C. elegans have demonstrated that Unc-45 facilitates the process of myosin folding and assembly in body wall muscles. Loss or overexpression of Unc-45 in C. elegans results in defective myofibril organization. In the zebrafish Danio rerio, unc-45b, a homolog of C. elegans unc-45, is expressed in both skeletal and cardiac muscles. Earlier studies indicate that mutation or knockdown of unc-45b expression in zebrafish results in a phenotype characterized by a loss of both thick and thin filament organization in skeletal and cardiac muscle. The effects of unc-45b knockdown on other sarcomeric structures and the phenotype of Unc-45b overexpression, however, are poorly understood in vertebrates.Unc-45 is a myosin chaperone and a Hsp90 co-chaperone that plays a key role in muscle development. Genetic and biochemical studies in Danio rerio. We showed that, in addition to thick and thin filament defects, knockdown of unc-45b expression disrupted sarcomere organization in M-lines and Z-lines of skeletal muscles in zebrafish embryos. Western blotting analysis showed that myosin protein levels were significantly decreased in unc-45b knockdown embryos. Similarly, embryos overexpressing Unc-45b also exhibited severely disorganized myosin thick filaments. Disruption of thick filament organization by Unc-45b overexpression depends on the C-terminal UCS domain in Unc-45b required for interaction with myosin. Deletion of the C-terminal UCS domain abolished the disruptive activity of Unc-45b in myosin thick filament organization. In contrast, deletion of the N-terminal TPR domain required for binding with Hsp90α had no effect.Both knockdown and overexpression provide useful tools to study gene function during animal development. Using such methods, we characterized the role of Unc-45b in myofibril assembly of skeletal muscle in Collectively, these studies indicate that the expression levels of Unc-45b must be precisely regulated to ensure normal myofibril organization. Loss or overexpression of Unc-45b leads to defective myofibril organization. Sarcomeres, the repetitive intracellular units within striated muscle fibers, are the basic contractile unit in skeletal and cardiac muscles. Sarcomeres contain highly organized arrangements of proteins and are responsible for the contractile properties of muscles. Two major types of filaments- thick and thin- can be found within these complex sarcomeric structures. In addition, sarcomeres contain other major structures, including the Z-lines and M- lines, which provide structural support to the sarcomere. Myofibrillogenesis, the process of assembling myofibrillar proteins into a highly organized sarcomere, is pivotal for normal muscle function and motility. Defective sarcomere organization often leads to malfunction and diseases of skeletal and cardiac muscles, including muscular dystrophy and cardiomyopathy .Caenorhabditis elegans, to control myofibril assembly. The C. elegans Unc-45 mutants showed decreased body movement and disorganized myofilament arrays in body wall muscles [The major protein components of the thick and thin filaments are myosin and α-actin, respectively. Recent studies indicate that molecular chaperones play an important role in myosin folding and thick filament assembly -4. Heat  muscles .C. elegans and Drosophila melanogaster express one isoform of Unc-45, many vertebrates, including the zebrafish, express two isoforms [While isoforms ,13. Thesisoforms ,15. Unc-isoforms . Unc-45bisoforms ,11.C. elegans demonstrated that the protein levels of Unc-45 are highly regulated by the ubiquitin/proteasome pathway [C. elegans ortholog of CHIP (carboxyl terminus of Hsc70-interacting protein), and UFD-2, an enzyme known to have ubiquitin-conjugating E4 activity in yeast, is necessary and sufficient to multiubiquitylate Unc-45 in vitro and directs Unc-45 degradation [C. elegans results in thick filament defects, decreased myosin expression, and mild paralysis [Previous studies in  pathway . A new Eradation . Overexparalysis . The decaralysis . A similaralysis . Remarkaaralysis ,19.Structurally, Unc-45b is comprised of three major domains: an N-terminal domain containing three tetratricopeptide repeats (TPR), a central domain, and a C-terminal UCS (Unc-45/CRO1/She4p) domain . The TPRWhile previous studies have contributed significantly to our understanding of the role of Unc-45 in myosin folding, several questions regarding Unc-45 structure and function remain unanswered. Is Unc-45b required for organization of other sarcomeric structures in addition to the thick and thin filaments? Does overexpression of Unc-45b disrupt myofibril organization in vertebrate skeletal muscles? Which protein domain is involved in the disruptive effect of Unc-45b when overexpressed? Addressing these questions may lead to increased understanding of Unc-45b function in muscle physiology and development that promote new approaches combating chronic muscular disorders.This study attempts to answer these questions and better ascertain the role of Unc-45b in sarcomere assembly in zebrafish embryos. Our results indicate that knockdown of Unc-45b result in disruption of sarcomere organization and decreased levels of myosin protein expression. We further showed that overexpression of Unc-45b resulted in similar disruption of myosin thick filament organization. The disruption of thick filament organization by Unc-45b depended on the C-terminal UCS domain required for interaction with myosin. Deletion of the C-terminal UCS domain abolished the disruptive effect of Unc-45b overexpression on thick filament organization. Together, these studies indicate that the expression levels of Unc-45b must be precisely regulated to ensure normal myofibril organization during muscle development. Knockdown and overexpression of Unc-45b result in defective myofibril organization.unc-45b in zebrafish embryos resulted in defective organization of myosin thick filaments and actin thin filaments [unc-45b knockdown on myosin and actin protein accumulation, we knocked down unc-45b expression in zebrafish embryos and analyzed myosin and actin protein expression and localization. As expected, knockdown of unc-45b resulted in severe disruption of thick and thin filament organization in zebrafish embryos  and the total myosin content (MF20) in zebrafish embryos at 24 and 48 hours post-fertilization (hpf). This effect was very similar to that observed in hsp90α1 knockdown embryos  antibodies. As illustrated in Figure flag did not show the complete disruption of thick filament organization. However, these fibers appeared to be smaller when compared with their neighboring myofibers that did not express the Unc-45bflag , Unc-45b is required for myosin folding and assembly. This function requires Unc-45b interaction with Hsp90α1. Loss of Unc-45b or Hsp90α1 function results in a failure in folding of the myosin head domain, leading to significant reduction of myosin accumulation and disruption of thick filament formation. Without thick filaments, other aspects of sarcomere assembly including development of the thin filaments, Z-discs, and M-lines does not occur normally.Our data, together with previous findings in Just as insufficient Unc-45b prevents sarcomere assembly, excessive levels of Unc-45b is detrimental to myofibril organization. Overexpression of Unc-45b results in defective thick filament organization. Two alternative possibilities present themselves as explanations for the lack of thick filament organization in Unc-45b overexpressing myofibers. One hypothesis is that normal myosin folding occurs in Unc-45b overexpressing myofibers. However, individual myosin units associated with excessive Unc-45b are unable to congregate and form thick filaments. These myosin units become vulnerable to degradation by the UPS. A second hypothesis is that myosin units are able to assemble into thick filaments in the presence of high levels of Unc-45b. However, the excess Unc-45b remains associated with myosin units for an extended period of time, preventing appropriate interactions with M-line protein or anchoring proteins such as titin. These thick filaments are rendered unstable and easy targets for degradation through the UPS. In either case, the disruptive effect of Unc-45b does not require interaction with Hsp90α1, but does require interaction with myosin.In summary, we have carried out the knockdown and overexpression studies to analyze Unc-45b function in myofibril organization in zebrafish embryos. We have demonstrated that proper levels of Unc-45b expression are critical for normal thick filament assembly. Both knockdown and overexpression of Unc-45b resulted in defective myosin thick filament organization. Together, these studies demonstrate that levels of Unc-45b expression must be precisely regulated during myofibrillogenesis. Low or high levels of Unc-45b expression could result in adverse effects on myofibril assembly.The expression of Unc-45b and Hsp90α1 were individually knocked down using morpholino-modified antisense oligos that block protein translation. These morpholinos were generated as previously described ,10. BothUnc-45b ATG-MO: 5' -ATCTCCAATTTCTCCCATCGTCATT- 3'Hsp90α1 ATG-MO: 5'-CGACTTCTCAGGCATCTTGCTGTGT-3'flagsmyd1:unc-45b, flagsmyd1:unc-45bΔTPR, and flagsmyd1:unc 45bΔUCS, were generated as minigenes expressing a flag-tagged zebrafish full-length Unc-45b, a mutant Unc-45b without the TPR domain (amino acids 120-934), or a mutant Unc-45b without the C-terminal UCS domain (amino acids 1-536). The muscle-specific expression of these constructs was obtained using the muscle-specific smyd1 promoter [DNA constructs, promoter . The DNAflag smyd1:unc-45bminigene, a full-length unc-45b coding region was amplified from the 24 hpf zebrafish embryos by RT-PCR using unc-45b-5'ER1 and unc-45b-3' primers together with the advantage 2 DNA polymerase (Clontech). The PCR product was cloned into the pGEM-T Easy Vector (Promega). To place a flag-tag sequence at the C-terminus of the protein, a 3' primer was made with a flag-tag coding sequence in frame at the end of the Unc-45b C-terminus. The Unc-45b was amplified using the 5' ATG primer together with the 3'-flag primer with pfu DNA polymerase. The PCR product was cloned into the pBluescript sk vector SmaI site. The DNA insert was then released from the plasmid by BamHI digestion. The insert containing the flag-tagged Unc-45b was cloned after the zebrafish muscle-specific smyd1 promoter at the BamHI site [flagsmyd1:unc-45b.To construct the mHI site . A SV40 smyd1 promoter to generate the expression construct flagsmyd1:unc-45bΔTPR. Similarly, DNA coding sequence without the UCS domain was amplified by PCR using the unc-45b-5'ER1 and unc-45b-5'ER1 primers. The PCR product was cloned after the smyd1 promoter to generate construct flagsmyd1:unc-45bΔUCS.The mutant constructs expressing a TPR or UCS domain deleted Unc-45b were constructed using PCR. The TPR domain deletion was carried out using PCR with the unc-45b-ΔTPR5' and unc-45b-3'flag primers. The PCR product was cloned after the unc-45b-5'ER1: gaattcaatgacgatgggagaaattggunc-45b-3': gctctggctaagatcgctgctgtunc-45b-3'flag: ctacttgtcatcgtcatctttataatcgttggaaaagggctttataagtccunc-45b-ΔTPR5': Atggagaccctcaggagacttggagctunc-45b-5'ER1: ctacttgtcatcgtcgtccttgtagtcaccttcaatggcccactttctggtsmyd1:egfp and myc smyd1:hsp90a1were used as controls. Constructions of these plasmids were described as previously reported [The plasmids reported ,21.flagsmyd1:unc-45b, flagsmyd1:unc-45bΔTPR, and flagsmyd1:unc-45bΔUCS) were injected into zebrafish embryos at early cell stages of 1 or 2 cells. Embryos were then placed in a 29°C incubator for 24-72 hours in order to facilitate animal growth. Similarly, 1-2 nl of MO solution (0.5 mM) was microinjected into zebrafish embryos at 1-2 cell stages.DNA constructs were dissolved in water at a concentration of 50 ng/μl along with phenol red (0.1%). Small volumes (1-2 nl) of the individual DNA constructs , anti-myomesin , anti-α-actin , and anti-MyHC for slow muscles . F59 monoclonal antibody was originally prepared against chicken fast skeletal muscle myosin . F59 is Secondary antibodies were FITC or TRITC-conjugates (Sigma). For animals injected with FLAG-tagged constructs, anti-FLAG primary  and subsequent appropriate secondary antibodies were additionally used to detect those muscle fibers expressing the injected DNA. The embryos were photographed under an upright microscope  equipped with a confocal image analyzer .Following injection with either Unc-45b or Hsp-90α1 morpholino oligos, embryos were left to develop between 24 and 72 hours post-fertilization. Specimens were then prepared for a Western blot through homogenization in loading buffer  along with an additional 0.1 mM DTT and 1 mM PMSF (both as protease inhibitors). Protein samples were run in a 7.5% polyacrylamide gel at 30-32 mAmps for protein separation. Proteins were then transferred onto a nitrocellulose membrane in transfer buffer . Actin and γ-tubulin transfer occurred at 400 mAmp for 1 hour. Myosin transfer occurred at 400 mAmp for 1 hour, followed by an additional 1.5 hours at 450 mAmp. Transfer membranes were stained with overall myosin heavy chain specific-IgG , actin specific-IgM , and γ-tubulin specific-IgG  antibodies followed by exposure to appropriate HRP-linked secondary antibodies . Pierce ECL Western Blotting Substrate  was used for detecting HRP-conjugated bound secondary antibodies. The volume equivalent of three embryos was used at each time stage analyzed. γ-tubulin was used as a loading control.Hsp90α1: ; UPS: (ubiquitin-proteasome system); TPR: (tetratricopeptide repeat), UCS: (Unc-45/CRO1/She4p).EB carried out the functional analyses of Unc-45b in zebrafish via knockdown and over-expression approaches. EB drafted the manuscript. PZ designed and constructed the minigenes expressing the full length or mutant Unc-45b proteins used in the study. SD conceived of the study, participated in its design and coordination and helped write the manuscript. All authors read and approved the final manuscript.Figure 1 (supplement) showed that overexpression of EGFP or Hsp90a1 had not effect on thick filament organization. A. DNA constructs expressing EGFP or myc-tagged Hsp90a1 in skeletal muscles of zebrafish embryos were directed using the smyd1 promoter. Myosin thick filament organization was analyzed by F59 staining. B-D. Single staining with anti-myosin (F59) antibody (red) shows that expression of GFP (B) has no effect on myosin thick filament organization . E-G. Double staining shows the expression of myc-tagged Hsp90a1 (E) in a single fiber and its lack of effect on myosin thick filament organization . G represents the merged image of E and F. Scale bars = 20 mm.Click here for file


Effective computational tools for large-scale identification of novel regulatory RNAs are strongly desired to facilitate our exploration of gene regulation mechanisms and regulatory networks. We present a new computational program named RSSVM (RNA Sampler+Support Vector Machine), which employs Support Vector Machines (SVMs) for efficient identification of functional RNA motifs from random RNA secondary structures. RSSVM uses a set of distinctive features to represent the common RNA secondary structure and structural alignment predicted by RNA Sampler, a tool for accurate common RNA secondary structure prediction, and is trained with functional RNAs from a variety of bacterial RNA motif/gene families covering a wide range of sequence identities. When tested on a large number of known and random RNA motifs, RSSVM shows a significantly higher sensitivity than other leading RNA identification programs while maintaining the same false positive rate. RSSVM performs particularly well on sets with low sequence identities. The combination of RNA Sampler and RSSVM provides a new, fast, and efficient pipeline for large-scale discovery of regulatory RNA motifs. We applied RSSVM to multiple Shewanella genomes and identified putative regulatory RNA motifs in the 5′ untranslated regions (UTRs) in S. oneidensis, an important bacterial organism with extraordinary respiratory and metal reducing abilities and great potential for bioremediation and alternative energy generation. From 1002 sets of 5′-UTRs of orthologous operons, we identified 166 putative regulatory RNA motifs, including 17 of the 19 known RNA motifs from Rfam, an additional 21 RNA motifs that are supported by literature evidence, 72 RNA motifs overlapping predicted transcription terminators or attenuators, and other candidate regulatory RNA motifs. Our study provides a list of promising novel regulatory RNA motifs potentially involved in post-transcriptional gene regulation. Combined with the previous cis-regulatory DNA motif study in S. oneidensis, this genome-wide discovery of cis-regulatory RNA motifs may offer more comprehensive views of gene regulation at a different level in this organism. The RSSVM software, predictions, and analysis results on Shewanella genomes are available at http://ural.wustl.edu/resources.html#RSSVM.An increasing number of  Shewanella genomes and predicted putative regulatory RNA elements in Shewanella oneidensis, a bacterium that has extraordinary respiratory and metal reducing abilities and great potential for bioremediation and alternative energy generation. Our findings not only recovered many RNA elements that are known or supported by literature evidence but also included exciting novel RNA elements for further exploration.RNA is remarkably versatile, acting not only as messengers to transfer genetic information from DNA to protein but also as critical structural components and catalytic enzymes in the cell. More intriguingly, RNA elements in messenger RNAs have been widely found in bacteria to control the expression of their downstream genes. The functions of these RNA elements are intrinsically linked to their secondary structures, which are usually conserved across multiple closely related species during evolution and often shared by genes in the same metabolic pathways. We developed a new computational approach to find putative functional RNA elements by looking for conserved RNA secondary structures that are distinguished from random RNA secondary structures in the orthologous RNA sequences from related species. We applied this approach to multiple  As demonstrated by previous studies Experimental screenings A number of algorithms have been developed for common RNA secondary structure prediction, such as RNAalifold Studies have shown that for a single sequence RNA secondary structure alone is not sufficient to distinguish functional RNA from random sequence RNA Sampler+Support Vector Machine). RSSVM applies a set of features to represent common RNA secondary structures and structural alignments generated by RNA Sampler, which predicts RNA structures more accurately than other approaches Shewanella genomes to identify putative cis-regulatory RNA motifs in the 5′-UTRs of orthologous genes.In this paper, we present a new SVM based functional RNA identifier named RSSVM  which measures the confidence of the prediction. The higher the P-value, the more confident the prediction. A P-value cutoff can be selected to call positive predictions. When a lower P-value cutoff is used, although more regulatory RNAs can be identified from the positive sets, more negative test sets may be simultaneously misclassified as regulatory RNAs, leading to a higher false positive rate.We examined the performance of RSSVM in identifying RNA regulatory motifs on 1686 positive and 1686 negative test sequence sets see  and compP-value cutoff are not readily comparable, because their corresponding sensitivities and false positive rates can be significantly different  . At the P-value for its predictions, thus we are not able to generate its ROC curve. But on all test sets, the overall FPR of QRNA is 0.05. At this FPR, RSSVM has a significantly higher sensitivity (0.86) than QRNA (0.51) (QRNA does not provide a similar measurement of A (0.51) .correlation coefficient (classificationCC), the geometric mean of the classification sensitivity and (1−FPR), to measure the overall performance of RSSVM in each identity range. Because the overall FPR of QRNA on all test sets is 0.05, to make fair comparisons, we use different P-value cutoffs for RSSVM, RNAz and Dynalign+LIBSVM to achieve the same FPR of 0.05 on all test sets. As shown in We further evaluated the performance of RSSVM on test sets with different ranges of average sequence identities. We use At the more stringent overall FPR of 0.01 on all test sets, RSSVM (0.68) and RNAz (0.65) have almost the same overall prediction sensitivity , and botOverall, for the best performance, RNAz, Dynalign+LIBSVM and QRNA are in favor of sequence sets with high identities. RSSVM, however, has consistent and more sensitive performance on the low-identity sets while keeping the same FPRs. These programs can complement each other for the best performance in identifying regulatory RNAs on sequences with a wide range of identities.structureCC), which approximates the geometric mean of the sensitivity and specificity of predicted base pairings SCI scores calculated based on common structures predicted by RNA Sampler, the information content (IC) which grasps the information of sequence conservation, and the mutual information (MI) which represents covariant mutations in the structural alignments, allow it to generate better SVM models to separate regulatory RNA motifs from shuffled ones, especially on sequence sets with low identities . For each UTR set, we report the classification result from the window with the best SVM probability for RSSVM or RNAz. We chose P≥0.95 and P≥0.50 as the confidence probability cutoffs for RSSVM and RNAz, respectively, which give the same overall false positive rate of 0.01 on all test sets. For QRNA, we classified a set as regulatory RNA if more than two pairwise alignments of the sequences were identified as “RNA”.As many known bacterial regulatory RNA sites are located in the 5′-UTR sequences and often conserved during evolution, we applied RSSVM, RNAz and QRNA on multiple S. oneidensis and E. coli in the Rfam seed alignments. RSSVM, RNAz and QRNA successfully detected 17, 16 and 11 of these 19 known RNA motifs, respectively, and the three approaches combined discovered 18 known RNA motifs  and 42 of 109 (39%) RNA motifs predicted by RSSVM and RNAz, respectively, overlap with these predicted transcription terminators. It indicates that the putative transcription terminators are significantly enriched in the predictions by RSSVM and RNAz, corresponding to the hypergeometric p-values of 4.0×10−26 and 5.3×10−17, respectively. In a previous study, Merino and Yanofsky S. oneidensis. They predicted 449 transcription attenuators in S. oneidensis, 123 of which are located in the 1002 orthologous UTR sets that we studied. 56 (34%) and 37 (34%) of the predictions by RSSVM and RNAz match the predicted transcription attenuators, showing significant enrichment with the hypergeometric p-values of 2.5×10−16 and 1.8×10−10, respectively. In both cases, RSSVM's predictions show higher enrichment than RNAz's predictions for putative transcription terminators or attenuators. In total, 72 unique RSSVM predictions overlap with predicted transcription terminators or attenuators. The 106 putative conserved terminators and the 123 predicted attenuators overlap in 74 orthologous UTR sets, which are more likely to contain real terminators. RSSVM, RNAz and QRNA identified 46 (71%), 30 (46%) and 23 (35%) of the common transcription terminators/attenuators, respectively, indicating that RSSVM has better sensitivity than RNAz and QRNA in finding putative conserved RNA motifs.As transcription attenuation is a common regulatory mechanism for RNA motifs in the 5′-UTRs, we checked whether the orthologous UTR sets contain any putative rho-independent transcription terminators predicted by Rnall ilvG, ilvI, leuA, rpoB, rpsL, rplU, aspS, glnS, flgB and fliE, or whose downstream genes or orthologs have been shown to be post-transcriptionally regulated in S. oneidensis or other bacterial species but without proposed regulatory RNA structures, such as ldhA, aroH, adhE, ahpC, SO1769, pflB, SO3896, speA, secE and aroF. RNAz and QRNA identified 11 and 7 of these 21 motifs with supporting literature evidence, respectively.We examined the leading genes of all the 166 operons with predicted regulatory RNAs by RSSVM . 40 of tilvG and ilvI for isoleucine, leuA for leucine, pheA for phenylalanine, tryE for tryptophan, thiC for thiamin, hisG for histidine, lysC for lysine, and aroH and aroF for aromatic amino acids. One common regulatory mechanism for some of these operons, such as ilvG, leuA, pheA, tryE and hisG, is that the 5′-UTR of the mRNA contains a transcription terminator and a short sequence that encodes a leader peptide enriched with amino acids that are the synthesized products of the downstream genes. The translation of the leader peptide may sense the concentration of the amino-acid charged tRNAs in the cell. When the charged tRNA is abundant, the leader peptide can be translated successfully and a stable terminator structure is formed, blocking the transcription of the downstream genes. But during the shortage of the amino acid charged tRNA, the translation of the leader peptide is stalled and the terminator structure is opened, allowing the transcription of the downstream genes. Another regulatory mechanism for some of the operons involved in biosynthesis pathways, such as for thiC and lysC, is the riboswitch, in which the RNA structure can bind small metabolites, the product of the downstream genes, and stabilize a terminator structure which will shut down the transcription or translation of the downstream genes.One class of our predicted RNA motifs correspond to known RNA regulatory motifs upstream of the operons involved in amino acid and vitamin biosynthesis, including rpsB , rplJ (L10), rpsL (S12), rplJ (L21), glnS (glutaminyl-tRNA synthetase) and aspS (aspartyl-tRNA synthetase). A large number of the operons in these functional categories are known to be regulated post-transcriptionally by RNA structural elements Another class of our predicted RNA motifs are located in the operons encoding ribosomal proteins and tRNA synthetases, such as pdhR (ranked 41), metJ and metB . The palindromic TF binding sites contained in the promoters of these genes are usually long and have complementary mutations in the alignments. In a previous comparative genomics study Shewanella species, but also shared by multiple genes in S. oneidensis. 62 of these palindromic sites match known transcription factor binding motifs, and their corresponding regulated target genes also show significant functional enrichment or expression coherence, indicating that these predictions are likely to be real. 231 of all the 1002 UTRs here studied contain predicted palindromic DNA motifs that have at least one type of supporting evidence, and 38 of them are in the 166 top predictions by RSSVM. There is no significant enrichment  for these putative palindromic sites in the RSSVM predictions, suggesting that the majority of the predictions by RSSVM are RNA structural motifs instead of palindromic TF binding sites. However, we cannot rule out the possibility that some genes may be regulated at both the transcriptional level (through TF DNA binding sites) and post-transcriptional level (through RNA regulatory motifs in mRNAs). Knowing the 5′ end of the mRNA would help resolve whether the predicted structure is within the mRNA, but that information is not currently available for most genes.In our predictions, some genes have been known to be regulated at the transcriptional level through binding of transcription factors (TF) to their palindromic DNA binding sites, such as SO3896, which encodes an outer membrane porin, called Omp35. A previous study (Maier and Myers 2004) showed that the mRNA levels of Omp35 in aerobic and anaerobic conditions are almost the same, but in anaerobic conditions the cell has 7-fold more Omp35 protein than it does in aerobic condition, strongly suggesting that Omp35 is regulated post-transcriptionally. In E. coli, some outer membrane porins, such as OmpA or OmpW, are regulated by antisense small RNAs (sRNA), micA and rybB. But these sRNAs are not found in S. oneidensis, suggesting that S. oneidensis may have a different regulatory mechanism for its outer membrane porins, one possibility being that regulatory RNA elements in the 5′-UTRs might be involved. Another example is for genes SO1769 and SpeA, both of which are found to be regulated post-transcriptionally in S. oneidensisBesides the known RNA motifs, our predictions also include some interesting candidate novel motifs. One interesting example is for gene LeuA operon as an example to illustrate detailed analysis of the predicted RNA structures. The predicted alternative structures in the 5′-UTR of the LeuA operon are shown in Leu is adequate, the leader peptide can be successfully translated, releasing the ribosome at the stop codon of the leader peptide, and the reformation of the anti-antiterminator stem keeps the terminator structure intact which constitutively shuts down the transcription of the downstream genes. When the concentration of tRNALeu is low in the cell, the ribosome is stalled at the region enriched with leucine codons and the anti-antiterminator stem stays opened, which enables the formation of the anti-terminator and prevents the formation of the terminator stem, allowing transcription of the downstream genes. In the structural alignment of the predicted LeuA terminator motifs in the five Shewanella species  by adding one improvement at a time . For a tShewanella study , it only takes RSSVM about 200 hours on a single CPU machine to finish the genome-wide scan of RNA motifs. The entire process can be easily run in parallel on multiple-CPU Linux clusters, allowing the whole genome prediction to be done in hours or less. We recommend that users run RNAz as well, since RNAz has better performance on sequences of high identity, which is complementary to the optimum performance of RSSVM on low-identity sequences. Moreover, consensus predictions by both approaches may provide extra confidence in the prediction quality. RSSVM is more advantageous than Dynalign+LIBSVM and QRNA in that RSSVM can take input of multiple sequences, which would provide more information on sequence conservation and complementary mutations than two sequences. Recently, Yao et al. RNA Sampler and RSSVM run reasonably fast for genome-wide scan of regulatory RNAs. On average, it takes RNA Sampler 125 seconds on a single CPU workstation to predict the common structure of a set of 5 RNA sequences of an average of 150 nt in length. For a project with the similar size of the LeuA, we can infer function and mechanism of the RNA motif from its structure. Although we cannot guarantee that the predicted structures are correct and perfectly match the real structures, they often indicate strong structural conservation information in the potential regulatory regions, which leads to sensitive detection of RNA motifs. Users can use Mfold The RNA classification of RSSVM is based on the common structures generated by RNA Sampler. These predicted common structures provide preliminary hints for the putative structures associated to the regulatory functions. As demonstrated in the RNA motifs for P-values in our case) will help increase prediction sensitivities, but at the same time more false positives may appear in the predictions. As seen in the ROC curves generated on the test sets  in computational predictions. Using looser cutoffs  from 372 eukaryotic RNA motif families from Rfam and the same number of shuffled sequence sets (negative eukaryotic test sets). Each sequence set contains 3–6 sequences whose average sequence identities ranges from 20% to 100%. The ROC curves on these test sequences are shown in Application of RSSVM to find RNA regulatory motifs/genes is not limited to the Shewanella research community and research groups who are interested in RNA regulatory motifs or post-transcriptionally regulation, we made the RSSVM software, predictions and comprehensive analysis results available online at http://ural.wustl.edu/resources.html#RSSVM.To better serve the S = 75 (structure sample size) and i = 15 (iterations), were used in all predictions. Although RNA Sampler is able to predict RNA secondary structures with pseudoknots, we opted to not allow pseudoknots in this study.We use the program, RNA Sampler Support Vector Machines (SVM) are supervised learning methods widely used for classification and regression. In these methods, labeled data are represented by vectors that are defined by various features, and support vector machines map the feature vectors to a higher dimensional space and construct a maximal separating hyperplane to classify the input data into binary categories. SVM has been used in previous studies We developed a new SVM classifier for detecting regulatory RNAs. Our SVM classifier differs from the previous ones in three major aspects: first, the recently developed new program, RNA Sampler, is used to predict common RNA secondary structures and structural alignments on any set of homologous RNA sequence, and feature vectors based on such predictions are used to build the SVM classifier; second, a different set of feature parameters are used to represent the common RNA structures and structural alignments; third, the SVM classifier is trained on a larger number of various bacterial RNA gene and motif families that cover a wider range of sequence lengths and identities than previous studies To train the SVM classifier, both positive and negative training sets are needed. We use sequences of 112 known bacterial regulatory RNA families retrieved from the Rfam database In total, we generated 8335 positive and 8335 negative training sequence sets. Using a similar procedure, we generated 1686 positive and 1686 negative test sequence sets that are not identical to any training set. The distributions of the sizes and average pairwise sequence identities of the training and test sets are shown in z score of all sequences sharing the common structure (Z) z score measures the thermodynamic stability of a sequence by comparing the MFE of the sequence to the MFE distribution of random sequences of similar length and base composition. (2) The structure conservation index (SCI) of the common structure, measuring the conserved structure information contained in the structural alignment. It is defined as A/ĒSCI = E, where AE is the consensus MFE of the common structure and Ē is the average MFE of all sequences I), measuring the sequence conservation of the stems in a structural alignment M), measuring the overall covariation of the complementary columns in the stems In our SVM classifier, we use six features to represent the common RNA secondary structure and structural alignment. These features are: (1) The mean minimum free energy (MFE) c) and the value of gamma of the RBF (g) to define a hyper-dimensional space that gives maximal separation of the positive  and negative training data (shuffled RNA motifs). We did a grid search to find the best combination of c and g within certain ranges . To avoid overfitting the training data, we employed a 5-fold cross-validation, in which the whole training sets were divided into 5 subsets of equal size and sequentially one subset was tested using the classifier trained on the remaining 4 subsets. Because each training set was predicted once, the accuracy of the cross-validation was the percentage of data which were correctly classified. We determined that the combination of c = 210 and g = 2−3.5 gave one of the best classification results and fewer false positive predictions. Thus we used these c and g parameters to train the SVM classifier on the whole training sets to obtain the final classification model. The option of “−b 1” was used to report confidence probability of classification .On each training sequence set, we ran RNA Sampler to generate the common structure and structural alignment and calculated the values of the six features described above. We implemented the SVM classifier for regulatory RNA structure detection using the core program LIBSVM z scores and SCI scores We predicted the common structures and structure alignments for all positive and negative test sets using RNA Sampler and classified the structures with the final SVM model. We also compared the performance of our SVM classifier on these test sets with that of other leading software for RNA motif identification, including RNAz Shewanella genomes for genome-wide regulatory RNA discovery.With the RNA secondary structure prediction algorithm, RNA Sampler, and the RNA motif identification algorithm, RSSVM, we can search putative regulatory RNA structural motifs from any orthologous RNA sequence set. As shown in the flow chart in Shewanella oneidensis MR-1, S. denitrificans OS217, S. frigidimarina NCIMB 400, S. amazonensis SB2B and S. baltica OS155 were downloaded from the NCBI Genebank database.The genomic sequences of S. oneidensis is limited, we assumed that two adjacent genes in the same orientation whose intergenic distance is less than 40 nt are in the same transcription unit S. oneidensis, we identified its first gene and this gene's orthologs in the other four Shewanella species, and then retrieved 120∼250 nt 5′-UTR sequence upstream and 20 nt downstream of the translation start codons of these genes as one set of orthologous sequences for RNA secondary structure search. We identified orthologous genes by comparing all protein sequences between S. oneidensis (the anchor genome) and the other species using the WU-BLAST program  −10; and (iii) the BLASTP alignment covered ≥60% of the length of at least one sequence.Since most of the known bacterial regulatory motifs are located in the mRNA leader sequences of the regulated transcription units (operons), we focused on finding conserved RNA regulatory motifs in the 5′-UTRs of orthologous transcription units (TU). Because our knowledge of the operon structures in Shewanella species. The mRNA leader sequences obtained had a high AU content, with a base composition of A 31%, U 29%, C 19% and G 21%.In total we obtained 1002 sets of orthologous mRNA leader sequences from the five We scanned each orthologous UTR sequence set in three overlapping windows, −250∼−100, −200∼−50, and −150∼20 (1 corresponds to the translation start site). We first predicted the common RNA structure for each window and generated corresponding structural alignment using RNA Sampler, and then provided the RNA Sampler output to the SVM classifier to predict whether the window contains a regulatory RNA structure. We also aligned sequences in the same window using ClustalW and applied RNAz and QRNA to predict the existence of RNA motifs. Because QRNA only takes two-sequence alignments as input, for each aligned sequence window, we split the multiple-sequence ClustalW alignment into pairwise alignments, each consisting of the sequence from the anchor species and a sequence from another species. We call that QRNA detected the RNA motifs in the sequence window only if at least two of all the pairwise alignments were predicted to contain an RNA motif by QRNA.Dataset S1Raw Data for ROC curves in (0.57 MB XLS)Click here for additional data file.Dataset S2Raw Data for ROC curves in (0.50 MB XLS)Click here for additional data file.Figure S1Cumulative distribution of sequence identities of the sequence sets with predicted regulatory RNAs by RSSVM and/or RNAz.(0.01 MB PDF)Click here for additional data file.Figure S2The Receiver Operating Characteristic (ROC) curves of RSSVM, RNAz, retrained RNAz on ClustalW alignments, and retrained RNAz on RNA Sampler alignments. (A) On all test sets. (B) On test sets with sequence identities lower than 70%. We retrained RNAz using the same training sets for RSSVM.(0.02 MB PDF)Click here for additional data file.Figure S3The Receiver Operating Characteristic (ROC) curves of RSSVM and RNAz on real and shuffled sequence sets of eukaryotic RNAs from Rfam. The curves of both programs on all test sets (sequence identities range between 20–100%) and on test sets of low identities (<70%) are drawn separately.(0.01 MB PDF)Click here for additional data file.Figure S4Shewanella sequence sets.Distribution of sequence identities and size of the sequence sets studied. (A) Training sets. (B) Test sets. (C) (0.01 MB PDF)Click here for additional data file.Figure S5Flow chart of the genome-wide identification of RNA regulatory motifs/genes using RNA Sampler and RSSVM.(0.01 MB PDF)Click here for additional data file.Table S1The prediction sensitivities and false positive rates of RSSVM, RNAz, Dynalign+LIBSVM and QRNA on test sets with different sequence identities. Different P-value cutoffs were used to fairly compare prediction sensitivities of different SVM models at the same FPR level. Numbers in bold fonts are the best results given by all the programs for an identity range.(0.01 MB PDF)Click here for additional data file.Table S2Top 166 predicted regulatory RNAs by RSSVM.(0.06 MB PDF)Click here for additional data file.Table S3Comparisons between different RNA motif identification algorithms.(0.01 MB PDF)Click here for additional data file.


A growing tumor in the body can be considered a complex ecological and evolutionary system. A new eco-evolutionary hypothesis  proposes that tumors have elevated phosphorus (P) demands due to increased allocation to P-rich nucleic acids, especially ribosomal RNA, to meet the protein synthesis demands of accelerated proliferation.We determined the elemental  and nucleic acid contents of paired malignant and normal tissues from colon, lung, liver, or kidney for 121 patients. Consistent with the GRH, lung and colon tumors were significantly higher (by approximately two-fold) in P content (fraction of dry weight) and RNA content and lower in nitrogen (N):P ratio than paired normal tissue, and P in RNA contributed a significantly larger fraction of total biomass P in malignant relative to normal tissues. Furthermore, patient-specific differences for %P between malignant and normal tissues were positively correlated with such differences for %RNA, both for the overall data and within three of the four organ sites. However, significant differences in %P and %RNA between malignant and normal tissues were not seen in liver and kidney and, overall, RNA contributed only ∼11% of total tissue P content.Data for lung and colon tumors provide support for the GRH in human cancer. The two-fold amplification of P content in colon and lung tumors may set the stage for potential P-limitation of their proliferation, as such differences often do for rapidly growing biota in ecosystems. However, data for kidney and liver do not support the GRH. To account for these conflicting observations, we suggest that local environments in some organs select for neoplastic cells bearing mutations increasing cell division rate  while conditions elsewhere may select for reduced mortality rate . Despite a greatly expanded knowledge base, post-occurrence cancer survival rates have shown only modest improvements in recent decades in vivo P-limitation of growth Ecological stoichiometry is the study of the balance of energy and multiple chemical elements in ecological interactions Biopsy samples were obtained via the Cooperative Human Tissue Network (CHTN) of the National Cancer Institute. Samples were obtained nearly exclusively from primary tumors originating in four organs . According to standard CHTN procedures, samples of tumor and of healthy adjacent tissues were obtained, with a portion examined by a pathologist for diagnosis and the remaining material snap-frozen in liquid nitrogen and held at −70°C until shipment on dry ice to ASU where they were held at −80°C until further processing. For nucleic acid analysis, sub-samples from each biopsy sample were fractured on dry ice and 50–100 mg samples were immediately homogenized with 1 ml Trizol (Invitrogen™). Following established extraction procedures t-tests on the null hypothesis that all (four) parametric ratios equaled unity. If assumptions of normality were not met, we performed analogous one-sample Wilcoxon tests on the analogous null. Attained significance for these multiple comparisons was adjusted using Holm's procedure for each comparative measure. In addition, to evaluate among-site differences in chemical composition among healthy tissues, we also performed Kruskal-Wallis tests for each parameter. This test is robust against violations of the assumptions of ANOVA. We also report Pearson's product moment correlation coefficient between total P and RNA content. All statistical calculations were performed using R Statistical Software, version 2.1.1.All comparative measures, i.e., %P, %N, N:P ratio, %RNA, %DNA and % of P contributed by RNA, were handled similarly. For each tissue of origin , data were analyzed directly and after being summarized in pair-wise fashion for each patient as a ratio of malignant tissue to normal. Ratios for percentage of P contributed by RNA were log-transformed. Outliers, defined as any measurement falling more than 1.5 inner-quartile ranges beyond the nearest inner quartile for a specific tissue, were removed before further analyses. No more than one or two data points were removed as clear outliers in any given analysis. Deviations from normality were probed with D'Agostino's test for skewness and Anscombe-Glynn tests for kurtosis. We tested homogeneity of variance assumptions and also compared variances of normal and malignant tissues for all measures using the Fligner-Killeen test for homogeneity of variance, both for the overall data set and for each organ site. In every case but two, Fligner-Killeen agreed with an analogous Bartlett test. In both exceptions, the Bartlett algorithm was obviously affected by skewness in the data. If normality and variance assumptions were met, absolute data were analyzed by two-way analysis of variance (ANOVA) with organ  and tissue type  as independent variables. The pair-wise malignant/normal ratios were evaluated for significant differences between malignant and normal tissues for the four organ sites by using one-sample −4), being higher in liver (∼1.3% and 0.75% respectively) relative to normal samples from kidney, colon, and lung . Finally, among-organ differences in %P in RNA for normal tissues also differed significantly (p<10−4). The percentage of total P contributed by P in RNA for normal tissues  but not for kidney and liver (p>0.8). This pattern also held for DNA concentrations  and for three of the four organ sites . This provides evidence that the GRH holds not only at the aggregate scale of the overall averages but also at the scale of individual patients.Next we consider differences between malignant and normal tissues. There was generally greater variance in %P and %RNA in malignant tissues relative to normal tissues see  and 5, bWhile the findings just described are broadly consistent with the GRH, in our samples RNA contributed only ∼10% of total P, in contrast to a previous finding of ∼50% for bacteria, crustaceans, and insects r2 = 0.72). In total, these results indicate that tumor development in lung and colon involves shifts of biochemical allocations, including both RNA and DNA, resulting in more than a two-fold increase in the mass-specific demand for phosphorus. We note that this increase is likely an underestimate of the elevated P demands of transformed cells, as the biopsy samples of tumor tissues likely involve an undetermined mixture of both transformed and normal cells along with acellular stromal matrix.Despite these issues, averaged total P content and RNA content for malignant or normal tissues for the four organ types showed a strong and significant positive relationship , tumors in lung and colon may reflect the outcome of long-term selection favoring cellular transformations increasing cell division rate (“r-selected”). In contrast, more stable local conditions in liver and kidney may instead predominantly favor transformed cells that have acquired lower rates of cellular mortality, such as reduced apoptosis (“K-selected”). Under the GRH, the r-strategy requires a particular biochemical allocation affecting biomass P content, but a K-strategy does not. These ideas can be tested by characterizing the particular genetic transformations that predominate in P-rich tumors vs. those that predominate in low-P tumors. Our hypothesis predicts that P-rich tumors should be dominated by cells with genetic lesions interfering with appropriate down-regulation of ribosome production or other cell-cycle checks while low-P tumors should be dominated by cells with mutations leading to inappropriately low rates of apoptosis or senescence.myc protein leads to increased cellular proliferation via amplified rates of ribosome biogenesis myc is over-expressed in 70% of colon cancers myc represents a possible pathway to a P-rich “r-selected” tumor. We propose a similar scenario for tumorigenesis via mutations involving retinoblastoma protein, which is involved in regulation of RNA polymerases I and III Fas-mediated COX-mediated Fas-mediated apoptosis provides an evolutionary mechanism by which tumor cells evade apoptosis signals via DcR3, a “decoy receptor” for the Fas protein ligand, FasL. DcR3 efficiently binds FasL and neutralizes its effectiveness as an effector molecule for cytotoxic T and NK cells. DcR3 has been shown to be significantly amplified in 50% of primary lung and colon tumors both cellular replication and cellular death (p53 being a prominent example, Existing data hint at the potential validity of such a framework. For example, it is known that over-expression of c-4 into replicating tumor cells 4 loss and mobilization of PO4 from bones, is another intriguing example of a connection between tumor development and P homeostasis. While preliminary, our findings indicate that, for at least some tumors, the requirements for the key nutrient element phosphorus differ substantially from those of normal tissues. Future studies are needed to evaluate whether the amplification of P content in tumor tissues that we document has physiological significance and whether it may provide additional avenues for therapy. Additional work further characterizing the stoichiometric signature of tumor tissues and examining the dynamical consequences of observed differences for tumor progression and for selection among clonal lineages is needed as well.Ecological studies have shown that P-rich organisms are generally more susceptible to P-limited growth due to insufficient supplies of P from the external environment or diet


C. elegans pharynx develop in an intricate yet reproducible way within the narrow confines of the embryonic pharyngeal primordium. To complement an earlier study of the pharyngeal M2 motorneurons, we have now examined the effect of almost forty mutations on the morphology of a bilateral pair of pharyngeal neurosecretory-motor neurons, the NSMs.We are interested in understanding how the twenty neurons of the unc-6, unc-34, unc-73), while the major sub-ventral branch was more sensitive to mutations that affect components of the extracellular matrix (e.g. sdn-1). Of the tested mutations, only unc-101, which affects an adaptin, caused the loss of the newly described thin minor process. The major processes developed synaptic branches post-embryonically, and these exhibited activity-dependent plasticity.A careful description of the NSM morphology led to the discovery of a third, hitherto unreported process originating from the NSM cell body and that is likely to play a proprioceptive function. We found that the three NSM processes are differently sensitive to mutations. The major dorsal branch was most sensitive to mutations that affect growth cone guidance and function (e.g. By studying the effects of nearly forty different mutations we have learned that the different NSM processes require different genes for their proper guidance and use both growth cone dependent and growth cone independent mechanisms for establishing their proper trajectories. The two major NSM processes develop in a growth cone dependent manner, although the sub-ventral process relies more on substrate adhesion. The minor process also uses growth cones but uniquely develops using a mechanism that depends on the clathrin adaptor molecule UNC-101. Together with the guidance of the M2 neuron, this is the second case of a pharyngeal neuron establishing one of its processes using an unexpected mechanism. C. elegans.The development of organ innervation requires numerous axon guidance cues that are evolutionarily conserved and more easily studied in simple organisms. Research in this area has led to a general model where receptors on growth cones, which are motile structures at the tips of growing axons, respond to a wide variety of cues that include long-range signals such as netrins or secreted forms of semaphorins, or contact-dependent cues that include ephrins, Slit and many components of the extracellular matrix -3. DiffeC. elegans pharynx is an isolated neuro-muscular organ composed of only 80 cells. It is located at the anterior end of the worm where its primary function is to rhythmically pump and grind bacterial suspensions (food) before transferring the product to the intestine. Twenty neurons innervate the pharynx in a highly reproducible fashion, and most of these may be ablated without severe effects on viability or pharyngeal pumping [The  pumping . There aC. elegans [The pharyngeal nervous system can be divided into four principal parts: two subventral nerve cords, one dorsal nerve cord, and one circular pharyngeal nerve ring located within the posterior half of the metacorpus . One int elegans . In thatneurosecretory-motor neurons), that can be visualized using the pTPH-1::GFP reporter [To address this question and better understand how the pharyngeal nervous system develops, we studied the genetic pathways that regulate guidance of another pair of pharyngeal neurons, the NSMs .Pharyngeal expression of the ent Fig. . When thhatching . BecauseThe NSML and NSMR neurons are bilateral homologues. The cell body of each neuron resides within a subventral pm4 muscle cell in the metacorpus and extends one major and one minor process Fig. . The majC. elegans neurons are typically simple and unbranched [C. elegans.branched . For thiunc-30 and unc-46. These mutations affect differentiation or GABA secretion in GABAergic neurons and should not have direct effects on NSM development since the NSMs are serotonergic neurons. Not surprisingly, the unc-30 and unc-46 mutations had little effect on the NSMs: 93 and 91% of the NSM neurons were scored as normal in these two mutants, and the rare abnormal neurons were cases where the length of the processes appeared as either too short or too long, compared to the wild-type  or exhibit a morphology so abnormal, with cell bodies frequently misplaced, that it is not easily classified (19%). 12% of the NSM neurons in these mutants lack the dorsal processes and 3% have a short sub-ventral process. These results indicate that sax-3 is important in establishing the anterior-posterior polarity of the NSM neurons, or their correct positioning within the primordium, and for axon initiation.Slit-Robo signaling is involved in midline guidance in both invertebrate and vertebrates . In C. e defects . In sax-slt-1 is the only known ligand for sax-3 in C. elegans and is involved in dorsal-ventral and midline guidance [slt-1 mutant caused the dorsal and sub-ventral and processes to be short in 16% and 22% of cases, respectively. The fact that the sax-3 mutation caused more severe and qualitatively different defects than the slt-1 mutation indicates that it can bind at least one other ligand during NSM neuron development.guidance . The sltunc-34 is homologous to the signal transduction protein ENABLED that is required for axon guidance and plays a vital role in downstream signalling for both the netrin and slit pathways [unc-34 mutants, 77% of the dorsal processes are absent indicating that this gene is essential for the initiation of the dorsal process from the NSM cell body. Another guidance gene, unc-69 is also important for the proper development of the major process. unc-69 encodes a protein with a short coiled-coil domain that is generally important for axon outgrowth and proper synaptic formation [unc-69 mutants, the initiation (28%) and termination (38%) of the dorsal process are primarily affected, with similar weaker effects on the sub-ventral process.pathways . In unc-ormation ,28. In uC. elegans they seem to play only a minor role in axon guidance but have critical functions in multiple aspects of epidermal morphogenesis [(vab-1). Our results indicate that ephrins play only a minor role, if any, in the development of the dorsal processes of the NSM neurons: vab-1 mutant exhibit 7% small dorsal process, 1% missing dorsal process and no sub-ventral defects.The ephrins are a highly conserved family of proteins that are involved in axon guidance in vertebrates whereas in ogenesis ,30. To fC. elegans is unc-129, which encodes a member of the TGF-beta family of secreted growth factor signalling molecules that acts as a dorso-ventral guidance cue [Another important axon guidance molecule in ance cue ,32. The kal-1, which encodes an extracellular protein with a fibronectin III domain that likely acts as a guidance cue [Finally, ance cue , had a sC. elegans, and are also important also for the maintenance of their morphologies [mec-1, sax-7, sdn-1, unc-23, unc-52 and unc-112 mutants. Our findings indicate that ECM or ECM-adhesion genes are involved in both the initiation and the termination of the major NSM processes. sdn-1 is a type I transmembrane heparan sulfate proteoglycan thought to be involved in cell-cell or cell-matrix adhesion [sdn-1 caused the most severe defects on the sub-ventral process, with 32% of them being absent, and another 5% being too short. The large transmembrane ECM adhesion molecule sax-7 caused severe defects in both the long dorsal and the subventral processes, with 37% and 34% being affected, respectively. mec-1 and unc-112 encode two extracellular proteins that are also involved mainly in development of the sub-ventral process. MEC-1, is an ECM protein with multiple EGF and Kunitz domains and is involved in organizing channel complexes within mechanosensory assemblies [mec-1 mutants, 8% of the NSM sub-ventral processes are absent and another 4% are short. In unc-112 mutants, 9% of the NSM sub-ventral processes are short. Other ECM genes such as unc-23, unc-52 exhibit low penetrance defects in the major process of the NSM neurons. Both these mutants lead to initiation and termination problems in the dorsal and sub-ventral processes of the NSM, which often caused thickened endings. unc-61 encodes a C. elegans septin that is thought to regulate the contact points between the cytoskeleton and the cell cortex, in this way possibly influencing attachment between the cell and the extracellular matrix [unc-61 mutant, 19% of the dorsal processes were too long or absent, and 5% of the subventral branches were truncated.ECM molecules provide instructive signals for many neurons in hologies . We studadhesion . Of all semblies , and UNCr matrix -40. In tC. elegans neurons require proper localization of active synapses for their morphology and maintenance [syg-1 mutant, but that both of the major processes are generally not affected by mutations in unc-101 or unc-104. SYG-1 is an immunoglobulin super-family protein that determines the position of specific synapses in C. elegans [syg-1 mutants have a shorter dorsal process and 24% have no dorsal process, indicating that formation of synapses is essential both for the initiation and the proper guidance of the dorsal process. The weak effects of unc-101 and unc-104 on the major processes perhaps reflect their intracellular functions [unc-104 mutant does have reduction in the formation of synapses, its function seems to reside principally in synaptic vesicle trafficking rather than synapse formation per se [Some ntenance . We foun elegans ,43. 26% unctions -47. For n per se ,47.tph-1 and mod-5 genes that respectively encode a tryptophane hydroxylase and a serotonin transporter [mod-5 mutant. This result supports the idea that functioning synapses may play a role in the development or maintenance of the NSM neurons.The NSM neurons are serotonergic, and their physiological activity depends on the nsporter ,48. Shorpha-2. pha-2 encodes a homeobox transcription factor necessary for the successful differentiation of the pm5 muscle cells that make up the isthmus, and also for the establishment of the correct morphologies of several pharyngeal structures, including the isthmus and metacorpus [pha-2 mutants, the isthmus is short and thick due to misplaced cell nuclei. In these mutants, 45% of NSM neurons abnormally send a major process anteriorly, and 21% of the dorsal processes are absent; another 27% of the neurons show other defects such as multiple branching and misplaced cell bodies. Our results indicate that pha-2 is not only required for the proper positioning of the NSM cell bodies within the pharynx but also determines the axonal polarity of the NSM neurons. mnm-5 is a mutant in which the cell bodies of the pharyngeal M2 neurons are often misplaced into the metacorpus, rather than being located in their normal position within the posterior bulb [mnm-5 is currently unknown. In this mutant, 8% of the NSM dorsal processes are missing, and 11% of the NSM cell bodies are misplaced or misshaped, and send grossly misguided branches.Unsurprisingly, we found that the NSM processes depend on correct cellular context to establish their trajectories: the NSM neurons were grossly abnormal in the pharyngeal mutant tacorpus ,50. In pior bulb . The molunc-101 mutation. Neurons are polarized cells that contain distinct sets of proteins in their axons and dendrites and the polarized movement of proteins is a result of selective transport. In C. elegans, clathrin-associated proteins are known to determine the polarity between axons and dendrites. unc-101 encodes a mu1 subunit of the AP-1 clathrin adaptor complex that is involved in polarized dendrite transport and for determining the axon-dendrite polarity in olfactory neurons [unc-101 mutants, the NSM neurons have no minor process whereas the major process is completely normal  almost all of the tested axon guidance mutants could perturb the establishment of the studied axon trajectories. The various axons must each be capable of responding to multiple, redundant cues to different effect in order to initiate and guide its unique trajectory. Thus M2 and NSM both depend on many of the same guidance pathways , yet produce very different morphologies. We have previously shown that the M2 growth cone requires an interaction with the M3 neuron for its proper programming [Drosophila and their growth cones are reprogrammed to prevent them from crossing again [In a broad perspective, and also taking into account our earlier work on the guidance of the pharyngeal neuron M2 ,52, sevegramming ,58, or wng again . The div1. The serotonergic NSM neurons harbour short synaptic branches that develop post-embryonically, and whose number can be regulated by serotonin levels.2. The growth of the NSM processes, just like that of the M2 neuron previously studied , relies pha-2, unc-34, and unc-101). Of these, only unc-34 and unc-101 are likely to directly affect the growth of the NSM processes, rather than its guidance. Thus NSM development integrates multiple (redundant) pathways and is a robust mechanism usually capable of withstanding failure in any one pathway.3. Of thirty-nine mutations tested, only ten produced less than 15% abnormal NSM neurons, yet only three caused highly penetrant defects in more than 80% of NSM neurons  or guidance cues and their interpretation . Thus the dorsal process probably requires more complex guidance decisions relative to the sub-ventral process, as one would expect from its more intricate trajectory.4. Of the twenty-nine mutants with significant effects on the NSM neurons, twenty-five mutants had more severe effects on the major dorsal than the subventral NSM process, including mutations that impair growth cone function  had more severe effects on the major sub-ventral branch. Of these, sdn-1 had the most severe effect, suggesting that adhesion or substrate choice is a relatively important parameter influencing the growth of that branch.5. Among the mutations studied, only four , this suggests that the minor branch does not depend on growth cones for its establishment, but rather relies on the targeted deposition of material from clathrin-coated vesicles or on the clathrin-dependent endocytosis of a signal from the environment by the outgrowing dendrite.6. Only one mutation, All strains were maintained using standard methods , and werkal-1(gb503), mod-5(mg280), mab-20 (bx24), unc-14(e57), unc-73(e936), unc-40(e271), unc-101(m1).Linkage group (LG) I: tph-1 (mg280), unc-52(e1421), unc-104(rh1016), vab-1(dx31).LG II: eat-4(ky5), mnm-5(et5), unc-69(e587), unc-119(e2498).LG III: efn-2(ev658), pha-3(ad607), sax-7(ok1244), unc-5(e35), unc-30(e318), unc-44(e362), unc-129(ev55), zag-1(ok214), zdls13.LG IV: max-1 (cz1632), mec-1(e1066), unc-23(e611), unc-46 (e177), unc-51 (e369), unc-61 (e228), unc-76 (e911), unc-112 (r367), vab-8(ev411).LG V: fax-1(gm83), pha-2 (ad472), sax-3 (ky123), sdn-1(zh20), slt-1 (eh15), syg-1(Ky652), tag-53 (gk163), unc-115(e222), wrk-1(ok695), zig-4 (gk34).LG X: zdls13 carries the tph-1::gfp transcriptional reporter expressed in the NSM, HSN and ADF neurons, and was a gift from Scott Clark. This is strictly a promoter reporter expressing no part of the TPH-1 protein.zdls13 were mounted on 2% agarose pads containing a drop of 100 mM levamisole. NSM pharyngeal neuron trajectories were scored at 400× and 1 000× magnification using a Leica DML or a Zeiss Axioplan compound microscope equipped with FITC filter sets, used with excitation 450–490 nm. Each NSM neuron of any given animal was scored into the following categories: Wild-type (cell body is properly placed in metacorpus and both the major and the minor processes show no guidance defect), short-dorsal process , short-subventral process , long-dorsal process , no-dorsal process , no-subventral process , anterior-misguidance (one of the processes extends anteriorly within the procorpus instead of growing posteriorly), no-minor process (the minor process is absent) and others (includes defects that are not categorized). Each strain was scored independently by two of the authors and the scoring results were found to be similar and therefore pooled in Table Worms carrying Worms were mounted on dried 2% agarose pads (in H2O), paralyzed by one drop of levamisole (100 mM) and examined by a Zeiss LSM 510 META System connected to an inverted Zeiss Axiovert 200 microscope.For some experiments L1 larvae were grown in the presence of 50 mM levamisole or 7.5 mM serotonin until they became 1-day old adults. They were then mounted on agarose pads, imaged by confocal microscopy and the number of synaptic branches counted by analysing Z-stacks of the images.Archival prints of the wild type adult pharynx were examined from four serially sectioned animals from the MRC collection  and several others in the Hall collection to follow the trajectory of the minor dendritic branch and of the multiple short synaptic branches of the two major axons.CA and MR contributed equally, carried out most of the experiments and helped with the writing of the manuscript. DHH provided electron microscopy results, and helped writing the manuscript. MP helped in experimental design and interpretations, and took the main responsibility for writing the article.


In contrast, plants deficient for RNA Polymerase IV (Pol IV) function show an increase in polyadenylated LTR RNA transcripts. These findings support a model in which Pol IV functions independently of the small RNA accumulation facilitated by RMR1 and RDR2 and support that a loss of Pol IV leads to RNA Polymerase II–based transcription. Additionally, the lack of changes in general genome homeostasis in rmr1 mutants, despite the global loss of 24 nt small RNAs, challenges the perceived roles of siRNAs in maintaining functional heterochromatin in the genomes of outcrossing grass species.Mutations affecting the maintenance of heritable epigenetic states in maize identify multiple RNA–directed DNA methylation (RdDM) factors including RMR1, a novel member of a plant-specific clade of Snf2-related proteins. Here we show that RMR1 is necessary for the accumulation of a majority of 24 nt small RNAs, including those derived from Long-Terminal Repeat (LTR) retrotransposons, the most common repetitive feature in the maize genome. A genetic analysis of DNA transposon repression indicates that RMR1 acts upstream of the RNA–dependent RNA polymerase, RDR2 (MOP1). Surprisingly, we show that non-polyadenylated transcripts from a sampling of LTR retrotransposons are lost in both  Most eukaryotic genomes are divided into two functional classes of regulation: the euchromatic and the heterochromatic. Heterochromatic regions, often composed of potentially deleterious transposons and retrotransposons, are typically viewed as “silent” or not transcribed. Paradoxically, evidence from multiple organisms indicates that heterochromatic regions must be transcribed to maintain a heterochromatic character. In plants, specialized RNA polymerase complexes are thought to specifically process repetitive regions of the genome into small RNA molecules that facilitate maintenance of a heterochromatic environment. We investigated the role of this specialized polymerase pathway in maintaining maize genome homeostasis with particular focus on RMR1, a novel protein related to a family of DNA repair proteins, whose function in modifying repetitive regions of the genome is unknown. We find most small RNA generation is dependent on RMR1, which appears to function downstream of the specialized polymerase, RNA polymerase IV. However, we provide evidence that the function of RNA polymerase IV is not disrupted by the absence of small RNA generation. Our results suggest the division of the plant genome into euchromatin and heterochromatin is maintained by template competition between the specialized plant polymerases and canonical RNA polymerase II, and not by the subsequent generation of small RNA molecules. A common feature of higher eukaryote genomes is an abundance of repetitive sequences, represented primarily by retroelements and DNA transposons. These repetitive sequences are often characterized as being heterochromatic, displaying both DNA and histone-level modifications associated with repressive chromatin environments Schizosaccharomyces pombeArabidopsis, a model for the RdDM pathway Dicer-like protein, DCL3. The siRNAs associate with an Argonaute protein (AGO4) that interacts with the C-terminus of NRPE1, the largest subunit of a second plant-specific RNA polymerase known as Pol V. The Pol V complex transcribes genomic sequence targeted for RdDM and in so doing presumably tethers the AGO4 complex to target DNA sequences via small RNA-nascent RNA interactions Repetitive sequences in plants are targeted by an RNA-directed DNA methylation (RdDM) pathway Arabidopsis the function of RdDM remains enigmatic. Loss of certain RdDM pathway components abolishes most 24-nt RNA species Arabidopsis genome. The Arabidopsis genome is composed of ∼10% repetitive sequence, most of which is found in pericentromeric regions Arabidopsis genes are close to small RNA clusters In mediator of paramutation1 (mop1) locus was found to encode an ortholog of Arabidopsis RDR2 required to maintain repression6 (rmr6) locus was recently shown to encode the ortholog of the largest subunit of the RNA polymerase IV complex, Arabidopsis NRPD1 required to maintain repression1 (rmr1) locus as encoding a Snf2-like ATPase responsible for maintaining both specific cytosine methylation patterns at a DNA transposon fragment and its cognate ∼24 nt RNA species Arabidopsis DRD1 and CLSY1 Multiple components of a maize RdDM pathway have been identified using genetic screens for factors necessary to maintain repressive states associated with paramutations. The de novo cytosine methylation Arabidopsis RMR1 ortholog remains unknown.While multiple loci encoding Snf2-like proteins have been identified in genetic screens for small RNA-directed silencing behaviors, the role of these ATPases in the RdDM pathway remains obscure. CLSY1 was identified in screens for components required for intercellular spreading of RNA-induced silencing Mutator DNA transposon. Additionally, both RMR1 and RDR2 are necessary for the accumulation of non-polyadenylated LTR retrotransposon RNA transcripts in a manner that is distinct from the role of Pol IV, which is necessary for the repression of polyadenylated transcripts from the same sampling of elements that are targeted by RMR1 and RDR2. These results point to an unexpected role for the RMR1 class of ATPases in mediating amplification of non-polyadenylated transcripts downstream of the repressive activity of Pol IV. Interestingly, we also find that in the highly repetitive maize genome, the loss of 24 nt RNAs is not associated with any obvious perturbation of genome homeostasis. On the contrary, the loss of RMR1 appears to dampen the phenotypic variances typical of inbreeding depression. This finding stands in contrast to results from plants deficient for maize RPD1 Here we show that RMR1 is responsible for the accumulation of a majority of maize 24 nt RNAs, and for the RDR2-independent inactivation of an autonomous Pl1-Rhoades allele were lost in homozygous rmr1-1 mutant plants rmr1-1 homozygotes relative to heterozygous siblings while the abundance of 21 nt RNAs appeared unchanged  of non-mutant levels in rmr1-1 homozygotes (rdr2 (mop1-1) mutants (rpd1 (rmr6-1) mutants Using gel blot hybridization, we previously observed that ∼24 nt RNAs homologous to a CACTA-type DNA transposon directly upstream of the nchanged . We confnchanged  [28]. Usozygotes . These d mutants  and rpd1rmr1 and rdr2 mutants  elements  known as Mu Killer (Muk) Muk facilitates heritable hypermethylation of MuDR elements Muk-induced repression Muk hairpin RNA is processed to 24 nt effector RNAs independent of RDR2 action Disparate roles for RDR2 have been shown in the establishment versus maintenance of repression at endogenous Muk-induced repression of MuDR. By crossing rmr1-1 homozygotes having both an active MuDR element and a mutable color allele (a1-mum2) to Muk homozygous plants that are also homozygous for either functional Rmr1 or the mutant rmr1-1 allele -primed cDNA, we detected little to no transcript for any of the LTRs, which is consistent with the observation that high copy number LTR retrotransposons are poorly represented in the polyadenylated RNA fraction CentA) indicating that, while these elements are transcribed, they are not polyadenylated  indicated that both sense and antisense orientations of each LTR RNA transcript were present in non-mutant B73. In rmr1 mutants both species of CRM transcript were reduced relative to non-mutant  on the CRM and Prem2/Ji transcripts. The qRT-PCR results  internal control. Interestingly the levels of CRM RNA were more reduced in rmr1 mutants as compared to Prem2/Ji , consistent with the existence of Prem2/Ji RNAs unaffected by RMR1 function. Both the CRM and Prem2/Ji transcripts detected are relatively low abundance, with CRM found at levels at least 60-fold lower than Aat transcripts and Prem2/Ji at levels at least 15-fold lower than Aat  by loss of RMR1 function as compared to the overall reduction of CRM RNAs detected in the random-primed cDNA. This led us to conclude that, in contrast to Prem2/Ji, the centromeric CRM retrotransposons are preferentially represented by antisense transcripts that are stabilized by RMR1 function.To quantify the loss of LTR RNA transcripts in an  results  verified Aat see  despite  mutants . We alsoArabidopsis in which levels of both the AtSN1 non-LTR retrotransposon transcript and transcripts from sequences flanking a solo-LTR were elevated in rdr2 mutants rmr1 mutants, we observed that both sense and antisense CRM transcripts were also reduced in rdr2 mutants  in rdr2 mutants relative to non-mutant siblings  mutants in a B73 genomic background equivalent to that of the rmr1 mutants analyzed, as LTR retrotransposon representation in 24 nt RNA populations in Arabidopsis is dependent on Pol IV function rmr1 and rdr2 mutants, the absence of RPD1 function correlated with an increase in LTR transcript abundance , though the level of Prem2/Ji transcripts still increased in the polyadenylated fraction. As Pol V transcripts were recently shown to lack polyadenylated tails Prem2/Ji and CRM polyadenylated transcripts is from RNA polymerase II. This is consistent to observations of Arabidopsis nrpe1 mutants in which loss of Pol V at specific loci was accompanied by a reciprocal recruitment of Pol II complex members We next looked at bundance . Furtherbundance . We quanbundance  and the siblings . In agreCRM and Prem2/Ji LTR RNA transcripts of both strand orientations are differentially affected in rpd1 mutants as compared to rmr1 mutants by performing strand-specific RT-PCR analogous to that carried out on rmr1 and rdr2 mutants  and non-mutant (n = 6) nuclei  nuclei . These rrmr1 mutants, while consistent with prior analysis of multiple Arabidopsis RdDM pathway mutants, are surprising for a genome dominated by repetitive sequences. However, recent genome-wide expression profiling of Arabidopsis RdDM mutants indicates that, even among genes proximal to small RNA generating sequences, normal expression patterns persist in all but a small fraction of genes rmr1 mutants relative to non-mutants. Interestingly, the small RNAs representing repetitive sequences found in intragenic regions or directly downstream of predicted maize genes  yielded normal seed set upon self pollination, whereas two lines derived from non-mutant F2 siblings (Rmr1-A632 homozygotes) yielded only 55% (13/22) phenotypically normal plants at the S5 stage. Nine of 24 plants from the two Rmr1-A632/Rmr1-A632 lines (3/9 and 6/13 off-types in the respective lines) were phenotypically abnormal. Four of 9 off-types were classified as “runts” (<∼1/3 of sibling height) and one of these had narrow leaf blades. None of these runts produced silking ears. Four plants had delayed silking relative to pollen shed; two of these plants produced tiny ears with no grains and two plants had normal sized ears with only a single grain each. One otherwise normal plant had vestigial apical leaves and no apical inflorescence. What was particularly intriguing about these observations is the uniformity of type in the homozygous rmr1-1 lines, as the appearance of phenotypically variable plants seen in the non-mutant lines is typical of inbreeding depression. Thus, while RMR1 appears dispensable for genome homeostasis, it is possible the RMR1 function may be responsible for some trans-generational behaviors of the epigenome.Most surprisingly from our pedigree analysis of seed set . At the Saccharomyces cerevisiae Snf2p Arabidopsis DRD1, and CLSY1 belong to a subfamily of Snf2 proteins defined by Rad54, an ATPase involved in homologous recombination (HR) via interactions with single-stranded and double-stranded DNA The Snf2 family of proteins that RMR1 belongs to encompasses a large group of functionally diverse proteins that are often referred to as “chromatin remodelers” based primarily on the functional analysis of Arabidopsis that Pol V, a related polymerase, actively transcribes intergenic regions, and that both Pol IV and V have Pol II-like holoenzyme compositions including some Pol II components themselves rdr2 mutant. The LTR retrotransposons analyzed here may be targets of Pol IV activity to the exclusion of Pol II even in the absence of RDR2, preventing generation of polyadenylated transcripts. Support for the effective targeting of Pol IV complex members independent of a functional RdDM pathway is found in the observation in Arabidopsis rdr2 mutants that Pol IV nuclear localizations are unaffected Prem2/Ji and CRM transcript levels in rpd1 mutants is likely due, in part, to the reciprocal gain of Pol II activity at Pol IV-targeted loci and the subsequent generation of transcripts that are no longer a substrate for RDR2 activity, and thus are not processed into small RNAs  mutant. Muk-induced repression is proposed to take place through a long hairpin transcript precursor, structures known to be the target of a viral defense pathway in ArabidopsisArabidopsis DRD1, but could potentially overlap or be fully analogous to the function of Arabidopsis CLSY1, which has similar effects on siRNA production We place RMR1 upstream of RDR2 activity and downstream of Pol IV based on the observation that RMR1 is necessary for the accumulation of sampled LTR RNA transcripts of both the sense and antisense orientations. As Rad54 proteins are known DNA-binding proteins rmr1 and rdr2 (mop1-1) mutants, while previous work had shown increase of Arabidopsis SINE element transcripts in rdr2 mutants with functional Pol IV Prem2/Ji and CRM elements in the genome from a large number of distinct contexts, and as such only gives us an average of cumulative effects of RdDM mutations on these elements, it is possible that specific elements could be differentially affected.It is curious that we were able to detect significant loss of non-polyadenylated LTR transcripts in rmr1 mutants argue against the direct requirement of small RNAs themselves for proper genome maintenance. This is particularly intriguing in maize as targets of the RdDM pathway have expanded in overall number and proximity to coding regions, and because maize Pol IV mutant plants have developmental defects rpd1 and rmr1 mutants could generate distinct phenotypic consequences. While rmr1 mutants may lack a majority of small RNAs, our results with Prem2/Ji and CRM transcripts suggest that Pol IV function might remain engaged at repetitive genomic loci. In this way genome dysfunction might only occur when the Pol IV holoenzyme is lost, leading to misregulation of silenced genomic regions by recruitment of Pol II. The loss of Pol IV may also deplete Pol II holoenzyme at regions normally transcribed by Pol II, leading to stochastic defects in gene regulation. This could be particularly detrimental in a genome where a large amount of repetitive sequence might act to significantly titrate out Pol II complexes in the absence of Pol IV.Our results with rmr1 mutants suggests that while small RNAs may not be required for normal development, they might have broad functions for out-crossing species such as maize that display regular and predictable differences in genome regulation depending on breeding strategies in ways that are not fully explained by genetic variation What remains an open question in the model put forth here and suggested elsewhere is the evolutionary significance of maintaining normal small RNA levels in the plant. This is particularly meaningful when viewed in light of the suggestion that Pol IV may function without other RdDM pathway members, or the recent finding that Pol V also has small RNA-independent functions in higher-order genomic organization rmr1, rpd1 (rmr6), and rdr2 (mop1) mutations are described previously rmr1-1 and rdr2 (mop1-1) small RNA, rdr2 (mop1-1) RT-PCR, and rmr1 morphological and rmr1 cytological analyses are as previously described rmr1 mutants and non-mutant plants were made using BC3F2rmr1-1 homozygotes (94% B73) derived from introgression of rmr1-1 into a color-converted B73 inbred line and non-mutant plants from the parental B73 line (97% B73). For rpd1 (rmr6), RT-PCR comparisons were made between homozygous mutants and non-mutant siblings from BC3F2 progeny (94% B73) derived from introgression of rmr6-1 into the same color-converted B73 inbred as mentioned above. For the inbreeding analysis in rmr1-1 and homozygous Rmr1-A632 recombinant inbred lines were established by single-seed descent from a specific A632-derived F2 progeny as previously described All rmr1-1 homozygotes and heterozygous siblings. The relative abundances for each biological replicate were calculated from the averages of the technical replicates for each sample, and these averages were subsequently averaged themselves to represent the 24 nt RNA abundances for each genotype with the values represented relative to a non-mutant abundance = 1.Small RNAs were enriched from total RNA extracted from 5 cm immature ear tissue and visualized following polyacrylamide gel electrophoresis (PAGE) as previously described Mu1 plasmid is as previously described All northern blots were carried out as previously described rmr1-1 materials were homozygous for the dominant A1 allele needed for full pigmentation in both plant and kernel tissues. To generate MuDR lines homozygous for the rmr1-1 allele, a single rmr1-1 homozygote was first crossed to a plant carrying both an active MuDR element at a reference position known as p1 and the a1-mum2 reporter allele 1 progeny grown from fully pigmented kernels were self-pollinated to recover spotted kernels ) that were complemented for all other necessary kernel color factors. F2 progeny plants derived from these spotted kernels were genotyped for rmr1 alleles as described rmr1-1 homozygotes were used to establish inbred lines via single seed descent for four generations, each time selecting spotted kernels from ears segregating both spotted and non-spotted (no MuDR) kernels. The specific plants used as pollen parents for the Muk crosses were confirmed to be heterozygous for MuDR (p1) via the ∼1∶1 segregation of spotted and non-spotted kernels upon testcrosses to a1-mum2/a1-mum2 plants  and subjected to Southern blot hybridization with a Mu1 radiolabelled probe as previously described Genomic DNA samples from homozygous mutants and heterozygous sibling plants were digested with alanine aminotransferase (Aat) cDNA was PCR amplified using previously described primers rmr1-1 and rdr2 (mop1-1) cDNA analysis, and 30 times for the rpd1 (rmr6-1) analysis. Strand-specific RT was carried out in the same fashion as the random-primed RT, except in the presence of 250 pmol of LTR-specific DNA oligonucleotides in the proper orientation, as well as DNA oligonucleotide primer specific to the Aat control RNA. PCR on strand-specific cDNA was carried out as described above.RNA was isolated from seedlings 4 days post-imbibition via standard Trizol (Invitrogen) purification. Oligo(dT)-primed cDNA was generated as previously described rmr1 mutant and non-mutant samples were calculated for CRM and Prem2/Ji from three technical replicates using the 2-ΔΔCT method T values for 1 ng of starting cDNA normalized to CT values of Aat. Quantifications of the strand-specific CRM transcripts were carried out similarly using independent biological samples and 2 technical replicates. Quantifications of CRM and Prem2 between rpd1 mutant and non-mutant siblings were carried out using three technical replicates and quantifications of CRM between rdr2 mutant and non-mutant siblings were carried out using two biological replicates. Levels of CRM and Prem2/Ji transcripts relative to Aat transcript abundance were calculated by generating a standard curve of Aat levels based on a dilution series of starting cDNA amounts from 5 ng to 0.2 ng, this calculation assumes equal efficiencies of amplification for the control Aat products and the experimental CRM and Prem2/Ji products.Real time RT-PCR was carried out on random primed cDNA generated as described above. All reactions were performed on an ABI 7300 real-time cycler (Applied Biosystems) using the DyNAmo HS SYBR Green qPCR kit (New England Biolabs) following the manufacturer's instructions. Relative transcript abundances between rpd1 (rmr6-1) mutants  enriched fraction and the flow-through. The Aat transcript was enriched >200-fold in both mutant and non-mutant samples relative to 45S in the poly(A) fractions  Onozuka R10 cellulase (Yakult Honsha), 1% (w/v) Macerozyme R10 (Yakult Honsha) as described Arabidopsis genome (TAIR7 genome release) using BLASTP. The resulting BLASTP top Arabidopsis HSP for each predicted maize protein was used to construct a dot-plot comparing the location of homologous maize-Arabidopsis gene pairs along the length of their corresponding chromosome using DAGCHAINER Arabidopsis synteny. The maize chromosome 9 contig did not appear to have any significant syntenic gene clusters with any Arabidopsis chromosome.Maize chromosome 1 and 9 sequence, and corresponding gene models are as previously described Arabidopsis and maize of the potentially syntenous regions identified in the visual dot-plot analysis  by a BLAST search. Those genes with significant homology to a repetitive element  were scored as having an attendant repetitive sequence upstream, downstream, or intragenic.Using an in-house Perl script, we generated comparative maps between analysis . Repetitanalysis  was idenFigure S1rmr1 mutants. (A) EtBr staining of PAGE-separated small RNA fractions from rdr2 mutants (−) and heterozygous siblings (+).  Small RNA northern blots hybridized with radiolabeled probes of various repetitive maize features and miR168 showing rdr2 mutants specifically lose 24 nt small RNAs corresponding to repetitive sequence.Plants deficient for RDR2 show analogous effects on small RNA populations as (0.32 MB TIF)Click here for additional data file.Figure S2MuDR functions. (A) Test cross progeny of an rmr1-1 homozygote with an active MuDR element (grey box) by a plant homozygous for the a1-mum2 reporter allele showing active MuDR (spotted kernels) segregates as expected from rmr1 mutants. (B) Cross of parental rmr1-1 homozygote from (A - grey box) to a Muk homozygote illustrating effective silencing of MuDR element. (C) Cross of parental rmr1-1 homozygote from (A- gray box) to an rmr1-1/rmr1-1 ; Muk plant showing MuDR remains active (spotted kernels) similar to (A).Representative ear progenies displaying active and silenced (0.57 MB TIF)Click here for additional data file.Figure S3Diagrams of LTRs assayed in this study. Schematics of the LTR retrotransposons  used in both RT- and qRT-PCR analysis with the region amplified by the primers used in this study underlined with an arrow. The direction of the arrow indicates the orientation of transcripts termed “sense” in the study while transcripts in the opposite orientation were termed “antisense.”(0.04 MB TIF)Click here for additional data file.Figure S4rdr2 material.  Comparison of of RT-PCR products recovered with strand-specific primers in the B73 inbred background (A) and the non-standard rdr2 mutant background (B). (C) Change in relative abundance (±2 s.e.m.) of CRM transcript in rdr2 mutants as compared to non-mutants by qRT-PCR.Strand-specific RT-PCR of (0.44 MB TIF)Click here for additional data file.Figure S5Aat. Enrichment of Aat, a polyadenylated Pol II-derived transcript, relative to maize 45S precursor transcript, which is non-polyadenylated, for the rpd1 mutant and non-mutant sibling samples used in qRT-PCR analysis assaying the enrichment of (2.74 MB TIF)Click here for additional data file.Figure S6Arabidopsis-maize homologous gene pairs. Dot plot mapping positions of homologous gene pairs identified by BLASTP searches for the Zea mays chromosome 1 contig compared to (A) Arabidopsis chromosome 1, (B) chromosome 2, (C) chromosome 4. Axis numbers indicate the position in the given chromosomal region and circled dots indicate the homologous gene pairs used to define the chromosomal regions referenced in Dot plot mapping positions of (0.17 MB TIF)Click here for additional data file.Figures S7Arabidopsis homologs identified in mop1-1 homozygotes. Small RNA sequences from the plus strand are above the x-axis and those from the minus stand are below the x-axis. Red bars indicate windows in which the relative number of small RNA hits exceeded the given scale. The repetitive sequence bar details areas of the gene region with similarity to known repetitive sequences identified by the Repbase CENSOR algorithm. DNA transposons are shown in yellow, LTR retrotransposons are shown in blue, and non-LTR retrotransposons in purple. (C) RT-PCR analysis of the putative homologs (with the exception of ZM_chr01_CG_01480 which gave no product) from the non-mutant B73 inbred (+) and rmr1 mutant (−) plants with Aat control.Gene structure, small RNA profile, and RT-PCR analysis of selected maize-(0.20 MB TIF)Click here for additional data file.Figures S8Arabidopsis homologs identified in Gene structure, small RNA profile, and RT-PCR analysis of selected maize-(3.48 MB TIF)Click here for additional data file.Figures S9Arabidopsis homologs identified in Gene structure, small RNA profile, and RT-PCR analysis of selected maize-(0.21 MB TIF)Click here for additional data file.Figure S10rmr1 mutants and non-mutants. (A) Comparison of flowering times and plant heights between rmr1-2 homozygotes (rmr1-2) and heterozygous siblings (+) (±1 s.e.m.). (B) Analogous measurements for sibling rmr1-3 genotypes.Flowering time and plant height between (0.05 MB TIF)Click here for additional data file.Figure S11rmr1-1 heterozygotes and (B) rmr1-1 homozygous mutants.UV light microscopy of DAPI-stained nuclei isolated from growing root tips. Comparison of (A) (2.00 MB TIF)Click here for additional data file.Table S1Zea mays (Zm) and Arabidopsis thaliana (At) chromosomal regions containing syntenous gene pairs.Relative gene and repetitive element content of (0.05 MB DOC)Click here for additional data file.Table S2rdr2 (mop1-1) mutants relative to the non-mutant genome that are homologous to the attendant repetitive sequence identified in Comparison of the relative number of small RNA sequence tags remaining in (0.03 MB DOC)Click here for additional data file.Table S3Probes and DNA oligonucleotide primers used in this study.(0.05 MB DOC)Click here for additional data file.Text S1Supplemental methods.(0.05 MB DOC)Click here for additional data file.