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Maize lines expressing RNAi to chromatin remodeling factors are similarly hypersensitive to UV-B radiation but exhibit distinct transcriptome responses 1Centro de Estudios Fotosintéticos y Bioquímicos (CEFOBI), Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531, 2000 Rosario, Argentina 2Department of Biology, 385 Serra Mall, Stanford University, Stanford, CA, USA 94305−5020. Email: walbot/at/stanford.edu *Correspondence to: Paula Casati, Centro de Estudios Fotosintéticos y Bioquímicos (CEFOBI), Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531, 2000 Rosario, Argentina; E-mail: casati/at/cefobi.gov.ar. The publisher's final edited version of this article is available at Epigenetics. See other articles in PMC that cite the published article.Abstract RNAi knockdown lines targeting two putative chromatin factors (a methyl-CpG-binding domain protein MBD101 and a chromatin remodeling complex protein CHC101) exhibit identical phenotypic consequences after UV-B exposure including necrosis in adult leaves and seedling death. Here we report that these RNAi lines exhibit substantially different transcriptome changes assessed on a 44K Agilent oligonucleotide array platform compared to each other and to UV-B tolerant non-transgenic siblings both before and after 8 h of UV-B exposure. Adult maize leaves express ~26,000 transcript types under greenhouse growth conditions; after 8 h of UV-B exposure 267 transcripts exhibit an expression change in the B73 control line. Most of these transcript abundance changes in B73 after UV-B treatment are not found in the two RNAi knockdown lines: 119 up-regulated transcript types and 128 down-regulated types are uniquely modulated in B73. The mbd101 RNAi line shows many more line-specific transcript changes (897 up, 68 down) than either B73 or the chc101line (72 up, 103 down). By functional analysis, the largest category of genes with predicted functions affected by UV-B is the DNA/chromatin binding group. Differential activation of suites of transcription factors in the control and transgenic lines are the likely explanation for the divergent transcriptome profiles. Keywords: ultraviolet-B, Zea mays, microarrays, transcriptome, transcription factors Introduction Genetic information encoded by eukaryotic DNA is compacted into chromatin permitting the genome to fit within the nucleus (for a review, see ref. 1). The basic unit of chromatin is the nucleosome, which is formed by wrapping 147 bp of DNA around a histone octamer; the nucleosomal structure is a barrier to proteins that act by contacting DNA including most transcription factors and the general transcriptional machinery. Gene expression required to maintain a normal phenotype is regulated by altering chromatin structure in response to various stimuli. 1-3 This chromatin restructuring is accomplished by three distinct processes that collectively regulate gene expression. First covalent modification of histone amino acids primarily in the N-terminal tails is accomplished by suites of histone modifying enzymes, changing histone–DNA interaction and thus changing protein binding affinities. Second, chromatin remodeling complexes alter histone–DNA interaction, facilitating nucleosome sliding to a new position, conformational changes in histone–DNA interactions, and histone loss or nucleosome disassembly. Third, methylation of DNA cytosine residues obstructs binding of some proteins and recruits others, including transcription factors. 1-3 Sessile plants are constantly exposed to diverse environmental perturbations and to survive they must acclimate to abiotic conditions such as excessive or inadequate light, water, salt, temperature, and pathogens. Because plants capture light for photosynthesis they also experience fluctuating solar ultraviolet-B radiation (UV-B 290−320 nm), and this energetic radiation causes direct damage to DNA, proteins, lipids, and RNA. 4-6 Plant acclimation responses include repair 7,8 and avoidance. 9,10 The mechanisms plants use for sensing and responding to UV-B have not been identified, 11-13 but some components in the UVB-induced signal transduction cascade have been identified recently in Arabidopsis thaliana. The bZIP transcription factor HY5 is required in both UV-B and for growth in visible light. 14 UVR8 is a UV-B specific factor with sequence similarity to the eukaryotic guanine nucleotide exchange factor RCC1. UVR8 is located principally in the nucleus and associates with chromatin via histones. 15 In maize, chromatin remodeling has also been implicated in UV-B responses, a discovery from transcriptome profiling of lines differing in UV-B sensitivity. Because there is less air mass and greater atmospheric transparency to shorter wavelengths, plants at high altitudes generally experience higher UV-B radiation flux. 16 We previously reported that maize landraces from high altitudes have adaptations (specific alleles) that increase UV-B tolerance; 17 they constitutively express higher levels of genes predicted to encode chromatin remodeling factors than temperate zone lines and then acclimate by showing greater UV-B mediated up-regulation of these genes. 18 To test the hypothesis that chromatin remodeling capacity is essential, transgenic plants (in the temperate B73 inbred) expressing RNAi to reduce four chromatin factors were found to be acutely sensitive to UV-B at doses that do not cause visible damage to maize lacking flavonoid sunscreens. Symptoms included necrotic sun burning of adult tissue, decreased photosynthetic pigments, altered expression of some UV-B-regulated genes, and seedling lethality. 18 These RNAi-expressing lines showed no symptoms in visible light and control, non-transgenic siblings in a UV-B tolerant temperate zone line (B73) lacked symptoms in UV-B. At the chromatin level, mass spectromic analysis of post-translational histone modifications demonstrated that UV-B tolerant B73 and high altitude landraces exhibit greater acetylation of N-terminal H3 and H4 tails after irradiation19 than UV-B sensitive temperate (W23 background) and the RNAi knockdown lines. These acetylated histones are enriched in the promoters and transcribed regions of UV-B up-regulated genes. 19 Therefore, chromatin remodeling capacity is important for effective responses to UV-B and loss of capacity is associated with hypersensitivity. Two of the RNAi lines used in the previous study were knockdown for chc101 and mbd101 genes. chc101 encodes a putative component of the SWItch/Sucrose NonFermenting (SWI/SNF) and Remodel the Structure of Chromatin (RSC) chromatin remodeling complex; CHC101 is a SWIB domain-containing protein and is a likely homolog of yeast Swp73 and Rsc6 proteins and human SMARD proteins. mbd101 encodes a putative methyl-CpG-binding domain (MBD) protein. Even though the precise roles of CHC101 and MBD101 have not been demonstrated in maize, the compelling biology is that both chc101 and mbd101 knockdown plants are hypersensitive to UV-B. 18 In this work, the transcriptome consequences of reduced expression of chc101 and mbd101 were analyzed under control greenhouse conditions and after 8 h UV-B with reference to non-transgenic B73 siblings. The mbd101 and chc101 RNAi lines have very distinctive differences to B73 controls and to each other in the standard growth conditions and after supplementary radiation treatment. The largest number of differentially regulated genes in all comparisons is the DNA/chromatin binding category in both control light and after UV-B. We discuss how the alterations in steady-state normal gene expression and altered responses to UV-B in the RNAi knockdowns can be distinctive and nonetheless both result in acute hypersensitivity to UV-B radiation. Results Biological materials, microarray design and data analysis A primary goal in this work was to investigate if increased sensitivity to UV-B radiation by transgenic plants showing decreased transcript levels of two putative chromatin proteins, MBD101 and CHC101, reflects inappropriate transcriptional regulation of acclimation genes. Prior work had demonstrated that both lines express lower levels of several chromatin factors, thus a second goal was to determine to what extent the transcriptomes of these lines overlap, both before and after UV-B treatment. 18 To address these points, we initiated a genomic scale analysis by performing expression-profiling experiments using 44K Agilent arrays containing 60-mer in situ synthesized oligo probes; probe sets are provided in quadruplicate in an array of 4×44, which allowed four pairs of independent hybridizations to be done on one slide. Prior microarray profiling of maize leaf gene expression utilized platforms available at that time, each with a major limitation. Initial work with spotted ESTs20,21 provided limited coverage of the expected ~50,000 maize genes and could not distinguish hybridization among gene family members. The Affymetrix maize chip has features for detecting approximately 12,000 genes and the 25-mer probe sets work well with the maize inbred lines utilized in probe design and less well with other lines and landraces given the high allelic diversity in maize. 22 An Agilent 22K in situ synthesized 60-mer array yielded high quality data for 11K sense and 11K matched antisense probes, and extended but still limited gene coverage.23 A platform with spotted 70-mer oligonucleotide probes capable of detecting about 40,000 maize genes provided good coverage but yielded inconsistent data, 24 because of a high frequency of malformed spots. 25 A new Agilent array type printed with 44K features in four grids on one slide provides coverage for approximately 39,000 maize genes and can thus refine and extend knowledge about maize leaf gene expression. In particular this platform can reliably detect genes expressed at very low levels to a much greater extent than the Affymetrix gene chip,24 and the coverage is 75−80% of the expected gene number of maize. For all comparisons, a double loop design was used (Supplementary Fig. 1).26 In these experiments, samples were compared one to another in a daisy-chain fashion. These designs, combining loops with reference designs improved efficiency and robustness of the analysis by creating multiple links among samples; evaluations between samples not compared directly are computationally derived. 26 For all biological replicates, dye swap labeling was done, that is, for each quadruplicate, two replicates were labeled using Cy3 dye and two using Cy5 dye. In all experiments, RNAi transgenic lines knockdown to chc101 and mbd101 genes, together with their non-transgenic WT siblings were used in families segregating 1:1. For chc101 lines, there was a 7.7-fold decrease in transcript levels compared to WT plants, while for mbd101 the decrease was 6.8-fold. Four-week-old maize plants were grown in greenhouse conditions without UV-B radiation. A matched set of plants was treated for 8 h under UV-B lamps that were covered by either a polyester plastic (PE) that absorbs UV-B but transmits UV-A and white light (control, no UV-B) or under a plastic sheet (CA) that transmits all UV-B (UV-B). Spectra are provided in Supplementary Fig. 2. The UV-B intensity used is about 3-fold higher than solar UV-B. Plants looked healthy without any visible phenotype immediately after the treatments (also see ref. 18). Samples consisted of a pool of leaf pieces at the top of the canopy nearest the light source from multiple individuals, to reduce any plant to plant variability. For each treatment/genotype combination, four independent RNA samples were prepared, representing four biological replicates of the experiments. Determination of significant differential expression was undertaken with analysis of variance (ANOVA) style models. 24 First, transcript levels in the transgenic lines were compared to those in the B73 non-transgenic siblings, both under greenhouse control conditions and after 8h UV-B treatment. Second, within a genotype, control and UV-B treated samples were also compared. Transcripts showing statistically significant changes and 1.5-fold differences as described in Methods were analyzed further. Assessing transcript diversity in adult leaves Of the 44 K probes printed in the array, about 26 K showed a median probe intensity level above background. When the transcriptomes of chc101 and mbd101 RNAi transgenic plants were compared to that of B73 non-transgenic siblings, nearly all of these transcripts were expressed to a similar level in all three genotypes. However, 7.5% of the transcripts (N = 2114) showed a significant change when chc101 or mbd101 knockdown plants were compared to WT siblings, combining totals from the normal growth regime in the absence of UV-B and the 8 h UV-B treatment. These data indicate that altering the steady-state level of putative chromatin protein can dramatically alter the transcriptome. The Venn diagrams in Figure 1
Specifically in the mbd101 plants, increased transcripts include some DNA and chromatin binding proteins such us a bromodomain-containing protein (BG836061), a zinc finger protein F35 (TC301590), a putative auxin-regulated protein (TC310355), and a DNA topoisomerase III (TC291312) (Supplementary Table 1). In chc101 plants, different DNA binding proteins showed increase expression: an ETTIN-like auxin response factor (TC283518), a RAV-like B3 domain DNA binding protein-like (TC301326), a putative proliferating cell nuclear antigen (TC313452), an ethylene-insensitive-3-like protein (TC293252), and a homeodomain leucine-zipper protein Hox8 (TC298016). Many more transcripts exhibit lower expression in chc101 and mbd101 knockdown plants compared to B73 plants (underlined, 375 in chc101 and 303 in mbd101, with 51 shared transcripts; Fig. 1A Collectively these results demonstrate that even under optimal growing conditions the RNAi lines have distinctive properties from the B73 inbred and from each other. Furthermore, summing the up- and down-regulated transcript types, 1.4% of the leaf transcriptome (N=363) is altered in mbd101 and 1.7% (N=452) in the chc101 knockdown line compared to WT siblings. Therefore, these RNAi plants show substantially altered gene expression, likely reflecting the importance of the target genes in establishing chromatin configurations that are pre-requisite for expression of many genes. Differences in transcriptomes are increased by UV-B radiation It is clear that UV-B modulates significantly the transcriptome of the transgenic lines when compared to the WT transcriptome. The mbd101 line has 363 altered transcripts in the absence of UV-B, while 656 transcripts are changed after 8 h of UV-B irradiation. In chc101 452 mRNAs are differentially expressed in control conditions without UV-B and 769 when plants are exposed to UV-B (Fig. 1B Among the transcripts designated as differentially regulated in one knockdown line, a few were expressed to the same extent under control and supplementary UV-B conditions (37 for chc101 and 4 for mbd101, Supplementary Table 1). The two transgenic lines also share a small number of differentially regulated genes under control conditions (N=56, less than 10% of the total gene count Fig. 1A Within line comparisons of control to UV-B treatment conditions reinforce that distinct transcriptome responses occur in each line When the control versus UV-B treatment transcriptomes of B73 plus the chc101 and mbd101 RNAi plants were analyzed, 1391 probes showed significant differential expression in response to the UV-B treatment in at least one maize line (Supplementary Table 2). This total is equivalent to 3.5% of the genes in the probe set and 5.4% of the leaf transcriptome demonstrating that heightened UV-B is a significant environmental challenge. Of these, 267 differentially expressed genes were modified by UV-B in the WT plants (128 increased, 139 decreased). Some of these genes were previously reported to be regulated by UV-B, confirming prior results, 18,20,21 and new genes are now designated as UV-B regulated in maize. In response to UV-B the transcriptomes of the transgenic lines are even more distinctive from each other and from B73 siblings than under control conditions. For the chc101 RNAi line, there were fewer significant changes after UV-B (175 total, 72 increased and 103 decreased comparing control to UV-B transcriptomes within this line). In previous pilot studies by qRT-PCR, 18,19 decreased transcript abundance of a subset of these genes was found after UV-B treatment. In contrast, for the mbd101 RNAi line, there were 897 transcripts that were up-regulated by UV-B but only 68 transcripts were down-regulated comparing the control to UV-B treatments. Therefore, the mbd101 line has seven times more up-regulated and half as many down-regulated transcripts as the WT line. Using qRT-PCR we previously reported about 2-fold increased levels of chc101 and mbd101 transcripts in B73 plants after the same UV-B treatment.18 Surprisingly, we did not detect any significant increase in mbd101 transcripts in this microarray study. For the mbd101 probe (TC306104), the 60-mer has 96% similarity (56 of 60 identical) to mbd120 (see http://www.chromdb.org); this second maize methyl binding domain protein will also hybridize with the 60-mer probe, hence cross-hybridization may mask differential expression. There is no probe for chc101 on the arrays; there is a probe for chc102, which is 95% similar overall, however, within the 60-mer probe there are 14 mismatches sufficient to prevent cross-hybridization. Independent categorization of differential expression and functional classification To continue the analysis, UV-B regulated genes were grouped according to similarity of expression patterns by self-organizing maps (SOMs) (Fig. 2
When the putative function of the gene products of the differentially regulated transcripts was analyzed, we observed that in the 1391 UV-B regulated genes, the major group (41%) corresponded to genes with unknown function as is typical for flowering plants; for clarity, the unknown category has been removed from this and subsequent pie chart representations in Fig. 3
In B73, cell wall-related proteins constitute the second largest regulated group (12.8%, Fig. 3B For uniquely down regulated proteins in B73, chc101 or mbd101 plants, DNA/chromatin binding proteins are the second largest group once again illustrating the impact UV-B has on this category of genes (Fig. 3C Expression of chromatin associated genes in UV-B regulation Because functional classification of genes identified such a large fraction of UV-B regulated genes as DNA or chromatin interacting proteins, including transcription factors, we investigated them in more detail. For example, 12 DNA binding proteins are increased and 15 decreased by UV-B only in B73 (Fig. 2B and K
Additionally, there are several DNA binding proteins that are not induced by UV-B in WT plants but are induced by UV-B in the chc101 or mbd101 RNAi mutants. WRKY transcription factors 28 (TC300389) and 32 (TC293926) are up-regulated by UV-B only in mbd101 plants; an ERF transcriptional factor 3 (TC305954), a DNA gyrase subunit (BI992346), and ABI5 (a bZIP protein, TC301287) show increased levels by UV-B in chc101 plants (Fig. 4 Discussion We investigated the transcriptome of RNAi knockdown lines targeting two putative chromatin factors (a methyl-CpG-binding domain protein MBD101 and a chromatin remodeling complex protein CHC101) that exhibit identical phenotypic consequences of UV-B exposure. After chc101 and mbd101 plants were irradiated for 8 h with UV-B lamps, 4 week old plants showed increased downward arching of adult leaves; while after 4 daily doses of UV-B these transgenic lines and two expressing RNAi to other chromatin-associated genes showed visible leaf injury, including leaf necrosis, which progressively worsened during a one-week recovery without UV-B. 18 UV-B absorbing sunscreen pigments are a key factor in acclimation responses in WT plants, 20 the concentration of these molecules was lower in the transgenic plants compared to their non-transgenic siblings. 18 Finally, both mbd101 and chc101 RNAi transgenic lines had lower levels of transcripts for a number of other chromatin-associated proteins, suggesting that down-regulation of one putative chromatin protein caused a sweeping change in expression of this class of genes. Based on these common phenotypes, we hypothesized that the mbd101 and chc101 lines would have very similar transcriptome defects under control and UV-B illumination, compared to WT siblings. What we demonstrated by transcriptome profiling is that these two RNAi lines exhibit substantially different transcriptome changes both compared to each other and to UV-B tolerant non-transgenic siblings under normal growth conditions. Nearly 3% (N=759) of the 26K transcripts present in WT leaves under control conditions without UV-B are modulated in one or both of the RNAi lines; 93% of these differentially regulated genes are line-specific (Fig. 1A mbd101 encodes a putative methyl-CpG-binding domain (MBD) protein; many MBD proteins interact with DNA when it is methylated in cytosine bases. Methylation is a common epigenetic modification of DNA found in the genomes of most organisms. Methylation of cytosine is catalyzed by specific DNA methyltransferases, 27-29 which transfer a methyl group from the donor S-adenosyl-L-methionine to the 5 position of the pyrimidinic ring. Methylation on cytosine is maintained by DNA methyltransferases when they occur at symmetrical contexts, i.e., CpG and CpNpG (where N is any nucleotide). 29 Cytosine methylation may affect gene expression in two ways: it can impede or recruit the binding of some transcription factors to their DNA recognition sequence, 30,31 and, by means of specific 5-methylcytosine binding proteins, it can induce nucleosome repositioning or the formation of repressive chromatin. 32,33 MBD proteins have recently been studied in plants, in particular in A. thaliana (reviewed in ref. 34). In Arabidopsis, there are 13 MBD genes, while maize has 14 based on sequence similarity. Out of the 13 members of the AtMBD family, 8 were found to bind methylated CpG sites; it is not clear what the roles for the other MBDs that do not bind methylated CpG sites are. There is no evidence that the orthologs of maize MBD101 bind to methylated DNA in Arabidopsis. Therefore, the role of MBD101 in maize is not clear. It has been proposed that monocot MBD proteins in particular have acquired functions other than binding to methylated CpG sites, such as binding to unmethylated DNA, 35 or binding to RNA, 36 and/or mediating protein–protein interactions. 37,38 In comparing transcripts under control and UV-B conditions within a line, the mbd101 RNAi lines show many more line-specific transcript changes (897 up, 68 down) than either B73 or the chc101 line (72 up, 103 down, Supplementary Table 2). Previously, we reported18 that the mbd101 line expresses several transcripts more highly than WT controls after UV-B: a mismatch repair protein (AW4555671), a pre-rRNA processing protein RRP5 (AW424457), a NADPH-cytochrome P450 oxidoreductase (AW267179), and a histone acetyltransferase HAC101(AW056341). We also measured decreased levels of other transcripts when compared to WT, such as a histone acetyltransferase HD2 HDT104 (AI622604), an alcohol dehydrogenase (AW330922), a snRNP Sm protein F-like (AW330881), a histone acetyltransferase HAG101 (AW155759), and a chromatin assembly factor group C NFC102 (AW155846). 18,19 With the larger current data set, the significantly higher number of transcripts increased by UV-B in this line suggests that MBD101 has a major role in gene repression as do other MBD proteins 30,31 and that the RNAi knockdown lines lack sufficient activity to repress a large number of genes that are normally down-regulated during UV-B. We hypothesize that decreased levels of MBD101 could permit transcription factor binding to DNA recognition sequences, even if DNA is methylated, or it could relieve the formation of repressive chromatin. On the other hand, CHC101 activity is implicated as crucial for transcriptional activation of acclimation genes after UV-B exposure. It is clear from this microarray profiling study that perturbation of CHC101 in maize has profound consequences under normal growth conditions in which nearly 2% of leaf transcripts are mis-regulated. There is an even larger effect after UV-B exposure in which 3% of transcripts are mis-regulated compared to WT siblings. These impacts are primarily a failure to express genes up to normal levels or to induce transcript abundance changes during UV-B. There are 143 transcripts that are increased while many more are decreased (626) in chc101 mutants compared to the WT in the presence of UV-B. This suggests that a consequence of decreased CHC101 is a failure to trigger acclimation responses in a timely manner. chc101 encodes a putative component of the SWI/SNF chromatin remodeling complex; the SWIB domain-containing protein. SWI/SNF chromatin-remodeling complexes mediate ATP-dependent alterations of DNA–histone contacts. SWI/SNF-like complexes studied in yeast, Drosophila, and mammals constitute at least nine subunits; the evolutionarily conserved core SWI/SNF subunits are essential and sufficient to remodel chromatin in vitro. 39,40 Mutations in genes encoding SWI/SNF subunits in yeast cause defects in mating-type switching and sucrose fermentation and affect the transcription of 5% of yeast genes. 41,42 In various mammalian SWI/SNF complexes, core subunits are combined with different regulatory subunits, including histone deacetylase and retinoblastoma tumor-suppressor Rb binding proteins (RbAP48). A. thaliana has four members of SWI/SNF ATPases, while rice (Oryza sativa) has three (http://www.chromdb.org/; 43-45). Functional overlap between individual members of this family; would allow assembly of specialized SWI/SNF complexes for various chromatin-based regulatory functions. 46 Our data demonstrate that decreased expression of one family member, maize chc101, impacts expression of many UV-B regulated genes. Analysis of the 267 gene expression changes in the B73 control line after 8 h of UV-B exposure indicate that modulation of transcription factor and other chromatin/DNA binding proteins is a key response as this is the largest category of affected genes (Fig. 2 UV-B elicits at least one additional DNA-level event: epigenetic reactivation of quiescent Mu-type maize transposons; 47 this reactivation is accompanied by decreased histone methylation around the ~215 bp terminal inverted repeats at the ends of Mu elements (Casati and Walbot, unpublished). Thus, it is possible that de-repression of genes is enhanced in the presence of UV-B, whether triggered by DNA repair unaccompanied by DNA methylation or other processes. In maize about 25% of C residues are methylated under normal conditions, 48 and it is not yet known, beyond the loss of DNA methylation at the termini of Mu transposons, if this epigenetic mark is modulated during UV-B acclimation at discrete sites throughout the genome. Collectively these data greatly expand the list of UV-B responsive genes in a normal inbred line at one treatment dosage. Furthermore, we conclude that the RNAi knockdown lines are hypersensitive to UV-B for different reasons: in mbd101 plants many genes are inappropriately expressed (ectopic activation) while in chc101 plants too few normally UV-B responsive genes are properly activated. A major goal of future studies will be to determine the in vivo roles of MBD101 and CHC101 in maize. Methods Plant Material Transgenic lines were deposited by the Plant Chromatin consortium at the Maize Genetics Stock Center (http://www.aces.uiuc.edu/maize-coop/). The transgenic lines are in a hybrid, mainly B73 background, and each contains an RNAi construct directed toward a specific target gene (for more information about the transgenic lines see http://www.chromdb.org/). For chc101 plants, stock 3201−01 T-MCG3348.02 was used; for mbd101 plants, stocks 3201−11 TMCG3818.11 and 3201−12 T-MCG3818.15 were used. For more information about the vectors used for transgenic plant construction, see http://www.chromdb.org/rnai/vector_info.html; and for information on the characteristics of the transgenic plants see Casati et al. 18, 19. As non-transgenic controls, siblings with the same genetic background but which lack the transgene construct encoding BASTA® herbicide resistance and an RNAi expression cassette were used. Lines heterozygous for the transgene (RNAi//-) were crossed by normal siblings to generate progeny families segregating 1:1 for the transgene; amalgamations from the different segregating families were used in some analyses. Segregation of the transgene was followed by BASTA® herbicide resistance test, presence of the transgene by PCR, and transcript levels by qRT-PCR. Radiation Treatments and Measurements For all experiments, plants were germinated under supplemental visible lighting to 20% of summer noon radiation without UV-B in greenhouse conditions. After that, plants were illuminated with UV-B lamps using fixtures mounted 30 cm above the plants (Phillips, F40UVB 40 W and TL 20 W/12) for 8 h; leaf samples were collected immediately after the radiation treatment. The bulbs were covered with CA filters to exclude wavelengths lower than 280 nm. As a control, plants were exposed for the same period of time under the same lamps covered with PE that absorbs all wavelengths lower than 320 nm (no UV-B treatment). The output of the UV-B source was recorded using an Optronics 752 spectroradiometer (Optronics Laboratories, Orlando, Fl) equipped with a certified internal standard. RNA Isolation, Target cRNA Preparation and Array Hybridization RNA and samples were prepared as described by Casati and Walbot 20 from a pool of top leaves from control or UV-B treatments. Target cRNA was prepared and labeled with either Cy3 or Cy5 dye (PerkinElmer, Boston, MA, USA) from 3 μg of total RNA using an Agilent Low RNA Input Fluorescent Linear Amplification Kit. Array hybridizations were carried out according to the manufacturer's instructions. For the experiments, Agilent Technologies microarrays were used, they contained 43,451 maize 60-mer probes synthesized in 4 subarrays per slide (4×44 version), control probes were detected with spike-in controls varying in concentration to permit validation of quantitative levels of gene expression in this design. Specifically, each array was hybridized with two samples, each of 0.825 μg labeled target cRNA, for 17 hours at 60°C. The samples were hybridized in a double loop design arrangement, as described by Kerr and Churchill (Supplementary Fig. 1). 25 Data were acquired with an Agilent G2565BA scanner. Hybridizations for all 12 comparisons were highly correlated as assessed from correlations between median signal intensities (r2 = 0.97 for both dyes; data not shown) and between log2 ratios of the signals (r2 = 0.94; data not shown). Oligonucleotide sequences, gene identities and both raw and normalized hybridization intensities for each probe can be downloaded from our array data deposited in the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo/) with accession number GSE 10400. Microarray Data Analysis The reliability and reproducibility of analyses was ensured by the use of quadruplicates in each experiment, the normalization of all 12 arrays to the median probe intensity level with background subtracted, and the use of well accepted and freely available software packages. The slide images were processed with Feature Extraction v. 9.5 (Agilent), including normalization of the data. After filtering out the few saturated spots flagged by Feature Extraction, and for each slide, we first calculated thresholds for background hybridizations with the internal negative controls, as described previously. 24 All statistical analyses were performed using either the R package (http://www.r-project.org/) or Microsoft EXCEL (http://www.microsoft.com) as described in Fernandes et al. 24 After normalization each experiment was analyzed separately, using analysis of variance (ANOVA) style models, and the differentially expressed transcripts were selected based on an unadjusted P value of 0.05 and a log ratio cutoff of 0.58 and −0.58 (a 1.5-fold expression ratio). The final list comprised probes that were listed as significantly different in at least three comparisons out of the total four comparisons. This list was annotated against transcript assemblies or ESTs from the TIGR wheat transcript assembly database (http://www.plantta.tigr.org/), using BLAST and filtering on a stringent e-value cutoff of 1e-05. For visualization, clustering of log 2 values of the expression ratios was performed using the “Cluster” program (Eisen Software, Lawrence Berkeley National Lab and the University of California at Berkeley, available from http://www.rana.lbl.gov/EisenSoftware.htm). To interpret the data, genes were grouped according to similarity of expression profiles with self-organizing maps or SOMs. Quantitative RT-PCR Primers were designed using the Primer3 software (Rozen and Skaletsky, 2000) and are listed in Table 2. Five μg of total RNA from each genotype/treatment combination was used for cDNA synthesis using Superscript III reverse transcriptase (Invitrogen, Carlsbad, CA). Quantitative, real-time PCR (qRT-PCR) was carried out in a DNA Engine OPTICON2 (MJ Research a division of Bio-Rad, Hercules, CA) as described in Casati and Walbot. 21 Three replicates were performed for each sample plus template-free samples and other negative controls (reaction without reverse transcriptase). To normalize the data to the non-transgenic controls, primers for a thioredoxin-like transcript were used. To confirm the size of the PCR products, and to check that they corresponded to a unique and expected PCR product, the final PCR products were evaluated on a 2% agarose gel in comparison to size standards; thermal denaturation profiles were obtained from the OPTICON2 at the end of the PCR reactions to check that the product had the exptected Tm.
Supp Figures Supplementary Figure 1. Schematic microarray hybridization design and analysis. Four replicates, each containing pooled tissues, were prepared for microarray analysis in a 6 sample loop design. In the hexagon, orange circles represent UV-B treated simples, and red circles represent control simples. Lines represent each pair of samples hybridized to the same array. Supplementary Figure 2. Irradiance spectra of the supplementary UV-B lamps. UV-B lamps covered with cellulose acetate filter (UV-B): in blue; UV-B lamps covered with polyester filter (control, no UV-B): ■ in pink. The supplementary lamps were used in a greenhouse, which has about 20% peak summer solar irradiation in the visible spectrum.Click here to view.(121K, ppt) Supp Table 1 Supplementary Table 1. Transcripts that are expressed differentially between mbd101 and chc101 RNAi transgenic plants and WT non transgenic siblings under control and/or UV-B conditions. Positive numbers indicate higher levels than WT, negative numbers indicate lower levels than WT. N.D. not significant change (p>0.05). Click here to view.(405K, xls) Supp Table 2 Supplementary Table 2. Transcripts regulated by UV-B radiation in mbd101 and chc101 RNAi transgenic plants and WT non transgenic siblings. Positive numbers indicate higher levels after UV-B treatment, negative numbers indicate lower levels after UV-B treatment. N.D. not significant change (p>0.05). The table includes the putative function of the protein encoded, the gene description and accession number, and the SOM group classification. Click here to view.(296K, xls) Acknowledgments The project was supported by the NIH (R03 TW07487) funded by the Fogarty International Center. P. C. is a member of the Research Career of the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) of Argentina. We thank Darren Morrow for help with the microarray hybridizations, John Fernandes for his assistance with the microarray data normalization and initial analysis and Lorena Falcone for helpful comments. Abbreviations
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Curr Opin Plant Biol. 2007 Dec; 10(6):645-52.
[Curr Opin Plant Biol. 2007]Curr Opin Plant Biol. 2007 Oct; 10(5):528-33.
[Curr Opin Plant Biol. 2007]Annu Rev Plant Physiol Plant Mol Biol. 1996 Jun; 47():75-100.
[Annu Rev Plant Physiol Plant Mol Biol. 1996]Plant Physiol. 2004 Oct; 136(2):3319-32.
[Plant Physiol. 2004]J Exp Bot. 2003 Jul; 54(388):1665-73.
[J Exp Bot. 2003]J Exp Bot. 2002 May; 53(371):1005-15.
[J Exp Bot. 2002]Plant Physiol. 2000 Jan; 122(1):117-26.
[Plant Physiol. 2000]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant Cell. 2008 Apr; 20(4):827-42.
[Plant Cell. 2008]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant Physiol. 2003 Aug; 132(4):1739-54.
[Plant Physiol. 2003]Genome Biol. 2004; 5(3):R16.
[Genome Biol. 2004]Genome Biol. 2006; 7(3):R22.
[Genome Biol. 2006]Genet Res. 2001 Apr; 77(2):123-8.
[Genet Res. 2001]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant Physiol. 2003 Aug; 132(4):1739-54.
[Plant Physiol. 2003]Genome Biol. 2004; 5(3):R16.
[Genome Biol. 2004]Plant Cell. 2008 Apr; 20(4):827-42.
[Plant Cell. 2008]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant Physiol. 2003 Aug; 132(4):1739-54.
[Plant Physiol. 2003]Plant Cell. 2008 Apr; 20(4):827-42.
[Plant Cell. 2008]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant Physiol. 2003 Aug; 132(4):1739-54.
[Plant Physiol. 2003]Cell Mol Life Sci. 2004 Oct; 61(19-20):2571-87.
[Cell Mol Life Sci. 2004]Plant Mol Biol. 1991 Jul; 17(1):111-23.
[Plant Mol Biol. 1991]Genes Dev. 1988 Sep; 2(9):1136-43.
[Genes Dev. 1988]Cell. 1999 Nov 24; 99(5):451-4.
[Cell. 1999]Trends Biochem Sci. 2006 Feb; 31(2):89-97.
[Trends Biochem Sci. 2006]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant Cell. 2008 Apr; 20(4):827-42.
[Plant Cell. 2008]Plant Mol Biol. 1991 Jul; 17(1):111-23.
[Plant Mol Biol. 1991]Genes Dev. 1988 Sep; 2(9):1136-43.
[Genes Dev. 1988]Mol Cell. 1999 Feb; 3(2):247-53.
[Mol Cell. 1999]Trends Genet. 2000 Aug; 16(8):345-51.
[Trends Genet. 2000]Cell. 1996 Dec 27; 87(7):1249-60.
[Cell. 1996]Genes Dev. 2002 Apr 1; 16(7):806-19.
[Genes Dev. 2002]Nucleic Acids Res. 2006; 34(10):2887-905.
[Nucleic Acids Res. 2006]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Nature. 1999 Feb 4; 397(6718):398-9.
[Nature. 1999]Plant J. 2006 May; 46(4):613-27.
[Plant J. 2006]Plant Cell. 2008 Apr; 20(4):827-42.
[Plant Cell. 2008]Plant Physiol. 2003 Aug; 132(4):1739-54.
[Plant Physiol. 2003]Genome Biol. 2004; 5(3):R16.
[Genome Biol. 2004]