Mycobacterium smegmatis, and transcription start site (TSS) mapping and N-terminal peptide mass spectrometry in Mycobacterium tuberculosis, provide complementary, empirical datasets to examine the congruence of transcription and translation in the Mycobacterium genus. We find that nearly one-quarter of mycobacterial transcripts are leaderless, lacking a 5’ untranslated region (UTR) and Shine-Dalgarno ribosome-binding site. Our data indicate that leaderless translation is a major feature of mycobacterial genomes and is comparably robust to leadered initiation. Using translational reporters to systematically probe the cis-sequence requirements of leaderless translation initiation in mycobacteria, we find that an ATG or GTG at the mRNA 5’ end is both necessary and sufficient. This criterion, together with our ribosome occupancy data, suggests that mycobacteria encode hundreds of small, unannotated proteins at the 5’ ends of transcripts. The conservation of small proteins in both mycobacterial species tested suggests that some play important roles in mycobacterial physiology. Our translational-reporter system further indicates that mycobacterial leadered translation initiation requires a Shine Dalgarno site in the 5’ UTR and that ATG, GTG, TTG, and ATT codons can robustly initiate translation. Our combined approaches provide the first comprehensive view of mycobacterial gene structures and their non-canonical mechanisms of protein expression.RNA-seq technologies have provided significant insight into the transcription networks of mycobacteria. However, such studies provide no definitive information on the translational landscape. Here, we use a combination of high-throughput transcriptome and proteome-profiling approaches to more rigorously understand protein expression in two mycobacterial species. RNA-seq and ribosome profiling in  Mycobacterium smegmatis and Mycobacterium tuberculosis. We found that nearly one-quarter of mycobacterial transcripts are leaderless in mycobacterial species, thus indicating that ribosomes must recognize these mRNAs by a novel mechanism and suggesting that there are alternative modes of bacterial translation beyond the Escherichia coli paradigm. Our translational profiling showed that many mycobacterial proteins are mis-annotated, and also found many new genes encoding small proteins that had been previously overlooked, which are likely to play novel roles in diverse cellular processes. We also developed a new reporter system that provides mechanistic insights into translation initiation through deep sequencing. Our data show that leaderless translation is a robust process that is conserved in mycobacteria, that leaderless translation only requires that the mRNA begin with a start codon, and predict that mycobacteria encode hundreds of small proteins. This work will help us understand gene structure, genome organization and protein expression in bacteria, and how the translational machinery differs in different organisms.The current paradigm for bacterial translation is based on an mRNA that includes an untranslated leader sequence containing the ribosome-binding site upstream of the initiation codon. We applied genome-scale approaches to map the protein-coding regions in the genomes of  Escherichia coli. Canonical translation initiation in bacteria is a multistep process that begins with the binding of a small (30S) ribosomal subunit to a Shine-Dalgarno element in the 5’ UTR of an mRNA. The Shine-Dalgarno sequence is generally centered 8–9 nt upstream of the start codon and interacts with a complementary sequence in the 16S rRNA of the 30S ribosomal subunit to help position this ribosomal subunit [The mechanism of bacterial translation initiation has been the subject of intensive study in the model organism, Translation of genes embedded in polycistronic mRNAs can be coupled to translation of the respective upstream gene in a process known as re-initiation, if the downstream start and upstream stop codons are positioned close to one another. Once translation of the upstream gene has terminated, the ribosome scans until it finds a suitable start codon further downstream . Low levE. coli, and those that have are mostly of mobile DNA origin, including from λ and P2 phage, and from Tn1721 [E. coli, suggest that leaderless gene structures may not be so unusual [E. coli as a model system, despite the relative paucity of leaderless genes in this species. It is likely that fundamental differences in translation underlie robust leaderless translation in those species with pervasive leaderless gene structures.“Leaderless” transcripts lack a 5’ UTR and Shine-Dalgarno sequence. In such cases, 70S ribosomes must bind directly to the first nucleotide of the mRNAs to initiate translation. Few leaderless genes have been identified and analyzed in m Tn1721 . More re unusual –17. Lead unusual –22 and i unusual –25. Thes unusual , 21, 26.E. coli than leadered and early studies focused on identifying factors that contributed to this difference. Leaderless transcripts are likely recognized by 70S ribosomes, rather than the 30S subunit [E. coli studies, leadered and leaderless translation processes are functionally distinct.Leaderless translation is poorly understood, compared with canonical leadered translation. Early studies established the absolute requirement for a 5’ ATG (AUG in the mRNA) for translation –29. Lead subunit . 70S bin subunit , whereas subunit , 34, an  subunit , 35–37.  subunit . MazF clcis-regulating downstream ORFs, short ORFs may encode small proteins with trans activities. Regulatory functions have been attributed to encoded small proteins themselves [In contrast to bacteria, eukaryotes utilize ribosome-scanning translation initiation mechanisms. Small open reading frames are frequently found in the 5’ UTRs of eukaryotic genes, and these upstream ORFs (uORFs) can attenuate translation of the annotated downstream ORF –41. Lessemselves  in respoemselves , global emselves , and ATPemselves .Mycobacterium includes major pathogens as well as non-pathogens. There have been very few studies of translation initiation mechanisms in mycobacteria, although a recent study inferred widespread leaderless translation in Mycobacterium tuberculosis by mapping transcription start sites (TSS) onto an annotated reference genome[Mycobacterium smegmatis. In parallel, we use TSS mapping coupled with mass spectrometry detection of protein N-termini to map the sites of initiation of the transcriptome and proteome of M. tuberculosis. These complementary approaches in related species reveal widespread non-canonical translation initiation, including leaderless translation and the use of alternative start codons. Lastly, we developed a next-generation sequencing-based translational reporter system, which allows a controlled assessment of the requirements of translation initiation in mycobacteria. This assay demonstrated that the requirements for leaderless and leadered translation are distinct, and supports the use of alternative start codons for leadered translation. Thus, our collective data provide the first systems-level description of key translational parameters in mycobacteria, a genus that exhibits significant endogenous leaderless translation.The genus ce genome. Here, wM. tuberculosis relied on annotation pipeline predictions [M. smegmatis without reliance on annotations. As each genome-wide approach has strengths and weaknesses, combining independent criteria or datasets provides higher confidence results. In this study, we used standard growth conditions including rich media and harvesting RNA from cells at mid-exponential phase to profile those genes most relevant to common experimental conditions. Mapped read depth tended to be greatest near the 5’ ends of the genes, facilitating our search for TSSs and translation initiation sites as the leading edge of stacked sequence reads from RNA-seq and ribosome profiling, respectively.The initial report of leaderless translation in dictions , which iM. smegmatis that were sufficiently expressed. We noted that many (206) upstream boundaries of mapped RNA-seq reads aligned perfectly with a ribosome profiling boundary, and also coincided with a putative ATG or GTG  initiation codon , combining for a chance alignment genome-wide at 0.0087—far below the 206 we observed. Therefore, RTG codon occurrences are enriched at the 5’ boundaries of transcripts.Focusing on the upstream boundaries of regions of sequencing signal in either the total RNA or ribosome profiling datasets, we identified putative TSSs and translation initiation sites for genes in on codon . Of theson codon . The aliM. smegmatis lends empirical support for their presence in M. tuberculosis [Our identification of abundant leaderless mRNAs in rculosis , as wellM. smegmatis and M. tuberculosis transcript mapping data in its entirety can be interactively viewed by links found at <http://www.wadsworth.org/research/scientific-resources/interactive-genomics/>, and run directly through common internet browsers.Leaderless transcripts generate distinctive 5’ read boundary profiles; their ribosomal footprints characteristically begin abruptly at the initiation codon. In addition, mRNAs with high ribosome occupancy can be enriched relative to their corresponding RNA-seq read depth in paired libraries that are otherwise comparable. Therefore, while some transcripts were not expressed highly enough to meet our read depth-mapping threshold in RNA-seq, ribosome isolation enriched those mRNAs enough to surpass the mapping threshold. Omitting the criterion of a coincident RNA-seq boundary from our analysis  identified 762 candidate leaderless transcript boundaries. While we expect more false positives in this list of 762 transcripts, 457 (60.0%) matched a predicted annotated start, which was very similar to the 63% observed for the most stringent list, conferring confidence to those candidate initiation sites generated by this approach. Of the remaining 305 candidate leaderless RTGs, 175 (23%) were in-frame with annotated genes, predicting new upstream (99 instances) or downstream (76 instances) start codons for those ORFs . The 130Leadered transcripts, however, generate a range of ribosomal footprints that begin in the 5’ UTR, spanning a putative Shine-Dalgarno site and the initiation codon . The ranConservatively bracketing the second broad peak to include spacing of 20 to 30 nt of separation between the footprint boundary and the next RTG, identified 731 candidate leadered initiation RTG codons. Of these, 423 (58%) mapped exactly to the start of an annotated gene, validating the predictive value of the leadered transcript dataset. Other RTG codons within this 20 to 30 nt footprint window were in-frame with the annotated ORFs, but were either upstream (45) or downstream (133) of the predicted start codon, indicating probable mis-assigned start codons. The remaining 130 RTG triplets within this ribosome footprint range could represent either initiation codons for new unannotated ORFs (as for the leaderless RTGs), or background internal RNA fragments that fortuitously include an RTG sequence.M. tuberculosis, to determine whether non-canonical translation initiation mechanisms are conserved throughout the genus. We used a modified RNA-seq approach to map TSSs genome-wide, identifying 4,978 TSSs representing 2254 genes  and 208 (19%) extended or shortened the annotated reading frames of same-frame leaderless RTGs that were upstream or downstream of the predicted annotated initiation codon, respectively. These novel leaderless TSSs would be missed in studies that rely on the accuracy of annotated genomes.We also took an independent approach in the related pathogenic species, 54 genes . We foun54 genes  of theseM. tuberculosis [M. smegmatis. We independently mapped sites of translation initiation in M. tuberculosis by a direct mass spectrometry (MS) approach focused on identifying the spectral signatures of those peptides with N-termini created by translation initiation, rather than tryptic digestion. We performed LC-MS/MS on tryptic digests of total protein from M. tuberculosis lysates and specifically searched for N-terminal peptides within annotated ORFs. ORFs that could be extended by conceptual translation to candidate initiation codons upstream were included in the search. To be confident of our N-terminal assignments, we then stringently limited our list to a very high-confidence subset of N-terminal peptides: those with acetylated N-terminal residues and those with intact methionines present at non-ATG codons. 211 protein N-termini met at least one of these criteria, 144 of which matched annotated starts (M. tuberculosis confirmed translation initiation for 51 peptides (24%) that coincided with an RTG at the +1 position of the transcript . Even though the reduced sensitivity (compared to our transcriptomic methods) of our N-terminal proteomic approach prevented a fully comprehensive survey of translation initiation sites, it provided independent, empirical evidence that leaderless mRNAs in M. tuberculosis are translated from the +1 nucleotide.Sites of translation initiation have been assumed from genome annotation predictions in rculosis , or deted starts . For leaanscript . Thirty-M. tuberculosis showed the expected discernable enrichment for A and T nucleotides that mark the -10 hexamer for sigma factor binding  in  binding . Lookingboundary  showed tboundary . Slight  or a new start either upstream or downstream of the predicted start (54 instances). Of these, 114 of had orthologs in M. tuberculosis  of M. smegmatis leaderless genes have expressed leaderless orthologs in M. tuberculosis. Orthologs with conserved leaderless initiation codons highlight the need for empirical reannotation of these genomes , and the +1 nucleotide identity could influence promoter strength as it does for T7 RNA polymerase [In itiation ; none ofnstructs ; transcrlymerase . Thus, tzeor) to allow selection of sequences that could successfully initiate translation, which could then be identified by PCR amplification followed by next generation sequencing  and at the annotated leadered start codon of the or gene . Leaderlor gene . ImportaWe then repeated the assay in the context of a consensus Shine-Dalgarno sequence. The zeocin resistant pool now showed strong enrichment for specific sequences at both the leaderless and leadered start codons . ATG andWe modified the unbiased zeocin resistance selection approach to define sequences suitable for ribosome binding in mycobacteria. A contiguous block of 6 nt was randomized upstream of a leadered ATG initiation codon, and constructs providing zeocin resistance were collected and sequenced . We founWe further leveraged our viability reporter system to determine whether any additional sequences support translation of leaderless transcripts near the ATG or GTG codon at the +1 position. Six contiguous random nucleotides were embedded immediately downstream (positions +4 through +9) of a leaderless ATG triplet . All traM. smegmatis, and our viability reporter assays, indicated that an RTG triplet at the TSS is necessary and sufficient to direct leaderless translation initiation. Therefore, leaderless +1 RTGs not initiating translation of annotated reading frames are initiating translation of novel ORFs , identified 22 unannotated ORFs . Our data suggest two cis mechanisms by which the ORF, rather than the encoded small protein, may regulate the downstream genes of the polycistronic mRNA (see below).Our ribosome profiling in vel ORFs . Our mosted ORFs . We alsoted ORFs . While tThe ORFs encoding small proteins can be categorized with respect to the position of their stop codon relative to the initiation codon of the adjacent annotated gene . The firM. tuberculosis using an entirely different experimental approach. Our TSS data indicated that 317 (28.8%) of the leaderless RTG codons initiated novel ORFs, and 197 of these are between 5–50 amino acids suggesting that M. tuberculosis encodes hundreds of undocumented small proteins . Our data indicate that these structures are significantly overrepresented in mycobacteria  will be translated as a leaderless mRNA in mycobacteria. Strikingly, no other codon initiates leaderless translation, in contrast to leadered translation, which can initiate with a wide variety of codons, including rare start codons such as TTG and ATT. In addition to Shine-Dalgarno dependence, differing start codon requirements indicate fundamental mechanistic differences between leadered and leaderless translation initiation. However, there is currently insufficient understanding of leaderless translation to determine why this difference exists.We developed novel reporters to begin to address mechanistic hypotheses about M. smegmatis are frequently leaderless in M. tuberculosis, in spite of sequence variation  near the initiating RTG codon. We observe robust leaderless initiation regardless of the reporter context, none of which have mycobacterial origins that could contain leaderless support elements. Varied contexts and disparate assays consistently produce robust leaderless translation efficiencies in mycobacteria. Thus, an ATG or GTG at the TSS is the only discernable criterion for translation initiation at that same site.The combination of multiple, independent observations strongly indicate that a +1 RTG codon is both necessary and sufficient for leaderless translation initiation. We did not identify any sequences beyond the start codon that were enriched in leaderless genes, either in mycobacterial genomes or by our viability reporter assays, suggesting that the RTG start codon is not supported by an enhancing downstream box . LeaderlE. coli have indicated that ATG was optimal for leaderless initiation, with <10% activity for GTG [E. coli is weak (10%) compared to initiation from a leadered transcript [M. smegmatis. Together, these observations indicate that recognition and translational initiation of leaderless mRNAs in M. smegmatis occurs by a distinctly different mechanism than that described for E. coli. Overall leaderless gene expression appears to be controlled by a balance of promoter activity, mRNA stability, and protein turnover; leadered gene expression has an additional level of control provided by features of the 5’ UTR, including the Shine-Dalgarno sequence and RNA secondary structure. We speculate that this additional level of expression modulation may have provided the evolutionary impetus for leadered gene structures.Previous studies in  for GTG . Moreoveanscript , again cM. tuberculosis? Substituting chemically similar but translationally inert nucleotides into the second and third positions of the RTG triplet, we see that they are found at TSSs much less often: RCG is found at 270 (5.4%) of M. tuberculosis TSSs, and RTA at 121 (2.4%). Clearly, the over-representation of RTG at TSSs  indicates that there is a strong evolutionary selection for RTGs at the TSS in mycobacteria.Analyses of TSS mapping data indicate that RNA polymerase exhibits context bias in selecting a TSS. For example, a cytosine at the -1 is preferred, followed by a pyrimidine at the +2 . Could RM. tuberculosis transcriptional start sites provides some experimental assessment of the accuracy of this broader definition. While N-termini were identified for 51 of 1098 (4.7%) leaderless +1 TSSs, only 4 of 558 (0.7%) candidate RTG codons from +2 to +5 had associated N-termini  (We conservatively defined leaderless genes as those that have an RTG beginning at the first (+1) nucleotide of their corresponding transcript. Leaderless genes have also been more broadly defined as those having a potential initiation codon from +1 through +5 , with th-termini . Many faed (558) . IncludiM. smegmatis, and presumably M. tuberculosis, than in E. coli. The reason for this disparity is unclear, although there are many differences in ribosomal proteins between mycobacteria and E. coli [E. coli as a model system. As illustrated in our genomic landscape profiles, the mutually exclusive presence of a -10 hexamer or a Shine-Dalgarno ribosome-binding site upstream of the initiation codon can distinguish leaderless from leadered genes. Our data suggest that other species with a high frequency of predicted leaderless gene structures [E. coli.Leaderless translation is far more efficient in  E. coli . Importaructures , 22 are cis elements that support translation initiation clearly show that a Shine-Dalgarno sequence is required for efficient leadered initiation. The purine-rich consensus of the recovered zeocin-resistant constructs agreed well with the canonical motif defined in E. coli [M. smegmatis , suggesting that these small protein singletons are not cis-regulators. It is unlikely that every member of the mycobacterial small proteome has an individual function, but clearly some of them bear hallmarks of functional features. Small protein ORFs that are part of an operon may function in the pathway encoded by the trailing genes of that operon. Expanded study of the emerging small proteome will help to identify the likely candidates, determine their functional roles, and evaluate their collective influence on the phenotype or phenotypic variation of the bacteria.The precedent and the presence of potential an operon, 52–54. We focus on small proteins encoded by leaderless transcripts because of the abundant support for their presence in both mycobacterial species analyzed here. However, as leadered initiation of annotated genes in mycobacteria still outnumber leaderless annotated genes by at least two to one, it is reasonable to speculate that leadered codons will initiate translation of small proteins at comparable rates. Therefore, the small proteome estimates derived solely from leaderless mRNAs under standard rich media growth conditions, as presented here, are conservative underestimates.E. coli. Further, our data may help improve current genome annotation pipelines to more accurately predict leaderless gene structures, transcription and translation isoforms, and translation initiation sites in bacteria. Moreover, we anticipate that genome-scale approaches combining ribosome profiling, TSS, and LC-MS/MS will uncover similar phenomena in diverse bacterial species, challenging long-held paradigms of translation initiation in bacteria.In summary, we have identified widespread, conserved, non-canonical translation initiation in mycobacteria. Abundant leaderless translation initiation, encoded small proteins, and coupled linkages suggest translation mechanisms in mycobacteria are likely to fundamentally differ from those modeled in 2155 strain of M. smegmatis was grown in Middlebrook 7H9 broth supplemented with ADC and 0.05% Tween 80 with shaking at 230 RPM at 37°C to an OD600 of ~1.0. Mycobacterium tuberculosis (strain H37Rv) was cultured in Middlebrook 7H9 supplemented with OADC, 0.05% Tween 80 and 0.2% glycerol to an OD600 of 0.8–1.0 for transcriptomics experiments, and the same strain was cultured as described in [The mcM. smegmatis culture, and grown at 37°C to an OD600 of ~1.0. Chloramphenicol was added to 100 μg/ml 2 minutes before harvesting cells to stabilize the mRNA-associated ribosomes. Cells were harvested by rapid filtration using a 500 ml 0.45 μm PES filter system (Celltreat) and flash frozen in liquid nitrogen together with 0.7 ml lysis buffer [Extracts were prepared as described  with mins buffer . The froThe pulverized cell powder was extracted with acid phenol and chloroform followed by isopropanol precipitation . 16S andRibosome profiling was performed as described . Briefly2155 reference sequence (GenBank CP000480.1).Both ribosomal footprints and the enriched mRNAs were converted into cDNA libraries as described , 57 withRaw read counts for both RNAseq and RiboSeq replicates  were addM. smegmatis was generated from the overlap of RTGs at RNA-seq boundaries (633) and ribosome profiling boundaries (1362) for 498 total. Mapped reads from RNA-seq and ribosome profiling were also visualized in a SignalMap browser (Nimblegen), with annotations provided by the J. Craig Venter Institute (JCVI) and PathoSystems Resource Integration Center (PATRIC).To reduce the false-positive rate with any single dataset, independent datasets were often combined to generate a working list of high-confidence calls. The high-confidence leaderless transcript dataset in Biological replicate cultures were grown to an optical density of 1 in roller bottles and inactivated with RNAlater (Ambion) prior to pelleting and RNA extraction. Pellets from 18 ml of culture each disrupted in 1 mL Trizol (Life Technologies) in Lysing Matrix B tubes (MP) in a FastPrep-24 (MP) using two cycles of 30–45 seconds at 6.5 m/sec. 300 μL chloroform was added, samples were centrifuged for 15 minutes at 4°C, supernatants were mixed with equal volumes of isopropanol, and the resulting samples were incubated for 1 hour at -20°C before centrifugation for 10 minutes at 4°C. Pellets were washed with 75% ethanol, resuspended in water, treated with DNase Turbo (Ambion) and purified by RNeasy (Qiagen) as directed by the manufacturer. RNA samples were subject to two consecutive rounds of ribosomal RNA depletion using a MICROBExpress kit (Ambion) as directed by the manufacturer.GAUCU; normal font indicates deoxyribonucleotides and italics indicate ribonucleotides), denatured at 65°C. for 10 minutes, and cooled in an ice-water bath. Three μL 10X T4 RNA ligase buffer (New England Biolabs), 1 μL RNaseOUT, 10 μL 50% PEG8000, 3 μL RNaseOUT, 10 μL of 10 mM ATP, 3 μL DMSO, and 1 μL T4 RNA ligase I (New England Biolabs) were added and reactions incubated 18 hours at 20°C. Seventy μL water was added and samples were purified by RNeasy (Qiagen) and eluted in 126 μL water. Samples were sheared in a Covaris sonicator in AFA MicroTubes (Covaris) as follows: exposure time, 180 seconds; duty cycle, 10%; intensity, 5; cycles/burst, 200. One μL each Tris pH 7.5, 100 mM DTT, and RNaseOUT (Life Technologies) were added and samples concentrated to 11.25 μL. One μL of 2.2 μg/μL SSS397  was added, samples were incubated at 65°C for 10 minutes and cooled in an ice-water bath. Four μL 5X first-strand buffer (Life Technologies), 1 μL dNTP mix containing 10 mM each dNTP, 0.5 μL RNaseOUT (Life Technologies), 0.25 μL of 1 mg/mL actinomycin D, 1 μL 100 mM DTT, and 1 μL Superscript III (Life Technologies) were added and reactions incubated 18 hours at 42°C. RNA was degraded by treatment with 10 μL each 1 N NaOH and 500 mM EDTA at 65°C. for 15 minutes, 25 μL 1 M Tris pH 7.5 was added, and cDNA was purified by MinElute kit (Qiagen) and eluted in 60 μL water.Transcription start sites were mapped as described in  with modTo add the remaining adapter sequences, samples were subject to PCR as follows: 10 μL 5X HF buffer (Finnzymes), 2.5 μL of 10 μM oligo SSS398 (AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTC), 2.5 μL of 10 μM reverse oligo , 20 μL 5 M betaine, 0.5 μL Phusion polymerase (Finnzymes), 0.4 μL dNTP mix containing 25 mM each dNTP, and 14.1 μL purified cDNA from the previous step. Thermal cycler settings: 1 cycle of 98°C for 3 minutes, 8 cycles of 98°C for 80 seconds, 60°C for 30 seconds, and 72°C for 30 seconds, 1 cycle of 72°C for 5 minutes. Reaction volumes were set to 100 μL on the thermal cycler to increase ramp time . Three rThree reactions were performed for each sample. Products were purified twice using Ampure XP beads (Agencourt) with a beads:sample ratio of 1.8 and an elution of 60 μL water.RNA-seq expression libraries were made from the same samples used for 5’-end mapping. 1 μg of MICROBExpress-treated RNA from each biological replicate was sheared by a Covaris sonicator as follows: exposure time, 180 seconds; duty cycle, 10%; intensity, 5; cycles/burst, 200. Samples were concentrated by vacuum centrifugation and cDNA was synthesized by adding 3 μg of random primers (Life Technologies), incubating at 70°C for 10 minutes and snap-cooling in an ice water bath, adding 4 μL 5X first-strand buffer (Life Technologies), 1 μL dNTP mix containing 10 mM each dNTP, 0.5 μL RNaseOUT (Life Technologies), 0.5 μL of 1 mg/mL actinomycin D, 1 μL 100 mM DTT, and 1 μL Superscript III (Life Technologies) and incubating overnight at 42°C. RNA was degraded and cDNA purified as described above for 5’ end mapping libraries. Each first-strand cDNA sample was divided into 8 replicate second-strand synthesis reactions. Approximately 100 ng cDNA was mixed with 3 μg of random primers (Life Technologies) and 2 μL 100 mM Tris pH 7.5, incubated at 95°C for 3 minutes, cooled rapidly to 50°C, and then cooled from 50°C to 4°C at a rate of -0.4°C/second. The following were added before an overnight incubation at 16°C: 8 μL NEBNext Second Strand Synthesis (dNTP-free) Reaction Buffer, 1.6 μL dNTP mix containing 10 mM each dATP, dCTP, dGTP, and dUTP, 4 μL NEBNext Second Strand Synthesis enzyme mix, and water to a final volume of 80 μL. Reactions were purified with MinElute columns (Qiagen). 1 μg of purified second-strand synthesis reaction was then subject to end repair, A-tailing, and adapter ligation using a TruSeq DNA Sample Preparation Kit (Illumina) according to the manufacturer’s instructions. Following the ligation and subsequent clean-up steps, the entire product was run on a 2% agarose gel and the region between approximately 250 and 600 bp was excised and extracted with a Qiagen gel extraction kit. Each sample was divided into 4 reactions containing approximately 80 ng DNA, 1 μL 100 mM Tris pH 7.5, and 2 μL USER enzyme mix (NEB) and incubated at 37°C for 30 minutes. The following were added for PCR: 10 μL 5X HF buffer (Finnzymes), 5 μL primer mix from Illumina TruSeq kit, 0.4 μL dNTP mix that contains 25 mM each dNTP, 20 μL 5 M betaine, and 0.5 μL Phusion polymerase (Finnzymes). Thermal cycler conditions were as follows: 1 cycle of 98°C. for 3 minutes, 10 cycles of 98°C for 1 minute, 60°C for 30 seconds, and 72°C for 30 seconds, 1 cycle of 72°C for 5 minutes. Reaction volumes were set to 100 μL on the thermal cycler to increase ramp time .Duplicate reactions were combined and purified twice with Ampure XP beads (Agencourt) according to the manufacturer’s instructions. Libraries were sequenced on an Illumina Genome Analyzer in a paired-end run producing 56 nt reads.M. tuberculosis H37Rv genome version NC_000962. The 1st base of “Read 1”  was extracted to determine the number of RNA 5’ ends mapped to each genome coordinate. Zero values were replaced by 0.5. To identify above-background peaks in 5’ end coverage, the mean coverage at each coordinate in the two biological replicate “converted” libraries was averaged and the ratios of “1st nt” coverage at each coordinate relative to the positions 10 nt upstream and 10 nt downstream were determined. Approximately 22,000 peaks were identified where at least one of the two ratios was over 25. These peaks in 5’ end coverage were subject to the following filters: (1) peaks with a mean “converted” library coverage under 20 were removed; and (2) the ratio of mean “converted” library “1st nt” coverage to mean RNA-seq expression library coverage in the 200 nt region upstream of the “1st nt” peak was determined, and only peaks with ratios of at least 0.7 were retained.Ssaha2 was used to map reads to st nt” coverage in the replicate libraries was summed and the ratio in the converted/non-converted libraries was determined. The distribution of ratios was bimodal, and Gaussian mixture modeling was used to estimate the means and standard deviations for two skewed normal distributions . RNA 5' ends with ratios greater than 1.74 had a cumulative probability of ≤0.01 of belonging to the processed 5’ end population (after adjusting for multiple comparisons by the Benjamini-Hochberg procedure) and were therefore designated transcription start sites (TSSs). Because transcriptional initiation is imprecise, the 6,900 statistically significant TSSs were filtered to remove all but the single TSS with the highest converted-library coverage in each 11 nt window. 4,978 TSSs passed this filter and are included in For each filtered RNA 5’ end, the “1Whole-cell protein lysates were prepared as described in . PelletelacZ gene by generating translational fusions. Briefly, oligonucleotides were synthesized with candidate initiation codons  at either the leadered or leaderless positions. A well-characterized E. coli derived promoter with a mapped +1 transcription start site was used to drive expression [lacZ reporter using 15-nt recombination arms in the promoter region and lacZ ORF by InFusion (Clontech). E. coli cultures were grown in LB supplemented with hygromycin, and M. smegmatis in 7H9 supplemented with Tween 80 and hygromycin. Cultures were expanded, their density determined by OD600, and lysed crude extracts were prepared and β-galactosidase activities measured by ONPG conversion and reading at OD420. Activities were calculated in Miller Units, and displayed as percentages relative to a leadered ATG control construct.Specific codons were tested for their ability to initiate translation of the pression . Putativpression —substitulacZ reporter. The same basic oligonucleotide design described for lacZ was modified to accommodate the zeor gene overlap for InFusion cloning. Clusters of nucleotides of each oligo were specified for functionality  or unspecified with random nucleotides to allow subsequent selection. Duplex DNAs were created by a single round of bidirectional primer extension and the library was created by InFusion cloning. Hygromycin-resistant E. coli colonies  were collected and a plasmid library was created for electroporation into M. smegmatis. Hygromycin-resistant M. smegmatis colonies  were scraped and grown under zeocin (100 μg/ml) selection in TSA + 0.05% Tween 80. Plasmids were purified with aliquots from the Hyg-resistant and Zeo-resistant pools, and these were used as templates for PCR amplification of the cloned leader segments for amplicon-based next generation sequencing (Ion Torrent). Equivalent amounts of the barcoded amplicons were pooled and sequenced on an Ion 318 chip . Sequence reads were aligned, trimmed, and the sequences at the randomized positions were compiled. Recovered sequences are shown as log10 converted heat maps of every possible codon, or as sequence logos for supporting elements. The enrichment of all codon combinations that contain at least one active initiation codon, with the notable exception of stop codons at the leadered position, indicates that clonal jackpot artifacts are not a major problem.A zeocin-resistance gene reporter was created to allow expression by translational fusion, as for the M. tuberculosis transcripts were identified that initiate small ORFs of 5–50 amino acids. The stop codons of these small ORFs were mapped relative to the annotated start of the next downstream ORF, and 23 were found to have coupled architectures (RTGA) at the junction of the two ORFs. To determine whether 23 of 220 represented an enriched population, 1000 random sites in the genome were considered arbitrary start sites for ORFs that were similarly analyzed. Of the 1000 randomly identified in silico ORFs, 32 were coupled to a downstream ORF. The enrichment of 23/220 to 32/1000 was determined to be significant .Two hundred and twenty leaderless (begin with an RTG) M. smegmatis RNA-seq and Ribo-seq data can be found at the European Nucleotide Archive <https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-2929/>. The M. tuberculosis RNA-seq and the TSS data have been submitted to GEO under the accession number GSE62152. The Mass Spec data used for N-terminal peptide identification have been submitted to MassIVE, ID number MSV000079012, password 1tuberculosis. The data are also posted in the form of mapped sequence reads , and viewed at http://www.wadsworth.org/research/scientific-resources/interactive-genomics/.The primary sequence data have been deposited in public repositories. The S1 Fig(A) Leaderless RTGs often initiate an annotated ORF at the annotated initiation codon. The RTG codon may specify an in-frame, upstream start that will add residues (gray) to the N-terminus of the predicted protein. Alternatively, it may initiate downstream of the annotated start codon and will omit residues from the predicted N-terminus. The annotated stop codon is unchanged. (B) RTG codons not initiating an annotated reading specify novel, unannotated, ORFs. These novel ORFs represent the first gene of this leaderless operon transcript, and frequently predict small proteins (sp) of under 50 amino acids. These novel ORFs terminate upstream of the predicted annotated start downstream (uORF), or they overlap in the -1 frame via a coupled tetramer, or extend into the annotated gene, utilizing a different frame.(PDF)Click here for additional data file.S2 FigEnrichments of RTG codons were found at the boundary (leaderless) and in the distances surrounding 24 nt of separation between the leading edge of the footprint and a candidate RTG codon (leadered). The observed twin peaks profile would be expected from populations of 70S ribosomes poised over either leaderless or leadered translation initiation RTG codons.(PDF)Click here for additional data file.S3 Fighttp://meme.nbcr.net/meme/tools/meme>. The two motifs with significant scores are pictured. Therefore, approximately one-half of the candidate leadered RTGs identified by ribosome profiling have an upstream sequence resembling a consensus Shine-Dalgarno sequence (AGGAGG), with the upper motif conforming to the Shine-Dalgarno core, and the lower motif representing a possible degenerate Shine-Dalgarno. The remaining candidate 5’ UTRs either had sequences that were too diverged from the canonical SD-like core element shared by the group above for inclusion, or they represent RNA fragments where the candidate initiating RTG is not a codon, or is internal to the transcript and is not a site of initiation.The 19 nt upstream of 731 candidate RTG codons 20–30 nt from a ribosome footprint boundary were analyzed for sub-sequence enrichment <(PDF)Click here for additional data file.S4 FigM. tuberculosis gene, Rv2122c, has an empirically determined transcription start site 18 nucleotides into the annotated open reading frame. (B) The M. smegmatis ortholog of Rv2122c, Msmeg_4181, also has RNA-seq and ribosome footprint boundaries beginning 18 nucleotides into the same predicted open reading frame. (C) Nucleotide alignment of the annotated ORFs with 20 additional nucleotides of 5’ sequence. The green outlined box frames the JCVI annotated initiation codon for which there is no supporting evidence (note that the ORF predicted by PATRIC for M. smegmatis is an ATG at +12). TSS, RNA-seq, and ribosome footprinting data are all consistent with transcription and translation initiating with the green shaded GTG codon at +18. The conserved -10 promoter nucleotides and the preferred -1 cytosine are shaded in blue. The TGA stop codon (unchanged) is in a red-shaded box.Rv2122c and Msmeg_4181 provide an example of phylogenetically corroborated mis-annotation. (A) The (PDF)Click here for additional data file.S5 FigPotential initiating leaderless RTG codons were mapped by position relative to the transcription start site (TSS) in M. tuberculosis . The distribution of RTGs is heavily weighted to the +1 site (left most bar). The number of N-termini that map to each position is also shown . The percentage of RTGs that are experimentally supported  is shown above each N-terminal tally.(PDF)Click here for additional data file.S6 FigBoth upstream and downstream ORFs showed the expected GC codon bias. The wobble positions of the upstream gene reflect the Shine-Dalgarno consensus sequence (black box), suggesting the coexistence of coupling and canonical translation initiation at these junctions.(PDF)Click here for additional data file.S7 FigM. smegmatis transcriptome datasets were generated in duplicate for both the RNA-seq and ribosome profiling. Compiled read counts from genes in each dataset plotted on log axes show the highly correlative line of identity typical of genome scale studies. Read counts for a given gene in each experiment were normalized for gene length , converted to log scale, and plotted as shown. Poorly expressed genes averaging a read depth of less than 1 have negative log conversions. RNA-seq (A) and ribosome profiling (B) replicates are shown.(PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.


Heterochromatin protein 1 (HP1) is a central factor in establishing and maintaining the heterochromatin state. As consequence of playing a structural role in heterochromatin, HP1 proteins can have both an activating as well as repressive function in gene expression. Here we probe how oligomerisation of the HP1-α isoform modulates interaction with chromatin, by spatially resolved fluorescence correlation spectroscopy (FCS). We find from fluctuation analysis of HP1-α dynamics that this isoform exists as a dimer around the periphery of heterochromatin foci and these foci locally rotate with characteristic turn rates that range from 5–100ms. From inhibition of HP1-α homo-oligomerization we find the slow turn rates (20–100 ms) are dimer dependent. From treatment with drugs that disrupt or promote chromatin compaction, we find that HP1-α dimers spatially redistribute to favor fast (5–10 ms) or slow (20–100 ms) turn rates. Collectively our results demonstrate HP1-α oligomerization is critical to the maintenance of heterochromatin and the tunable dynamics of this HP1 isoform. More in detail, we preliminarily probed, for the first time, the actual existence and precise localization of HP1α homo-dimers in the nuclei of live cells by the Number and Brightness (N&B) analysisIn previous works we measured chromatin dynamics apparent = ε + 1) in each pixel of the image into a brightness map (background = 1), the molecular brightness of monomeric EGFP is thus 0.3 counts/dwelltime/s. From this value we can extrapolate that a HP1-α dimer would have an apparent brightness of 1.60 (given that Bdimer = (2 × 0.3) = 0.6), a HP1-α trimer would have an apparent brightness of 1.90 (given that Btrimer = (3 × 0.3) = 0.9) and so on.Here we use NIH3T3 cells transiently transfected with HP1α-EGFP and stained with Hoechst 33342 (as a reference of DNA) to measure the spatiotemporal regulation of HP1-α oligomerization within the nuclear compartment and how this modulates HP1-α dynamics. To investigate HP1-α oligomerization we use the well-established N&B approachness map , we founin vitro study that reported HP1-α dimers to induce the nucleation of a higher order chromatin structure that is incompatible with transcription. To prove that the detected increase of molecular brightness observed at the periphery of heterochromatin foci is in fact due to HP1-α-EGFP oligomerization and not solely HP1-α binding interaction, we then performed the same type of experiment in a cell transiently transfected with HP1-α-I165E-EGFP . In both instances the rotation of heterochromatin foci is modulated, to favor either slow or fast turn rates, and thus it appears that the tunable dynamics of HP1-α is achieved by changes in its oligomerization state. In general, two major findings here are somewhat surprising and deserve a more detailed discussion. First, the HP1-α oligomers (dimers or tetramers) are found only at the heterochromatin periphery (irrespective of the size of the heterochromatin focus), while the monomeric form is found at the heterochromatin center and throughout the nucleoplasm. This in turn suggests that a precise spatial organization of HP1-α oligomers is crucial for the regulation of heterochromatin organization. We may speculate that HP1-α dimers at the periphery of heterochromatin foci form a dimerization interface that recruits specific ligands, presumably involved in heterochromatin spreading, although the mechanism of spreading is still to be clarified30Proper understanding of how heterochromatin is established and maintained will ultimately enhance our understanding of stable gene repression. Here, we detected for the first time pericentric heterochromatin, a major repressive chromatin domain, mainly composed of major and minor satellite repeats . Different functions have been assigned to this repressive chromatin locus, the most commonly reported being its participation in kinetochore attachment in mitosis and subsequent chromosome segregation. However, pericentric heterochromatin seems to play also important roles in organizing the repressive compartments of the nucleus, probably by recruitment of silenced genes to the pericentric region, as shown for imprinting or allelic exclusion during B cell developmentTo conclude, we may speculate that an intranuclear heterochromatin target area of particular interest for future investigations might be 2. Freshly split cells were plated onto 35-mm glass bottom dishes coated with fibronectin and then, after twenty four hours, transiently transfected with EGFP, H2B-EGFP (Plasmid #11680 purchased from Addgene), HP1α-EGFP (Plasmid #17652 purchased from Addgene) or HP1α-I165E-EGFP . Freshly split cells were plated onto MatTek 35-mm glass bottom dishes coated with 3 μg/mL fibronectin and then transiently transfected with one of the EGFP tagged plasmids using Lipofectamine 2000 according to manufacturer’s protocol. Induction of chromatin compaction was carried out by treating the NIH3T3 cells transiently transfected with HP1α with Actinomycin D  for 5–10 minutes. Induction of chromatin loosening was carried out by treating the NIH3T3 cells transiently transfected with HP1α with sodium butyrate  for 1–4 hoursNIH3T3 cells were grown in high glucose medium from Invitrogen, supplemented with 10% Fetal Bovine Serum, 5 ml of Pen-Strep and HEPES at 37°C and in 5% CO5 times in the EGFP channel at maximum speed , with fluorescence being sampled every 100 nm (32 pixels to a line). The average laser power at the sample for both frame and line scan acquisitions was maintained at the 1–2 mW. The data acquired were processed by the SimFCS software developed at the Laboratory for Fluorescence Dynamics (www.lfd.uci.edu).The microscopy measurements were performed on a Zeiss LSM710 Quasar laser scanning microscope, using a 40X water immersion objective 1.2 N.A. . EGFP was excited with the 488 nm emission line of an Argon laser. Hoechst 33342 was excited with the 405 nm emission line of a diode laser. EGFP and Hoechst were measured sequentially using the 510–560 nm and 410–490 nm emission ranges, respectively. For each channel the pinhole was set to 1 Airy Unit. Image acquisition for Number and Brightness analysis involved selecting a region of interest within a NIH3T3 cell nucleus at an electronic zoom that resulted in a pixel size of 50–100 nm for a 256 × 256 pixel frame size. A time series of 100 frames was then collected in the EGFP channel at this zoom, with the pixel dwell time set to 12.61 μs/pixel, which resulted in a line time of 7.56 ms and a frame time of 1.15 s. Calibration of the monomeric brightness of the EGFP based constructs was performed by measurement of cells transfected with free EGFP under identical experimental conditions. Line scan acquisition for pair correlation analysis involved selecting a 3 μm line within the NB acquisition ROI that traversed heterochromatin foci (as indicated by the Hoechst 33342 or HP1α fluorescence intensity). The selected line was then rapidly scanned 2 × 10www.lfd.uci.edu, as described in previously published papers272 (second moment). These two properties describe the apparent number (N) and brightness (B) of the molecules that give rise to the intensity fluctuation, according to equations Calculation of the Number and Brightness of molecules in each pixel of an image was performed using the SimFCS software available at The true molecular brightness (ε) of the molecules that give rise to the measured apparent brightness (B) in the case of a photon counting detector are related according to equation 2detector) should equal the average intensity of the detector noise (‹k›detector). In the case of an analogue detector (as was used in the results presented here) this is not true due to characteristics of the analog amplifier and the settings of the analog-to-digital converter. Thus the detector’s brightness contribution needs to be accounted for by a term we call the S factor, which returns the background brightness to 1 so that the molecular brightness of the molecules can be extracted. By analysis of pixels that did not contain fluorescence from the sample, we found the brightness of the background to be between 1.3–1.6 depending on the laser power required. Taking into account this S factor we then calibrated the monomeric brightness of free EGFP so that in the instance oligomerization was observed when tagged to H2B or HP1α we could extract the stoichiometry of the oligomer. The effect of cell movement was subtracted by the moving average algorithm, as previously describedwhere 1 is the brightness contribution of the detector given that the photon counting detector variance (σwww.lfd.uci.edu), as described in the 567x-coordinate corresponds to the point along the line (pixels) and the y-coordinate corresponds to the time of acquisition. The pair correlation function (pCF(pixel distance)) is displayed in pseudo colors in an image in which the x-coordinate corresponds to the point along the line and the y-coordinate corresponds to the autocorrelation time in a log scale. The distances at which pCF analysis was carried out were not fixed across all experiments, but instead determined on an individual basis by the chromatin density variation along each line measured. In general a distance of 4–8 pixels (which corresponds to 400–800 nm) was employed. In general for each experiment, 2 × 105 consecutive lines  were acquired. Time regions within each experiment  with no average change in fluorescence intensity (e.g. due to photobleaching) were then selected for the correlation analysis, as also described elsewhere6Calculation of the pair-correlation functions was done using the SimFCS software developed at the Laboratory for Fluorescence Dynamics .


The liver X receptors  and peroxisome proliferator-activated receptor gamma  nuclear receptor transcription factors (TFs) are master regulators of energy homeostasis. Intriguingly, recent studies suggest that these metabolic regulators also impact tumor cell proliferation. However, a comprehensive temporal molecular characterization of the LXR and PPARG gene regulatory responses in tumor cells is still lacking.To better define the underlying molecular processes governing the genetic control of cellular growth in response to extracellular metabolic signals, we performed a comprehensive, genome-wide characterization of the temporal regulatory cascades mediated by LXR and PPARG signaling in HT29 colorectal cancer cells. For this analysis, we applied a multi-tiered approach that incorporated cellular phenotypic assays, gene expression profiles, chromatin state dynamics, and nuclear receptor binding patterns.Our results illustrate that the activation of both nuclear receptors inhibited cell proliferation and further decreased glutathione levels, consistent with increased cellular oxidative stress. Despite a common metabolic reprogramming, the gene regulatory network programs initiated by these nuclear receptors were widely distinct. PPARG generated a rapid and short-term response while maintaining a gene activator role. By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points.Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome. These results further provide a detailed molecular map of metabolic reprogramming in cancer cells through LXR and PPARG activation. As ligand-inducible TFs, these nuclear receptors can potentially serve as attractive therapeutic targets for the treatment of various cancers.The online version of this article (doi:10.1186/s13073-016-0328-6) contains supplementary material, which is available to authorized users. Metazoan systems are exposed to a multitude of extracellular stimuli, including both compounds that are endogenously synthesized and those obtained through diet –3. In reThe liver X receptors (LXRs), also referred to as Nuclear Receptor Subfamily 1, Group H, Member 2 (NR1H2) and Nuclear Receptor Subfamily 1, Group H, Member 3 (NR1H3), and peroxisome proliferator-activated receptor gamma (PPARG), also referred to as Nuclear Receptor Subfamily 1 Group C Member 3 (NR1C3), are ligand-activated nuclear receptor transcription factors (TFs) that respond to oxysterols  and fattProtective functions have consistently been reported for LXRs in a variety of diverse cancers. For instance, diets rich in plant-derived phytosterols, a putative LXR agonist , were shTo better understand the underlying gene regulatory functions of LXRs and PPARG that lead to metabolic reprogramming in cancer cells, we performed a comprehensive genome-wide analysis of LXR and PPARG activity in HT29 colorectal cancer cells. Despite common physiological effects on energy homeostasis, paradoxically, the genome-wide molecular programs elicited by LXRs and PPARG appear to be temporally distinct. Our results highlight the advantages of integrating multiple levels of transcriptional regulation rather than relying on a single feature. From a broader perspective, this work supports the notion that common phenotypic effects can be mediated through distinct gene regulatory mechanisms.HT29 colorectal cancer cells were obtained from ATCC and grown under recommended cell culture conditions using McCoy’s 5A media containing 10 % fetal bovine serum (FBS) and 1 % penicillin/streptomycin. GW3965 (Sigma), T0901317 (Santa Cruz), and rosiglitazone (Sigma) powder were diluted in DMSO and added to media at a final concentration of 10 μM. Prior to drug treatments, HT29 cells were grown in phenol-red free McCoy’s 5A media containing 10 % charcoal/dextran-treated FBS and 1 % penicillin/streptomycin.Cell-based phenotypic assays were performed in 96-well cell culture plates. Cell proliferation measurements were determined using the CyQuant assay (Invitrogen) for DNA content and CellTiter-Glo Luminescent Cell Viability Assay (Promega) for ATP levels. Glutathione levels for oxidative stress were determined using the GSH-Glo Glutathione Assay (Promega).For analyses of metabolites, cell cultures were washed with phosphate-buffered saline, molecular biology-grade water and then subsequently pelleted for mass spectrometry. Cell pellets were resuspended in 50 % methanol, shaken at 4 °C for 30 minutes and centrifuged at 12,000 rpm for 10 minutes. Duplicate aliquots of supernatant were dried at 55 °C for 60 minutes using a vacuum concentrator system (Labconco). Derivatization by methoximation and trimethylsilyation was performed as previously described . All derFlag-tagged (3-prime 3X-Flag tags separated by glycine spacers) LXRA cDNA plasmid constructs were transfected (Fugene) into HT29 cells. HT29 cells were subsequently selected using G418 (Invitrogen) and expanded prior to GW3965 drug treatment and ChIP-seq experimentation.ChIP-seq was performed as previously outlined . AntibodRNA-seq was performed as previously outlined  using Net-tests were performed to assign significance for cellular phenotypic assays and metabolite levels. Only reproducible binding sites identified by replicate ChIP-seq experiments were reported and used for downstream analyses. ChIP-seq peaks were identified using MACS peak caller [p value ranked. The top 50 % of p value-ranked sites from each category were used for cofactor motif analyses. For assigning TF motif fold enrichments, we compared the total number of motifs found across a set of binding sites with the number of motifs identified after scrambling binding site sequences. For RNAP2 read depth promoter analyses, sequences within 500 bp of transcription start sites were used as promoters. Connectivity maps were generated using Cytoscape (http://www.cytoscape.org/) and Enrichment map [http://software.broadinstitute.org/gsea/msigdb/annotate.jsp). Wilcoxon rank sum tests were used to assign significance for H3K36me3 enrichment analyses. Differential gene expression was determined using DESeq [Two-sided Student’s k caller , while mk caller  on the tment map . Kyoto Eng DESeq . High-coWe evaluated the proliferative and metabolic effects of LXRs and PPARG in HT29 colorectal cancer cells with several cellular assays. First, we assayed cellular proliferation by measuring DNA and ATP content in cells after 24, 48, and 96 h of treatment with the LXR agonist GW3965 and the PPARG agonist rosiglitazone Fig. , b and bTo better characterize cellular metabolic alterations, we next assessed metabolite levels through mass spectrometry of HT29 cell lysate after drug treatment Fig. –f. We fop < 0.01, fold change cutoff ±2) in response to each drug , as well as after 24 and 48 h of drug treatment. For each time point, we calculated the number of differentially regulated genes  chromatin modification under control  culture conditions and after 24- and 48-h drug treatments. Because H3K27ac is a modification that appears at active regulatory elements , this teWe next compiled all time points for each drug treatment separately to identify loci showing dynamic changes in H3K27ac enrichment across the entire duration of treatment , LXRB (NR1H2), and PPARG (NR1C3). We used an early (2-h) and a late (48-h) time point for these experiments to further preserve temporal information. These two datasets spanned the entire temporal molecular characterization and allowed for an examination of the immediate effects of drugs on their direct protein targets. We obtained high-quality antibodies for LXRB and PPARG; however, because we could not identify a suitable commercial ChIP-seq grade antibody for LXRA, we engineered HT29 cells to express a C-terminal Flag-tagged LXRA transgene protein and used a Flag antibody for ChIP-seq experiments. Importantly, normalized sequencing read depth at identified LXRA/B or PPARG binding sites was highly concordant across replicate ChIP-seq experiments for both time points Fig. . AdditioWe next integrated the 2-h and 48-h binding information for LXRB and PPARG proteins, as these datasets illustrate temporal occupancies of TFs under endogenous promoter control. Intriguingly, LXRB and PPARG generated opposing profiles Fig. ; the numWe analyzed the sequence content of LXRB and PPARG binding sites to identify cooperating TFs that may be necessary for LXR and PPARG function. To elucidate potential temporal changes in cofactor preference, we used the top 50 % of sites ranked by significance that displayed stronger occupancy at 2 or 48 h for this assessment. The analysis of several canonical TF sequence motifs at these sites identified a strong enrichment for the AP1 motif Fig. . Indeed,We next performed ChIP-seq to analyze the binding of JunD, a known heterodimer of the AP1 TF complex , to valip < 0.01, fold change cutoff ±2) into activated and repressed targets to assign putative regulatory functions. To infer early regulatory functions, we compared 24-h RNA-seq data with 2-h ChIP-seq data and used the 48-h datasets to assess late activities . We first used our RNAP2 ChIP-seq data to determine the predictive value of RNAP2 normalized read depth at promoters as a measurement for global gene expression  of raw ChIP-seq signal at several loci spanning 48-h, GW3965-repressed genes are provided in Additional file We next divided the LXR sites overlapping with RNAP2 sites (LXR + RNAP2) into promoter binding events and LXR + RNAP2 binding events distal to promoters (±500 bp) to determine if promoter association can explain the observed bimodal distribution of RNAP2 read enrichment Fig. , e. Notap = 1.265e-8, LXRB p = 1.394e-9) in H3K36me3 gene body occupancy  for both proteins , a histone modification found in gene bodies that is correlated with expression , 63. We ncy Fig. , f. IncoAlthough gene regulatory networks govern genome function and underlie diverse physiological and developmental processes, our overall understanding of how these transcriptional programs are spatiotemporally regulated remains rudimentary. Here we sought to understand the gene regulatory networks that control tumor cell metabolism and proliferation in a temporal manner by generating a thorough characterization of the gene regulatory effects of LXR and PPARG signaling. Collectively, our work illustrates how two distinct gene regulatory cascades lead to a common phenotypic outcome and further provides a better molecular understanding of how extracellular metabolic cues impact tumor cell physiology.PDK4 expression . Our metabolomic interrogation further identified an increase in aerobic glycolysis, demonstrating a role for this regulatory network in the Warburg effect. Although this observation is contrary to the observed increase in oxidative stress, the assessment of metabolite concentrations cannot distinguish cause from effect and, therefore, the increase in aerobic glycolysis may reflect an indirect cellular response to oxidative stress rather than a direct effect stemming from LXR and PPARG signaling.Multiple studies have suggested a role for LXR and PPARG metabolic nuclear receptors in tumor cell biology –67. Our Through an investigation that interrogated multiple tiers of transcriptional regulation and genome organization, we demonstrated that these overlapping cell phenotypes are mediated though widely distinct signaling cascades at the molecular level. The genome-wide cellular response to rosiglitazone was rapid and supported by quick changes to metabolite levels, linear transcriptional profiles, abrupt chromatin alterations, and a short-lived burst of PPARG binding. By contrast, the more gradual changes to cellular metabolites, a stalled transcriptional response, gradual increases in the chromatin landscape, and dramatic increase in genome-wide LXRB occupancy with time highlight a more sustained GW3965 response.Despite these differing molecular networks, both sets of nuclear receptors were strongly associated with AP1 transcriptional regulators, with PPARG displaying an early preference for AP1 motifs and co-occupancy, while LXRs exhibited a more pronounced late association with AP1 motifs and proteins. In light of the consistent association with upregulated genes, PPARG appears to behave as a transcriptional activator. This is consistent with the canonical model of type II nuclear receptor function, wherein ligand binding leads to the displacement of co-repressor complexes from nuclear receptors and subsequent recruitment of co-activator proteins . The regBy relying on a unique, multi-tiered approach, our detailed results provide a molecular understanding of how extracellular nutrients impact cancer cell physiology at the genome level. This comprehensive analysis illustrates the complexity of genome function and structure by elucidating how common phenotypic outcomes are genetically encoded through diverse transcriptional programs. Our results finally allude to the tantalizing possibility that tumor cell growth can be altered, or even fully inhibited, through metabolic reprogramming.FBS, fetal bovine serum; KEGG, Kyoto Encyclopedia of Genes and Genomes; LXR, liver X receptor; LXRA, liver X receptor alpha; LXRB, liver X receptor beta; PPARG, peroxisome proliferator-activated receptor gamma; RNAP2, RNA polymerase II; TF, transcription factor.


Patients with neuroblastoma due to N-Myc oncogene amplification have a high frequency of tumor metastasis. However, it is not clear how N-Myc induces cell migration, invasion and metastasis. The histone demethylase JMJD1A activates gene transcription by demethylating the lysine 9 residue of histone H3 (H3K9) at target gene promoters. The long noncoding RNA MALAT1 induces lung cancer cell migration and plays a pivotal role in lung cancer metastasis. Here we demonstrated that N-Myc up-regulated the expression of JMJD1A in N-Myc oncogene-amplified human neuroblastoma cells by directly binding to the JMJD1A gene promoter. Affymetrix microarray studies revealed that the gene second most significantly up-regulated by JMJD1A was MALAT1. Consistent with this finding, RT-PCR and chromatin immunoprecipitation assays showed that JMJD1A bound to the MALAT1 gene promoter and demethylated histone H3K9 at the MALAT1 gene promoter. Moreover, JMJD1A and MALAT1 induced, while the small molecule JMJD1A inhibitor DMOG suppressed, neuroblastoma cell migration and invasion. Taken together, our data identify a novel pathway through which N-Myc causes neuroblastoma cell migration and invasion, and provide important evidence for further development of more potent JMJD1A/MALAT1 inhibitors for the prevention of tumor metastasis. MYCN oncogene amplification and consequent N-Myc mRNA and protein over-expression, are seen in a quarter of tumors and correlate with poorer prognosis in neuroblastoma patients [Neuroblastoma, which originates from precursor neuroblast cells in the sympathetic nervous systems, is the most common extracranial solid tumor in children. patients , 2.Myc oncoproteins, including N-Myc and c-Myc, induce malignant transformation and tumor progression by directly binding to cognate DNA sequences and modulating gene transcription , 4. Myc Gene transcription is a dynamic process, during which lysine residues of histone H3 are modified by histone demethylases and methyltransferases to change RNA polymerase's ability to access the transcription start site , 6. Manyin vitro and in vivo [Also known as KDM3A and JHDM2A, JMJD1A belongs to the Jumonji C-domain-containing protein (JMJD) family, and demethylates mono-methyl and di-methyl histone H3K9  in vivo -9. While in vivo , JMJD1A  in vivo .The long noncoding RNA MALAT1, also known as NEAT2, is over-expressed in metastatic, compared with primary, lung cancer tissues, and is associated with poor prognosis in patients with non-small cell lung cancer . Recent In the current study, we identified one Myc-responsive element E-Box at the JMJD1A gene core promoter, and showed that N-Myc up-regulated JMJD1A gene transcription by binding to JMJD1A gene promoter. JMJD1A demethylated histone H3K9 at the MALAT1 gene promoter, leading to transcriptional activation of MALAT1. These mechanisms contributed to neuroblastoma cell migration and invasion, which could be reversed by the small molecule JMJD1A inhibitor DMOG.MYCN-amplified BE(2)-C and CHP134 human neuroblastoma cells. Importantly, N-Myc siRNA-1 and N-Myc siRNA-2 significantly reduced JMJD1A mRNA and protein expression in the two neuroblastoma cell lines  with bioconductor package (http://www.bioconductor.org/). We used 1.5 fold change as the cut-off for JMJD1A siRNA-1 versus control siRNA experiment and 2.0 fold change as the cut-off for N-Myc siRNA-1 versus control siRNA experiment, since JMJD1A siRNA-1 caused less changes in gene expression in 30 hours. The genome-wide analysis revealed that JMJD1A siRNA-1 reduced the expression of 0.15% (63 probes/41717 probes) of genes, but up-regulated the expression of 0.67% (280 probes/41717 probes) of genes  of genes down-regulated by JMJD1A siRNA-1 were up-regulated by N-Myc siRNA-1 Fig. , 7.94% . In compAs shown in Supplementary JMJD1A is known to up-regulate gene transcription by demethylating mono-methyl and di-methyl histone H3K9 -9. We thWe next examined whether JMJD1A contributed to a cancer phenotype. Alamar blue assays showed that knocking-down JMJD1A gene expression with JMJD1A siRNA-1 or JMJD1A siRNA-2 for 72 hours did not have a significant effect on BE(2)-C cell proliferation, but slightly reduced CHP134 cell proliferation Fig. . We therWe next examined whether MALAT1 also induced cell migration and invasion. RT-PCR and Alamar blue assays showed that transfection with MALAT1 siRNA-1 or MALAT1 siRNA-2 reduced MALAT1 gene expression Fig. , but didN-oxalylglycine (NOG) and its derivatives as histone demethylase inhibitors, and demonstrated that its dimethyl ester prodrug DMOG exerted histone lysine methylating activity in cells [in vitro by using NOG as the model compound. As shown in Table 1 and Supplementary 50 of 67μM, and inhibited other histone demethylases at much higher concentrations.We next examined whether small molecule JMJD1A inhibitors suppressed neuroblastoma cell migration and invasion. We previously identified in cells . As DMOGNext we examined the effects of DMOG on neuroblastoma cell proliferation, migration and invasion. As shown in Fig. JMJD1A gene expression is down-regulated by the microRNA mir-155 -20. Myc As a histone demethylase, JMJD1A exerts biological effects by demethylating mono-methyl and di-methyl histone H3K9 and consequently modulating gene transcription -9. WhileOne of the genes most significantly reduced by JMJD1A siRNAs in our Affymetrix microarray study is the long noncoding RNA MALAT1. Our RT-PCR and ChIP assays confirm that JMJD1A directly binds to the MALAT1 gene core promoter, and demethylates histone H3K9 at the MALAT1 gene core promoter. The data indicate that JMJD1A up-regulates MALAT1 gene expression by demethylating H3K9 at the MALAT1 gene core promoter. This is consistent with previous reports that JMJD1A activates gene transcription by demethylating histone H3K9 at promoter regions of target genes, such as transition protein-1, protamine 1 , 26, difJMJD1A has been well documented to induce tumor progression by up-regulating HIF1α expression and stimulating angiogenesis , 20, 27.Long noncoding RNAs exert biological effects mainly through regulating gene transcription in cis and in trans , 33. RecHistone deacetylase inhibitors are among the most promising novel anticancer agents , and havIn summary, this study demonstrates that a novel pathway, involving transcriptional up-regulation of JMJD1A, which demethylates histone H3K9 at MALAT1 gene promoter and activates MALAT1 gene transcription, plays an important role in N-Myc oncoprotein-mediated neuroblastoma cell migration and invasion. Moreover, the small molecule JMJD1A inhibitor DMOG reduces MALAT1 expression and suppresses neuroblastoma cell migration and invasion. These findings therefore identify JMJD1A and MALAT1 as important factors for N-Myc-mediated neuroblastoma cell migration, invasion and potentially metastasis, and provide important evidence for further development of more selective and potent JMJD1A/MALAT1 inhibitors for the prevention of tumor metastasis.Neuroblastoma BE(2)-C and CHP134 cells were cultured in Dulbecco's modified Eagle's medium supplemented with 10% fetal calf serum.Cells were transfected with siRNAs from Qiagen  or Ambion  using Lipofectamine 2000  reagent as we described , 23. TheGene expression in tumor cells was examined by quantitative real-time RT-PCR as described previously , 36. Forhttp://www.r-project.org/) with bioconductor package (http://www.bioconductor.org/).Neuroblastoma BE(2)-C cells were transfected with scrambled control siRNA, N-Myc siRNA-1 or JMJD1A siRNA-1. Thirty hours after transfection, RNA was extracted from the cells with RNeasy mini kit. Differential gene expression was examined with Affymetrix Arrays , according to the manufacturer's instruction. Results from the microarray hybridization were analysed in R  were placed in the center of 6 well plates. BE(2)-C cells were added into the wells outside the inserts. Sixteen hours later, the inserts were removed to create “wounds”. Photos of the “wounds” were taken under microscope, and the areas of the remaining “wounds” were measured and analyzed with Image J software .BE(2)-C cells were transfected with siRNA or treated with JMJD1A inhibitors for 20 hours, and then detached and added onto BD Falcon Cell Culture Inserts coated with Matrigel inside BD BioCoat Matrigel Invasion Chambers . Cells invaded through Matrigel to the bottom side of the inserts were stained with toluidine blue, photographed under microscope and quantified.ChIP assays were performed with an anti-N-Myc, anti-JMJD1A, anti-di-methyl H3K9 or control antibody and PCR with primers targeting up-stream negative control region or core promoter region of the JMJD1A or MALAT1 gene promoter with the protocol we described . Fold enThe inhibitory activities of NOG against JMJD1A were assayed according to a previously reported method . The inhAll data for statistical analysis were calculated as mean ± standard error, and differences were analyzed for significance using ANOVA among groups or unpaired t-test for two groups. A probability value of 0.05 or less was considered significant.


Arabidopsis genes encoding nuclear exosome components AtRRP6L1 and AtRRP6L2, cause de-repression of the main flowering repressor FLOWERING LOCUS C (FLC) and thus delay flowering in early-flowering Arabidopsis ecotypes. AtRRP6L mutations affect the expression of known FLC regulatory antisense (AS) RNAs AS I and II, and cause an increase in Histone3 K4 trimethylation (H3K4me3) at FLC. AtRRP6L1 and AtRRP6L2 function redundantly in regulation of FLC and also act independently of the exosome core complex. Moreover, we discovered a novel, long non-coding, non-polyadenylated antisense transcript  originating from the FLC locus in wild type plants. The AtRRP6L proteins function as the main regulators of ASL synthesis, as these mutants show little or no ASL transcript. Unlike ASI/II, ASL associates with H3K27me3 regions of FLC, suggesting that it could function in the maintenance of H3K27 trimethylation during vegetative growth. AtRRP6L mutations also affect H3K27me3 levels and nucleosome density at the FLC locus. Furthermore, AtRRP6L1 physically associates with the ASL transcript and directly interacts with the FLC locus. We propose that AtRRP6L proteins participate in the maintenance of H3K27me3 at FLC via regulating ASL. Furthermore, AtRRP6Ls might participate in multiple FLC silencing pathways by regulating diverse antisense RNAs derived from the FLC locus.The exosome complex functions in RNA metabolism and transcriptional gene silencing. Here, we report that mutations of two  Arabidopsis FLOWERING LOCUS C (FLC) delays flowering; therefore, repressing expression of FLC provides a critical mechanism to regulate flowering. This mechanism involves multiple levels of regulation, including genetic regulation by transcription factors, and epigenetic regulation by modifications of genomic DNA and histones at the FLC locus. This work examines the role of non-coding RNAs in the epigenetic regulation of FLC, finding that the different RNAs produced from the FLC locus may have different functions in altering the epigenetic landscape at the FLC locus, and revealing that AtRRP6L1 and AtRRP6L2, two components of the exosome, an RNA-processing complex, play roles in regulating these non-coding RNAs. Therefore, this work explores the complex ties between RNA processing, non-coding RNAs, and epigenetic regulation of FLC, a key repressor of flowering. The regulation of gene silencing occurs at multiple levels and non-coding RNAs (ncRNAs) have emerged as important regulators of genome silencing at the transcriptional and posttranscriptional levels The exosome is an evolutionarily conserved complex of RNase-like and RNA binding proteins involved in 3′ to 5′ decay and processing of various RNA substrates Arabidopsis has three possible functional homologs of RRP6: the nuclear proteins AtRRP6L1 and AtRRP6L2, and the cytoplasmic protein AtRRP6L3 Arabidopsis RRP6Ls physically associate with the exosome core remains to be tested.The nuclear form of eukaryotic exosome also associates with the second catalytic RRP6 subunit, a substoichiometric, nuclear-specific, 3′ to 5′ exoribonuclease Schizosaccharomyces pombe), the exosome acts in several different small RNA (smRNA) pathways to affect constitutive and facultative heterochromatin silencing, in either RNAi-dependent or RNAi-independent manners The exosome complex broadly affects epigenetic silencing of heterochromatic and euchromatic loci by regulating a variety of ncRNAs Arabidopsis correspond to ncRNAs, many originating from heterochromatic loci, suggesting that the exosome participates in various silencing pathways in ArabidopsisArabidopsis showed that the exosome has little effect on the smRNAs that function in the main silencing mechanisms, siRNA-dependent methylation of DNA (RdDM). Rather, we showed that the exosome associates physically with long, polyadenylated RNAs transcribed from the scaffold regions of several heterochromatic loci, and exosome defects affected the level of histone H3K9me2, an epigenetic mark that alters chromatin structure Arabidopsis rrp6 homologues AtRRP6L1 and AtRRP6L2 participate in these epigenetic mechanisms and may function redundantly AtCSL4, the genes encoding the Arabidopsis exosome core complex subunits are essential for viability Arabidopsis RRP6-Like proteins are not essential for viability rrp6 and rrp6l mutants provide tools to study the role of the exosome during development.Our previous genome-wide survey revealed that many exosome targets in Arabidopsis FLC (FLOWERING LOCUS C), which encodes a MADS-box transcription factor that suppresses flowering Epigenetic regulation by long non-coding RNAs (lncRNAs) and histone modifications plays a key role in controlling the expression of FLC regulation through chromatin modifications has been well studied FLC expression requires H3K4 methylation, a permissive chromatin modification, on FLC chromatin, and H3K4 demethylation leads to FLC repression FLC silencing requires Polycomb complex 2 (PRC2) -deposited H3K27me3, a repressive chromatin modification FLC provides a central mechanism for both the vernalization pathway, which regulates flowering time in response to periods of prolonged cold, and the autonomous pathway, which regulates flowering independently of environmental signals FLC silencing, and different lncRNAs produced from the FLC locus may have distinct functions. For example, lncRNAs COOLAIR and COLDAIR participate in the epigenetic silencing of the FLC locus FLC locus as two alternatively polyadenylated isoforms, AS I and AS II, and it was shown that the processing of AS I and II function in FLC epigenetic silencing by affecting H3K4 demethylation FLC repression early during cold treatment, possibly mediated by direct effects on the FLC promoter FLC intron 1, and plays a role in FLC silencing via recruitment of Polycomb repressing complex 2 (PRC2) to FLC during vernalization FLC in vernalization requires COLDAIR FLC silencing The processing and metabolism of lncRNAs play a crucial role in AtRRP6L1 and AtRRP6L2 result in delayed flowering in early-flowering Arabidopsis ecotypes that do not require vernalization for flowering. We found that AtRRP6L1 and AtRRP6L2 epigenetically regulate FLC silencing by regulating different antisense transcripts and modulating H3K4me3 and H3K27me3 histone modifications at the FLC locus. Moreover, we discovered a novel antisense transcript, termed Antisense Long (ASL), which originates from the FLC locus in wild type plants and is regulated by AtRRP6L1 and AtRRP6L2. Our study demonstrates that Arabidopsis RRP6L proteins play an important role in the regulation of genes expressed in specific developmental phases via participating in lncRNA-mediated epigenetic silencing.Here, we report that mutations of Arabidopsis RRP6L1 and RRP6L2 and found that these mutations lead to de-repression of known heterochromatic loci and that RRP6L1 and 2 likely function redundantly in this process AtRRP6L1 was isolated from the Wisconsin population of T-DNA mutants AtRRP6L2 comes from the SALK collection, in the Columbia (Col-0) ecotype rrp6l1-3 mutant is a null allele and rrp6l2-3 is nearly null We previously examined T-DNA mutations in rrp6l1-3, rrp6l2-3, and rrp6l1-3 rrp6l2-3 double mutants (hereafter rrp6l1/2) and compared them to wild-type plants of Col-0 and Ws ecotypes. When we examined the phenotype of different rrp6l1 and rrp6l2 alleles, we found that these single mutants did not show significant phenotypic alterations, although they exhibited a mild delay in flowering, as measured by leaf number at bolting  activates FLC expression FRI, such as the early-flowering accessions Col-0 and Ws ecotypes used in this study, do not require vernalization for flowering. Thus, our data suggest that AtRRP6L1and AtRRP6L2 could be involved in regulation of FLC expression through the autonomous flowering pathway.To control for the ecotype, we examined the phenotypes of  bolting . By contnditions  and beconditions . These fFLC expression, we examined whether mutations of AtRRP6Ls affect the expression of FLC. We observed no change in FLC expression in the rrp6l1-3 and rrp6l2-3 single mutants, consistent with the degree of the observed phenotypic alterations, and we confirmed this observation with additional AtRRP6L1 and AtRRP6L2 T-DNA alleles  and FLOWERING LOCUS T (FT), which act downstream of FLC. We found that the rrp6l1/2 mutants showed lower levels of both SOC1 and FT transcripts  transcripts, AS I and AS II FLC transcription rrp6l1/2 mutants showed changes in the ratio of 3′ end processing and polyadenylation of these antisense transcripts. We found that, compared to wild type plants, the rrp6l1 or rrp6l2 single mutants, and the rrp6l1/2 double mutants had lower levels of processed AS I and II transcripts  to analyze the levels of H3K4me3 at various regions of the FLC locus  also suggests that AtRRP6L proteins might participate in the processing of different types of antisense RNAs, in addition to the known antisense transcripts derived from the FLC locus. Alternatively, AtRRP6L could also participate in co-transcriptional regulation of antisense transcription by binding to nascent antisense transcripts. Also, the level of AtRRP6L1 enrichment at the FLC locus was relatively modest , which degrades uncapped RNA. We found that TPE treatment did not affect ASL levels, indicating that ASL has a 5′ cap . Next, wnrpd1 (Pol IV) and nrpe1 (Pol V) mutants; we detected ASL in these mutants, indicating that Pol IV and V do not affect ASL, although nrpd1 mutants showed a minor change in ASL levels  in wild type plants using antibodies against AtRRP6L1 protein . The RNAP6L1-TAP . TogetheFLC silencing and several lncRNAs affect H3K4 demethylation and H3K27 trimethylation FLC silencing during the vegetative phase after H3K27me3 has been established We then hypothesized that the ASL RNA may play a role distinct from that of AS I and II. Histone remodeling factors affect FLC locus in rrp6l1/2 mutants. To our surprise, we observed that the rrp6l1/2 mutants showed significantly decreased levels of H3K27me3 along the entire FLC locus -ChIP assays using anti-H3 antibodies. MNase degrades nucleosome-free regions, allowing the estimation of nucleosome density. We found a lower nucleosomal density at the FLC locus in rrp6l1/2 mutants , an Arabidopsis homolog of Trithorax 1, dynamically regulates activation of FLC through trimethylation but not dimethylation of H3K4 and atx1 mutations led to the loss of H3K4me3 and gain of H3K27me2 during the vegetative phase, but did not affect H3K4me2 and H3K27me3 FLC locus could be independent of each other, at least during the vegetative phase. Together, the previous reports and our data suggest that the decrease of H3K27me3 in rrp6l1/2 mutants could be caused by the decrease in ASL RNA expression, and AtRRP6Ls may participate in the respective pathways for FLC silencing through regulating the expression of AS I, AS II, and ASL RNAs.AtRRP6Ls might affect the level of H3K27me3 indirectly, by regulating H3K4 demethylation through regulating either AS I and II, or ASL transcripts, FLC locus, which leads to maintenance of H3K27 trimethylation during vegetative growth. Taken together, the previous reports and our data suggest that the regulation of chromatin structure via various lncRNAs is a central mechanism in FLC silencing, and different lncRNAs may function in different chromatin modification pathways. The AtRRP6L proteins may play a role in silencing pathways by regulating antisense transcription.We identified ASL, a novel, long antisense RNA that is distinct from the previously-described antisense RNAs. We observed that the ASL transcript physically associates with H3K27me3, suggesting that it could play a role in H3K27 trimethylation and function differently than AS I and II RNAs. The PRC2 complex binds ncRNAs with high affinity but does not recognize specific sequences, while its binding affinity correlates with the length of the RNA FLC. These differences suggest that ASL may have functions distinct from the functions of AS I and II in FLC silencing, and the mechanism of FLC silencing could be more complicated than previously thought.ASL has several features in common with AS I and AS II. First, ASL is transcribed by RNA Pol II; second, it is alternatively spliced, existing in 2 isoforms; third, its transcription is driven by the same promoter that drives AS I and AS II; fourth, the 5′ part of ASL overlaps with the 5′ region of AS I and II. However, in contrast to AS I and II, the ASL transcript is long , is non-polyadenylated, and extends into intron 1 of Arabidopsis homologs of Nrd1, Nab3 and Sen1 have not yet been characterized.RNA Pol II transcribes ASL. Various non-polyadenylated Pol II RNAs, such as snRNA, snoRNAs, and some mRNAs, are processed by the exosome, which is recruited by the Nrd1-Nab3-Sen1 termination complex in the noncanonical 3′ end-processing pathway rrp6l1-3 and rrp6l2-3 single mutants showed decreased levels of ASL, and ASL was almost undetectable in the rrp6l1/2 double mutant. Based on the results of the α-amanitin chase experiments, the rrp6l1-1 mutation does not affect the stability of ASL, suggesting that AtRRP6L1 and AtRRP6L2 could be the main regulators of ASL synthesis. This finding is very intriguing, since defects in the exosome and RRP6 usually lead to abnormal accumulation of various RNAs due to failures of RNA degradation or processing AtRRP4 and AtRRP41 inducible RNAi plants and the AtCSL4-2 mutant Xist ncRNA involved in X-chromosome inactivation, although it remains to be seen whether this effect is direct The In our study, we found that AtRRP6L1 protein physically associates with the ASL transcript, suggesting that AtRRP6L1 plays a direct role in regulation of ASL levels, likely through ASL synthesis rather than degradation. In addition, recent work demonstrated that another 5′-3′ exoribonuclease, Xrn1, also directly contributes to RNA synthesis of several mRNAs in budding yeast, by physically associating with chromatin and contributing to transcription elongation FLC transcript was unaffected in the exosome core subunit mutants, AtRRP4 and AtRRP41 inducible RNAi lines and AtCSL4-2 T-DNA mutants, suggesting that the function of AtRRP6L1 and AtRRP6L2 in regulation of FLC expression could be independent of the exosome complex. This could also indicate that the exosome core complex is not necessary for metabolism of RNAs produced from the FLC locus and different RNA decay factors could participate in their degradation. For example, in yeast, the XRN family of 5′ to 3′ exoribonucleases works in both the nucleus and cytoplasm, and has diverse functions in RNA metabolism We found that the level of FLC is regulated mainly through histone modifications rather than DNA methylation ArabidopsisFLC silencing mainly by histone modifications suggested that the FLC locus could be one of the targets of the AtRRP6L proteins. In accord, we observed that defects in AtRRP6L proteins caused a decrease in antisense RNAs, resulting in the alteration of histone modifications and de-repression of FLC.Silencing of FLC silencing via regulation of antisense transcription, which means that AtRRP6L proteins could participate in 2 different pathways, one involved in H3K4 demethylation and the other involved in H3K27 trimethylation. First, AtRRP6Ls could participate in the H3K4 demethylation pathway via regulating synthesis of AS I and AS II. Second, AtRRP6L proteins could function in the H3K27 trimethylation pathway via regulating the synthesis of ASL. However, more work will be needed to untangle the interrelationships of the different lncRNAs and the roles they play in the epigenetic architecture at FLC. How AtRRP6L proteins and the ncRNAs controlled by them help recruit chromatin modifiers to modulate silencing by affecting histone modifications that repress transcription remains an intriguing topic for future work.It is intriguing to speculate that AtRRP6L proteins may have dual functions in atrrp6l1-3 allele was isolated from the BASTA population from the University of Wisconsin atrrp6l1-1, atrrp6l2-2, atrrp6l2-3, atrrp6l2-4 and atrrp6l3-1 alleles correspond to SALK_004432, SALK_113786, SALK_011429, and SALK_149898, and SALK_122492, respectively. iRNAi lines of RRP41, csl4-2, RNA Pol IV , RNA Pol V  mutants were described previously RRP41 was induced by germinating and growing seedlings on ½× MS plates containing 8 mM 17β-estradiol, following a previously published method The Long day and short day conditions for plant growth were 16 hours light/8 hours dark and 8 hours light/16 hours dark, respectively. Flowering time was measured by counting rosette leaf number at the time of flowering RRP6L1 for RNA-IP and ChIP, we complemented atrrp6l1-3 with the RRP6L1-TAP transgene. For RRP6L1-TAP complementation, the entire genomic region of RRP6L1 including 1.5 kb upstream from the ATG codon was amplified by PCR using LA taq polymerase (Takara) and cloned into TAP-tag carrying destination vector pDB1008 atrrp6l1-3 mutant was transformed using Agrobacterium-mediated transformation and the progeny plants containing both the T-DNA insertion allele and the transgene were identified by PCR.For chromatin immunoprecipitation (see below), we used the Tandem Affinity Purification (TAP) affinity tag to selectively precipitate RRP6L1 by expressing a RRP6L1- TAP fusion protein. For construction of plant lines with affinity-tagged t, ACTIN 7 (At5g09810) as an internal reference.Trizol reagent (Invitrogen) was used to isolate total RNA from seedlings. 10-, 14-, 18-, and 21-day-old seedlings were used for examining the expression of ASL. 11-day-old seedlings were used for investigating expression of genes and antisense RNAs examined in our study. For RT-qPCR, 2–4 µg of total RNA was digested with DNase I (Fermentas) and reverse transcribed for one hour at 42°C (oligo-dT primers) or at 50°C (gene-specific primers), with 100 units of PrimeScript reverse transcriptase (Takara). RT-qPCR  was used to quantify transcripts using the comparative threshold cycle method  and then filtered through miracloth. After isolation of the nucleus-containing fraction by centrifugation, the fraction was treated with MNase (NEB) at 37°C for 10 min. Anti-histone H3 (ab1791) was used for the ChIP. The purification of ChIPed DNA and qPCR was performed as described in ChIP assay.MNase-ChIP was performed following a previously-described method RNA-IP assays were performed as described previously ACTIN 7 primers, followed by qRT-PCR. The level of ASL transcript was normalized relative to the level of ACTIN 7 transcript.Eleven-day-old seedlings were treated with 5 µM α-amanitin (Sigma) for 0, 6 and 9 h or 17 h. After RNA extraction, cDNA was synthesized using ASL-specific and Total RNA extracted from 11-day-old seedlings was treated with TPE (Epicentre) at 42°C, and purified with phenol∶chloroform. Complementary cDNA was synthesized using RNA sequence specific primers followed by RT-qPCR.Figure S1FLC and AS I and II in different rrp6l1 and rrp6l2 mutants, and ChIP assay of rrp6l1-3 using anti-H3K27me3. (A) The late-flowering phenotype and RT-PCR analysis of FLC mRNA expression of rrp6l1-1/rrp6l2-2/rp6l3-1 mutants grown under long day conditions. 20-day-old (after transferring to soil) plants are shown. RRP6L3 is the cytoplasmic protein FLC mRNA expression in rrp6l1-3, rrp6l1-1, rrp6l2-3, and rrp6l2-4 single mutant alleles. (C) RT-qPCR analysis of AS I and AS II transcripts in rrp6l1-3 and rrp6l2-3 single mutants. Ws and Col-0 ecotypes, were used as wild-type controls. The expression of AS I and II transcripts was normalized to the expression of total antisense RNA, as described previously rrp6l1-3 mutants. ChIP assay was performed using H3K27me3 antibodies. The level of H3K27me3 in rrp6l1-3 mutants was plotted relative to the level of H3K27me3 in Col-0 plants. The error bars in ChIP experiments represent the standard error of the mean and correspond to the difference between 2 biological replicates.Expression of (TIF)Click here for additional data file.Figure S2nrpd1 and nrpe1 mutants. TUBULIN 2 was used as the loading control. (C) RT-PCR of ASL in rrp6l1-1 and rrp6l2-4 mutants. The ASL transcript was normalized to ACTIN 7.Tiling RT-PCR to identify full-length ASL RNA and examine ASL expression. (A) The strategy of tiling RT-PCR to obtain full-length ASL. Arrowheads indicate serial primers used in RT-PCR. PCR products obtained after tiling RT-PCR were cloned for sequencing analysis. (B) Expression of ASL transcript in (TIF)Click here for additional data file.Table S1Oligonucleotides used in this study.(XLS)Click here for additional data file.