ORIGINAL PAPER

Expression dynamics of metabolic and regulatory componentsacross stages of panicle and seed development in indica rice

Rita Sharma & Pinky Agarwal & Swatismita Ray &

Priyanka Deveshwar & Pooja Sharma &

Niharika Sharma & Aashima Nijhawan & Mukesh Jain &

Ashok Kumar Singh & Vijay Pal Singh &

Jitendra Paul Khurana & Akhilesh Kumar Tyagi &Sanjay Kapoor

Received: 22 November 2011 /Revised: 2 March 2012 /Accepted: 6 March 2012 /Published online: 31 March 2012# Springer-Verlag 2012

Abstract Carefully analyzed expression profiles can serve as avaluable reference for deciphering gene functions. We exploitedthe potential of whole genome microarrays to measure thespatial and temporal expression profiles of rice genes in 19stages of vegetative and reproductive development. We couldverify expression of 22,980 genes in at least one of the tissues.Differential expression analysis with respect to five vegetativetissues and preceding stages of development revealed reproduc-tive stage-preferential/-specific genes. By using subtractive log-ic, we identified 354 and 456 genes expressing specificallyduring panicle and seed development, respectively. The meta-bolic/hormonal pathways and transcription factor families

playing key role in reproductive development were elucidatedafter overlaying the expression data on the public databases andmanually curated list of transcription factors, respectively.During floral meristem differentiation (P1) and male meiosis(P3), the genes involved in jasmonic acid and phenylpropanoidbiosynthesis were significantly upregulated. P6 stage of panicle,containing mature gametophytes, exhibited enrichment of tran-scripts involved in homogalacturonon degradation. Genes reg-ulating auxin biosynthesis were induced during early seeddevelopment. We validated the stage-specificity of regulatoryregions of three panicle-specific genes,OsAGO3,OsSub42, andRTS, and an early seed-specific gene, XYH, in transgenic rice.

The authors Rita Sharma and Pinky Agarwal contributed equally to thiswork.

Electronic supplementary material The online version of this article(doi:10.1007/s10142-012-0274-3) contains supplementary material,which is available to authorized users.

R. Sharma : P. Agarwal : S. Ray : P. Deveshwar : P. Sharma :N. Sharma :A. Nijhawan :M. Jain : J. P. Khurana :A. K. Tyagi :S. Kapoor (*)Interdisciplinary Centre for Plant Genomics and Department ofPlant Molecular Biology, University of Delhi South Campus,Benito Juarez Road,New Delhi 110021, Indiae-mail: kapoors@genomeindia.org

A. K. Singh :V. P. SinghDivision of Genetics, Indian Agriculture Research Institute,New Delhi 110012, India

Present Address:R. SharmaDepartment of Plant Pathology,University of California,Davis, CA 95616, USA

Present Address:P. Agarwal :M. Jain :A. K. TyagiNational Institute for Plant Genome Research,Aruna Asaf Ali Marg,New Delhi 110067, India

Present Address:S. RayBiotechnology and Bioresources Management Division, TataEnergy Research Institute,Lodhi Road,New Delhi 110003, India

Present Address:N. SharmaPlant Molecular Biology and Biotechnology Group, MelbourneSchool of Land and Environment, University of Melbourne,Parkville 3010 Victoria, Australia

Funct Integr Genomics (2012) 12:229–248DOI 10.1007/s10142-012-0274-3

The data generated here provides a snapshot of the underlyingcomplexity of the gene networks regulating rice reproductivedevelopment.

Keywords Development .Expression .Meta-analysis .Metabolicpathways . Panicle . Promoter. Seed .Transcription factors

Introduction

Reproductive development is a dynamic process involvingcomplex interplay of various regulatory networks. Spatialand temporal transcriptome profiles represent snapshot of geneactivity and thus have been extensively used for decipheringthe role of individual genes/pathways or regulatory networksand plausible interactions among them (Adams 2008). In fact,in the past decade, multitude of microarray-based studies havebeen performed towards elucidating reproductive organ devel-opment in Arabidopsis (Alves-Ferreira et al. 2007; Becerra etal. 2006; Fait et al. 2006; Hennig et al. 2004; Wellmer et al.2006; Wellmer et al. 2004; Zhang et al. 2005; Wilson et al.2005b; Day et al. 2008), rice (Endo et al. 2004; Furutani et al.2006; Hobo et al. 2008; Kondou et al. 2006; Lan et al. 2004;Hirano et al. 2008; Suwabe et al. 2008; Jiao et al. 2009; Wanget al. 2010; Fujita et al. 2010; Li et al. 2007a, b; Wang et al.2005; Deveshwar et al. 2011), maize (Grimanelli et al. 2005;Liu et al. 2008; Lee et al. 2002), wheat (Wilson et al. 2005a),and other non-model plant systems (Hansen et al. 2009;Laitinen et al. 2005; Endo et al. 2002; Tebbji et al. 2010).One of the limitations of these studies is that most of thesescored the number of probe sets rather than unique transcriptsas an estimate of gene expression. Moreover, these studiesmainly focused on analyzing spatial expression profiles invarious cell/tissue types or restricted time points during devel-opment. Therefore, it is very difficult to make cross compar-isons due to collection of tissues at different stages ofdevelopment and lack of an internationally accepted stagingsystem in rice similar to that of Arabidopsis (Smyth et al.1990). Here, we report the time-course analysis of expressiondynamics in indica rice encompassing the complete series ofreproductive development, from panicle initiation to seed mat-uration. All the analysis was performed on the list of probe IDsrepresenting non-TE-related unique transcripts. We believethat our experimental design provides more realistic and com-plete view of transient as well as long-term developmentalresponse, which is not attainable by organ/cell-type specificor single time point/stage-based studies.

We categorized panicle and seed development into nine(P1–P6 and P1-I–P1-III) and five (S1–S5) categories, respec-tively, and used Affymetrix arrays to generate spatial andtemporal expression profiles during rice reproductive organdevelopment. Itemized comparisons with five vegetative tis-sues including 7-day-old seedlings (SD), roots (R), Y leaf

(YL), mature leaf (ML), and shoot apical meristem (SAM)revealed reproductive stage preferential/specific genes.Enrichment of transcription factor coding genes and hormonalpathways in vegetative, panicle, and seed stages implied theirsignificance during plant growth and development. The datahave previously been extensively validated by qPCR analysisof candidates from various gene families encoding transcrip-tion factors (Agarwal et al. 2007; Arora et al. 2007; Nijhawanet al. 2008; Jain et al. 2008; Sharma et al. 2010), signaltransduction components (Jain et al. 2006; Jain and Khurana2009; Singh et al. 2010; Jain et al. 2007), RNA interferencemachinery (Sharma et al. 2010; Sharma et al. 2009), and stressresponsive factors (Ray et al. 2011). Due to prior submissionin Gene Expression Omnibus database, various researchers(Cao et al. 2008; Howell et al. 2009; Ma and Zhao 2010; Jianget al. 2009; Li et al. 2009) have also used this dataset foranalyzing expression profiles of rice genes depicting the con-fidence of rice community in the quality of the data. We havealso earlier used part of the data generated here to identifyanther-specific transcripts by comparing the expression pro-files of rice genes during anther development with those ofvegetative and seed stages analyzed here (Deveshwar et al.2011). However, the goal of this study is to (1) identify keygenes/pathways regulating various stages of panicle and seeddevelopment, (2) provide an insight into magnitude and re-dundancy in rice transcriptome during different stages ofvegetative and reproductive development, and (3) provide anin planta validation of stage specificity of selected genes usingpromoter-reporter analysis. Expression profiles of four candi-date genes, exhibiting varied expression patterns, have beenverified by promoter-GUS analysis in transgenic rice.

Materials and methods

Collection of plant material and categorization of panicleand seed stages

The vegetative tissues and rice panicles spanning all the stagesof panicle and seed development were collected from field-grown Oryza sativa indica var. IR64 plants at IARI (IndianAgricultural Research Institute, New Delhi, India). For evalu-ating the precise stages of development, we performed thehistochemical analysis with the anthers collected at differentstages of development and correlated it with the length ofpanicles (for details, see Supplementary Figure S1). Based onthe stages of anther development and information available inliterature (Ikeda et al. 2004; Itoh et al. 2005; Raghavan 1988),panicles were divided into six groups (P1–P6; SupplementaryTable S1, Figure S1 and S2). To document morphologicaldetails, panicles collected from all six groups were photo-graphed using a digital camera (Canon PowerShot S1 IS,Singapore). The P1 stage was further categorized into three

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sub-groups (P1-I–P1-III) and photographed under a dissectingstereo-zoom microscope (MZ12.5 with DFC320 camera;Leica Gmbh, Germany). The seed development was catego-rized into five groups (S1–S5) based on the days after polli-nation (Supplementary Table S1, Figure S2). To documentseed stages, spikelets at different stages of seed developmentwere dehusked and dissected to extract embryos. The mor-phological details were observed and photographed using thedissecting stereo-zoom microscope. Three biological repli-cates of five vegetative tissues, including ML, YL, R, SD,and SAM, were also collected from field-grown plants. Foruniformity and simplicity, all the categories of panicle andseed development and vegetative tissues are referred asstages of development in the manuscript. The detailsof stages used are provided in Supplementary Table S1.

Microarray experiments and data analysis

Affymetrix GeneChip®Rice Genome arrays containing 51,279rice transcripts (approximately 48,564 japonica and 1,260 ind-ica transcripts) were used to study the global changes in geneexpression during rice reproductive development. RNA wasisolated as described (Arora et al. 2007; Nijhawan et al.2008). cDNA synthesis, cRNA synthesis, labeling, and hybrid-izations followed by scanning were carried out as per manu-facturer’s instructions and described (Affymetrix, Santa Clara,CA; (Arora et al. 2007). In total, 57 .CEL files representingthree biological replicates each of ML, YL, R, SD, nine paniclestages (P1-I−P1-III, P1−P6), and five seed stages (S1−S5) wereimported in ArrayAssist 5.0.0 microarray data analysis soft-ware (Stratagene) followed by quantile normalization by usingGCRMA algorithm and log2 transformated (Wu et al. 2003).The correlation coefficient between biological replicates wasanalyzed. The data were separately normalized using MAS 5.0algorithm to generate Present/Absent calls. The unique numberof transcripts represented on the GeneChip® was identified asdescribed previously (Deveshwar et al. 2011) and filtered data-set was used for downstream analysis.

Principal component analysis, using 19 principle compo-nents, was carried out withmean centering and scaling of all thevariables to unit variance and presented as three-dimensionalview using eigenvalues, E1–E2–E3. Differential expressionanalysis was carried out with respect to all four vegetativestages (SAM, YL, ML, SD), taken separately, as well as withrespect to preceding stage by applying an FDR correction basedon Benjamini and Hochberg method and p value cut off of≤0.05 (Benjamini andHochberg 1995). For early panicle stages(P1-I, P1-II, and P1-III), SAMwas taken as reference and the pvalues were given as uncorrected at a cut off of ≤0.005. Toidentify stage-specific genes, log2 expression value cut off of≥5.64 (normalized average expression value (NAEV) ≥50) inthe stage of interest and ≤3.90 (NAEV ≤15) in rest of the stageswas employed. However, to identify panicle-specific genes, the

filter was not applied to S1 stage of seed development due tohigh similarity in transcript pool of P6 and S1 stages. GOannotations for selected datasets were downloaded from therice genome annotation project (RGAP) database (http://rice.plantbiology.msu.edu/). The metabolic pathways induced/sup-pressed during reproductive development were analyzed usingdata available in RiceCyc database of Gramene (http://pathway.gramene.org/expression.html; Jaiswal et al. 2006). Weanalyzed meta-profiles of short-listed datasets using RiceOligonucleotide Array Database (ROAD; http://www.ricearray.org/expression/meta_analysis.shtml).

A comprehensive list of all the transcription factor familygenes was generated using HMM analysis (Madera andGough 2002) as well as keyword search as described previ-ously (Arora et al. 2007). The differential expression pro-files were analyzed as described above. Hypergeometricdistribution analysis was also performed to identify tran-scription factor families enriched in panicle/seed-specificdata sets. Cluster analysis on rows was performed for se-lected datasets, using Euclidean distance metric and Ward’sLinkage rule of Hierarchical clustering.

qPCR analysis

The expression profiles of four selected genes were validat-ed using qPCR analysis as described earlier (Jain et al. 2006;Arora et al. 2007). Three biological and three technicalreplicates were performed for each stage and standard errorwas calculated between them. ACTIN was used as an en-dogenous control. The data were normalized to match theprofiles with that of microarray data.

Promoter-reporter constructs

About 1.5−2 kb putative promoter regions of selected genes(−1,560 to +16 of RTS, −1,742 to +20 of OsAGO3, −1,518 to+10 of OsSub42, −1,266 to +71 of XYH) including partial orcomplete 5′ UTR were PCR amplified. The list of primers isgiven in Supplementary Table S2. Amplified DNA fragmentswere cloned in pENTRTM/D-TOPO vector (Invitrogen Inc.,USA) and validated by sequencing. LR reaction was per-formed using Gateway® LR ClonaseTM II enzyme mix(Invitrogen, USA) as per manufacturer’s instructions to trans-fer the promoter DNA from pENTRTM/D-TOPO vector topMDC164, expression vector carrying the gene encodingGUS as reporter (Arabidopsis Biological Resource Center;Curtis and Grossniklaus 2003).

Rice transformations and GUS histochemical assay

Final vectors were mobilized into Agrobacterium tumefaciensstrain AGL1 by electroporation. The PB1 variety of indica ricewas transformed using the protocols described previously

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(Mohanty et al. 1999; Toki et al. 2006). The list of primers usedto confirm the presence of transgene is given in SupplementaryTable S2. GUS histochemical assay was performed to check theactivity of GUS (Jefferson et al. 1987). Different tissues of thetransgenic as well as wild-type plants were incubated in GUShistochemical buffer containing 10 % methanol at 37°C for 16−20 h followed by incubation in acetone/ethanol (1:3). Theobservations were recorded by using DFC320 mounted onMZ12.5 Stereo microscope (Leica Gmbh, Germany).

Genomic localization of differentially expressed genes

To localize the genes on respective chromosomes, only thosewith NAEVof ≥50 (log2 expression value ≥5.64) in at least oneof the stages were analyzed. The genes exhibiting ≥2 foldsdifferential expression in any of the 19 stages were extracted.In-house generated programs (written in “C” and Perl) wereused to identify Gene Clusters with Similar Expression(GCSEs) profiles. All the genes were sorted based on theirchromosomal positions as given in RGAP database of MSU(http://rice.plantbiology.msu.edu/). Based upon the expressionprofiles obtained after differential expression analysis, all thegenes were assigned the stage preferential/specific profiles andthen a sequential scan was performed by comparing the ex-pression profile of each gene with the next gene in order. Ifexpression profiles of two or more contiguous genes match up,the regionwas scored as a GCSE. To display the GCSEs on ricechromosomes, Differential Gene Locus Mapping (DIGMAP)version 2 (http://geneexplorer.mc.vanderbilt.edu/DIGMAP/; Yiet al. 2005) was used. The per cent identity between the genesfalling in the same GCSE was calculated using MegAlignsoftware 4.03 (DNASTAR Inc.). Genes sharing ≥70 % identityat protein level were considered to be tandemly duplicated. Tocheck if the genes comprised in a GCSE were involved in thesame or different pathways, GOSlim assignments and putativefunctions for all of the genes were obtained from RGAPdatabase (http://rice.plantbiology.msu.edu/index.shtml) andRiceCyc database of Gramene (http://pathway.gramene.org/expression.html; Jaiswal et al. 2006).

Results

Magnitude of rice transcriptome

Since the number of probesets (57,381) on GeneChip® RiceGenome Array do not correspond to the number of annotat-ed genes, we carried out an extensive curation exercise tofilter probesets that (1) do not map to any annotated tran-scription unit, or (2) represent internal controls or TE-relatedgenes, or (3) are not the 3′ most probeset (in case of multipleprobesets per transcription unit). This resulted in a dataset of37,927 probe sets representing unique genes on the chip,

which was used for all the subsequent analyses (for details,see Supplementary Figure S3).

Genome-wide expression profiles of all 14 stages of repro-ductive development, along with five stages of vegetativedevelopment including ML, YL, SAM, R, and SD, wereanalyzed using GeneChip® Rice Genome Arrays(Affymetrix). A correlation of >0.96 was obtained amongthree biological replicates of all the stages analyzed. A prin-ciple component analysis performed on the dataset clearlydemonstrated, on one hand, the expanse and distinctness ofvegetative transcriptomes and, on the other, underlined themolecular continuum as well as progression of panicle andseed development paths emanating from SAM to P1-I and P6-S1 transitions, respectively (Fig. 1a). The distinct positioningof both reproductive and vegetative tissues/time points alsoprovided validation of our staging system.

To comprehend the magnitude of rice transcriptome andcontribution of individual tissues, the number of expressedgenes in each stage/tissue was determined. The analysis ver-ified expression of 22,980 unique genes in at least one of thestages/tissues analyzed which is comparable to the number ofgenes detected using cDNA arrays (Jiao et al. 2009). Themaximum number of genes (20,421) was called “present” inpanicles implying the need for diverse transcript populationduring development of specialized floral organs (Fig. 1b).Among vegetative tissues, seedlings and roots exhibitedhigher number of transcripts in comparison to leaf tissues,probably because of diverse and higher metabolic activity.

A comparison of expressed genes revealed that 9,021 genesexpressed in all the stages analyzed and thusmight be involvedin basal metabolic pathways. About 35-45 % genes from eachstage exhibited overlapping expression in multiple develop-mental windows, whereas, only 0.5 % to 3.2 % genes werespecific to each developmental stage (Fig. 1b). Among repro-ductive stages, P6 stage of panicle, that harbors mature pollen,had maximum number of specific transcripts as many of themcould be stored for pollen germination and tube growth(Becker and Feijo 2007). Roots exhibited maximum percent-age of specific genes (2.3 %, Fig. 1b) among vegetative tissuessuggesting that root being an underground part might havedeveloped some unique biochemical pathways (Zhang et al.2005). More than 650 genes are expressed in both panicle andseed stages, whereas, 321 transcripts were shared betweenSAM and panicles. Panicles were found to share the maximumnumber of transcriptional entities with roots (146) compared toother vegetative stages analyzed in this study.

Differential expression analysis during rice reproductivedevelopment

Since no single method can identify all the relevant geneswith potential involvement in rice reproductive develop-ment, two strategies were adopted to identify differentially

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Fig. 1 a Principle component analysis of various developmentalstages. The graph shows all the data points projected in the three-dimensional space formed by three coordinates after rotation. Eachdata point represents an independent tissue with green color represent-ing leaf stages (ML and YL); gray represents root (R) and seedlings(SD); purple represents SAM and early panicle stages (P1-I to P1-III);red represents panicle (P1 to P6) and blue represents seed (S1 to S5)stages. The eigenvalues E1–E2–E3 were used for plotting the data. Theclosely related developmental stages are encircled. b Overview of geneexpression during different stages of development. The number ofgenes called “Present” in each stage as well as the number of genesspecific to one, two, or more than two stages has been shown as the

stacked bar graph. The color legend is given on the topmost left of thegraph. c Differential expression analysis during stages of panicle andseed development with respect to vegetative stages. The number ofgenes showing up- and downregulation in each panicle stage withrespect to each of the four vegetative stages is plotted. Pink columnsrepresent the commonly up- and downregulated genes with respect toall four vegetative stages; whereas, genes specifically upregulated ineach stage are represented by yellow columns. The dotted line repre-sents the pattern exhibited by differentially expressed genes withrespect to all four vegetative stages during temporal stages of repro-ductive development. SD seedling, R root, ML mature leaf, YLY leaf,SAM shoot apical meristem, P panicle, S seed stages

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expressed genes during panicle and seed development. Inthe first approach, the transcript levels of all the genes werecompared with the vegetative stages individually as well ascollectively. In the second approach, the transcriptome ofeach stage was compared with that of preceding stage toidentify genes whose expression might have triggered tran-siently in response to specific developmental cues.

Reproductive vs. vegetative development

The datasets were analyzed to identify up/downregulatedgenes in each stage with respect to all four vegetative tissues,collectively. The resulting dataset would, therefore, includegenes whose transcript levels change as a function of repro-ductive development. Based on differential expression analysiswith respect to vegetative stages, early panicle stages (P1 andP2) showed higher number of differentially expressed geneswith respect to R and SD; whereas, later panicle stages (P5 andP6) had larger number of differentially expressed genes withrespect to leaf stages (Fig. 1c). Conversely, the maximumnumber of genes involved in seed development was differen-tially regulated with respect to young root; whereas, the seedtissues had the least number of differentially expressed geneswhen compared with mature leaf. Among the seed stages, thenumber of downregulated genes with respect to vegetativestages gradually increased during development suggestinggeneral suppression of transcriptional activity commensuratewith the onset of the dormant phase in seeds.

Among panicle stages, the maximum number of differ-entially expressed genes was found in P2 stage (that corre-sponds to initiation of male meiosis) with 1,101 and 1,053genes up- and downregulated, respectively, suggestinghigher order genic activity at this particular stage; whereas,the minimum differential transcript accumulation was ob-served at the post-meiotic P4 stage (Fig. 1c). The S1 stage,corresponding to 0–2 days post-fertilization development,represents the least differentially expressed gene pool,which increased in S2 and S3 stages involving enlargementof organs. Using subtractive logic, the upregulated genes ineach stage were compared with those in every other stage toidentify genes that were exclusively activated in a particularstage of reproductive development. This analysis revealed13, 32, 67, 87, 81, and 248 genes to be specifically upregu-lated in P1–P6 stages of panicle development, and 303, 241,213, 72, and 295 genes uniquely induced in S1–S5 stages ofseed development, respectively (Fig. 1c, yellow bars).Notable of these were anther-specific proline rich proteincoding genes uniquely induced in P3 and P4 stages ofpanicle development. Transcription factors were particularlyenriched in upregulated datasets during early seed stages;whereas, those involved in carbohydrate metabolism andubiquitin-mediated proteolysis were exclusively upregulatedin later seed stages. As the development of reproductive

organs progressed, the number of uniquely induced transcriptsalso increased.

Similarly, differential expression analysis of early paniclestages (P1-I to P1-III) with respect to shoot apical meristem(SAM) identified 425, 710, and 2,032 genes exhibiting ≥2fold change in P1-I, P1-II, and P1-III stages, respectively. Ofthese, 202, 385, and 902 genes were upregulated in P1-I, P1-II, and P1-III, respectively. In total, 49 genes were induced inall three stages. Among the differentially upregulated genes, alarge proportion (106, 159, and 691 genes, in P1-I, P1-II, andP1-III stage, respectively) was specific to individual stagessuggesting the rapid development-dependent molecularswitching in these stages.

Analysis of cascadial expression during reproductivedevelopment

As each stage analyzed in this study represents a character-istic phase in flower and seed development, one wouldexpect significant upregulation of specific transcriptionalunits with respect to preceding stage, many of which willbe important for regulating the precise developmental eventsand may have induced for a very short period of time. Toidentify these components, we performed differential ex-pression analysis by comparing each stage with its preced-ing stage of development. For P1 stage, SAM was taken asreference. This analysis revealed 2,009, 81, 905, 41, 1,854,and 3,590 genes getting more that 2 folds upregulated (pvalue≤0.05) in P1−P6 stages, respectively (Fig. 2a). Amongseed stages, as the development progressed, the number ofupregulated genes declined. In total, 1,973, 1,064, 289, 137,and 178 genes were upregulated in S1, S2, S3, S4, and S5stages, respectively (Fig. 2a). To shortlist the most signifi-cant genes, the ones with NAEVof ≥50 (or log2 expressionvalue ≥5.64) in any of the vegetative stages were filtered outfrom respective upregulated sets resulting in a set of 65, 2,66, 3, 79, and 415 genes uniquely upregulated in P1−P6stages, respectively and 112, 204, 33, 19, and 11 genes in S1−S5 seed stages, respectively (Fig. 2a). The expression

�Fig. 2 a Differential expression analysis during reproductive develop-mental stages taking preceding stage of development as reference. Blackbars represent total number of genes upregulated by ≥2 folds at p value≤0.05 with respect to the preceding stage. Gray bars represent theupregulated genes with NAEV ≤15 in vegetative stages (SupplementaryTable S3). b Major pathways induced with respect to preceding stageduring rice reproductive development. The genes exhibiting ≥2 foldsupregulation in reproductive stages with respect to preceding stage andinvolved in jasmonic acid, phenylpropanoid, and IAA biosynthesis havebeen presented with their expression profiles plotted in the form of a heatmap. Color bar at the base represents log

2expression values, with green

color representing low-level expression, black representing medium-level, and red signifying high-level expression. Developmental stagesused for expression profiling are given on the top of each column (fordetails, see Supplementary Table S1)

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profiles of these genes have been compiled as a heat map(Supplementary Figure S4).

Integration of upregulated dataset with the publicly avail-able RiceCyc database (http://www.gramene.org/pathway/ricecyc.html) revealed metabolic and hormonal pathwaysinvolved in reproductive development (Fig. 2b). The genesinvolved in jasmonic acid biosynthesis were upregulatedduring floral organ differentiation (P1), meiotic stage ofanther development (P3), and pollen development (P6) andthose implicated in phenylpropanoid biosynthesis exhibitedsignificant upregulation during floral organ differentiation(P1), male meiosis (P3), and microspore development (P5).The analysis also showed that five genes involved in Indole-3-Acetic Acid (IAA) biosynthesis were also upregulated inS1 stage (Fig. 2b). The genes involved in salvage pathwayof purines were upregulated during late panicle (P5 and P6)and early seed (S1) stages.

The ROAD (http://www.ricearray.org) provides gene ex-pression data across 1,867 publicly available rice microarrayhybridizations assembled together to perform meta-analysis.Meta-profiles of all three datasets shown in Fig. 2b, ana-lyzed using ROAD database, conformed with their signifi-cant induction during stages of reproductive development(Supplementary Figure S5).

Identification of reproduction-specific genes and theiraffiliation to metabolic pathways

The dataset of differentially expressed genes was furtherfiltered to identify genes that expressed specifically in oneor more stages of panicle and seed development. Threehundred and fifty four genes exhibited panicle-specific ex-pression (expression value ≥50 in panicle stages and ≤15 inother stages) with 3 % of them coding for transcriptionfactors. Whereas, 456 genes were expressed only in seeddevelopmental stages (expression value ≥50 in seed stagesand ≤15 in other stages) with 9 % of them encoding tran-scription factors. Interestingly, 40 % genes in both panicleand seed-specific datasets have not even been annotated yet,probably because of narrow windows of their expression.The expression of about 48 % of the panicle-specific genes(171) initiates at P1, P2, P3, and P4 stages, which in mostcases is detected till P5 or P6 stage. However, 183 genesexpressed only in the P6 stage harboring mature male andfemale gametophytes. Since male gametophytic cells out-number the female gametophytic cells in every floret, thebulk of these genes represent mature pollen-specific tran-scripts. In fact, most of these genes code for pollen aller-gens, transporters, and components of cytoskeleton andthose involved in cell wall metabolism (see SupplementaryTable S3 for details). These categories of genes might playrole in pollen–pistil interactions and pollen tube germina-tion. Putative homolog of pollen-specific gene, SF3, of

sunflower exhibited P6 stage-specific expression (Baltz etal. 1992). Many of panicle stage-specific genes seem to beinvolved in flavonoid and lipid biosynthesis.

During seed development, the most prominent domain,S2–S5, comprised of 93 genes with high representation ofgenes coding for seed storage proteins (proline and glute-lins), seed allergens and those involved in starch biosynthe-sis and ubiquitin-mediated proteolysis. In total, 19, 46, 28,7, and 55 genes were found to be specific to S1, S2, S3, S4,and S5 stages, respectively. The expression profiles of pan-icle and seed-specific genes have been presented in the formof hierarchical cluster maps in Supplementary Figure S6.

We compared the dataset of panicle/seed-specific geneswith two available expression data sets generated in differ-ent rice subspecies using different microarray platforms(Sato et al. 2011; Wang et al. 2010). A higher number ofpanicle and seed-specific genes were common between ourdataset (IR64) and the data generated by Wang et al. (2010)for other indica varieties (Zhenshan 97 and Minghui 63) incomparison to those identified in japonica (Nipponbare)rice by Sato et al. (2011; Supplementary Figure S7). Sincethe data generated in earlier studies was limited to fewerspatial stages of panicle and seed development, many of thegenes detected specifically in our dataset could be specificto the stages not analyzed previously.

On collating the information from Gramene database, asignificant number of genes involved in biosynthesis ofgibberellins, strictosidine, and fatty acids and their elonga-tion were found to exhibit panicle-specific expression(Fig. 3). However, transcripts of those involved in starchdegradation were specially detected in seed stages (Fig. 3).The genes involved in brassinosteroid biosynthesis wereupregulated in P5 stage, where these may be stored in starchgranules and later released during pollination and fertiliza-tion (Clouse and Sasse 1998). Various genes involved ingibberellin biosynthesis were upregulated during male mei-osis (P3), heading stage (P6) as well as early stages of seeddevelopment (S1 and S2). In addition, few genes involved inent-kaurene biosynthesis, which is a common gibberellinprecursor, were also upregulated at S1 stage of seed devel-opment suggestive of their involvement of GA during earlyseed development (Davidson et al. 2003). Analysis of meta-profiles of the genes highlighted in Fig. 3 supports theirspecific expression in limited stages of development(Supplementary Figure S8).

Expression dynamics of transcription factorsduring reproductive development

The number of transcription factor (TF) coding genes in riceis estimated to be 2,527 categorized into 65 genes families(Riano-Pachon et al. 2007). However, 216 of these genes areorphans as their role in transcriptional regulation is

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Fig. 3 Schematic representation of major pathways involving panicle/seed-specific genes. Nine major pathways represented by panicle/seed-specific genes are highlighted. The expression profiles of the genes areshown in the form of heat maps. Color bar at the base represents log2

expression values, where green color represents low-level expression,black shows medium-level expression, and red signifies high-level ex-pression. Developmental stages used for expression profiling are given onthe top of each column (for details, see Supplementary Table S1)

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ambiguous. Here, we reanalyzed the rice genome usingname search and HMM analysis and identified a total of2,314 transcription factor genes belonging to 68 gene fam-ilies. Except for a few gene families, additional memberswere identified in each gene family (Supplementary TableS5). Of these, 2,100 TF genes are represented on riceGeneChip® array. Differential expression analysis of thesegenes with respect to vegetative stages (ML, YL, R, and SD)revealed 204 and 246 genes exhibiting ≥2 folds upregulation(p value≤0.05) in at least one of the panicle and seed stages,respectively. Only 80 genes were upregulated in both panicleand seed stages, whereas, the rest were exclusive to eitherpanicle or seed development. Conversely, 55 genes weredownregulated in both panicle and seed stages. Differentialexpression analysis revealed 18 TF families including SBP,GRF, and DOF exhibited higher number of upregulated genesin panicles. Further, hypergeometric distribution analysis(Supplementary Table S5) revealed that 14 families, namelyBBR_GAGA, BTB/POZ, bZIP, GRF, HORMA, MADS,NAM, PWWP, SBP, TRIHELIX, WRKY, YABBY, C2H2,and DOF, were particularly enriched during panicle develop-ment. Out of these, bZIP, MADS, and C2H2 families had morethan 10 upregulated members. Twenty-seven families includ-ing MYB, NAM, HSF, MADS, POZ, and bZIP had relativelyhigher number of genes upregulated in seed stages (Fig. 4).Nine TF families, namely, bHLH, BTB/POZ, bZIP, HSF,MADS, SRS, TRIHELIX, YABBY, and C2H2, were signifi-cantly enriched, with five of them having ten or more upregu-lated members. Of these, we have earlier shown the detailedexpression patterns of bZIP, MADS and C2H2 families,wherein certain members are panicle/seed-specific (Agarwalet al. 2007; Arora et al. 2007; Nijhawan et al. 2008). Similaranalysis of downregulated genes revealed 14 gene familiesincluding WRKY, C2H2, and AP2 with higher number ofmembers downregulated in panicles; whereas, 27 gene fami-lies including bHLH, TUBBYand C3H had higher number ofdownregulated genes in seeds (Fig. 4). An enrichment analy-sis of downregulated members lays emphasis on genes whoseexpression is probably not an essential feature for the devel-opment process (Supplementary Table S5).

In total, 52 TF genes including members of bHLH, bZIP,B3, C2H2, HOMEOBOX, MADS, MYB, NAM, SBP, andWRKY gene families had vegetative stages-specific expres-sion with fifteen of them exhibiting SAM-specific and tengenes exhibiting root-specific expression in contrast to onlyone gene specific to each leaf and seedlings. Panicle stageswere found to have specific expression of only eleven TFgenes having representation of two genes each from bHLHand DOF gene families. Forty-seven TF genes exhibitedseed-specific expression with a majority of them beingspecific to the S2 stage (2–5 DAP), suggesting that S2 mightrepresent an important developmental hot spot that shouldbe investigated in detail. A hierarchical cluster map showing

expression profiles of the transcription factor coding genesexpressing in a developmental stage specific manner ispresented in Supplementary Figure S10.

Gene Clusters with Similar Expression profiles

Previous studies have shown correlation between expressionprofiles and physical location of genes in eukaryoticgenomes including Drosophila, nematode, mouse, andhumans (Michalak 2008). Such a phenomenon has also beenidentified in rice and Arabidopsis (Ren et al. 2005; Ren et al.2007; Zhan et al. 2006). To get a genome-wide perspectiveof the influence of physical proximity of genes on theirexpression profiles, we selected 18,180 differentiallyexpressed genes (≥2 folds with NAEV ≥50) and analyzedtheir physical location on rice chromosomes as described inthe “Materials and methods” section. This analysis revealed1,278 GCSE profiles comprising of 2,792 genes(Supplementary Tables S6 and S7). In total, 25 varied ex-pression patterns were observed (Supplementary Table S8),of which 8 major patterns comprising of more than 80 % ofthe data are shown in Fig. 5. The maximum number ofclusters was found to exhibit SAM + panicle-preferentialexpression (209) and vegetative stages-preferential expres-sion (200). One hundred and eighty-five clusters exhibitedpanicle-preferential expression; whereas, 147 GCSEs werefound to be seed-preferential. Most of the GCSEs (1,099)comprised of two genes. The largest GCSE included 12genes on chromosome 10 (10_43) exhibiting root-preferential expression followed by a cluster of 7 genes onchromosome 1 (Supplementary Table S6). We did not ob-serve any chromosomal bias in the distribution of GCSEs.To check if the genes comprising a GCSE were involved insimilar function, information related to their affiliation tovarious biochemical pathways was retrieved from Gramenedatabase (http://pathway.gramene.org/expression.html).Apparently, of the 35 clusters (74 genes), for which pathwaydata was available, genes in 18 clusters belonged to samebiochemical pathways. In ten of these GCSEs, however,some of the genes were found to have >70 % identity atamino acid level, which could suggest their origin fromtandem duplication events. The annotated genes in othereight GCSEs were involved in different pathways andexhibited <16 % identity in their protein sequences. In nineGCSEs, all the members of a cluster had not yet beenannotated, but, based on the available information; theyseem to be involved in similar pathways.

Molecular characterization of candidate promoters

Based on their expression profiles, we selected four geneswith stage-specific/preferential expression in panicle andseed stages namely, OsAGO3 (LOC_Os04g52550),

238 Funct Integr Genomics (2012) 12:229–248

Fig. 4 Graphical representation of a up- and b downregulated tran-scription factor family genes in panicle and seed stages. The totalnumber of genes of each transcription factor family represented onthe GeneChip® is shown in the form of area graph (gray). The graph adepicts the number of upregulated and graph b depicts the number of

downregulated genes, respectively, in panicle (red) and seed (green)stages. The axis on the left represents the number of differentiallyexpressed genes (shown in bar chart); whereas, broken axis withdifferent data ranges on the right represents total number of genesrepresented on the GeneChip® (shown by the area graph)

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OsSub42 (LOC_Os04g45960), RTS (LOC_Os01g70440),and XYH (AK108917) exhibiting P3–P4, P4–P5, P5–P6,and S1 specific expression, respectively, for in planta vali-dation of promoter activities. Analysis of meta-profiles ofthese genes in Affymetrix data during developmental stagesshowed consistency in expression profiles of these geneswith the publicly available data (Supplementary FigureS9a). The respective expression profiles were validated us-ing qPCR and promoter-reporter constructs were preparedusing GUS as reporter (Fig. 6). OsAGO3 is an argonautefamily gene containing PIWI domain (Sharma et al. 2010)with high transcript accumulation in P3 and P4 stages. Thepromoter activity was observed specifically in anthers atmeiotic and tetrad stage suggesting its involvement inmicrosprorogenesis (Fig. 6). Analysis of its meta-profileduring consolidated data from microarray experiments cov-ering anatomical stages showed that its transcripts are par-ticularly enriched in 0.7 to 1.0 mm anthers (SupplementaryFigure S9b). The second gene, OsSub42 encodes asubtilisin-like serine protease detected in P4 and P5 stages.The GUS activity was observedmainly in anthers, specifically

Fig. 5 Chromosomal localization of co-expressed genes in rice.Microarray-based expression profiles of co-expressed genes at 19stages of vegetative and reproductive development were extractedand plotted in sequential order based on their location on rice

chromosomes. Each profile is shown by a different color. The colorlegend has been given at the base. The chromosome numbers areindicated on the left and Locus ID of first and last gene comprising acluster on each chromosome has been given

�Fig. 6 Expression profiles of candidate genes and respective promoters.The panel on the left presents the expression profiles exhibited by candi-date genes.Black bars represent the values obtained using microarray andwhite bars represent qPCR data. The qPCR values have been normalizedto those obtained from the microarray dataset. The error bars representthe standard error between three biological replicates of each stage. Thegene names are given in the top left corner of each graph. Right panelrepresents the expression of GUS reporter derived by promoters ofcandidate genes in different stages of development in rice. Stages ana-lyzed are as below: a amature leaf, b root, c T.S. stem, d seed, e, f floret atP3, g floret at P4, h floret at P5, i, j floret at P6, k anther of floret at P3,l anther of floret at P4,m anther of floret at P6, nmature gynoecium. Scalebar (a–j) 1 mm, (k–n) 0.1 mm. b a mature leaf, b root, c stem, d matureseed, e, i florets at P2, f, j florets at P3, g, k florets at P4 stage, h, l matureflorets. Scale bar, 0.5 mm. c a mature leaf, b T.S. stem, c root, d matureseed, e floret at P3, f floret at P4, g, h floret at P5, i floret at P6, j maturefloret at P6 after anthesis, k dissected P6 floret showing GUS stainedanthers, l anther at P6, m stigma at P6, n isolated pollen at P6. Scale bar(a–k) 1 mm, (l–n) 0.1 mm. d a callus, b mature leaf, c root at pre-pollination stage, d pollen at P6, e anther at P6, f floret at P6, g gynoeciumat P6, h seed at S1 stage, i 0 DAP seed (S1), j, k 1 DAP seed (S1), l 2 DAPseed (S1),m seed at S2 stage, n seed at S3 stage, o seed at S5 stage. Scalebar, 0.5 mm. “1” represents wild type and “2” denotes the transgenicplant. The scale bar is equal to 0.5 mm

240 Funct Integr Genomics (2012) 12:229–248

Funct Integr Genomics (2012) 12:229–248 241

at single-celled microspore and bicellular pollen stage withvery low-level expression in nodal portion of the stem, stigmaand embryo (Fig. 6). Upon dissection of anthers at uninucleatestage, GUS activity was observed in the anther wall as well asin developing pollen. Meta-profile analysis during ana-tomical stages showed accumulation of its transcripts in1.2 to 1.5 mm anthers (Supplementary Figure S9b). Thethird gene, RTS is an anther-specific gene that expressesexclusively in tapetum and has been shown to be essen-tial for pollen development in rice (Luo et al. 2006). TheRTS promoter derived specific expression in post-meioticanthers with low level GUS activity in stigma. Meta-profile analysis revealed its specific expression in 1.6to 2.0 mm anthers (Supplementary Figure S9b). XYHexhibiting S1 stage-specific expression encodes 1, 4-beta-D xylan xylanohydrolase. The GUS activity wasobserved specifically in ovary and style in pollinatedpanicles suggesting that it might have role during pene-tration of pollen tube. Meta-profile analysis during ana-tomical stages conforms its specific expression in ovariesat 1 day after fertilization (Supplementary Figure S9b).The consistency in the expression profiles of these genesin specific developmental events/stages and organsstrengthens the reliability of our microarray data as wellas staging system used.

Discussion

The reproductive phase in rice commences with the transitionof shoot apical meristem to floral meristem and culminates atmature seed about a month after fertilization (Itoh et al. 2005).Since genes regulating panicle and seed development aremajor determinants of yield, understanding gene regulationis crucial for improving yield potential of rice. Here, weanalyzed the genome-wide spatial and temporal expressionprofiles of rice genes during nine stages of panicle and fivestages of seed development, demarcated based on the land-mark events involved. The transcriptome of each develop-mental stage was compared with the vegetative tissues aswell as the preceding stage of development to investigatestage-specific regulation of gene expression. Analysis ofstage-specific/preferential gene expression along with litera-ture mining revealed that the upregulated genes in our study,during panicle initiation stages (P1-I, P1-II, and P1-III) withrespect to vegetative controls have previously been implicatedin flowering time control (OsFTL1, OsMADS5, OsMADS14,and 15 of rice; Komiya et al. 2008; Jia et al. 2000; Lee et al.2003; Moon et al. 1999; Kang and An 1997), meristemorganization (CLAVATA1 of Arabidopsis; Clark et al. 1997),and regulating symmetry (DIV of Antirrhinum; Galego andAlmeida 2002), thus adding credibility to our data. Homologsof previously characterized genes for involvement in

establishment of polarity (FE of Ipomea; Iwasaki andNitasaka 2006), sexual fate of meristems (TS2 of maize;DeLong et al. 1993), and brassinosteroid response (BIM2 ofArabidopsis; Yin et al. 2005) were specifically upregulated inP1-I stage; whereas, those showing similarity with genesassociated with circadian clock (LHY and ELF3 ofArabidopsis; Ding et al. 2007; Liu et al. 2001), flowering timecontrol (FPF1 and CO of Arabidopsis; Kania et al. 1997; Anet al. 2004), panicle branch initiation (RFL of rice; Kyozuka etal. 1998), and organ primordia formation (ZmOCL1; Ingramet al. 2000) were specifically upregulated in P1-II stage. Thelist of genes showing P1-II specific upregulation also includedthose involved in meristem organization (TSO1 ofArabidopsis; Song et al. 2000) and cell specialization inanthers (TPD1 of Arabidopsis; Yang et al. 2003). Inductionof 80 genes was detected in both P1-I and P1-II stages includ-ing genes involved in initiation and maintenance of rachis andbranch meristem (LAX and, OSH1 of rice and JUBEL2 ofbarley; Komatsu et al. 2001; Sentoku et al. 1999; Muller et al.2001), panicle branching (OsTB1 of rice; Takeda et al. 2003),whereas those showing upregulation in P1-II–PI-III window(146 in number) included genes involved in flowering timecontrol and floral organ identity (OsMADS1, 2, 6, 7, 8, and 58of rice; Agrawal et al. 2005; Chung et al. 1994; Chung et al.1995; Greco et al. 1997; Jeon et al. 2008; Kang et al. 1997;Lee et al. 2003; Prasad et al. 2005; Prasad et al. 2001; Prasadand Vijayraghavan 2003; Yamaguchi and Hirano 2006;Yamaguchi et al. 2006; Jeon et al. 2000), auxiliary meristeminitiation (SPT of Arabidopsis; Komatsu et al. 2003), anddetermination of floral organ number and shape (PNH ofArabidopsis; Lynn et al. 1999).

Similarly, overlaying the data of differentially expressedgenes on RiceCyc database provided important insights intogenes and pathways that are specifically altered during ricereproductive development. For instance, jasmonic acid andphenylpropanoid biosynthesis pathways are mainly upregu-lated during panicle development and IAA biosynthesisduring early seed development. Since several genes in-volved in jasmonic acid and phenylpropanoid biosynthesishave already been implicated in anther dehiscence and pol-len development (Ma 2005; Yang et al. 2007; Millar et al.1999; Wilson and Zhang 2009), detailed investigation of thenovel candidate genes, related to these pathways, identifiedin this study would be useful.

Seed development in rice involves embryo and endo-sperm development, encompassing cell division, organ ini-tiation, and maturation (Agarwal et al. 2011; Itoh et al.2005). The genes homologous to cell differentiation proteinRCD1 of wheat and FIE2 of Arabidopsis exhibit S2–S3–S4stage-specific expression (Danilevskaya et al. 2003; Drea etal. 2005; Okazaki et al. 1998). The homolog of Arabidopsislate embryogenesis protein D-34 expresses specifically inS2–S3–S4–S5 stages (Hundertmark and Hincha 2008). Rice

242 Funct Integr Genomics (2012) 12:229–248

genes homologous to Arabidopsis MFT and DC-8 of carrot,implicated in grain maturation and OlE-5 of coffee involvedin stabilization of oil bodies in embryos were detectedspecifically in S3–S4–S5 stages (Chardon and Damerval2005; Cheng et al. 1996; Simkin et al. 2006). It would beinteresting to examine if these genes in rice have similarfunctions to the ones already deduced in other plants. Also,the genes involved in auxin distribution and transport havebeen shown to play a role in establishing embryonic patternin wheat (Fischer-Iglesias et al. 2001). Functional character-ization of IAA biosynthesis genes identified in this studymight, therefore, prove useful in understanding the role ofIAA in embryo establishment.

The role of gibberellins in floral induction, bolting anddevelopment of anther, pistil, and seed has been well docu-mented (Hu et al. 2008). Upregulation of genes involved ingibberellins biosynthesis during panicle and seed develop-mental stages reiterates its role in rice reproductive develop-ment. Some of the genes controlling same step of betanidindegradation, brassinosteroid biosynthesis, flavonoid biosyn-thesis, homogalacturonon degradation, cytokinin glucosidebiosynthesis, and sucrose degradation exhibited eitherpanicle- or seed-specific expression suggesting that probablydifferent genes may have taken up similar functions in differ-ent tissue types.

The regulation of these metabolic and hormonal pathwaysat transcriptional level is partly executed by specific transcrip-tion factors. Therefore, spatial and temporal expression pat-terns of genes encoding transcription factors can reveal thetarget genes serving as nucleation points for building generegulatory networks. The list of seed-specific transcriptionfactor genes included those belonging to MYB and NAMfamilies followed by noteworthy representation from AP2,AUX_IAA, bZIP, C3H, HSF, and MADS-box families.Many genes belonging to these families are critical for theprocess of seed development (Agarwal et al. 2011). Similarly,significant enrichment of bZIP, MADS, and C2H2 familiesduring panicle development highlights potential sites of theirfunction. Therefore, this analysis has revealed a large datasetof candidate genes, which apparently play important roles indifferent stages of panicle and seed development.

The gene expression dataset presented here would also bea useful resource to mine candidates for promoter functionvalidation. The genes exhibiting P3–P6 specific high ex-pression are likely to have anther-specific expression. Thepromoters of these genes once verified in transgenic systemcan be used to generate male-sterile lines for hybrid seedproduction (Gupta et al. 2007; Perez-Prat and van LookerenCampagne 2002; Roque et al. 2007; Twell et al. 1990; Xu etal. 2006). Since meiosis is the main source of variationbecause of recombination, halting meiosis by targeting P2and P3-specific genes could be another approach to multiplythe elite varieties without variations. Many of the genes

exhibiting P6 stage-specific expression encode allergens.Switching off these genes by knock out mutation/RNAiapproaches can have significant impact on society by reduc-ing the allergy cases (Bhalla et al. 2001). Similarly, seed-specific promoters could have important implications inimproving grain quality and yields in cereal crops and havebeen exploited for the production of biologically/commer-cially relevant products (Aluru et al. 2008; Furtado andHenry 2005; Furtado et al. 2008; Lamacchia et al. 2001;Qu le and Takaiwa 2004; Russell and Fromm 1997;Sunilkumar et al. 2002).

The identification of reproductive stage-specific genes isnot trivial. In past few years, many groups have attempted tounderstand transcriptional dynamics during rice panicle andseed development (Endo et al. 2002; Fujita et al. 2010;Furutani et al. 2006; Jiao et al. 2009; Kondou et al. 2006;Ma et al. 2005; Sato et al. 2011; Wang et al. 2010).However, very less overlap is observed among the datasetsgenerated across different studies. This is largely because ofdifferences in tissue sampling and subspecies/varieties usedin different experiments. Moreover, tissue/stage-specific ex-pression is strongly influenced by choice of microarrayplatform and parameters used for data analysis. For instance,when we compared our panicle and seed-specific datasetswith those extracted by Wang et al. (2010) and Sato et al.(2011), fewer genes were common between datasets gener-ated from different rice subspecies. Since we used prepro-cessed datasets by both the groups for comparison, differentmethodologies used would be another cause of less redun-dancy in these datasets. For extracting specific datasets, bothWang et al. (2010) and Sato et al. (2011) have used Shannonentropy values [<3 and <4.5, respectively] as a measure toassess tissue-specificity. Sato et al. (2011) further filtered thedata by applying a stringent minimum expression value (8 inlog2) cut-off in at least one of stages interrogated. SinceShannon entropy values do not discriminate between bio-logically relevant stages, a large number of genes withrelatively high expression in non-reproductive stages havealso been shortlisted in both these reports. We, however,worked on log2 normalized expression value cut-offs of <15(3.9 in log2, for a gene to be called not-expressed) and >50(5.6 in log2, for a gene to be called expressed). Selection ofthese cut-offs was based on normalized signal intensityvalues of non-rice probes (Magnaporthe grisea) on the riceAffymetrix chip (Deveshwar et al. 2011), which was used todiscriminate between expressed and non-expressed genes.In spite of all these differences, significant number of geneswas common between the panicle/seed-specific datasetsextracted in all three studies (Supplementary Figure S7).These genes would likely have higher reproducibility andthus would serve as candidates for detailed investigation(Supplementary Table S4). By generating meta-profiles ofshortlisted genes/datasets, we have shown that large-scale

Funct Integr Genomics (2012) 12:229–248 243

meta-analysis by integrating data generated in independentstudies can provide cross validation of gene expression.

The next challenge would be to decipher genetic regula-tory networks by integrating existing information resources.Coupling multiple datasets with co-expression analysis willhelp in elucidating gene clusters underlying biological pro-cesses. As a first step towards this, we have made an attemptto analyze the correlation between expression and physicallocation of genes on the genome. The close placement of2,792 genes on rice chromosomes comprising a total of1,278 GCSEs suggests a link between genome organizationand regulation of expression. Though many of these regionscould also have resulted due to tandem duplications, pres-ence of different set of genes in a cluster suggested thatthese might have co-evolved for regulation of similar bio-logical processes. Several groups have tried to explain thephenomenon based on tandem duplications, overlappinggenes, chromatin domains, shared regulatory elements, clus-tering of genes involved in similar metabolic pathways, etc.but so far no single factor could explain it (Michalak 2008).Further analysis of these genes will reveal if they are in-volved in a regulatory cascade or their expression could beattributed to the ripple effect of transcriptional activation,where intensive transcription activity at one locus may causeupregulation of its physically neighboring loci (Carninci2008; Ebisuya et al. 2008).

Acknowledgements This work was supported by Department ofBiotechnology, Ministry of Science & Technology, Government ofIndia (Project No. BT/AB/FG-I(PH-II)(4)/2009). We acknowledgeDr. Ramesh Hariharan and his team at Strand LS Bengaluru, Indiafor their help in microarray data analysis and Ms. Manupriya forproviding the list of transcription factor family genes in rice. SeniorResearch fellowship by the Council for Scientific and Industrial Re-search (CSIR) to R.S., S.R., P.D, M.J., A.N., and P.S. and UniversityGrants Commissions (UGC) fellowship to P.A. are acknowledged.

Microarray data used in this study have been deposited in the GeneExpression Omnibus database at the National Center for Biotechnolo-gy Information under the accession nos. GSE6893 and GSE6901. Allthe datasets shortlisted in this manuscript including list of panicle orseed-specific genes, differentially expressed genes during panicle orseed development with respect to all four vegetative stages and uniquegenes upregulated with respect to preceding stage of development aregiven in Supplementary Table S3.

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