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Cell Reports, Volume 17 Supplemental Information Neuronal CTCF Is Necessary for Basal and Experience-Dependent Gene Regulation, Memory Formation, and Genomic Structure of BDNF and Arc Dev Sharan Sams, Stefano Nardone, Dmitriy Getselter, Dana Raz, Moran Tal, Prudhvi Raj Rayi, Hanoch Kaphzan, Or Hakim, and Evan Elliott

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Page 1: Dev Sharan Sams, Stefano Nardone, Dmitriy Getselter, Dana ... · PDF fileDev Sharan Sams, Stefano Nardone, Dmitriy Getselter, Dana Raz ... (mouse B-lymphoblasts CH12-LX ... mount sections

Cell Reports, Volume 17

Supplemental Information

Neuronal CTCF Is Necessary for Basal and

Experience-Dependent Gene Regulation, Memory

Formation, and Genomic Structure of BDNF and Arc

Dev Sharan Sams, Stefano Nardone, Dmitriy Getselter, Dana Raz, Moran Tal, Prudhvi RajRayi, Hanoch Kaphzan, Ofir Hakim, and Evan Elliott

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Supplemental Information

Neuronal CTCF is necessary for basal and experience-dependent

gene regulation, memory formation, and genomic structure of

BDNF and Arc.

Dev Sharan Sams1, Stefano Nardone

1, Dmitriy Getselter

1, Dana Raz

2, Moran Tal

2,

Prudhvi Raj Rayi3, Hanoch Kaphzan

3, Ofir Hakim

2, Evan Elliott

1

1 Bar Ilan University, Faculty of Medicine, Safed, Israel

2 The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University,

Ramat-Gan, Israel 3 University of Haifa, Faculty of Natural Sciences, Haifa, Israel

Corresponding Author (Lead contact):

Evan Elliott

Bar Ilan University Faculty of Medicine

8 Hanrietta Sold Street, Safed, 13215, Israel

email: [email protected]

phone: 972-72-264-4968

2nd phone: 972-50-767-1550

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Figure S1 related to Figure 1. GFAP and QKI in hippocampus of mice

Immunohistochemistry of mouse hippocampus stained for CTCF, Astrocyte marker

GFAP (a) and oligodendrocyte marker QKI (b). These are additional pictures from

experiment outlined in Figure 1.

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Figure S2 related to Figure 2. Conditional Knockdown of CTCF in the

hippocampus

a-b.) CTCF expression levels in the hippocampus of CTCF cKO mice. Knockdown of

CTCF revealed by real time PCR analysis of mRNA expression in hippocampus of

CTCF cko mice (a) with respect to wild type (n=6 per group; *p<0.00001 two tailed t-

test) and Western Blot analysis (b) of CTCF protein in wild type and CTCF cko

hippocampus. Error bars represent SEM. c.) Apoptosis in hippocampus of CTCF cKO

mice. TUNEL analysis revealed apoptosis in CTCF cko mice in the 13th postnatal

week, but not in the 10th or 11th postnatal week. Scale bar, 200 μm. d.) Degeneration

of hippocampus in week 14 in the CTCF cKO mice. Nissl Staining revealed a more

degenerated hippocampus in the 14 week CTCF cko mice compared to the 10 week

CTCF cko mice. Scale bar, 100 μm. e.) Golgi staining of hippocampus in week 10 in

the CTCF cKO mice. Representative Golgi images of neuron from hippocampus

(Dentate gyrus and CA1 region) used for the sholl analysis and dendritic length

measurement, as described in figure 2.

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Figure S3 related to Figure 4. Virus mediated knockdown of CTCF in the

hippocampus

a-b.) Injection of Cre/GFP expressing virus into the hippocampus (DG) of floxed

CTCF mice. Immunohistochemistry of mouse hippocampus (dentate gyrus) stained

for CTCF in mice injected with Cre/GFP expressing viruses (b), or GFP only

expressing viruses (a). These are additional pictures from experiment outlined in

Figure 4a, and are taken over two weeks after viral injection. Areas expressing GFP

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display knockdown in CTCF. GFP expression peaks a few days after infection, and

decreases significantly by two weeks after infection, when CTCF knockdown

becomes apparent. Therefore, not all infected cells in the area display GFP staining at

this time point. c-d.) Injection of Cre into floxed CTCF mice does not induce

apoptosis in the hippocampus. TUNEL staining was performed on floxed CTCF mice

that were sacrificed six weeks after stereotaxic injection of Cre expressing viruses to

the hippocampus. There is no difference in TUNEL staining between mice injected

with Cre/GFP expressing viruses (d), or GFP only expressing viruses (c). TUNEL

staining is visualized in red. Residual expression of GFP from the AAV-GFP and

AAV-GFP/Cre viruses are visualized in green. Low expression of green is due to the

transient nature of AAV-driven expression.

Figure S4 related to Figure 5. ChIP-seq distribution of CTCF relative to the

genome in the hippocampus

a.) CEAS results showing the distribution and enrichment of CTCF binding Peaks

relative to the genome background with respect to key genome features such as

specific chromosome, promoters, gene bodies, or exons. The P-value is given in

parenthesis (mouse genome Refseq mm9 annotation). b.) A snapshot of the DREME

de novo motif search displaying significant match to known CTCF motif.

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Figure S5 related to Figure 6. CTCF binding sites of Hdac3 and hdac7 in the

hippocampus and BDNF gene expression in hippocampus after fear conditioning

a.) Hdac3 and Hdac7 show enrichment for CTCF in hippocampus. Representative

Genome Browser images of Peaks of CTCF enrichment identified by ChIP-seq for

Hdac3 and hdac7 respective in hippocampus. b.) Total BDNF, but not BDNF exon 1,

displays activity-induced expression in wild type, but not CTCF cKO mice. Total

BDNF, but not BDNF exon 1, displays activity-induced expression in wild type, but

not CTCF cko mice. Real Time PCR analysis of hippocampal gene expression in WT

and CTCF cko animals subjected to fear conditioning context + shock (C+S), or

context alone (C). The pairing of context and shock increased gene expression of total

BDNF (n=6 per group; Two Way Anova; *p<0.05 Tukey test), but not BDNF

expressed from promoter 1. Error bars represent SEM.

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Figure S6 related to Figure 7. High-Order chromatin structure is visualized in

the genomic regions of Arc and BDNF in Hi-C data.

The high-order chromatin structure of BDNF and Arc genes are visualized in dataset

of 1 kb resolution Hi-C experimentation (mouse B-lymphoblasts CH12-LX). Data set

and juicebox software for data visualization were downloaded from

www.aidenlab.org/juicebox. Squares demarcate topogically associated domains in the

vicinity of the BDNF and Arc genes.

Table S1. List of Differentially expressed genes in CTCF cko hippocampus,

Related to Figure 5

Table S2. ChIP-seq CTCF peaks in mouse hippocampus, Related to Figure 5

Table S3. Genomatix analysis of the CTCF ChIP-seq peaks, Related to Figure 5

Table S4. Beta output of predicted gene targets and motifs, Related to Figure 5

Table S5. Primers sets of qPCR and 4c, Related to Figure 5-7, S2 and S5

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Experimental methods

Mouse Brain microdissection and RNA extraction

Immediately after decapitation, the brain was removed and placed into a 1 mm metal

matrix (Stoelting, cat# 51380). The brain was sliced using standard razor blades

(GEM, 62-0165) into 2 mm slices that were quickly frozen on dry ice. The

hippocampus was punched using a 13-gauge microdissection needle on each

hemisphere and stored in -80C. RNA extraction was performed using RNAeasy mini

kit (Qiagen, Valencia, CA, USA). RNA was reverse transcribed to cDNA using the

High Capacity RNA to cDNA kit (Applied Biosystems, Foster City, CA). cDNA was

then analyzed by quantitative RT-PCR.

RNA-seq bioinformatics

Adapters were trimmed from sequences using cutadapt tool (Martin 2011). Reads that

were shorter than 40 nucleotides or that mapped to rRNA sequences (using Bowtie

1.0.0) were removed. TopHat (v2.0.10) was used to align the remaining reads to the

mm10 genome. All libraries had at least 20 million uniquely aligned reads to the

genome. Read counting to Refseq genes was done with HTseq-count (version

0.6.1p1) using the intersection_strict option (Anders et al. 2015), followed by

differential expression analysis with DESeq2 using the options betaPrior FALSE,

cooks Cutoff FALSE and independent Filtering FALSE (1.6.3) (Anders et al. 2013).

Raw P values were adjusted for multiple testing using the procedure of Benjamini and

Hochberg. Gene ontology analysis on differentially expressed genes was performed

using the Toppgenetool (https://toppgene.cchmc.org/) (Chen et al. 2009).

ChIP-seq library preparation and bioinformatics

Sequencing of ChIP-seq was performed by the Nancy & Stephen Grand Israel

National Center for Personalized Medicine (G-INCPM), Weizmann Institute of

Science, Israel. 2.5-5.8ng of ChIP DNA was processed as previously described

(Blecher-Gonen et al. 2013). Libraries were evaluated by Qubit and TapeStation.

Sequencing libraries were constructed with barcodes to allow multiplexing of 6

samples on one lane. Between 20-49 million single-end 61-bp reads were sequenced

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per sample on Illumina HiSeq 2500 v4 instrument. Adapters were trimmed using the

cutadapt tool (Martin 2011). Following adapter removal, reads that were shorter than

40 nucleotides were discarded (cutadapt option –m 40). The reads were aligned

uniquely to the mouse genome (mm10) using bowtie (version 1.0.0) (Langmead et al.

2009). Bound regions were detected using MACS2 (version 2.0.10.20131216) (Zhang

et al. 2008). GREAT was used for assigning genomic regions to genes (McLean et al.

2010). CEAS (version 1.0.2) was used for obtaining statistics on ChIP enrichment of

genome features (on genome version mm9) (Shin et al. 2009) and Motif analysis was

performed using MEME-ChIP on peak summits that were extended by 150 bases to

each direction (Bailey et al. 2009) and Genomatix was used to identify

overrepresented TF families (http://www.genomatix.de). BETA was run in the BETA

plus mode that includes motif findings (Wang et al. 2013). ChIP-seq peaks were taken

from MACS2 analysis and RNA-seq data of differential expressed genes with

FDR<0.05 were considered.

Immunohistochemistry

Mice were perfused with saline for two minutes, followed with 4% paraformaldehyde

for at least five minutes. Brains were dissected, and then incubated in 30% sucrose for

at least two days, followed by slicing on a sliding microtome to produce 30 micron

floating slices. Slices were blocked for one hour in blocking solution (10% horse

serum, 0.3%triton and 1XPBS, and then incubated with primary antibodies (CTCF

(Millipore) 1:100; NeuN (Millipore) 1:200; GFAP and QKI (UC Davis/NIH

NeuroMab Facility) 1:200) overnight at room temperature. The following day, slices

were washed with incubated for 1 hour with secondary antibodies (alexa488 and cy3),

stained for five minutes with Hoechst (Sigma), and washed three times, followed by

mounting. Tunel staining: 30 μm thick floating sections of 4% paraformaldehyde

fixed mice brain were used to analyze apoptotic cells. The brain slices were processed

using the In Situ Cell Death Detection Kits (Roche Life Science) according to

manufacturer’s instruction. Before mounting, Hoechst (sigma) was added for 2 min,

and slices covered with mounting gel and coverslip. Nissl staining: Nissl staining was

performed using cresyl violet solution on floating brain slice. Brain slices were

defatted in xylene and stained with cresyl violet solution. Followed by dehydration in

graded alcohols (95% ethanol) and cleared with xylene before mounting. All

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immunohistochemistry images were taken on Zeiss LSM710 confocal microscope or

Zeiss AxioImager M2 and processed with Zen software.

Rapid Golgi Staining

Ten week old mice brains were dissected and immediately stained according to the

Rapid GolgiStain Kit (FD Neurotechnologies, Ellicott, MD, USA) protocol procedure.

The brain was sectioned into slices 150 μm thick and mounted. Images of whole-

mount sections of CA1 and DG hippocampal region were acquired using Zeiss

AxioImager M2. The dendritic length, sholl analysis and spine number were analyzed

using Imaris 7.3.2 software (Bitplane AG, Zurich, Switzerland) as described

previously (Schneider et al. 2014).

Real time PCR

Real-time PCR was performed on an ABI ViiA™ 7 RealTime PCR detection system

in 10 μl volume containing FastStart Universal SYBR Green Master (Roche) and

primers (S Table 5) at a concentration of 0.5 μM each. 10 ng of cDNA was dispersed

in each well, and all samples were tested in triplicates. PCR program consists of 15

minute activation phase at 95 degree Celsius, followed by 40 cycles at the following

temperatures: 10s of 94 degrees, 30s of 60 degrees. Real Time PCR data was

normalized to the housekeeping gene HPRT.

Video tracking analysis

All Behavioral experiments were recorded with the Panasonic WV-CL930 camera

and with the Ganz IR 50/50 Infrared panel. The recorded videos of all the experiments

were analyzed by the Ethovision XT 10/11 (Noldus) software.

Western blot

Brain tissue and/or peripheral tissue were homogenized in a tissue homogenate buffer

(50 mM Tris-HCl (pH 7.5), 150 mM KCl, 0.32 M sucrose, Protease inhibitor cocktail

(Sigma)). Protein concentrations were determined using Bradford reagent (Sigma).

Samples (30 μg) were subjected to SDS-PAGE and transferred onto a nitrocellulose

membrane. The membrane was blocked for 1 h in 1XPBS containing Tween 20 and 5

% non-fat milk followed by overnight incubation with a primary antibody in 5 %

BSA. The primary antibodies used were the following: anti-CTCF (1:3000

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(Millipore)) and anti-actin (1:3000 (Santa Cruz Biotechnology)). Next day, the

membrane was washed with 1XPBS and incubated with LI-COR dye-conjugated

secondary antibody for 1 h. Membranes was then scanned on the LI-COR Odyssey

scanner.

Rotarod test

Rotarod tests were used to study the locomotor activity. The test was conducted using

an accelerating Rotarod (MedAssociates, St. Albins, VT). The speed of the Rotarod

was set to 40 r.p.m. The amount of time each mouse spent on the rod was measured.

The latency to fall was recorded with a 300 s cutoff time.

References:

Anders, S. et al., 2013. Count-based differential expression analysis of RNA

sequencing data using R and Bioconductor. Nature protocols, 8(9), pp.1765–

1786.

Anders, S., Pyl, P.T. & Huber, W., 2015. HTSeq--a Python framework to work with

high-throughput sequencing data. Bioinformatics (Oxford, England), 31(2),

pp.166–169.

Bailey, T.L. et al., 2009. MEME SUITE: tools for motif discovery and searching.

Nucleic acids research, 37(Web Server issue), pp.W202-8.

Blecher-Gonen, R. et al., 2013. High-throughput chromatin immunoprecipitation for

genome-wide mapping of in vivo protein-DNA interactions and epigenomic

states. Nature protocols, 8(3), pp.539–554.

Chen, J. et al., 2009. ToppGene Suite for gene list enrichment analysis and candidate

gene prioritization. Nucleic Acids Research , 37(suppl 2), pp.W305–W311.

Available at: http://nar.oxfordjournals.org/content/37/suppl_2/W305.abstract.

Langmead, B. et al., 2009. Ultrafast and memory-efficient alignment of short DNA

sequences to the human genome. Genome biology, 10(3), p.R25.

Martin, M., 2011. Cutadapt removes adapter sequences from high-throughput

sequencing reads. EMBnet. journal, 17(1), p.pp-10.

McLean, C.Y. et al., 2010. GREAT improves functional interpretation of cis-

regulatory regions. Nature biotechnology, 28(5), pp.495–501.

Schneider, K. et al., 2014. ProSAP1 and membrane nanodomain-associated syndapin i

promote postsynapse formation and function. Journal of Cell Biology, 205(2),

pp.197–215.

Shin, H. et al., 2009. CEAS: cis-regulatory element annotation system. Bioinformatics

(Oxford, England), 25(19), pp.2605–2606.

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Wang, S. et al., 2013. Target analysis by integration of transcriptome and ChIP-seq

data with BETA. Nature protocols, 8(12), pp.2502–2515.

Zhang, Y. et al., 2008. Model-based analysis of ChIP-Seq (MACS). Genome biology,

9(9), p.R137.