Editing of transcripts encoding mutant channels affects numerous biophysical properties including channel opening, closing, and inactivation. Thus EA1 symptoms could be influenced not only by the direct effects of the mutations on channel properties, but also by their influence on RNA editing. These studies provide the first evidence that mutations associated with human genetic disorders can affect cis-regulatory elements to alter RNA editing.Adenosine-to-inosine RNA editing in transcripts encoding the voltage-gated potassium channel Kv1.1 converts an isoleucine to valine codon for amino acid 400, speeding channel recovery from inactivation. Numerous Kv1.1 mutations have been associated with the human disorder Episodic Ataxia Type-1 (EA1), characterized by stress-induced ataxia, myokymia, and increased prevalence of seizures. Three EA1 mutations, V404I, I407M, and V408A, are located within the RNA duplex structure required for RNA editing. Each mutation decreased RNA editing both  The Kv1.1 voltage-gated potassium (Kv) channel α-subunit plays an important role in regulating neuronal excitability. By dampening excitability at the axon initial segment and juxtaparanodal region346781012RNA transcripts encoding Kv1.1 are modified by a site-specific adenosine-to-inosine (A-to-I) RNA editing event in which a genomically-encoded isoleucine (AUU) is converted to a valine (IUU) codon at amino acid position 400 of the protein15KCNA1) that have been associated with this disorder19202122232425181920212223242526Episodic ataxia type-1 (EA1) is a sporadic neurological disorder characterized by stress-induced motor discoordination, involuntary, repetitive muscle contraction (myokymia), and can coincide with seizuresin vitro editing system and the V408A mutation decreased the extent of editing in a previously characterized mouse model of EA1. Furthermore, we show that editing can have a variable effect on each type of EA1 mutant protein, altering voltage sensitivity, activation and deactivation, and inactivation with a Kvβ subunit. Not only do our studies demonstrate that EA1 mutations can impede RNA editing and alter resulting protein function, but also represent the first examples of existing disease-associated human mutations which act to disrupt cis-regulatory elements required for RNA editing.At least three EA1-associated mutations  have been identified within the duplex region required for editing of Kv1.1 RNAs2021222328data not shown)in vitro using these minigenes as a template and a range of concentrations for each RNA was subjected to an in vitro editing assay using ADAR2 protein derived from nuclear extracts isolated from HEK293 cells transiently expressing ADAR2et al.in vitro. Furthermore, the magnitude of this rate decrease corresponded to the proximity of the mutation to the editing site (I400 V), with the most severe deficit observed for the V404I mutation (81% rate reduction at 2 nM RNA), and a 58% and 17% reduction in editing rate for the I407M and V408A mutations, respectively.Three known EA1-associated mutations, V404I, I407M, and V408A, lie within the predicted 114-bp RNA duplex, which represents the minimum sequence required for site-specific editing of Kv1.1 transcripts by ADAR2 15. Usingin vivo, we isolated RNA from multiple dissected brain regions and spinal cord of wild-type and V408A/+ mutant animals to determine RNA editing profiles by high-throughput sequence analysis of Kv1.1 transcripts. Since this deep-sequencing approach generates sequence reads covering both the V408A mutation and the editing site, it was possible to quantify allele-specific editing profiles in V408A/+ heterozygotes. Results from this analysis indicated that the extent of editing for the wild-type allele in V408A/+ mutant mice was similar to that observed in wild-type animals. Editing for the mutant V408A allele showed a 59% reduction in site-specific editing efficiency in all tissues examined when compared to either wild-type littermates or the V408A/+ wild-type allele  or edited (E) isoforms of the wild-type, V404I, I407M, or V408A Kv1.1 subunits, expressed as homotetramers.All three EA1 mutations can affect the rate of editing  in vivo  and 2. Aseein Materials & Methods). Conductance (G) versus voltage (V) curves were fit to a Boltzmann function, The voltage dependence of activation for each channel subtype was analyzed to determine editing-dependent changes, and representative traces for each channel are shown in 1/2) and the relative voltage sensitivity (k)  . Consist editing . By cont editing . Thus, e editing . Editing editing .To examine how editing affected channel opening kinetics, the time to reach half-maximal activation across a range of voltages was determined. The only editing-dependent change was observed for the I407M mutation. Both I407M channels opened more slowly than their wild-type counterparts, but the slowing was more severe for I407M E channels , leadingClosing (deactivation) kinetics were measured by fitting single exponential curves to tail current traces to obtain estimates of tau (τ), the reciprocal of the closing rate constant. Editing resulted in wild-type channels closing slightly faster . In addiSlow inactivation (C-type) was examined by analyzing channel function under conditions of long depolarizations. The I407M E and V408A E channels demonstrated editing-dependent dysfunction, with a prominent fast component of their inactivation appearing alongside the slow component. Thus, while a single exponential function was sufficient to describe the inactivation for the majority of the channels, I407M E and V408A E required a double exponential fit . Both thet al.Previous studies by Bhalla data not shown). This variability in the extent of inactivation for the mutant channels is consistent with previous studies demonstrating that the extent of inactivation could be manipulated by varying the aliphatic amino acid residues at the position of the editing siteOocytes expressing each channel subtype, along with Kvβ1.1, were subjected to short depolarizing pulses to different voltages and the resulting fast inactivation traces were fit to a single exponential. These studies identified a previously uncharacterized difference in wild-type channels where editing modestly slowed the rate of channel inactivation . V404I Ndata not shown). In wild-type channels, editing led to an increase in the relative amplitude of the fast component of inactivation. An editing-dependent change also was observed for the V404I channels, where editing brought the relative amplitude of the fast component closer to that of the wild-type channel  are within close proximity to the Kv1.1 editing site (I400 V) and also are predicted to disrupt the critical RNA duplex structure required for this post-transcriptional modification.The conversion of A-to-I by RNA editing has been shown to represent an important post-transcriptional modification by which to modulate the function of numerous proteins critical for nervous system function15173738cis-regulatory elements to change their gene’s RNA editing profile, by altering the RNA structure required for site-selective A-to-I conversion. Results using both in vitro and in vivo model systems have shown significant reductions in the extent and rate of editing for Kv1.1 transcripts harboring specific EA1 mutations  to assess cumulative inactivation, as well as probing the voltage-dependence of their inactivation. Since these mutations also led to decreases in the editing of Kv1.1 transcripts, additional experiments will be required to test the relative contribution of editing-dependent and independent effects, especially when the Kv1.1 proteins are co-assembled into heterotetramers with other Kv1.x family members2041These studies also have revealed that the effects of EA1 mutations on Kv1.1 function are far more complex than originally anticipated, as each mutation produces channels with unique biophysical properties that depend the I400 V amino acid identity, mediated by RNA editing. The V404I mutation altered several electrophysiological parameters on its own, but the edited isoform demonstrated less drastic changes than the non-edited isoform, as observed for channel voltage sensitivity, closing kinetics, and the amplitude of β-inactivation . Althougin vivo will be comparatively slow, possibly resulting in unanticipated effects that could prevent normal neuronal signaling.Although our studies suggest that edited isoforms of mutant channels represent a smaller portion of the total Kv1.1 population, they may still exert functional effects, particularly in tissues with higher editing levels  . This iset al.While no clear correlation has been established between the diverse clinical phenotypes of EA1 patients and specific mutations within Kv1.1181920212223242526Xenopus expression vector, pGEM HEA 463 bp-region encompassing the duplex required for Kv1.1 editing was amplified using the polymerase chain reaction (PCR) from human genomic DNA using sense (5′-GCGAAGCTTCCTCTTCATCGGGGTCATCCT-3′) and antisense (5′-GCGGCGGCCGCAGTTTTGGTTAGCAGTGG-3′) oligonucleotide primers in exon 2. To aid in subcloning, the primers incorporated Hind III and Not I restriction sites on their 5′-ends for the sense and antisense primers, respectively. The PCR amplicon was subcloned into the mammalian expression vector, pRc-CMV (Thermo Fisher) to generate a wild-type Kv1.1 minigene. To generate the V404I, I407M, and V408A minigenes, the wild-type Kv1.1 construct was mutagenized using the QuikChange II Site-Directed Mutagenesis kit (Agilent Technologies), where the PCR reactions were supplemented with 5% DMSO. Full-length mouse Kv1.1 (Addgene) and mouse Kvβ1.1 (Thermo Scientific) cDNAs were subcloned into the in vitro from the wild-type Kv1.1 minigene, as well as corresponding minigenes harboring the V404I, I407M, and V408A mutations using the MAXIscript kit (Ambion) with T7 RNA polymerase according to manufacturer’s instructions. Nuclear extracts were prepared from transiently transfected HEK293 cells expressing rat ADAR2, as described previously, and stored at −80 °C until required32in vitro editing analysis, nuclear extracts were diluted 1:10 in dialysis buffer , before a 2-hour incubation at 30 °C with RNase inhibitors and RNA substrates varying in concentration from 0.125 to 2 nM. Nuclear extracts represented one-third of the total 50 μL reaction volume which was diluted with the RNA substrate and water to reduce the glycerol concentration into a range necessary for ADAR2 activity. The incubation time was determined empirically by time-course analyses to ensure that editing of the wild-type Kv1.1 minigene was within the linear range of the reaction (data not shown). Reactions were terminated by the addition of TRIzol (Ambion) and RNA was extracted according to the manufacturer’s protocol. RNA was reverse-transcribed with random primers using the High Capacity cDNA Reverse Transcription kit (Applied Biosystems) and the extent of RNA editing was quantified by high-throughput multiplexed sequence analysis as described previouslyRNAs were transcribed in vitro RNA editing analyses.All animal care and experimental procedures involving mice were approved by the Vanderbilt University Medical Center Institutional Animal Care and Use Committee and were performed in accordance with relevant guidelines and regulations. Mice harboring the heterozygous V408A mutation (V408A/+) were generously provided by Dr. James Maylie Xenopus laevis were approved by the University of Puerto Rico Institutional Animal Care and Use Committee and were performed in accordance with relevant guidelines and regulations. Kvβ1.1 and full-length, wild-type, V404I, I407M, and V408A Kv1.1 RNAs were transcribed in vitro, capped, and polyadenylated using the T7 mScript Standard mRNA Production System (CELLSCRIPT). Ovary sections containing several hundred oocytes were removed from adult specimens of Xenopus laevis obtained from Xenopus Express . Oocytes were dispersed with type II collagenase and manually defolliculated. Stage V and VI oocytes were then selected by manual inspection for subsequent RNA injection. On day 1, oocytes were injected with 38.6 nL of one of the eight full-length Kv1.1 RNAs encoding edited and non-edited isoforms of wild-type, V404I, I407M, and V408A channels, with or without the Kvβ1.1 RNA. Injection concentrations were optimized individually for each construct, with greater concentrations required for the I407M and V408A RNAs due to protein expression differences previously described in the literature212, 2.5 mM CaCl2, 10 mM HEPES, pH 7.4. The internal solution consisted of: 120 mM K-glutamate, 2.5 mM EGTA, 10 mM HEPES, pH 7.4. The pH of the solutions was adjusted using N-methyl-D-glucamine, as an alternative to NaOH, to limit the introduction of sodium ions into the solutions. To gain electrical access to the oocyte interior, the internal solution was supplemented with 0.3% saponin and used for a brief permeabilization prior to recording. The oocyte membrane potential was controlled using a CA-1B High Performance Oocyte Clamp (Dagan Corporation). Analog current signals were digitized at 100 kHz using an SBC6711 A/D D/A board  and filtered at 5 kHz. To avoid errors introduced by series resistance, only traces exhibiting less than 10 μA were used for analysis. GPATCH M software, kindly provided by Dr. F. Bezanilla (University of Chicago), was used for data collection and clamp control. Leak currents were subtracted using a linear P/4 procedure. Data were analyzed using ANALYSIS software, also provided by Dr. F. Bezanilla, for fitting data with exponential functions and measuring current amplitudes. In addition, single exponential curves were fitted to recovery from the inactivation data using Graphpad Prism (Graphpad Software) to determine the rate constant, τ. As the channels encoded by edited V408A transcripts closed too rapidly for measurements of tail current amplitude, conductance (G) was calculated using Ohm’s law, All animal care and experimental procedures involving r signifies the reversal potential, determined empirically. For where I represents the maximal current at the test potential (V) and Vin vitro .Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


IGH) gene loci are subject to specific recombination events during B-cell differentiation including somatic hypermutation and class switch recombination which mark the end of immunoglobulin gene maturation in germinal centers of secondary lymph nodes. These two events rely on the activity of activation-induced cytidine deaminase (AID) which requires DNA double strand breaks be created, a potential danger to the cell. Applying 3D-fluorescence in situ hybridization coupled with immunofluorescence staining to a previously described experimental system recapitulating normal B-cell differentiation ex vivo, we have kinetically analyzed the radial positioning of the two IGH gene loci as well as their proximity with the nucleolus, heterochromatin and γH2AX foci. Our observations are consistent with the proposal that these IGH gene rearrangements take place in a specific perinucleolar “recombination compartment” where AID could be sequestered thus limiting the extent of its potentially deleterious off-target effects.The immunoglobulin heavy chain ( IGH) genes must first be rearranged during the so-called V(D)J recombination process which takes place in bone-marrow B-cells. This B-cell then circulates through the blood to a secondary lymphoid organs where the rearranged IGH gene locus is further modified. Fine tuning to the immunogen relies on somatic hypermutation (SHM) events occurring within the variable part of the IGH gene  are created through enzymatic activities performed by the RAG1/2 complex in bone marrow, and the result of activation-induced cytidine deaminase (AID) in lymph nodes IGH) geneph nodes , histoneph nodes , Polycomph nodes , insulatph nodes  as well ph nodes , replicaph nodes  and repaph nodes  factorieph nodes , 17. It IGH alleles changes during B-cell maturation. The non-productive IGH allele remains close to the nuclear periphery while its productive counterpart occupies a more central position [IGH allelic expression and recombination [IGH locus has been less studied in humans. Since among mammals, the organization of chromatin tends to be species-specific - for instance, heterochromatin clusters are prominent in mice but not in humans - we have addressed the nuclear localization of the two IGH alleles in human B-cells undergoing maturation. To do so, we have made use of a system developed by Fest and collaborators whereby the maturation of B-cells is recapitulated in vitro [0 are activated and induced to proliferate in the presence of cytokines and monoclonal antibodies. Differentiating cells are harvested starting at Day4 . With this methodological approach, we have explored the hypothesis that both SHM and CSR take place in a specific nuclear compartment containing AID and all recombinogenic agents necessary. This hypothesis was based on the observation that RAG1/2 and AID are stored in the nucleolus when overexpressed [IGH locus localizes to the perinucleolar region in both B-cell lymphomas [in situ hybridization (3D-FISH) to the Fest system, the IGH locus visualized at successive stages of B-cell maturation was indeed found to associate with the nucleolus concomitantly with SHM and CSR, a time when the IGH gene locus underwent DNA damage while interacting with perinucleolar AID.In mice, the nuclear compartmentalization of the productive and non-productive position –20. Thisbination –20. Howein vitro . In thisxpressed , 23. In ymphomas  and nuclymphomas . ApplyinIGH gene loci was studied at the various steps of B-cell differentiation recapitulated in vitro in the Fest system. 3D-FISH images were produced and computer analyzed as previously described [0 in naïve B-cells. Contrasting with murine B-cells where the non-productive allele has been reported to lie in the peripheral heterochromatic region of the nucleus [The radial distribution of the human escribed . In orde nucleus –20, on aIGH gene loci colocalized with heterochromatin as previously reported in murine cells [IGH loci relative to constitutive heterochromatin as revealed by staining with an antibody directed at histone H3 trimethylated on lysine 9 (H3K9me3). The corresponding fluorescence profiles were extracted on single confocal section images. Calculated at each stage of differentiation as described in materials and methods, the Pearson's coefficients of colocalization between IGH and H3K9me3 were constantly negative . Again this was particularly striking in plasmocytes  than the nonproductive (~30%) IGH allele (data not shown).AID is the enzyme crucial for SHM and CSR of immunoglobulin genes  which coe Figure . We nexti Figure . As descex vivo system, events occurring in lymph nodes are recapitulated with specific stimuli activating B-cells prior to inducing SHM and CSR. We used 3D-FISH in combination with immunofluorescence staining to explore the kinetics of nuclear positioning of the two IGH gene loci in normal B-cells isolated from peripheral blood and induced to activate for 5 to 6 days in vitro. We did not observe any major difference between the productive and non-productive IGH alleles which exhibited a somewhat variable positioning from the center of the nuclei towards their periphery at all stages investigated until Day4. Despite this heterogeneity, the pattern of IGH localization changed at Day5/6 with a statistically significant movement towards the center of the nucleus for both the productive and non-productive alleles. This more central localization of the two IGH alleles was even more evident in plasmocytes. This lack of overt difference between the two IGH alleles in this human system contrasts with the murine situation where the non-productive IGH allele, but not its productive counterpart, has been reported to associate with peripheral heterochromatin [IGH gene loci.Somatic hypermutation and class switch recombination depend upon the action of a highly mutagenic enzyme, AID, whose activity creates double strand breaks within immunoglobulin genes in differentiating B-cells. It is therefore not surprising that AID be expressed at a very low level which is one way to prevent off-target activities which would prove highly deleterious through mutations, translocations and possibly cell death , 30. Anohromatin –20. HereIGH loci has clearly evidenced the variability and mobility of these genes crucial for the physiology of differentiating B cells. Interestingly, in non-lymphoid cells, the IGH locus forms a peripheral lamin-associated domain (LAD) [vice versa during cell differentiation. Indeed, their relocation towards transcription factories occurs by extrusion of decondensing chromatin loops into interchromosomal spaces where they can intermingle with neighboring chromosome territories [IGH locus is essential for both SHM and CSR as it is required for AID to function through deamination of single-stranded DNA [IGH gene loci are associated with recombination events taking place in specific nuclear compartments.Still, our analysis of the nuclear positioning of the two in (LAD) . Their rin (LAD) . It is kritories . In the nded DNA . We thusIGH gene locus has been reported as belonging to so-called nucleolus-associated domains (NADs) [IGH gene locus associates with the nucleolus in lymphoid cells in specific association with recombination events. The main function of the nucleolus is to transcribe rRNA for ribosome biogenesis but it is also implicated in the cellular response to stress and in the regulation of the cell cycle J recombination in the case of the RAG1/2 enzymes or at the later AID-dependent step, have been shown to accumulate in the nucleolus , 23. Mors (NADs) . We inteiewed in . As protucleolus , 23, it A breaks , we obseive loci . This is alleles . Our res0; CD19+CD27-) were purified from peripheral blood mononuclear cells by depletion with magnetic beads . Then the cells were activated in RPMI 1640 (Invitrogen) supplemented with 10% FCS and antibiotics (Invitrogen). Purified B-cells were cultured at 7.5х105 cells/ml in 24-well plates and stimulated during 4 days with 2 µg/ml F(ab’)2 Fragment Goat Anti-Human IgA+IgG+IgM (H+L) , 50 ng/ml recombinant human soluble CD40L associated with 5 µg/ml cross-linking Ab , 2.5 µg/ml CpG oligodeoxynucleotide 2006  and 50 U/ml recombinant IL-2 . To initiate plasmablast generation, the cells were harvested on Day4, washed, and seeded at 4 × 105/ml with IL-2 (50 U/ml), IL-4 (10 ng/ml), and IL-10 (10 ng/ml) (R&D Systems). Mature plasmocytes were isolated from peripheral blood using the CD138+ Plasma Cell Isolation Kit (Miltenyi Biotech).Peripheral blood cells from healthy volunteers were obtained from the French Blood Center. Naive B cells  B cells proliferate like in primary follicle and to the Day4 usually triple in number like in the Dark Zone of germinal center, and at the Day5/6 the cells display a transition of centrocytes to the Light Zone of germinal center with maximal AID expression.The  centers . The in 2 in a humidified atmosphere at 37°C. The AID expression was stimulated by addition of 20 ng/ml IL-4 as described elsewhere [The Burkitt Lymphoma BL2 cell line expressing AID-GFP fusion protein was grown in suspension in RPMI-1640 medium, supplemented with 10% complement-inactivated fetal calf serum, L-glutamine (2mM), penicillin (100 U/ml) and streptomycin (100 mg/ml) in 5% COlsewhere  and the IGH locus and RP11-259B19 for the J/D region. The probes were purchased stained from Blue Gnome . After probe hybridization, slides were washed according to the manufacturer's protocol. Nucleoli where detected using mouse anti-B23 and anti-C23 antibodies  and chicken anti-mouse Alexa 647 . Active RNA-pol II was detected using rabbit anti-RNA pol II antibodies (Active motif) and goat anti-rabbit antibodies. Heterochromatin was detected using rabbit anti-H3K9me3 antibodies (Active motif) and goat anti-rabbit secondary antibodies.Cells were immobilized on Cell-Tak -coated glass coverslips. The slides were then treated as described previously to preserve their 3D structure. Denatured nuclei were hybridized overnight with denatured probes. The probes used in this study were RP11-346I20 that recognizes the constant region of the http://rsb.info.nih.gov/ij/).Nuclei were scanned with an axial distance of 100 nm using a laser scanning confocal microscope . Stacks of gray-scale two-dimensional images were obtained with a pixel size of 47 nm. Displayed overlays of confocal images were processed with ImageJ  and reverse transcribed into cDNA with Superscript II (Invitrogen). Quantitative RT-PCR (qRT-PCR) was performed using the TaqMan Universal Master Mix and assays-on-demand from Applied Biosystems . Gene expression levels were quantified using HPRT1 as endogenous control. The 2 exp(−ΔΔCt) method was used to determine the relative expression of AID.The human samples were obtained in accordance to the National legislation.


More than 50,000 adult and cord blood samples were collected in Tempus tubes and stored at the Norwegian Institute of Public Health Biobank for future use. In this study, we systematically evaluated and compared five blood-RNA isolation protocols: three blood-RNA isolation protocols optimized for simultaneous isolation of all blood-RNA species ; and two protocols optimized for large RNAs only . We estimated the following parameters: RNA quality, RNA yield, processing time, cost per sample, and RNA transcript stability of six selected mRNAs and 13 miRNAs using real-time qPCR.Whole blood samples from adults (n = 59 tubes) and umbilical cord blood (n = 18 tubes) samples collected in Tempus tubes were analyzed. High-quality blood-RNAs with average RIN-values above seven were extracted using all five RNA isolation protocols. The transcript levels of the six selected genes showed minimal variation between the five protocols. Unexplained differences within the transcript levels of the 13 miRNA were observed; however, the 13 miRNAs had similar expression direction and they were within the same order of magnitude. Some differences in the RNA processing time and cost were noted.Sufficient amounts of high-quality RNA were obtained using all five protocols, and the Tempus blood RNA system therefore seems not to be dependent on one specific RNA isolation method.The online version of this article (doi:10.1186/s13104-016-2224-y) contains supplementary material, which is available to authorized users. Blood-based biobanks such as the NIPH Biobank at the Norwegian Institute of Public Health (NIPH), and multi-center studies, increasingly incorporate studies identifying candidate mRNA and microRNA (miRNA) expression profile based biomarkers for a wide range of disorders. Identification of biomarkers in an easily accessible and minimally-invasive biological sample such as blood would be a valuable complementing tool for diagnostics and prognostics of different types of diseases. The strong stability of miRNAs in circulating blood and their role as key regulators of almost every biological process  suggestsThe Norwegian Mother and Child Cohort Study (MoBa) is a prospective population-based pregnancy cohort study conducted by the NIPH. Participants were recruited from all over Norway from 1999 to 2008, and the cohort now includes more than 114,500 children, 95,200 mothers and 75,200 fathers . BiologiRecently, we have systematically evaluated a blood-RNA isolation protocol for blood samples collected in the Tempus tubes using Tempus 6-port RNA isolation kit (Life Technologies) on a 6100 Nucleic Acid Prep Station , 20. ThiCDKN1A, FOS, IL1B, IL8, MYC, TP53) and 13 miRNAs  selected based on our previous studies . The ΔΔCq values were generated by subtracting the ΔCq-value for the reference samples  from the ΔCq-value for the samples . For miRNA data, the target miRNAs were normalized by the average of three stably expressed reference genes ; this is given by ΔCq; where ∆Cq (sample) = Cq (target miRNA) − Cq (reference snRNAs). The ∆Cq values were then presented as normalized expression (NRQ = 2Cq−∆). The NRQ values were then log2-transformed in order to make the values symmetrical around zero. The reference gene stability was evaluated and results are presented in Additional files The quantification cycle , followed by post hoc Tukye’s HSD (honest significant difference) tests to allow for multiple comparisons or by non-parametric Kruskal–Wallis test. Normal distribution and equality of variances were evaluated using the Shapiro–Wilk normality test and the Levene’s or Bartlett test of homogeneity of variance. The correlations of the log2-NRQ values of the 13 miRNAs between the three RNA isolation protocols  were analyzed by Pearson or Spearman statistics and the regression lines were generated using GraphPad Prism 5.0 . Statistical analyses were performed using the R statistical programming environment (version 3.1.1), and results with p < 0.05 were accepted as statistically significant. The data are presented as mean ± SE. The coefficient of variation (CV) of the non-normalized raw Cq-value for each gene was calculated by dividing the mean Cq-value with the standard deviation. CV, expressed as a percentage, was used for computing the degree of variation in the average Cq-values of the RNA isolation protocols.Statistical analysis of RNA yield, purity, integrity and ∆


Numerous studies suggesting the relation between self-rated health (SRH) and depression have been reported using different measures. Therefore, we attempted to determine the difference in a depressive scale based on the different ways of measuring health between global SRH  and age-comparative SRH (SRH-age). Then, the combined effect of SRH-global and SRH-age on depressive symptoms was further investigated.Data from the Korean Longitudinal Study of Ageing (KLoSA) from 2008 to 2012 were analyzed. We divided the SRH-global and SRH-age into three levels—high, middle, and low—and combined each into nine new categories (SRH-combi). The Center for Epidemiologic Studies Depression Scale-10 Korean edition was used as the dependent variable.b = 0.654, p < 0.001) and middle SRH-age  showed association with higher CESD scores. Participants with high SRH-global × low SRH-age also had higher scores  compared to the “middle SRH-global × middle SRH-age” reference group. In contrast, among the middle  and high SRH-global  groups, participants with superior SRH-age had statistically lower CESD scores than the reference group.A total of 8621 participant were enrolled at baseline. Individuals with lower SRHs-age compared to SRH-global tended to be more vulnerable to depressive symptoms. Low SRH-global with low  contains supplementary material, which is available to authorized users. Major depressive disorder (MDD) contributes the significant burden of diseases in developed countries, and there will be further increases –3. AccorIn addition, the Republic of Korea has become a rapidly aging society. As a result, geriatric depression has also emerged as a major social issue. It is widespread and affects at least one in six patients treated in general medical practice and an even higher percentage in hospitals and nursing homes. Depression later in life has serious consequences, including distress among patients and caregivers, which is amplified by disability associated with medical and cognitive disorders of later life, increased health care costs, and increased mortality related to suicide and medical illness. In fact, in 2011, the age-standardized suicide mortality rate in Korea was 33.3 per 100,000 individuals, the highest among all OECD countries .Thus, it is important to identify the determinants associated with depressive symptoms as early as possible. In fact, numerous studies suggesting the relation between self-rated health (SRH) and depression have been reported , 6–8. SRThe questions for measuring SRH could be classified according to three main categories. The first is a non-comparative SRH, which is usually measured by asking respondents whether they would rate their health as excellent, good, fair, poor, or very poor. The next is an age-comparative SRH measured by asking respondents whether they would rate their health status as better, the same, or worse if compared to that of other people their age. The last is a time-comparative SRH, in which respondents are asked to rate their health compared to how it was at a given time in the past.  The threWe used data from the Korean Longitudinal Study of Ageing (KLoSA) from the second panel survey in 2008 to the fourth in 2012. A basic survey for KLoSA has been conducted every even-numbered year starting in 2006, mainly using the same survey categories regarding social, financial, and health. The population of KLoSA includes, in principle, all adults aged 45 and over. Many other surveys of elderly people in other countries only include the population aged 50 and over. In contrast, Korea experienced a financial crisis in the late 1990s, and career changes in the population of middle-aged individuals in their late 40s became an important social issue. Therefore, KLoSA decided to extend the population to include those aged between 45 and 49. The KLoSA used the Computer Assisted Personal Interviewing (CAPI) survey method. Because age-comparative SRH was not included in the first survey conducted in 2006, we defined the starting point as the second wave in 2008.The institutional review board from the Graduate School of Public Health, Yonsei University, approved this research . Since we used the national public opened data with de-identification and designed retrospective cross-sectional study, we did not seek informed consent for participation. However, KLoSA initially explained the aim of survey and collected informed consents from participants at baseline.The CESD was created in 1977 by Laurie Radloff  and reviThese factors include age, marital status, living area, education, and economic situation. Age group was carefully classified according to four categories: 54 or below, 55 to 64, 65 to 74, and 75 or above. Living area was divided into three levels: rural area, small to medium city, and metropolitan. Educational level was classified according to four levels from elementary school to college or over. The household heads provided their annual household income level. We then divided the income level into four categories based on the quartile results: Low, Low-Middle, Middle-High, High.These factors included whether they performed regular exercise, the number of chronic diseases, cancer history, the proportion of health expenditure in household income, type of medical security system, and whether they joined private health insurance. The number of chronic diseases was divided into four levels: none, one, two, three or more. Excessive health expenditure was defined as the proportion of health expenditures in household income and classified according to four levels from 5 % or below to 20 % or over.We also included the type of medical security system and whether they joined private health insurance to adjust the effect of security for health on depression. In Korea, the medical security system is classified as national health insurance (NHI) or medical aid. People can qualify for medical aid if their single-family household income is < $600 per month; otherwise, they have mandatory NHI. Those who have NHI based on employment pay a monthly insurance premium according to their annual salary, and people who are self-employed pay for their premium based on the value of their property.There are two types of private health insurance in Korea , 24. TheI.“How would you rate your general health status?” Reply alternatives were Excellent, Quite good, Neither good nor poor, Quite poor, and Poor .II.“Now I’m going to ask you about life satisfaction. Please answer how satisfied you are with the following compared to people of your own age. How satisfied are you with your health?” The answer was measured by a continuous variable from 0 to 100 by units of ten. In other words, Zero meant absolutely dissatisfied and 100 meant absolutely satisfied. To make a comparable study design, we classified this according to five categories as Excellent (90 to 100), Quite good (70 to 80), Neither good nor poor (40 to 60), Quite poor (20 to 30), and Poor (0 to 10) (referred to subsequently as SRH-age).III.To measure the combined effect between SRH-global and SRH-age, we re-categorized both health status variables as follows: the health status of participants was defined as High (who answer Excellent and Quite good), Middle (Neither good nor poor), or Low (Quite poor and Poor). We then made another health status variable for the combined analysis (referred to subsequently as SRH-combined).  and other covariates  were initially analyzed with product-moment correlation. As a second step, multiple linear regression analyses  were used separately for the different SRHs with CESD as the dependent variable, and the variables were included in the factors as independent variables. To compare the goodness of fit among three different SRHs, Quasi-Akaike Information Criterion (QIC) was also applied. In general, the lower value was relatively better than the others. Statistical analyses were performed using SAS, version 9.3 . Significant differences are indicated according to the following: * P < 0.05 and ** P < 0.001.We evaluated both the separate effects of SRH-global and SRH-age and the combined effect of both variables. For analysis of combined effect, we selected the “middle SRH-global × middle SRH-age” group as reference. Differences in CESD-mean by each variable were tested using a Table According to the SRH-global, there were 2537 participants (29.4%) with ratings of Low, 3119 (36.2%) with ratings of Middle, and 2965 (34.4%) with ratings of High at baseline . In contrast, the estimates for CESD-10 scores were decreased when both SRH variables were high, although there was statistical difference only in SRH-age  and not SRH-global .Before the multivariate analysis using SRH-combined, we first performed multivariate analyses using SRH-global and SRH-age with three levels Table . Accordib = 0.654, p < 0.001) and middle  SRH-age showed association with the increased CESD score with statistically significant difference. Interestingly, participants with high SRH-global × low SRH-age also had a higher CESD score  compared to the reference group “middle SRH-global × middle SRH-age.” In contrast, participants whose SRH-age was superior to their SRH-global had significantly lower CESD than the reference group among the middle  and high SRH-global  groups Fig. To determine the combined effect of SRH-global and SRH-age on depressive symptoms, we used another health status variable, SRH-combined Table . Accordib = 0.119, p = 0.029) had a slightly increased CESD score compared to married participants. In terms of living area, participants living in metropolitan areas  had significantly lower CESD scores than those in rural areas. In educational level, participants with college education or over  only showed decreased CESD scores compared to those with elementary school education. The employees  among the participants demonstrated significantly negative association with CESD.Regarding the other covariates, singles  showed association with low CESD scores, and participants in households in which medical expense/total income was 20 % or above presented significantly increased CESD scores  compared to the reference participants with household expenses for medical cost less than five percent of total house income.Compared to those with medical aid, participants with medical insurance  had high CESD scores compared to the reference “middle SRH-global × middle SRH-age” group  and middle SRH-global × low SRH-age  indicated that association with higher CESD scores. However, there was no statistical difference in women in the “high SRH-global × low SRH-age” group regardless of the positive estimate .Male participants rating low SRH-age matched with all kinds of SRH-global . In the “middle SRH-global × the high SRH-age” group [MH], all quartile groups had lower CESD scores compared to the reference group . Interestingly, only the middle-low quartile group in the “middle SRH-global × the low SRH-age”  and “high SRH-global × the low SRH age”  categories showed statistical differences  to 10 (“very good”). Although this scoring system was different from that used in the two previous studies, it was the same method to our measurement of SRH-age. Therefore, when we put all these results together, it is clear that SRH could clearly reflect depressive symptoms or be useful and efficient indicators for the depressive disorder.A cross-sectional survey of a nationally representative sample of Israeli persons aged 45 years or older showed that individuals aged 65 years or older were more likely to give a more favorable rating of their health when asked to compare themselves with people of the same age and sex than when the rating was made without a comparison instruction . HeckhauFirst, we could not expand this result to all age groups. Since this KLoSA panel was designed to determine the characteristics of families with older persons aged 65 or over, the participants here could be left-truncated at the baseline.Second, we could not evaluate whether there is a real effect of SRH-age changes with age. As previous studies conducted in other countries mentioned that SRH-age had greater association with older than with younger people, it was necessary to evaluate this using other national data in Korea. However, it was impossible that KLoSA is the only Korean national survey using SRH-age until now.Third, SRH could differ from one culture to another, even if the questions are the same , 46. ForFourth, we could not generalize the association of SRH and various health outcomes. Although SRH is a good indicator for predicting mortality rate, mortality is not as same as depressive symptom in this research. Thus, we clearly mention that it should be differentiated when you compare the results to other health outcomes like comorbidity or mortality.Finally, SRH-age is not exactly the same as in other studies. Other studies , 27 measThere are several limitations in this study.Although global SRH is a well-known indicator for estimating depressive disorder, it is suggested that use of both general SRH and age-comparative SRH would be more powerful when considering analyzing depression. In conclusion, individuals with lower SRHs-age compared to SRH-global tend to be more vulnerable to depressive symptoms.


Hevea brasiliensis. This physiological syndrome involves the agglutination of rubber particles, which leads to partial or complete cessation of latex flow. Latex harvesting consists in tapping soft bark. Ethephon can be applied to stimulate latex flow and its regeneration in laticifers. Several studies have reported transcriptome changes in bark tissues. This study is the first report on deep RNA sequencing of latex to compare the effect of ethephon stimulation and TPD severity. Trees were carefully selected for paired-end sequencing using an Illumina HiSeq 2000. In all, 43 to 60 million reads were sequenced for each treatment in three biological replicates . Differentially expressed genes were identified and annotated, giving 8,111 and 728 in response to ethephon in slight TPD trees and in ethephon-induced severe TPD trees, respectively. A biological network of responses to ethephon and TPD highlighted the major influence of metabolic processes and the response to stimulus, especially wounding and jasmonate depression in TPD-affected trees induced by ethephon stimulation.Tapping Panel Dryness (TPD) affects latex production in  Hevea brasiliensis accounts for more than 40% of rubber consumption worldwide. With more than 10 million hectares, rubber cultivation and its industry play an important socio-economic role in rubber producing countries. Natural rubber is synthesized in laticifers, which form an articulated network of anastomosed latex cells. Latex containing natural rubber is collected by tapping the bark of rubber trees. Latex is the cytoplasm of laticifers. Ethylene induces several metabolic pathways in latex. For certain Hevea clones, the application of ethephon, an ethylene releaser, stimulates latex regeneration between two tappings and latex flow after tapping, hence latex production. The growing demand for natural rubber prompts farmers to use quick-starter clones and intensive harvesting systems, which have led to increasingly large losses in rubber production. The physiological syndrome called Tapping Panel Dryness (TPD) is responsible for an estimated 12 to 20% loss in rubber production1, which could increase in a context of climate change.Natural rubber produced by 2. A lutoid is a single-membrane microvacuole with lysosomal characteristics. Lutoidic NAD(P)H oxidase is a major source of superoxide anion species in latex . This production of reactive oxygen species (ROS) induces peroxidatic degradation of the unsaturated lipids of the membrane. Such lutoid instability leads to the release of lutoid proteins in cytosol and promotes rubber particle agglutination3. Under exacerbated conditions, an irreversible type of TPD, called brown bast (BB), occurs. This form is related to deformation of the bark due to thylosoid formation, lignified gum, and abnormal division of parenchyma cells, and may be related to a cyanogenesis process5. These two types of TPD were recently called ROS-TPD and BB-TPD6. TPD, trunk phloem necrosis, brown bast, dry bark, etc. show the same anatomical symptom4. However, these syndromes might be related to different stress origins such as rootstock-scion incompatibility7, soil compaction, and environmental or harvesting stress8.Environmental and harvesting stresses can lead to oxidative stress in laticifers and consequently to TPD inductionHbMyb1, HbTOM20 and HbTCTP116. Differential transcript abundance was observed for twenty-seven candidate genes, related to TPD occurrence, in latex and phloem tissues for ROS-scavenging, ethylene biosynthesis and signalling genes6. The technologies used in these previous studies led to partial identification of genes associated with TPD occurrence. More recently, the technology of RNA sequencing has opened up new perspectives for a full comprehensive analysis of TPD through a transcriptome comparison between TPD-free and TPD-affected trees. Given the stoppage in latex flow, deep sequencing of RNA has focused solely on bark tissues of severe TPD-affected trees. These analyses notably revealed a down-regulation of genes related to rubber biosynthesis17 as well as jasmonate production18. A few studies have attempted to analyse latex from early TPD-affected trees. The first one revealed post-transcriptional regulation with both RNA degradation and a shift in miRNA biogenesis19. The second suggested differential expression of proteins related to rubber biosynthesis, the reactive oxygen metabolism and cell apoptosis20.Numerous molecular studies have led to the identification of TPD-regulated genes, such as 6. High latex viscosity in a localized part of the bark reduces latex flow. This transient symptom concerns a small proportion of the tapping cut. In contrast, the ROS-TPD type resulting from the physiological fatigue of laticifers concerns a larger share of the tapping cut, which increases regularly over the tapping period and requires a tapping rest of several months for total recovery. Ethephon treatment accelerates the latex metabolism and induces earlier and greater TPD occurrence, especially for rubber clone PB 260 with a high latex metabolism6. Firstly, the effect of ethephon was analysed on slight TPD-affected trees. Secondly, slight and severe TPD-affected trees subjected to ethephon stimulation were compared. RNA sequencing was carried out in three biological replicates and a differential expression analysis was carried out. This study identified 728 differentially expressed genes associated with ethephon-induced TPD, 272 of which were specifically regulated by TPD and not by ethephon treatment. When ethephon-induced TPD became established, an overall decrease in gene expression was observed, except for genes related to the GO “stimulus response” term, particularly those related to the wounding and jasmonic acid pathways.This paper sets out to provide new insight into the molecular regulatory mechanism of ethephon-induced TPD in latex and to identify a set of differentially expressed genes associated with ethephon-induced TPD occurrence. The study identified a set of differentially expressed genes associated with TPD occurrence. Several earlier publications tried to study TPD, but at the last stage of TPD. They therefore only obtained 100% TPD-affected trees and had to study bark tissue. The novelty of our study is to carefully monitor the onset of the syndrome and manage to select trees with slight and severe TPD symptoms still able to produce some latex. Regular monitoring of the dry cut length (DCL) on the tapping panel revealed that all the trees had a variation in DCL valueLatex flows out from laticifer vessels after tapping soft bark. Latex drops appear instantly on the tapping cut. The dry cut length (DCL) was recorded just after tapping and before latex flowed along the cut. Most trees showed a partial DCL ranging from 0 to 100% Fig.  were fou21. Of the 86,941 contigs, 72,910 were previously annotated by BLASTX. Reads were counted for the 86,941 contigs.RNAs from the latex of non ethephon-treated trees (control), and both slight and severe ethephon-induced TPD trees were paired-end sequenced using an Illumina HiSeq 2000. In all, 43 to 60 million reads were obtained for each oriented TRUSeq library  were selected when their FDR adjusted p-value was lower than 0.05. In latex, 8,111 DEGs were detected in response to ethephon stimulation with a similar number of over-expressed (3883) and under-expressed  genes  of the read data was carried out for 8,111 DEGs. The PCA highlighted the variation between the three types of samples  , and “response to stimulus”  were overrepresented Fig. . For DEGTranscription factors are crucial regulators of gene expression. They were extracted from the two classes of ethephon-induced TPD treatments in Supplementary Data The comparison of slight and severe ethephon-induced TPD trees revealed a dramatic drop in the number of regulated transcription factors from 316 to 50 Table . The und28. With regard to TPD, some gene expression markers, such as HbMyb1, HbTOM20 and HbTCTP1, have been identified through differential display RT-PCR, microarrays and suppression subtractive hybridization29. The expression of six MYB genes was changed in ethephon-induced TPD-affected trees (one over-expressed and five under-expressed). In contrast, none of the other candidate genes was associated with TPD, neither HbTOM20 (2 contigs (CL1183Contig1 and CL1183Contig4) not expressed in latex) nor HbTCTP1, despite the high expression of one of the two contigs, CL1Contig21026 (107-142 reads) and CL1Contig7138 (41881-52466 reads). This variability in gene expression markers reveals that some candidate genes are associated with either clonal response or certain environmental or experimental conditions, and are not directly related to the biological process studied. In addition, these technologies provided a partial and a-priori view of transcriptome expression. More recently, high-throughput sequencing was used to describe global gene expression changes in bark18. Ethephon-induced TPD resulted in an overall decrease in gene expression, which was less in latex (631 DEGs) than in bark 18. The down-regulation of some genes related to rubber biosynthesis in bark18 was confirmed at protein level20. Bark tissue consists of several cellular types . The larger number of over-expressed DEGs in bark, compared to latex, suggests that either at least one bark tissue type other than laticifers might maintain a certain level of metabolic activity and gene expression, or the greater stringency in this study led to fewer DEGs being selected.This study reports on the first deep RNA sequencing in the latex of ethephon-induced TPD-affected trees. It was made possible by the selection of slight and severe TPD-affected trees producing latex, based on the monitoring of TPD occurrence in a large panel of trees for 3 years. Latex from TPD trees was collected just before the tapping cut became totally dry. Several other studies were previously carried out on latex from healthy trees only, notably to understand molecular mechanisms related to rubber production30. Rubber clone PB 260, studied in this paper, has an intrinsic high latex metabolism6. For this clone, ethephon application can accelerate TPD occurrence: more than 60% of ethephon-treated trees were severely affected by TPD after 15 months of stimulation, while a small number of trees had a partial dry cut without ethephon treatment6. Several reports have revealed the dramatic change in gene expression in latex from ethephon-treated trees using RNA sequencing (8111 DEGs for clone PB 260 (this study), 10216 DEGs for clone PR 10724, 509 DEGs for clone Reyan7-33-9723), and cDNA microarrays (163 DEGs31). A proteomics analysis of ethylene-stimulated rubber latex identified 143 and 404 ethylene responsive latex proteins using mass spectrometry from 2-DE and DIGE gels, and iTRAQ, respectively32. The present study actually revealed only 3,883 over-expressed DEGs, mostly involved in “cellular process”, “metabolic process”, “binding” and “catalytic activity”. Wang and co-workers concluded that ethylene improves carbohydrate catabolism and energy production but not rubber biosynthesis itself directly32, confirming rapid acceleration of the glycolytic pathway supplying precursors for the biosynthesis of IPP, as suggested by Liu and co-workers too24.Ethephon is applied to the tapping cut of certain rubber clones to stimulate latex metabolism and prolong latex flow, and consequently latex production34, a genome-wide analysis showed that the Hevea genome activated 8 genes encoding S-adenosyl-L-methionine synthase (SAMS), 14 genes encoding 1-aminocyclopropane-1-carboxylic acid (ACC) synthase (ACS) and 16 genes encoding ACC oxidase (ACO)23. Although 7 ACS and 8 ACO contigs were identified in the present RNA sequencing analysis, a small number of counts confirmed previous assumptions of low ethylene production in latex33. By contrast, latex cells are well-equipped for ethylene perception and signalling. A large number of ethylene receptors were expressed: 7 contigs in clone PB 260 23, while only 91 have been classified and functionally verified21. For rubber clone PB 260, 27 and 39 DEGs encoding ERF were identified in latex by Piyatrakul and co-workers21 and in the present study, respectively. In clone Reyan7-33-97, 21 DEGs were reported23. These results suggest a regulation of ethylene responsive genes in latex by ERFs in these rubber clones. Several members of three ERF groups  are highly expressed in latex21. HbERF-II and HbERF-VIIIa deduced proteins contained the repressor EAR motif. Their high expression under normal conditions suggests a certain negative control of ethylene response. By contrast, their lowering in TPD-affected trees is expected to activate ethylene responsive genes. This deregulation could be the source of latex cell dysfunction. Several members of HbERF-IX are assumed to be essential integrators of complex hormonal signalling pathways in Hevea. HbERF-IXc4 and HbERF-IXc5 are two orthologs of ERF1, which is at the crosstalk of the ethylene and jasmonate signalling pathways35. Lastly, ethylene stimulation induced several families of microRNAs38. This also suggests post-transcriptional regulation by ethylene.Ethylene biosynthesis and signalling pathways are particularly affected by ethephon stimulation. Following the first isolation of ethylene biosynthesis genes39. Regulation of MYC gene expression by ethephon was confirmed by this study as well as in TPD-affected trees. Several ethylene signalling transcription factors are also known to drive the response to jasmonate. The EIN3 gene, which encodes a primary transcription factor of the ethylene signalling pathway, is induced by both methyl jasmonate and ethylene, and might control JA/ethylene-responsive genes40. ERFs from groups II and VIII can also more specifically control JA-responsive genes. Contig CL17512Contig1 corresponding to HbERF-IIb2, an ortholog of ORA57 involved in the control of JA biosynthesis35, was expressed at a very low level. This confirms previous assumptions that the expression of most genes related to jasmonate synthesis is repressed in TPD-affected trees18.This study also revealed dramatic down-regulation of DEGs related to jasmonic acid (JA) stimulus, carbohydrate and wounding responses. Tapping induces mechanical wounding, which is responsible for jasmonate production. Several upstream regulators down-expressed during TPD occurrence may explain these results. For instance, MYC transcription factors involved in the activation of JA-responsive genes were strongly under-expressed by ethephon2. This study showed that ethephon stimulation and TPD severity respectively induced the under-expression of 113 and 34 genes, which are related to “oxido/reductase activity”  are highly expressed in latex21. In TPD-affected trees, the consumption of oxygen by NADH-cytochrome-c-oxidoreductase from lutoids is particularly high42. According to these authors, NADH-dependent oxygen consumption is inhibited by superoxide dismutase activity43. ERF-VII transcription factors are known to regulate hypoxia-responsive genes. HbERF-VIIa17, an ortholog gene of AtEBP, might play a role in the response to the accumulation of reactive oxygen species occurring during latex regeneration21.The involvement of oxidative stress in TPD was recently reviewedTo conclude, this study is the first high-throughput RNA sequencing in latex at the onset of ethephon-induced TPD. The overall differentially expressed genes associated with ethephon stimulation and the severity of TPD have been identified and a gene network has been proposed to address this issue. The depression in jasmonate response and ROS-scavenging systems were a common feature observed in latex (this study) and in bark (previous studies). Allelic variation in the sequences of gene expression markers associated with TPD might be exploited on already mapped and phenotyped segregating populations in order to identify the genetic markers associated with phenotypes related to latex production and TPD susceptibility.Latex was collected from 9-year-old trees of clone PB 260 at the Sembawa Research Centre belonging to the Indonesian Rubber Research Institute . Trees were tapped for three years using the S/2 d2 harvesting system  with or without application of 2.5% ethephon 12 times a year (ET 12/y). The dry cut length (DCL) was monitored after tapping for 3 years. Trees were categorized as slight- (<25% of DCL) or severe-TPD trees (>75%) according to the mean DCL for the last year of tapping. Nine trees were selected for further RNA sequencing: three slight-TPD trees under S/2 d2 (control), three slight-TPD trees under S/2 d2 ET 12/y, and three severe-TPD trees under S/2 d2 ET 12/y.44 by Duan and coll.36. Latex samples were thawed in a water bath at 50 °C and transferred to centrifuge tubes. After centrifugation for 30 min at 15,000 g at 20 °C, the aqueous fraction was transferred to a 13 mL-tube, then the volume was adjusted to 10 mL with extraction buffer containing 4 M guanidium isothiocyanate, 1% sarcosine, 1% polyvinylpyrrolidone and 1% ß-mercapto-ethanol. After homogenization, the tubes were kept on ice, then centrifuged at 10,000 g at 4 °C for 30 minutes. The supernatant was transferred to a new tube containing 3 mL of 5.7 M CsCl. Ultracentrifugation in a swinging bucket was carried out at 82,705 g at 20 °C for 20 hours. The supernatant and caesium cushion were discarded whilst the RNA pellet was washed with 70% ethanol. After 30 minutes of air drying, the pellet was dissolved in 200 µL of sterile water. Although DNA could not cross the caesium cushion for this centrifugation condition, a DNAse treatment was performed using TurboDNAse . DNA contamination was then checked by PCR amplification using primers of the Actin gene including the intron sequence. RNAs were conserved at −80 °C pending further analysis.For each selected tree, 6 mL of latex was collected in a 15-mL Falcon tube containing 6 ml of 2X alkaline fixing buffer  with constant manual mixing, and immediately deep-frozen in liquid nitrogen. Total RNAs were isolated using the caesium chloride (CsCl) cushion method adapted from SambrookThe quality and quantity of total RNA samples were checked using the Agilent Bioanalyzer and Quant-iT RiboGreen RNA Assay Kit, respectively. The sequencing technology used was an Illumina Hiseq 2000 . RNA-seq libraries were produced by the TruSeq_Stranded_mRNA_SamplePrep_Guide_15031047_D protocol  using 2 µg of total RNA. The RNA-seq samples were sequenced in paired-end (PE) mode with a sizing of 260 bp and a read length of 100 bases. Seven samples per Hiseq 2000 lane were analysed using individual bar-coded adapters, generating approximately 60 million PE reads per sample.45. The mapper Bowtie version 246 was used to align reads against the rubber clone PB 260 reference transcriptome21 . Reads were counted for the 86,941 contigs. The abundance of each contig was calculated by a local script which parses SAM files and counts only paired-end reads for which both reads map unambiguously one contig, removing multi-hits. According to this procedure, around 95% of PE reads were associated with a contig.Each RNA-seq sample followed the same pipeline of bioinformatics analyses from trimming to the counting of transcript abundance as follows. Read pre-processing criteria included trimming library adapters and performing quality control. The raw data (fastq) were trimmed by the fastx toolkit for Phred Quality Score Qscore >20, read length >30 bases, and the ribosome sequences were removed with the sortMeRNA tool47. All steps of the transcriptomic experiment, from growth conditions to bioinformatic analyses were stored and managed through the CATdb database48 (http://tools.ips2.u-psud.fr.fr/CATdb/) Project_ID NGS2014_07_Hevea according to the “minimum information about a high-throughput sequencing experiment” standards.Statistical analyses were carried out with R software (version 3.3.1) and the edgeR package (version1.12.0). Library sizes were normalized using the TMM method. A differential expression analysis was performed using an exact test based on negative binomial distribution using an empirical Bayes estimation of the dispersion, where data were filtered by the default mode proposed by edgeR: genes that did not have at least 1 read after a count per million in at least half of the samples were discarded. To control the FDR, raw p-values were adjusted. We considered as being differentially expressed, those contigs with an adjusted p-value under 0.05, fulfilling criteria for a robust RNA-Seq analysisA principal component analysis (PCA) and heatmap clustering analysis were performed using the R Mixomics and flashClust packages, respectively, after log transformation of the normalized count data. Data scaling and the Euclidean distance were calculated by the Pareto and Ward methods, respectively.Arabidopsis thaliana orthologs selected according to the best e-values. The At DEGs were implemented to perform gene ontology (GO) enrichment using the BiNGO plugin (Cytoscape© software)49 following the procedure by default. Briefly, over-representation of the biological process was assessed when compared to Arabidopsis thaliana whole annotation as the reference. A hypergeometric test was used as a statistical test, then multiple testing correction was applied using Benjamini & Hochberg False Discovery Rate (FDR) correction at the significant level of 0.05. The Bingo graph represents the over-represented GO category as nodes. Node size is proportional to the gene number related to the respective category. The colour of the nodes represents the significance of the over-representation, with a colour scale ranging from yellow at a p-value of 0.05 to dark orange at a p-value corresponding to 5 orders of magnitude smaller than the significance level (10−5 × 0.05).A BINGO network analysis was carried out using Cytoscape 3.4.0 for the DEG groups. DEGs were converted into their respective et al. 2002, http://www.ncbi.nlm.nih.gov/geo) ProjectID GSE101568.The RNA sequencing data have been submitted to the international repository GEO (Gene Expression Omnibus, Edgard R. Supplementary Data


N6-methyladenosine (m6A) is an abundant modification in messenger RNA and noncoding RNAs that affects RNA metabolism. Methyltransferase-like protein 16 (METTL16) is a recently confirmed m6A RNA methyltransferase that methylates U6 spliceosomal RNA and interacts with the 3′-terminal RNA triple helix of MALAT1 (metastasis-associated lung adenocarcinoma transcript 1). Here, we present two X-ray crystal structures of the N-terminal methyltransferase domain (residues 1–291) of human METTL16 (METTL16_291): an apo structure at 1.9 Å resolution and a post-catalytic S-adenosylhomocysteine-bound complex at 2.1 Å resolution. The structures revealed a highly conserved Rossmann fold that is characteristic of Class I S-adenosylmethionine-dependent methyltransferases and a large, positively charged groove. This groove likely represents the RNA-binding site and it includes structural elements unique to METTL16. In-depth analysis of the active site led to a model of the methyl transfer reaction catalyzed by METTL16. In contrast to the major m6A methyltransferase heterodimer METTL3/METTL14, full-length METTL16 forms a homodimer and METTL16_291 exists as a monomer based on size-exclusion chromatography. A native gel-shift assay shows that METTL16 binds to the MALAT1 RNA triple helix, but monomeric METTL16_291 does not. Our results provide insights into the molecular structure of METTL16, which is distinct from METTL3/METTL14. N6-methyladenosine (m6A) is the product of a dynamic and abundant modification in eukaryotic messenger RNA (mRNA) and noncoding RNAs (ncRNA)1 that affects RNA stability2, pre-mRNA processing3, microRNA biogenesis4 and translation efficiency5. Approximately three to five m6A sites occur in each mRNA molecule, predominantly within 3′-untranslated regions and near stop codons7. Most m6A sites lie within a highly conserved RRACH  sequence motif8 and are regulated by adenosine methyltransferases (‘writers’), m6A-binding proteins (‘readers’) and m6A-demethylating enzymes (‘erasers’)9.6A RNA marks are catalyzed by a heterodimeric ‘writer’ complex comprised of methyltransferase-like protein 3 and methyltransferase-like protein 14 (METTL3/METTL14), which specifically methylates adenosine within the RRACH motif with no obvious structural preferences10. Recently, methyltransferase-like protein 16 (METTL16) was confirmed to be an m6A RNA methyltransferase that modifies U6 spliceosomal RNA12 and the MAT2A mRNA encoding S-adenosylmethionine (SAM) synthase13. In addition, METTL16 also binds to ribosomal RNA, mRNA, and long ncRNAs, such as X-inactive specific transcript and the 3′ triple helix of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1)14. Unlike METTL3/METTL14, METTL16-dependent m6A marks do not occur within the RRACH sequence motif and they are found in introns and at intron-exon boundaries12. Preliminary studies suggest that METTL16 uses a combination of sequence and structure to recognize its RNA substrates11. Interestingly, one study has proposed that METTL16 has evolved an additional role in pre-mRNA splicing, allowing METTL16 to function as both an m6A ‘writer’ and ‘reader’11. As an m6A ‘writer’, METTL16 rapidly methylates the MAT2A mRNA in the presence of SAM, leading to intron retention followed by nuclear degradation11. When SAM levels are low, prolonged occupation of METTL16 on MAT2A mRNA enhances splicing of retained intron11.Most mEscherichia coli to human and they all possess an N-terminal methyltransferase domain17. As a SAM-dependent methyltransferase (SAM-MTase), METTL16 is predicted to have a highly conserved Rossmann fold18. In characterized MTases, the conserved Rossmann fold is composed of alternating β strands and α helices, forming a seven-stranded β sheet that is sandwiched between clusters of α helices. In general, the SAM-binding site is usually found in the N-terminal segment of the β sheet, whereas the substrate-binding site lies within the C-terminal segment19. Although MTases are structurally similar, they use a variety of mechanisms to specifically recognize their targets, such as oligomerization and unique structural elements. These unique structural elements include variable loop regions within the Rossmann fold and auxiliary domains within and/or flanking the Rossmann fold22.METTL16 homologs are found from S-adenosylhomocysteine (SAH) at 2.1 Å resolution. We analyzed the salient MTase features of METTL16_291 based on characterized SAM-MTases; this analysis highlights the unique attributes of METTL16_291 and contrasts it to the structural studies of METTL3/METTL14. Moreover, we investigated the oligomeric state of METTL16 and its ability to bind to the MALAT1 RNA triple helix.In this work, we present the structural analysis of human METTL16 based on two X-ray crystal structures of the N-terminal MTase domain (residues 1–291) of human METTL16 (METTL16_291): an apo form at 1.9 Å resolution and a post-catalytic complex with 6A RNA MTases bind to SAM and RNA, transfer a methyl group from SAM to adenosine, and then the methylated RNA and SAH products dissociate from the MTase  in the protein buffer. Including TCEP was necessary to prevent protein precipitation. The ‘3214576’ β sheet is packed between two clusters of α and 310 (η) helices  and various RNAs but obtained only a SAH-bound complex after soaking crystals with SAM. The presence of SAH, rather than SAM, was determined based on calculations of electron density maps . R82 forms a salt bridge with the carboxyl group of SAH. Moreover, six water molecules mediate hydrogen-bonding interactions between SAH and D108, I109, T111, S114, Y117, T132, Q162 and R230  that is characteristic of the SAM-MTase core . From this comparative analysis, we discovered that most METTL16-SAH interactions overlap  indicates that the sulfur atom location of SAH in our complex is unique, which may be a crystallization artifact resulting from an interaction between R82 and E217 of a symmetrically related molecule in the crystal lattice. Importantly, the conformation of SAH in METTL16_40–291/SAH, as preserved in other SAM-MTases, is properly oriented after a productive methyl transfer reaction. Thus, these structural snapshots suggest that METTL16_40–291/SAH represents a post-catalytic state that likely occurs before the state captured in METTL16_291/SAH.Next, we compared the SAH-binding sites of our METTL16_291/SAH structure and an unpublished X-ray crystal structure of METTL16 containing residues 40–291  amino and carboxyl groups of the homocysteine moiety, (ii) 3′-hydroxyl of the ribose moiety and (iii) N1 of adenine. Altogether, our structures indicate that METTL16 uses an extensive network of noncovalent interactions to facilitate binding of SAH and likely SAM as well.33 and found a positively charged groove covering an area of ~2000 Å2, which could interact favorably with the negatively charged phosphate backbone of RNA  is missing in our structure and may also contribute to substrate recognition. Third, the RNA substrate specificity of METTL16 is not yet clear. The m6A sites in U6 snRNA and MAT2A mRNA, two confirmed substrates, reside in single-stranded bulges flanked by double-stranded RNA36. The active site of METTL16_291/SAH can easily accommodate single-stranded RNA within a ~37 × 18 Å groove , in complex with an extrahelical adenosine acceptor  to examine the oligomerization states of both human METTL16 and METTL16_291. Our SEC data indicate that METTL16 exists as a homodimer because it elutes at a volume equivalent to a molecular weight of ~103 kDa, which is about twice the size of a single METTL16 polypeptide chain   Fig. . FurtherDa) Fig. . In contDa) Fig. . These ron Figs.  and S1. 14. Therefore, we used a native electrophoretic mobility shift assay (EMSA) to determine if METTL16 and METTL16_291 can interact with the MALAT1 RNA triple helix in vitro. Our results show that monomeric METTL16_291 (1 μM) does not bind to the MALAT1 RNA triple helix but METTL16 (0.5 µM dimer) does bind  and human METTL14  in complex with SAH22 onto SAH-bound METTL16_291. This comparative structural analysis revealed that METTL16_291 is similar to only METTL3 (rmsd 2.1 Å across 40 Cα atom pairs) and not METTL14  is the loop between αNC and αZ as well as N-terminal part of αZ in METTL16_291  RNA targets do not have a RRACH motif and (ii) majority of METTL16-dependent m6A marks are found in introns43. These findings might not be that surprising considering METTL16 knockdown accounts for a ~20% loss of the m6A methylome in 293A-TOA cells11. Nonetheless, METTL16, which is distributed throughout the nucleus of HeLa cells, interacts with a wide range of RNAs, including long ncRNA, mRNA, miRNA, rRNA, snRNA and snoRNA14. Validated m6A targets include U6 snRNA, whose methyl mark at A43 is apparently essential for spliceosome activity, and MAT2A mRNA; both RNAs are methylated by METTL16 in a UACm6_AGA sequence13. METTL16 also interacts with the MALAT1 RNA triple helix, which is 13 base pairs from a weak m6A signal near A8290 in a ACAm6_ACA sequence44. Thus, it will be interesting to determine if the MALAT1 RNA triple helix itself or adjacent regions are substrates of METTL16 because MALAT1 is a cancer-promoting long ncRNA45. Furthermore, our studies show that full-length METTL16 is required to bind to the MALAT1 RNA triple helix, suggesting that the C-terminal domain expands the RNA interactome of METTL16. Two regions of the C-terminal domain of METTL16 (residues 289–399 and 514–562) are conserved in vertebrates11 while the N-terminal MTase domain is conserved from E. coli through human , which methylates A1618 in 23 S rRNA15. Both METTL16 and RlmF can install m6A marks within the ACm6_AGR sequence15. Human METTL16 interacts with 18 S and 28 S rRNAs, which contain m6A marks at A1832 and A4220, respectively48. These marks occur within a GUAm6_ACR sequence, which would appear to be a suboptimal substrate for METTL3/METTL14 and maybe METTL16. Interestingly, the Am6_ACR motif found in rRNA also appears at A8290 in MALAT1 RNA. Another factor that may influence RNA substrate recognition and MTase activity is protein cofactors. Thus far, La protein, La-related protein 7, and methylphosphate capping enzyme have been identified as binding partners of METTL16 in a U6 snRNA-dependent manner12. Thus, more cellular, biochemical, and structural studies of METTL16 are necessary to elucidate its function at the molecular level.mRNA modifications, especially man Figs.  and S1. 6A RNA MTases by analyzing the ligand-binding sites and proposing a structural model of methyl transfer catalyzed by METTL16. Interestingly, METTL16 has an extensive, positively charged groove to bind RNA and this groove is largely comprised of structural elements unique to METTL16, suggesting this area may contribute to the RNA substrate specificity of METTL16 that is distinctly different from METTL3/METTL14. Moreover, our SEC and SEC-SAXS data show that METTL16 is a homodimer; however, the N-terminal domain of METTL16 is a monomer, indicating that the C-terminal domain facilitates protein dimerization. Homodimeric METTL16 is required to bind to the MALAT1 RNA triple helix while monomeric METTL16_291 is sufficient to methylate U6 and MAT2A RNAs11. Hopefully, future studies will reveal the biochemical and structural basis of the unique RNA substrate specificity of METTL16 and its roles as an m6A ‘writer’ and ‘reader’.Our work expands the structural knowledge of human m49. The expressed METTL16_291 and METTL16 proteins have an N-terminal His6-tag followed by a Tobacco Etch Virus (TEV) protease cleavage site and a Ser-Asn-Ala linker, which is encoded in the pMCSG68 vector. The sequence of the gene was confirmed by DNA sequencing (University of Notre Dame Genomics Facility).The sequences encoding human METTL16_291 (residues 1–291) and METTL16 (residues 1–562) [UniProt ID: Q86W50] were amplified by PCR using a pcDNA3-METTL16 plasmid and the following primers: Forward: 5′-TACTTCCAATCCAATGCCATGGCTCTGAGTAAATCAATGCATGCAA-3′ and Reverse: 5′-TTATCCACTTCCAATGTTACTAATCATAAAAACTCCAAGCTAAGGCC-3′ for METTL16_291; Forward: 5′-TACTTCCAATCCAATGCCATGGCTCTGAGTAAATCAATGCATGCAA-3′ and Reverse: 5′-TTATCCACTTCCAATGTTACTAGTTAACTGCAACAAGCCTGAAAATTTG-3′ for METTL16. Then, the DNA insert was incorporated into the pMCSG68 vector  using a ligase-independent cloning methodE. coli (Agilent Technologies) cells grown in 2 L LB media supplemented with 150 μg/ml ampicillin. The bacteria were cultured with shaking at 190 RPM at 37 °C until the OD600 exceeded 1.0 (~4 h). Afterwards, cultures were chilled to 18 °C, and protein expression was induced by the addition of 0.5 mM isopropyl-D-thiogalactopyranoside for 18 h. Cells were harvested by centrifugation at 5,000 x g for 15 min at 4 °C, resuspended in ice-cold binding buffer  and stored at −80 °C.Protein overexpression was carried out in BL21 Gold 6-tagged protein was eluted by gravity with 20 ml elution buffer . The imidazole concentration was lowered to 20 mM and the His6-tag was cleaved with TEV protease  during dialysis for 18 h at 4 °C. The sample was reapplied onto a HisTrap HP resin to remove both the cleaved His6-tag and the His6-tagged TEV protease. Flow-through was collected and concentrated to 2.0 ml using Amicon ultra centrifugal filters . The protein was further purified by SEC  using size exclusion buffer (SEB) containing 25 mM HEPES pH 7.5 at RT, 100 mM KCl, 50 mM NaCl and 1 mM TCEP. The peak fractions of METTL16_291 and METTL16 were pooled and concentrated to 27 mg/ml and 10 mg/ml, respectively. A280 values were measured and molarity calculated using an extinction coefficient of 43890 and 63370 L/(mole·cm) for METTL16_291 and METTL16, respectively.Thawed cells were disrupted by sonication , using 4-s bursts with 26-s intervals for cooling in an ice/water bath. Lysate was cleared by centrifugation at 26,000 x g for 40 min at 4 °C. The supernatant was transferred to a 50-ml column packed with 3 ml of pre-washed HisTrap HP resin  and incubated for 5 min at 4 °C. The column was connected to a Vac-Man Laboratory Vacuum Manifold (Promega) to wash the protein-bound resin six times with 50 ml binding buffer for each wash. The His2HPO4, 45 mM NaH2PO4, pH 8.5. Crystals measuring approximately 0.3 × 0.3 × 0.2 mm appeared after 3 days. To obtain the SAH-bound METTL16_291 complex, 0.2 µl of 200 mM SAM solution  was added to the drop with mature crystals. Crystals were cryoprotected by soaking in crystallization solution supplemented with 25% ethylene glycol, vitrified in liquid nitrogen and stored until data collection. Diffraction data were collected under cryocooled conditions (100 K) at the Advanced Photon Source, Argonne National Laboratory, on beamline 22-ID. XDS50 package was used for data reduction. The statistics of the data collection and processing are summarized in Table Crystals grew at 19 °C using the hanging-drop method. The crystallization drop contained 4 µl METTL16_291 (27 mg/ml) and 2 µl of reservoir solution, which contained 1.3 M K51 and the X-ray crystal structure of human methyltransferase 10 domain containing protein . ARP/wARP52 was used to build the initial model, which afterwards was placed inside the unit cell with the ACHESYM server53. Manual fitting in the electron density maps was completed in COOT54 with iterative rounds of model refinement in Refmac55. Ten and four TLS57 groups were added for apo and SAH-bound METTL16_291, respectively, as recommended by the TLSMD server58. The refinement statistics are listed in Table The crystal structures of METTL16_291 were solved by molecular replacement using Phaser59. All samples  were diluted to ~21 µM in 100 µl total volume of SEB buffer supplemented with 1 mM MgCl2. RNA was denaturated at 95 °C for 1 min, snap-cooled on ice for 5 min and incubated at room temperature for 1 h. METTL16 and the MALAT1 RNA triple helix were mixed at a 1:1 ratio of 21 μM:21 μM and incubated at room temperature for 45 min prior to injection. Samples were injected onto a Superdex 200 10/300 GL column  pre-equilibrated with SEB buffer supplemented with 1 mM MgCl2 and resolved at a flow rate of 0.6 ml/min. Thyroglobulin (670 kDa), gamma-globulin (158 kDa), ovalbumin (44 kDa) and myoglobin (17 kDa)) were used as standards . Molecular weights of METTL16_291, METTL16, MALAT1 RNA triple helix and METTL16/MALAT1 RNA triple helix complex were calculated using a standard curve.The 94-nt MALAT1 RNA triple helix 5′-GGAAGGUUUUUCUUUUCCUGAGAAAACAACACGUAUUGUUUUCUCAGGUUUUGCUUUUUGGCCUUUUUCUAGCUUAAAAAAAAAAAAAGCAAAA-3′ was generated using the pHDV-MALAT1 ENE + A WT plasmid as described previously60. Samples pre-equilibrated in SEB buffer supplemented with 1 mM MgCl2 were injected onto the SEC column at the following concentrations: 30 μM METTL16, 25 μM MALAT1 RNA and METTL16 + MALAT1 RNA complex at a 2:1 ratio of 30 μM:15 μM. Data were recorded at room temperature on a PILATUS 3 1 M detector with 0.5-s exposures every 3 s at 1.0 Å wavelength. Sample cell-to-detector distance was 3.5 m, and the data range was 0.0163 Å−1 to 0.3666 Å−1 . Baseline scattering was averaged from data points measured before and after the protein peak, whereas sample frames corresponding to the elution peak were averaged to maximize the signal-to-noise ratio. Data were processed using the BioCAT beamline pipeline, which is based on ATSAS package61. Guinier analysis was performed in PRIMUS62 and GNOM63 for calculation of the radius of gyration (Rg) and the pair distribution function, P(r). Molecular masses are based on the calculation of low-resolution ab initio models with the use of DAMMIF64, DAMAVER65, DAMMIN66, and DAMFILT.Solution SAXS data were collected at the Advanced Photon Source BioCat, 18-ID beamline in the SEC-SAXS pipeline32P]ATP as described previously14. Immediately before incubating RNA with protein, RNA was denaturated at 95 °C for 1 min, snap-cooled on ice for 5 min, and incubated at room temperature for 1 h. Then, 2 nM 5′-[32P]-labeled MALAT1 RNA was mixed with 1 μM METTL16_291 or METTL16 in binding buffer  at room temperature for 45 min. The reactions were resolved using 5–6% native polyacrylamide gel , 1 mM MgCl2) and running buffer . Electrophoresis was run under an electric field of 8 V cm−1 for 2.5 h. Gels were visualized on phosphor screen and scanned using an Amersham Typhoon IP Biomolecular Imager .The MALAT1 RNA triple helix was 5′-end radiolabeled with [γ-41. Molecular illustrations were created using UCSF Chimera67, which also calculated rmsd values across pairs of Cα atoms within 3 Å radius for all superposition analyses. Surface electrostatic potential was calculated using the PDB2PQR server33. The amino acid sequences of METTL16 from 394 chordates were aligned using ClustalX268 and conservation calculated using the ConSurf server69.Disordered region of METTL16 was calculated by MobiDB serverCoordinates and structure factors were deposited in the Protein Data Bank (PDB): apo METTL16_291, PDB ID: 6b91; METTL16_291/SAH complex, PDB ID: 6b92.Supplementary Information