supporting information - pnas.org information ... sorted cells was carried out using the qiagen...

Supporting InformationYadav et al. 10.1073/pnas.0900843106SI Text: Analysis of Microarray DataRaw Data Analysis and Quality Assessment. All microarray dataanalyses were performed in the statistical environment R, usingBioConductor packages (1, 2). The probe set-to-locus mappingsfor the ATH1 chip were obtained from TAIR. All ambiguousprobe sets on this chip were treated in the gene enumerationsteps of this study in the following manner: controls and probesets matching no or several loci in the Arabidopsis genome wereignored in the downstream analysis steps. In addition, redundantprobe sets that represent the same locus several times werecounted only once.

The normalization of the raw data Cel files was performedwith the MAS5 algorithm using the default settings of thecorresponding R function (3). To estimate the amount ofexpressed (detected) and unexpressed genes, the present callinformation of the nonparametric Wilcoxon signed rank test wascomputed with the affy package (4, 5). Genes that receivedpresent calls in all replicates of a given cell type were consideredas expressed. The quality of the Affymetrix GeneChips wasassessed with analysis routines provided by the affyPLM library(6). Analysis of differentially expressed genes (DEGs) wasperformed with the LIMMA package using the normalizedexpression values (7). The Benjamini and Hochberg method wasselected to adjust p-values (P) for multiple testing and todetermine FDRs (8). As confidence threshold an adjusted P �0.01 was used. A gene was considered a DEG if it fell below thisthreshold in at least one of all possible contrasts (samplecomparisons) among the 3 cell samples: CLV3p, FILp andWUSp.

Cluster Analysis. Cluster analyses were performed in R on theMAS5 normalized expression data that were scaled with thedefault factor of 500. For the intensity interval clustering, themean intensity values of the replicates were grouped into thefollowing intervals: A � absent: �220; L � low: 220–1,000; M �medium: 1,001–5,000; and H � high: �5,000. Subsequently, the4 interval labels for each sample were concatenated in thesample order: CLVp, FILp and WUSp. The concatenated labelsof the 3 samples provide 81 possible intensity interval clusters,of which only 49 were observed in the dataset (Table S5). TheCLV3n cells were not considered for this analysis because theydid not represent any one specific cell types of the SAMs.

Hierarchical clustering of expression profiles was performedwith the hclust function in R that performs agglomerativehierarchical clustering (1, 9). Complete linkage was used ascluster joining method and Pearson correlation values were usedas distance/similarity measure for the expression profiles acrossthe cell types. To have a sufficient number of samples forcalculating robust correlation-based distances, the intensity val-ues of all replicates instead of their mean values were used forthis purpose. To simplify the visual interpretation of the hier-archical clustering result, the heatmap in Fig. 2B shows only themean intensity values for the replicates of each cell type.

Gene Ontology Analysis. Enrichments analysis of Gene Ontology(GO) terms was performed as described in an earlier study (10).In summary, the Arabidopsis gene-to-GO mappings from TAIR(available at http://geneontology.org) were used for these anal-yses. The hypergeometric distribution was applied to test genesets for the overrepresentation of GO terms. To perform thistest, the GOHyperGAll function was used (10, 11), whichcomputes for a given sample population of genes, the enrichment

test for all nodes in the GO network, and returns raw andadjusted p-values. As an adjustment method for multiple testing,it uses the Bonferroni method (12). The relative proportion ofGO terms associated with various DEG sectors is expressed aspercentage of total (Fig. 2E). A complete list of GO-termsassociated with all DEG sectors is available in Table S7.

Venn diagrams. Venn diagrams were calculated with custom Rfunctions that are available at http://faculty.ucr.edu/%7Etgirke/Documents/R�BioCond/R�BioCondManual.html. A 3-way Venndiagram for differentially expressed genes (DEGs) was calcu-lated by organizing 2515 DEGs into 3 subgroups. This wasaccomplished by determining the genes that showed significantup-regulation in 1 of the 3 cell types (Fig. 2C and Table S5). The3 gene lists obtained from this analysis were used for generatingthe 3-way Venn diagram, which revealed 7 possible overlap/uniqueness sectors. For generating the 4-way Venn diagram (Fig.2D) representing the number of detected genes (expressed), thepresent call information for ap1-1;cal1-1 (cell-sorted) and wholeap1-1;cal1-1 (unsorted) datasets were obtained from Table S3.The wild type-developmental series dataset of AtGenExpresswas downloaded from GEO database (13). The cell type-specificdata of the Arabidopsis root, which includes 13 cell types (LRC,SRC, WOL, GL2, J0571, S17, S32, COBL9, JO121, S4, SUC2,J251, RM1000) and the data from 3 developmental stages(stage1, stage2 and stage3) were obtained from GEO database(14, 15). To estimate the amount of expressed (detected) andunexpressed genes, the present call information of the nonpara-metric Wilcoxon signed rank test was computed with the affypackage (4, 5). Genes that received present call in all replicatesof given cell type/sample were considered as detected (ex-pressed).

Real-Time PCR. Primers used for real-time RT-PCR were designedto amplify 180bps to 450bps long DNA fragments. Total RNAwas isolated with the RNeasy RNA isolation kit followed byDNase I treatment (Qiagen) from 100,000 protoplasts derivedfrom CLV3p, WUSp and FILp cell samples. cDNA synthesis wascarried out by using SuperScriptIII reverse transcriptase (In-vitrogen), according to the manufacturer’s instructions. Real-time PCR was done with Bio-Rad iQ5 sequence detectionsystem, using SYBR Green chemistry (Bio-Rad) with the fol-lowing PCR conditions. Step1: 95 °C for 3 min. Step2: 40 cyclesof 95 °C for 10 s followed by 56 °C for 1 min. Step3: 72 °C for 30 s.Each reaction was carried out in triplicates. UBIQUTIN1 wasused to normalize the mRNA levels (16).

In situ hybridization on wild type tissue sections. For probe synthe-sis, the PCR-amplified cDNAs were cloned into pCR4-TOPO,pENTR D/TOPO vector (Invitrogen) and pGEM T-easy (Pro-mega). A complete list of probes used in this study can be foundin oligonucleotides table given at the end of this document. Theprobes were synthesized with appropriate RNA polymerases andall other steps were followed according to the following protocol(http://plantlab.caltech.edu/html/protocols.html).

Whole mount in situ hybridization of ap1-1;cal1-1 shoot apices (Thismethod works on ap1-1;cal1-1 SAMs but we have not obtainedconsistent results with the wild type tissue). Shoot apices of 4-week-old ap1-1;cal1-1 plants were fixed in chilled PBS, pH 7, contain-ing 4% (wt/vol) paraformaldehyde (Sigma), 4% (vol/vol) DMSO(Sigma). Tissue infiltration was carried out on ice by applying

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vacuum for 15 min twice to the samples. After vacuum infiltra-tion samples were exchanged with fresh fixative and gentlyagitated at 4 °C for 12 h. Next day, fixative was exchanged with2 washes of PBS for 30 min each. This was followed by serialchanges of 30%, 40%, 50%, 60%, 70%, 85%, 90%, 95%, ethanoleach step lasting for 60 min and the tissue was stored in 100%ethanol overnight at 4 °C.

Samples were transferred to a 24 well FALCON plates for insitu pretreatment. Hydration of samples was carried out inreverse ethanol series starting at 100%, 2�, 95%, 90%, 80%,60%, 30% and dH2O each step lasting for 3 min at roomtemperature. Samples were equilibrated in 2� SSC for 15–20min. This was followed by proteinase K treatment (30 �g/mL) in100 mM Tris pH 8, 50 mM EDTA for 30 min at 37 °C with gentleagitation. Proteinase K treatment was followed by treatmentwith glycine (2 mg/mL) in PBS for 3 min. Samples were washedwith 1XPBS twice, followed by postfixing of tissues in 4%(wt/vol) paraformaldehyde PBS pH 7, for 10 min. After washingtwice with PBS, samples were passed through 0.1 M triethanol-amine (Sigma) (made fresh to pH 8) and acetic anhydride(Sigma) for 10 min. Samples were washed with 1XPBS twice andexchanged with ethanol series starting at 30%, 60%, 80%, 90%,95%, 2� 100% each for 2 min.

The hybridization and posthybridization reactions were car-ried out in FALCON plates. The subsequent steps of washing,

blocking and antibody applications were followed according tothe web protocol (http://plantlab.caltech.edu/html/protocol-s.html).

Shoot apices were trimmed under the dissection microscopeand mounted in 50% glycerol in depression slide.

FACS Analysis. mGFP5-ER and Ds-Red-N7 expressing cells wereisolated on a FACS-Aria (Becton Dickinson) fitted with a 100�m nozzle. The cells were sorted at a flow rate of 5,000 to 7,000events per second and with a fluid pressure of 35 psi. Appro-priate gates were used to separate fluorescent cells from non-fluorescent cells. GFP positive cells were selected by theiremission intensity in the green channel (�530 nm) and Ds-Redcells were selected by their emission intensity in the red channel(�610 nm). Cells were sorted directly into the lysis buffer(Qiagen RLT buffer), mixed and immediately frozen at �80°C.

RNA Extraction and Microarray Hybridization. RNA extraction fromsorted cells was carried out using the QIAGEN RNeasy PlantMini Kit (Cat# 74904) using a previously standardized protocol(11). The typical yield of RNA from 100,000 cells rangedbetween 200-300 ng. The RNA quality was determined by usingthe Agilent 2100 Bioanalyzer. A two-step RNA amplification,followed by labeling and hybridization was carried out accordingto the Affymetrix GeneChip Expression Analysis manual andaccording to the manufacturer’s instructions.

1. R Development Core Team (2008) R: A Language and Environment for StatisticalComputing. (Vienna, Austria.). Available at www.R-project.org.

2. Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W (2005) Bioinformatics andComputational Biology Solutions Using R and Bioconductor (Springer, New York).

3. Qin LX, et al. (2006) Evaluation of methods for oligonucleotide array data via quan-titative real-time PCR. BMC Bioinformatics 7:23.

4. Liu WM, et al. (2002) Analysis of high density expression microarrays with signed-rankcall algorithms. Bioinformatics 18:1593–1599.

5. McClintick JN, Edenberg HJ (2006) Effects of filtering by Present call on analysis ofmicroarray experiments. BMC Bioinformatics 7:49.

6. Bolstad BM, et al. (2005) Quality Assessment of Affymetrix GeneChip Data in Bioin-formatics and Computational Biology Solutions Using R and Bioconductor. (Springer,New York).

7. Smyth GK (2004) Linear models and empirical bayesmethods for assessing differentialexpression in microarray experiments. Stat Appl Genet Mol Biol 3(3).

8. Benjamini Y (1995) Controlling the false discovery rate—a practical and powerfulapproach to multiple testing. J Roy Statist Soc Ser B Methodological 57:289–300.

9. Murtagh F (1985) Multidimensional Clustering Algorithms. COMPSTAT Lectures 4.10. Horan K, et al. (2008) Annotating genes of known and unknown function by large-

scale coexpression analysis. Plant Physiol 147(1):41–57.11. Falcon S, Gentleman R (2007) Using GOstats to test gene lists for GO term association.

Bioinformatics 23:257–258.12. Boyle EI, et al. (2004) GO:TermFinder-open source software for accessing Gene Ontol-

ogy information and finding significantly enriched Gene Ontology terms associatedwith a list of genes. Bioinformatics 20:3710–3715.

13. Schmid M, et al. (2005) A gene expression map of Arabidopsis thaliana development.Nat Genet 37:501–506.

14. Brady SM, et al. (2007) A high-resolution root spatiotemporal map reveals dominantexpression patterns. Science 318:801–806.

15. Birnbaum K, et al. (2003) A gene expression map of the Arabidopsis root. Science302:1956–1960.

16. Charrier B, Champion A, Henry Y, Kreis M (2002) Expression profiling of the wholeArabidopsis shaggy-like kinase multigene family by real-time reverse transcriptase-polymerase chain reaction. Plant Physiol 130:577–590.



Fig. S1. Analysis of CLV-WUS network in ap1-1;cal1-1 background. Whole mount RNA in situ hybridization patterns of CLV3 expression (A) and WUS expression(B) in ap1-1;cal1-1. The expression patterns of the 2 genes closely resemble that of previously published expression patterns on the wild type SAMs. (C and D)The effects of transient, dexamethasone (DEX)-induced, silencing of CLV3 in ap1-1;cal1-1 background. (C and D) are the 3D-reconstructed top views ofap1-1;cal1-1 SAMs before (C) and 48 h after DEX-application (D). The temporal sequence of CZ expansion pattern, as monitored by pCLV3::mGFP5-ER (green),closely resembles that of the sequence observed in wild type SAMs, as shown in earlier study (reference 4, main manuscript). FM4–46, a lipophilic-dye, is addedto highlight the cell outlines in D.



PUM10 At1g35750 (S5)

AIL7 At5g65510 (S5)

Cyclin-like At5g06270 (S5)

Carboxy-lyase At5g06300 (S5)

Fig. S2. Validation of differentially-expressed genes. Comparison of expression patterns of genes on wild type tissue sections, as revealed by RNA in situhybridization patterns, and MAS5-normalized microarray mean intensity values of the replicates for 25 new genes that are selected to validate the differentialexpression analysis. Left represent RNA in situ patterns and the corresponding plots representing MAS5-normalized mean intensity values of the replicates across4 cell types (CLVn, CLV3p, FILp and WUSp) are given at Right. The gene names, corresponding locus identification numbers and Affymetrix array element names,and the DEG sectors they belong to are given on individual panels.



MCT2 At5g07930 (S5)

HMG At1g04880 (S5)

HDG4 At4g17710 (S5)

MCT1 At1g37140 (S5)

Fig. S2. (continued).



Alliinase At1g70560 (S5)

Syntaxin At3g59270 (S4)

WRKY13 At54g39410 (S4)

WRKY 74 At5g28650 (S4)




CKX3 At5g56970 (S4)

Nodulin MtN3 family protein At1g21460 (S4)

B3 TF At1g26680 (S4)

HMG At1g76110 (S4)




ATBZIP11 At4g34590 (S6)

Choline Kinase At4g09760 (S6)

DFL1 At5g54510 (S6)

CYT p450 At4g39480 (S6)




GA3OX3 At4g21690 (S7)

ATHB25 At5g65410 (S7)

Protease inhibitor At3g53980 (CLV3n)

Nodulin MtN3 family protein At5g50790 (CLV3n)




LCR68 At2g02130




Fig. S3. CLV3 expression overlaps with that of WUS in the L3 layers of SAMs. (A–C) Side- views of a 3-week-old wild type SAM showing the expression overlapbetween CLV3 and WUS. (A) a combined image of pCLV3::mGFP5-ER (green) and pWUS::Ds-Red-N7 (red). Arrows point to the 3 superficial cell layers of the SAM.(B) pWUS::Ds-Red-N7 image of (A). (C) pCLV3::mGFP5-ER image of (A). (D) Side view of 3-week-old wild type SAM showing the expression of pWUS:mGFP-ER(green) and cell outlines stained with FM4–64 (red). Note that WUS expression is detected in cells of the L3 layers (E–H) Longitudinal sections of WT Ler SAMtissues. In situ hybridization with CLV3 antisense probe (E) and with WUS probe (F–H). Note, WUS transcripts are not detected in the L2 layer of inflorescencemeristem. WUS transcripts are detected in the L2 layer of the flower meristem (H). (I and J) Top views of WUS expression patterns visualized by whole mountRNA in situ hybridization in ap1-1;cal1-1 SAM tissues. (I and J) represent images of the same SAM taken at different depths of focus. Note, higher levels of WUStranscripts in the most centrally-located cells of the expression domain.



Fig. S4. qRT-PCR validation of microarray data. The transcript abundance of a representative set of 7 differentially-expressed genes among CLV3p and CLV3ncell types. The transcript abundance is shown for B3 transcription factor (At1g26680), ALLINIASE (At1g70560), PUM10 (At1g35750), MCT1 (At1g37140), MCT2(At5g07930), SYNTAXIN-LIKE (At3g59270), and SHINE2 (At5g25390). The gene names, corresponding locus identification numbers and Affymetrix array elementnames are given on individual panels.



HDG5 At5g46880 (S5)

HDG1 At3g61150 (S7)

ACR4 At3g59420 (S2)

AtML1 At4g21750 (S2)

PDF2 At4g04890 (S2)

Fig. S5. Validation of cell type-specific microarray data. The representation of MAS5-normalized microarray intensity values for 47 characterized differentially-expressed genes, across 4 cell types (CLV3n, CLV3p, FILp, and WUSp). These genes were selected from the literature based on their RNA in situ or promoter reporterexpression patterns. The gene names, corresponding locus identification numbers and Affymetrix array element names, and the DEG sectors they belong to aregiven on individual panels.



PDF1 At2g42840 (S2)

HDG2 At1g05230 (S2)

ENP At4g31820 (S2)

BDG1 At1g64670 (S2)

AS2 At1g65620 (S7)




3

FIL At2g45190 (S7)

CUC3 At1g76420 (S7)

BP At4g08150 (S3)

SPT At4g36930 (S4)

AIL7 At5g65510 (S5)

STM At1g62360 (S4)

3




UFO At1g39590 (S4)

WUS At2g17950 (S4)

TFL1 At5g03840 (S4)

REM1 At4g31610 (S4)

PIN1 At1g73590 (S4)




MNP At3g50870 (S4)

CLV1 At1g75280 (S4)

CLV3 At2g27250 (S5)

CUC1 At3g15170 (S5)

CKX5 At1g75450 (S4)




YUC1 At4g32540 (S5)

PHV At2g34710 (S5)

PI At5g20240 (S5)

AIL5 At5g57390 (S5)

AIL6 At5g10510 (S5)

TEL1 At3g26120 (S5)

Fig. S5 (continued).



LBD18 At2g45420 (S7)

PTL At5g03680 (S7)

JLO At4g00220 (S7)

ROXY1 At3g02000 (S7)

YAB3 At4g00180 (S7)




BOP2 At2g41370 (S7)

BOP1 At3g57130 (S7)

LMI At5g03790 (S7)

MP/ARF5 At1g19850 (S7)

GA20OX1 At4g25420 (S7)




Other Supporting Information Files

Table S1 (XLS)Table S2 (XLS)Table S3 (XLS)Table S4 (PDF)Table S5 (XLS)Table S6 (XLS)Table S7 (XLS)

PRS At2g28610 (S7)

AS1 At2g37630 (S7)






http://www.pnas.org/cgi/data/0900843106/DCSupplemental/ST4_PDF



