Immunity, Volume 41

Supplemental Information

Distinct Epigenetic Signatures

Delineate Transcriptional Programs

during Virus-Specific CD8+ T Cell Differentiation Brendan E. Russ, Moshe Olshanksy, Heather S. Smallwood, Jasmine Li, Alice E.

Denton, Julia E. Prier, Angus T. Stock, Hayley A. Croom, Jolie G. Cullen, Michelle L.T.

Nguyen, Stephanie Rowe, Matthew R. Olson, David B. Finkelstein, Anne Kelso, Paul G.

Thomas, Terry P. Speed, Sudha Rao, and Stephen J. Turner

Inventory of Supplemental information. Methods: Description of materials and methods. Figure S1. Histone methylation patterns of constitutively expressed or repressed gene loci in virus-specific CTL. Mapping of genome wide H3K4me3 and H3K27me3 methylation distribution within the promoter region (defined as -3 kb/+1 kb of known TSS) within naïve, effector and memory CTL. Figure S2. Enumeration of histone sequence tag density for H3K4me3 and H3K27me3 within defined promoter regions of naïve, effector and memory CTL. Figure S3. Chip validation of sequence tag density for H3K27me3 within gene loci from naïve and effector CTL. Multi-dimensional scaling analysis of RNA-seq data for naïve, effector and memory CTL both in the resting state, and after 5hrs of peptide stimulation. Figure S4. Histone methylation patterns of gene loci demonstrated to be upregulated upon naïve OT-I T cell activation. Dynamics of novel bivalent gene loci during naïve OT-I CTL differentiation. Figure S5. Phenotypic and functional characteristics of recently activated naïve OT-Is. Bioanalyser plots of DNA fragment size from nuclei for sequential ChiP analysis. Supplementary Table 1. Enumeration of H3K4me3 and H3K27me3 sequence tags that mapped to promoter regions within naïve, effector and memory CTL. Available online. Supplementary Table 2. Log2 Fold change (FC) of differentially expressed genes between naïve, effector and memory OT-I CD8+ T cells after 5hrs of peptide stimulation. Available online. Supplementary Table 3. Gene list for the hierarchical cluster analysis for H3K4me3 and H3K27me3 enrichment within the promoter of T cell related gene loci.  Supplementary Table 4. Primer sequences for ChIP experiments for selected gene promoters. Supplementary Table 5. Primer sequences for chemokine mRNA quantitative PCR.

a" b"

Oaz1% Krt8%

Naive&

Effector&

Memory&

Supplementary Figure 1. a, b (related to Fig. 1). Histone methylation patterns of constitutively expressed or repressed gene loci in virus-specific CTL. ChIP-seq, using an Illumina HiSeq2000, was performed on naïve, effector and memory OT-Is for both H3K4me3 and H3K27me3 histone PTMs. Data were mapped back to the mouse genome (version mm10) and peaks determined using the MACS software package. Shown is the pattern of H3K4me3 (red, above line) and H3K27me3 (blue, below line) peaks within the promoter, gene body and 3’UTR regions of the Oaz1 housekeeping gene, or Krt8 gene within naïve, effector and memory OT-Is. (rel Panels c, d. Mapping of genome wide H3K4me3 and H3K27me3 methylation distribution within -3kb / +1 kb of known TSS within naïve, effector and memory CTL. ChIP-seq, using an Illumina HiSeq2000, was performed on naïve, effector and memory OT-Is for both H3K4me3 and H3K27me3 histone PTMs and mapped back to the mouse genome as described. The genome wide spatial distribution of H3K4me3 and H3K27me3 enrichment around the TSS of known promoters defined as -3kb / +1 kb of known TSS.

H3K4me3" H3K27me3"

Distance"from"TSS"(kb)":3K" :2K" :1K" +1K"0"

#seq

uence"tags" Naive"

Effector"Memory"

Naive"Effector"Memory"

c" d"

Supplementary Figure 2, (related to Fig. 1). Enumeration of gene promoters and gene bodies with distinct levels of H3K4me3 and H3K27me3 sequence tag deposition. (a-d) the number of H3K4me3 (a, b) or H3K27me3 (c, d) sequence tags within either gene promoters (a, c) or gene bodies (b, d) was determined then rank ordered. Cut offs were determined into those with low levels (green), intermediate levels (purple) or high levels (orange). (e, f) The number of gene promoters that exhibited changes in histone PTM levels (lo, int, hi) between naïve, effector and memory CTL subsets were quantified. Shown is the nubmer of gene promoters that demosntrated different patterns for H3K4me3 (e) or H3K27me3 (f). There was little change in levels observed within gene bodies (data not shown).

12000"

10000"

8000"

6000"

4000"

2000"

0"

#"of"gen

e"prom

oters"

Histone"PTM"paMerns" Histone"PTM"paMerns"

8000"

6000"

4000"

2000"

0"

H3K4me3" H3K27me3"

CumulaPve"window"

a" b"

c" d"

e" f"

10"

2"

8"

6"

4"

0"

Naïve"OTI"

D10"Effector"

1800"

600"

1500"1200"

900"

0"

300"

b"

Normalise

dH3K

27me3""

tag"coun

t/prom

oter"

Supplementary Figure 3. a, b (related to Fig 1 and 2). Validation and determination of sensitivity of H3K27me3 ChIP-seq data. (a) The number of H3K27me3 tag counts within the gene promoter (-3 kb to 1 kb either side of the TSS) was determined for gene loci identified as having differential patterns of H3K27me3 sequence tags between naive and effector OT-I (Figure 1 and Supplementary Table 1. (b) H3K27me3 ChIP was performed on naïve and in vitro activated CD8+ OTI T cells (day 10) and the degree of enrichment within a 400 bp region immediately upstream of the TSS. Data represent 3 individual biological replicates ±SE. Panel c. Multidimensional scaling analysis of RNA-seq data from virus-specific CTL. Naïve (CD44loCD62Lhi), effector (day 10 after infection) and memory (day 60 after infection) OT-I CTL were sort purified from secondary lymphoid tissues and RNA extracted either before (resting) or after 5 h of in vitro activation with 1 µM of OVA257 peptide (stimulated). mRNA levels were determined using RNA-seq and differential gene expression determined based on tag counts that mapped to exons. Data was transformed into Log2 fold change and multidimensional scaling analysis carried out as described in the supplementary methods. Shown in data for individual RNA-seq samples for naïve (green), effector (red) and memory (blue) CTLs both before (closed circles) an after (open circles) stimulation. Shown are the differences in transcriptional levels between each subgroup in two dimensions.

a"

ResPng" SPmulated" All"data"naive"effector"memory"

naive"effector"memory"

c"

Supplementary Figure 4a-e (related to Fig. 3). Histone methylation patterns of gene loci demonstrated to be upregulated upon naïve OT-I T cell activation. ChIP-seq, using an Illumina HiSeq2000, was performed on naïve, effector and memory OT-Is for both H3K4me3 and H3K27me3 histone PTMs. Data were mapped back to the mouse genome (version mm10) and peaks determined using the MACS software package. Shown is the pattern of H3K4me3 (red, above line) and H3K27me3 (blue, below line) peaks within the promoter, gene body and 3’UTR regions of the listed gene loci. Panels f-k (related to Fig. 5). Dynamics of novel bivalent gene loci during naïve OT-I CTL differentiation. (a-f) Shown is the pattern of H3K4me3 (red, above line) and H3K27me3 (blue, below line) peaks within the promoter, gene body and 3’UTR regions of gene loci that were bivalent in naïve OT-I CD8+ T cells, but resolved to H3K4me3+/H3K27me3- in effector and memory OT-I subsets.

Supplementary Figure 5a-d (related to Fig. 1, 2). Phenotypic and functional characteristics of recently activated naïve OT-Is. Naïve (CD44loCD62Lhi) OT-I CTL were sort purified from secondary lymphoid tissues and activated in vitro with 1 µM of OVA257 peptide for 5 or 24 hours. (a) Chemokine mRNA levels induced after 5 h of activation of naïve OT-I were determined by quantitative real-time PCR. Shown is the relative increase in mRNA levels for various chemokines when compared to naïve resting, OT-I CTL. (b-d) OT-I CTL were stained for co-expression of effector molecules (b) CD25 and CD69 (c) TNF-α and IFN-γ or (d) TNF-α and CCL3 either before (0 h) or after peptide stimulation (5 or 24 h). Panel e (related to Fig. 5). Bioanalyser analysis to validate DNA fragment size from naïve OT-I for sequential ChIP (a) Sort purified naïve OT-I CD8+ T cells (CD44loCD62Lhi) were fixed with 0.6% PFA, sonicated with samples then run on a bioanalzyer to determine the average fragment size before sequential ChIP (Fig 5, j-m). Shown is the trace histogram showing that the majority of DNA fragments are below 200 bp in length. Peaks 1 and 5 are size markers (b) Panel shows the density plot of the bioanalyzer lane with the 10 kb marker in purple.

e"

Supplementary Table 3 (related to Fig. 2). Gene list for the hierarchical cluster analysis for H3K4me3 and H3K27me3 enrichment within the promoter of T cell related gene loci. Gene Name Heirarchical Cluster

group Referencea

Bcl11b Cluster 1 1 Sell Cluster 1 2 Ets1 Cluster 1 3 Bcl6 Cluster 1 4 Ccr9 Cluster 1 5 Gzma Cluster 1 6 Fasl Cluster 1 7 Itgae Cluster 1 8 Prf1 Cluster 1 9 Id2 Cluster 1 10

Cd44 Cluster 1 11 CD27 Cluster 1 12 GzmK Cluster 1 13 Runx3 Cluster 1 14

Tox Cluster 1 15 Prdm1 Cluster 2 16 Gzmb Cluster 2 17 CCR7 Cluster 2 18 Ifng Cluster 2 19

IL2Ra Cluster 2 20 Xcl1 Cluster 2 21 Ccl4 Cluster 2 22 Bcl2 Cluster 2 23 Tnf Cluster 2 24

Klrg1 Cluster 2 25 Ccl5 Cluster 2 26 Ctla4 Cluster 2 27 Ccl3 Cluster 2 28 Il2 Cluster 2 29 Spn Cluster 2 30

Gata3 Cluster 2 31 Bmi1 Cluster 3 32 Irf4 Cluster 3 33 Irf8 Cluster 3 34

Tbx21 Cluster 3 35 CD69 Cluster 3 36 Foxo1 Cluster 3 37

Id3 Cluster 3 38 Eomes Cluster 3 35 Bcl2l11 Cluster 3 39

aReferences((

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36.( Shiow,(L.R.!et!al.(CD69(acts(downstream(of(interferonBalpha/beta(to(inhibit(S1P1(and(lymphocyte(egress(from(lymphoid(organs.(Nature(440,(540B544((2006).(

37.( Rao,(R.R.,(Li,(Q.,(Gubbels(Bupp,(M.R.(&(Shrikant,(P.A.(Transcription(factor(Foxo1(represses(TBbetBmediated(effector(functions(and(promotes(memory(CD8(+)(T(cell(differentiation.(Immunity(36,(374B387((2012).(

38.( Yang,(C.Y.!et!al.(The(transcriptional(regulators(Id2(and(Id3(control(the(formation(of(distinct(memory(CD8+(T(cell(subsets.(Nature!immunology(12,(1221B1229((2011).(

39.( Pellegrini,(M.,(Belz,(G.,(Bouillet,(P.(&(Strasser,(A.(Shutdown(of(an(acute(T(cell(immune(response(to(viral(infection(is(mediated(by(the(proapoptotic(BclB2(homology(3Bonly(protein(Bim.(Proceedings!of!the!National!Academy!of!Sciences!of!the!United!States!of!America(100,(14175B14180((2003).(

(

Supplementary Table 4 (related to Figs. 3-5, Fig. S3). Primer sequences for ChIP experiments. Gene$ Forward$(5'>3')$ Reverse$(5'>3')$ Location*$ Reference$

Afmid$ CCTGGAGGAACTTGTCTTCG% GAAGAAATCTGGCGCTCAAC% +65%to%+176% This%study%Atf6$ CGGAGGCAAACTATCTCACC% GTGCTGAAATCCTCGTAGGG% 3177%to%361% This%study%Blimp1$ CCAACCTGCCCTTAGGTATG%% AGGCAGCTACAATCCGTCTC%% −99%to%−48% This%study%CCL3$ GGGCATATGGCTTCAGACAC%% AGCAGGTGACAGAGGGTGAG%% −93%to%−0% This%study%Ccl4$ CCCAACCCTTGTCTTAGGC% GCTGATCTGAGTTGGGAACC% 357%to%+2% This%study%CCL5$ GACAACAGCTCCCTGCTACC%% CAGGATGACTCCCTCTCTGG%% −317%to%−200% This%study%Eomes$ GCAGGGAGCTTGTAAAGACG%% TTTGAAGTCTGCGAACATGG%% −276%to%−384% This%study%GzmA$ TTCCCTAGGAGGCTACAAACC% TGAGAGTGCAAAGGATGTGG% 3%197%to%3%30% This%study%GzmB$ GGCTACAAACCCCACCCTAT% GAAAACTCCTGCCCTACTGC% 3%192%to%3%30% Ref.%1%GzmK$ GCTTTGAAACCTTGGGTGTG% AGGGCTTCGGTGTTAAGGAG% −156%to%−6% This%study%HoxHA11$ AGGAGAAGGGGTTCCTTCAA% CTCCGCGGTTTGTCAATAAT%% −883%to%−758% Ref.%2%Ifng$ AGAGCCCAAGGAGTCGAAAG% CACCTCTCTGGCTTCCAGTT% −269%to%−2% Ref.%3%Il2ra$ ACAGACTGAGAGGCCTGAGC% ATCAGGATGGAGGAGGGAAC% −99%to%−48% This%study%IRF4$ CTGTAGTCGGGCAGAAGGAG% GGTCCGCTATCTCAGCATTC% −138%to%−45% This%study%IRF4$ CTGTAGTCGGGCAGAAGGAG% GGTCCGCTATCTCAGCATTC% 3138%to%345% This%study%IRF8$ AGAGGCTCTCCAAACCTGAAC% TCCGAGAAATCACTTTTGCAC% −363%to%−182% This%study%KLRG1$ GTTTACTGCAGCGTCCACAC%% ATACACACGGACTCCCAAGC%% −287%to%−202% This%study%Sema7a$ CGAGGGAAGTGGAACTGAAG% AGAACCCAGCTGCAAAGAAG% 3292%to%3205% This%study%Tbx21$ GAATTCGCGCTGTATTAGCC%% GCCTTTGCTGTGGCTTTATG%% −107%to%−10% This%study%Tmem163$ ACAAGGATTGCACCTTGTCC% CATTTAAGGGCAGCAGATCC% 3216%to%3131% This%study%TNF$ GTAGGGCCACTACCGCTTC% AGACGGCCGCCTTTATAGC% −133%to%−12% Ref.%3%Ttc26$ AACACACGGAACCAAGAAGC% GAGTTGCCACATCCACACAG% 3109%to%+8% This%study%Ttc39b$ TTACTTCGCCCAGAGGACAG% TTCTTGACACAGCGACTTGG% 3478%to%3366% This%study%Xcl1$ GACCACACCACCTCATTTCC% TCGGATCTTCCATCCTGAAG% −215%to%−137% This%study%1Location is size of genomic region targeted measured from the transcriptional start site of the annotated gene.

References

1. Juelich, T. et al. Interplay between chromatin remodeling and epigenetic changes during lineage-specific commitment to granzyme B expression. Journal of Immunology 183, 7063-7072 (2009). 2. Young, M.D. et al. ChIP-seq analysis reveals distinct H3K27me3 profiles that correlate with transcriptional activity. Nucleic acids research 39, 7415-7427 (2011). 3. Denton, A.E., Russ, B.E., Doherty, P.C., Rao, S. & Turner, S.J. Differentiation-dependent functional and epigenetic landscapes for cytokine genes in virus-specific CD8+ T cells. Proc Natl Acad Sci U S A 108, 15306-15311 (2011).

Supplementary Table 5(related to Fig. S5). Primer sequences for chemokine mRNA quantitative PCR.

!Target' Forward'primer'(5'>3')' Reverse'primer'(5'>3')' Product'

length'Ref'

Ccl1% TGCTGCTGGCTGCCGTGTGG% TTGAGGCGCAGCTTTCTCTACC% 198% This%study%Ccl2% TCTCTTCCTCCACCACCATGC% AGCTTCTTTGGGACACCTGCTG% 206% This%study%Ccl3% TCTCCACCACTGCCCTTGC% AGGCAGTCGGGGTGTCAGC% 96% This%study%Ccl4% ACACCTCCCGGCAGCTTCAC% AGAAGCATCAGGGCTGAGGAGG% 231% This%study%Ccl5% CCTCGTGCCCACGTCAAGG% TGGCACACACTTGGCGGTTCC% 97% This%study%Ccl6% ATCCTTGTGGCTGTCCTTGG% TGATGCCCGGCTTGATGCAC% 202% This%study%Ccl7% TCTGCCACGCTTCTGTGCC% AACAGCTTCCCAGGGACACCG% 178% This%study%Ccl8% TGCCCCATGGAAGCTGTGG% ACGCAGCCCAGGCACCATC% 226% This%study%Ccl9% TACTGCCCTCTCCTTCCTCATTC% TCCGTGAGTTATAGGACAGGCAGC% 179% This%study%Ccl11% ACCATGCAGAGCTCCACAGC% TCTTCTTGGGGTCAGCACAGATC% 238% This%study%Ccl12% TGGCTGGACCAGATGCGGTG% CTTCCCGGGGACACTGGCT% 124% This%study%Ccl17% TGCTGCCTGGATTACTTCAAAGG% AGCCCTGGCGTCTCCAAATGC% 220% This%study%Ccl19% AGACCAGCCCTGGGTGGATCG% TGGCTGGGTTAGGTCTGGGAC% 187% This%study%Ccl20% CGGTGGCAAGCGTCTGCTC% AGTTGCTTGCTGCTTCTGCCTGG% 83% This%study%Ccl21% ATCCCGGCAATCCTGTTCTC% GGTTCTGCACCCAGCCTTC% 82% This%study%Ccl22% ACTACATCCGTCACCCTCTGC% TAGCTTCTTCACCCAGACCTGC% 146% This%study%Ccl24% TACGATCGTTGCCGGCCTCC% TGATGAAGATGACCCCTGCC% 185% This%study%Ccl25% AGGCACCAGCTCTCAGGACC% TGGGCATGGACAACCGGCATC% 154% This%study%Ccl27% ACATGGAACTGCAGGAGGC% ACACAGACACTGCGCCGAGC% 79% This%study%Cxcl1% ATCCAGAGCTTGAAGGTGTTGC% AAGGCAAGCCTCGCGACC% 90% This%study%Cxcl2% AGTTTGCCTTGACCCTGAAGC% AGGCTCCTCCTTTCCAGG% 94% This%study%Cxcl3% TCACCACAGCCCTTCGCAC% TCACCGTCAAGCTCTGGATGG% 229% This%study%Cxcl4% GTCGCTGCGGTGTTTCGAG% ATAGGGGTGCTTGCCGGTCC% 277% This%study%Cxcl5% TTGGAGGTGATCCCTGCAGGTC% ATCACAGGAGCTTCTGGATCCAG% 101% This%study%Cxcl7% TGCGCTGGCTCCCCTTACAG% CATTTGGGTCCAGGCACG% 205% This%study%Cxcl9% TGAAGTCCGCTGTTCTTTTCC% AGTGGATCGTGCCTCGGCTG% 123% This%study%Cxcl10% GTCCTAATTGCCCTTGGT% TCTTGCTTCGGCAGTTAC% 119% This%study%Cxcl12% ATCGCCAGAGCCAACGTCAAGC% TGCCCTTGCATCTCCCACG% 226% This%study%Cxcl13% AGGCTCAGCACAGCAACGC% ACCATTTGGCACGAGGATTCAC% 244% This%study%Cxcl14% AAGCCAAAGTACCCACACTGCG% TACCTGGACATGCTCTTGGTGG% 65% This%study%Cxcl15% ACATGGCTGCTCAAGGCTGG% TGGGACTGCTATCACTTCCTTTCTG% 200% This%study%Cxcl16% ACTGCAGCCATGGCCTATGTG% ACGAGCCTGCTGCCCTACC% 172% This%study%Cxcl17% AAGCCACGGGGACCAACACC% TGATCACAGGGACACTGCTTCC% 147% This%study%Cx3l1% TGACCTCACGAATCCCAGTGGC% TCTTGGACCCATTTCTCCTTCG% 136% This%study%Xcl1% AGTCTGCTGCCTCACCCCAT% AACTGGCAGCCGCTGGGTTTG% 98% This%study%

Gapdh% CCAGGTTGTCTCCTGCGACTT% CCTGTTGCTGTAGCCGTATTCA% 133% This%study%

!

Russ$et$al.,$2014$Supplemental$Methods$ 1$Related to Experimental Procedures.

Processing of RNA-Seq data: RNA seq was carried out as described in supplementary methods.

Data quality was checked with fastqc software. Paired end RNA-Seq data was aligned to Mouse

mm10 genome using TopHat (with Bowtie2). Only concordant pairs with mapping quality > 10

were kept. The number of reads assigned to each gene was found using Bioconductor R package.

Count data was analysed using edgeR Bioconductor package (GLM formulation). Before doing this

genes which did not have >= 3 counts in every sample for at least one group were filtered out.

Genes were declared DE if they had FDR < 0.05 and log2 FC > 1.

Processing of ChIP-seq data. Data quality was checked with fastqc software and it was found to

be of good quality. Then it was aligned to mm10 mouse genome (NCBI 38) using bowtie2 aligner

(http://bowtie-bio.sourceforge.net/bowtie2/index.shtml). Only reads with mapping quality of 30 and

above were kept (filtering was done using SAMtools (http://samtools.sourceforge.net). Peaks were

found using MACS version 1.4 software (http://liulab.dfci.harvard.edu/MACS/ - see Zhang$et$ al,$2008)$without input and with default settings. Only 1 read was kept at every location. Peaks were

assigned to gene promoters using BEDTools (http://bedtools.readthedocs.org/en/latest/). Only

(mm10) genes which had unique TSS (according to RefSeq) were considered and promoters were

defined from 3 Kb upstream of TSS to 1 Kb downstream of TSS, where TSS is based on RefSeq

(and up/down-stream is strand-dependent). Similarly, gene bodies were defined from 1 Kb

downstream of TSS till the end of the gene.

RNA-seq: RNA was extracted from sorted naïve, effector OT-I CTLs (~106) using 1 mL TRIzol

reagent (Invitrogen), followed by chloroform extraction and isopropanol precipitation. Extracted

RNA was treated recombinant DNAse I (Roche) according to the manufacturers instructions. RNA

was then purified using the RNeasy MinElute Cleanup columns (Qiagen). For memory OT-I CTL,

RNA was extracted from Trizol suspensions using the Zymo Research Direct-zol RNA miniprep

kit, treated with 10 U DNAse for 20 min at RT and then concentrated using the Qiagen RNeasy

MinElute clean up kit. Purified RNA quality checked using the Nano Total RNA kit on an Agilent

2100 Bioanalyzer. We then used Illumina’s TruSeq RNA v2 sample preparation protocol according

to manufacturers instructions for generation of RNA-seq libraries. Briefly, this protocol invovled

the following steps. i) cDNA Synthesis: mRNA was purified via oligo(dT) beads followed by

fragmentation using divalent cations and heat. The 1st strand cDNA synthesis was performed using

random primers, followed by 2nd strand cDNA synthesis. ii) cDNA library preparation. cDNA

fragments were DNA blunt end repaired followed by addition of 3' adenylation of DNA fragment.

Sequencing adapters were then ligated to the ends utilising T-A pairing of adapter and DNA

Russ$et$al.,$2014$Supplemental$Methods$ 2$fragments. This was then followed by PCR amplification of the library. The cDNA libraries were

run on a Illumina HiSeq2000 generating the following number of reads for naïve, effector and

memory subsets (in the resting state, or after 5 h of peptide stimulation):

Resting + 5h Stimulation

Sample 1 95 million 122 million

Naive Sample 2 91 million 86 million

Sample 3 79 million 74 million

Sample 1 69 million 62 million

Effector Sample 2 100 million 95 million

Sample 3 51 million 53 million

Memory Sample 1 45 million 50 million

Sample 2 37 million 36 million

Processing of RNA-seq data: Data quality was checked with fastqc software. Paired end RNA-Seq

data was aligned to Mouse mm10 genome using TopHat (with Bowtie2). Only concordant pairs

with mapping quality > 10 were kept. The number of reads assigned to each gene was found using

Bioconductor R package. Count data was analysed using edgeR Bioconductor package (GLM

formulation). Before doing this genes which did not have >= 3 counts in every sample for at least

one group were filtered out. Genes were declared DE if they had FDR < 0.05 and log2 FC > 1.

Multidimensional Scaling (MDS) as implemented in EdgeR function plotMDS (in two dimensions)

was used for data visualization. Briefly, MDS takes as input the set of pairwise distances between

any two samples and plots points in 2-dimensional space (plane) attempting to preserve as much as

possible the original distances between any two samples.

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