Evolving interest in comprehensively profiling the full range of small RNAs present in small tissue biopsies and in circulating biofluids, and how the profile differs with disease, has launched small RNA sequencing (RNASeq) into more frequent use. However, known biases associated with small RNASeq, compounded by low RNA inputs, have been both a significant concern and a hurdle to widespread adoption. As RNASeq is becoming a viable choice for the discovery of small RNAs in low input samples and more labs are employing it, there should be benchmark datasets to test and evaluate the performance of new sequencing protocols and operators. In a recent publication from the National Institute of Standards and Technology, Pine et al., 2018, the investigators used a commercially available set of three tissues and tested performance across labs and platforms.In this paper, we further tested the performance of low RNA input in three commonly used and commercially available RNASeq library preparation kits; NEB Next, NEXTFlex, and TruSeq small RNA library preparation. We evaluated the performance of the kits at two different sites, using three different tissues  with high (1 μg) and low RNA (10 ng) input from tissue samples, or 5.0, 3.0, 2.0, 1.0, 0.5, and 0.2 ml starting volumes of plasma. As there has been a lack of robust validation platforms for differentially expressed miRNAs, we also compared low input RNASeq data with their expression profiles on three different platforms .The concordance of RNASeq results on these three platforms was dependent on the RNA expression level; the higher the expression, the better the reproducibility. The results provide an extensive analysis of small RNASeq kit performance using low RNA input, and replication of these data on three downstream technologies.The online version of this article (10.1186/s12864-018-4726-6) contains supplementary material, which is available to authorized users. Due to their stability, clinical relevance, and functional role in disease pathogenesis, small RNAs have the potential to be important reporters of dysregulated cellular processes across a range of diseases –3. TheirBiological diversity in the number and types of small RNAs present in a sample type may also play a role in the performance of the kits and downstream validation. It has become increasingly evident that tRNA fragments, YRNA fragments and other species of small RNAs are important cellular regulators and are abundant in biofluids , 12–14. Validation of differentially expressed small RNAs, on other technologies, remains one of the most significant hurdles to its utility and clinical implementation. We assessed the performance of several platforms for validation of the RNASeq data, HTG EdgeSeq, Qiagen miRNome and Abcam FirePlex. Not surprisingly, we found that the performance of each platform correlated better when the expression level and fold change between the RNAs was larger.As was suggested in a recent publication by Pine et al., 2018 , sequenc. Figure We tested three commonly used small RNA sample preparation kits for next generation sequencing , on three different tissues , at two concentrations , and at two different sites (MGH and TGen). Figure 2a and bp-values calculated by Wilcoxon two-sided rank sum test with continuity correction for pairwise comparisons between the three kits is presented in Additional file 1: Table S2.The median percentage of reads aligned to the human transcriptome (after removing rRNA) for both 10 ng and 1 μg inputs were: Illumina TruSeq 74.12% (IQR: 70.7–79.63%), NEXTFlex 67.51% (IQR: 63.57–72.76%) and NEB Next 60.03% (IQR: 52.58–71.78%). Although there is no appreciable difference in the percentage of reads that were unmapped to the human transcriptome (~ 6.5%) and to UniVec contaminants (< 0.5%) across all three kits, the percentage of reads that mapped to human rRNA was significantly different . The NEXTFlex kit had the highest percentage of reads that were too short . A detailed sample list with the percentage of reads in each category can be found in Additional file p-values calculated by Wilcoxon two-sided rank sum test with continuity correction for pairwise comparisons between the three kits is presented in Additional file Reads mapped to the human transcriptome were further examined and the RNA categories/biotypes they mapped to are displayed in Fig. The effect of lowering the input amount of RNA 100 fold, from 1 μg to 10 ng, approximately doubled the percentage of reads that are categorized as too short (< 15 nts) for NEXTFlex (7 to 14%) and NEB Next (4 to 8%), while remained unchanged for TruSeq (2%)  and NEB Next . The percentage of reads that were too short (<15nts) for TruSeq 10 ng input samples were also different between the two sites . The percentage of input reads that map to the human transcriptome is significantly different between the two sites for the 10 ng samples for all three kits. Additional file DESeq2 [While there are no statistically significant differences between the sites for the 1 μg input amount of RNA for all three kits  indicating that the lower input amount of RNA does increase the variability in the read counts assigned to miRNAs.When differences between the kits and the sites are included, the correlation between the 1 μg and 10 ng inputs of a tissue never drops below 0.88 . With the tissue specificity of the miRNAs exceeding the technical variability of the kits, expectedly, the majority of the statistically significant differentially expressed miRNAs (absolute fold change > 2 and adjusted P < 0.05) between pairwise combinations of the three tissues are in common between the three kits .The fold changes of the differentially expressed miRNAs (between different tissues) detected from RNASeq, for each pairwise tissue comparison, were compared to the fold changes obtained from three validation platforms: Qiagen miRNome miRNA PCR array, HTG EdgeSeq, and Abcam FirePlex. Only miRNAs that were robustly expressed in RNASeq  with an absolute fold change > 2 and an adjusted 8 (256) read counts in sequencing correlate well (> = 0.9) with fold changes from qPCR. These data provide a guide for the expression threshold of miRNAs discovered via sequencing - for validation on high throughput qPCR platforms such as the Qiagen miRNome arrays.Aliquots of RNA from each tissue were sent to Qiagen and measured on the Qiagen miRNome arrays, which allows for assessment of 1066 miRNAs. Table DESeq2 (See Methods). Table P < 0.05) in both HTG EdgeSeq and RNASeq. On average, about 85% of the differentially expressed miRNAs in RNASeq are detected by HTG EdgeSeq with greater than 95% of the miRNAs being concordant with RNASeq. NEXTFlex, on average has the highest number of miRNAs that were concordant with HTG EdgeSeq . Of the miRNAs that were not significant in HTG EdgeSeq, but were significant in RNASeq, 82% were in agreement with RNASeq regarding the directionality of the fold change. Approximately 30% of the miRNAs significant by RNASeq, but not significant by HTG EdgeSeq, had an average expression < 100 counts in RNASeq.Aliquots of RNA from each tissue sample was sent to HTG for analysis on their HTG EdgeSeq platform. The HTG EdgeSeq library that we used for comparison to conventional sequencing surveyed 2085 human miRNA. The three tissues were sequenced with HTG EdgeSeq in triplicate with an input amount of 20 ng and one set was sequenced with an input amount of 10 ng. The number of miRNAs detected by HTG EdgeSeq at greater than 10 RPM was 946 ± 51 (mean ± standard error) and 325 ± 20 at greater than 100 RPM. There were no statistically detectable differences in the number of miRNAs detected between the 20 ng and the 10 ng inputs, therefore, all replicates were included as one analysis. PCA Fig.  demonstrP < 0.05 was used to determine significance. On average, ~ 70% of the miRNAs that were detected by FirePlex were concordant with RNASeq in both directionality and statistical significance. Of the miRNAs that were measured to be significantly differentially expressed by sequencing, but not by FirePlex , a significant proportion of them (87%) were in agreement with RNASeq regarding the directionality of the fold change. Table An aliquot of RNA from each tissue was sent to Abcam for testing on their FirePlex, hybridization and flow sorting platform. A total of 131 miRNA probes were included on a custom made FirePlex panel for the three tissues and the samples were run in triplicates. A full list of the probes and the number of tissues in which they were detected is presented in Additional file We next sought to compare low input RNASeq from a different sample type; plasma. We chose two kits; TruSeq  and the NEXTFlex kit (because it was the most different from the other two kits). We examined the effect of plasma input volume on sequencing results. Total extracellular RNA was isolated from five different volumes of a large pooled plasma sample, from 200 μL to 5 mL. Figure Investigators interested in small RNAs have a number of choices regarding which of the protocols and kits for RNA isolation, library sample preparation, and downstream validation platforms would be most suitable for their experiments. The findings of the miRNA Quality Control Study described significant differences among platforms for miRNA detection . We wereWe assessed the data quality from small RNASeq when reducing RNA input by 100× from 1 μg to 10 ng, and the correlation of the sequencing results from these 10 ng samples with downstream validation platforms. We used three different tissues, brain, liver and placenta to examine differences in RNA expression across three sequencing kits . We then took the differential expression patterns between tissues and assayed them on platforms that used qPCR (Qiagen miRNome assay) or miRNA hybridization strategies with different readouts, sequencing with HTG EdgeSeq and flow sort using Abcam FirePlex. To enable comparisons across the kits, all data analyses were performed identically on all samples.While each of the kits have inherent sequencing biases for a subset of detected RNAs  of the remaining miRNAs that were not statistically significant in HTG EdgeSeq have fold changes in the same direction as RNASeq. FirePlex too utilizes a probe-based miRNA enrichment strategy with no separate RNA isolation step. There is a reasonably high level of concordance with RNASeq (~ 70%), with the majority of the fold changes of miRNAs that did not reach significance, in the same direction as in RNASeq. However, it is important to keep in mind that all three technologies discussed here do not have the ability to distinguish sequence or length variations or isoforms of miRNAs (isomiRs) from the canonical mature miRNA.It appears that as the average expression of the miRNAs in RNASeq increases beyond 250–300 RPM, there is a good correlation with both Qiagen qPCR and HTG EdgeSeq as validation platforms. This is especially useful to be aware of when working with extracellular RNA from biofluid samples where the miRNA profiles are dominated by a few miRNAs with orders of magnitude more expression compared to the remaining miRNAs.We also assessed small RNASeq with plasma samples at different volumes. For research purposes, plasma sample volumes are typically limited so that many different assays and analyses can be performed using the same sample. If the RNAs related to a disease were identified and present in plasma for use as a diagnostic, acquiring larger volumes would not be a problem. However, we tested a range of volumes for RNA input consistent with what is used for research and discovery, from 200 μL to 5 mL. We found that the data across all volumes correlated very well. The smallest volumes tended to cluster slightly away from the larger volumes. However, it should be noted that these findings were from freshly isolated good quality plasma; whether these findings hold up for archival samples of variable age was not explored.There are a growing number of studies that have identified small RNAs as pivotal to normal cellular function and development of disease –22, yet All of these data are available and can be combined with the data from Pine et al., 2018  using thThe results indicate 4 important findings: 1) We recommend using the BiooScientific NEXTFlex kit, as it detects the largest number of miRNAs, owing to its 4 N random adaptor sequence that ameliorates ligation bias. However, there are challenges to implementing this kit with low input RNA. When using this kit, both sites found an increased amount of reads that were too short to be used in downstream analysis, the kit required more experience and familiarity before technicians were able to use it consistently. 2) Reassuringly, the biological difference between tissues for miRNAs exceed that of the difference in input RNA or between the three small RNA sequencing kits tested here. 3) The validation of findings from RNA sequencing experiments by other technologies such as qPCR, EdgeSeq and FirePlex is principally dependent on the expression levels in RNA sequencing; the higher the expression and fold change of the RNA, the more likely it will be validated in other technologies. 4) Small RNA sequencing from freshly extracted plasma samples can be carried out efficiently with input volumes as low as 200 μL with over 300 miRNAs detected at > 10 read counts. These data demonstrate for the first time, a multi-site quantitative analysis of miRNA discovery via RNA sequencing for low input RNA amounts and subsequent validation on three distinct platforms.The three total human RNA sources distributed were obtained from Ambion (Thermo Fisher Scientific): Human Brain Reference RNA (Cat. No. AM6050), Human Liver Total RNA (Cat. No. AM7960) and Human Placenta Total RNA (Cat. No. AM7950) Two concentrations of the total RNA were used in each library preparation. RNA was quantified in triplicate using Quant-iT Ribogreen RNA Assay kit, Low-Range protocol . We used 1 μg, which is the staring input recommended by each sequencing kit, and 10 ng. A large pool of plasma (30 mL) was used for comparison of kits and input volumes. Whole blood was collected from normal healthy volunteers in EDTA tubes, spun at 2500 rpm to separate plasma. Plasma was pooled, and 1 mL aliquots placed in tubes and stored at − 80 °C. The appropriate number of tubes were combined and isolated for each comparison. For example, for the 5 mL input volume, 5 aliquots were selected and the RNA isolated . The reagents were utilized with the following modifications. The 3′ adapter, 5′ adapter, Stop Solution, RNase Inhibitor and RT primer were diluted by 50% with water . During Small RNA libraries were generated using NEXTFlex Small RNA Library Prep Kit v2 (Cat #5132–03). The manufacturer’s instructions where followed through PCR amplification. The optional stop point was used post the RT reaction prior to clean up and PCR amplification. In regards to PCR amplification the 1 μg samples received 12 cycles and the 10 ng sample received 18 cycles. Following PCR amplification, the libraries where then run in a 6% TBE Gel for 30 min at 200 V and the between 150 to 170 bp were excised from the gels. At this point there was a divergence from the manufactures instruction, an ethanol precipitation was used in place of the recommenced bead purification. The resulting pellet of RNA was resuspended in 11 μl of ultra pure water.Small RNA libraries were generated using NEB Next Small RNA Library Prep Set for Illumina (NEB #E7330S). The manufacturer’s instructions where followed through with the PCR amplification. The PCR amplification was done under the parameters of 1 μg starting input received 12 cycles and the 10 ng input received 15 cycles. Following PCR amplification, the libraries where then run in a 6% TBE Gel for 60 min at 120 V and the between 140 to 160 bp were excised from the gels using a razor blade. Diverging from the manufacture protocol, gel pieces were fractured into smaller pieces and allowed to incubation on a rotator overnight in water. Then an ethanol precipitation was performed to precipitate the RNA and the resulting pellet of RNA was resuspended in 11ul of ultra pure water.. The difference in the percentages of reads assigned to the various RNA biotypes when the read length is restricted to <=50 nts for the Site 2 samples is shown in Additional file .Samples were quantified with the Agilent High Sensitivity DNA Kit . The peak for the sample was integrated from 120 bp to 160 bp to get the pMolarity of the product that will cluster on the sequencer. Samples with similar pMolarity were grouped on the same lane and pooled together to create a total of 8 unique pools containing 15 samples with different barcodes. These pools were then quantified with the Agilent High Sensitivity DNA Kit to get the final pMolarity for the pools. The pools were then denatured and clustered on a single read Illumina V3 flowcell . Site 1 flowcells ran on the Illumina HiSeq sequencing platform  for 50 cycles for with a 7 cycle indexing read. The samples from Site 2 were sequenced on an Illumina NextSeq 500 for single read 76 cycles. Site 2 sequenced to a read length of 76 nts, whereas Site 1 samples were sequenced to <=50 nts. To ensure a fair comparison between the RNA fragments detected by the two sites, only reads that were in the range of 15–50 nucleotides were considered. Density plots of the unrestricted read length distributions from both sites are presented in Additional file Samples were sent to HTG for sequencing. The HTG EdgeSeq miRNA Whole Transcriptome Assay was used to run the NIST RNA samples as described previously , with thSamples were processed using the FirePlex miRNA Assay (Abcam) as per the published protocol .In brief, for each tissue sample, 1 ng total RNA was loaded. The plate was incubated at 37 °C for 60 min with shaking. After rinsing twice with 1X Rinse A, 75 μL of 1X Labeling Buffer was added to each well. The plate was incubated at room temperature for 60 min with shaking. After two rinses with 1X Rinse B followed by one rinse with 1X Rinse A, a catch plate was added to the vacuum manifold and the filter plate put under constant vacuum. 65 μL of 95 °C RNAse-free water was added twice to each well to elute the ligated sample. 30 μL of this meltoff was added to a clean PCR plate and mixed with 20 μL PCR master mix. The mixture underwent 32 cycles of PCR amplification. Next 60 μL of Hybe Buffer was added back to each well of the original particles followed by 20 μL of the PCR product, and the plate was incubated at 37 °C for 30 min with shaking. After rinsing twice with 1X Rinse B followed by one rinse with 1X Rinse A, 75 μL of 1X Reporting Buffer was added to each well and the plate incubated at room temperature for 15 min with shaking. After rinsing twice with 1X Rinse A, 175 μL of Run Buffer was added to each well. The samples were then scanned on an EMD Millipore Guava 6HT flow cytometer. The flow cytometer output was analyzed with the FirePlex Analysis Workbench software.Samples were evaluated with real-time PCR using the miScript PCR System . Briefly, 10 ng of each sample was reverse transcribed and then preamplified (13 cycles) using the miScript Single Cell qPCR Kit, according to the manufacturer’s protocol. Following preamplification, the 25 μl amplification product was diluted to 127 μl using nuclease-free water. From there, 110 μl of the diluted product was diluted to a 330 μl final volume using nuclease-free water. Real-time PCR was then performed using the human miRNome . 100 μl of diluted product was applied to each of the three, 384-well plates associated with the miRNome. Real-time PCR was performed on a ThermoFisher instrument using the recommended miScript cycling parameters.Illumina HiSeq 2500 or Illumina MiSeq in the form of .bcl are converted to the fastq format using bcltofastq v1.8.4 and checked for quality to ensure the quality scores do not deteriorate drastically at the read ends. The adapters from the 3′ end are clipped using cutadapt v.1.10 [http://cutadapt.readthedocs.io/en/stable/guide.html). Reads shorter than 15 nts are discarded and after adapter trimming, the 3′ bases below a quality score of 30 are trimmed as well.The raw sequence image files from the t v.1.10  . For the EdgeSeq analysis, miRNAs were deemed to be statistically differentially expressed if they had an absolute fold change > 2 and an adjusted P < 0.05 (Benjamini Hochberg). For the FirePlex analysis, the data was log-transformed after adding a pseudo value of 1 and two-tailed t-tests were used to determine significance at a nominal P < 0.05.For both RNASeq and EdgeSeq, differential expression was conducted for all miRNAs that had expression in at least 25% of the samples across the two groups that were compared with the DESeq2  package Additional file 1:Table S1. Percentage of input reads aligned to the human transcriptome, human rRNA, UniVec contaminant sequences and discarded because they are too short (< 15 nts) and unmapped to the human transcriptome. Table S2. Median (Inter-quartile range) of percentage of input reads aligned to the human transcriptome, human rRNA, UniVec contaminant sequences. Table S3. Percentage of reads aligned to the human transcriptome to each RNA biotype for all samples. Table S4. Median (Inter-quartile range) of percentage of input reads aligned to different RNA biotypes between the three sequencing kits. Table S5. Median (IQR) of percentage of input reads aligned and comparison of input amount of RNA. Table S6. Median (IQR) of percentage of input reads aligned and comparison between the two sites for the two input amounts of RNA. Table S7. Median (IQR) of number of miRNAs greater than 10 counts detected in at least 25% of the samples between the two sites for the two input amounts of RNA. Table S8. Pearson’s and Spearman’s correlation coefficient by tissue, kit and input amount. Table S9. Kit specific miRNAs found in each tissue for each kit. The top 5 miRNAs for each tissue that have expression greater than 10 RPM in one kit, but less than 5 RPM in the other two are presented for each tissue and kit. Table S10. miRNAs included on the custom made FirePlex Panel. The columns denote the number of samples that had above detection-limit expression in each tissue. Table S11. Database of RNA biotypes used. (XLSX 89 kb)Additional file 2:Figure S1. Density plot of read lengths for all three kits and tissues respectively by site. Site2 sequenced to a length of 76 nts, whereas all of Site1 samples were sequenced to <=50 nts. Figure S2. Comparison of percentage of reads assigned to the various RNA biotypes for read length restricted to less than 50 nts versus read length = 76 nts. Site2 sequenced to a length of 76 nts. Figure S3. PCA plot showing that the BiooScientific NEXTFlex samples from Site2 cluster by themselves indicating a batch effect. Also, the figure on the right shows the number of miRNAs detected > 10 counts for the two input amounts 10 ng and 1 μg by Site for the BiooScientific NEXTFlex samples. (PDF 5418 kb)


In Japan, the number of elderly individuals living alone is continuing to increase as society ages. Although studies have considered quality of life, life expectancy, and gender differences in elderly individuals living alone, only a few have considered the health and lifestyle of these individuals. Therefore, we aimed to investigate the factors that affect the self-rated health of elderly individuals living alone to understand this group and how best to offer them support.We include 113 individuals. There was a significant difference (P < 0.05) in some characteristics , activities of daily living , and instrumental activities of daily living . The Japanese elderly population (age ≥ 65 years) has reached a record high of 33 million. This constitutes the highest number of elderly men and women as a proportion of the population when compared with other developed nations since 2005 . In tandThe increase in the number of elderly individuals is a recognized social concern, and in recent years, there have been several studies regarding elderly individuals living alone. However, most of these examined quality of life –6, the pIn this study, we aimed to clarify the factors associated with SRH among elderly individuals living alone, and which factors positively contribute to the basic understanding, so that we can support these individuals to have a better SRH. Therefore, we clarified the characteristics, activities of daily living (ADLs), and instrumental ADL (IADLs) of elderly individuals living alone, and how these relate to SRH.We conducted a cross-sectional study by face-to-face interviews. Study participants were divided into two groups based on SRH , and statistically significant differences in characteristics, ADLs, and IADLs were examined.Using systematic sampling, we randomly selected elderly individuals living alone within a rural area of Kagoshima prefecture (Town A). This region has an elderly population rate of 35.1%, which is above the national average. Individuals were included if they were aged ≥ 65 years, had lived alone for at least 1 year, and had no communication impairments. Individuals who agreed to participate in the study were visited at home and interviewed by the authors in the presence of a member of staff from the Senior Citizen’s Welfare Division of the local town hall.The interviews were performed using a structured questionnaire. The questions included the following: length of time spent living alone, marital status, certification of need for long-term care or support, the presence of chronic illness, frequency of hospital visits per month, the presence of emotional support, the presence of functional support, supporter characteristics, and SRH. Participants graded their SRH on a 4-point scale as good, quite good, fair, or poor. Those who responded “good” or “quite good” were included in the good SRH group, and those who responded “fair” or “poor” were included in the poor SRH group.Activities of daily living were evaluated using the functional independence measure (FIM). This measure consisted of 18 items, including 13 motor tasks and 5 cognitive tasks, with each task evaluated regarding the participant’s level of independence on a 7-point scale from 1  to 7 (complete independence).Instrumental activities of daily livings were evaluated using the Frenchay activities index (FAI). The FAI is a measure of IADLs that was developed by Holbrook and Skilbeck  to evalut test, with age, length of time living alone, and the frequency of medical examination per month expressed as mean ± standard deviation . The number of participants was expressed as a percentage and analyzed by Chi square tests. Finally, the ADLs and IADLs were expressed as mean ± standard deviation  and analyzed by the Mann–Whitney U test. Differences with a P value < 0.05 were considered statistically significant.Various data obtained from the two groups were analyzed using IBM SPSS for Windows. Basic analyses were by a We included 113 elderly participants in the survey, and their characteristics are summarized in Table Participants were divided into two groups according to the degree of SRH: a good SRH group (n = 77) and a poor SRH group (n = 36). The good SRH group tended to be older (P < 0.01), have a lower rate of chronic illnesses (P < 0.05), have a lower frequency of hospital visits per month (P < 0.001), receive a higher rate of emotional support (P < 0.001), and have a difference in the ratio of supporters (P < 0.05) compared with the poor SRH group.The ADL results are summarized in Table The mean total FIM score in the poor SRH group was 112.4 ± 11.9  points, with 81.2 ± 8.3  points for motor tasks, and 31.2 ± 5.7  points for cognitive tasks. In addition, the good SRH group had higher scores (indicating independence) for motor tasks (P < 0.05) compared with the poor SRH group, and scores were particularly high for toileting (P < 0.05).The IADL data are shown in Table The mean total FAI score in the poor SRH group was 18.3 ± 9.9  points, with 9.2 ± 4.5  points for household affairs, 2.3 ± 2.6  points for outdoor household activities, 1.5 ± 1.6  points for outdoor activities, 1.7 ± 2.0  points for hobbies, and 0.1 ± 0.5  points for work.The good SRH group had higher total scores (P < 0.01) than the poor SRH group in moderate items, with high scores for household affairs (P < 0.01) and outdoor household activities (P < 0.01). For minor items, high scores were also obtained for light housework (P < 0.01), heavy housework (P < 0.01), local shopping (P < 0.01), and driving a car or traveling by bus (P < 0.05).There are contradictory reports concerning age. For example, one study rejected the relationship between SRH and mortality, which are similar variables in elderly populations . Other sJapan’s long-term care insurance services are offered when people age 65 years or older need care and support or people aged 40–64 years develop age-related diseases that require care and support. In this system, insured persons are assessed for mental and physical condition, reviewed by a doctor, and certified as “self-supporting”, support level 1–2, or care level 1–5. In a study of elderly individuals , it was Regarding the presence or absence of emotional support in Japanese participants, one study reported that the SRH of the parent was clearly correlated with support received from their offspring , similarResearch has shown that independence of ADLs is facilitated by having good physical abilities, which is also an important variable of better perceived health, indirectly supporting the results of this study . For mosIt has become apparent that, in general, the elderly living alone do not intensively pursue outdoor activities or hobbies but instead seem to realize their health by performing housework. They view housekeeping, which requires physical effort, to be particularly important. In the gender-related difference in Japanese lifestyle, females are exclusively involved with housework . There iImportant factors for good SRH in elderly individuals living alone include the following: (1) they do not have chronic illnesses, or if present, they do not require frequent hospital visits; (2) they can obtain emotional support from offspring; and (3) they can maintain motor function in daily life; (4) they can perform toileting independently; and (5) they can perform most habitual activities independently .It was notable that good SRH was associated with significantly more advanced age compared with poor SRH. Good SRH was also associated with less certification of the need for long-term care, fewer chronic illnesses, fewer hospital visits, more emotional support, and more support from offspring. Significantly higher independence was also noted for FIM motor tasks in those with good SRH compared with poor SRH, particularly for toileting, and there was a significant difference in the total FAI scores between the two groups. It was also noted that engaging in mild- and moderate-intensity activities was significantly different between the groups. Therefore, we conclude that understanding the lifestyles of elderly individuals who live alone and the factors that affect their SRH are important when offering support.A limitation of this study is that the participants were selected from only one rural area of Japan. The 113 participants accounted for only 12.5% of all elderly individuals living alone in Town A, so we cannot conclude that it is representative of all elderly individuals living alone. A verification power analysis was performed, as instructed which indicated powers (1 − β) of 0.689, 0.623, and 0.889 for t tests, Chi square tests, and Mann–Whitney U tests, respectively. It was possible that some items could not be detected in the attributes section due to the small sample size. Although no related articles were identified, we concluded that the ADLs or IADLs of elderly individuals living alone are likely to be affected by aging and that the fluctuation of SRH may be influenced by depression, which must be taken into consideration. Furthermore, the results were probably affected by the unique culture of Japan.


At the single-cell level, we found that not all episomes were uniformly transcribed following reactivation stimuli. However, those episomes that were being transcribed would spontaneously aggregate to form transcriptional “factories,” which recruited a significant fraction of cellular RNA polymerase II. Focal assembly of “viral transcriptional factories” decreased the pool of cellular RNA polymerase II available for cellular gene transcription, which consequently impaired cellular gene expression globally, with the exception of selected ones. The viral transcriptional factories localized with replicating viral genomic DNAs. The observed colocalization of viral transcriptional factories with replicating viral genomic DNA suggests that KSHV assembles an “all-in-one” factory for both gene transcription and DNA replication. We propose that the assembly of RNA polymerase II around viral episomes in the nucleus may be a previously unexplored aspect of KSHV gene regulation by confiscation of a limited supply of RNA polymerase II in infected cells.Locally concentrated nuclear factors ensure efficient binding to DNA templates, facilitating RNA polymerase II recruitment and frequent reutilization of stable preinitiation complexes. We have uncovered a mechanism for effective viral transcription by focal assembly of RNA polymerase II around Kaposi's sarcoma-associated herpesvirus (KSHV) genomes in the host cell nucleus. Using immunofluorescence labeling of latent nuclear antigen (LANA) protein, together with fluorescence IMPORTANCE B cells infected with Kaposi's sarcoma-associated herpesvirus (KSHV) harbor multiple copies of the KSHV genome in the form of episomes. Three-dimensional imaging of viral gene expression in the nucleus allows us to study interactions and changes in the physical distribution of these episomes following stimulation. The results showed heterogeneity in the responses of individual KSHV episomes to stimuli within a single reactivating cell; those episomes that did respond to stimulation, aggregated within large domains that appear to function as viral transcription factories. A significant portion of cellular RNA polymerase II was trapped in these factories and served to transcribe viral genomes, which coincided with an overall decrease in cellular gene expression. Our findings uncover a strategy of KSHV gene regulation through focal assembly of KSHV episomes and a molecular mechanism of late gene expression. Gene expression is regulated by the formation of active chromatin hubs (ACHs) at enhancer regions of the genome, where many tissue-specific gene promoters are brought into proximity . The ideHerpesviruses are known to establish replication compartments (RCs), which are nuclear structures for viral replication. RCs are the result of the assembly of cellular and viral proteins, and they function as factories to facilitate efficient viral genome replication, gene expression, and RNA export . StudiesKSHV is the eighth member of the human herpesvirus family identified in 1994 . Infecti14–de novo infection model  to regions of active gene transcription and formed genomic hubs  was observed. Based upon the results of this study, we postulate that the redistribution of viral episomes in the cell nucleus and recruitment of RNA Pol II to generate viral transcriptional factories is a fundamental molecular mechanism for effective viral gene expression.In this study, we developed an approach to fluorescently label transcribing KSHV episomes in infected cells. We also established a technique to visualize ongoing viral DNA replication by targeting single-stranded DNA. By imaging KSHV transcription in situ by generating probes specifically to intronic regions (O-tetradecanoyl-phorbol-13-acetate (TPA). In combination with LANA immune staining to mark the location of viral episomes in infected cells, we successfully obtained the first images of reactivating KSHV episomes in situ  of total RNA isolated from a mixed population of both latent infected cells and reactivating cells. Using such an approach, it is impossible to know the cell-to-cell variation in response to stimuli—much less the response of individual viral genomes (episomes) in a particular cell. Knowing how and where transcription takes place in the nucleus can provide useful insight into the regulation of viral gene expression. Are only a few episomes actively transcribing RNA, or do all the episomes in the cell transcribe viral genes simultaneously, and if so, how? To answer such questions, we applied an RNA-FISH approach to visualize viral transcripts. This technique was first described in a study of cellular gene regulation, in which target transcripts were marked near the transcribing genomic locus  regions , 34. Usi regions , which a in situ . The res in situ . Brighte in situ  were preshould be in close proximity with RNA Pol II. Accordingly, we stained for RNA Pol II and probed for K-Rta RNA intron-containing transcripts by RNA-FISH. The results showed colocalization of K-Rta RNA with cellular RNA Pol II in BCBL-1 cells  of RNA Pol II is known to be phosphorylated and position of CTD phosphorylation sites  regulates recruitment of different protein complexes and thus regulates the function of RNA Pol II. The results demonstrated that S5-phosphorylated, but not S2-phosphorylated RNA Pol II preferentially colocalized with K-Rta RNA. Interestingly, RNA Pol II S2 signals in proximity to K-Rta RNA signals were significantly lower  in K-Rta inducible BCBL-1 cells (TREx-K-Rta BCBL-1). TPA was also included during reactivation to further induce reactivation. With this approach, we were able to achieve nearly 100% induction of cells expression of K-Rta RNA , thus weGAPDH, β-actin, RNA Pol II (RBP1), and interleukin-10 (IL-10) were all decreased during KSHV reactivation , which would then be hybridized by the fluorescence-labeled DNA oligonucleotides without having to perform DNA denaturation. Avoiding denaturation also permitted us to perform multiplex analysis with protein staining, as well as RNA-FISH. Control studies with RNase A treatment did not eliminate the signal with the TR probes, thereby indicating the probes were hybridized to ssDNA . In fact, staining patterns were significantly different from RNA-FISH staining . DNA-FISH with RNA Pol II staining showed that RNA Pol II was recruited to the sites of KSHV DNA replication, and colocalized with single-stranded viral DNAs . Active It is known that gene expression is a very complex process that involves multiple biochemical reactions and physical processes, which ultimately leads to significant variability in the abundance of gene products. Collective evidence from single-cell sequencing further highlights the dynamics of transcription . In thisM.CviPI DNA methyltransferase. By assessing the accessibility of the enzyme to KSHV episomes, they examined chromatin structure changes in response to TPA  and by using K-Rta inducible cells to further eliminate the variation of effects on the endogenous K-Rta promoter activation. By taking these measures, we were able to achieve nearly 100% uniformity in the activation of endogenous K-Rta expression based on the signals of RNA-FISH in TREx-BCBL-1 K-Rta cells . HoweverGiven the observed translocation of RNA Pol II to viral genomes, we were interested in studying its impact on cellular gene transcription. As expected, most cellular gene expression, including RNA Pol II (RBP1) itself, was significantly decreased, relative to viral gene expression, during KSHV reactivation. It is clear that the formation of viral transcriptional factories and the activity of lytic viral proteins –47 are m–IL-6 locus might also be translocated to be neighboring with viral genomes within the transcriptional factory during KSHV reactivation. Physically neighboring cellular IL-6 gene with KSHV genome might then result in genomic recombination between host and viral genomes. A similar scenario has been suggested for cellular genes between MYC and IGH -seq analyses and that K-Rta protein also directly binds to PAN RNA . Re. Re65). pression . In thatpression . We specpression , 68, forpression . We thinIn summary, we established an immune-FISH approach to study KSHV gene expression at the single-episome level. We propose that the physical accumulation of RNA Pol II near viral genomes in the infected cell nucleus represents an additional layer of KSHV gene regulation, which facilitates the reutilization and repurposing of limited quantities of cellular RNA Pol II. Identifying this molecular mechanism of viral transcriptional factory formation should lead to new strategies to inhibit herpesvirus replication.2 in RPMI 1640 medium supplemented with 15% fetal calf serum, 2 mM l-glutamine, and antibiotics. K-Rta expression and KSHV reactivation was induced in TREx K-Rta BCBL-1 cells with 20 ng/ml 12-O-tetradecanoyl-phorbol-13-acetate (TPA) and 100 ng/ml doxycycline. For other PEL cell lines—BCBL-1, BC2, and HBL-6—KSHV reactivation was induced with 20 ng/ml TPA, 1 mM sodium butyrate, or both agents in combination.BCBL-1 and BJAB cells were generous gifts from D. Ganem . BC2 and HBL-6 cells were obtained from Masahiro Fujimuro . TREx-(F3H3)-K-Rta BCBL-1 cells that expresses Flag ×3 and hemagglutinin (HA) ×3 tags at the N-terminal region of K-Rta were generated by using TREx-BCBL-1 cells  with Flp-recombination according to the manufacturer's protocol (Invitrogen), and cultured in complete RPMI 1640 containing 50 μg/ml blasticidin and 100 μg/ml hygromycin B. These B cell lines were grown at 37°C in the presence of 5% COWhen applicable, a double thymidine block was used to synchronize the cell cycle and to synchronize the initiation of reactivation and increase efficacy of viral reactivation . TREx K-Total RNA was purified with the RNeasy Plus minikit (Qiagen). Eluted RNA was converted to cDNA by using Superscript II reverse transcriptase (Thermo Fisher Scientific) and diluted 1:100. Portions (4 μl) of template were used for every 20-μl reaction, and all samples were analyzed in triplicate using SYBR green Supermix (Bio-Rad) on a QuantStudio 3 real-time PCR system using specific primers designed previously by Fakhari and Dittmer . Meltingg for 10 min at 4°C), the protein concentration was measured by using a Pierce bicinchoninic acid protein assay kit (Thermo Fisher Scientific), and equal amounts of total cell lysates were subjected to an SDS-PAGE (6% for Pol II and 10% for the other proteins) and subsequently transferred to a Immobilon-P polyvinylidene difluoride (EMD Millipore) using a semidry transfer apparatus (Bio-Rad). Membranes were blocked for 10 min at room temperature in TBST –5% skim milk, followed by incubation with primary antibodies overnight at 4°C. The membranes were subsequently washed with TBST three times for 10 min each time at room temperature and then incubated with horseradish peroxidase-conjugated antibodies for 1 h at room temperature. The membranes were washed three times with TBST and visualized with enhanced with SuperSignal substrate (Thermo Fisher Scientific). Where indicated, the cells were treated with 10 μM MG132 (Sigma) or 16 nM bortezomib to inhibit proteasome. The following antibodies were used for immunoblotting: anti-K-Rta  and lysed in radioimmunoprecipitation assay buffer . After centrifugation , anti-K2O]). Coverslips were incubated with a mixture of FISH probes and secondary antibodies in hybridization solution  for 18 h at 37°C. The FISH probe sequences are listed in At 28 h (unless otherwise stated in the legends) after the induction of KSHV reactivation, the cells were harvested and washed three times with diethylpyrocarbonate (DEPC)-treated PBS. The cells were then spotted onto coverslips and subsequently fixed with 4% formaldehyde in DEPC PBS solution for 10 min. After washing three times with DEPC-PBS, the cells were quenched with 100 mM glycine DEPC-PBS solution for 10 min. After a rinsing with DEPC-PBS, the cells were permeabilized with a 1:1 methanol-acetone solution for 15 min and washed with DEPC-PBS. Primary antibodies  were diluted in dilution buffer , followed by incubation for 1 h at 37°C. The slides were washed three times with DEPC-PBS and then washed three times with FISH wash buffer  equipped with a ×60, 1.42NA oil immersion objective lens, xenon arc lamp, and standard filters for DAPI (blue), FITC (green), and TRITC  channels. 3D image stacks were acquired with 0.2-μm spacing in the z-axis; and image deconvolution was performed postacquisition using on-board software . Image data were transferred to a separate computer for 3D image rendering and subsequent analysis using VoloCITY 3D imaging suite .Chromatin immunoprecipitation (ChIP) assays were performed as described previously . The ant


SINE B2 element for their UP-regulation of translation. Mouse AS Uchl1 is the representative member of natural SINEUPs. It was originally discovered for its role in increasing translation of Uchl1 mRNA, a gene associated with neurodegenerative diseases. Here we present the secondary structure of the SINE B2 Transposable Element (TE) embedded in AS Uchl1. We find that specific structural regions, containing a short hairpin, are required for the ability of AS Uchl1 RNA to increase translation of its target mRNA. We also provide a high-resolution structure of the relevant hairpin, based on NMR observables. Our results highlight the importance of structural determinants in embedded TEs for their activity as functional domains in lncRNAs.Pervasive transcription of mammalian genomes leads to a previously underestimated level of complexity in gene regulatory networks. Recently, we have identified a new functional class of natural and synthetic antisense long non-coding RNAs (lncRNA) that increases translation of partially overlapping sense mRNAs. These molecules were named SINEUPs, as they require an embedded inverted  They can be natural sources of regulatory sequences, co-opted to rewire gene regulatory networks7. In physiological conditions, TE mobilization has been implicated in the evolution of embryonic stem cells8 and placenta9, in pluripotency maintenance11, in the development of the mouse neocortex13 and in immune responses triggered by proinflammatory interferon-γ7. In addition, TEs can be “exonized” in protein-coding transcripts and function as regulatory RNA domains, contributing to alternative splicing14 or originating miRNAs16. Recently, a number of studies have highlighted a functional role of TEs when embedded in long non-coding RNAs (lncRNAs). lncRNAs are defined as transcripts >200 nt in length with no coding capability. lncRNAs have been implicated in a variety of biological functions, regulating gene expression at many levels18. Based on updated catalogues of annotated lncRNAs19, it is estimated that more than 80% of human and 66% of mouse lncRNAs contain at least one exonized TE. As a consequence, 40% of human and 33% of mouse lncRNA sequences derive from TEs22. Selective families of TEs can be found enriched or depleted in sub-classes of lncRNAs in the two species, arguing for an active role of TEs in evolution and function of lncRNAs23. In this context, exonized (or embedded) TEs would represent the molecular basis for domain organization in lncRNAs25. However, direct evidence for domain functionality of embedded TEs is still limited to few examples. Human Alu elements embedded in a group of lncRNAs, called 1/2-sbsRNAs, provide an RNA recognition motif that base pairs with complementary Alu sequences in the 3′ untranslated region of protein-coding mRNAs to drive their decay26. An embedded Alu element is involved in recruiting proteins of the Polycomb Repressor Complex, thus modulating the biological activity of ANRIL, a lncRNA associated to coronary artery disease27.Transposable elements (TEs) are mobile repetitive sequences that represent about 50% of the mammalian genomes. Previously referred to as genomic “junk”, it is now increasingly acknowledged that TEs contribute to a wide range of biological processes, ultimately promoting genome evolution through rearrangements of genome structure and function. Specific TEs can be regulatory DNA elements acting as promoters or enhancers28. The translation enhancer function of AS Uchl1 depends on two RNA domains. At the 5′, the region overlapping with Uchl1 mRNA confers target mRNA specificity and is referred to as the Binding Domain (BD). In the non-overlapping sequence, the invSINEB2 element provides the translation activation function of AS Uchl1 and it is defined as the Effector Domain (ED). By solely combing BD with the invSINEB2 ED it is possible to retain the gene-specific up-regulation function of AS Uchl128. Similarly, AS Uchl1 activity can be transferred to a synthetic construct by changing the antisense sequence in the BD30. Bioinformatic mining of the FANTOM3 collection of lncRNAs identified at least 31 naturally occurring AS lncRNAs overlapping with protein-coding mRNAs at the 5′ end and containing an invSINEB2 element28. Altogether, AS Uchl1 can be considered the representative member of a new functional class of natural and synthetic AS lncRNAs named SINEUPs, as they require a SINE B2 element to UP-regulate translation31. While natural SINEUPs are investigated for their role in translational control under stress, synthetic SINEUPs are currently under intense scrutiny for their use in therapeutic intervention for gene-dosage dependent genetic diseases such as haploinsufficiences.Recently, we have demonstrated that an embedded inverted SINE B2 (invSINEB2) element acts as a functional domain in antisense (AS) Uchl1, an AS lncRNA able to increase translation of partially-overlapping protein-coding sense Uchl1 mRNADespite recent advances in supporting the functional role of embedded TEs as lncRNA domains, it still remains to be determined how these elements can retain a specific biological function despite very poor sequence conservation. The crucial challenge is the understanding of the structure/function relationship between embedded TEs and lncRNAs and the definition of structural determinants that contribute to their biological function.This work describes the structural features of the invSINEB2 element as ED embedded in AS Uchl1 RNA. Chemical footprinting combined with functional validation in murine neuroblastoma cells identified a short hairpin as key structural determinant for the ability of AS Uchl1 to increase translation. A high-resolution structure of the hairpin has been derived based on NMR observables.Our results strengthen the role of structural determinants in embedded TEs for their activity as functional domains in lncRNAs.in vitro transcribed from a plasmid and prepared for secondary structure determination using chemical footprinting. DMS (dimethyl sulfate) and CMCT (1-cyclohexyl-(2-morpholinoethyl)carbodiimide metho-p-toluene sulfonate) were used as methylating agents. DMS preferentially methylates positions N1 and N3 of adenines and cytosines, respectively, while CMCT methylates position N3 of uridines and to a lesser extent N1 of guanines. The level of methylation is directly related to the accessibility of potential modification sites to solvent. Therefore, hydrogen bonded nucleotides are not methylated, while non-hydrogen bonded are. The methylation sites were analysed by reverse transcribing RNA into cDNA starting from a fluorescently labelled DNA primer. The DNA oligos were analysed on large sequencing gels and visualized on a densitometer  corresponding to the invSINEB2 element of AS Uchl1 was r Figure . Data frThe invSINEB2/183 RNA folds into a structure with mostly helical secondary structure elements  from the full length AS Uchl1 (ΔSL1 mutant). According to mFOLD structure prediction, this deletion would not affect the stable helical regions, but rearrangements in IL4 are expected. To investigate invSINEB2-ΔSL1 activity when embedded in full length AS Uchl1, we took advantage of murine neuroblastoma Neuro2a cells, as they express Uchl1 mRNA but do not contain detectable levels of endogenous AS Uchl1. AS Uchl1 activity was defined as UchL1 protein increase in the presence of unchanged mRNA levels, as quantified by western blotting and qRT-PCR, respectively. AS Uchl1 caused an ~1.9-fold increase in UchL1 protein levels while maintaining stable Uchl1 mRNA levels, as expected for a post-transcriptional regulatory mechanism. Interestingly, the ΔSL1 deletion mutant abolished the ability of AS Uchl1 RNA to up-regulate UchL1 protein levels  has been derived on the basis of NMR observables and restrained molecular dynamics simulations. A set of 100 structures was calculated using a simulated annealing protocol from which 10 of the lowest energy structures were selected and subjected to subsequent energy minimization. The hairpin adopts an A-type helical stem, which is terminated by a triloop Fig. . The fin1H resonances suggesting a dynamic nature of the two nucleotides. Interestingly, the arrangement of the loop nucleobases GUG clusters into one of two possible energy minima in the final ensemble of structures. In one family of structures G79 exhibits a χ angle of around 100° and is nearly coplanar with G77 , which however do not give observable imino G77 Fig. , while iG77 Fig. . In bothres Fig. .A 400 ns MD simulation was performed with model 1 of the refined structures as a starting conformation. It has been divided into two equal parts which were analysed separately to validate the convergence of the simulation. Since both parts provided similar qualitative data, only results from the second part (200–400 ns) are shown here. The ensemble averages The snapshots in the simulation could be reweighted such that the weighted ensemble averages satisfied all NOEs. From the 20 highest weighted structures, a set of 5 structures was chosen, in which every NOE is satisfied in at least one structure. This set was selected by i. taking the highest weighted structure and ii. including from the next highest structures the ones which reduce the number of unsatisfied NOEs. This set of structures can be found in the Supplementary Material.The amount in which imino protons are participating in hydrogen bonds has been calculated for each donor as a fraction of the reweighted ensemble Table . In agreThe average annotations for pairs of bases were calculated from the reweighted ensemble and are shown in Supplementary Material Figure The entire PDB was searched for fragments of NMR models in solution with some degree of structural similarity to a template built using the apical 13 nucleotides (U72-A84) of model 1. All the structures with an εRMSD <1.0 are reported in Table 33. As independently transcribed RNAs, SINEs have been shown to possess important biological functions. SINEB2 and Alu suppress mRNA transcription upon heat shock by direct interaction with RNA polymerase II36. BC1 and SINE elements are involved in RNA localization and in the regulation of translation in neurons37. More recently, “exonized” or “embedded” SINE elements have been hypothesized to act as portable domains in lncRNAs, thus contributing to their biological functions38. A major issue to the “embedded domain” hypothesis is represented by the poor sequence conservation of lncRNAs during evolution. It is becoming evident that the sequences with higher inter-species homology do not necessary represent the functional domains of lncRNAs. This has been seen in several examples including Xist, a lncRNA involved in X chromosome inactivation40. In other cases, as in HOTAIR, the mouse and human genes share very little sequence conservation and display a completely different exon/intron organization. However, in the two species, the pattern of expression and the biological function are fully conserved41. Overall these data suggest that conserved lncRNAs’ functions are based on structural determinants. This concept may stand true also for embedded TEs. To address the issue of structural/functional relationship in lncRNA domains, here we take advantage of the modular organization and the well-defined biological function of AS Uchl1. This transcript contains an embedded invSINEB2 element acting as ED and crucial for its ability to increase translation of Uchl1 mRNA28.The mouse genome contains approximately 350,000 SINE B2 sequences, dispersed throughout the genome, as independent transcriptional units or embedded in longer RNA polymerase II transcripts42, positioned either at the 5′ end, as for BC143, or at the 3′ terminus, as in the case of salmon SmaI SINE44.We show that a large portion of the invSINEB2 secondary structure is comprised of helical structural elements. Absence of longer single stranded segments precludes any sequence-specific recognition. Therefore it is more likely that the functionality of invSINEB2 is based on its structural features. The invSINEB2 structure exhibits several internal loops and hairpins that may serve as structural motifs for specific recognition by a currently unknown partner molecule. An extended stem-loop structure, with terminal loops and internal bulges, has been previously observed for other SINE RNAsper se a structural determinant of AS Uchl1 activity. We have found that the structure of the invSINEB2 RNA is mostly not affected by SL1 deletion, at least as predicted by mFOLD. The prediction is compatible with our chemical footprinting data that indicate a stable “basal” structure of the molecule with a more flexible region at its “apical” part. Altogether, our results support the model of the invSINEB2 as an independent folding unit acting as ED by the mean of a terminal stem loop structure. Recently, a similar model was reported for human lincRNA-p21 (hLinc-p21), a lncRNA containing an embedded SINE. This intergenic lncRNA was originally discovered in mouse as involved in stress responses mediated by p53. hLinc-p21 is a single exon gene and contains an inverted repeat Alu element (IRAlus). The authors show that structural determinants in the embedded IRAlus contribute to the nuclear localization of hLinc-p2145.Terminal stem loop hairpin structures are often used as functional RNA motifs given their overall accessibility. This is confirmed also for the embedded invSINEB2 element of AS Uchl1. Deletion of the SL1 structural motif abolished the ability of AS Uchl1 to increase endogenous UchL1 protein levels. These results can be interpreted according to two models: 1) the SL1 terminal structural element is needed to maintain the overall structure of the invSINEB2, which in turn is necessary for AS Uchl1 activity; 2) SL1 represents 46.It should be noted that the structure/function model observed for the embedded SINEs in AS Uchl1 and hLinc-p21 seems to differ from what is observed in RNA polymerase III-transcribed SINE B2 RNA. The repression of RNA polymerase II transcription by SINE B2 RNA strictly depends on an internal single stranded region, rather than on a terminal stem loop structure47. It will be interesting to examine whether structural determinants contribute to the biological activity of these embedded repeats.Interestingly, the impact of repeats on lncRNA functions can be also extended to repeats not derived from TEs. The Firre lncRNA contains a repeat RNA domain that is necessary and sufficient for nuclear retention48. In particular, a Free Right Alu Monomer (FRAM) embedded in AS PPP1R12A is essential for its ability to up-regulate translation. In the future, it will be interesting to assess whether embedded SINEs of human and mouse origin share the same structural determinants or, alternatively, whether different structural determinants are recruited for the same biological function.SINE B2 elements are not conserved in humans. We have recently identified human antisense lncRNAs that share the same domain anatomy of AS Uchl1 and function as natural SINEUPs in human cellsGiven the requirement of SL1 for AS Uchl1 function, we further provided a high-resolution description of its structural determinants using NMR. The SL1 hairpin features a stable G:C rich stem with a single U:U mismatch. On the other hand, its loop exhibits dynamic properties. The central GUG of the loop is followed by two A:U base pairs. According to chemical footprinting of the full length invSINEB2/183 both A:Us are accessible to methylating agents. NMR data on the truncated invSINEB2/38 clearly shows the formation of U75:A81 base pair. MD simulations also show that the U76:A80 base pair (adjacent to GUG) is stable. The discrepancies between NMR and MD results can be attributed to higher solvent accessibility of U76:A80. However, the susceptibility of the two A:U base pairs to methylation in invSINEB2/183 may suggest that SL1 is destabilized in the full length construct compared to the truncated construct used in NMR studies. The dynamic properties of the loop could be a significant factor for SINEUP activity.49. The secondary structure of the SL1 hairpin with a triloop followed by two unstable base pairs shares a certain degree of similarity with the anticodon arm of tRNA molecules. However, comparison of the SL1 3D structure with known structures from the PDB does not show a high degree of similarity on the high-resolution level and dismisses the possibility that tRNA mimicry could be the ground for recognition and interaction of AS Uchl1 mRNA. A similar terminal triloop structure is also seen in BC1 RNA although structure/function relationship studies have provided conflicting results on the exact contribution of structural determinants to BC1 function50. Analysis of transgenic mice expressing structural variants in vivo indicates a prominent role for the supporting basal structure in dictating BC1 biological activity51 suggesting a much more complex scenario than expected from the evolutionary origin of TEs.SINEB2 elements are evolutionary linked to tRNA genesIn conclusion, we have shown that SL1 is a structural determinant required for AS Uchl1 activity. Further studies will elucidate the precise mechanism to increase protein translation by the embedded invSINEB2 and whether the SL1 motif is the sole ED portion responsible for AS Uchl1 activity. This knowledge will be important to optimize synthetic SINEUPs for their use as therapeutics of human genetic diseases such as haploinsufficiencies.28. PCR fragment was digested with EcoRI and HindIII and sub-cloned into pUC19 vector for in vitro transcription (pUC-T7-invSINEB2). A T7 priming site was included in the forward primer. The following primers were used for cloning:The nucleotide sequence corresponding to the invSINEB2 repeat embedded in AS Uchl1 was PCR-amplified from a pcDNA 3.1(-) plasmid expressing AS Uchl1 full lengthFWD EcoRI T7 invSINEB2 GAGAGAATTCTAATACGACTCACTATAGGG-CAGTGCTAGAGGAGGREV HindIII B2 GAGAAAGCTTAAGAGACTGGAGCAS Uchl1 mutant lacking the SL1 domain within the invSINEB2 element (Δ68–77 nt) was obtained by gene synthesis and cloned between at XbaI/HindIII sites in pcDNA 3.1(-).in vitro transcribed using a T7 RNA polymerase (Promega), rNTPs (Jena Bioscience) and pUC-T7-invSINEB2. The overnight transcription reaction was quenched with EDTA. Phenol-chloroform extraction was used to remove the proteins and extensive ultrafiltration with H2O through a 1000 MWCO membrane (Millipore) removed the low molecular weight components.183 nt RNA used for chemical footprinting was in vitro transcription, however, at a considerably larger scale and with a DNA oligonucleotide (Eurogentec) containing a T7 promoter used as a template. Last two 5′ residues of the template were 2′-OMe modified in order to keep by-products to a minimum. Unlabelled rNTPs (Jena Bioscience) and 13C, 15N-labeled rNTPs (CIL) were used for the preparation of a natural abundance and a uniformly double labelled RNA, respectively. Phenol-chloroform extraction was followed by precipitation in ethanol, the precipitate was recovered with centrifugation and by redissolving it in water. RNA was further purified with denaturing (7 M urea) PAGE electrophoresis (15%). Only bands containing the full length 38 nt RNA were excised from the gel and recovered by electroelution (Schleicher & Schuell). Finally, the RNA solution was extensively ultrafiltrated with the NMR buffer . The RNA concentration in the NMR samples was 0.5 mM.Similarly, 38 nt RNA construct (GGUAACCUCGUGGUGGUUGUGAACCACCAUGUGGAUGG) for NMR studies was also prepared by in vitro transcribed using a T7 RNA polymerase and corresponding pUC plasmids. After overnight transcription was quenched with EDTA the reaction mixture was loaded directly onto a GE HiPrep DEAE anion exchange column. The RNA fraction was collected and the product was precipitated in ethanol. After desalting and drying the RNA was dissolved in NMR buffer.The full length 183 nt invSINEB2 element and the ΔSL1 construct used for NMR were 2O and used for primer extension. ATTO 620 5′ fluorescently labelled 18 nt DNA oligos (Eurogentec) were used as primers. The primer is complementary to the 3′ of invSINEB2 RNA and was hybridized to it by incubating the mixture at 70 °C for 5 min followed by flash cooling on ice. 80 pmol of primer and 20 pmol of RNA resulted in efficient hybridization and were used for each reaction. 200 U of Superscript II reverse transcriptase (Invitrogen) was used for primer extension. Reactions were incubated for 45 min at 42 °C following the manufacturer’s protocol and using the supplied buffer. 125 μM dNTP mixture was added to the reaction mixture. Reactions were stopped by a 20 min incubation at 70 °C. Subsequently, the modified RNA was degraded with a 10 min incubation with 2 μL (10 mg/mL) RNase A at 60 °C. The reaction mixtures were then directly loaded to large sequencing 8% 7 M urea PAGE gel.InvSINEB2 RNA was treated either with dimethyl sulfate (DMS), which methylates As and Cs, or 1-cyclohexyl-(2-morpholinoethyl)carbodiimide metho-p-toluene sulfonate (CMCT), which methylates Us and to a lesser extent Gs. 2 μL of 20% solution of DMS in ethanol were added to 20 μL of RNA solution. Modification reactions were incubated at room temperature for 2, 5, 10 or 20 min. Reactions were quenched with 475 μL of 30% β-mercaptoethanol/0.3 M NaOAc mixture. For CMCT reactions Tris HCl was added to 25 μL of RNA to adjust the pH to 8.1. 1 μL of CMCT solution (500 g/L) was added to each reaction, which were incubated at room temperature for 2, 5, 10 or 20 min. Reactions were quenched with 100 μL of 0.3 M NaOAc. DMS and CMCT solutions were prepared fresh each time minutes before treatment. The modified RNA from quenched reactions was recovered by ethanol precipitation. Dried RNA was redissolved in 20 μL HPositive control reactions were run in a similar manner, however, with the DMS or CMCT treatment performed for half a minute at 90 °C. Negative control reactions were not treated with methylating agents. In order to position the bands within the RNA sequence classical sequencing reactions with ddNTPs were run in parallel on gels. Non-methylated RNA was used in primer extension reactions with individual ddNTPs being added to the reaction in the ratio of dNTP:ddNTP of 1:5. Bands were visualized on a Perkin Elmer ProEXPRESS imaging system.Neuro2a cells were obtained from ATCC (Cat. No. ATCC-CCL-131) and maintained in culture with Minimum Essential Medium + GlutaMAX™-I  supplemented with 10% FBS (Sigma) and 1% antibiotics (penicillin/streptomycin) as suggested by the vendor. Neuro2a cells were plated in 6 well-plates the day before transfection at 80–90% confluency and transfected with AS Uchl1 plasmids using Lipofectamine® 2000  and following manufacturer’s instructions. Cells were collected at 48 hours after transfection and split in two samples for RNA extraction and Western Blot analysis.™ ECL™ Detection Reagents . Image detection was performed with Alliance LD2-77WL system . Image quantification was done using ImageJ software.For Western blot analysis, cell pellets were dissolved in Laemmli sample buffer, briefly sonicated, boiled and loaded on 12% poly-acrilamide gels. Immunoblotting was performed with the following primary antibodies: anti-UCHL1 rabbit polyclonal antibody  1:5000 and anti-β-actin , 1:2000. Signals were revealed after incubation with horseradish peroxidase-conjugated secondary antibodies  in combination with Amershamet al.28. The amplified transcripts were quantified using the comparative Ct method and relative gene expression was calculated with the ΔΔCt method .Total RNA was extracted from cell pellets using RNeasy Mini Kit (QIAGEN) following manufacturer’s instructions. RNA was treated with on-column DNase I  followed by a second DNase I digestion in solution  to avoid plasmid DNA contamination. Single strand cDNA was prepared from 1 μg of purified RNA using iScript™ cDNA Synthesis Kit  according to manufacturer’s instructions. Real Time qRT-PCR was carried out using SYBR green fluorescent dye  and an iCycler IQ Real time PCR System (Bio-Rad). The reactions were performed on diluted cDNA (1:20). Oligonucleotide sequences of primers used in this study for GAPDH, Uchl1 and AS Uchl1 were previously described in Carrieri t-test. Differences with p < 0.01 were considered significant.All data are expressed as mean ± standard deviation on n ≥ 3 replicas. Statistical analysis was performed using Excel software. Statistically significant differences were assessed by Student’s 2H2O or 5% 2H2O, 95% H2O. 1D 1H and 2D NOESY, DQF-COSY and TOCSY NMR spectra were recorded with the natural abundance sample. 2D 13C and 15N HSQC and HCN spectra were recorded with the isotopically enriched sample. 3D NOESY-HSQC and HCCH-TOCSY spectra were also acquired, but gave poor S/N ratio due to low RNA concentration. Cross-peak intensities were therefore evaluated from 2D NOESY spectra.Spectra were recorded with the RNA either in a 100% All spectra were acquired on an Agilent VNMRS 600 MHz spectrometer equipped with a cryogenic probe. DPFGSE water suppression scheme was used for suppression of the water signal. All experiments were performed at temperatures of 0, 25 or 37 °C. NMR spectra were processed and analysed using VNMRJ (Agilent), NMRpipe and Sparky software (UCSF).2H2O with mixing times ranging from 80 to 250 ms. NOE distance restraints for exchangeable protons were obtained from 2D NOESY spectra recorded at 0 °C in 5% 2H2O, 95% H2O with a mixing time of 250 ms. Cross-peaks were classified as strong (1.8–3.6 Å), medium (2.6–5.0 Å) and weak (3.5–6.5 Å).NOE distance restraints for non-exchangeable protons were obtained from 2D NOESY spectra recorded at 25 °C in 100% trans conformations. Torsion angles β were restrained to 180 ± 40° (trans). Torsion angles ε were restrained to 235 ± 65° to exclude the unfavourable gauche+ conformation. Torsion angles γ were restrained to 60 ± 40° (gauche+). Due to the absence of H1′/H2′ cross-peaks in 2D TOCSY spectra, which indicate an N-type sugar pucker, torsion angles δ of all nucleotides were restrained to 85 ± 30°. Torsion angles χ were restrained to −120 ± 90° (anti) based on the intensity of intraresidual H6/H8-H1′ NOESY cross-peaks, excluding loop nucleotides.Backbone torsion angle restraints  were used only for the helical region of the hairpin. Torsion angle restraints for α and ζ were set to 0 ± 120° to exclude ff14SB force field52. Initial fully extended structure was created using the leap module of Amber. The structure was then subjected to molecular dynamics (MD) calculations using a generalized Born implicit solvation model53. During MD NMR restraints were gradually introduced in order to obtain a hairpin structure. This was used as a starting structure for a series of simulated annealing (SA) calculations. For each of 100 SA calculation a random starting velocity was used. For the first 200 ps the molecules were held at a constant temperature of 1000 K. The molecules were then cooled to 300 K in the next 400 ps, after which the temperature was further decreased to 0 K in the next 400 ps. The force constants were 20 kcal mol−1 Å−2 for NOE distances and 500 kcal mol−1 rad−2 for torsion angles. The SHAKE algorithm for hydrogen atoms was used with a tolerance of 0.0005 Å.Structure calculations were performed using AMBER 14 software with the A family of 10 structures with the lowest energy was subjected to a maximum of 10000 steps of steepest descent minimization and selected for further analysis. Helical parameters were determined with 3DNA 2.0 software.54 was used to search similar motifs, independent of sequence. Similarity was measured using the εRMSD, which reports on the relative distance and orientation of all pairs of interacting bases.The 13 residue hairpin (72–84) of model 1 of the refined structures was compared to solution-state NMR structures in the PDB . baRNAba56. All bonds were constrained, and snapshots were saved for later analysis every 4 ps57.Model 1 from the refined structures (29 nt) has been used as a starting structure for unrestrained molecular dynamics simulations (MD) of 400 nanoseconds length. The structure was solvated with water and neutralized with sodium ions. Water molecules were then replaced with ions to obtain a 0.1 mol/L concentration of NaCl, resulting in a solution of 18822 water molecules, 64 sodium and 36 chloride ions. After energy minimization, the system was subjected to a 400 ns unrestrained MD at constant temperature (T = 300 K) and pressure (P = 1 bar)60 and ions61.Simulations were done with GROMACS 4.6.7 using the AMBER force field including the latest corrections for RNA62 such that the averaged reweighted ensemble satisfies all NOE distance restraints. The NOE intensities were classified as weak, medium and strong, corresponding to average distances rweak ≤ 6.5 Å, rmedium ≤ 5.0 Å and rweak ≤ 3.6 Å. Since NOEs are proportional to 1/r6 the NOEs from the simulation were calculated as  NOEi(t) = 1/ri(t)6 for all detectable pairs of hydrogens i, and corrected if their average was The snapshots from the simulations were reweighted according to the maximum entropy principleλi were initialized to zero and updated according to λi is incremented by the amount on the right side. K is a constant with the value 10−5. σ accounts for errors in the experimental values and is equal to 0.563. If λi becomes positive, it is set to zero. This cycle is repeated until all The weighted average value of each NOE is calculated as Each simulation snapshot was weighted by the final set of weights W(t) which satisfied all NOE constraints. Hydrogen bonds involving imino protons (G:H1 and U:H3) were calculated as the sum of the weights of the snapshots in which the following criteria were satisfied: the distance between donor and acceptor had to be less than 3.5 Å and the angle hydrogen-donor-acceptor less than 30°. Each hydrogen bond has a stability value between 0 and 1.54. The stability of an annotation for a pair of bases was calculated as the sum of the weights of the snapshots in which the annotation was present, and is defined in the range from 0 to 1.For the reweighted ensemble, annotations were calculated using baRNAbaThe coordinates for the family of the 10 lowest energy structures of the 29 nt RNA construct (CCUCGUGGUGGUUGUGAACCACCAUGUGG) have been deposited in the Protein Data Bank with the accession code 5LSN. Chemical shifts have been deposited in the Biological Magnetic Resonance Data Bank as the entry 34038.Supplementary information