Transcriptional profiles of spatially and temporally restricted cell populations from the Arabidopsis gynoecium reveals the meristematic nature of the gynoecial medial domain.
Abstract
Plant meristems, like animal stem cell niches, maintain a pool of multipotent, undifferentiated cells that divide and differentiate to give rise to organs. In Arabidopsis (Arabidopsis thaliana), the carpel margin meristem is a vital meristematic structure that generates ovules from the medial domain of the gynoecium, the female floral reproductive structure. The molecular mechanisms that specify this meristematic region and regulate its organogenic potential are poorly understood. Here, we present a novel approach to analyze the transcriptional signature of the medial domain of the Arabidopsis gynoecium, highlighting the developmental stages that immediately proceed ovule initiation, the earliest stages of seed development. Using a floral synchronization system and a SHATTERPROOF2 (SHP2) domain-specific reporter, paired with FACS and RNA sequencing, we assayed the transcriptome of the gynoecial medial domain with temporal and spatial precision. This analysis reveals a set of genes that are differentially expressed within the SHP2 expression domain, including genes that have been shown previously to function during the development of medial domain-derived structures, including the ovules, thus validating our approach. Global analyses of the transcriptomic data set indicate a similarity of the pSHP2-expressing cell population to previously characterized meristematic domains, further supporting the meristematic nature of this gynoecial tissue. Our method identifies additional genes including novel isoforms, cis-natural antisense transcripts, and a previously unrecognized member of the REPRODUCTIVE MERISTEM family of transcriptional regulators that are potential novel regulators of medial domain development. This data set provides genome-wide transcriptional insight into the development of the carpel margin meristem in Arabidopsis.
The seed pod of flowering plants develops from the gynoecium, the female reproductive structure of the flower (Seymour et al., 2013). The gynoecium generates the ovules (the precursors of the seeds) and develops into the edible fruit in many fruiting species. As an estimated two-thirds of the calories of humankind’s diet are derived from gynoecia and seeds, the gynoecium is a globally vital structure (Oram and Brock, 1972; Singh and Bhalla, 2007).
In the flowering plant Arabidopsis (Arabidopsis thaliana), the gynoecium is a morphologically complex, multiorgan structure with a diversity of tissues and cell types (Sessions and Zambryski, 1995; Bowman et al., 1999; Seymour et al., 2013). The mature gynoecium displays morphological and functional differentiation along apical-basal, medio-lateral, and adaxial-abaxial (inner-outer) axes. Stigmatic and stylar tissue form at the apex of the gynoecium, where the pollen grains are received and germinate. The stigma and style also constitute the apical-most portion of the transmitting tract, a structure that allows the pollen tube cell and sperm cells to reach the internally located female gametophytes (Sessions and Zambryski, 1995; Sessions, 1999; Crawford and Yanofsky, 2008; Fig. 1, A–C). Located basal to the stigmatic and stylar tissue is the ovary portion of the gynoecium.
Figure 1.
A system for the collection of temporally and spatially restricted cell populations from the Arabidopsis gynoecium. A, Microscopic image of a mature wild-type Arabidopsis gynoecium. The stigma (stg), style (sty), carpel valve (cv), abaxial replum (abr), gynophore (gn), and ovary (ovy) are false colored. B, False-colored confocal cross section of a stage 8 gynoecium. Medial and lateral domains of the Arabidopsis gynoecium are indicated. The CMM/medial ridge is false colored pink. C, False-colored stage 11 cross section. Ovules (ov), septum (s), and carpel valves (cv) are indicated. D, Confocal microscope image of the pSHP2-YFP two-component reporter in the pAP1-AP1::GR; ap1; cal background. YFP expression from the pSHP2-YFP reporter is confined chiefly to the medial domain of the gynoecium at late stage 7/early stage 8, although weak, nonmedial domain expression can be detected in portions of the stamens. Sepals (Se) and stamens (St) are labeled. E, Z-stack composite three-dimensional projection image of a gynoecium isolated from the flower at midstage 8. YFP expression from the pSHP2-YFP reporter is detected in the medial domain and at the apex of the gynoecium. F, Chloral hydrate image of an inflorescence of a pAP1-AP1::GR; ap1; cal plant after mock treatment. Inflorescence-like meristems do not transition to floral meristems. G, Chloral hydrate image of an inflorescence of a pAP1-AP1::GR; ap1; cal plant 125 h after spray application of dexamethasone synthetic hormone. Samples were enriched for stages 6 to 8. H, Percentage of flowers at a given stage from inflorescences used for FACS sorting. Stages 6, 7, 8p (preovules), and 8s (postovules) are indicated on the x axis as St6, St7, St8p, and St8s, respectively. Stage 8p is before any visible morphological manifestation of ovule primordia upon observation under differential interference contrast (DIC) microscopy. Stage 8s ovule primordia were observed and were at ovule stage 1-I or 1-II according to Schneitz et al. (1995). I, Confocal microscopy of YFP fluorescence of protoplasted cells after FACS. A to C are adapted from Azhakanandam et al. (2008) with permission.
Ovules form within the ovary from a meristematic structure termed the medial ridge or carpel margin meristem (CMM), located in medial portions of the gynoecium (Bowman et al., 1999; Alvarez and Smyth, 2002; Reyes-Olalde et al., 2013; Fig. 1, A–C). Plant meristems are analogous to animal stem cell niches, as they maintain a set of undifferentiated cells that can divide and differentiate into numerous tissues and cell types (Aichinger et al., 2012). Early during floral development, patterning events divide the gynoecial primordium into a medial domain that contains the CMM and lateral domains that will form the walls of the gynoecium (Bowman et al., 1999). These domains express different sets of transcriptional regulators from early developmental time points.
Many genes that play a role in the development of the CMM and in the generation of ovules from this structure have been analyzed previously (Reyes-Olalde et al., 2013). However, due to the complexity of the developing gynoecium and the heterogeneity of the gynoecial tissues, the ability to analyze the transcriptomic signature of the developing CMM or even other specific developing gynoecial structural domains has been limited. Wynn et al. (2011) previously evaluated the transcriptional properties of the gynoecial medial domain using hand-dissected gynoecial samples from the seuss aintegumenta (seu ant) double mutants that display a loss of many medial domain-derived structures, including ovules. They identified 210 genes displaying reduced expression in seu ant gynoecia from floral stages 8 to 10 (stages according to Smyth et al. [1990]). Many of these genes were shown via in situ hybridization to be preferentially expressed in the developing medial domain of the wild-type gynoecium, and several of these genes have been shown to function during the development of ovules from the medial domain (Reyes-Olalde et al., 2013). However, it is difficult with this approach to obtain samples from gynoecia younger than stage 8 and, thus, to assay the earliest gynoecial patterning events.
An alternative approach to investigate the transcriptional properties of specific cellular populations utilizes FACS of protoplasted cells to isolate specific cell populations based on patterns of gene expression. This approach has been applied successfully to the Arabidopsis shoot apical meristem (SAM; Yadav et al., 2009, 2014) and roots (Birnbaum et al., 2003, 2005; Carter et al., 2013; Lan et al., 2013) as well as to developing cell lineages within the Arabidopsis leaf epidermis (Adrian et al., 2015).
Here, we developed a novel FACS-based system for the transcriptomic analysis of a specific cellular population from the developing gynoecium, specifically the population of cells expressing the transcriptional regulator SHATTERPROOF2 (SHP2). SHP2 encodes a MADS domain transcription factor that is expressed early within the developing CMM and, thus, functions as a marker for the meristematic population of cells that generate the transmitting tract and ovules (Ma et al., 1991; Savidge et al., 1995; Colombo et al., 2010; Larsson et al., 2014). In order to focus our analysis on early stages of gynoecium development during which key patterning events occur, we generated a SHP2 domain-specific reporter in a genetic background that allowed the synchronization of floral development. This, coupled with FACS-based protoplast sorting procedures and RNA sequencing (RNA-seq), provided a unique temporal and spatial precision to assay the transcriptional signature of the gynoecial SHP2 expression domain.
Our system provides the ability to isolate large numbers of cells from a temporally and spatially restricted gynoecial domain. We apply this method to investigate the transcriptomic signature of the medial domain of the gynoecium at the developmental stages when key patterning events and ovule initiation occur. Our analysis reveals many genes that are expressed preferentially within the developing medial portions of the gynoecium, including members of the REPRODUCTIVE MERISTEM (REM) family of transcriptional regulators (Swaminathan et al., 2008; Romanel et al., 2009). We also take advantage of strand-specific RNA-seq technology to find protein coding genes and noncoding RNAs as well as to examine isoforms and naturally occurring antisense transcripts that are expressed preferentially in the medial domain. This work complements and extends previous analyses of medial domain development and generates a list of potential novel regulators of medial domain development that are strong candidates for future functional analyses. Furthermore, global analyses of the transcriptomic data set indicate a similarity of the pSHP2-expressing cell population to previously characterized meristematic domains, further supporting the meristematic nature of this gynoecial tissue.
RESULTS AND DISCUSSION
FACS-Based Protoplast Sorting Allows the Collection of the SHP2-Expressing Cell Population from a Temporally Restricted Inflorescence Sample
The transcriptional regulator SHP2 is preferentially expressed in the medial domain of the gynoecium and in a subset of the medial domain-derived tissues (Savidge et al., 1995; Colombo et al., 2010; Larsson et al., 2014; Fig. 1, D and E). SHP2 plays an important role in the development of the medial domain and in the specification of ovule identity (Liljegren et al., 2000; Favaro et al., 2003; Pinyopich et al., 2003; Colombo et al., 2010; Galbiati et al., 2013). To better characterize the molecular mechanisms of the medial domain and ovule development, we sought to identify transcripts that are differentially expressed within the medial domain of the Arabidopsis gynoecium relative to the rest of the inflorescence. To enable this, we generated a transgenic line containing a two-component reporter system in which a pUAS-3xYPET reporter was driven by a pSHP2-GAL4 driver construct (see “Materials and Methods”). Throughout this article, we refer to this two-component reporter as pSHP2-YFP (YFP for yellow fluorescent protein).
To better understand the early specification of medial and lateral gynoecial domains and in the earliest stages of ovule primordium initiation, we focused our transcriptomic analysis on floral stages 6 to 8, when these key developmental events occur (Bowman et al., 1999). In order to increase our ability to collect a large number of pSHP2-YFP-expressing cells from this specific bracket of developmental stages, we crossed the pSHP2-YFP reporter into an ap1 cal-based floral synchronization system that allows the collection of large numbers of semisynchronized flowers at roughly the same developmental stage (Wellmer et al., 2006; Ó’Maoiléidigh and Wellmer, 2014). The expression of the pSHP2-YFP reporter in the floral synchronization system was largely similar to that observed in wild-type inflorescences (Ma et al., 1991; Colombo et al., 2010; Larsson et al., 2014) and was confined chiefly to the medial domain and medial domain-derived tissues (Fig. 1, D and E). Some expression was observed in nonmedial gynoecial positions. The most apparent of this was within the apex of the developing gynoecium, where the pSHP2-YFP reporter is detected in both medial and lateral positions. Additionally, expression could be observed in a small number of cells within the stamens (Fig. 1D) and occasionally on the edges of sepals that appeared to have undergone a homeotic transformation toward a carpelloid fate (data not shown). Thus, the vast majority of the pSHP-YFP reporter expression reflected the endogenous pSHP2 expression domain (in the medial and apical portions of the gynoecium). We cannot exclude the possibility that a small minority of the expression domain may reflect ectopic expression of the reporter due to the genetic background or transgene insertion site or limitations of the regulatory sequences used in the pSHP-YFP reporter construct.
Microscopic examination of our semisynchronized inflorescence samples indicated that flowers ranged between floral stage 1 and early stage 8, with a strong enrichment for floral stages 6 through early 8 (Fig. 1, G and H). Flowers that had developed beyond late stage 8 were not detected in our samples. Thus, our biological sample is strongly enriched for transcripts that are expressed during early patterning of the gynoecium and the earliest stages of ovule development (initiation) and does not include later floral developmental stages, where SHP2 is expressed in stigma, style, and valve margin tissues. Additionally, as the initial expression of the pSHP-YFP reporter is detected at late stage 5 or early stage 6 (Larsson et al., 2014), we expect that the population of YFP-expressing protoplasts derived from this material will be highly enriched with cells from the stage 6 to 8 medial domain.
FACS sorting of protoplasts derived from these inflorescences yielded three populations of sorted cells (collected in biological quadruplicate): YFP-positive, YFP-negative, and all-sorted cells (Supplemental Fig. S1). The all-sorted sample included all protoplasts recovered (regardless of YFP expression) after sorting gates were applied to remove debris and broken cells (see “Materials and Methods”). We additionally collected (also in biological quadruplicate) nonsorted samples from entire nonprotoplasted inflorescences to measure the abundance of transcripts in the biological starting material before protoplast generation and FACS sorting. In order to evaluate the purity of the YFP-positive protoplasts during a preliminary FACS run, YFP-positive cells were resorted. Ninety-six percent of the YFP-positive cells were found to resort into the YFP-positive gate, indicating a high degree of enrichment and purity in the YFP-positive sample (Supplemental Fig. S1). Confocal microscopy also revealed an enriched population of intact YFP-positive protoplasts after FACS (Fig. 1I).
We used quantitative real-time (qRT)-PCR to estimate the degree of enrichment of the endogenous SHP2 and NGATHA1 (NGA1) transcripts in RNA samples derived from the YFP-positive and YFP-negative samples. NGA1 is expressed in the adaxial portions of the gynoecium starting at stage 7 in a domain that partially overlaps with the SHP2 expression domain (Alvarez et al., 2009; Trigueros et al., 2009) and thus provides an additional benchmark to estimate the enrichment of medial domain-expressed transcripts. The normalized level of the SHP2 transcript was approximately 30-fold higher in the YFP-positive samples relative to the YFP-negative samples (P < 0.001), while the NGA1 transcript was approximately 4-fold higher in the YFP-positive samples (P < 0.05). The difference in the levels of TUBULIN6 (TUB6) was not found to be statistically significant (P = 0.4) between the YFP-positive and YFP-negative samples (Supplemental Fig. S2).
Transcriptomic Analysis of the Gynoecial SHP2 Expression Domain and Identification of Candidate Regulators of Gynoecial Medial Domain Development
To investigate the transcriptomic profile of the gynoecial SHP2 expression domain, we performed high-throughput RNA-seq from the collected protoplasts and nonprotoplasted inflorescence samples. We expect that the identification of differentially expressed genes (DEGs) between the YFP-positive and YFP-negative samples (referred to as YFP+/−) will provide insight into the set of transcripts differentially expressed in the gynoecial medial domain relative to the rest of the inflorescence. Additionally, DEGs identified in the all-sorted and nonsorted comparison (referred to as all-sorted/nonsorted) are expected to reveal transcripts that are differentially represented as a result of the protoplasting/FACS-sorting protocol.
Two lanes of the HiSeq2500 Illumina sequencing platform yielded 320 million raw reads, with an average of 20 million reads per library. Nearly 11 million reads were filtered out after removing barcode adapters and low-quality sequences. The remaining 306 million reads were aligned against The Arabidopsis Information Resource (TAIR) 10 reference genome (Lamesch et al., 2012), with more than 90% of them successfully mapping to the genome sequence. Among the mapped reads, 244 million reads mapped uniquely to only one location and were used for subsequent analyses. A detailed breakdown is shown in Supplemental Table S1.
We used three different programs to determine expressed and differentially expressed protein-coding genes in our data set: Cufflinks (Trapnell et al., 2012), edgeR (Robinson et al., 2010), and DESeq2 (Love et al., 2014; see “Materials and Methods”); non-protein-coding gene models were considered separately and are presented below. These open-source programs are among the most cited RNA-seq analysis tools used for the identification of DEGs. Various studies suggest that, among the different RNA-seq analysis tools, no single method outperforms the other ones (Rapaport et al., 2013; Soneson and Delorenzi, 2013). In our study, we compared the results of edgeR, DESeq2, and Cufflinks using our data set (Fig. 2). Our choice of these three tools reflects significant differences in the underlying algorithms. Cufflinks uses isoform expression estimates, while edgeR and DESeq2 compute gene level-based expression estimates. Furthermore, edgeR and DESeq2 use different normalization approaches and dispersion estimates. As these three programs use different algorithms, we expected each program to return a somewhat different set of DEGs. Here, the term DEG is used to indicate a gene whose steady-state transcript level differs significantly at a false discovery rate (FDR) < 0.001 and shows a fold change of 4 or more between the two compared RNA samples.
Figure 2.
Venn diagrams of DEGs using Cufflinks, edgeR, and DESeq2 (FDR < 0.001 and fold change > 4). A, Venn diagram showing DEGs identified between the all-sorted/nonsorted samples with the three programs used for differential expression analysis of RNA-seq expression profiles. B, Venn diagram showing DEGs between YFP+/− samples identified in the three programs. C, Intersection of the DEGs (48) from both data sets (A and B). A total of 363 DEGs, after removing DEGs induced by the protoplasting/FACS-sorting stress, were used for downstream analysis.
We reasoned that any gene identified as a DEG by all three programs was highly likely to be differentially expressed in our data set. Thus, to identify potential regulators of gynoecial medial domain development, a stringent criterion was used to select a subset of the YFP+/− DEGs for downstream analysis. For a gene to be selected from the YFP+/− comparison, we required that the transcript be identified as differentially expressed by all three independent software packages. This led to the identification of 411 triply identified DEGs (e.g. the overlap sections in the Venn diagram in Fig. 2B).
Additionally, we sought to confirm that these 411 genes were not differentially expressed as a result of the protoplasting and sorting procedure. We reasoned that DEGs identified as differentially expressed between the all-sorted and nonsorted samples would characterize the set of genes whose expression was altered by the protoplasting and sorting procedure. As a conservative estimate of the protoplast-induced gene set, we identified transcripts in the union set of all the nonsorted/all-sorted DEGs (the union of the three software packages) even if they were identified by only one software program (Fig. 2A). This identified 880 genes as differentially expressed as a result of the protoplasting procedures. If the 411 triply identified YFP+/− DEGs truly represent a signature of the medial domain, then we expect a relatively small overlap between the set of DEGs identified in the two comparisons. Only 48 transcripts were found in common between the YFP+/− DEGs and the all-sorted/nonsorted DEGs (Fig. 2C), indicating a high degree of specificity in the DEGs identified in each comparison. We then removed these 48 transcripts from our analysis to eliminate any that might be differentially expressed as a result of the protoplast generation or FACS-sorting procedures, leaving 363 cleaned protein-coding DEGs from the YFP+/− comparison (Fig. 2C). We note that this gene set is a rather conservative estimate of the set of DEGs, as some of the 48 overlapping transcripts that were removed may indeed by differentially expressed between the YFP-positive and YFP-negative samples. Additionally, genes that display a statistically significant differential expression between the YFP-positive and YFP-negative samples at a magnitude of less than 4-fold may still be biologically significant. The expression profiles of these 363 YFP+/− DEGs are represented in a heat map (Supplemental Fig. S3). This gene set includes 95 DEGs whose transcript levels were higher in the YFP-positive samples (enriched) and 268 DEGs whose transcript levels were lower (depleted) in the YFP-positive samples relative to the YFP-negative samples (Supplemental Table S2).
For the 95 DEGs that were enriched in the YFP-positive sample (at a fold change > 4), we expected many to be preferentially expressed in the medial portions of the gynoecium at floral stages 6 to 8. To test this, we examined the literature to determine the expression patterns of members of this gene set. From the top 15 of the 95 YFP-positive enriched DEGs (ranked by fold change), five have been reported previously to be preferentially expressed in the gynoecial medial domain via in situ or reporter gene analysis (i.e. HECATE1 [HEC1], HEC2, SHP1, SHP2, and STYLISH1 [STY1]; Ma et al., 1991; Savidge et al., 1995; Kuusk et al., 2002; Gremski et al., 2007; Colombo et al., 2010) and three others were described previously as enriched in medial domain-derived tissues in published transcriptomic data sets (i.e. AT1G66950, AT5G14180, and AT1G03720; Skinner and Gasser, 2009; Wuest et al., 2010; Table I). An additional gene from this list, CRABS CLAW (CRC), has been shown via in situ hybridization to be expressed in portions of the medial gynoecial domain as well as nonmedial portions of the gynoecium (Bowman and Smyth, 1999; Azhakanandam et al., 2008). The expression pattern of the remaining six genes from this gene list have not yet been assayed in the gynoecium. Thus, as predicted, the set of 95 genes enriched in the YFP-positive sample is enriched for genes that are preferentially expressed in the gynoecial medial domain.
Table I. Top 15 DEGs enriched in the YFP-positive sample as ranked by fold change.
Arabidopsis gene identifiers are shown in the first column, gene names (TAIR 10 annotation) are shown in the second column, and the third column shows the reference for each available reporter line and/or in situ hybridization (NA, not applicable). Average RPKM values are indicated for each sample (YFP_NEG = YFP negative and YFP_POS = YFP positive).
| Gene Identifier | Gene Name | Reference for Expression | YFP_NEG Average Expression | YFP_POS Average Expression | Fold Expression Difference | P | FDR |
|---|---|---|---|---|---|---|---|
| AT3G50330 | HEC2 | Gremski et al. (2007) | 1.267 | 80.148 | 67.0 | 1.26E−81 | 5.36E−78 |
| AT5G67060 | HEC1 | Gremski et al. (2007) | 0.708 | 40.298 | 59.4 | 1.44E−105 | 2.44E−101 |
| AT1G66950 | ATPDR11 | Wuest et al. (2010) | 0.136 | 5.931 | 45.2 | 9.47E−76 | 2.02E−72 |
| AT3G58780 | SHP1 | Ma et al. (1991) | 1.678 | 54.233 | 33.9 | 1.06E−52 | 7.54E−50 |
| AT5G17040 | Unknown | NA | 0.272 | 7.453 | 28.0 | 1.06E−29 | 1.24E−27 |
| AT1G06920 | OFP4 | NA | 0.453 | 11.267 | 25.9 | 6.18E−34 | 1.04E−31 |
| AT3G51060 | STY1 | Kuusk et al. (2002) | 3.141 | 73.227 | 24.5 | 2.22E−98 | 1.89E−94 |
| AT5G14180 | MPL1 | Skinner and Gasser (2009) | 1.348 | 25.806 | 20.1 | 9.86E−52 | 6.22E−49 |
| AT2G42830 | SHP2 | Ma et al. (1991) | 1.642 | 31.392 | 20.1 | 1.58E−74 | 2.99E−71 |
| AT1G03720 | Unknown | Skinner and Gasser (2009) | 1.898 | 31.968 | 17.7 | 6.66E−52 | 4.54E−49 |
| AT2G33850 | Unknown | NA | 0.676 | 10.904 | 16.7 | 1.85E−19 | 7.15E−18 |
| AT1G69180 | CRC | Bowman et al. (1999) | 19.435 | 296.675 | 16.0 | 2.60E−78 | 8.84E−75 |
| AT2G22460 | Unknown | NA | 0.727 | 10.899 | 15.6 | 2.85E−17 | 8.52E−16 |
| AT2G21650 | MEE3 | Pagnussat et al. (2005); Baxter et al. (2007) | 1.333 | 17.643 | 13.9 | 1.65E−16 | 4.37E−15 |
| AT2G24540 | AFR | NA | 0.84 | 11.029 | 13.8 | 2.27E−24 | 1.61E−22 |
Published functional analyses of HEC1, HEC2, SHP1, SHP2, and STY1 indicate that these genes function during the development of the medial domain or medial domain-derived tissues (Kuusk et al., 2002; Favaro et al., 2003; Pinyopich et al., 2003; Gremski et al., 2007; Colombo et al., 2010). Many other genes in the set of 95 DEGs enriched in the YFP-positive sample have been shown previously to play a role in medial domain development (e.g. NGA family members [Alvarez et al., 2009; Trigueros et al., 2009], SPT [Heisler et al., 2001], and CUC2 [Kamiuchi et al., 2014]). Other genes within this list are interesting candidates for future functional studies. These include members of the REM family of transcriptional regulators (Swaminathan et al., 2008; Romanel et al., 2009), several auxin synthesis- or signaling-related genes, such as LIKE AUXIN RESISTANT1 (LAX1 [AT5G01240]; Bennett et al., 1996) and YUCCA4 (YUC4 [AT5G11320]; Cheng et al., 2006), as well as transcription factors regulating other developmental processes, such as MATERNAL EFFECT EMBRYO ARREST3 (MEE3 [AT2G21650]; Pagnussat et al., 2005) and GLABROUS3 (AT5G41315; Payne et al., 2000).
It is important to note that the 48 DEGs that were identified in both the YFP+/− and all-sorted/nonsorted comparisons (Fig. 2C) should not be discounted as potential medial domain regulators. These genes may be both preferentially expressed in the YFP-positive cell population and induced in response to the protoplasting procedure (Supplemental Table S2). Indeed, some of these genes, including the transcription factors HEC3 and BRASSINOSTEROID-ENHANCED EXPRESSION1, have been reported to be preferentially expressed in medial domain-derived tissues and to function in gynoecium development (Gremski et al., 2007; Crawford and Yanofsky, 2011). However, we chose to use the cleaned set of 363 YFP+/− DEGs for downstream analyses in order to reduce the likelihood of the inclusion of genes whose expression was significantly altered by the protoplasting process.
REM Family Members Are Differentially Expressed in the SHP2 Expression Domain
In order to look for enriched categories of transcription factors within the set of 363 cleaned YFP+/− DEGs (Fig. 2C), we used the online Transcription Factor Enrichment Calculator (https://dgrinevich.shinyapps.io/ShinyTF). Members of the ABI3/VP1 transcription factor family that includes the REM and NGA family transcription factors were found to be statistically overrepresented (Supplemental Table S7; corrected P < 9.97E-06). The REMs belong to the plant-specific B3 superfamily of transcription factors, and the expression of many REM family members is observed in meristematic tissues, such as the inflorescence meristem, floral meristem, and CMM (Franco-Zorrilla et al., 2002; Swaminathan et al., 2008; Romanel et al., 2009; Wynn et al., 2011; Mantegazza et al., 2014a, 2014b). The numerical designations used to describe the REM family members in this article are taken from Romanel et al. (2009). In our study, six REM members were among the 363 statistically significant YFP+/− DEGs; five were found to have enriched expression in the YFP-positive sample, while one, REM25 (AT5G09780), was approximately 4-fold less abundant in the YFP-positive sample. The REM13 (AT3G46770) transcript level is enriched approximately 12-fold in the pSHP2-YFP-expressing cells. REM13 was predicted previously to be preferentially expressed in the inner integument, ovule primordia, and medial domain based on transcriptomic data (Skinner and Gasser, 2009). We employed in situ hybridization to assay the expression pattern of the REM13 transcript during gynoecial development (Fig. 3). Using a REM13 antisense probe, we detected signal in the medial portions of the gynoecium corresponding to the CMM as early as stage 7. Expression also was observed in the initiating ovule primordia in stage 8 gynoecia and then continued to be detected in portions of the ovules at later developmental stages.
Figure 3.
The candidate medial domain regulator REM13 (AT3G46770) is expressed within the medial gynoecial domain and developing ovules (ov). Results are from an RNA in situ hybridization with REM13 probe. A to D, Antisense probes. E, Sense strand probe. A, Hybridization signal is detected in the CMM (adaxial portions of the medial gynoecial domain) in a stage 7 longitudinal section. B to D, In transverse gynoecial sections, REM13 expression is detected in the ovule primordia; stage 7 (B), stage 8 (C), and stage 9 (D) gynoecia are shown. E, A stage 8 section hybridized with a REM13 sense strand probe. Bars = 50 μm.
REM34/ATREM1 (AT4G31610; Franco-Zorrilla et al., 2002; Romanel et al., 2009), REM36 (AT4G31620; Mantegazza et al., 2014b), and VERDANDI (VDD/REM20; Matias-Hernandez et al., 2010; Mantegazza et al., 2014b) also displayed enriched expression levels in the YFP-positive sample of approximately 8-, 9-, and 6-fold, respectively. Published in situ hybridization patterns indicate enriched medial domain expression patterns for REM34/ATREM1 and VDD/REM20 (Franco-Zorrilla et al., 2002; Matias-Hernandez et al., 2010; Wynn et al., 2011). Additionally, the expression of AT5G60142, a previously unnamed member of the REM family, is enriched approximately 11-fold in the YFP-positive sample (Supplemental Table S3). AT5G60142 is an interesting candidate for functional studies that is located on chromosome V in tandem with REM11 (AT5G60140) and REM12 (AT5G60130) and shares a high degree of sequence similarity with these two genes as well as REM13 (Romanel et al., 2009; Mantegazza et al., 2014b). We propose to designate AT5G60142 as REM46.
Gene Set Enrichment Analysis
To gain global insights into underlying biological mechanisms of medial domain development and function, Gene Set Enrichment Analysis (GSEA) was performed for the 95 YFP-positive enriched DEGs in the medial domain. This analysis identified 147 Gene Ontology (GO) terms that were statistically overrepresented (P < 0.01), including gynoecium development (GO:0048467), flower development (GO:0009908), response to gibberellin (GO:0009739), and auxin homeostasis (GO:0010252; Fig. 4; Supplemental Table S6). This GSEA analysis further suggests that the set of 95 genes enriched in the YFP-positive sample function as regulators of medial domain development.
Figure 4.
GO term overrepresentation of SHP2 domain-enriched genes suggests a role for this set of genes in floral, gynoecial, and ovule development. The BiNGO/Cytoscape representation shows overrepresented GO terms from the 95 YFP+/− DEGs displaying enriched expression in the YFP-positive samples. Edges represent the parent/child relationships of the GO terms (Ashburner et al., 2000), while the color of the nodes indicates the degree of statistical significance (P < 0.01) as reported by BiNGO (Maere et al., 2005). To unclutter the figure, given the large number of significant GO terms, selected nodes and edges were removed from this graphical representation.
In contrast, when performing GSEA with DEGs identified between the all-sorted/nonsorted samples, a different set of 304 overrepresented GO terms were identified, including response to stress (GO:0006950) and response to wounding (GO:0009611), suggesting that many of the genes identified as differentially expressed between the all-sorted/nonsorted samples reflect stress-induced changes in gene expression during protoplast/FACS sorting.
The Transcriptomic Signature of the SHP2-Expressing Cell Population Shares Commonalities with the Transcriptional Signatures of Other Meristematic Samples
In order to gain insight into the characteristics of the 363 YFP+/− DEGs identified from the SHP2 expression domain, we compared the expression profile of this set of genes across several different tissues. Using Spearman rank correlation analysis, we compared our data set with existing Arabidopsis RNA-seq transcriptomic data sets from whole flowers (Mizzotti et al., 2014) and aerial seedling tissues (Gene Expression Omnibus [GEO] accession no. GSE54125) as well as from laser-capture microdissected inflorescence meristems, floral meristems, and stage 3 flowers (Mantegazza et al., 2014a). In the sample-wise hierarchical clustering (Fig. 5A), the transcriptomic profiles from the SHP2-expressing (YFP-positive) sample clustered more closely with the meristematic samples, while the YFP-negative and all-sorted samples clustered more closely with the whole-flower and whole-seedling samples. This suggests that the expression signature of the YFP-positive sample is more similar to that of the floral and inflorescence meristems and young flowers than it is to whole flowers or young vegetative seedlings (Fig. 5A).
Figure 5.
The transcriptomic signature of the SHP2-expressing domain is more similar to the transcriptomes of other meristematic samples than it is to whole flower. A, Dendrogram based on hierarchical clustering using Spearman rank correlation using RNA-seq (RPKM) expression values from flowers and other tissues. B, Comparison of RNA-seq and Affymetrix ATH1 array samples including transcriptomic data from whole flower, SAM, and seedling. WT, Wild type. Data from Mizzotti et al. (2014)(1), Mantegazza et al. (2014a)(2), GEO accession number GSE54125(3), and Yadav et al. (2009, 2014)(4) were used for comparison. Samples corresponding to this study are color coded red in both dendrograms.
Further supporting the similarity of the SHP2-expressing domain to other meristematic samples, the expression levels of GA20OX1 (AT4G25420) and GA20OX2 (AT5G51810) were both significantly depleted in the YFP-positive sample relative to the YFP-negative sample (Supplemental Table S10). GA20OX1 and GA20OX2 encode key biosynthetic enzymes of the plant hormone GA (Phillips et al., 1995). Levels of expression of GA20OX1 and GA20OX2 are low in the SAM relative to expression in the juxtaposed young organ primordia, and high levels of GA synthesis interfere with the maintenance of meristematic fate in the SAM (Hay et al., 2002; Jasinski et al., 2005). These data suggest that low levels of GA also may be associated with the meristematic nature of the CMM. Although not discussed here, the expression values of genes annotated with a role in ethylene signaling are found in Supplemental Table S10.
We additionally compared the medial domain transcriptional signature with data sets generated with the Affymetrix ATH1 array, allowing comparisons with transcriptomic signatures of a variety of cell types, including vascular and meristematic cell types from the Arabidopsis SAM isolated via FACS (Yadav et al., 2009, 2014). When these additional samples are included, the hierarchical clustering dendrogram (Fig. 5B) shows that the YFP-positive sample is more similar to the SAM cell types than to the vascular procambium (AtHB8) and phloem cell types (S17). This again suggests the meristematic character of the YFP-positive sample (Fig. 5B). One should be cautious, however, to interpret the results of this (or any) cross-platform (array/RNA-seq) comparison until validated cross-platform comparison methods are available. To the best of our knowledge, there is no clear consensus in the literature of a standard cross-platform comparison practice (Mudge et al., 2008; Bradford et al., 2010; Guida et al., 2011; Nookaew et al., 2012). Indeed, many researchers have used both platforms (array/RNA-seq) in the same experiment and compare the final results rather than find a way to directly compare the two technologies (Marioni et al., 2008; Nookaew et al., 2012; Xu et al., 2013; Wang et al., 2014; Zhao et al., 2014). Here, we employ a Spearman rank correlation, as it is less sensitive than the Pearson correlation to strong outliers, makes no assumptions about data distribution, and does not inflate type I error rates. This approach fits well with the data in this work, as samples do not cluster based on technology platforms but rather based on the apparent cell type similarities of gene reads per kilobase of transcript per million mapped reads (RPKM) expression levels.
Transcriptomic Analysis of the SHP2 Expression Domain Complements Existing Medial Domain and CMM Data Sets
Wynn et al. (2011) previously carried out a related transcriptomic study and identified many genes that were shown via in situ hybridization to be expressed preferentially in the developing medial domain of the wild-type gynoecium. When comparing the 95 enriched DEGs from our RNA-seq experiment (Supplemental Table S2; Supplemental Fig. S3) with a set of 210 medial domain-enriched genes from Wynn et al. (2011), 23 genes were found in common (Table III). The 24% overlap of these two gene sets is significantly higher than expected by chance (hypergeometric test, P = 3.15 × 10−30; Halbritter et al., 2012). Members of the REM, HEC, and NGA gene families, as well as several auxin homeostasis-related genes, were among the set of 23 genes identified in both experiments (Table III).
Table III. Overlapping DEGs between the 95 DEGs from this study that display enrichment in SHP2-expressing cells and 210 DEGs from Wynn et al. (2011) displaying reduced expression in the seu ant double mutant relative to other genotypes.
| Annotation/Gene Symbol | Gene Identifier | RNA-seq (This Study) | Array (Log2 Scaled Expression Values from Wynn et al. [2011]) | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Log2 Fold Change | Fold Change | P | FDR | Wild Type | ant | seu | seu ant | ||
| HEC1 | AT5G67060 | 5.9 | 59.4 | 1.44E-105 | 2.44E-101 | 8.887 | 8.355 | 8.030 | 7.292 |
| Cys proteinase | AT1G03720 | 4.1 | 17.7 | 6.66E-52 | 4.54E-49 | 8.998 | 8.165 | 8.409 | 7.053 |
| Plant invertase | AT3G62820 | 3.7 | 12.9 | 4.76E-40 | 1.42E-37 | 8.614 | 8.900 | 8.857 | 7.833 |
| REM13 | AT3G46770 | 3.6 | 12.2 | 8.42E-20 | 3.36E-18 | 8.653 | 8.620 | 7.954 | 7.271 |
| ATCEL2 | AT1G02800 | 3.4 | 10.4 | 7.33E-90 | 4.16E-86 | 11.927 | 11.466 | 11.182 | 9.948 |
| LAX1 | AT5G01240 | 3.3 | 9.7 | 2.74E-59 | 2.45E-56 | 9.311 | 9.254 | 9.226 | 8.709 |
| LTP2 | AT2G38530 | 3.3 | 9.5 | 6.42E-54 | 4.97E-51 | 11.297 | 10.301 | 10.987 | 10.056 |
| AMP-dependent synthetase | AT1G21540 | 3.2 | 9.3 | 3.45E-22 | 1.91E-20 | 8.547 | 8.859 | 7.986 | 7.917 |
| AGO5 | AT2G27880 | 3.0 | 8.0 | 1.20E-71 | 1.45E-68 | 10.194 | 9.653 | 9.977 | 8.937 |
| UGT84A2 | AT3G21560 | 2.9 | 7.6 | 2.77E-73 | 4.29E-70 | 9.735 | 9.707 | 8.868 | 8.370 |
| TAA1 | AT1G70560 | 2.8 | 6.9 | 1.34E-69 | 1.43E-66 | 9.608 | 9.072 | 9.068 | 7.623 |
| ATDOF5.8 | AT5G66940 | 2.7 | 6.6 | 2.26E-39 | 6.53E-37 | 10.380 | 10.135 | 9.761 | 8.007 |
| VDD | AT5G18000 | 2.6 | 6.0 | 3.71E-31 | 5.10E-29 | 8.554 | 7.719 | 8.536 | 7.018 |
| MCT1 | AT1G37140 | 2.6 | 5.9 | 8.22E-10 | 7.74E-09 | 8.003 | 7.406 | 7.572 | 6.713 |
| Unknown | AT2G41990 | 2.5 | 5.6 | 5.70E-39 | 1.56E-36 | 9.690 | 9.448 | 9.068 | 8.450 |
| Protein kinase superfamily protein | AT1G74490 | 2.5 | 5.5 | 6.27E-37 | 1.40E-34 | 7.798 | 7.727 | 7.312 | 6.976 |
| NGA3 | AT1G01030 | 2.3 | 5.1 | 4.07E-37 | 9.23E-35 | 7.543 | 7.666 | 7.214 | 7.007 |
| NGA1 | AT2G46870 | 2.3 | 4.8 | 9.56E-39 | 2.58E-36 | 8.423 | 8.516 | 7.849 | 7.168 |
| Cystatin/monellin | AT1G03710 | 2.3 | 4.8 | 1.64E-34 | 2.98E-32 | 10.186 | 10.156 | 9.780 | 8.809 |
| YUC4 | AT5G11320 | 2.3 | 4.8 | 8.01E-21 | 3.70E-19 | 7.787 | 7.889 | 7.858 | 7.070 |
| Heavy metal transport | AT1G56210 | 2.2 | 4.7 | 7.11E-49 | 3.46E-46 | 9.229 | 8.487 | 9.092 | 8.507 |
| ANAC098 | AT5G53950 | 2.1 | 4.2 | 1.88E-22 | 1.08E-20 | 8.719 | 8.453 | 8.270 | 7.780 |
| Unknown | AT1G51670 | 2.1 | 4.1 | 6.00E-30 | 7.25E-28 | 9.507 | 9.049 | 9.027 | 8.388 |
Reyes-Olalde et al. (2013) recently performed a comprehensive literature survey of genes that function during CMM development. They reported 86 protein-coding genes corresponding to transcription factors, hormonal pathways, transcriptional coregulators, and others of widely diverse functions. Fifteen of these 86 CMM developmental regulators are found within the set of 363 YFP-positive DEGs displaying a greater than 4-fold expression difference (Fig. 6, gene names marked in red; hypergeometric test, P = 3.3 × 10−13; Halbritter et al., 2012). Additionally, there are 32 DEGs that are statistically significant (at FDR < 0.01), where the fold enrichment or depletion is less than 4-fold. As many biologically significant DEGs may display less than 4-fold expression difference, these genes also are indicated (Fig. 6, marked with triple asterisks). Thus, a total of 47 of the 86 genes reported by Reyes-Olalde et al. (2013) also are detected as differentially expressed between YFP-positive and YFP-negative samples in our analysis. The expression profiles of the 86 genes reported by Reyes-Olalde et al. (2013) within the medial domain-enriched data set from this work, as well as within data from floral meristem-enriched samples (Mantegazza et al., 2014a), are displayed in the heat map in Figure 6 (RPKM values can be found in Supplemental Table S9).
Figure 6.
Heat map representation of the expression profiles of previously identified regulators of CMM development. Expression profiles in RPKM are for the 86 genes reported by Reyes-Olalde et al. (2013) with functional roles during CMM development. Transcriptional profiles from this study (YFP POS = YFP positive, YFP NEG = YFP negative, ALL SORT = all sorted, and NO SORT = nonsorted) as well as from Mantegazza et al. (2014a) corresponding to flower stage 3 (FL. STAGE 3), floral meristem (FL. MERISTEM), and inflorescence meristem (IN. MERISTEM) are included. Genes color coded in red are those identified as DEGs between YFP-positive and YFP-negative samples (fold change > 4 and FDR < 0.001), while genes that displayed a statistically significant expression level (FDR < 0.01) between YFP-positive and YFP-negative samples (regardless of their fold change) are indicated with triple asterisks.
Transcript Isoforms in the Arabidopsis Medial Domain
One utility of transcriptome analysis through RNA-seq is the identification of novel alternative spliced transcripts, alternative transcription start sites (TSSs), and instances of isoform switching (Sims et al., 2014). To further characterize the transcriptome of the SHP2 expression domain at the isoform level, we first selected isoforms that showed a significant (α < 0.01) change in their expression between YFP+/− samples using Cufflinks/Cuffdiff. For this analysis, we did not apply a fold magnitude cutoff, thus capturing all isoforms with α < 0.01. To avoid transcripts that were affected by the cell-sorting procedure, we removed all isoforms that showed a significant (α < 0.01) expression level change between all-sorted/nonsorted samples. This resulted in 4,555 YFP+/− differentially expressed isoforms (Supplemental Table S8). Within this set of isoforms differentially expressed between the YFP+/− samples, we sought to highlight multiple-isoform genes that showed major changes in the relative frequency of individual isoforms between the YFP-positive and YFP-negative samples. To this end, we estimated the relative frequency of each isoform as a percentage of the total expression for the gene. Among the 4,555 significantly differentially expressed isoforms, only 52 isoforms from multiple-isoform genes displayed changes of 20% or more in their relative frequency. The major isoform (most highly expressed isoform) differed between YFP+/− samples for only 15 genes (Table II).
Table II. List of genes displaying isoform-switching behavior between the SHP2-positive and SHP2-negative cell populations.
Genes for which the most highly expressed isoform differed between YFP+ and YFP− samples are shown. Matches between the Cufflinks transcripts and the TAIR 10 genome are indicated with Class Code (CC): = for complete transcript match and j for potentially novel isoform (fragment; Trapnell et al., 2012). YFP NEG = YFP negative, YFP POS = YFP positive, NO SORT = nonsorted, and ALL SORT = all sorted.
| Isoform Identifier | TSS Group Identifier | CC | Nearest Reference Identifier | Isoform RPKM for YFP NEG | Isoform RPKM for YFP POS | Isoform RPKM for NO SORT | Isoform RPKM for ALL SORT | Isoform Relative RPKM for YFP NEG | Isoform Relative RPKM for YFP POS | Isoform Relative RPKM for NO SORT | Isoform Relative RPKM for ALL SORT |
|---|---|---|---|---|---|---|---|---|---|---|---|
| TCONS_00000095 | TSS74 | = | AT1G02110.1 (DUF630) | 11.54 | 37.20 | 15.31 | 19.62 | 0.28 | 0.53 | 0.34 | 0.37 |
| TCONS_00007286 | TSS5864 | = | AT1G23340.1 (DUF239) | 5.46 | 1.34 | 6.93 | 5.17 | 0.75 | 0.40 | 0.71 | 0.74 |
| TCONS_00014129 | TSS11387 | = | AT2G42890.2 (MEI2-LIKE2) | 7.90 | 2.20 | 5.42 | 5.77 | 0.51 | 0.29 | 0.56 | 0.43 |
| TCONS_00041486 | TSS33793 | = | AT5G53050.3 (α/β-hydroxylase) | 3.23 | 0.48 | 1.31 | 2.46 | 0.51 | 0.11 | 0.54 | 0.038 |
| TCONS_00002986 | TSS2424 | = | AT1G43850.1 (SEU) | 6.26 | 18.06 | 7.02 | 11.62 | 0. 30 | 0.54 | 0.26 | 0.47 |
| TCONS_00032425 | TSS26386 | = | AT4G32250.2 (protein kinase) | 2.19 | 11.19 | 3.58 | 5.11 | 0.16 | 0.48 | 0.19 | 0.27 |
| TCONS_00000744 | TSS563 | = | AT1G10570.2 (OTS2) | 14.70 | 6.40 | 8.02 | 9.45 | 0.69 | 0.48 | 0.38 | 0.69 |
| TCONS_00004152 | TSS3371 | = | AT1G61820.1 (BGLU46) | 9.49 | 0.82 | 4.71 | 3.79 | 1.00 | 0.42 | 0.74 | 0.086 |
| TCONS_00006607 | TSS5332 | = | AT1G14170.1 (KH domain containing) | 10.18 | 2.62 | 5.68 | 5.39 | 0.51 | 0.29 | 0.046 | 0.49 |
| TCONS_00014122 | TSS11382 | = | AT2G42830.2 (SHP2) | 0.63 | 4.62 | 1.20 | 0.78 | 0.51 | 0.19 | 0.33 | 0.15 |
| TCONS_00001240 | TSS954 | j | AT1G16710.2 (HAC12) | 3.50 | 5.88 | 7.11 | 5.77 | 0.46 | 0.71 | 0.77 | 0.78 |
| TCONS_00006659 | TSS5370 | = | AT1G14690.2 (MAP65-7) | 39.97 | 16.72 | 28.41 | 18.98 | 0.62 | 0.41 | 0.69 | 0.53 |
| TCONS_00039135 | TSS31808 | = | AT5G19130.1 (GPI transamidase) | 3.46 | 17.27 | 13.34 | 12.45 | 0.38 | 0.74 | 0.72 | 0.73 |
| TCONS_00033470 | TSS27205 | = | AT5G06610.1 (DUF620) | 7.57 | 1.18 | 3.31 | 4.72 | 0.53 | 0.16 | 0.33 | 0.40 |
| TCONS_00031775 | TSS25869 | = | AT4G23660.1 (PPT1) | 2.56 | 9.59 | 3.23 | 6.70 | 0.35 | 0.76 | 0.29 | 0.69 |
Remarkably, the transcriptional coregulator SEUSS (SEU; AT1G43850), previously implicated in medial domain development (Franks et al., 2002; Azhakanandam et al., 2008), showed a significant increase of isoform AT1G43850.1 in the YFP-positive samples, while its second isoform, AT1G43850.2, did not change significantly between samples. As a result, isoform 1 was the major (predominant) isoform in YFP-positive cells and isoform 2 was the major (predominant) isoform in the other samples. The functional significance, if any, of this isoform switching is currently unknown. The two SEU mRNA isoforms differ only in the length of their 5′ untranslated regions (UTRs; TAIR 10). However, this difference in the 5′ UTR raises the possibility that the SEU isoforms might be differentially regulated at a posttranscriptional level.
The SHP2 (AT2G42830) gene also was found in this list of 15 genes displaying an isoform switch (Table I). The two SHP2 isoforms differ in the splice donor site at the 5′ end of intron 4 (TAIR 10). This alternative splicing event is expected to add six nucleotides (two amino acids) to the AT2G42830.2 isoform. To our knowledge, the functional consequences of this alteration to the SHP2 protein sequence has not yet been investigated. The shorter AT2G42830.1 isoform is detected as the majority isoform in the YFP-positive samples.
The regulation of gene expression through alternative promoter usage or the use of alternative TSSs is observed frequently in multicellular organisms (Ayoubi and Van De Ven 1996). Using the same pipeline and criteria we employed to select differentially expressed isoforms in the YFP+/− samples, we identified 93 isoforms that were differentially expressed as a result of the use of alternative promoter/TSSs (Supplemental Table S8, promoter usage tab). Interestingly, one such promoter/TSS switch was found for the REVERSIBLY GLYCOSYLATED POLYPEPTIDE5 (RGP5) gene (isoform). Members of the RGP family (RGP1 and RGP2) involved in sugar metabolism are expressed in other Arabidopsis meristematic tissues, such as the root tip and the apical meristem of young seedlings (Drakakaki et al., 2006). In our work, the transcript level of RGP5 isoform 2 (AT5G16510.2) in the YFP-positive sample is 61% higher relative to the level of this isoform in the YFP-negative sample, while the level of isoform 1 (AT5G16510.1) is 75% lower (Fig. 7; Supplemental Table S8).
Figure 7.
Differential expression of RGP5 isoforms. A promoter/TSS switch was found for the RGP5 gene (AT5G16510). Isoform 2 (AT5G16510.2) increases its expression in the YFP-positive domain, while isoform 1 (AT5G16510.1) of the same gene decreases its expression in the same domain. Three asterisks indicate a statistically significant difference at FDR < 0.01; ns indicates not statistically different.
Auxin Homeostasis and the Development of the Gynoecial Medial Domain
Auxins are a class of plant hormones that regulate growth and development (Woodward and Bartel, 2005; Sauer et al., 2013). The most common plant auxin is indole-3-acetic acid. The regulation of auxin homeostasis (including synthesis, response, transport, inactivation, and degradation) plays an essential role in patterning the gynoecium and other lateral organs (Woodward and Bartel, 2005; Sehra and Franks, 2015). The role of auxin during the development of the medial and lateral domains of the gynoecium is less clearly defined; however, recent studies suggest that auxin homeostasis mechanisms are likely to be distinct in medial and lateral domains (Larsson et al., 2014; Moubayidin and Ostergaard, 2014; Sehra and Franks, 2015).
To better analyze auxin homeostatic mechanisms during medial domain development, we examined the expression of 127 genes with an annotated function in auxin homeostasis. Of these 127 genes, 80 were expressed in our data set and 60 were differentially expressed at FDR < 0.01 in the YFP+/− comparison, without applying a fold enrichment filter (Supplemental Table S10). The expression levels of TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS1 (TAA1) and YUC4, two genes encoding proteins in the auxin synthetic pathway, were strongly enriched (more than 4-fold) in the YFP-positive samples, as predicted from previously published expression patterns indicating enriched expression within the medial portions of the gynoecium (Zhao et al., 2001; Cheng et al., 2006; Stepanova et al., 2008; Tao et al., 2008; Trigueros et al., 2009; Martínez-Fernández et al., 2014). Within the PINFORMED (PIN) family of polar auxin transporters, the expression levels of PIN1, PIN3, and PIN7 were enriched significantly in the YFP-positive sample (Supplemental Table S10). This is consistent with the reported expression patterns at the protein level of these PIN transporters within the medial domain of the gynoecium (Benková et al., 2003; Blilou et al., 2005; Larsson et al., 2014; Moubayidin and Ostergaard, 2014).
Auxin induces gene expression through a family of transcription factors called AUXIN RESPONSE FACTORS (ARFs; Woodward and Bartel, 2005). At a fold change level of 1.5 and FDR < 0.01, 10 ARFs were enriched in the YFP-positive sample (ARF1, ARF2, ARF3/ETTIN, ARF4, ARF5, ARF6, ARF7, ARF8, ARF16, and ARF18), while no ARFs were identified as depleted in the YFP-positive sample (Supplemental Table S10). Our data suggest that these ARF family members may be expressed preferentially in the medial domain and play a role during the development of this meristematic tissue. Previous studies have documented gynoecial developmental defects in arf3/ettin mutants (Sessions and Zambryski, 1995) as well as in arf6 arf8 double mutants (Nagpal et al., 2005; Wu et al., 2006). Interestingly, the levels of the precursor transcripts for two TRANS-ACTING SIRNA3 (TAS3) genes (AT5G49615 and AT3G17185) were reduced significantly (FDR < 0.01) in the YFP-positive sample (Fig. 8; Supplemental Table S8). The trans-acting small interfering RNAs that are encoded by the TAS3 genes negatively regulate the levels of ARF2, ARF3, and ARF4 transcripts (Williams et al., 2005). Thus, the enrichment of ARF2, ARF3, and ARF4 transcript levels in the SHP2 expression domain may be due in part to a reduction in the level of expression of the TAS3-encoded trans-acting small interfering RNAs in the medial domain.
Figure 8.
Differential expression of TAS3 and ARF genes. Expression of the ARFs (ARF2, ARF3, ARF4) and TAS3 transcripts is shown. Expression levels of ARF2, ARF3, and ARF4 are significantly enriched in the YFP-positive sample relative to the YFP-negative sample at FDR < 0.01. Expression levels of the TAS3 genes AT5G49615 (TAS3B) and AT3G17185 (TAS3), which negatively regulate the expression of ARF2, ARF3, and ARF4 expression (Williams et al., 2005), are significantly reduced (FDR < 0.01) in the YFP-positive sample. All error bars indicate confidence intervals as reported by Cufflinks. Three asterisks indicate statistically significant differences at FDR < 0.01; ns indicates not statistically different.
SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE3 and the cis-NAT Antisense Gene AT2G33815
The SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE (SPL) genes function in the regulation of the transition from juvenile to adult growth phases and the regulation of shoot regenerative capacity (Wu and Poethig, 2006; Wang et al., 2008, 2009; Zhang et al., 2015). In our study, the expression of SPL3 (AT2G33810) was more than 4-fold lower in the YFP-positive sample relative to the YFP-negative sample. SPL3 encodes a DNA-binding protein directly regulating APETALA1 (AT1G69120), a key regulator of floral meristem identity specification (Leal Valentim et al., 2015). Interestingly, the expression of the cis-NAT antisense gene AT2G33815, complementary to portions of the SPL3 gene, also was reduced significantly approximately 4.5-fold in the YFP-positive sample (Cufflinks data in Supplemental Table S8). In both plant and animal systems, the coexpression of overlapping sense and antisense transcripts can lead to the generation of cis-NAT-derived small interfering RNAs that can regulate gene expression at transcriptional and posttranscriptional levels (Zhang et al., 2015). The expression of another regulator of SPL3 activity, miRNA157D (AT1G48742), also was reduced significantly in the YFP-positive samples. miRNA157D reduces the translation of the SPL3 transcript by acting through a miRNA156/157-responsive element in the SPL3 3′ UTR (Gandikota et al., 2007; Wang et al., 2009). These data suggest that the miRNA156/157/SPL module may act during medial domain development and may be regulated by the cis-NAT antisense gene AT2G33815. A complete list of differentially expressed natural antisense, transposable element, and other non-protein-coding transcripts identified as differentially expressed by Cufflinks, DESeq2, and edgeR is found in Supplemental Table S8.
Protoplasting-Induced Stress Genes
While the predominant focus of this work was to perform transcriptomic analysis in medial domain-enriched cells (YFP+/−), transcripts induced by the protoplasting and sorting process (all-sorted/nonsorted) also were identified (see “Materials and Methods”). To facilitate the visualization of all samples, we generated an interactive six-way Venn diagram using the Web-based tool InteractiVenn (Heberle et al., 2015). By uploading Supplemental File S1 to InteractiVenn (http://www.interactivenn.net), mousing over, and clicking on the numbers in the Venn diagram, researchers will find gene identifiers from DEGs between YFP+/− and all-sorted/nonsorted samples (three programs and two comparisons). As expected, when comparing such different types of samples (all-sorted/nonsorted and YFP+/−), few DEGs (26) overlapped across the six samples (Fig. 9). The lack of overlap of DEGs across the entire experiment indicates that the YFP+/− DEGs reported here are not a result of protoplasting stress-induced processes.
Figure 9.
Six-way Venn diagram image showing detailed overlap from all the DEG data sets. The total numbers of DEGs under each condition and for each program are indicated in parentheses. CTR = DEGs between all-sorted/nonsorted and YFPs = DEGs between YFP+/−. Cuff = Cufflinks, edg = edgeR, and Des = DESeq2. The interactive tool can be accessed online using the InteractiVenn Web tool (http://www.interactivenn.net.) and uploading Supplemental File S1.
When comparing the protoplasting-induced gene set from this work (all-sorted/nonsorted DEGs) with those induced due to FACS-sorting methodology in SAM by Yadav et al. (2009) and in roots as reported by Birnbaum et al. (2005), few DEGs were found in common (seven across all data sets; Supplemental Fig. S4), indicating that different tissues and/or different protoplasting techniques generate different sets of protoplast-induced gene expression changes. Thus, appropriate controls should be included to control for condition-specific protoplasting-induced gene expression changes.
CONCLUSION
Despite the importance of the gynoecial medial domain in ovule development, no domain-specific transcriptome has been reported previously, mainly due to the difficulty of isolating the meristematic cells from which ovules are derived. In this work, we developed a novel FACS-based system using the SHP2 expression domain using a GAL4/pUAS-based two-component system that, when combined with flower synchronization and flow cytometry, allowed for the efficient isolation of medial domain cells expressing SHP2. The quality and quantity of biological samples that can be recovered with our system enables cell type- and strand-specific RNA-seq transcriptomic analysis and opens up possibilities for small RNA, metabolomic, and proteomic analyses (Petersson et al., 2009; Breakfield et al., 2012; Petricka et al., 2012; Li et al., 2013; Moussaieff et al., 2013). This approach, coupled with high-throughput RNA-seq, has yielded a unique and novel snapshot of the gynoecial medial domain transcriptome and a set of candidate regulators of medial domain development for future functional analysis.
MATERIALS AND METHODS
Construction of pSHP2-GAL4; pUAS-3xYpet Dual-Construct Lines
The SHP2 promoter fragment was amplified from Columbia-0 wild-type genomic DNA using the primers proSHP2gwF1 (5′-CACCATCTCCAACGCATTGTTACG-3′) and proSHP2gwR1 (5′-CATTTCTATAAGCCCTAGCTGAAG-3′). This fragment contains the sequences from −2,170 to +1 relative to the SHP2 ATG and includes the 5′ UTR, the first intron, and the first Met codon of SHP2. This promoter was shown previously to mimic the endogenous SHP2 expression pattern (Colombo et al., 2010). This genomic fragment was cloned into the pENTR/D-TOPO vector (Invitrogen) to create plasmid LJ001 and then shuttled via Gateway LR reaction (Invitrogen) into the destination vector JMA859 (i.e. pEarleygate303-GAL4) to create plasmid AAS003. Transgenic Arabidopsis (Arabidopsis thaliana) lines were created by Agrobacterium tumefaciens-mediated transformation of the AAS003 plasmid into the S. No. 1880 seed stock that contained the pGWB2-pUAS-3xYpet responder construct (see below), generating the pSHP2-GAL4; pUAS-3xYpet dual-construct line (S. No. 1896), referred to as pSHP2-YFP. The pSHP2-YFP plants were crossed to the ap1 cal1 Wellmer floral induction system (Wellmer et al., 2006) as described below.
JMA859 (pEarleygate303-GAL4) is a modified pEarleygate303 (Earley et al., 2006) plasmid in which the reporter was replaced by the coding sequences from the GAL4 Saccharomyces cerevisiae transcriptional activator. To achieve this, pEarleygate303 was cut with NcoI (New England Biolabs) and SpeI (New England Biolabs). Then, fusion PCR was used to create the insert that fused the GAL4 sequences to the deleted portions of pEarlygate303. This required three PCRs: first PCR with primers pEarl303NcoIFor (5′-TGGCCAATATGGACAACTTCT-3′) and pEarl303Rev_GAL4(tale) (5′-ATGGAGGACAGGAGCTTCATACACAGATCTTCTTCAGAGA-3′); second PCR with primers GAL4F_pEarl303(tale) (5′-TCTCTGAAGAAGATCTGTGTATGAAGCTCCTGTCCTCCAT-3′) and GAL4Rev_SpeI (5′-CCGGACTAGTCTACCCACCGTACTCGTCAA-3′); and then a fusion PCR joining these two fragments using the external primers to amplify. The product of the fusion PCR was double digested with NcoI/SpeI and ligated into NcoI/SpeI-cut pEarleygate303.
JMA382 (pUAS-pGWB2) was created from pGWB2 (Nakagawa et al., 2007) by replacing the p35S sequences in pGWB2 with pUAS sequences (HindII/XbaI sites used). A Gateway LR reaction was then used to move the 3xYpet cassette from JMA710 (pENTR/D-TOPO-3xYpet) into JMA382, creating vector JMA721 (i.e. pGWB2-pUAS-3xYpet). Homozygous single insertion site transgenic lines harboring JMA721 were then generated (S. No. 1880).
Plant Material
In a wild-type inflorescence, cells expressing SHP2 represent a small percentage of the total cells. Additionally, wild-type inflorescence contains a full range of developmental series of floral stages. The Wellmer floral synchronization system (Wellmer et al., 2006) was used to maximize the amount of gynoecial tissue from floral stages 6 to 8 (Smyth et al., 1990). The Wellmer group kindly provided pAP1-AP1::GR; ap1; cal seeds (kanamycin resistant in the Landsberg erecta background; S. No. 1927). The pSHP2-GAL4; pUAS-3xYpet dual-construct plants (S. No. 1896) were crossed to pAP1-AP1::GR; ap1; cal. Lines homozygous for erecta, ap1, cal, and the transgenes were selected in F2 and F3 generations (generating S. No. 2060). Because of the mixed ecotype cross (Columbia-0 and Landsberg erecta), lines that were erecta homozygous mutant and gave a consistent YFP expression pattern and consistent inducibility of the AP1-GR activity were selected before the generation of protoplasts. Plants were grown under constant light and temperature at 22°C to minimize circadian transcriptional fluctuations. To induce flowering in the transgenic plants, 20 μm of the synthetic steroid hormone dexamethasone (Sigma) in 0.015% (v/v) Silwet was applied directly (spray application) approximately 30 d after planting (Wellmer et al., 2006). Inflorescences were collected for protoplast generation approximately 120 h after dexamethasone-induced floral synchronization. When collecting samples for protoplast preparation, five to six inflorescence heads were fixed for chloral hydrate clearing and DIC microscopy to determine the developmental stages of the flowers of the inflorescence samples. Additionally, before protoplasting, whole inflorescences were collected and frozen immediately in liquid nitrogen for analysis of the transcriptional starting state of the nonprotoplasted tissue (nonsorted samples; see “Experimental Design”).
Experimental Design
Material for RNA samples was gathered from batches of plants grown at 1-week intervals to generate biological replicates (material from each week was considered as a biological replicate). To reduce variability between bioreplicates due to environmental heterogeneity within the growth chamber, each bioreplicate was drawn from a pool that contained plants grown within three different chamber positions. Four biological replicates of each of four tissue samples (YFP-positive, YFP-negative, all-sorted, and nonsorted samples) were collected (16 samples total). Whole inflorescences were collected for nonsorted samples and immediately frozen in liquid nitrogen before RNA isolation (i.e. these samples were not subjected to protoplasting or FACS sorting). The all-sorted samples represented the total population of protoplasts that come off the FACS machine after debris and broken cells are removed based on sorting gates (Supplemental Fig. S1). The YFP-positive and YFP-negative protoplast populations are processed equivalently to the all-sorted samples except that a final FACS-sorting gate is used to divide the all-sorted protoplasts into YFP-positive and YFP-negative samples (Supplemental Fig. S1). RNA was isolated from these three protoplast populations as well as from entire nonprotoplasted inflorescences (nonsorted). The YFP-positive, YFP-negative, and all-sorted samples were prepared and collected as described below (see “Protoplast Recovery and Cell Sorting”).
Protoplast Recovery and Cell Sorting
Protoplasts from the S. No. 2060 plants were generated according to the protocol of Birnbaum et al. (2005), with adaptations for inflorescence plant material. Inflorescences (approximately 200) were hand collected with forceps and/or scissors and chopped with a Personna double-edge prep blade (American Safety Razor; 74-002) within a 15-min period. Cell wall polysaccharides were digested by immersing the chopped plant material in 10 mL of filter-sterilized solution B in a 50-mL Falcon tube. Solution B (prepared according to Birnbaum et al., 2005) is prepared from solution A (10 mm KCl, 2 mm MgCl2, 0.2 m MES, and 600 mm mannitol) to which cell wall-digesting enzymes were added (final concentrations of 1.5% (w/v) Cellulase [Yakult], 1% (w/v) Pectolyase [Yakult], and 1% (w/v) Hemicellulase [Sigma]). This mixture is then dissolved by gently swirling, covered in foil, and warmed in a water bath at 55°C for 10 min to inactivate DNases and proteases. After cooling to room temperature, CaCl2 (2 mm final) and bovine serum albumin (0.1% (w/v) final) were added, and the solution was filter sterilized through a 25-μm filter.
After 1 h of incubation at room temperature with occasional gentle agitation, 10 mL of the protoplast-rich solution B was filtered through a 70-μm filter basket to a 50-mL Falcon tube. A 10-mL rinse of solution A was applied directly to the material left in the 70-μm filter basket to rinse through any protoplasts left behind. Protoplasts were spun at 500g and 10°C for 10 min; the majority of the supernatant was removed by aspiration, being careful not to disturb the protoplast pellet, which is typically not tightly compacted. Protoplasts were resuspended in 25 mL of solution A as a rinse step to remove cell wall-digesting enzymes. Protoplasts were filtered again through a 50-μm filter mesh to a new tube, adding 8 mL of solution A to again rinse through any protoplasts stuck in the filter. Protoplasts were spun again at 500g for 10 min. The majority of the supernatant was removed, leaving 2 mL of the protoplasts in solution after the second centrifugation step. Propidium iodide (5 μg mL−1 final concentration) was added to the protoplasts (to allow separation of broken protoplasts), and a final filtering step though a 30-μm mesh filter (CellTrics; Partec) was carried out before loading onto the FACS machine.
Flow cytometry through FACS sorting (Moflo XDP; Beckman Coulter) was used to isolate the YFP-expressing cells from the total pool of cells. The FACS machine was equipped with a cooling device (set to 10°C) and fitted with a 100-μm nozzle. Protoplasts were sorted at a rate of up to 10,000 events per second at a fluid pressure of 25 p.s.i. Four sorting gates were set in an effort to collect the cleanest set of protoplasts and to eliminate debris and broken cells. A first gate based on size and granularity using side-scatter and forward-scatter parameters was used to select for intact protoplasts. Then, a second gate was used to select for single cells and remove doublets. A third gate was used to select for cells that were negative for propidium iodide signal, as broken protoplasts and debris are preferentially stained by propidium iodide, which is excited by the 488-nm laser and emits at 617 nm. The total population of protoplasts that came off the FACS sorter machine after these gates constituted the all-sorted sample. In parallel, the YFP-positive protoplasts and YFP-negative protoplasts were separated into two collection tubes using the gates described above and one additional sorting gate based on the level of emission intensity in the green channel (529-nm/28-nm filters). Preliminary experiments with protoplasts that did not express the YFP transgene were used to set this gate and determine the levels of autofluorescence of the protoplasts. Protoplasts were collected directly into 14-mL tubes containing 4 mL of Trizol (Invitrogen/Life Technologies) and occasionally agitated during the approximately 40 min of sorting required to collect the protoplasts. Trizol was the method of choice, as it maintains a high level of RNA integrity during tissue homogenization while also disrupting and breaking down cells and cell components. In order to minimize artifactual changes to transcript levels, the entire process of cell wall digestion, protoplast generation, and FACS sorting was kept under 3 h. This procedure typically yielded between 300,000 and 500,000 YFP-positive protoplasts. These YFP-positive protoplasts typically represented approximately 0.5% of the total FACS-sorting events. On average, from four sorting trials representing four biological replicates, the number of cells collected and processed for each sample was 575,000 for the YFP-positive samples, 1,000,000 for the YFP-negative samples, and 493,000 for the all-sorted samples.
RNA Extraction and qRT-PCR
Total RNA was extracted from sorted protoplasts collected in Trizol (keeping a 3:1 ratio of Trizol to sorted cells) and by modifying the Plant RNeasy Mini Kit (Qiagen) protocol as follows: collected cells in Trizol (4 mL total) were vortexed for 5 min at room temperature and 1 mL of chloroform (Sigma) was added. The solution was vortexed again for 1 min at room temperature and centrifuged at 4,000 rpm for 10 min at 4°C to separate phases; RNA from the aqueous phase (top layer) was carefully sucked up and mixed with 700 μL of Qiagen RLT buffer (Plant RNeasy Mini Kit; Qiagen) and 7 μL of B-mercaptoethanol (Sigma). A total of 500 μL of 100% ethanol was added, and solution was then transferred to a Qiagen MinElute column (Plant RNeasy Mini Kit; Qiagen) and spun in a 2-mL microfuge tube for 15 s at approximately 10,000 rpm. A total of 500 μL of Qiagen RPE buffer (Plant RNeasy Mini Kit; Qiagen) was added to the spin column and spun for 15 s at approximately 10,000. A total of 750 μL of 80% (v/v) ethanol was added to the MinElute column and spun at approximately 10,000 rpm for 15 s (twice) to ensure the removal of all guanidine salts that may inhibit downstream applications. A final 5-min spin at top speed with the cap off was performed to remove trace amounts of ethanol. Total RNA was then eluted with 10 μL of RNase-free water. A second elution was performed with another 10 μL of RNase-free water. It is worth noting that one biological replicate (fourth biological replicate) from the YFP-positive protoplasts was lost at this point, leaving only three biological replicates for this tissue sample and yielding a total of 15 samples sequenced in two lanes and used for the experiment.
Prior to high-throughput sequencing, qRT-PCR was conducted on YFP-positive and YFP-negative samples using the 2–ΔΔCT method as suggested by Schmittgen and Livak (2008) to assess the relative gene expression of the specific medial domain markers SHP2 and NGA1. Total isolated RNA was quantified using fluorometric quantitation (Qubit RNA Assay Kit; Life Technologies) for both YFP-positive and YFP-negative samples (approximately 100 ng). The SuperScript III First-Strand Synthesis System (Invitrogen/Life Technologies) was used to generate complementary DNA (cDNA; diluted 1:4 prior to qRT-PCR analysis) from total RNA. The qRT-PCR assay was performed (Thermal Cyclers from Applied Biosystems) using a SYBR Green mix (QuantiTect SYBR Green PCR Kits; Qiagen). Three biological replicates of the YFP-positive and YFP-negative samples were included, and each biological replicate was assayed in triplicate. The expression levels of the ADENINE PHOSPHORIBOSYL TRANSFERASE1 (AT1G27450) gene was used for normalization.
Bar Plots
Bar plot graphs were constructed using the R packages bear (http://sourceforge.net/projects/yjlee-r-packages/files/bear/) and plyr (https://cran.r-project.org/web/packages/plyr/index.html) to calculate means, se, and confidence intervals and ggplot2 (https://cran.r-project.org/web/packages/ggplot2/index.html) to generate the plots.
Library Preparation and mRNA Sequencing
Total RNA isolated was quantified using fluorometric quantitation (Qubit RNA Assay Kit; Life Technologies), and RNA quality was assessed using the Agilent 2100 Bioanalyzer. The RNA integrity number for the 15 samples was higher than 7.3, which is above the Illumina threshold for library construction (greater than 7). Strand-specific cDNA libraries were constructed from approximately 100 ng of total RNA using a NEB Ultra Directional Library Prep Kit for Illumina (New England Biolabs). The average size of the cDNA fragments was approximately 250 bp. The 15 bar-coded libraries were pooled, and single-end sequencing was performed in a HiSeq 2500 device (Illumina) with HiSeq SR Cluster Kit version 4 for the flow cell and HiSeq SBS version 4 for sequencing reagents. cDNA libraries were sequenced in 125 cycles plus seven cycles for multiplexed samples. Sequencing was performed in two lanes of a flow cell; all 15 libraries were sequenced twice, and the results from the two independent lanes were analyzed as technical replicates. As no lane-specific effects were observed during data analysis, the reads from each lane were pooled for the analysis of DEGs (see “Table Counts and Technical Replicates”).
Bioinformatics Analysis
All bioinformatics analyses were performed on a server cluster with 128 gigabytes of RAM, two 8-core processors per compute node, and a Ubuntu Linux-Distribution 12.04 operating system using the Simple Linux Utility Resource Management queue management system at the Bioinformatics Research Center at North Carolina State University.
Read Processing
Quality control and preprocessing of metagenomic data were performed using FastQC software (Schmieder and Edwards, 2011). Adapters and low-quality sequences were filtered out with Ea-Utils software (Lindgreen, 2012). Reads with phred-like quality score greater than 30 and read length greater than 50 bp were kept and aligned against the TAIR 10 reference genome.
Sequence Alignment to the Arabidopsis Genome
The splice junction mapper TopHat2 (version 2.0.10; Trapnell et al., 2009) was used to align filtered RNA-seq reads to the TAIR 10 genome (Ensembl annotation) downloaded from the iGenome database (http://support.illumina.com/sequencing/sequencing_software/igenome.html). Default parameters for TopHat2 were used except for strand specificity (–library-type = fr-firststrand) to match to the first strand of cDNA synthesized (antisense to the mRNA) and maximal intron length (–I 2000), as it has been shown that the large majority of known introns are smaller than the selected threshold (Li et al., 2013). To align reads solely and exclusively against TAIR 10 annotated gene models, the arguments –T (transcriptome only) and –no-novel-juncs (no novel junction) also were included. Uniquely mapped reads were extracted from the TopHat2 output binary (BAM) file using samtools (Li et al., 2009) and selecting for the NH:i:1 two-character string tag. Only uniquely mapped reads were used for downstream analysis.
Table Counts and Technical Replicates
The HTSeq: Analyzing High-Throughput Sequencing Data with Python software (Anders et al., 2015) was used with default parameters except for the stranded = reverse mode to generate tables-counts for downstream differential expression analysis for the R packages edgeR (Robinson et al., 2010) and DESeq2 (Love et al., 2014).
Using edgeR, we assessed the gene level variance versus log gene expression level among technical replicates (corresponding to two lanes in the flow cell of the Illumina HiSeq 2500). A linear-dependent Poisson distribution was observed for technical replicates (Supplemental Fig. S5), in accordance with several studies (Marioni et al., 2008; Anders and Huber, 2010; Robinson et al., 2010). Thus, differential gene expression analysis was performed using pooled technical replicates.
Gene Expression and Differential Gene Expression
Gene expression and differential gene expression analyses were carried out using the R packages edgeR (Robinson et al., 2010) and DESeq2 (Love et al., 2014) and the Linux-based Cufflinks program (version 2.2.1) -G option (Trapnell et al., 2012) for DEGs and transcripts. To facilitate future use of these data sets, all the expressed genes identified and their expression values (F/RPKM) in the YFP+/− (Supplemental Table S3) and all-sorted/nonsorted (Supplemental Table S4) samples are included.
Filters were applied to determine if a gene was detected, abiding by the suggestions of statisticians and bioinformaticians (Bourgon et al., 2010; Rau et al., 2013; Soneson and Delorenzi, 2013; Love et al., 2014; Pimentel et al., 2014; Seyednasrollah et al., 2015) as a means to enrich for true DEGs, to reduce type I error, and to improve P value adjustment. The edgeR function (Robinson et al., 2010) cpm (counts per million) was used to discard those genes whose cpm was lower than a threshold of two reads per gene in at least three biological replicates, as suggested in the edgeR vignette. For Cufflinks, a minimum RPKM of 5 was set for a gene to be expressed, following the criteria of Suzuki et al. (2015). According to Sims et al. (2014), 80% of genes can be accurately quantified with FPKM/RPKM > 10. DESeq2 performs independent filtering using the results function, as described in the DESeq2 vignette (Love et al., 2014). An FDR cutoff of less than 0.01 was used to determine DEGs in all three programs. The Gene Regulatory Information Server was used to identify transcription families in the data set (Yilmaz et al., 2011). Enriched categories of transcription factors within the set of cleaned 363 YFP+/− DEGs was assessed with the online Transcription Factor Enrichment Calculator tool (https://dgrinevich.shinyapps.io/ShinyTF).
Venn Diagrams and Heat Maps
Venn diagrams were constructed using the R package VennDiagram (Chen and Boutros, 2011) and the Web-based tool package InteractiVenn (Heberle et al., 2015). Heat maps were produced using the R package pheatmap (http://cran.r-project.org/web/packages/pheatmap/index.html). RPKM normalization by gene length and library size values was produced using the rpkm function from edgeR (Robinson et al., 2010). To calculate gene length, a TAIR 10 gene length list (coding sequence plus UTRs) was constructed by extracting length information from the TAIR 10 GFF file with homemade Perl script. Genes with multiple isoforms were collapsed, and length was calculated using the longest one. RPKM values were then calculated for clustering purposes and to have an intermediate point of comparison between Cufflinks, edgeR, and DESeq2. Samples were clustered (default clustering) with parameters provided in the software. The R package colorRamp (http://stat.ethz.ch/R-manual/R-devel/library/grDevices/html/colorRamp.html) was used to produce a gradient of color values corresponding to gene fold change values.
GSEA
GO enrichment tests were performed using the R package topGO (Alexa and Rahnenführer, 2009), with the classic algorithm (where each GO category is tested independently) and the Fisher statistical test for biological processes, molecular function, and cellular component. Enrichment analysis was performed separately for all the genes that were differentially expressed between the YFP+/− samples and the all-sorted/nonsorted samples. Network analysis of GO terms was performed using the BiNGO (Maere et al., 2005) plugin for Cytoscape (Shannon et al., 2003). GO terms for the 268 genes identified as depleted in the YFP-positive sample, as well cellular component and molecular function for the YFP+/− sample, can be found in Supplemental Table S6.
Dendrograms
The R Dist function was used to compute a distance matrix using the Spearman method (Spearman test rank correlation) and the R Cor function to compute the variance of the matrix. To perform hierarchical clustering, the hclust function in R was used. All statistical analyses were performed in R version 3.0.2. Dendrogram plots were built using the R ape package with edge.color = blue.
Confocal Microscopy
Confocal microscopy was performed using a Zeiss LSM 710 microscope model (Zeiss Axio Observer Z.1) with objective type Plan-Apochromat 20×/0.8 M27. Z-stack intervals were set to 2 μm, and the total thickness of the stack was 62 μm.
Chloral Hydrate Clearing and DIC Microscopy
Inflorescence samples were fixed in a solution of nine parts ethanol to one part acetic acid for 2 h at room temperature and then washed twice in 90% (v/v) ethanol for 30 min each wash. Inflorescences were transferred to Hoyer’s solution (70% (w/v) chloral hydrate, 4% (v/v) glycerol, and 5% (w/v) gum arabic) and allowed to clear for several hours to overnight. Samples were then dissected in Hoyer’s solution. The dissected inflorescence heads were mounted in Hoyer’s solution under coverslips and examined with DIC optics on a Zeiss Axioskop 2 to determine the floral stages.
In Situ Hybridization
For in situ hybridization analysis, Arabidopsis Columbia-0 flowers were fixed and embedded in paraffin as described previously (Franks et al., 2002; Wynn et al., 2011). Sections of plant tissue were probed with digoxigenin-labeled antisense and sense RNA probes (Roche). Probes corresponded to nucleotides +686 to +920 of REM13 relative to the transcriptional start site of the coding sequence using the following oligonucleotides to amplify the template: REM13_ISH_Fwd (5′-AAAATAGAACGCGCATACCG-3′) and REM13_ISH_Rev (5′-TCGTGAACCAAACCGTGATA-3′). Hybridization and immunological detection were performed as described previously (Franks et al., 2002; Wynn et al., 2011).
Illumina sequencing raw data (fastq) have been submitted to the GEO database (accession no. GSE74458).
Supplemental Data
The following supplemental materials are available.
Supplemental Figure S1. Sorting gates used to select YFP samples and the resorting of the YFP-positive cells to assess sample purity.
Supplemental Figure S2. qRT-PCR enrichment of the medial domain genes SHP2 and NGA1 and the gene TUB.
Supplemental Figure S3. Expression profiles for the 363 DEGs (fold change > 4 and FDR < 0.001) across all four samples (YFP positive, YFP negative, all sorted, and nonsorted).
Supplemental Figure S4. Venn diagram comparison of stress-induced genes due to the protoplast/FACS-sorting procedure.
Supplemental Figure S5. Gene level variance versus log gene expression level among technical replicates.
Supplemental Table S1. Summary of RNA-seq data.
Supplemental Table S2. DEGs from the YFP+/− and all-sorted/nonsorted comparison.
Supplemental Table S3. All the expressed protein-coding genes identified with three different programs between the YFP+/− samples.
Supplemental Table S4. All the expressed protein-coding genes identified with three different programs between the all-sorted/nonsorted samples.
Supplemental Table S5. Raw high-throughput count data for the YFP+/− and all-sorted/nonsorted comparison.
Supplemental Table S6. GSEA for the YFP+/− and all-sorted/nonsorted comparison, including biological process, molecular function, and cellular component.
Supplemental Table S7. Transcription factor families identified in the DEGs from YFP+/− and their statistical enrichment.
Supplemental Table S8. Isoform expression, regulation of gene expression by alternative promoters, and antisense transcripts identified by Cufflinks, edgeR, and DESeq2.
Supplemental Table S9. Expression profile (RPKM) of the 86 genes described by Reyes-Olalde et al. (2013) expressed in the medial domain.
Supplemental Table S10. Hormone-related-genes present in our data set.
Supplemental File S1. Data file to upload to the Web-based tool package InteractiVenn.
Supplementary Material
Acknowledgments
We thank Sarah Schuett (CVM, Flow Cytometry Facility, North Carolina State University [NCSU]) and the Genomic Sciences Laboratory Research Facility (NCSU) for library preparation and Illumina sequencing; William Thomson and Emily Wear (NSCU) for FACS-sorting assistance; Frank Wellmer and Diarmuid O’Maoileidigh (Smurfit Institute, Trinity College of Dublin) for the pAP1-AP1::GR; ap1; cal floral synchronization system; Colleen Doherty (NCSU) for help with Cytoscape/BiNGO analysis; Maria Angels De Luis Balaguer (NCSU) for assistance with cross-platform expression correlation approaches; José Alonso and Ross Sozzani (NCSU) for thoughtful comments on the article; Jigar Desai, Dmitry Grinevich, and Colleen Doherty (NCSU) for help with the transcription factor enrichment analysis; Aureliano Bombarely (Virginia Tech) for help with GO term analysis; and Eva Johannes (CMIF, Molecular Imaging Facility, NCSU) for laser scanning confocal microscope assistance.
Glossary
- CMM
carpel margin meristem
- SAM
shoot apical meristem
- qRT
quantitative real-time
- RNA-seq
RNA sequencing
- DEG
differentially expressed gene
- FDR
false discovery rate
- GSEA
Gene Set Enrichment Analysis
- GO
Gene Ontology
- GEO
Gene Expression Omnibus
- RPKM
reads per kilobase of transcript per million mapped reads
- TSS
transcription start site
- UTR
untranslated region
- TAIR
The Arabidopsis Information Resource
- DIC
differential interference contrast
- cDNA
complementary DNA
Footnotes
This work was supported by the National Science Foundation (grant no. IOS–1355019 to R.G.F. and S.H.) and the FP7–PEOPLE–2013–IRSE FRUIT LOOK program (to E.S., L.C., and R.G.F.).
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References
- Adrian J, Chang J, Ballenger CE, Bargmann BOR, Alassimone J, Davies KA, Lau OS, Matos JL, Hachez C, Lanctot A, et al. (2015) Transcriptome dynamics of the stomatal lineage: birth, amplification, and termination of a self-renewing population. Dev Cell 33: 107–118 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Aichinger E, Kornet N, Friedrich T, Laux T (2012) Plant stem cell niches. Annu Rev Plant Biol 63: 615–636 [DOI] [PubMed] [Google Scholar]
- Alexa A, Rahnenführer J (2010) topGO: Enrichment Analysis for Gene Ontology; 2010. Bioconductor package version 3.2; https://www.bioconductor.org/packages/release/bioc/html/topGO.html - Accessed Dec. 2015
- Alvarez J, Smyth DR (2002) CRABS CLAW and SPATULA genes regulate growth and pattern formation during gynoecium development in Arabidopsis thaliana. Int J Plant Sci 163: 17–41 [Google Scholar]
- Alvarez JP, Goldshmidt A, Efroni I, Bowman JL, Eshed Y (2009) The NGATHA distal organ development genes are essential for style specification in Arabidopsis. Plant Cell 21: 1373–1393 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11: R106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Anders S, Pyl PT, Huber W (2015) HTSeq: a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166–169 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. (2000) Gene Ontology: tool for the unification of biology. Nat Genet 25: 25–29 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ayoubi TA, Van De Ven WJ (1996) Regulation of gene expression by alternative promoters. FASEB J 10: 453–460 [PubMed] [Google Scholar]
- Azhakanandam S, Nole-Wilson S, Bao F, Franks RG (2008) SEUSS and AINTEGUMENTA mediate patterning and ovule initiation during gynoecium medial domain development. Plant Physiol 146: 1165–1181 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Baxter CEL, Costa MMR, Coen ES (2007) Diversification and co-option of RAD-like genes in the evolution of floral asymmetry. Plant J 52: 105–113 [DOI] [PubMed] [Google Scholar]
- Benková E, Michniewicz M, Sauer M, Teichmann T, Seifertová D, Jürgens G, Friml J (2003) Local, efflux-dependent auxin gradients as a common module for plant organ formation. Cell 115: 591–602 [DOI] [PubMed] [Google Scholar]
- Bennett MJ, Marchant A, Green HG, May ST, Ward SP, Millner PA, Walker AR, Schulz B, Feldmann KA (1996) Arabidopsis AUX1 gene: a permease-like regulator of root gravitropism. Science 273: 948–950 [DOI] [PubMed] [Google Scholar]
- Birnbaum K, Jung JW, Wang JY, Lambert GM, Hirst JA, Galbraith DW, Benfey PN (2005) Cell type-specific expression profiling in plants via cell sorting of protoplasts from fluorescent reporter lines. Nat Methods 2: 615–619 [DOI] [PubMed] [Google Scholar]
- Birnbaum K, Shasha DE, Wang JY, Jung JW, Lambert GM, Galbraith DW, Benfey PN (2003) A gene expression map of the Arabidopsis root. Science 302: 1956–1960 [DOI] [PubMed] [Google Scholar]
- Blilou I, Xu J, Wildwater M, Willemsen V, Paponov I, Friml J, Heidstra R, Aida M, Palme K, Scheres B (2005) The PIN auxin efflux facilitator network controls growth and patterning in Arabidopsis roots. Nature 433: 39–44 [DOI] [PubMed] [Google Scholar]
- Bourgon R, Gentleman R, Huber W (2010) Independent filtering increases detection power for high-throughput experiments. Proc Natl Acad Sci USA 107: 9546–9551 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bowman JL, Baum SF, Eshed Y, Putterill J, Alvarez J (1999) Molecular genetics of gynoecium development in Arabidopsis. Curr Top Dev Biol 45: 155–205 [DOI] [PubMed] [Google Scholar]
- Bowman JL, Smyth DR (1999) CRABS CLAW, a gene that regulates carpel and nectary development in Arabidopsis, encodes a novel protein with zinc finger and helix-loop-helix domains. Development 126: 2387–2396 [DOI] [PubMed] [Google Scholar]
- Bradford JR, Hey Y, Yates T, Li Y, Pepper SD, Miller CJ (2010) A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling. BMC Genomics 11: 282. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Breakfield NW, Corcoran DL, Petricka JJ, Shen J, Sae-Seaw J, Rubio-Somoza I, Weigel D, Ohler U, Benfey PN (2012) High-resolution experimental and computational profiling of tissue-specific known and novel miRNAs in Arabidopsis. Genome Res 22: 163–176 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Carter AD, Bonyadi R, Gifford ML (2013) The use of fluorescence-activated cell sorting in studying plant development and environmental responses. Int J Dev Biol 57: 545–552 [DOI] [PubMed] [Google Scholar]
- Chen H, Boutros PC (2011) VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinformatics 12: 35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cheng Y, Dai X, Zhao Y (2006) Auxin biosynthesis by the YUCCA flavin monooxygenases controls the formation of floral organs and vascular tissues in Arabidopsis. Genes Dev 20: 1790–1799 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Colombo M, Brambilla V, Marcheselli R, Caporali E, Kater MM, Colombo L (2010) A new role for the SHATTERPROOF genes during Arabidopsis gynoecium development. Dev Biol 337: 294–302 [DOI] [PubMed] [Google Scholar]
- Crawford BCW, Yanofsky MF (2008) The formation and function of the female reproductive tract in flowering plants. Curr Biol 18: R972–R978 [DOI] [PubMed] [Google Scholar]
- Crawford BCW, Yanofsky MF (2011) HALF FILLED promotes reproductive tract development and fertilization efficiency in Arabidopsis thaliana. Development 138: 2999–3009 [DOI] [PubMed] [Google Scholar]
- Drakakaki G, Zabotina O, Delgado I, Robert S, Keegstra K, Raikhel N (2006) Arabidopsis reversibly glycosylated polypeptides 1 and 2 are essential for pollen development. Plant Physiol 142: 1480–1492 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Earley KW, Haag JR, Pontes O, Opper K, Juehne T, Song K, Pikaard CS (2006) Gateway-compatible vectors for plant functional genomics and proteomics. Plant J 45: 616–629 [DOI] [PubMed] [Google Scholar]
- Favaro R, Pinyopich A, Battaglia R, Kooiker M, Borghi L, Ditta G, Yanofsky MF, Kater MM, Colombo L (2003) MADS-box protein complexes control carpel and ovule development in Arabidopsis. Plant Cell 15: 2603–2611 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Franco-Zorrilla JM, Cubas P, Jarillo JA, Fernández-Calvín B, Salinas J, Martínez-Zapater JM (2002) AtREM1, a member of a new family of B3 domain-containing genes, is preferentially expressed in reproductive meristems. Plant Physiol 128: 418–427 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Franks RG, Wang C, Levin JZ, Liu Z (2002) SEUSS, a member of a novel family of plant regulatory proteins, represses floral homeotic gene expression with LEUNIG. Development 129: 253–263 [DOI] [PubMed] [Google Scholar]
- Galbiati F, Sinha Roy D, Simonini S, Cucinotta M, Ceccato L, Cuesta C, Simaskova M, Benkova E, Kamiuchi Y, Aida M, et al. (2013) An integrative model of the control of ovule primordia formation. Plant J 76: 446–455 [DOI] [PubMed] [Google Scholar]
- Gandikota M, Birkenbihl RP, Höhmann S, Cardon GH, Saedler H, Huijser P (2007) The miRNA156/157 recognition element in the 3′ UTR of the Arabidopsis SBP box gene SPL3 prevents early flowering by translational inhibition in seedlings. Plant J 49: 683–693 [DOI] [PubMed] [Google Scholar]
- Gremski K, Ditta G, Yanofsky MF (2007) The HECATE genes regulate female reproductive tract development in Arabidopsis thaliana. Development 134: 3593–3601 [DOI] [PubMed] [Google Scholar]
- Guida A, Lindstädt C, Maguire SL, Ding C, Higgins DG, Corton NJ, Berriman M, Butler G (2011) Using RNA-seq to determine the transcriptional landscape and the hypoxic response of the pathogenic yeast Candida parapsilosis. BMC Genomics 12: 628. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Halbritter F, Vaidya HJ, Tomlinson SR (2012) GeneProf: analysis of high-throughput sequencing experiments. Nat Methods 9: 7–8 [DOI] [PubMed] [Google Scholar]
- Hay A, Kaur H, Phillips A, Hedden P, Hake S, Tsiantis M (2002) The gibberellin pathway mediates KNOTTED1-type homeobox function in plants with different body plans. Curr Biol 12: 1557–1565 [DOI] [PubMed] [Google Scholar]
- Heberle H, Meirelles GV, da Silva FR, Telles GP, Minghim R (2015) InteractiVenn: a web-based tool for the analysis of sets through Venn diagrams. BMC Bioinformatics 16: 169. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Heisler MG, Atkinson A, Bylstra YH, Walsh R, Smyth DR (2001) SPATULA, a gene that controls development of carpel margin tissues in Arabidopsis, encodes a bHLH protein. Development 128: 1089–1098 [DOI] [PubMed] [Google Scholar]
- Jasinski S, Piazza P, Craft J, Hay A, Woolley L, Rieu I, Phillips A, Hedden P, Tsiantis M (2005) KNOX action in Arabidopsis is mediated by coordinate regulation of cytokinin and gibberellin activities. Curr Biol 15: 1560–1565 [DOI] [PubMed] [Google Scholar]
- Kamiuchi Y, Yamamoto K, Furutani M, Tasaka M, Aida M (2014) The CUC1 and CUC2 genes promote carpel margin meristem formation during Arabidopsis gynoecium development. Front Plant Sci 5: 165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kuusk S, Sohlberg JJ, Long JA, Fridborg I, Sundberg E (2002) STY1 and STY2 promote the formation of apical tissues during Arabidopsis gynoecium development. Development 129: 4707–4717 [DOI] [PubMed] [Google Scholar]
- Lamesch P, Berardini TZ, Li D, Swarbreck D, Wilks C, Sasidharan R, Muller R, Dreher K, Alexander DL, Garcia-Hernandez M, et al. (2012) The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools. Nucleic Acids Res 40: D1202–D1210 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lan P, Li W, Lin WD, Santi S, Schmidt W (2013) Mapping gene activity of Arabidopsis root hairs. Genome Biol 14: R67. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Larsson E, Roberts CJ, Claes AR, Franks RG, Sundberg E (2014) Polar auxin transport is essential for medial versus lateral tissue specification and vascular-mediated valve outgrowth in Arabidopsis gynoecia. Plant Physiol 166: 1998–2012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Leal Valentim F, Mourik S, Posé D, Kim MC, Schmid M, van Ham RC, Busscher M, Sanchez-Perez GF, Molenaar J, Angenent GC, et al. (2015) A quantitative and dynamic model of the Arabidopsis flowering time gene regulatory network. PLoS ONE 10: e0116973. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25: 2078–2079 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Li S, Liberman LM, Mukherjee N, Benfey PN, Ohler U (2013) Integrated detection of natural antisense transcripts using strand-specific RNA sequencing data. Genome Res 23: 1730–1739 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Liljegren SJ, Ditta GS, Eshed Y, Savidge B, Bowman JL, Yanofsky MF (2000) SHATTERPROOF MADS-box genes control seed dispersal in Arabidopsis. Nature 404: 766–770 [DOI] [PubMed] [Google Scholar]
- Lindgreen S. (2012) AdapterRemoval: easy cleaning of next-generation sequencing reads. BMC Res Notes 5: 337. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ma H, Yanofsky MF, Meyerowitz EM (1991) AGL1-AGL6, an Arabidopsis gene family with similarity to floral homeotic and transcription factor genes. Genes Dev 5: 484–495 [DOI] [PubMed] [Google Scholar]
- Maere S, Heymans K, Kuiper M (2005) BiNGO: a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in biological networks. Bioinformatics 21: 3448–3449 [DOI] [PubMed] [Google Scholar]
- Mantegazza O, Gregis V, Chiara M, Selva C, Leo G, Horner DS, Kater MM (2014a) Gene coexpression patterns during early development of the native Arabidopsis reproductive meristem: novel candidate developmental regulators and patterns of functional redundancy. Plant J 79: 861–877 [DOI] [PubMed] [Google Scholar]
- Mantegazza O, Gregis V, Mendes MA, Morandini P, Alves-Ferreira M, Patreze CM, Nardeli SM, Kater MM, Colombo L (2014b) Analysis of the Arabidopsis REM gene family predicts functions during flower development. Ann Bot (Lond) 114: 1507–1515 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Marioni JC, Mason CE, Mane SM, Stephens M, Gilad Y (2008) RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res 18: 1509–1517 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Martínez-Fernández I, Sanchís S, Marini N, Balanzá V, Ballester P, Navarrete-Gómez M, Oliveira AC, Colombo L, Ferrándiz C (2014) The effect of NGATHA altered activity on auxin signaling pathways within the Arabidopsis gynoecium. Front Plant Sci 5: 210. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Matias-Hernandez L, Battaglia R, Galbiati F, Rubes M, Eichenberger C, Grossniklaus U, Kater MM, Colombo L (2010) VERDANDI is a direct target of the MADS domain ovule identity complex and affects embryo sac differentiation in Arabidopsis. Plant Cell 22: 1702–1715 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mizzotti C, Ezquer I, Paolo D, Rueda-Romero P, Guerra RF, Battaglia R, Rogachev I, Aharoni A, Kater MM, Caporali E, et al. (2014) SEEDSTICK is a master regulator of development and metabolism in the Arabidopsis seed coat. PLoS Genet 10: e1004856. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Moubayidin L, Ostergaard L (2014) Dynamic control of auxin distribution imposes a bilateral-to-radial symmetry switch during gynoecium development. Curr Biol 24: 2743–2748 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Moussaieff A, Rogachev I, Brodsky L, Malitsky S, Toal TW, Belcher H, Yativ M, Brady SM, Benfey PN, Aharoni A (2013) High-resolution metabolic mapping of cell types in plant roots. Proc Natl Acad Sci USA 110: E1232–E1241 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mudge J, Miller NA, Khrebtukova I, Lindquist IE, May GD, Huntley JJ, Luo S, Zhang L, van Velkinburgh JC, Farmer AD, et al. (2008) Genomic convergence analysis of schizophrenia: mRNA sequencing reveals altered synaptic vesicular transport in post-mortem cerebellum. PLoS ONE 3: e3625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Nagpal P, Ellis CM, Weber H, Ploense SE, Barkawi LS, Guilfoyle TJ, Hagen G, Alonso JM, Cohen JD, Farmer EE, et al. (2005) Auxin response factors ARF6 and ARF8 promote jasmonic acid production and flower maturation. Development 132: 4107–4118 [DOI] [PubMed] [Google Scholar]
- Nakagawa T, Kurose T, Hino T, Tanaka K, Kawamukai M, Niwa Y, Toyooka K, Matsuoka K, Jinbo T, Kimura T (2007) Development of series of Gateway binary vectors, pGWBs, for realizing efficient construction of fusion genes for plant transformation. J Biosci Bioeng 104: 34–41 [DOI] [PubMed] [Google Scholar]
- Nookaew I, Papini M, Pornputtapong N, Scalcinati G, Fagerberg L, Uhlén M, Nielsen J (2012) A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae. Nucleic Acids Res 40: 10084–10097 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ó’Maoiléidigh DS, Wellmer F (2014) A floral induction system for the study of early Arabidopsis flower development. In Riechmann JL, Wellmer F, eds, Flower Development. Springer, New York, pp 307–314 [DOI] [PubMed] [Google Scholar]
- Oram RN, Brock RD (1972) Prospects for improving plant protein yield and quality by breeding. Aust Inst Agr Sci J 38: 163–168 [Google Scholar]
- Pagnussat GC, Yu HJ, Ngo QA, Rajani S, Mayalagu S, Johnson CS, Capron A, Xie LF, Ye D, Sundaresan V (2005) Genetic and molecular identification of genes required for female gametophyte development and function in Arabidopsis. Development 132: 603–614 [DOI] [PubMed] [Google Scholar]
- Payne CT, Zhang F, Lloyd AM (2000) GL3 encodes a bHLH protein that regulates trichome development in Arabidopsis through interaction with GL1 and TTG1. Genetics 156: 1349–1362 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Petersson SV, Johansson AI, Kowalczyk M, Makoveychuk A, Wang JY, Moritz T, Grebe M, Benfey PN, Sandberg G, Ljung K (2009) An auxin gradient and maximum in the Arabidopsis root apex shown by high-resolution cell-specific analysis of IAA distribution and synthesis. Plant Cell 21: 1659–1668 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Petricka JJ, Schauer MA, Megraw M, Breakfield NW, Thompson JW, Georgiev S, Soderblom EJ, Ohler U, Moseley MA, Grossniklaus U, et al. (2012) The protein expression landscape of the Arabidopsis root. Proc Natl Acad Sci USA 109: 6811–6818 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Phillips AL, Ward DA, Uknes S, Appleford NE, Lange T, Huttly AK, Gaskin P, Graebe JE, Hedden P (1995) Isolation and expression of three gibberellin 20-oxidase cDNA clones from Arabidopsis. Plant Physiol 108: 1049–1057 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pimentel H, Parra M, Gee S, Ghanem D, An X, Li J, Mohandas N, Pachter L, Conboy JG (2014) A dynamic alternative splicing program regulates gene expression during terminal erythropoiesis. Nucleic Acids Res 42: 4031–4042 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pinyopich A, Ditta GS, Savidge B, Liljegren SJ, Baumann E, Wisman E, Yanofsky MF (2003) Assessing the redundancy of MADS-box genes during carpel and ovule development. Nature 424: 85–88 [DOI] [PubMed] [Google Scholar]
- Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND, Betel D (2013) Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. Genome Biol 14: R95. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rau A, Gallopin M, Celeux G, Jaffrézic F (2013) Data-based filtering for replicated high-throughput transcriptome sequencing experiments. Bioinformatics 29: 2146–2152 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Reyes-Olalde JI, Zuñiga-Mayo VM, Chávez Montes RA, Marsch-Martínez N, de Folter S (2013) Inside the gynoecium: at the carpel margin. Trends Plant Sci 18: 644–655 [DOI] [PubMed] [Google Scholar]
- Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26: 139–140 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Romanel EAC, Schrago CG, Couñago RM, Russo CAM, Alves-Ferreira M (2009) Evolution of the B3 DNA binding superfamily: new insights into REM family gene diversification. PLoS ONE 4: e5791. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sauer M, Robert S, Kleine-Vehn J (2013) Auxin: simply complicated. J Exp Bot 64: 2565–2577 [DOI] [PubMed] [Google Scholar]
- Savidge B, Rounsley SD, Yanofsky MF (1995) Temporal relationship between the transcription of two Arabidopsis MADS box genes and the floral organ identity genes. Plant Cell 7: 721–733 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schmieder R, Edwards R (2011) Quality control and preprocessing of metagenomic datasets. Bioinformatics 27: 863–864 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schmittgen TD, Livak KJ (2008) Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc 3: 1101–1108 [DOI] [PubMed] [Google Scholar]
- Schneitz K, Hülskamp M, Pruitt RE (1995) Wild-type ovule development in Arabidopsis thaliana: a light microscope study of cleared whole-mount tissue. Plant J 7: 731–749 [Google Scholar]
- Sehra B, Franks RG (2015) Auxin and cytokinin act during gynoecial patterning and the development of ovules from the meristematic medial domain. Wiley Interdiscip Rev Dev Biol 4: 555–571 [DOI] [PubMed] [Google Scholar]
- Sessions A. (1999) Piecing together the Arabidopsis gynoecium. Trends Plant Sci 4: 296–297 [DOI] [PubMed] [Google Scholar]
- Sessions RA, Zambryski PC (1995) Arabidopsis gynoecium structure in the wild and in ettin mutants. Development 121: 1519–1532 [DOI] [PubMed] [Google Scholar]
- Seyednasrollah F, Laiho A, Elo LL (2015) Comparison of software packages for detecting differential expression in RNA-seq studies. Brief Bioinform 16: 59–70 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Seymour GB, Østergaard L, Chapman NH, Knapp S, Martin C (2013) Fruit development and ripening. Annu Rev Plant Biol 64: 219–241 [DOI] [PubMed] [Google Scholar]
- Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13: 2498–2504 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sims D, Sudbery I, Ilott NE, Heger A, Ponting CP (2014) Sequencing depth and coverage: key considerations in genomic analyses. Nat Rev Genet 15: 121–132 [DOI] [PubMed] [Google Scholar]
- Singh MB, Bhalla PL (2007) Control of male germ-cell development in flowering plants. BioEssays 29: 1124–1132 [DOI] [PubMed] [Google Scholar]
- Skinner DJ, Gasser CS (2009) Expression-based discovery of candidate ovule development regulators through transcriptional profiling of ovule mutants. BMC Plant Biol 9: 29. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Smyth DR, Bowman JL, Meyerowitz EM (1990) Early flower development in Arabidopsis. Plant Cell 2: 755–767 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Soneson C, Delorenzi M (2013) A comparison of methods for differential expression analysis of RNA-seq data. BMC Bioinformatics 14: 91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Stepanova AN, Robertson-Hoyt J, Yun J, Benavente LM, Xie DY, Doležal K, Schlereth A, Jürgens G, Alonso JM (2008) TAA1-mediated auxin biosynthesis is essential for hormone crosstalk and plant development. Cell 133: 177–191 [DOI] [PubMed] [Google Scholar]
- Suzuki A, Matsushima K, Makinoshima H, Sugano S, Kohno T, Tsuchihara K, Suzuki Y (2015) Single-cell analysis of lung adenocarcinoma cell lines reveals diverse expression patterns of individual cells invoked by a molecular target drug treatment. Genome Biol 16: 66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Swaminathan K, Peterson K, Jack T (2008) The plant B3 superfamily. Trends Plant Sci 13: 647–655 [DOI] [PubMed] [Google Scholar]
- Tao Y, Ferrer JL, Ljung K, Pojer F, Hong F, Long JA, Li L, Moreno JE, Bowman ME, Ivans LJ, et al. (2008) Rapid synthesis of auxin via a new tryptophan-dependent pathway is required for shade avoidance in plants. Cell 133: 164–176 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25: 1105–1111 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg SL, Rinn JL, Pachter L (2012) Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 7: 562–578 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Trigueros M, Navarrete-Gómez M, Sato S, Christensen SK, Pelaz S, Weigel D, Yanofsky MF, Ferrándiz C (2009) The NGATHA genes direct style development in the Arabidopsis gynoecium. Plant Cell 21: 1394–1409 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wang C, Gong B, Bushel PR, Thierry-Mieg J, Thierry-Mieg D, Xu J, Fang H, Hong H, Shen J, Su Z, et al. (2014) The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance. Nat Biotechnol 32: 926–932 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wang JW, Czech B, Weigel D (2009) miR156-regulated SPL transcription factors define an endogenous flowering pathway in Arabidopsis thaliana. Cell 138: 738–749 [DOI] [PubMed] [Google Scholar]
- Wang JW, Schwab R, Czech B, Mica E, Weigel D (2008) Dual effects of miR156-targeted SPL genes and CYP78A5/KLUH on plastochron length and organ size in Arabidopsis thaliana. Plant Cell 20: 1231–1243 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wellmer F, Alves-Ferreira M, Dubois A, Riechmann JL, Meyerowitz EM (2006) Genome-wide analysis of gene expression during early Arabidopsis flower development. PLoS Genet 2: e117. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Williams L, Carles CC, Osmont KS, Fletcher JC (2005) A database analysis method identifies an endogenous trans-acting short-interfering RNA that targets the Arabidopsis ARF2, ARF3, and ARF4 genes. Proc Natl Acad Sci USA 102: 9703–9708 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Woodward AW, Bartel B (2005) Auxin: regulation, action, and interaction. Ann Bot (Lond) 95: 707–735 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wu G, Poethig RS (2006) Temporal regulation of shoot development in Arabidopsis thaliana by miR156 and its target SPL3. Development 133: 3539–3547 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wu MF, Tian Q, Reed JW (2006) Arabidopsis microRNA167 controls patterns of ARF6 and ARF8 expression, and regulates both female and male reproduction. Development 133: 4211–4218 [DOI] [PubMed] [Google Scholar]
- Wuest SE, Vijverberg K, Schmidt A, Weiss M, Gheyselinck J, Lohr M, Wellmer F, Rahnenführer J, von Mering C, Grossniklaus U (2010) Arabidopsis female gametophyte gene expression map reveals similarities between plant and animal gametes. Curr Biol 20: 506–512 [DOI] [PubMed] [Google Scholar]
- Wynn AN, Rueschhoff EE, Franks RG (2011) Transcriptomic characterization of a synergistic genetic interaction during carpel margin meristem development in Arabidopsis thaliana. PLoS ONE 6: e26231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Xu X, Zhang Y, Williams J, Antoniou E, McCombie WR, Wu S, Zhu W, Davidson NO, Denoya P, Li E (2013) Parallel comparison of Illumina RNA-Seq and Affymetrix microarray platforms on transcriptomic profiles generated from 5-aza-deoxy-cytidine treated HT-29 colon cancer cells and simulated datasets. BMC Bioinformatics (Suppl 9) 14: S1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Yadav RK, Girke T, Pasala S, Xie M, Reddy GV (2009) Gene expression map of the Arabidopsis shoot apical meristem stem cell niche. Proc Natl Acad Sci USA 106: 4941–4946 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Yadav RK, Tavakkoli M, Xie M, Girke T, Reddy GV (2014) A high-resolution gene expression map of the Arabidopsis shoot meristem stem cell niche. Development 141: 2735–2744 [DOI] [PubMed] [Google Scholar]
- Yilmaz A, Mejia-Guerra MK, Kurz K, Liang X, Welch L, Grotewold E (2011) AGRIS: the Arabidopsis Gene Regulatory Information Server, an update. Nucleic Acids Res 39: D1118–D1122 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zhang TQ, Lian H, Tang H, Dolezal K, Zhou CM, Yu S, Chen JH, Chen Q, Liu H, Ljung K, et al. (2015) An intrinsic microRNA timer regulates progressive decline in shoot regenerative capacity in plants. Plant Cell 27: 349–360 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zhao S, Fung-Leung WP, Bittner A, Ngo K, Liu X (2014) Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells. PLoS ONE 9: e78644. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zhao Y, Christensen SK, Fankhauser C, Cashman JR, Cohen JD, Weigel D, Chory J (2001) A role for flavin monooxygenase-like enzymes in auxin biosynthesis. Science 291: 306–309 [DOI] [PubMed] [Google Scholar]
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