Abstract
Transcriptional regulatory mechanisms governing plant cell wall biosynthesis are incomplete. Expression programs that activate wall biosynthesis are well understood, but mechanisms that control the attenuation of gene expression networks remain elusive. Previous work has shown that small RNAs (sRNAs) derived from the HvCESA6 (Hordeum vulgare, Hv) antisense transcripts are naturally produced and are capable of regulating aspects of wall biosynthesis. Here, we further test the hypothesis that CESA-derived sRNAs generated from CESA antisense transcripts are involved in the regulation of cellulose and broader cell wall biosynthesis. Antisense transcripts were detected for some, but not all members of the CESA gene family in both barley and Brachypodium distachyon. Phylogenetic analysis indicates that antisense transcripts are detected for most primary cell wall CESA genes, suggesting a possible role in the transition from primary to secondary cell wall biosynthesis. Focusing on one antisense transcript, HvCESA1 shows dynamic expression throughout development, is correlated with corresponding sRNAs over the same period and is anticorrelated with HvCESA1 mRNA expression. To assess the broader impacts of CESA-derived sRNAs on the regulation of cell wall biosynthesis, transcript profiling was performed on barley tissues overexpressing CESA-derived sRNAs. Together the data support the hypothesis that CESA antisense transcripts function, through an RNA-induced silencing mechanism, to degrade cis transcripts, and may also trigger trans-acting silencing on related genes to alter the expression of cell wall gene networks.
Introduction
As young plant cells grow and divide, they produce thin and elastic primary cell walls (PCWs). When cell growth ceases, certain cell types will undergo cell wall thickening to form rigid secondary cell walls (SCWs). The major polysaccharide for both PCW and especially SCW is cellulose. Cellulose is made by plasma membrane resident glycosyltransferases (GTs) called cellulose synthases (CESAs). CESAs synthesize individual β-(1,4) linked glucan chains, which associate to form larger paracrystalline microfibrils. Individual CESA proteins interact to form large, rosette-shaped cellulose synthase complexes (CSCs) (Brown and Montezinos 1976; Mueller and Brown 1980; Giddings et al. 1980; Herth 1985; Kimura et al. 1999). The exact number of CESA proteins in a given CSCs is unclear, but current models describe it as a hexamer of trimers that utilize at least three unique non-redundant CESA isoforms (Taylor et al. 2000; Taylor et al. 2003; Gonneau et al. 2014; Hill et al. 2014). Additionally, PCW and SCW CSCs use different sets of CESAs. In Arabidopsis thaliana for example, AtCESAs 1, 3, and 6/2/5 are highly co-expressed and interact to form PCW CSCs (Persson et al. 2007) while AtCESAs 4, 7, and 8, are highly co-expressed and form SCW CSCs (Brown et al. 2005; Persson et al. 2005). All plants examined to date have co-expressed orthologs of each of these Arabidopsis CESAs indicating conservation across plant lineages (Carroll and Specht 2011). In Hordeum vulgare (barley) for example, HvCESAs 1, 2, and 6 are co-expressed and comprise CSCs for PCWs, while HvCESAs 4, 7, and 8 are for SCW CSCs (Burton et al. 2004).
PCW and SCW formation each require the concerted action of many additional GTs and cell wall modifying enzymes. Hemicellulose and pectin GTs, needed for PCW formation, tend to be co-expressed with PCW CESAs, while GTs and lignin biosynthetic enzymes tend to be co-expressed with SCW CESAs (Persson et al. 2005; Brown et al. 2005; Mutwil et al. 2009). Thus, PCWs and SCWs are each synthesized by the products of specific gene networks. Importantly, as cells begin to cease cell growth, there is a transition from PCW to SCW gene networks. The factors that drive this transition are not fully understood, but are beginning to come to light (Li et al. 2016; Watanabe et al. 2018).
As might be expected, the actions of hormones and transcription factors are major players in regulating cell wall gene networks. Auxin, abscisic acid, brassinosteroids, cytokinins, ethylene, and giberellic acid have been shown to play various roles in SCW formation (Didi et al. 2014). Transcription factor (TF) networks have been identified as activators of primary (Sakamoto et al. 2018; Saelim et al. 2019) and secondary wall biosynthetic programs both naturally and in response biotic and abiotic stresses (Kubo et al. 2005; Mitsuda et al. 2005, 2007; Zhong et al. 2006; McCarthy et al. 2009; Zhou et al. 2009; Zhong et al. 2010; Yamaguchi and Demura 2010; Wang and Dixon 2012; Ko et al. 2012, 2014; Hussey et al. 2013; Zhong and Ye 2014; Nakano et al. 2015; Zhang et al. 2018). While much is known about activation and up-regulation of cell wall synthesizing components, the corresponding mechanisms that selectively down-regulate the same gene networks are still unclear (Wang and Dixon 2012; Li et al. 2016).
Previous work has demonstrated that the transition from PCW to SCW may be regulated in part at the post-transcriptional level by CESA-derived small RNAs (sRNAs) (Held et al. 2008). Here, we test the hypothesis that cell wall gene networks can be regulated by antisense RNA-derived sRNAs centered around the expression of CESA genes. A survey of barley and Brachypodium distachyon CESA genes for additional antisense transcripts was performed. Antisense transcripts were detected for some, but not all HvCESA genes, with a concentration on PCW CESAs. A developmental time course of one of these antisense transcripts (HvCESA1) and its corresponding sRNAs over time also showed a correlated relationship. This analysis was extended to the closely related grass, Brachypodium to see if this phenomenon was unique to barley. Antisense RNAs were also detected for some but not all BdCESAs, and were generally confined to direct barley orthologs, suggesting evolutionary conservation. Lastly, cell wall gene expression profiling was performed to examine the extent to which CESA sRNAs can impact the expression of cell wall gene networks. The data show close and distant targeting of cell wall-related genes moderated by sRNA mechanisms demonstrating the potential for broader cell wall gene network regulation.
Methods
Plant growth and tissue collection
Seeds of Hordeum vulgare cv. black hulless were imbibed in aerated water for 24 hours to stimulate germination. Imbibed seeds were transferred to moist vermiculite and placed in the dark at 28°C until hypocotyls emerged, generally 3-5 days. Seedlings were then transferred to autoclaved soil (Promix BX) supplemented with Osmocote (Scotts) 14-14-14 slow release fertilizer (1.8 g/L). Seedlings were grown in a Percival E36HOX growth chamber under high intensity fluorescent lamps (450-700 μmol m-2 sec- 1) programmed for a 16-hour photoperiod (25 °C day, 20°C night).
Brachypodium distachyon seeds were imbibed in aerated water for 48 hours to stimulate germination, then transferred to damp vermiculite and incubated at 22°C in the dark for 7 days to stimulate cotyledon growth. On day 9, seedlings were transferred to autoclaved soil (Promix BX) supplemented with Osmocote (Scotts) 14-14-14 slow release fertilizer (1.8 g/L). Seedlings were grown in a Percival E36HOX growth chamber under high intensity fluorescent lamps (180-200 μmol m-2 sec-1) programmed for a 20-hour photoperiod (22 °C constant). Third-leaf tissue from ≥ 5 plants was excised, measured for length, and pooled in liquid nitrogen at 17, 19, 21, 24, and 27 days after imbibition.
Preparation of Barley and Brachypodium RNA
Pooled third-leaf samples for both survey and time course experiments were pulverized using a mortar and pestle under liquid nitrogen, and then homogenized under TRIzol® reagent (Invitrogen-Thermo/Fisher). Aliquots of each RNA sample were treated for DNA contamination using the TURBO DNA-free kit (Invitrogen-Thermo/Fisher) per the manufacturer’s instructions for rigorous treatment. Each RNA sample (0.5 μg) was separated on a 0.7-1% agarose gel and visualized with ethidium bromide dye to check for RNA degradation. Gels were imaged by a Chemidoc EQ camera (BioRad) using Quantity One software (Version 4.5.2 Build 070) to verify uniform RNA loadings. Gel images were analyzed using ImageJ (Version 1.49E). All time course measurements were normalized to the RNA loading.
Detect of antisense RNA transcripts
Gene-specific primer design for tagged SS-RT-PCR
Gene-specific primers (GSPs) for antisense transcript detection for HvCESA and BdCESA gene families were designed using the OligoAnalyzer 3.1 software, as described previously (Held et al. 2008). Primers were verified for specificity by BLAST analysis against either the NCBI barley or Brachypodium transcript library. Each primer was pairwise aligned against every member of the corresponding CESA gene family to ensure specificity. To improve PCR specificity and eliminate the potential for artefacts and off-target, sense-derived transcripts, the tag1 sequence was added to the 5’ end of each barley sense GSP for cDNA synthesis (Craggs et al. 2001), while the tag2 sequence was added to the 5’ end of each Brachypodium sense-GSP for cDNA synthesis.
Preparation of CESA Antisense cDNA for family surveys
First strand cDNAs for antisense transcripts of Hv and Bd CESAs were synthesized from 1.7 μg of DNase-treated total RNA extracted from barley (13 days post imbibition, dpi) and Brachypodium third leaves (17 dpi) using the SuperScript III First-Strand Synthesis System (Invitrogen 18080-051), using tagged sense-GSPs (Table S1). Control cDNAs were prepared as follows; Oligo-dT-primed (OdT) cDNA; No primer control (NPC) cDNA with the primer replaced with nuclease free water; No reverse transcriptase control (NRT) cDNA with the RT enzyme replaced with nuclease free water. cDNA reactions were then treated with RNase H to remove residual complementary RNA per the manufacturer’s protocol, and then diluted in a 1:9 ratio of cDNA with nuclease free water.
Amplification of antisense transcripts
For HvCESA antisense transcripts, first-strand cDNAs synthesized for each were amplified by PCR using the corresponding antisense GSP and the tag1 primer. For BdCESA antisense transcripts, first-strand cDNAs synthesized for each were amplified by PCR using the corresponding antisense GSP and the tag2 primer (Table S1). Oligo dT primed cDNA was also amplified individually with each pair of HvCESA sense and antisense GSPs, as controls for amplicon size and sense mRNA presence. To rule out non-specific amplification by the tag primers (Tag controls), oligo dT primed cDNAs were amplified with antisense GSPs and the tag1 primer (for barley samples) or tag2 primer (for Brachypodium samples). All PCR amplifications were assembled on ice in 25 μl reactions using 5 μl of 5X Green GoTaq buffer (Promega M3001), 0.5-1 μl of each primer (10 μM), 0.5 μl of dNTPs (10 μM each), 4 μl of diluted cDNA template, and 1.25 units of GoTaq polymerase. Cycling conditions for all reactions were optimized for melting temperature and extension time (Table S1). Barley PCR reactions were cycled with 2 minutes of activation at 95°C, followed by 35 cycles of 95°C for 1 min, optimized annealing temperature for 1 min, and 72°C for the optimized extension time. Final elongation was 72°C for 5 minutes. Brachypodium PCR reactions were cycled with 2 minutes of activation at 95°C, followed by 37 cycles of 95°C for 30 s, optimized annealing temperature for 30 s, and 72°C for the optimized extension time. Final elongation was 72°C for 5 minutes. At least 3 technical replicates were performed for each antisense cDNA sample. Experiments were performed with at least three biological replications.
HvCESA1 antisense time course analysis
First-strand cDNAs synthesized using the HvA1-sense-tag1 GSP, were used as templates for PCR following the same assembly as the initial detection survey. Cycling conditions for reactions using HvA1-sense GSP primer and tag1 primer included 2 min of activation at 95°C, followed by 34 cycles of 95°C for 1 min, 60°C for 1 min, and 72°C for 45 sec. Final elongation was 72°C for 5 minutes. Antisense transcript cycling conditions were optimized to terminate amplifications during the mid/late-log phase so that semi-quantitative densitometry could be performed. Three replicates of equal volumes of antisense PCR products for each time point were separated by agarose gel electrophoresis. Gels were imaged by a Chemidoc EQ camera using Quantity One software (Version 4.5.2 Build 070). Gel images were analyzed using ImageJ (Version 1.49E). Background subtraction was performed with a rolling ball radius of 50.0 pixels. Densitometry was performed, and then normalized to the densitometry results from the RNA loading gel.
Characterization of Amplicons
Equal volumes of each PCR product for each sample and control reaction were separated by agarose gel electrophoresis with ethidium bromide staining. Antisense amplification products were excised and purified with the Zymoclean Gel DNA Recovery Kit (Zymo) and cloned into the pGEM T-Easy vector kit (Promega). Clones were fully sequenced and confirmed as the targeted sequence. Inclusion of tag sequences confirmed that cDNA samples were primed by sense-tag1 (barley samples) or sense-tag2 (Brachypodium samples) GSP primers and thus could only be derived from endogenous antisense transcript templates.
Ribonuclease protection assays
Design of HvCESA1 RPA Probes
A 400-base pair region inside the sequence of the HvCESA1 antisense was amplified by RT-PCR from an oligo dT primed cDNA using 5’TAAGCGCCCAGCTTTCAA and 5’ GATACCTCCAATGACCCAGAAC oligonucleotide primers and GoTaq Green polymerase (Promega). The PCR product was cloned into the pGEM T-Easy vector (Promega). α-32P-UTP (Perkin Elmer Health Sciences) radiolabeled probes were prepared from linearized plasmid templates (SpeI or NcoI) having 5’ overhangs from either T7 or SP6 RNA polymerase using the MAXIscript Kit (Ambion) to produce the HvCESA1 antisense-targeting (466nt) and HvCESA1 sense-targeting (506nt) riboprobes respectively. A 61-nt portion of the HvCESA1 sense-targeting riboprobe and an 82-nt portion of the HvCESA1 antisense-targeting riboprobe were derived from the pGEM T-Easy vector, so empty vector probes were similarly prepared for both as negative controls.
HvCESA1 Time Course RPA Assay
Ribonuclease protection assays were performed by using the Ribonuclease Protection Assay (RPA) III kit (Ambion). Labeled riboprobes were gel-purified by 5% PAGE containing 8 M urea in 1XTBE buffer per kit instructions, and hybridized with 10–20 μg total RNA from either barley, yeast, or mouse for 16–18 h at 42 °C. Reaction mixtures were digested with RNase A/T1 (1:100) for 30 min at 37 °C, then stopped with inactivation buffer (Ambion) and protected fragments were precipitated by using 10 μg yeast RNA as a carrier. The protected fragments were separated by 12.5% PAGE containing 8 M urea in 1X TBE buffer. γ-32ATP (Perkin Elmer Health Sciences) end-labeled Decade Marker (Ambion), prepared per manufacturer’s protocol, served as the size standard. Autoradiograms of RPA gels were uniformly scanned at 600 dpi grayscale in a lossless format. The intensity of bands in the 21-24nt range were analyzed using ImageJ (Version 1.49E).
Custom cell wall microarray analysis
Viral Inoculation of Barley Plants
Plant inoculations were carried out as described previously (Holzberg et al. 2002; Held et al. 2008). Third-leaf tissues from plants visibly demonstrating photobleaching were harvested 7 to 13 days after inoculation, with maximal photobleaching at about 8 days after inoculation. Senescent tissue was trimmed from the leaf tip if present, followed by snap-freezing in liquid nitrogen. Frozen VIGS-infected tissues were pulverized using a mortar and pestle under liquid nitrogen, and then combined with TRIzol® reagent (Invitrogen, Carlsbad CA). RNA was then prepared per the TRIzol® protocol.
Construction of Custom Microarray
A custom, single-channel, Agilent (Santa Clara, CA) microarray based on the 8×16K architecture was designed to identify genes regulated in response to cellulose synthase silencing enriched in sequences involved in cell wall biosynthesis, stress response, and RNA regulation. Each slide contained 8 arrays, with approximately 16K probes per array (Wolber et al. 2006). A total of 3778 60-mer probes were selected from a list of candidate genes by the Agilent eArray service, with four technical replications of each probe per array. Empty vector (EV) treated samples and HvCESA-silencing (HvCESA-CR2) treated samples were prepared and pre-screened for silencing of HvCESA6 transcript levels via qPCR prior to microarray analysis to confirm a HvCESA family silenced state as described earlier (Held et al. 2008).
Microarray Hybridization and Data Extraction
VIGS-treated barley RNA samples were verified for quality by a Bioanalyzer 2100 instrument and hybridized to the custom 8×16K microarray per the manufacturer’s protocol (Agilent). Sixteen total samples were hybridized, one per array, with 6 BSMV-EV treated samples (negative control) and 10 BSMV-HvCESA-CR2 treated samples. Hybridized arrays were imaged with an Agilent Technologies Scanner G2505B, and signals were extracted using the Agilent Feature Extraction Tool (Version using protocol GE1_107_Sep09).
Processing of Microarray Data
Extracted microarray data was processed using the limma package from Bioconductor. Backgrounds were corrected using the normexp method with a +50 offset (Ritchie et al. 2007). Arrays were normalized between each other using the quantile method. All signals within 110% of the 95th percentile of the negative controls for 6 or more arrays were ignored. Signals from replicate probes for each array were then averaged and used to identify differentially expressed genes (adjusted p < 0.05).
Collection of BdCESA sRNA sequences
Brachypodium sRNASeq dataset OBD02 (GSM1266844) (Jeong et al. 2013) hosted at mpss.danforthcenter.org was queried (Nakano et al. 2006) using selected BdCESA nucleotide sequences. All sRNAs matching BdCESAs were BLASTed against the Brachypodium genome to ensure specificity to only BdCESA genes (E-value cutoff of 1E-10), and any sequences with alternate targets were omitted.
Results
Antisense transcripts detected for multiple barley CESAs
Tagged, strand-specific RT-PCR (SS-RT-PCR) (Craggs et al. 2001; Li et al. 2013) was used to survey the barley CESA gene family for antisense transcripts in barley third-leaves (Burton et al. 2004; Held et al. 2008). The presence of antisense RNAs were tested for HvCESA1 (MLOC_55153.1), HvCESA2 (MLOC_62778; AK366571), HvCESA4 (MLOC_66568.3), HvCESA5/7 (MLOC_43749; AK365079), HvCESA6 (MLOC_64555.1), and HvCESA8 (MLOC_68431.4). HvCESA3 (MLOC_61930.2) was omitted from this study because its expression did not cluster with either primary or secondary-wall expression (Burton et al. 2004). To ensure antisense strand specificity, a tag sequence (tag1) was added to the 5’ end of each barley gene-specific cDNA synthesis primer (Craggs et al. 2001) (Fig 1A). Antisense transcripts were detected for HvCESA1, HvCESA4, and HvCESA6, with lengths of 913, 966, and 898 nucleotides respectively (Fig 1B). DNA sequencing confirmed that the antisense transcripts were complementary to the corresponding exonic sequence with no introns or indels. Further, all three amplicons included the tag1 sequence on the correct end of the transcript, confirming that the PCR product was the direct product of an antisense-transcript. Control, sense amplicons of the same sizes (minus the length of the tag) were detected for each HvCESA, and showed much brighter bands, despite being cycled under the same conditions, indicating that their relative quantity is very high compared to corresponding antisense transcripts. No antisense transcripts were observed for the remaining HvCesAs (Fig 1B).
Expression of HvCESA1 antisense and sense transcripts anticorrelate during leaf growth
HvCesA1 antisense transcripts were monitored during barley third leaf development as previously described for HvCESA6 (Held et al. 2008) using the tagged SS-RT-PCR method. Untagged SS-RT-PCR was used to track the HvCesA1 sense transcript levels. The quantity of HvCesA1 antisense transcript was lowest on day 10, then increased to a maximum on days 15 and 16 by a factor of ∼2.5-4.5 (Fig 2B and Fig S1). Over the same time period, HvCesA1 sense signal was highest on days 10 to 13, then fell by approximately half on days 14 to 16 (Fig 2B). The accumulation of HvCESA1 antisense transcripts, coupled with the decrease of HvCESA1 sense transcripts are similar to those previously observed for HvCesA6 (Held et al. 2008).
HvCESA1 sRNAs also accumulate over development
Ribonuclease protection assays were performed to examine the presence and abundance of CESA-derived sRNAs over the same time period. Antisense HvCESA1 sRNAs (∼21-24-nucleotides) were identified via a ribonuclease protection assay (RPA) using a sense RNA riboprobe (Fig 3; Fig S2). The sense probe was designed to be internal to the known antisense region of HvCESA1 (Fig S3), so only antisense sRNAs within the HvCESA1 antisense transcript would be detected. The signal intensity of the HvCESA1 sRNAs varied over time, showing an overall increase in intensity from days 11 to 16. The overall dynamic increase of the signal was by a factor of ∼2.5 for bands in the 21-24nt sRNA range (Fig 3), a trend similar to that of the antisense transcripts and to HvCESA6 sRNAs previously observed (Held et al. 2008).
Antisense transcripts are detected for multiple Brachypodium CESAs
RNA pools from rapidly growing Brachypodium third-leaves were assayed using tagged, SS-RT-PCR for BdCESA1 (Bradi2g34240), BdCESA2 (Bradi1g04597), BdCESA4 (Bradi2g49912), BdCESA5 (Bradi1g02510), BdCESA6 (Bradi1g53207), BdCESA7 (Bradi3g28350), BdCESA8 (Bradi1g54250), and BdCESA9 (Bradi4g30540) antisense RNA transcripts (see Table S1 for primers). BdCESA3 (Bradi1g29060) and BdCESA11 (Bradi1g36740) were not examined, as they each are missing specific motifs characteristic of cellulose synthases (Handakumbura et al. 2013).
PCR amplification of the antisense cDNAs yielded antisense amplicons for BdCESA1, BdCESA4, BdCESA6, and BdCESA8, with lengths of 1059, 1078, 1107, and 1009 base-pairs respectively (Fig 4). Multiple sequence alignment of Brachypodium CESAs 1 and 8 with barley CESAs showed that antisense transcripts were detected for orthologous PCW CESAs (Fig S4). DNA sequencing of each antisense amplicon confirmed that all transcripts were complementary and exonic (no introns or indels), and that all four amplicons included the tag2 primer from cDNA synthesis again indicating that SS-RT-PCR products could only have come from endogenous antisense RNA transcripts. Control sense amplicons of the same sizes were detected for each BdCESAs and showed much brighter bands despite being cycled under the same conditions (Fig 4). Similar to barley, the relative quantity of BdCESA antisense transcripts is low compared to the sense mRNAs. No antisense transcripts for the remaining BdCESAs were detected despite the presence of the control sense amplicons.
To evaluate the presence of BdCESA sRNAs, sRNASeq databases were queried. Third leaf tissue data sets were not available, but similar tissue from 6-week old leaf and stem was considered comparable. sRNASeq data showed sRNA populations that matched each of the BdCESAs (Table S2). BdCESAs 1, 4, and 8, which produce antisense transcripts (Fig 4), had elevated sRNA counts compared to the other BdCESAs, although BdCESA6, which also produced antisense transcripts, had a lower count (Table S2). BdCESAs not associated with antisense transcripts, generally had lower counts, with the lone exception of BdCESA5. The source of BdCESA5 derived sRNAs is unclear, but they are apparently generated independent of antisense transcripts. In general, BdCESAs that expressed antisense transcripts had elevated sRNA counts compared to those where antisense transcripts were not detected.
Broad gene expression changes are observed by increasing CESA sRNAs
Previous work has shown silencing HvCESA genes by VIGS caused significant and direct reductions in CESA gene expression, and also caused indirect reductions in other cell wall biosynthetic genes (Held et al. 2008). That’s because VIGS of CESA genes stimulates the production of naturally abundant CESA sRNAs which have the potential to regulate cell wall biosynthesis in trans. The original study only examined a small subset of cell wall biosynthesis genes (Held et al. 2008), therefore, to more broadly examine the effects cause by over production of HvCESA sRNAs on cell wall gene networks, a microarray study of CESA VIGS-treated barley tissues was performed to compare the expression patterns of empty vector (EV) treated samples and HvCESA-silenced (HvCESA-CR2) samples. The results from the microarray indicate that 91 probes showed significant values (adj. p ≤ 0.05), with a distribution of annotated functions (Table 1). A total of 70 probes showed downregulated expression, while 21 probes showed upregulated expression (Table S3). One of the significantly down regulated genes was HvCESA6, a major target of the VIGS construct, confirming that silencing had indeed taken place (Held et al. 2008). Approximately 43 of the probes are specific to genes annotated for cell wall modification activity, cell wall structural proteins, glycosyltransferase activity, and glycosylhydrolase activity, suggesting the potential for broader regulatory control on cell wall gene networks via trans acting effects (Vasquez et al. 2004; Allen et al. 2005). If CESA derived sRNAs are used to help in the PCW to SCW transition, one might expect a concomitant drop in expression of genes annotated for PCW biosynthesis. While there are outliers on both sides, many down-regulated genes from this list are predicted to function in PCW biosynthesis (especially CW glycoproteins) and numerous up-regulated genes are predicted to function in SCW biosynthesis (particularly lignification) as would be expected (Table S2). Altogether, these data support the potential for broader cell wall gene network regulation via CESA-derived sRNAs.
Discussion
Plant cell walls are composed of complex networks of cellulose, various hemicelluloses, pectin, lignin and glycoproteins. The amounts and proportions of these polymers vary greatly among plant cell types and across plant development. The ability of plant cells to generate wall types tailored for specific physiological roles and the ability to change wall polysaccharide biosynthesis upon various external stimuli (e.g. biotic/abiotic stresses) requires complex, multi-level regulatory control. Gene expression networks for polymer biosynthesis are co-regulated to facilitate coordinated polymer deposition, but they also need to allow flexibility to selectively respond various stresses.
Here we provide further evidence that post-transcriptional regulation is employed to selectively attenuate the expression of cellulose synthase genes and that this regulation has the potential to broadly affect the expression of other cell wall biosynthetic genes. We also show that CESA antisense transcripts were not restricted to barley, as they also occur in Brachypodium. The detection of CESA antisense transcripts in another plant species suggests that they might be common in all higher plants. Further, antisense transcripts were detected for several orthologous PCW CESAs (Fig S4) and therefore may represent an evolutionary conserved regulatory mechanism for limiting the expression of PCW CESAs.
While much is known about activation and repression of SCW gene networks, relatively little is known regarding the repression of PCW networks (Wang and Dixon 2012; Li et al. 2016). Between barley and Brachypodium, a total of 7 antisense transcripts were detected. Five of these antisense transcripts are produced from PCW CESA genes, with the lone SCW exceptions being HvCESA4 and BdCESA4 for barley and Brachypodium, respectively (Fig S4). While the significance of HvCESA4 and BdCESA4 SCW antisense transcripts are not fully understood at present, the data support our previous hypothesis that post-transcriptional sRNA regulation is important for the transition from the PCW to SCW gene network (Held et al. 2008).
Future work directed at detecting antisense transcripts in Arabidopsis is in progress. Moving this research into a more tractable genomic model will help shed light on the mechanisms of sRNA biogenesis. Using an inducible SCW system in Arabidopsis (Zuo et al. 2000; Pesquet et al. 2010) should help further clarify the roles of CESA sRNAs and their putative involvement in mediating the transition from PCW to SCW biogenesis.
Supplemental Materials
Acknowledgements
The authors thank the Vijayanand Nadella, William H. Broach, Rachel Yoho, and Kaiyu Shen of the Ohio University Genomics Facility for DNA sequencing, RNA bioanalyzer, and custom microarray support. Mr. A. Miner is thanked for his support during manuscript revision. This investigation was conducted in a facility constructed with support from Research Facilities Improvement Program Grant Number C06 RR-014575-01 from the National Center for Research Resources, National Institutes of Health.