemental

Experimental Procedures for more details). The data shown are representative of

three MITOMI replicate experiments (i.e. independent microfluidic chips).

(D) Fold decrease in Kaiso mRNA expression as determined by qPCR in KAISO KD as

compared to shRNA control cells. Error bars represent the standard deviation from

three replicate experiments.

(E) Western blot for NCoR1 and KAISO protein in NCoR1 antibody immunoprecipitated

cell lysate samples from pre-adipocytes (D0) and differentiated (D6) 3T3-L1 cells.

The presented western blot constitutes representative data from three replicate

experiments.

(F) SDS-PAGE followed by western blot for KAISO protein in SMRT antibody immuno-

precipitated cell lysate samples from shRNA control (empty vector treated), KAISO

KD, NCoR1 KD, and SMRT KD pre-adipocyte 3T3-L1 cells. Densitometric analyses

for detected KAISO bands are shown below the western blot panel. The presented

western blot constitutes representative data from two replicate experiments.

(G) SMRT ChIP in SMRT KD, KAISO KD, and shRNA control cells at promoter-

proximal SMRT binding sites containing a KAISO motif.

(H) KAISO ChIP-qPCR (using a KAISO-specific antibody from Abcam, cat no.: ab12723)

for 15 selected SMRT-bound promoter-proximal regions with a KAISO motif in

comparison to 15 SMRT-bound promoter-proximal or -distal regions lacking such a

motif. Error bars represent the standard deviation observed in two replicate

experiments.

Figure S4. Control Experiments to Examine the Significance of Open Chromatin

and Histone Mark Enrichment within SMRT-Bound Regions

Figure S4, Related to Figure 4. Control Experiments to Examine the Significance

of Open Chromatin and Histone Mark Enrichment within SMRT-Bound Regions

(A-E) Enrichment of randomized SMRT peaks within DNase I hypersensitive sites (A),

and H3K27ac (B), H3K27me3 (C), H3K4me1 (D), and H3K4me3 (E) marked

regions (see Supplemental Experimental Procedures for more details).

Figure S5. SMRT-Bound Regions Show Increased Chromatin Accessibility 24h

after 3T3-L1 Differentiation Induction and hence after SMRT Release

Figure S5, Related to Figure 4. SMRT-Bound Regions Show Increased Chromatin

Accessibility 24h after 3T3-L1 Differentiation Induction and hence after SMRT

Release

(A) Contour plot showing the dynamic changes in SMRT binding (as RPKM) and DNaseI

hypersensitive changes (i.e., chromatin accessibility) at all SMRT-bound regions in

pre-adipocytes (D0) and during differentiation (at 2h, D1, and D6). DHS data was

used from (Siersbaek et al., 2011). The degree of chromatin accessibility is

measured in terms of peak height observed at DNase I hypersensitive sites.

Horizontal and vertical line levels were arbitrarily chosen.

(B) Contour plot showing the dynamics of chromatin accessibility at SMRT D0 promoter-

proximal peak regions enriched for the KAISO motif.

Figure S6. Transcriptional Dynamics of All SMRT-Bound Genes

Figure S6, Related to Figure 5. Transcriptional Dynamics of All SMRT-Bound

Genes

(A-B) RNA pol II occupancy at promoters (-30 to +300 bp relative to TSS) of all

proximally or distally bound SMRT target genes over the course of terminal

adipogenesis.

(D-E) Gene body RNA pol II occupancy of all proximally or distally bound SMRT target

genes over the course of terminal adipogenesis.

(C-F) Randomly selected control genes show low promoter and gene body RNA pol II

densities.

Figure S7. KAISO KD Cells Exhibit Accelerated Cell Cycle Progression during the

Early Mitotic Clonal Expansion Phase of Terminal Adipogenesis

Figure S7, Related to Figure 6. KAISO KD Cells Exhibit Accelerated Cell Cycle

Progression during the Early Mitotic Clonal Expansion Phase of Terminal

Adipogenesis

(A-B) Propidium iodide (PI) staining-based FACS analysis of KAISO KD (A) and shRNA

control (B) cells during the first 24h after induction of differentiation. The presented

figure constitutes representative data from three replicate experiments.(C) Histograms

indicating the percentage of KAISO KD and shRNA control cells at each cell cycle

phase (G0/G1, S, and G2/M) during the first 24h after differentiation induction

(**P<0.01, *P<0.05; two-sided t-test). Error bars show the standard error of the mean

from three replicate experiments.

Figure S8. Simplified, Schematic Model of the Molecular Mechanisms Underlying

the Involvement of SMRT in Terminal Adipogenesis

Figure S8. Simplified, Schematic Model of the Molecular Mechanisms Underlying

the Involvement of SMRT in Terminal Adipogenesis

M indicates methylated DNA.

Supplemental Experimental Procedures

3T3-L1 Cell Culture and Differentiation

Mouse embryonic fibroblast-adipose like cells (cell line 3T3-L1) obtained from ATCC

were maintained in Dulbecco‟s modified Eagle‟s medium (DMEM, Invitrogen) containing

10% fetal calf serum (FCS; Amimed), 1X antibiotic solution (Invitrogen) and the cultures

were incubated at 37°C and 5% CO2. Cells were sub-cultured in 1:5 into new petri-

plates when they were 75-80% confluent. 3T3-L1 pre-adipocytes at 2 days post-

confluence were differentiated into adipocytes using differentiation inducing cocktail of

1µM Dexamethasone (Dex), 0.5mM isobutyl-methyl-xanthine (IBMX) and 167nM insulin

in DMEM with 10% FCS. After two days of induction with differentiation medium, cells

were washed with cell culture grade 1X phosphate buffered saline (PBS) and complete

medium containing 167nM insulin was added. Two days thereafter, fresh DMEM

medium containing FCS was added to the cells and at day six, cells were stained with

oil red-O to estimate the extent of differentiation into mature fat cells.

Chromatin Immunoprecipitation of SMRT, NCoR1, and RNA Polymerase II

Cells were collected from pre-adipocytes (D0) and at five distinct time points after

induction of differentiation (2h, D1, D4, and D6). The cells were washed two times with

1X PBS and cross-linked using 1% formaldehyde for 10 min at room temperature

followed by quenching the reaction using 125mM glycine for 5 min. After quenching, the

petri-plates were placed on ice, cells were scraped using a cell scraper and collected in

falcon tubes. The cells were then washed three times using cold 1X PBS and cell

pellets were stored at -80°C until further use. The cells were lysed in nuclei extraction

buffer (50mM HEPES-NaOH pH 7.5, 140mM NaCl, 1mM EDTA pH 8.0, 10% glycerol,

0.5% NP-40, 0.25% TritonX-100) supplemented with a protease inhibitor tablet (Roche)

and phosphatase inhibitors (5mM NaF, 1mM β-glycerol phosphate and 1mM sodium

orthovanadate) for 10 min at 4°C while shaking to isolate the nuclei. The isolated nuclei

were then washed using protein extraction buffer (200mM NaCl, 1mM EDTA pH 8.0,

0.5mM EGTA pH 8.0, 10mM Tris-HCl pH 8.0) supplemented with a protease inhibitor

tablet (Roche) and phosphatase inhibitors (5mM NaF, 1mM β-glycerol phosphate and

1mM sodium orthovanadate) at room temperature for 10 min. Washed nuclei were

resuspended in chromatin extraction buffer (1mM EDTA pH 8.0, 0.5mM EGTA pH 8.0,

10mM Tris-HCl pH 8.0 and 1% TritonX-100) supplemented with protease and

phosphatase inhibitor tablets (Roche) and incubated for 20 min on ice. The chromatin

was fragmented using a Bioruptor (Diagenode) sonicator for 80 min using high

amplitude and 30s ON & 30s OFF cycles to obtain 200-500 bp-sized fragments. A

cooling unit was used to circulate the cold water during sonication to avoid de-

crosslinking because of overheating. The fragmented chromatin was centrifuged at

17,000xg for 10 min and then clear supernatant was collected in chilled 15ml falcon

tubes. The DNA concentration of the chromatin was estimated using a NanoDrop and

the sonicated chromatin was diluted with ChIP dilution buffer (1mM EDTA pH 8.0,

10mM Tris-HCl pH 8.0 and 1% TritonX-100 containing protease and phosphatase

inhibitors) to get 100 µg/ml of chromatin for each IP. BSA and ssDNA (Salmon Sperm

DNA) -preblocked protein-A sepharose (80 µl/IP) beads were added to the samples and

incubated for 2h to remove non-specific- binding chromatin. To the supernatant, 5 µl/IP

rabbit polyclonal anti-SMRT antibody (Abcam, cat no.: ab-24551), anti-NCoR1 (Abcam,

cat no.: ab-24552), or RNA Pol-II antibody (Santa Cruz, cat no.: sc9001) was added to

immuno-precipitate the chromatin complex at 4°C overnight. After the overnight

incubation, 50µl blocked beads were added to each sample and incubated for 90 min at

4°C to pull down the respective antibody-chromatin complexes. The beads were then

washed four times with low salt wash buffer (20mM Tris-Cl pH 8.0, 150mM NaCl, 2mM

EDTA pH 8.0, 0.1% SDS, 1% TritonX-100) followed by two washes with high salt wash

buffer (20mM Tris-Cl pH 8.0, 500mM NaCl, 2mM EDTA pH 8.0, 0.1% SDS, 1% TritonX-

100), lithium chloride wash buffer (10mM Tris-Cl pH 8.0, 0.25 M LiCl, 1mM EDTA pH

8.0, 1% NP-40, 1% sodium deoxycholate) and tris-EDTA (TE) buffer (10mM Tris-Cl pH

8.0, 1mM EDTA pH 8.0). After removing the wash buffer completely, protein-bound

chromatin complexes were eluted from beads for 30 min using elution buffer (100mM

sodium bicarbonate and 1% SDS in milliQ water). The eluted chromatin was then

reverse-crosslinked by incubating the eluted supernatant at 65°C overnight on a heat

block after adding 8µl of 5M NaCl. The next day, DNA was purified from the reverse-

crosslinked chromatin by proteinase and RNase digestion followed by purification using

Qiagen DNA purification columns. The purified DNA was eluted in 50µl of Qiagen

elution buffer.

ChIP-Seq

Multiplex libraries were prepared using barcoded adapters (see Table SE1 below) for

each sample following an Illumina recommended protocol with slight modifications. In

brief, ChIP-DNA fragments were end-repaired using an End-IT DNA end repair kit

(Epicentre Technologies, Madison, WI, USA) followed by the addition of an „A‟ base and

ligation of bar-coded adapters. The ligated DNA fragments were separated on a 2%

agarose gel to select 200-400 bp-sized DNA fragments and DNA was subsequently

isolated from gel slices using a Qiagen gel extraction kit. The gel-extracted DNA was

then amplified for 17 cycles by PCR using high fidelity Phusion hot start polymerase

(NEB). The concentration and quality of purified amplified DNA were estimated

respectively using a Qubit dsDNA high sensitivity kit (Invitrogen) and a Bioanalyzer

2100 (Agilent). After the quality confirmation, the DNA libraries were sequenced on an

Illumina Genome Analyzer-II (Genomics sequencing facility, CIG, UNIL, Lausanne).

Pass-filtered reads from the Illumina‟s analysis pipeline were used for further analysis.

Table SE1. Barcoded Adapters Used for Preparing Sequencing Libraries

Adapter Bar-

code

Modification Sequence (5' - 3')

Seq_1F GTAT None ACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAT

Seq_1R GTAT 5' phosphate TACAGATCGGAAGAGCTCGTATGCCGTCTTCTGCTTG

Seq_2F CATT None ACACTCTTTCCCTACACGACGCTCTTCCGATCTCATT

Seq_2R CATT 5' phosphate ATGAGATCGGAAGAGCTCGTATGCCGTCTTCTGCTTG

Seq_3F ACGT None ACACTCTTTCCCTACACGACGCTCTTCCGATCTACGT

Seq_3R ACGT 5' phosphate CGTAGATCGGAAGAGCTCGTATGCCGTCTTCTGCTTG

Seq_4F TGCT None ACACTCTTTCCCTACACGACGCTCTTCCGATCTTGCT

Seq_4R TGCT 5' phosphate GCAAGATCGGAAGAGCTCGTATGCCGTCTTCTGCTTG

SMRT ChIP-Seq Data Handling and Processing

Raw tags were barcode-sorted and trimmed using the fastx-toolkit

(http://hannonlab.cshl.edu/fastx_toolkit/) and aligned to the mm9 genome assembly

using BWA with default settings. Reads with low mapping quality were removed

(minimum mapping quality –q 10) as well as PCR duplicates using rmdup from the

samtools suite. SMRT libraries from each time point were three times randomly down-

sampled to four million unique tags after mapping. Each set of down-sampled libraries

was merged to create a single library consisting of ~20M tags, which was later used for

identifying peaks (see below).

SMRT Peak Calling

Peaks were called using the QuEST 2.4 algorithm with a bandwidth of 40 bp and a

region size of 400 bp. An input library with ~20M tags was used as a negative control. A

score threshold of 15 was chosen together with the stringent peak calling parameter set,

i.e., rescue-fold as well as enrichment-fold of three. Peak calling was repeated for the

three down-sampled merged libraries, and peak regions were combined, while peak

maxima were all retained, but when closer than 100 bp to each other, only the highest-

scoring peak was retained. Values of the QuEST kernel bandwidth were selected,

because default parameters did not yield satisfying results in terms of defining binding

regions for SMRT based on manual inspection of the resulting peaks. Specifically,

SMRT peaks tended to be wider (480-880 bp) than the default allowed kernel bandwidth

for transcription factors; therefore we chose a larger value. In addition, we based the

selection of the score threshold on the enrichment profiles of SMRT-positive compared

to SMRT-negative control regions as assessed by ChIP-qPCR as well as manual

inspection and saturation analyses. This allowed us to exclude regions with low signal

to noise ratios, while including regions that proved reproducibly positive based on ChIP-

qPCR even if their overall enrichment was only low to moderate.

NCoR1 DNA Binding Enrichment at SMRT-Bound Regions

Sequencing reads were aligned similar to how SMRT reads were processed as

described above. SeqMINER software version 1.2.1 was used to cluster SMRT peaks

according to both the NCoR1 ChIP-Seq signal at the two time points D0 and D4 at

these locations as well as input with libraries down-sampled to 4M each.

Temporal Classification of SMRT Peaks

The seqMINER software version 1.2.1 was used with default settings to determine the

temporal DNA occupancy behavior of SMRT at peaks predicted from the single merged

libraries. Using the peak maxima as a base, the down-sampled library of each time

point was used to cluster peaks according to their raw tag enrichment profile across

differentiation. In 10 clusters, we observed either SMRT sites with predominant binding

at D0, or sites with similar binding profiles throughout differentiation (i.e., D0, 2h, D1,

D4, and D6).

Annotation of SMRT Peaks to Putative Target Genes

SMRT peaks were assigned to the nearest transcription start site (TSS) using the

RefSeq gene annotation (UCSC, refGene table, accessed 02/08/11). Peaks were

considered promoter-proximal when less than +/-1kb away from the TSS and promoter-

distal otherwise.

De Novo Motif Identification within SMRT Peaks

We performed de novo motif analysis on sequences around proximal and distal SMRT

peak maxima (+/-100bp) separately for D0-specific and all-time point sites, using the

software package MEME. We restricted the identification of motifs to 15 with a minimum

and maximum length of 5 and 25 bp, respectively. Obtained motifs were filtered

according to E-value (<1E-4) and motif occurrence among input sites (>5%). Passed de

novo motif PWMs were compared against known PWMs deposited in TRANSFAC,

JASPAR, and UNIPROBE using the TOMTOM motif comparison software

(http://meme.sdsc.edu/meme/cgi-bin/tomtom.cgi).

Binding Site Overlap between SMRT and Adipogenic TFs

We obtained genome-wide DNA binding locations of relevant adipogenic TFs from

previously published ChIP-Seq datasets (see below) and determined the co-occurrence

with SMRT sites by intersecting whole peak regions (min. >1 bp overlap criteria). We

obtained raw ChIP-Seq datasets for RXR and PPARfrom the NCBI Gene Expression

Omnibus (GEO) website (accession: GSE13511) and re-analyzed both datasets.

Libraries were aligned against the mm9 genome using the BWA short-read aligner,

quality filtered (minimum mapping quality –q 10), PCR-duplicates were removed with

samtools, and peaks at distinct time points of adipogenesis (D0, D1, D2, D3, D4, and

D6) were called with QuEST 2.4 using parameters for TF binding sites, i.e. a ChIP score

threshold of 50, a bandwidth of 30 and a region size of 300 (default settings for TF

identification). These parameters yielded results, which closely mirrored the results

communicated in the respective paper. Published genome-wide C/EBP (D0, 2h, 4h,

and D2), C/EBP (D0 and 4h), RXR (4h), STAT5a (4h), and glucocorticoid receptor

(GR, 4h) binding sites in 3T3-L1 cells were obtained from the NCBI GEO database

(accession: GSE27826).

Human KAISO ChIP-Seq Data Analysis

Publicly available genome-wide ZBTB33/KAISO ChIP-Seq binding sites from a

lymphoblastoid cell line (GM12878) were downloaded from the ENCODE website

(http://hgdownload.cse.ucsc.edu/goldenPath/hg18/encodeDCC/wgEncodeHudsonalpha

ChipSeq/; Myers lab, Hudson Alpha Institute). Peaks from two technical replicates were

joined and only overlapping peaks were retained for further analysis, thus resulting in

1,253 peak regions. de novo motif analysis was performed with MEME (min. motif width

= 5; max. motif width = 25) using sequences extracted from whole peak regions of all

1,253 peaks and highest enriched (top 25% or 313) peaks, respectively. Synteny

between SMRT peaks enriched with the palindromic CGCG motif and human KAISO

binding sites enriched with the palindromic motif (as identified by de novo motif finding

using all 1,253 binding sites) was assessed with the UCSC liftOver tool

(http://genome.ucsc.edu/cgi-bin/hgLiftOver) requiring that at least 10% of bases (within

a KAISO peak region) must map to the mm9 genome assembly.

MITOMI Analysis

KAISO target sequence synthesis and labeling

To validate and estimate the relative affinity of KAISO to a series of DNA motifs derived

from human KAISO ChIP-Seq data as well as SMRT peaks, sequences containing the

respective motifs (10 bp) flanked by 10 bp up- and down-stream were designed. The 10

bp flanking sites were specifically chosen not to contain any “CG” sites as to not

confound the methylation assay (see Table S4D for all DNA sequences). Specifically,

the 10 bp upstream flank was chosen from the mouse Mre11a gene promoter, which

contains the full palindromic “TCTCGCGAGA” motif and which is also bound by SMRT.

The 10 bp upstream flank was also used as the downstream flank. We also flanked

each fragment by a “CCC” clamp at the 5‟ end to prevent degradation and by a

complementary sequence at the 3‟ end to allow primer hybridization. Target sequences

of interest were purchased as single stranded DNA from Life Technologies and double

stranded DNA was generated according to a previously described procedure (Maerkl

and Quake, 2007) except that the labeled, generic primer used here (5‟-Cy5-

GTGGTACCTCCAAGGG-3‟ ordered from Integrated DNA Technologies (IDT)) was

designed such as it does not contain any CG di-nucleotieds. The double stranded,

labeled DNA sequences were purified using a Qiagen nucleotide purification kit and

then methylated (when appropriate) using a CpG methylase kit (New England Biolabs,

Cat no: M-0226L) according to a protocol recommended by the vendor. Each reaction

was subsequently purified using a Qiagen nucleotide purification kit and eluted in a final

volume of 30 µL. 20 µL of 1.5% BSA in dH2O was added to each reaction and the entire

volume was then transferred to a 384-well plate to generate an 8-fold dilution series for

each DNA sequence. All target DNA sequences in BSA aqueous solution were

deposited onto epoxy-coated glass substrates (CELL Associates) using Qarray

(Genetix) or SpotBotIII (ArrayIt) microarrayers with a 946MP4 pin configuration

(European Biotek Network SPRL).

Preparation and synthesis of KAISO protein

The open-reading frame of KAISO (RIKEN clone E130014G12) was cloned into

pDONR221 Entry vector using Gateway® technology and sequence-verified.

Subsequently, it was sub-cloned into the pMARE vector to enable in vitro expression as

described previously (Hens et al., 2011). For each experiment, KAISO was expressed in

vitro using the TnT® SP6 High-Yield Wheat Germ Protein Expression kit (Promega).

MITOMI analysis of KAISO-DNA interactions

All MITOMI experiments were performed on 768-unit devices as described previously

(Maerkl and Quake, 2007). The molds for MITOMI devices and devices itself were

fabricated at the Center of MicroNanoTechnology (CMI) Core Facility at the EPFL.

Surface chemistry was performed as described in (Hens et al., 2011). Data extraction

was performed according to (Maerkl and Quake, 2009). The detected surface-bound

DNA values (RFU) were normalized against surface-immobilized protein amounts and

plotted separately for each target sequence. To assess the differences in DNA binding

of KAISO to different DNA probes, linear regression lines were fitted to the data points

corresponding to each target sequence separately (see Figure S3C for a representative

MITOMI chip). Only data points with free DNA below 10,000 RFUs were considered in

order to remain in the linear part of the saturation curve. The slopes of the regression

curves within one MITOMI chip were scaled relative to the slope of the sequence for

which KAISO showed strongest affinity (i.e., methylated palindrome). The averages and

standard deviations of the relative affinity values from three MITOMI replicates are

shown in Figure 3G of the main manuscript.

RNA Polymerase II Transcription Dynamics

Genome-wide maps of RNA pol II occupancy during 3T3-L1 adipogenesis (D0, D1, D2,

D3, D4, and D6) were obtained from the NCBI GEO database (accession: GSE13511).

Raw reads were aligned with bwa against the mm9 genome assembly, mapping quality

filtered (MAQ >10), and PCR duplicates were removed with samtools. Tags were

counted within RefSeq transcript bodies (+300 bp relative to the TSS until the transcript

end) and near the promoter (-30 to +300 bp relative to TSS). Gene body and promoter

counts were later transformed into a reads per kilo base per million mapped reads

(RPKM) measure to compare the occupancy at different days of differentiation.

Testing for Differential RNA Pol II Occupancy between SMRT KD and shRNA

Control Cells

Genome-wide RNA pol II occupancy maps were generated in SMRT KD and shRNA

control cells using RNA pol II ChIP-Seq following the method as described above for

ChIP-Seq. Raw reads (~32M) were barcode-trimmed, mapped with BWA against the

mm9 genome assembly, low quality reads were filtered out (MAQ <10), and PCR

duplicates were removed with Samtools resulting in ~12.4M (SMRT KD) and ~12.6M

(shRNA control) unique reads, respectively. Tags were counted within RefSeq-based

gene body coordinates (i.e., +300 bp relative to TSS and until end of gene) to quantify

gene transcription levels. Total gene body tag counts were down-scaled in the shRNA

control condition by multiplying and rounding total gene counts by a global scaling

factor, which is the ratio of the total number of mapped tags between both conditions.

Gene body transcription levels were normalized by applying quantile normalization

(normalize. quantiles function in the affy package, R, www.r-project.org) on log2-

transformed gene body densities (i.e., tags/kb), and back-transformed as well as

rounded to obtain again gene body tag count values. Transcripts that featured in both

conditions a gene body RPKM value less than a library size adjusted input experiment

(representing background) or a gene body RPKM value less than one (representing low

transcription) were filtered out. We tested for differential transcription between the

SMRT KD and shRNA control condition with an exact two-sided binomial test (p=0.5),

using the normalized gene body tag count values, for each transcript separately. P-

values were adjusted for multiple hypotheses testing using Benjamini & Hochberg FDR

correction (function p. adjust in R). Transcripts were considered as differentially

transcribed between the two conditions if the transcription level was >1.5-fold higher or

lower in one or the other condition with an FDR cutoff < 1%.

Analysis of Open Chromatin and Histone Modification Data

DNase I hypersensitivity (DHS) and histone modifications (i.e., H3K4me1, H3K4me2,

H3K4me3, H3K27ac, and H3K27me3) in pre-adipocytes, during the early and late

stages of terminal fat cell differentiation were obtained from the NCBI GEO database

(accessions: GSE27826 and GSE21365). SMRT-bound sites were classified to be

enriched in DHS or histone modifications if they overlapped by at least 1 bp with the

latter sites. Randomization tests were performed to evaluate for background

enrichments of SMRT within functional sites by shifting conservatively SMRT peaks

randomly 10 kb upstream or downstream, this way preserving local DNA/chromatin

properties, and testing for overlap with DHS or histone modified sites.

Functional Annotation of SMRT Targeted Genes

We used the DAVID Bioinformatics Resource 6.7 (http://david.abcc.ncifcrf.gov/) to

obtain a functional annotation (i.e., Panther biological process) of SMRT-bound genes

using an FDR cutoff of 10%. We performed this analysis separately for genes linked to

SMRT peaks with distinct spatial-temporal properties (Table S2).

Permutation Test for Enrichment in SMRT Targets among Differentially

Transcribed Genes Between SMRT KD and shRNA Control Cells

To evaluate the significance of our results regarding the over-representation of

differentially transcribed genes among SMRT-bound genes, we randomly permutated

SMRT peaks within each chromosome 100 times, re-annotated each peak to the

nearest gene TSS, and computed the overlap between the permutation-based- and

observed gene list.

Lentivirus-Mediated Knockdown of SMRT, NCoR1, and KAISO

The lentiviral mammalian vector pLKO.1 containing SMRT, NCoR1 and Kaiso-specific

shRNAs (three shRNAs per target were used) along with control shRNA (empty pLKO.1

plasmid or GFP shRNA) were obtained from Sigma. Viral particles containing shRNA

expression plasmid were generated in 293T cells using a CalPhos mammalian

transfection kit (Clontech) according to (Barde et al., 2001). 293T cells were transfected

with transfer plasmids containing SMRT or Kaiso-specific shRNAs or control shRNAs

along with packaging plasmids (Pcmvr8.74 and PMd2.G) and the next day, the culture

medium was refreshed and after 24h, viral particles along with medium were collected

in 50 ml falcon tubes. Viral particle-containing medium was filtered with 0.45µm

centricon syringe filters and preserved at -80°C in small aliquots. 3T3-L1 cells at a

density of 5 X 103 cells were transduced with viral particles containing a pool of three

shRNA expression plasmids in 10cm petri-plates. After 72h of viral incubation, the

medium was changed to a puromycin selection medium (2 µg/ml puromycin in complete

DMEM medium) to select the stably transduced cells. After every two days, puromycin

selection media was changed and the stably transduced cells were selected for one to

two weeks before performing actual experiments. The control shRNA- transduced cells

were treated similarly.

RNA Isolation and Quantitative PCR

Total RNA was isolated using a Qiagen RNAeasy plus mini kit according to the

recommended protocol. RNA concentration was estimated using a nanodrop and 2.5µg

of total RNA was used for single strand cDNA synthesis (single strand cDNA synthesis

kit, Invitrogen). cDNA was diluted 1:100 using nuclease free water and 1.5µl was used

for each qPCR reaction. The qPCR was performed using custom oligos designed with

in-house developed GetPrime software (Gubelmann et al., 2011). Power SYBR Green

Master Mix (Applied Biosystems) used for the qPCR reaction and PCR amplification

was monitored with Applied Biosystems 7900HT Fast Real-Time PCR System. A

Hamilton Liquid Handling Robotic System was used to assemble the 384-well plates.

Primers were optimized for linear and single product amplification. Primers used for

qPCR are listed at the end of this document.

SMRT ChIP-qPCR

We randomly selected 15 peaks/sites from the ChIP-Seq results for verification of

SMRT binding and reduced enrichment in SMRT KD cells. qPCR was performed as

described above in the qPCR section. Similarly, to validate that KAISO is recruiting

SMRT at promoter-proximal regions, we performed ChIP-qPCR for 12 selected genes

targeting SMRT DNA binding sites containing a KAISO motif in KAISO KD, SMRT KD,

and shRNA control cells. ChIP was performed as described above for SMRT ChIP-Seq.

Percent enrichment vs Input was calculated using the standard equation:

100*2^(Corrected Input Ct - Ct of IP sample). Input was adjusted / corrected to 100% as

1% of IP sample was used as Input DNA. Primers used for qPCR are listed at the end

of this document. Average enrichment of two genomic regions without SMRT peaks

based on ChIP-Seq data were used as negative controls to estimate or subtract the

non-specific enrichment by the antibody, and an isotype match rabbit antibody was

used to control the non-specific enrichment by the beads used for ChIP.

KAISO ChIP

KAISO ChIPs were performed according to the method described by (Reddy et al.,

2009) with few modifications. In brief, the cells were fixed and quenched with glycine as

described above in the ChIP section. The cell layers were then washed three times with

cold 1x PBS. After washing the cells with PBS, they were lysed and scraped in Farnham

lysis buffer (5mM PIPES at pH 8.0, 85mM KCl, 0.5% NP-40) with added protease

inhibitor. The cells were then centrifuged at 200xg for 5min at 4°C and the crude nuclear

extract stored at -80°C. During ChIP, an aliquot of 30 X 106 nuclei was suspended in

1.5ml of RIPA buffer (1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS in PBS at pH

7.4) and the chromatin was fragmented using a Bioruptor sonicator for 30 min using

high amplitude and 30s ON & 30s OFF cycles to obtain 200-500 bp-sized fragments

and the samples were centrifuged at 17000xg for 15 min to remove debris. The

chromatin was then diluted using RIPA buffer and added to dynal magnetic beads

(Sheep-anti mouse IgG conjugated Dynabeads, Invitrogen, Cat no: 110-31) pre-treated

with 5µg specific anti-mouse antibody for KAISO (Santa Cruz, Cat no: sc-23871 or

Abcam, Cat no: ab12723) for immune-precipitation of specific complexes. The samples

were incubated overnight at 4°C on a rotator, then magnetic beads were washed 5

times with lithium chloride wash buffer (100 mM Tris at pH 7.5, 500 mM LiCl, 1%NP-

40,1% sodium deoxycholate) and finally once with 1X TE buffer (10 mM Tris-HCl at pH

7.5, 0.1 mM Na2EDTA). The chromatin complex was eluted using elution buffer (1%

SDS, 0.1 M NaHCO3) for 1 h at 65°C using an Eppendorf thermo-mixer. The chromatin

was then de-crosslinked overnight at 65°C and ChIP DNA purified using a Qiagen PCR

purification kit and eluted in 50 µl of elution buffer. To validate the KAISO enrichment at

SMRT bound regions, 15 SMRT regions positive for KAISO motif were selected along

with 15 SMRT bound promoter and candidate enhancer regions lacking a discernible

KAISO motif. Two intergenic genomic regions were selected as negative controls. For

each qPCR reaction, 1.5 µl of 1/10 diluted ChIP DNA was used.

H3K9me2 ChIP-qPCR

Chromatin preparation from 3T3-L1 cells followed by ChIP was performed as described

above for KAISO ChIP except that Sheep-anti rabbit IgG conjugated dynabeads

(Invitrogen, Cat no: 112.03D) coated with anti-rabbit H3K9me2 antibody (Abcam, Cat

no: ab-1220) were used for IP. For estimating the enrichment of this histone mark, the

same genomic regions validated for KAISO binding were evaluated using qPCR.

Immunoprecipitation (IP)

The cells were grown and differentiated as described above. At the D0 and D6 time

points, the cells were washed twice with PBS containing protease and phosphatase

inhibitors, trypsinized, and collected by centrifugation at 1000xg for 10 min. The cells

were lysed by passing them through a 26-guage needle 25 times in Triton X-100 IP

buffer (20mM Tris-Cl, pH. 7.4, 150mM NaCl, 10% glycerol, 1% Triton X-100, 1mM

EDTA, 1mM DTT) supplemented with protease and phosphatase inhibitors (Roche).

Lysates were cleared by centrifuging at maximum speed in a tabletop refrigerated

centrifuge for 10 min. Antibodies (10 μg/IP) against SMRT (Abcam, ab-24551), NCoR1

(Abcam, ab-24552), and isotype matched rabbit antibody (Millipore) were added to the

cell lysate and incubated for 3h at 4°C while rotating. Protein-A sepharose beads (50µl)

that were washed and pre-blocked with BSA were then added to the samples and

further incubated for 2h to pull down the protein-antibody complex. The beads were

then washed 5 times with Triton X-100 IP buffer and once with 1X TE buffer. After the

last wash, beads containing immune-precipitated protein complexes were boiled in 60μl

of 2X SDS sample loading buffer. Proteins present in the eluted supernatant were

resolved on a 7.5% SDS-PAGE gel, and then transferred to a nitrocellulose membrane.

Immunoblotting was performed with anti-KAISO antibody (Abcam, ab-12723). To

confirm the SMRT and NCoR1 pull-down by the respective antibodies, the same blots

were also developed for SMRT and NCoR1. To further validate the presence of KAISO

in a SMRT-containing complex, SMRT IP in KAISO KD, NCoR1 KD, SMRT KD and

Empty vector (shRNA control) 3T3-L1 preadipocyte cells followed by western blotting for

KAISO was performed as described above. Densitometric analysis of the bands

detected in western blot was performed using AlphaDigidoc-1201 software. The stable

knockdown 3T3-L1 cells for these genes were made as detailed in the lentivirus-

mediated gene knockdown section.

Cell Cycle Analysis using FACS

The standard method of Propidium Iodide (PI) based FACS analysis was used to

observe the changes in cell cycle progression. 3T3-L1 cells (SMRT KD, KAISO KD, and

shRNA control cells) were cultured in six-well plates as described above. At specific

time points (-72h, 0h, 16h, 18.5h, 20h, 22h and 24h), the cells were trypsinized, washed

two times with 1X PBS and cooled on ice for 30 min. The cells were then fixed by drop-

wise addition of 70% ethanol, while gently vortexing the cells to avoid clumping. Before

PI staining, fixed cells were washed three times with 1X PBS and 200µl of staining

buffer (50µg/ml PI, 0.01% triton X-100, 10µg/ml RNase-A in PBS) was subsequently

added to each sample. The samples were then incubated for 45 min at 37 ºC for

staining and RNA degradation as RNA might interfere with the PI staining of DNA.

10,000 live-gated cells from each sample were then analyzed to determine their cell

cycle phase using an Accuri-6 flow cytometer (settings: FSC-SSC gate for live cell

singlet selection and FL2A histogram for PI-stained cell signal intensity). FlowJo

analysis software was then used to calculate the proportion of G0/G1, S, and G2/M cells

in each sample. Significant differences in the number of cells at a specific cell cycle

phase between the different samples were determined using a student‟s two-sided t-

test.

Effect of the PPARγ Ligand Rosiglitazone on the Differentiation Capacity of SMRT

KD 3T3-L1 Cells

An equal number of SMRT KD and shRNA control cells (50,000/well) were sub-cultured

into six-well plates and grown to confluence. Two days post-confluence, the cells were

differentiated using MDI medium (normal differentiation induction medium), 100nM &

250nM PPARγ ligand-containing medium, 167nM insulin and 1µM dexamethasone-

containing medium. After two days, 167nM insulin-containing DMEM medium with 10%

FCS was added to each well which was changed to DMEM medium containing 10%

FCS on the fourth day of differentiation. At D6, the wells were washed two times with 1X

PBS and the cells were fixed using 10% formalin in PBS. The accumulated fat droplets

inside cells were then stained using oil red-O to estimate the extent of differentiation.

List of Primers Used for ChIP-qPCR and Gene Expression Analyses

Gene Primer Sequence

control1_ChIP_F CACACAGCTGACCTCCAGAA

control1_ChIP_R AGTGGCAAGGTCTCTGCTTC

control2_ChIP_F GGGTGCTAGCCTTCCTGACT

control2_ChIP_R TCCAAGGTTCTCCCGACATA

Ampk1_ChIP_F CGGTGCTGGTGGCTAGAG

Ampk1_ChIP_R TCCTCCTAAAATGGCTACAAGG

Cdk12_ChIP_F GTGCCGTTTCGGTTTAATCT

Cdk12_ChIP_R CTAGCCTCCGCCTCACAC

Atf2_ChIP_F CATCCCTACAACCTCCAAGC

Atf2_ChIP_R GGCAGGACCATGAATTAGTGA

Atf4_ChIP_F CGCAGACCCCTGATCCTA

Atf4_ChIP_R GGCGAGTCACCTAAACCTCA

Atf6_ChIP_F CAGATCCACTCACCCCAGTC

Atf6_ChIP_R CCATGGAGTCGCCTTTTAGT

Atf7_ChIP_F ACTCGTGGGGCTGAGTTG

Atf7_ChIP_R ACTCAAGCCACGCTCACA

Camk1d_ChIP_F AAAGCACCACGTGTACAAACA

Camk1d_ChIP_R CTCTTTGCTGGGCTACCTTG

Chmp4b_ChIP_F CCTTTGACCTCTGCGAGACT

Chmp4b_ChIP_R AAGCCGGGAGTCTGAGTTTT

Crebzf_ChIP_F GGGGGTGGAAACTAGGTTTTAT

Crebzf_ChIP_R CTTTGCGGTGATGTCATAGG

Hdac4_ChIP_F CAGGGCAGTTAGGCACTCTC

Hdac4_ChIP_R TTGCCCTCAAAGCCTCAG

Hnrnpa2b1_ChIP_F ACTAACGCGTCTCCGCTTAC

Hnrnpa2b1_ChIP_R AGGAGAGTGTAGGCCCTTCC

Med1_ChIP_F GATCGCGAGATTAATCGTGTT

Med1_ChIP_R GAGACTTTGGTGCGGTTCC

Meis1_ChIP_F CCGACCAGAATGCTAGAACC

Meis1_ChIP_R TTGTGTAAGACGCGACCTGT

Ndufa11_ChIP_F CCAGTGTCATCGCAAGACC

Ndufa11_ChIP_R CTGACCTTTGCTTCCAGACC

Por_ChIP_F TTCCGAGGAGAGGATGAGG

Por_ChIP_R AAATCTCTGCTGTTGGTACGG

Rxra_ChIP_F AGTGAAACTTCCCGGAGGA

Rrxa_ChIP_R GAGAGGTGCCAGAGAACAGG

Suv39h1_ChIP_F CCTGCGCAGTAGCAAAGC

Suv39h1_ChIP_R GGCTAGCAATATGACTGACAAGG

Tle3_ChIP_F GCCGCCACATTATTTTGTTAC

Tle3_ChIP_R AGCACGAGGTCTGAACTGC

Ncoa4_ChIP_F TGTCTGGGTCGGTCTAAGGT

Ncoa4_ChIP_R GCCACTCTCGTCCTTACCG

Map3k14_ChIP_F GGGCTTTGAGGCAAGACTAA

Map3k14_ChIP_R CAAGGACAAGTGGCTCACC

Arf3_ChIP_F GGGCTATGGCAGCTAGCAC

Arf3_ChIP_R CGGAGGTTCAGGACGTGT

Nkrf_ChIP_F AACCGGTCTCCAACTTCAAA

Nkrf_ChIP_R GCAGAGTGCGTCAATGAAGA

Ccnt1_ChIP_F CGACACCCCGTAGACGAA

Ccnt1_ChIP_R AGATAGTCCCGCCCACCT

Tipin_ChIP_F GCCGCTGTCTAGGTGAGGT

Tipin_ChIP_R GGGCTCCACTTCCAAAATCT

Pfkfb2_ChIP_F GAGCTTGGTGGCATTGTTG

Pfkfb2_ChIP_R AAGGGAAGGCTTTTAATTCACC

Hnrnpk_ChIP_F CAGAGGATAATGGCGTCTGC

Hnrnpk_ChIP_R CCCCTCACCACAGAGTGC

Ets1_ChIP_F TGTTGCTATGAAGGGGAGTGT

Ets1_ChIP_R CCCAGCTCAAAGACAACAAGA

Sirt1_ChIP_F AAGAGTGAGCCACACTTACGG

SIRT1_ChIP_R ACCTCTAGGTGGCGTCCAA

Aspn_gene_F TCGATTTGTTTCCAACATGTCC

Aspn_gene_R CCGATGTCAGACCTAGATCAG

Tle1_gene_F CTCAGGAACATCAACAACAGG

Tle1_gene_R CGATGATGGCATTCAACTCTG

Tnfaip6_gene_F CAACCCACATGCAAAGGAG

Tnfaip6_gene_R TACTCATTTGGGAAGCCCG

Trpv6_gene_F CTTGTGCCAAATAACCAGGG

Trpv6_gene_R CATCAGGTGTTGGAACATCAC

Wnt5a_gene_F ACGCTTCGCTTGAATTCCT

Wnt5a_gene_R CCCGGGCTTAATATTCCAA

Cebpα_gene_F AAACAACGCAACGTGGAGA

Cebpα_gene_R GCGGTCATTGTCACTGGTC

Six1_gene_F AAGGAAAGGGAGAACACCG

Six1_gene_R TTCTGGTCTGGACTTTGGG

Akt1_gene_F AGCTCTTCTTCCACCTGTC

Akt1_gene_R GAGGTTCTCCAGCTTCAGG

Kaiso_gene_F TGCTTGGGGTAGGACTCTGA

Kaiso_gene_R TGAATGTCTGTAGCAGAAATCAGTT

Smrt_gene_F CATGAAGGTCTACAAGGACC

Smrt_gene_R TGCATAAACTTCTCACGGA

Tgfβ3_gene_F AATTACTGCTTCCGCAACC

Tgfβ3_gene_R TTTCCAGCCTAGATCCTGC

Plin4_gene_F GAGGCCTTCCAGATGACAG

Plin4gene__R CACCATGGTGTTCAAGCTC

Srf_gene_F TGAAGAAGGCCTATGAGCTG

Srf_gene_R TATACACATGGCCTGTCTCAC

Twist1_gene_F AGCTACGCCTTCTCCGTCT

Twist1_gene_R TCCTTCTCTGGAAACAATGACA

Snai2_gene_F TGCAAGATCTGTGGCAAGG

Snai2_gene_R CAGTGAGGGCAAGAGAAAGG

Itga1_gene_F AAGGCAAATGGGTTCTTATTGG

Itga1_gene_R CAACTGGACACTTATAGACATCTC

Postn_gene_F GAGGTGGAGAAACAGGAGAG

Postn_gene_R CTTCTAGGCCCTTGAACCC

Mrps6_gene_F CGAGGAGGGTATTTCCTGG

Mrps6_gene_R CTAACCACGTCAATGTCTCG

Pten_gene_F TAACTGCAGAGTTGCACAG

Pten_gene_R CAAGATCTTCACAGAAGGGT

Coup-tf1_gene_F CCAAGCATGATGCTTGTGG

Coup-tf1_gene_R CTTCTCACATACTCCTCCAGG

Fzd4_gene_F CAACTTAGTGGGACACGAG

Fzd4_gene_R AAAGGAAGAACTGCAGCTG

Fzd8_gene_F TTGAAAGCACTGGCCTTTTAC

Fzd8_gene_R AGGTGACCTGTGGCCTTAAA

Egfr_gene_F TGGAGCTATGGTGTCACTG

Egfr_gene_R TGAGATGTCACTTGCTGGG

Ebf1_gene_F TACAGCAATGGGATACGGA

Ebf1_gene_R GGCCTTCATACACTATGGC

Id2_gene_F GAGACCTGGACAGAACCAG

Id2_gene_R ATTCAGATGCCTGCAAGGA

Foxc2_gene_F CGGCTAGGACTGGACAACTC

Foxc2_gene_R CTGACAGCTCGCATTGCTC

Ccdc99_ChIP_F CACTAACTCCACCTCAGCACAG

Ccdc99_ChIP_R CCGGCGCTTACTTAGCAG

Ddx20_ChIP_F GTGGACTCGGAGGTTGTCA

Ddx20_ChIP_R CCCCGCCTCAAGTCTAAATA

Mdh2_ChIP_F CAAGCTTCTTGCGCTTCTCT

Mdh2_ChIP_R GACTCCAACGACCTCCACTC

Psmd5_ChIP_F GAGATCTTACGGAGCGAAGC

Psmd5_ChIP_R GACCGCGTTGAGAAAGGAT

Mgmt_ChIP_F AATGGCAGTAAATTCTTCAATAAGC

Mgmt_ChIP_R GGCTCATTTTCTGTGCTGTTG

Med6_ChIP_F CAGTAAAGGCGATGACTACCG

Med6_ChIP_R TTTTGACCTCCCCGCTAAC

Med23_ChIP_F TCCAAACAGGTCGCAGTTC

Med23_ChIP_R GACAGCGCTGCTTGATCC

Nfatc3_ChIP_F CTCTGGCGCTTCTTGCTC

Nfatc3_ChIP_R ACCGACCTATCGCGTGAGT

Nr4a1_ChIP_F GGAGGGGAGGAGATCCTGT

Nr4a1_ChIP_R GGAGGGGGTGTTGTAAATCC

Runx2_ChIP_F GCGAAGGAATGTGTAAACAGG

Runx2_ChIP_R AGAGGCATTTTGCGTTGTG

Prkg1_ChIP_F AGCCTAGTGAAATGTGAACAGATG

Prkg1_ChIP_R AAGGAACTCTTGGCTTATTCCAT

Prkca_ChIP_F GTCCCGTGTTGTGATGAATG

Prkca_ChIP_R TTCCAACATGAACAGCAAGC

Rarβ_ChIP_F CCTCTGGGCAGCTGATACTT

Rarβ_ChIP_R GTGCAGGAAATGCCTTTTG

Med27_ChIP_F CATTTCTTTGTCATTCACTATTAAGCA

Med27_ChIP_R TGATCTCCATCTAGGGAAGTCAT

Pld1_ChIP_R GCATAGCCTCAGCTTCCTGT

Pld1_ChIP_R AATCTGTACAGTTGCCTTTCTAATCA

Supplemental References

Barde, I., Salmon, P., and Trono, D. (2001). Production and Titration of Lentiviral Vectors. In Current Protocols in Neuroscience (John Wiley & Sons, Inc.).

Gubelmann, C., Gattiker, A., Massouras, A., Hens, K., David, F., Decouttere, F., Rougemont, J., and Deplancke, B. (2011). GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR. Database, bar040.

Hens, K., Feuz, J.-D., Isakova, A., Iagovitina, A., Massouras, A., Bryois, J., Callaerts, P., Celniker, S.E., and Deplancke, B. (2011). Automated protein-DNA interaction screening of Drosophila regulatory elements. Nat Meth 8, 1065-1070.

Maerkl, S.J., and Quake, S.R. (2007). A systems approach to measuring the binding energy landscapes of transcription factors. Science 315, 233-237.

Maerkl, S.J., and Quake, S.R. (2009). Experimental determination of the evolvability of a transcription factor. Proceedings of the National Academy of Sciences 106, 18650-18655.

Reddy, T.E., Pauli, F., Sprouse, R.O., Neff, N.F., Newberry, K.M., Garabedian, M.J., and Myers, R.M. (2009). Genomic determination of the glucocorticoid response reveals unexpected mechanisms of gene regulation. Genome Research 19, 2163-2171.

Siersbaek, R., Nielsen, R., John, S., Sung, M.-H., Baek, S., Loft, A., Hager, G.L., and Mandrup, S. (2011). Extensive chromatin remodelling and establishment of transcription factor /`hotspots/' during early adipogenesis. Embo J 30, 1459-1472.

Yu, C., Markan, K., Temple, K.A., Deplewski, D., Brady, M.J., and Cohen, R.N. (2005). The Nuclear Receptor Corepressors NCoR and SMRT Decrease Peroxisome Proliferator-activated Receptor γ Transcriptional Activity and Repress 3T3-L1 Adipogenesis. Journal of Biological Chemistry 280, 13600-13605.