RNA extracted from formalin-fixed paraffin-embedded (FFPE) samples is chemically modified and degraded, which compromises its use in gene expression studies. Most of the current approaches for RNA quality assessment are not suitable for FFPE derived RNA.TBP gene mRNA as the target sequence. The RT-PCR amplicon sizes, 92, 161, 252 and 300 bp, cover a range of amplicon sizes suitable for a wide range of RT-qPCR assays. The QC assay was used to evaluate RNA prepared by two different protocols for extracting total RNA from needle microdissected FFPE breast tumour samples. The amplification products were analysed by gel electrophoresis where the spectrum of amplicon sizes indicated the level of RNA degradation and thus the suitability of the RNA for PCR. The ability of the multiplex endpoint RT-PCR QC assay to identify FFPE samples with an adequate RNA quality was validated by examining the Cq values of an RT-qPCR assay with an 87 bp amplicon.We have developed a single-tube multiplex endpoint RT-PCR assay specifically designed to evaluate RNA extracted from FFPE tissues for mRNA integrity and performance in reverse transcription - quantitative real-time PCR (RT-qPCR) assays. This single-tube quality control (QC) assay minimises the amount of RNA used in quality control. mRNA integrity and the suitability of RNA for RT-PCR is evaluated by the multiplex endpoint RT-PCR assay using the The multiplex endpoint RT-PCR assay is well suited for the determination of the quality of FFPE derived RNAs, to identify which RT-PCR assays they are suitable for, and is also applicable to assess non-FFPE RNA for gene expression studies. Furthermore, the assay can also be used for the evaluation of RNA extraction protocols from FFPE samples. Formalin-fixed paraffin-embedded (FFPE) tissue samples are routinely used for diagnosis of disease. There is increasing interest in extracting RNA from these samples as the large numbers of archival FFPE samples constitute an invaluable resource for the investigation of diagnostic, prognostic or predictive disease associated alterations in gene expression (reviewed in ). FurtheHowever, RNA extracted from FFPE specimens is extensively degraded and chemically modified, which compromises its use in PCR based applications (reviewed in ). DegradWhereas the extent of chemical modifications of the RNA initially limits the PCR amplification size, with time RNA degradation becomes more important in determining the size of amplifiable PCR fragments . The RNAThe quality of the extracted RNA is a critical factor for both microarray based and reverse transcription - quantitative real-time PCR (RT-qPCR) gene expression experiments. Microarray based approaches are more sensitive to RNA degradation and chemical modifications , which pRT-qPCR assays are less affected by RNA degradation and chemical modifications especially when the RT-qPCR amplicon size is less than 100 bp ,12.260/A280 and A260/A230 absorbance ratios . Thus, a longer fragment size in the multiplex endpoint RT-PCR assay was correlated with a smaller Cq value in the RT-qPCR assay for both total RNA extraction protocols .Despite the improvements in methodologies for extracting RNA from FFPE specimens, one significant and challenging problem still remains. The quality of the extracted RNA is compromised and the degree of RNA degradation and the extent of chemical modifications of the RNA may limit its use in downstream applications. It is therefore critical to assess the RNA quality at the cDNA stage to identify the RNA preparations which are suitable for a particular RT-qPCR analysis.The multiplex endpoint RT-PCR approach used in this study has been developed and optimised to assess RNA extracted from FFPE specimens for its use in RT-qPCR assays. The assay is sensitive to RNA degradation as well as chemical modifications, which both determine the length of an amplicon during PCR amplification. This methodology is similar in principle to one that has been used extensively in our laboratory for the assessment of DNA from FFPE samples .TBP for our multiplex endpoint RT-PCR assay, because it was shown to be relatively stably expressed in a range of tumour types such as bladder cancer [TBP is expressed at moderate [The choice of the target gene mRNA is of particular importance. It is desirable, that the target gene mRNA is ubiquitously expressed across most cell types and that the level of gene expression shows a similar magnitude among the samples. We selected r cancer , renal cr cancer , hepatocr cancer , glioma r cancer ,29 and br cancer . TBP is moderate ,29,38 tomoderate . The chomoderate .G6PD gene actually overlie potential polymorphic sites [We also designed our primers to avoid underlying polymorphic sites. Target gene mRNA from highly polymorphic genes perhaps should be avoided. The primers in a previous approach which used the ic sites . Primer Our multiplex endpoint RT-PCR approach utilises random primers to synthesise cDNA. Thus after the cDNA is assessed, the same cDNA can subsequently be used in the final gene expression experiment(s). This then also controls for the cDNA synthesis step.The knowledge about which fragment sizes can be amplified during a RT-qPCR assay helps to identify samples suitable for gene expression analysis and which amplicon sizes can be used for an RT-qPCR assay design. The range of PCR amplicon sizes covered by our assay takes into account the RNA sizes normally obtained from FFPE. The upper size range is interrogated by three PCR amplicon sizes , and helps to identify samples suitable for sometimes more demanding applications, such as discrimination between gene splice variants. The 92 bp PCR fragment helps to identify samples suitable for FFPE-friendly RT-qPCR assays which we normally design with amplicon sizes less than 90 bp.q values in the RT-qPCR assay and are probably the best suited samples to deliver reliable gene expression data for most genes of interest in gene expression analysis.The good agreement between the results observed for the multiplex endpoint RT-PCR assay and the RT-qPCR results Figure  shows thtype DX test [There is an increasing demand for the use of RNA from FFPE both in research and in molecular diagnostic applications such as the Onco DX test ,40,41. TThe validated quality control multiplex endpoint RT-PCR assay presented here overcomes the limitations of current approaches and is a robust method and well suited for determining the quality of a RNA preparation, especially for FFPE derived RNA. In addition, the assay can be used for routine quality control assessment of cDNA synthesis. The assay is also applicable for comparing or refining methodologies for RNA extraction and cDNA synthesis. Finally, the approach is cost effective and only requires equipment which is widely available.Thirty breast tumour FFPE blocks  were retrieved from the archives of the Department of Pathology at the Peter MacCallum Cancer Centre. The institutional ethics committee approved the study .The bench surface, the manual rotary microtome Leica RM2235 (Leica Microsystems), the equipments and glass slides were cleaned with RNaseZap  prior to use according to the manufacturer's directions. Diethyl pyrocarbonate (DEPC)  treated water  was used throughout the histology procedures.For haematoxylin and eosin (H&E) staining, a 3 μm section from each FFPE block was stained to identify the tumour enriched area for needle microdissection. From each FFPE block, one to five 7 μm sections were prepared and mounted on the glass slides. The number of sections used in microdissection was determined by the content of tumour cells in the tumour enriched marked areas therefore ensuring a adequate amount of tumour cells to be microdissected for each sample. The content of tumour cells in all cases was assessed by a pathologist and was in the range of 40 to 90%. After baking the sections for five minutes on a hotplate at 70°C, the sections were deparaffinised in three changes of xylene for two minutes each and were taken to water by three changes of 100% ethanol for two minutes each and DEPC water for two minutes. Subsequently, the sections were stained with 0.5% methyl green to assist with needle microdissection. FFPE blocks were sectioned freshly just prior to needle microdissection and subsequent total RNA extraction to minimise RNA degradation after sectioning.Two protocols were used to extract total RNA from FFPE samples. The first protocol utilised the High Pure FFPE RNA Micro Kit  and the second protocol utilised TRIzol reagent. The latter protocol was adapted as described from a recently published protocol . The expIn the first protocol referred to as protocol 1 (P1), needle microdissected tissue from each sample was transferred immediately to a 1.5 mL Eppendorf tube containing 60 μL tissue lysis buffer provided by the High Pure FFPE RNA Micro Kit. Total RNA was extracted according to the manufacturer's protocol, eluted in 20 μL elution buffer and stored at -80°C.g for 14 minutes at 4°C the upper aqueous layer was immediately transferred into a new 1.5 mL Eppendorf tube. An equal volume of 2-propanol was added to the aqueous layer, vortexed thoroughly and incubated overnight at -20°C. The sample was centrifuged at 12,000g for 10 minutes at 4°C. The supernatant was removed. The RNA pellet was washed with 1 mL 70% ethanol (4°C), vortexed thoroughly and centrifuged at 12,000g for five minutes at 4°C. The supernatant was removed and the 70% ethanol washing step was repeated. The supernatant was removed again and the RNA pellet was dried for 15 minutes at room temperature and resuspended in 30 μL RNase free water. Residual genomic DNA co-extracted with total RNA was digested by DNase treatment employing the Turbo DNA-Free kit (Ambion) according to the manufacturer's instructions in a final volume of 50 μL. The extracted total RNA was stored at -80°C.In the second protocol referred to as protocol 2 (P2), needle microdissected tissue from each sample was immediately transferred to a 1.5 mL Eppendorf tube containing 260 μL of the lysis buffer from the Agencourt FormaPure Kit  and incubated at 70°C for one hour. Subsequently the tube was cooled to room temperature, 20 μL proteinase K provided with the FormaPure Kit was added and incubated at 55°C for one hour. The reaction mixture was cooled to room temperature, 500 μL TRIzol  and 100 μL chloroform were added, vortexed thoroughly and incubated for three minutes. After centrifugation of the tube at 12,000260/A280.Total RNA concentrations were measured by the NanoDrop ND-2000 spectrophotometer  after DNase treatment for each sample derived by each protocol in duplicate. Mean values were used to calculate the total RNA input for cDNA synthesis. RNA purity was estimated by the absorbance ratio AOne hundred fifty and 75 ng respectively of total RNA was reverse transcribed using the Superscript III Reverse Transcriptase  with 250 ng random hexamers  according to the manufacturer's instructions in the presence of 20U RNase inhibitor (Roche) in a final volume of 20 μL. The mixture was incubated for one hour at 55°C. The resulting cDNA was stored at -20°C.TBP mRNA (NM_003194) as the target sequence  and 2 μL  of undiluted cDNA as template respectively. The initial denaturation  was followed by 40 cycles of 30 seconds at 95°C, 30 seconds at 60°C and 30 seconds at 72°C, and a final extension step at 72°C for seven minutes. Genomic DNA extracted from peripheral blood from normal individuals (2 ng/μL) was used as negative control and a cDNA mixture prepared from total RNA of different cell lines served as a positive control. Each sample was analysed once.PCR was performed on the Veriti 96-well Thermal Cycler  in a Thermo-Fast 96 PCR Detection Plate MkII  with a final reaction volume of 20 μL, containing 350 nmol/L each of the primers 92-F: 5'-GGATAAGAGAGCCACGAACC-3' and 92-R: 5'-TGCCAGTCTGGACTGTTCTT-3', 550 nmol/L each of the primers 161-F: 5'-GGGCACCACTCCACTGTAT-3' and 161-R: 5'-CACGAAGTGCAATGGTCTTT-3', 250 nmol/L each of the primers 252-F: 5'-GGGAGCTGTGATGTGAAGTTT-3' and 252-R: 5'-TGAGAGCCATTACGTCGTCT-3', 100 nmol/L each of the primers 300-F: 5'-GGCGGAAGTGACATTATCAA-3' and 300-R: 5'-CAGGCTGTTGTTCTGATCCA-3' , 200 μmol/L of each dNTP, 0.5U of HotStarTaq DNA Polymerase  in 1× of the supplied PCR buffer containing 2.5 mmol/L MgClHpaII DNA Molecular Weight Marker (GeneWorks) was run alongside the PCR products to determine their size.The PCR products were evaluated for band abundance and size by agarose gel electrophoresis. The samples were run on a 2% (w/v) agarose gel in a 1× TBE Buffer system and stained with ethidium bromide. The wells were loaded with 20 μL of the PCR product mixture with 5 μL 5× loading dye. One μL pUC19/P (Crossing Point) value corresponds to the current recommended term Cq (Quantification Cycle) value [PCR was performed on the LightCycler 480 Instrument (Roche). Resulting data were analysed and quantified with the LightCycler 480 software release 1.5.0 (Roche), utilising the second derivative maximum method . The cale) value .TBP mRNA (NM_003194) as the target sequence  in a final reaction volume of 10 μL using the e Figure . The TBPeviously . 300 nmohttp://www.graphpad.com). Where appropriate, data are presented as the mean ± standard deviation (SD). Nonparametric correlations between a longer amplicon size in the multiplex endpoint RT-PCR assay and the appropriate Cq value obtained in RT-qPCR were evaluated by calculating the Spearman correlation coefficient. A two-tailed P-value  of <0.05 was considered to be statistically significant for each correlation.Statistical analyses were performed using GraphPad Prism version 5.03 for Windows (GraphPad Software, San Diego, CA, The authors declare that they have no competing interests.EAT, TM and DJB carried out the experiments. TM, EAT and AD conceived the experiments and analysed the data. SBF, AD and TM initiated the project and supervised the work. All authors contributed important ideas throughout the project and were involved in the writing of the manuscript. All authors have read and approved the manuscript.


Diabrotica spp.). This study provides new information to improve the environmental assessment of dsRNAs that become pesticidal through an RNAi process. Three agricultural soils differing in their physicochemical characteristics were obtained from the U.S., Illinois , Missouri  and North Dakota , and exposed to the target dsRNA by incorporating insect-protected maize biomass and purified (in vitro-transcribed) DvSnf7 RNA into soil. The GM and control (non-GM maize) materials were added to each soil and incubated at ca. 22°C for 48 hours (h). Samples were collected at 12 time intervals during the incubation period, extracted, and analyzed using QuantiGene molecular analysis and insect bioassay methods. The DT50  values for DvSnf7 RNA in IL, MO, and ND soils were 19, 28, and 15 h based on QuantiGene, and 18, 29, and 14 h based on insect bioassay, respectively. Furthermore, the DT90 (time to 90% degradation) values for DvSnf7 RNA in all three soils were <35 h. These results indicate that DvSnf7 RNA was degraded and biological activity was undetectable within approximately 2 days after application to soil, regardless of texture, pH, clay content and other soil differences. Furthermore, soil-incorporated DvSnf7 RNA was non-detectable in soil after 48 h, as measured by QuantiGene, at levels ranging more than two orders of magnitude . Results from this study indicate that the DvSnf7 dsRNA is unlikely to persist or accumulate in the environment. Furthermore, the rapid degradation of DvSnf7 dsRNA provides a basis to define relevant exposure scenarios for future RNA-based agricultural products.A laboratory soil degradation study was conducted to determine the biodegradation potential of a DvSnf7 dsRNA transcript derived from a Monsanto genetically modified (GM) maize product that confers resistance to corn rootworm (CRW;  Genetically modified (GM) crops expressing traits that confer protection from insect pests and facilitate weed management provide significant value in agriculture and require novel modes of action for sustainable efficacy. Comprehensive science-based ecological risk assessments (ERA) are required to ensure that products with benefits for agriculture are also safe for the environment. Ecological risk from the cultivation of a GM crop will be a function of both potential harm (hazard) and environmental exposure Bacillus thuringiensis (Bt) is minimal due to the lack of persistence of Bt proteins in soil Bt cotton showed that Cry1Ac has a half-life (DT50) of 16 days (d) when incorporated into soil microcosms Bt maize Bt crops, which showed no detection, persistence, or accumulation of Cry1Ac in Bt-cotton fields Bt-maize fields Bt proteins do not accumulate as a result of continuous cultivation With the introduction of GM crops, attention has focused on the environmental fate of transgenic-derived DNA and proteins. The environmental exposure of Cry proteins derived from Bt proteins, the rate of nucleic acid degradation can be influenced by the biophysical characteristics of soil and sediments in addition to other abiotic and biotic factors Similar to the case of Degradation of DNA in the soil environment is likely due to processing by DNases. High molecular weight gDNA molecules may first be cleaved into oligonucleotides of approximately 400-bp by microbial restriction endonuclease I activity. These oligonucleotide substrates can then undergo further degradation through the activity of microbial-produced DNases. Bacterial populations may also increase by approximately one order of magnitude in soil exhibiting DNA-degrading activity et al., soil samples amended with either dried DNA or RNA were analyzed for released nitrogen and CO2 evolution as a measure of nucleic acid degradation. The results of this study found that RNA degraded as quickly as DNA in different soils Less information is available on the degradation kinetics of RNA in soil, however data collected to date provides no evidence that RNA persists any longer than DNA Crops that express double-stranded RNA (dsRNA) molecules are being developed which take advantage of the endogenous RNAi machinery of target insects and can produce highly specific insecticidal oligonucleotides (siRNA) for agricultural pest control. DvSnf7 dsRNA expressed in GM maize confers protection against the Western Corn Rootworm (WCR) In vitro T7 RNA Polymerase-transcribed 968 nucleotide (nt) DvSnf7 RNA (IVT DvSnf7 RNA) was used to treat soil samples and serve as the reference standard for the QuantiGene 2.0 microplate assay TAATACGACTCACTATAGGG) in pUC19 plasmid. The identity of the recombinant pUC plasmid template used to produce the IVT DvSnf7 RNA was verified by DNA sequencing. For IVT RNA synthesis, the pUC plasmid was linearized by BglII restriction digestion and incubated with nucleoside triphosphates  and T7 RNA Polymerase in transcription buffer overnight at 37°C. The reaction was then treated with DNase I  and extracted with phenol∶chloroform (1∶1 volume∶volume). The size of the IVT DvSnf7 RNA was confirmed by agarose gel electrophoresis and its concentration was determined using a NanoDrop 8000  according to the manufacturer's instruction. Aliquots of the IVT DvSnf7 RNA sample were stored in a −80°C freezer.2PO4, 10 mM Na2HPO4, 137 mM NaCl, 2.7 mM KCl, pH 7.0; Roche Diagnostics, Indianapolis, IN) to the desired concentrations. Given the mass ratio of plant tissue to soil in the samples, the QuantiGene and insect bioassay methods were not sufficiently sensitive to generate quantifiable measurements of the endogenously expressed DvSnf7 RNA over the entire experimental range (90% degradation). Samples were therefore treated with an IVT DvSnf7 RNA solution of sufficient concentration to detect dsRNA after 90% of the initial DvSnf7 RNA had degraded. The IVT DvSnf7 solution was diluted such that ∼400 µl solution was required for dosing each sample. Samples were incubated at ambient temperature for the required interval and then placed in −80°C storage until all samples were collected and prepared for extraction.Three soil types were collected from the top 15 cm of fields in Illinois (IL), Missouri (MO) and North Dakota (ND) and subsequently characterized for percent sand, silt and clay; USDA textural class; bulk density; percent organic matter; pH; cation exchange capacity (CEC); field moisture capacity (FMC) at 1/3 Bar and at 15 Bar; and a number of chemical elements . The three soils were sieved at AGVISE Laboratories through a 2 mm screen to remove non-soil debris prior to analysis. Upon receipt, each soil was spread on large trays to air dry and then repacked and stored at ambient temperature under aerobic conditions. At the start of the study, 1 g soil samples were weighed into 50 ml conical tubes. Samples containing maize tissue were amended with a mixture of DvSnf7-expressing lyophilized root and shoot tissue (20∶80 w/w) derived from V8-V10 growth stage plants at a rate of 20 mg tissue per g soil. Due to relatively low expression of DvSnf7 in maize tissue, a solution of IVT DvSnf7 was diluted in 1× PBST , the pH 7 buffer was substituted with 1× PBST pH 12 to improve the extraction efficiency of clay-bound RNA. Samples were then agitated in a paint shaker (Harbil), for 10 minutes and passed through a 0.22 µm vacuum filter. Samples containing high clay ND soil were centrifuged for 10 minutes at 7500× Prior to sample analysis by a DvSnf7-specific QuantiGene assay , aliquots of sample extracts were purified to remove potential hybridization inhibitors . Briefly, 1 ml aliquots of the sample extracts were mixed with an equal volume of citrate-buffered phenol pH 4.3  and chloroform . Emulsified samples were separated via centrifugation and the RNA was precipitated from the aqueous phase with isopropanol. Following precipitation, samples were centrifuged, air-dried, and resuspended in DEPC-treated water . The concentration of DvSnf7 RNA in purified samples was determined with a QuantiGene 2.0 assay following the manufacturer's instructions. A custom QuantiGene probe set was designed by the manufacturer to hybridize to the sequence within DvSnf7 and IVT DvSnf7 RNA that confers insecticidal activity. The IVT DvSnf7 RNA and the sequence-specific recognition by the QuantiGene probe set has previously been described in detail IVT DvSnf7 RNA that served as a standard curve to quantify DvSNf7 RNA in soil extracts. For each bioassay, extract solutions were prepared by aliquoting each test and control soil sample extract into three replicates, diluting with purified water, incorporating the dilution into an agar-based SCR diet  and then vortex-mixing the solution until visually homogeneous. These diet mixtures were then dispensed in 0.25 ml aliquots into 48-well plates . SCR larvae (≤30 h after the first observation of hatching) were individually placed on these diets with a target number of 24 insects tested for each sample replicate. The insects were incubated for a period of 12 d at 27°C, 70% relative humidity and in total darkness. Assays were evaluated for survival at the end of the incubation period and results were subjected to a correction to account for control mortality. Standard curves for SCR bioassays were analyzed by probit analysis under PROC PROBIT in SAS, the OPTC function was used to correct for control mortality, and DvSnf7 soil concentrations were estimated by inverse prediction.Southern Corn Rootworm (SCR) was selected for these bioassays because it was more amenable than Western Corn Rootworm (WCR) to laboratory bioassays and displayed comparable sensitivity to the DvSnf7 RNA 50 and DT90 values, the time periods required for 50% and 90% degradation of the initial DvSnf7 RNA concentration in soil.A standard 3-parameter logistic equation The environmental fate of DvSnf7 dsRNA was determined in three different soils that have physical characteristics representative of world regions where maize is grown, including a silt loam (IL), loamy sand (MO), and clay loam (ND) soil. Prior to the study, the three soils were characterized by determining percent sand, silt and clay, USDA textural class, bulk density, percent organic matter, pH, cation exchange capacity (CEC), and field moisture capacity (FMC) at 1/3 Bar and 15 Bar .in planta expression of DvSnf7 RNA is low, tissue-amended soil samples were also supplemented with a solution of IVT DvSnf7 dsRNA to ensure that a robust quantitation could be obtained at all time intervals of an experimental range covering at least 90% degradation of the initial DvSnf7 RNA concentration. The concentration of DvSnf7 in soil samples collected at 12 time intervals during the 48 h incubation was determined using a QuantiGene assay. The QuantiGene assay detects both in planta-expressed DvSnf7 and in vitro-transcribed DvSnf7 via hybridization with target sequence-specific probes. After an initial induction period of a few hours, DvSnf7 RNA degraded rapidly in all three soils and was no longer detected by QuantiGene after 24–36 h  to about 29 h (MO soil) using results obtained from QuantiGene and SCR bioassay . These results indicate that the DvSnf7 RNA was degraded and devoid of any detectable biological activity within 2 days of incorporation into soil.Degradation kinetics of DvSnf7 RNA in soil amended with maize tissue were calculated using a 3-parameter logistic equation. The estimated DTbioassay . The estSince DvSnf7 RNA was observed to degrade rapidly in soils amended with maize tissue, we tested whether dsRNA would be degraded with similar kinetics when applied to soil alone. The three representative soils were treated with a solution of IVT DvSnf7 dsRNA and incubated at ambient temperature for up to 48 h. Analysis by QuantiGene demonstrated that regardless of soil class, DvSnf7 RNA degraded rapidly in soil alone, with similar kinetics to soil amended with maize tissue . These rTo determine whether the observed DvSnf7 degradation kinetics are dependent on the amount of dsRNA applied to the soil microcosms, the relationship between degradation kinetics and the initial dsRNA concentration was investigated. Tissue-amended silt loam soil (IL) was treated with four different DvSnf7 RNA concentrations ranging from to 0.3 to 37.5 µg per gram of soil and degradation kinetics of the dsRNA was measured at each treatment level. The lowest treatment level (0.3 µg/g) was the lowest initial dsRNA concentration that would allow quantifiable QuantiGene measurements after at least 90% degradation of the applied dsRNA. Despite varying the amount of DvSnf7 added to soil by more than two orders of magnitude, there was no significant observable change in dsRNA degradation kinetics . These rBt proteins that exhibit half-lives typically ranging from approximately one to several days This study demonstrates that the DvSnf7 dsRNA rapidly degrades in the soil environment with a half-life of less than 30 h. This degradation is relatively rapid when compared to Viable resident microbial communities have been shown to be necessary for the decomposition of leaf litter and plant genomic DNA The biodegradation of dsRNA is also likely mediated by microbial-produced ribonucleases 2) exhibited an exponential decrease in concentration with a DT90 of approximately 141 h and no detectable amount of RNA found after 14 d 14C and 3H exhibited up to 62% degradation after 14 d When RNA is released into the environment, the same RNases responsible for intra-cellular degradation are active in an extra-cellular capacity. Single-stranded RNA (ssRNA) from viral genomes exhibit a half-life on the order of days in seawater Bt proteins, the expression of DvSnf7 in planta is relatively low such that addition of a DvSnf7 RNA solution was required to produce a full and quantitative degradation profile in soil microcosms. Therefore, we tested whether the degradation kinetics were dependent on the concentration of dsRNA applied to soil. Despite varying the amount of dsRNA in soil microcosms by over two orders of magnitude, there was little observed change in the half-life of DvSnf7. Furthermore, there was no discernible correlation between the applied amount of the dsRNA and efficiency of analytical recovery from soil suggesting the soil microcosms were not saturated with the applied nucleic acid (data not shown). Consistent with these results, saturation was not observed when DNA was applied to microcosms over a range of concentrations up to 28 µg of DNA per gram of soil in planta by this GM maize is unlikely to persist in the soil environment.In comparison to In summary, we have demonstrated the environmental degradation of dsRNA in multiple soil environments. The degradation of dsRNA was characterized by an initial acclimation phase followed by a rapid loss of DvSnf7 RNA and its associated biological activity in three different soils, exhibiting half-lives ranging from about 14 to 30 h. Rapid degradation of the dsRNA was observed in soil alone or soil amended with maize tissue and the rate of degradation was largely independent of the RNA treatment level. Taken together these results demonstrate that the DvSnf7 dsRNA from a CRW-protected GM maize is unlikely to persist or accumulate in the soil environment. In a broader context, these results provide fundamental information to define environmental exposure scenarios for ecological risk assessment of future RNA-based agricultural products.


Behavioral choice alters one’s preference rather than simply reflecting it. This effect to fit preferences with past choice, is known as “choice-induced preference change.” After making a choice between two equally attractive options, one tends to rate the chosen option better than they initially did and/or the unchosen option worse. The present study examined how behavioral choice changes subsequent preference, using facial images for the choice options as well as blind choice techniques. Participants rated their facial preference for each face, and chose between two equally preferred faces and subsequently rated their facial preference. Results from four experiments demonstrated that randomly chosen faces were more preferred only after participants were required to choose “a preferred face,” (in Experiment 1) but not “an unpreferred face,” (in Experiment 2) or “a rounder face” (in Experiment 3). Further, preference change was still observed after participants were informed that choices were actually random (in Experiment 4). Our findings provide new and important implications characterizing the conditions under which random choice changes preference, and show that people are tempted to make a biased evaluation even after they know that they did not make the choice for themselves. Although people often believe that their preference guides choice, the idea that choice alters their preference has been an acceptable alternative One possible explanation for choice-induced preference change is that having to choose between two similarly attractive options causes cognitive dissonance, which is resolved by re-evaluating the options after the choice is made. This occurrence is referred to as “cognitive dissonance theory” An alternative explanation of choice-induced preference change is self-perception theory. Within the theory, it is assumed that individuals come to know their own preferences by inferring them from observations of their own behavioral choices to the extent that internal cues are ambiguous In the last few years, notable characteristics of choice-induced preference change have been empirically demonstrated. One remarkable aspect of the preference change is its stability. For example, Sharot, Fleming Yu, Koster and Dolan Other recent studies have developed a new method to measure preference change, and indicate that choice does not necessarily need to be guided by one’s own preference In the present study, we investigated the conditions under which arbitrary choices alter subsequent preferences, and whether preference change can be revoked once choice decisions are made. Using a blind choice task In Experiment 1, we investigated whether choice induces preference change even when options included facial images that had not previously been examined. Previous studies have examined this post-choice change in preference by using a variety of options  that could be expected or experienced, such as kinds of illnesses All experiments were approved by the local ethical committee of the Keio University, Japan. Before starting each experiment, participants individually provided informed consent and signed a written consent form. A proper debriefing was conducted for each participant at the end of our study, explaining the purpose of using deceptive instructions during a blind choice task as described hereafter.Twenty adults  participated in the present experiment. All participants had normal to corrected-normal vision and were not aware of the purpose of the experiment. They were individually tested and paid 1,000 Japanese yen for their participation.www.facegen.com/) in four subcategories: two races ×two genders . All faces were emotionally neutral, and had no hair. In our preliminary experiment, a separate group of seven participants  rated facial attractiveness on a scale from 1 to 8 . The mean scores for the attractiveness ratings of the faces were 4.15±0.40 for the male faces and 4.20±0.58 for the female faces.The facial stimuli were presented on a 21-inch monitor  controlled by the MATLAB program  using a MacBook Pro . Participants sat at a viewing distance of 57 cm away from the monitor. Stimuli consisted of 240 faces generated by computer software . In the task, participants were required to evaluate their subjective preference for faces presented on a computer screen one at a time. Face images were 7°×11° in visual angle in the center of the screen against a black background. In each trial, participants pressed the space key to initiate presentation of a face image and rated their preference for that face on a scale from 1 to 8 using numbers on their keyboard . Participants were able to view the face until a response was made in each trial . Two sessions were separated according to the gender of the faces, in which the faces were presented in a random order. The order of sessions  was counter-balanced across the participants.In the blind choice task , particiAfter completing the choice task, the participants were again required to evaluate subjective preference for facial stimuli during the post-choice rating task. In the task, all 240 faces were presented one by one in a randomized order. This was completely identical to the pre-choice rating task.i − µ) − the value of the stimulus relative to all other stimuli in that session. We performed a one-sample t test to examine whether these scores were significantly different from zero (µ = 0). A paired t test was conducted to examine the differences in preference change between the chosen faces and unchosen faces.We analyzed the data in the same manner as in Sharot et al. t test revealed preference changes for the chosen faces (t(19) = 3.50, p<.005), while ratings for the unchosen faces were not modulated (t(19) = −1.13, p>.1). The significant increase in ratings for the chosen face was larger than the non-significant decrease for the unchosen faces (t(19) = 3.33, p<.005).The one-sample en faces . RatingsThis experiment demonstrated that even when choices were made randomly, , choice shaped facial preference. Indeed, facial preference ratings for chosen options increased after making choices while ratings for unchosen options remained the same. This result was consistent with that reported by Sharot et al. In most previous studies, the choice task in typical free-choice paradigm asks participants to choose a more attractive or preferred option between two alternatives Twenty different adults  participated in Experiment 2 . All participants had normal to corrected-normal vision. They were individually tested after taking informed consent and paid 1,000 Japanese yen for their participation.The facial stimuli and the experimental settings were identical to those in Experiment 1.The pre-choice and post-choice rating tasks were identical to those in Experiment 1. Only the blind choice task was different from that of Experiment 1, as participants were asked to choose unpreferred faces during the blind choice task.t test revealed no preference changes when choosing unpreferred faces (t(19) = 0.51, p>.1), or unchosen faces (t(19) = 0.16, p>.1). Preference changes in the chosen and unchosen faces did not significantly differ (t(19) = 0.25, p>.1). These results suggest that preference-related choice does not always induce preference change. That is, post-choice change in preference was not seen in unpreferred judgment. These results cannot be fully accounted for by the cognitive dissonance theory. Cognitive dissonance theory predicts that choosing unpreferred faces induces preference change, because there are dissonant cognitions between choice of unpreferred faces and preference for faces. The results in Experiment 2 indicated that the choice between a preferred option and unpreferred option has a different implication in the psychological process in a binary choice situation despite semantic correspondence. Indeed, previous research has indicated that assessing an object as preferable and unpreferable relies on different psychological mechanisms A one-sample ed faces . Rating However, we could not rule out the possibility that experimental artifacts ostensibly canceled out the effect of preference change in Experiment 2. Participants were asked to choose ‘preferred’ faces in Experiment 1, whereas they were asked to choose ‘unpreferred’ ones in Experiment 2. According to cognitive dissonance theory, declaring options as ‘unpreferred’ might decrease ratings for them during a post-choice task. However, our data did not show this pattern within a preference change effect. As pointed out in some previous studies, it could be that merely selecting or attending to an affectively neutral stimulus influences its subsequent affective evaluation even when participants make a decision unrelated to preference To test whether post-choice change in preference is triggered by the mere act of choosing that is not directly related to preferential decision-making, we conducted Experiment 3, in which participants were asked to choose a preferred face during some trials (preference judgment) and a rounder face during other trials (roundness judgment). The roundness judgment is often used as a comparative condition to preference judgment for facial attractiveness Twenty-one different adults  participated in Experiment 3 . Again, all participants had normal to corrected-normal vision. They were individually tested after taking informed consent and paid 1,000 Japanese yen for their participation.The facial stimuli and the experimental settings were identical to those in Experiment 1 and 2. As a preliminary experiment, a separate group of five participants  rated the facial roundness of the facial stimuli used in Experiment 1 on a scale from 1 to 8 . The mean scores for the roundness ratings of the faces were 4.33±1.57 for male faces and 4.83±1.39 for female faces, respectively. Facial attractiveness was based on the preliminary findings from Experiment 1.This third experiment contained the pre-choice rating, the blind choice, and the post-choice rating tasks. The pre-choice and post-choice rating tasks were identical to those in Experiments 1 and 2. Only the blind choice task differed from Experiments 1 and 2; in the blind choice task, there were two types of trials: preference judgment and roundness judgment trials. All pairs of faces were determined by a MATLAB program and were divided into these two trials in which an approximately equal number of trials for each set were included. In the preference judgment trials, participants were instructed to choose a more preferred face between two alternatives as in Experiment 1. During the trials, after briefly presenting two dummy faces, the instruction on the center of screen read “Preference.” In the roundness judgment trials, after briefly presenting two dummy faces, participants were asked to choose the rounder of the two faces when the instruction on the screen read “Roundness”. Before starting the experiment, participants were fully instructed to judge the physical roundness of faces on each pair . These trials were intermixed throughout a session and the number of each trial was approximately identical. Crucially, choices during the blind choice task were not based on pre-existing preferences for both preference and roundness judgment. As with Experiment 1, approximately 70% of both the preference judgment and roundness judgment trials consisted of pairs of faces that participants had rated the same in the pre-choice rating task . The rest of the trials during the preference judgment trials included pairs of faces differently rated by the participants. We assigned the more preferred face onto side that a participant previously chose and the less preferred face onto opposite side of the screen . Similarly, of the remaining trials during the roundness judgment consisted of pairs of faces that a separate group of participants had rated differently for facial roundness. For those trials, we assigned the rounder face onto the side that the participant previously chose and the less round face onto the opposite side .F = 10.5, p<.005). The simple-effect analysis revealed that change in preference for the chosen face was significantly higher than the unchosen face in preference judgment  = 4.15, p<.05), and that the unchosen face was significantly higher than the chosen face during the roundness judgment  = 8.26, p<.01). Neither the main effect for choice nor that in judgment type was statistically significant  = 0.29, p>.1, for choice; F = 0.41, p>.1, for judgment type). In addition, one-sample t tests revealed that ratings for the chosen faces for the preference judgment trials significantly increased after making choices (t(20) = 3.04, p<.01), while those for the unchosen faces was not modulated by choice (t(20) = 0.19, p>.1). In contrast, neither post-choice change in preference for the chosen nor the unchosen during the roundness task was statistically significant  = −0.92 p>.1; unchosen, t(20) = 1.71 p>.1). That is, it indicated that ratings were changed after the blind choice only when participants responded to choose preferred faces between two alternatives, whereas post-change in preference was significant between chosen and unchosen faces for the roundness task.To examine the difference in preference change as a dependent variable between preference trials and the roundness trials, we conducted a 2×2 repeated-measures ANOVA with choice  and judgment type in a trial , which were both within-subject factors. Results  demonstrThese results could ensure that the mere act of choosing that is not directly related to preference decision-making was not sufficient to induce preference change. As far as our data is concerned, we assumed that enhanced commitment by a choice decision for preferred faces could produce preference change, but not the mere act of choice relatively independent of preference . Therefore, what to choose is important for choice-induced preference change.Experiment 1 revealed that chosen faces came to be preferred even when choices were not guided by pre-existing preferences. Here, we examined the effects when participants were informed that their choices had not reflected their own preferences, but only after the choices were made. Recent studies suggest that the update of preference occurs immediately after making a choice and its updated preference is stable Twenty-two different adults  who did not participate in Experiments 1, 2, or 3 participated in Experiment 4. Again, all participants had normal to corrected-normal vision. They were individually tested after taking informed consent and were paid 1,000 Japanese yen for their participation.The facial stimuli and the experimental settings were identical to those in Experiment 1, 2 and 3.Most parts of the experimental tasks were identical to those in Experiment 1 except for the fact that participants received debriefing for the blind choice task immediately after the choice task. Before the blind choice task, participants were instructed to choose a preferred face, although they cannot consciously perceive their options, as done in Experiment 1. After completing the choice task, the experimenter gave the participants a debriefing form describing that the procedure of the blind choice task made it impossible to choose truly preferred faces based on their own preferences and asked them to carefully read and understand the contents. The debriefing of subjects was done using both written and oral explanations. During the debriefing, the illustrative figure complemented that the two briefly presented faces (dummy faces) were indeed identical faces and crucially the two faces were always unrelated to the target faces that were presented after choice, whereby participants could not make preference decisions based on their own preferences. All of the participants could fully understand this debriefing instruction, and signed the written form and participated in the post-choice rating task.t tests revealed preference changes even after participants received the debriefing feedback (t(21) = 2.69, p<.05), while ratings for the unchosen faces were not modulated by choice (t(21) = −0.89, p>.1). The increase in ratings for the chosen face tended to be larger than the non-significant decrease for the unchosen faces (t(21) = 1.94, p<.1).One-sample feedback . RatingsThese results revealed that choice-induced preference change persisted even after participants explicitly understood that their choices were not based on their own preferences. In fact, randomly chosen faces were more preferred even after participants explicitly understood that preferences do not have to fit with their choices. This implies a tendency for preference change is close to that of Experiment 1, though we could not determine whether the debriefing before post-choice rating diminished the preference change effect. Future study should address whether the debriefing eliminate the effect by comparing debriefed and non-debriefed conditions within an experiment. Nevertheless, our results indicate that preference can be changed irrespective of whether participants believe that the choices for face to be true or false. One interpretation of these results are that choice-induced preference change may be irrevocable even if participants were informed that choice is actually random later, once choices trigger revaluation at the moment of choice The present study revealed several important features of choice-induced preference change. Choice-induced preference change has been examined using a variety of option types, such as household objects Since Brehm’s Alternatively, our results can be explained by self-perception theory that does not posit the reduction of cognitive dissonance However, both theories cannot fully predict our novel observations from Experiments 1 and 2 showing that randomly chosen faces were more preferred only after participants were required to choose “a preferred face,” but not “an unpreferred face”, suggesting that preference-related choice does not always induce preference change. Even though choices for preferred and unpreferred options were semantically opposite and both revealed relative preference for each option in a binary choice situation, each of the choices influenced subsequent preference differently. This may be partially due to the fact that face is generally a positive stimulus and participants potentially evaluate how attractive someone is, but not how unattractive she or he is In light of the functional separability, choices of unpreferred options may induce revaluation under some conditions. Indeed, Sharot et al. The results from Experiment 4 demonstrated that preference change was still observed even after people explicitly knew their choice had been random. This raises the possibility that post-choice change in preference is not derived from consciously fitting preferences with choices in post-choice rating task, and that the updated preferences tend to be irrevocable once preference decision is made. These results are consistent with newer models suggesting that preference change occurs right at the moment of choice, thus immediately updating one’s preference Alternatively, a persistent impact of choice can be interpreted in terms of implicit choice memory The results from the present four experiments demonstrated that randomly chosen faces were more preferred only after participants were required to choose “a preferred face,” but not “an unpreferred face,” and preference change was observed even after participants were informed that choices were actually random. Our results show important constrains under which random choice alters subsequent preference, suggesting different psychological processes involved in choice of preferred option and unpreferred one. Moreover, the impact of choice on preference formation may persist, once people make a choice even though it is actually random. This implies that people are tempted to make a biased evaluation with unaware of the causal origin of their own preference.


Caenorhabditis elegans the UNC-40 (DCC) receptor mediates a response to the UNC-6 (netrin) guidance cue that directs HSN axon development. UNC-40 becomes asymmetrically localized within the HSN neuron to the site of axon outgrowth. Here we provide experimental evidence that the direction of guidance can be explained by the stochastic fluctuations of UNC-40 asymmetric outgrowth activity. We find that the UNC-5 (UNC5) receptor and the cytoskeletal binding protein UNC-53 (NAV2) regulate the induction of UNC-40 localization by UNC-6. If UNC-40 localization is induced without UNC-6 by using an unc-53 mutation, the direction of UNC-40 localization undergoes random fluctuations. Random walk models describe the path made by a succession of randomly directed movement. This model was experimentally tested using mutations that affect Wnt/PCP signaling. These mutations inhibit UNC-40 localization in the anterior and posterior directions. As the axon forms in Wnt/PCP mutants, the direction of UNC-40 localization randomly fluctuates; it can localize in either the anterior, posterior, or ventral direction. Consistent with a biased random walk, over time the axon will develop ventrally in response to UNC-6, even though at a discrete time UNC-40 localization and outgrowth can be observed anterior or posterior. Also, axon formation is slower in the mutants than in wild-type animals. This is also consistent with a random walk since this model predicts that the mean square displacement (msd) will increase only linearly with time, whereas the msd increases quadratically with time for straight-line motion.How the direction of axon guidance is determined is not understood. In  Caenorhabditis elegans extends short neurites in different directions immediately after the animal hatches. These neurites, which dynamically extend and retract filopodia, become restricted to the ventral side of the neuron where a leading edge forms. Multiple neurites extend from this surface until one develops into a single axon extending to the ventral nerve cord , the Wnt receptor MIG-1 (Frizzled), the planar cell polarity (PCP) component VANG-1 (Van Gogh), or the UNC-40 effectors, MIG-10 (Lamellipodin) and MADD-2 (TRIM) inhibit intracellular UNC-40 localization in the anterior or posterior directions. In the mutants the probability of UNC-40 being present at a specific side of the neuron is altered; UNC-40 localizes with some probability to either the ventral, anterior, or posterior directions during initial axon formation. The probability of UNC-40 localization in the ventral direction is higher than the probability of anterior or posterior localization. This allows a biased random walk model to be experimentally tested. We observe that the behavior of the system approximates a biased random walk. As predicted, even though the direction of UNC-40 localization can be in the anterior or posterior direction, axon formation will nevertheless be guided towards the ventral source of UNC-6 over time. This is consistent with the direction of guidance being determined by the sequence of stochastic fluctuations of UNC-40-mediated axon outgrowth activity, rather than by the direction of UNC-40 localization and axon outgrowth at any discrete time. We also observe that the time in which it takes for an axon to form is delayed in the mutants. This is consistent with how displacement is described by a random walk. That is, the mean square displacement will tend to increase only linearly with time, not quadratically with time as is the case of straight-line motion. Together these results indicate that the direction and timing of UNC-6 guidance can be explained by the stochastic fluctuation of intracellular UNC-40 outgrowth activity and the exertion of a bias by multiple cues.Experimental evidence for a biased random walk is obtained by asking whether the system behaves as a random walk when it is manipulated. In this paper we observe the behavior of the system by removing the influence of different external asymmetric guidance cues that regulate the probability of movement in different directions. Previously we reported evidence that the HSN response to UNC-6 is indeterminate for the direction of UNC-40 localization and axon outgrowth. An UNC-40 variant, UNC-40 (A1056V), induces an asymmetrical localization of UNC-40 in HSN even in the absence of UNC-6 . UNC-40 C. elegans variety Bristol strain N2, strains containing the following mutations and transgenes were used in these studies:All strains were maintained as described . Strainsmig-1(e1787), unc-40(e1430), unc-40; LGII unc-53(n152) LGIII, mig-10(ct41); LGIV, unc-5(e53), egl-20(n585), kyIs262 ; LGV, rpm-1(ur299), madd-2 (ky592); LGX, unc-6(ev400), vang-1(tm1422). Transgenes maintained as extrachromosomal arrays included: zdIs5 [mec-4::GFP], kyEx1212 , kyEx927  , gmEx384 . Some strains were provided by the Caenorhabditis Genetics Center.LGI, Genotypes of strains carrying multiple mutations were confirmed by PCR for deletions or sequencing of individual mutations. All mutant alleles used in this study either eliminate or severely reduce gene function. The hermaphrodite sex was analyzed in all experiments.zdIs5 transgene, which encodes mec-4::GFP. An anterior protrusion was scored as the axon traveling laterally more than 3 cell body length from the cell body. Dorsal or posterior protrusion was scored as the axon traveling dorsally or posteriorly for a distance greater than two cell body lengths from the cell body. The AVM was considered multipolar if more than one process, greater than one cell body length, was observed.For analysis of the AVM axon protrusion phenotype, L4 stage larvae were mounted on a 5% agarose pad. The AVM axon was visualized in L4 stage larvae expressing the unc-86::myrGFP transgenic strain, KyIs262. Synchronized populations were obtained by allowing eggs to hatch overnight in M9 buffer without food. The resulting L1 nematodes were fed and grown at 20°C to the specified developmental stage. The HSN development at different larval stages in mutants (L1–L4) was followed by the gonad size, , distal tip cell migration (mid-L3) and P6.p cell invagination (L3–L4 transition and mid-L4) as markers  microscopy. The UNC-40::GFP localization was determined by measuring the average intensity under lines drawn along the dorsal and ventral edges of each HSN cell body by using IP lab software.For analysis of UNC-40::GFP in HSN neurons, L2 stage larvae expressing the P≧0.05 and was considered asymmetrical if P≤0.05. Further, within an asymmetric population, the highest percent intensity was considered to localize UNC-40::GFP to either anterior, posterior or central domain of the dorsal surface.For analysis of the anterior–posterior orientation of UNC-40::GFP along the dorsal surface, the dorsal segment was geometrically divided into three equal lengths . The line-scan intensity plots of each of these segments were recorded. ANOVA test was used to determine if there is a significant difference between intensities of three segments. The dorsal distribution was considered uniform if egl-20 and mig-1 mutants were determined by Chi-square (χ2) analysis. In this assay, only HSNR migration and axon outgrowth was quantified. The HSNR cell migration in egl-20 and mig-1 mutants was considered as defective if it migrated less than 70% of the distance between anus and vulva (egl-20(n585), χ2 = 0.014, P = 0.90; mig-1(n1787) χ2 = 1.346, P = 0.24; these P values (>0.05) indicate that HSN cell migration and HSN axon defects are independent events.For nd vulva . The genunc-53 mutants axon extension and guidance are defective  is a cytoskeletal binding protein related to the mammalian Neuronal Navigators (NAVs) and in efective . The NAVefective . In C. end axons .unc-6(ev400) mutation the AVM axon has a strong bias to migrate anteriorly, whereas mutants with the unc-53(n152) allele have the wild-type ventral projection. Surprising, a different pattern emerges in unc-53(n152); unc-6(ev400) double mutants; the axon will protrude in any direction; anterior, posterior, dorsal, or ventral ; unc-6(ev400) mutants , was shown not to disrupt axon protrusion unless in the background of the loss-of-function unc-6(ev400) mutation or the unc-6(rh46) mutation.The unusual axon protrusion pattern observed from AVM, prompted us to examine the effects of  mutants ; Table 2nd unc-6 . In thatunc-40 mutants and this rescuing UNC-40::GFP protein becomes localized to the ventral side of HSN beginning at the early L2 stage when a distinct ventral leading edge develops ;unc-6(ev400) or unc-40(ur304);unc-6(rh46) mutants intracellular UNC-40::GFP becomes localized in different directions (unc-40(ur304);unc-6(ev400) and unc-53(n152);unc-6(ev400) mutants, we examined UNC-40::GFP localization during HSN axon formation in the unc-53(n152); unc-6(ev400) mutants. In these experiments, we first assay for the distribution of UNC-40::GFP along the dorsal–ventral axis (unc-40(ur304) allele. i.e. removing the UNC-6 bias reveals a stochastic fluctuation.UNC-40::GFP becomes localized to the ventral side of the neuron beginning in the early L2 stage , whereasy of HSN . In the rections . Becauseral axis . In the ral axis . We findUNC-6 is thought to interact with UNC-40 homodimer receptor complexes and with UNC-40 and UNC-5 complexes . We reasunc-53(n152) mutation and an unc-5 loss-of-function mutation both cause mild protrusion phenotypes, double unc-53(n152); unc-5(e53) mutants show a strong phenotype that is similar to unc-6(ev400) mutants (unc-53(n152) and unc-5(e53) mutants, in the double mutants the induction of a polarized distribution of UNC-40 is defective (unc-53(n152); unc-5(e53) mutants UNC-40::GFP localization is similar to that observed in unc-6(ev400) or unc-5(e53); unc-6(ev400) mutants, i.e. UNC-40::GFP is not asymmetrically localized but is uniformly dispersed around the periphery of HSN ; unc-5(e53) and unc-53(n152);unc-6(ev400) have opposite UNC-40 localization phenotypes. It was, therefore, of interest to know whether either phenotype predominates in triple mutants. We find that the triple mutants, unc-53(n152);unc-5(e53);unc-6(ev400), have axon protrusion phenotypes and UNC-40 localization phenotypes similar to the unc-53(n152);unc-6(ev400) mutants. That is, the HSN axon often protrudes from the dorsal or anterior sides of the neuron  and the MIG-1 (frizzled) receptor affect the migration of the HSN cell along the anterior–posterior axis during embryogenesis . To deteross HSN . The eglild type , indicat animals , Fig. 6BC. elegans is encoded by vang-1. Similar to the phenotype of egl-20 and mig-1 mutants, in vang-1 mutants UNC-40::GFP can be asymmetrically localized to the anterior or posterior sides of HSN  (A core component of the Wnt/PCP pathway is Van Gogh or Strabismus (Vang/Stbm or Vangl)  . Togetheegl-20 and mig-1 mutants MIG-10::GFP is uniformly dispersed around the periphery of HSN  proteins and it co-localizes with MIG-10 (lamellipodin), an actin-regulatory pleckstrin homology (PH) domain protein, at the ventral side of HSN . We testy of HSN . The unimig-10 phenotypes are similar to that observed in egl-20 and mig-1 mutants, i.e. UNC-40::GFP is often asymmetrically localized to the anterior and posterior domains ;egl-20(−) mutants the precocious axon extension phenotype is suppressed, suggesting that UNC-40 mediates the formation of the precocious axons.In comparison to wild-type animals, the probability of UNC-40 localization at the ventral side decreases in the mutants, whereas the probability of localization at the anterior and posterior sides increases. Whereas there is little fluctuation in the direction of UNC-40 localization in wild-type animals, and much fluctuation in the UNC-40 (A1056V) and  evident . HoweverL3 stage . We examansition . In addi2 stages . In unc-Do the movements of axon guidance follow patterns that can be described quantitatively by statistical physics? The UNC-40 receptor binds the extracellular guidance cue UNC-6 and is required for axon outgrowth. In response to UNC-6, UNC-40 becomes asymmetrically localized and we show that there is a probability of UNC-40 being present at each of the different sides of the neuron during initial outgrowth. This provides experimental evidence for random fluctuations of UNC-40 activity within a neuron. We hypothesize the fluctuations of UNC-40 activity cause fluctuating sites of axon outgrowth and thus a succession of imbalanced outwards force across the surface of the neuron. The relationship between these stochastic fluctuations and the macroscopic properties of axon guidance can be described by non-equilibrium statistical physics. We propose that the observed behaviors of UNC-6 guidance approximate a random walk model. We experimentally tested this hypothesis using mutations that alter the fluctuations and we observe that the pattern of UNC-40 localization and axon outgrowth is consistent with this model.C. elegans is that axons that express only the UNC-40 receptor are guided towards the ventral source of extracellular UNC-6, whereas those expressing the UNC-5 receptor are guided away. Thus the molecules and signaling pathways encoded by the neuron determine whether the axon has an attractive or repulsive response to UNC-6. Although this model explains most experimental results, there are some that are not consistent with this model. For example, the SDQR axon is directed away from the ventral source of UNC-6 in wild-type animals and is directed ventrally in unc-6 null mutants, however the axon can be directed towards an ectopic dorsal source of UNC-6 in unc-6 null mutants ; unc-5(e53) mutants, suggesting that in unc-53(n152) mutants UNC-5 receptor activity is required to induce in HSN the signal that causes asymmetric UNC-40 localization. Although both unc-5 and unc-6 affect the guidance of cells and axons other than HSN, UNC-40 is asymmetrically localized in the unc-53(n152);unc-5(e53);unc-6(ev400) and the unc-53(n152);unc-6(ev400) mutants, indicating that the proper guidance of neighboring cells and axons is not required for UNC-40 asymmetrical localization in HSN. The simplest model is that UNC-5 functions cell-autonomously in HSN for the asymmetric localization of UNC-40 in unc-53(n152) mutants.We find that UNC-5 is required for the guidance of the HSN axon towards the UNC-6 source in the 0 in HSN . There i0 in HSN . The cyt0 in HSN . We findi.e., UNC-5 regulates the induction of UNC-40 asymmetric localization in HSN. Our observation that unc-5 function can affect the guidance of neurons that primarily require unc-40 function for guidance is a similar to earlier observations that the loss of unc-40 function also affects guidance in neurons that primarily require unc-5 function  can induce the asymmetrical localization of UNC-40 in HSN even in the absence of UNC-6 and that the direction of the asymmetric localization in this case is indeterminate . This raunc-53;unc-6 double mutants (unc-53(n152);unc-6(ev400) mutants there is a probability of 0.22 for anterior localization and a probability of 0.11 for posterior localization . However, the displacement of the particle is actually non-linear over time because of random motion. Einstein predicted that the mean displacement of the particle increases with the square root of time  mutants there is a probability of 0.59 for anterior localization and a probability of 0.37 for posterior localization  tends to increase only linearly with time in the mutants, whereas the msd tends to increase quadratically with time in wild-type animals, where random fluctuations are reduced. In other words, because of the stochastic fluctuations in direction, the axon takes longer to grow out in the mutants. In wild-type animals, the random fluctuations are reduced and the force is directed in a straight line, where distance becomes proportional to the time interval . Finally, while UNC-6-ligated UNC-40 induces asymmetric UNC-40 localization, Wnt/PCP signaling is inhibitory. A lack of Wnt/PCP signaling early in the guidance process increases the probability that the outgrowth process will begin too soon.Our evidence indicates that the response to the UNC-6 guidance cue is stochastic. A process is induced that causes the localization of the UNC-40 receptor and axon outgrowth activity in a random direction. This stochastic fluctuation can be repressed by the effects of the extracellular UNC-6 gradient and by the function of several genes. Together these factors create a strong bias for UNC-40 localization and axon outgrowth activity in only one specific direction. However, when this bias is altered, UNC-40 activity stochastically fluctuates and there is a probability for UNC-40 outgrowth activity at each side of the neuron. The movement of the axon than approximates a random walk.in principle HSN axon guidance must be deterministic. After all, if the effects of UNC-40 outgrowth activity were known at each discrete time during outgrowth, the direction of axon guidance could be precisely determined. However, using the probabilistic approach taken here, we conclude that the random fluctuation of intracellular UNC-40 outgrowth activity determines the direction of HSN axon guidance. We observe in the mutants that at any discrete time UNC-40 and axon outgrowth can be directed anteriorly or posteriorly, although over time the axon is guided ventrally. The movement of any object  that is described as a random walk has this property. That is, whatever causes the object to move in a specific direction at one particular time doesn't determine the overall trajectory of the object over time. This raises an unintuitive and controversial conclusion that the molecular mechanisms that regulate the direction of axon outgrowth don't determine the direction of axon guidance. In this model, guidance molecules regulate different aspects of the stochastic process. Some, such as UNC-5 and UNC-53, regulate the induction of the stochastic process, whereas others, such as EGL-20 and MIG-10, create the bias that provides specific directionality.In a deterministic model, the intracellular localization of UNC-40 towards the source of UNC-6 determines the direction of HSN axon guidance. It could be argued that It is increasingly recognized that random fluctuations are fundamentally important to many natural phenomena. They influence the behavior of complex systems, including cells, organisms, ecology, and the atmosphere. The results presented here suggest that the stochastic fluctuation of UNC-40 outgrowth activity underlies the ability of the neuron to determine the direction of guidance in response to UNC-6. This hypothesis implies that axon guidance is a biological process that makes and exploits random fluctuations to create function.Left: A schematic of a random walk of N steps that ends at distance X.Right: Illustration of a hypothetical random walk caused by the stochastic fluctuation of intracellular UNC-40 receptor localization. Sites where axon outgrowth is directed (red dots) randomly fluctuate over time causing a succession of outgrowths (shades of gray).N steps. Here is a simple model for a walk in one dimension to illustrate formulization of movement. The same basic model can be applied to walks in two or three dimensions, and can be extended with more sophisticated methods of including different probabilities and unequal steps.A random walk model can predict the average distance traveled in a walk of t deciding to take one step of length δ to the right or left at random. With each step the walkers location changes by Δx = ± δ. After N steps the walker's location will be:Nδ and −Nδ. Therefore, the average distance over a large number of different walks, all with N steps, will be zero because the probability of a right or left direction is equal. Since X2 is always positive, the square root of that average can be used to find the average distance from the origin of the walk after N steps:Envision a ‘‘walker’’ at each time period ΔThe difference in the characteristic distance covered by an object undergoing a random walk versus one with straight-line motion can be significant. For example after a million steps of one millimeter in length:


Until now, the precise control of the spatiotemporal parameters inherent to regulating RNA localization has not been experimentally possible. Here, we demonstrate the development and use of a chemically–inducible RNA–protein interaction to regulate subcellular RNA localization. Our system is composed primarily of two parts: (i) the Tet Repressor protein (TetR) genetically fused to proteins natively involved in localizing endogenous transcripts; and (ii) a target transcript containing genetically encoded TetR–binding RNA aptamers. TetR–fusion protein binding to the target RNA and subsequent localization of the latter are directly regulated by doxycycline. Using this platform, we demonstrate that enhanced and controlled subcellular localization of engineered transcripts are achievable. We also analyze rules for forward engineering this RNA localization system in an effort to facilitate its straightforward application to studying RNA localization more generally.Evidence is accumulating in support of the functional importance of subcellular RNA localization in diverse biological contexts. In different cell types, distinct RNA localization patterns are frequently observed, and the available data indicate that this is achieved through a series of highly coordinated events. Classically,  Saccharomyces cerevisiae, defining body axis polarity in Drosophila and C. elegans, fibroblast and neuronal growth cone migration, synaptic plasticity, and storage of maternally–derived transcripts [for some pertinent reviews, see: cis–elements within localized transcripts that are recognized by cognate RNA-binding proteins (RBPs)  . Throughcis–RNA elements with the cognate RBPs; Step II–assembly, transport and targeting of the RNP complex to the appropriate location; and Step III–translational de–repression at the site of RNA localization. Modulation of the RNA-protein interaction during Steps I and III is understood in some detail, and may be achieved, for example, via transcription–mediated changes In the relatively few instances where the functional importance of subcellular RNA localization is validated, it is clear this is a dynamic and highly regulated process. Regulation can occur at three main points: Step I–the interaction of cis–elements introduced into target transcripts that are localized exclusively by native mechanisms cis–elements based on MS2 and boxB RNA binding sites have been encoded into target transcripts and co–expressed with protein fusions between the MS2 coat or λN proteins and endogenous localization effector proteins Dissecting the functional significance of subcellular transcript localization presents a major but important challenge. In much the same way that systems for inducible and dynamic regulation of gene expression have been invaluable in establishing the roles proteins play in various biological processes, we envision that the ability to modulate subcellular RNA localization will play an indispensable role in establishing its functional significance more globally. Simultaneously, as we gain a better understanding of how RNA localization shapes cellular function, opportunities to use this knowledge in design–oriented applications in areas such as synthetic biology and neurobiology will emerge. Towards this long–term objective, previous efforts have used endogenously recognized S. cerevisiaeHere, we present a general strategy that overcomes the inherent limitations above. Guided by insights from several natural localization mechanisms Saccharomyces cerevisiae was used as a model context for this work, as many of the molecular details underlying its natural RNA localization machinery have been elucidated. Several transcripts, such as the ASH1 mRNA, are asymmetrically trafficked to the growing bud in S. cerevisiae [reviewed in 5–1.2, was genetically encoded within the 5′ or 3′ UTR of this transcript as either a single aptamer (5′ and 3′ UTR) or in tandem arrays (3′UTR only). Two synthetic RBPs were designed and consisted of a TetR–EGFP (TG) core fused either to the N–terminus of full–length She2p to give TG–She2 or the C–terminus of full–length She3p to give She3–TG  represses the HO promoter in both, leading to overall growth suppression on – ade media she2Δ or she3Δ yeast strains, respectively, we expect to observe growth on – ade media only if the She2p and She3p components remain functional. As shown in Next, we tested the functionality of She2p and She3p within TG–She2 and She3–TG using a plate–based growth assay in which effective asymmetric distribution of Ash1p is made dependent on functional She2p and She3p within TG–She2 and She3–TG. Asymmetric Ash1p accumulation within the daughter cell  allows the maternal 5–1.2–vYFPΔ transcript containing a single aptamer within its 5′UTR. Our previous work established that when presented in different 5′UTR sequence contexts, this aptamer interacts with TetR to robustly regulate translation 5′UTR aptamer, translational repression synergistic with efficient localization could be simultaneously achieved. To evaluate attaining small molecule–regulated control over subcellular localization, she2Δ or she3Δ yeast were co-transformed with TG–She2 or She3–TG, respectively, and the 5–1.2–vYFPΔ reporter transcript. Initially, we encoded the TetR–binding aptamer within the 5′UTR sequence context used in the translation repression assays  with Cy5–labeled probes, respectively. To minimize experimenter–introduced bias in our analyses of subcellular localization, we used computer–aided methods  Region 1, which is the area encompassed by Mask 1, and thus defines the region within which enhanced target transcript accumulation occurs; and Region 2, which is the area encompassed by Mask 2, but excludes Region 1. We defined a Localization Index as the ratio of the mean Cy5 fluorescence signal density of Region 1 to that of Region 2. Effectively, this metric reflects the ratio of the average co–localized to non–localized reporter transcript signal.For a more quantitative assessment of the RNA localization capabilities of our system and to facilitate more standardized comparisons under varying experimental conditions, we devised a straightforward analytical procedure to determine TetR–fusion protein and target RNA co–localization. After capturing microscopy images, a computational algorithm was used to define two masks, one defining the TG–She2/She3–TG foci (Mask 1) and another the entire cell body (Mask 2) . Two reg5–1.2–vYFPΔ transcript and either TG–She2 or She3–TG, in either the presence or absence of doxycycline  or She3-TG (p = 0.01) protein was expressed, without negatively impacting doxycycline–induced reversibility of localization  is not observed. This may be due to residual interaction between the TetR aptamer and TG–She2/She3–TG even in the presence of doxycycline that causes a slight enhancement in transcript signal co–localizing with the TetR fusion proteins, or bias introduced by the analysis method. To explore the cause of the apparent incomplete induction, we performed localization analysis with strains co–expressing TG–She2/She3–TG and the .2_vYFPΔ . These d5′UTR. However, many naturally occurring instances of RNA localization are mediated by cis–elements located with the 3′UTR of the target transcript 3′UTR–encoded TetR aptamers. Along with defining a functional localization system having experimental utility, we examined failed designs to better understand the link between preserved protein–RNA interaction biochemistry and observable RNA localization. We believe this is useful for two main reasons. First, if poor transcript localization efficiency were due to sub–optimal aptamer display preventing high affinity interaction with TG–She2 and She3–TG, this would allow us to emphasize pursuing design–oriented and/or selection–based strategies to define an aptamer display context compatible with high affinity interaction with the TetR fusion proteins. Second, our previous efforts regulating translation using TetR–aptamer interactions suggested that an intact protein–RNA interaction is necessary but not sufficient for functionality As shown above, effective and inducible RNA localization is attainable with a single aptamer positioned within a target transcript’s 5–1.2 aptamer within the 3′UTR of our vYFPΔ reporter (vYFPΔ_5–1.2), and co–expressing this transcript with either TG–She2 or She3–TG and measuring vYFPΔ_5–1.2 localization as before  the same as was successfully used previously with MS2–binding aptamers in the 3′UTR5–1.2 localization was observed using either TG–She2 or She3–TG  or 3′UTR (Kd = 0.8 nM) contexts 5 and vYFPΔ_(5–1.2)10 reporter constructs containing five and ten aptamer sequences within the 3′UTR, respectively. No enhanced localization was observed using the vYFPΔ_(5–1.2)5 transcript with either TG–She2 or She3–TG (5–1.2)10 transcript with both She2–TG and She3–TG was achieved (5–1.2)10 transcript closely matched that for the 5–1.2_vYFPΔ (single aptamer in the 5′UTR) transcript  of individual RBPs and putative components of the RNA localization machinery to establishing the transcript–specific subcellular mRNA distribution patterns observed naturally. Indeed, it is estimated that between 2–8% of the genome of model eukaryotes encode RBPs, and these may act combinatorially and/or hierarchically to control various RNA fates, including localization In vitro transcription and equilibrium binding experiments were performed using a cytometric bead binding assay 3′ ends of the reporter transcript was performed using 3′–RACE Firefly luciferase levels were determined using a standard luciferase assay as described previously The K5547 (to test She2) or K4822 (to test She3) yeast strains harboring the indicated vector(s) was grown to saturation at 30°C in Synthetic Defined Media #1 (SD1)  +20 g/L glucose. Cultures were diluted 10,000-fold into minimal media and grown for 16 hours. Yeast cultures were diluted serially ten-fold, and 5 µL of each dilution was spotted onto agar plates as indicated and grown at 30°C for three days before visualization. Tryptophan dropout plates contained SD1, 20 g/L agar and 20 g/L glucose. Plates lacking tryptophan and adenine contained SD1 without adenine, 20 g/L agar and 20 g/L glucose.g for 2 minutes. Cells were washed once in Spheroplast Buffer , and incubated at 37°C for 15 minutes in 100 µL Spheroplast Buffer containing 2 U zymolyase (Zymo Research) and protease inhibitors (Sigma). Laemmli sample buffer was added to a final concentration of 1× and samples were incubated for 10 minutes at 95°C. Samples were centrifuged at 12,000×g for 1 minute. The supernatants were loaded and separated by SDS–PAGE and transferred to a PVDF membrane. TetR was detected using an anti–TetR monoclonal antibody .Cells expressing the indicated proteins were grown to mid-log phase. Lysates were prepared by pelleting the yeast in a microcentrifuge at 5,000×g and washed three times in cold Buffer B (BB) . Cells were resuspended in 1 mL BB containing 2U Zymolyase (Zymo Research) and 2 mM vanadyl ribonucleoside complex, and incubated for 15 minutes at 30°C. Cells were centrifuged at 850×g, washed twice in cold BB and incubated in 70% ethanol at room temperature for one hour. Upon harvesting by centrifugation at 400×g, cells were resuspended in 1 mL Washing Buffer (WB) , and incubated at room temperature for 3 minutes. Cells were pelleted by centrifugation at 400×g and resuspended in 100 µL Hybridization Buffer  containing 250 nM FISH hybridization probes, and incubated overnight. FISH probes consisted of a pool of 20–mer Cy5-labeled oligodeoxynucleotides specific for unique sequences within the target transcript (Biosearch). Cells were washed in 1 mL WB, collected by centrifugation at 400×g and resuspended in 1 mL WB and incubated at 30°C for thirty minutes. Cells were collected as above, resuspended in 100 µL of WB containing 1x Whole Cell Stain Blue (Thermo), and incubated at room temperature for thirty minutes. Cells were washed twice with 1 mL WB, resuspended in 2x SSC solution , and spotted on glass slides for imaging.The W303–1A yeast strains transformed with the indicated plasmids were grown to saturation at 30°C in Synthetic Defined Media #2 (SD2)  + 20 g/L glucose. Cultures were diluted 150-fold into 10 mL of SD2+20 g/L galactose to induce TetR-fusion expression, and grown for 16 hours at 30°C to mid-log phase. Alpha-factor mating pheromone (Zymo Research) was added to a final concentration of 10 µg/mL, and cultures were incubated at 30°C for four hours. Cells were fixed using formaldehyde  and incubated for 40 minutes at room temperature. Cells were pelleted by centrifugation at 3,000×Images of cells were captured using a Zeiss AxioObserver microscope with filters (Chroma) optimized for DAPI (Whole Cell Stain), GFP  and Cy5 (FISH probes) excitation and detection. Data acquisition was performed with Metamorph software (Molecular Devices). Automated image analysis was performed using the Cell Profiler software


The relationship between RNA expression and cell function can often be difficult to decipher due to the presence of both temporal and sub-cellular processing of RNA. These intricacies of RNA regulation can often be overlooked when only acquiring global measurements of RNA expression. This has led to development of several tools that allow for the real-time imaging of individual engineered RNA transcripts in living cells. Here, we describe a new technique that utilizes an oligonucleotide-based probe, ratiometric bimolecular beacon (RBMB), to image RNA transcripts that were engineered to contain 96-tandem repeats of the RBMB target sequence in the 3′-untranslated region. Binding of RBMBs to the target RNA resulted in discrete bright fluorescent spots, representing individual transcripts, that could be imaged in real-time. Since RBMBs are a synthetic probe, the use of photostable, bright, and red-shifted fluorophores led to a high signal-to-background. RNA motion was readily characterized by both mean squared displacement and moment scaling spectrum analyses. These analyses revealed clear examples of directed, Brownian, and subdiffusive movements. In addition to having direct effects on global RNA levels, these factors can also influence RNA trafficking and distribution, allowing for subcellular regulation. Due to the complex and diverse nature of RNA regulation, it is apparent that there is a need to acquire both a spatial and temporal profile of RNA expression at the single cell level to unravel the relationship between RNA processing and cell function. This has led to the development of several approaches that are capable of imaging individual RNA transcripts in single living cells, in real-time ASH1 mRNA particles in live yeast DrosophilaPerhaps, the most widely adopted approach to detect individual RNA transcripts in living cells utilizes a green fluorescent protein (GFP) fused to the coat protein of bacterial phage MS2 (GFP-MS2) A significant limitation of the GFP-MS2 system is the high background signal that stems from the GFP-MS2 fusion proteins that are not bound to target RNA. This makes this system sensitive to the relative and total level of target RNA expression and GFP-MS2 expression. One approach that has been taken to minimize this background signal involves redirecting the unbound GFP-MS2 to a subcellular compartment that is removed from the site of interest Recently, several groups have also sought to improve upon the GFP-MS2 system by adopting alternative combinations of RNA binding proteins and their respective RNA targets  Another fluorescent probe that has been widely adopted for the imaging of RNA in living cells is the molecular beacon (MB) Recently, we developed a new probe for imaging RNA in living cells, ratiometric bimolecular beacons RBMBs; , to overGFP RNA with 96-tandem repeats of the RBMB target sequence within the 3′-untranslated region. Upon hybridization, the RNA transcripts were visualized as discrete, bright fluorescent spots by wide-field fluorescence microscopy with high signal-to-background  and at the 3′-end with an Iowa Black RQ-Sp quencher . The sequence of the second oligonucleotide is: 5′-AF750-mGmAmG mCmUmG mCmAmC mGmCmU mGmCmC mGmUmC-IBRQ-3′. To form RBMBs, the two oligonucleotides are hybridized at a molar ratio of 1∶1.5 RBMB1∶RBMB2 in phosphate buffer  at room temperature overnight. A slightly higher concentration of RBMB2 is utilized to ensure complete hybridization of RBMB1. The presence of unbound RBMB1 in cells can create an unwanted background signal. Excess RBMB2 is also easier to distinguish from hybridized RBMBs via size exclusion chromatography, than RBMB1. The hybridized RBMB is purified using a Superdex 75 prep grade column  and concentrated using a Microcon YM-10 centrifugal device . The final concentration of the RBMBs was determined using a Cary 100 spectrophotometer .RBMBs are composed of two 2′-O-methyl RNA oligonucleotides that are hybridized together. One of the oligonucleotides is labeled with a CF640R  reporter dye at the 5′-end and has the sequence: 5′-CF640R-2. HT1080-GFP-96mer cells, which stably express GFP RNA with 96-tandem repeats of the RBMB target site with the 3′-UTR were generated by infecting HT1080 cells with pLenti-dsGFP-96mer, as previously described Human fibrosarcoma cells, HT1080, were purchased from ATCC , and were cultured in MEM media supplemented with 1% Pen/Strep and 10% fetal bovine serum (FBS). The cells were incubated at 37°C with 5% COThe introduction of RBMBs into cells was achieved by microporation with a Neon transfection system  as per manufacturer's protocol. Briefly, a cell pellet containing 300,000 cells was resuspended in 11 µL Resuspension Buffer, supplied with the kit, and mixed with 1 µL of 9.6 µM RBMBs (34). The final concentration of RBMBs was 0.8 µM. After microporation, cells were washed 3 times in culture medium (without FBS and Pen/Strep) and seeded on poly-d-lysine  coated 8-well chambered coverglass system  for ∼1 hr. For studies utilizing the spinning disk confocal system for fluorescence imaging (described below), Hoechst 33342 (Invitrogen) was added at a final concentration of 0.01 µg/µL.Wide-field fluorescence microscopy was performed using an Olympus IX81 motorized inverted fluorescence microscope equipped with a back-illuminated EMCCD camera , a SOLA Light Engine  and a CoolLED pE-100 . A plan Apo 100× (NA 1.45) oil objective was used. The Stream Acquisition function in Metamorph software  was used to acquire 150 images in the CF640R channel. Images were acquired using the filter set ET620/60×, ET700/75 m, T660lpxr for CF640R. On occasion, the filter set HQ710/75, HQ810/90, Q750LP was also used to image Alexa 750, to confirm RBMB delivery. Before imaging, cells were equilibrated to 37°C on the microscope stage using a live-cell stage top incubation system . Imaging was typically performed 1 to 2 hrs after cells were seeded in the wells of the chambered coverglass system.Local background subtraction was performed on the images using the Rolling Ball Background Subtraction plugin in ImageJ 2r is mean squared displacement, n is time lag, N is length of trajectory, and p is position.D is the diffusion coefficient, t is the time lag, and α is the scaling exponent. The scaling exponent α can be used to define the motion: 0 = static, 1 = diffusive, 2 = directed.v) relative to different time lags is analyzed .MSS) can be used to define motion as confined, diffusive, or directed .Trajectories were analyzed using custom MATLAB (Mathworks) code. Mean squared displacement (MSD) analysis of trajectories was performed  using alFirst individual trajectories were analyzed using MSD analysis and separated into three groups  based on their individual α values. MSD analysis was then performed by averaging across all tracks within each group to increase the number of observations at longer time lags and the reliability of the measurement. MSS analysis was performed in the same way on these three groups of tracks.To measure the speed and displacement of the directed set of trajectories, the position was smoothed over 5 frames (or 1.4 s). The frame-to-frame instantaneous speed was measured for the entire trajectory and the maximum speed per trajectory measured. In addition the net displacement from the start to the end of the track was measured.GFP RNA construct with 96-tandem repeats of the RBMB binding site in the 3′-UTR. Cells were imaged approximately 1 to 2 hrs following microporation, to ensure that the cells had time to adhere and spread onto poly-d-lysine coated coverglass. All imaging studies were performed using a live-cell stage-top incubation system operating at 37°C and 5% CO2 to ensure physiologic conditions. Individual RNA transcripts within single cells appeared as discrete, bright fluorescent spots via wide-field fluorescence microscopy and RNA movements were readily captured by performing streaming acquisition Click here for additional data file.Movie S2Representative movie of RNA transcripts moving in living cells. Individual RNA transcripts appear as discrete fluorescence spots. A transcript undergoing directed transport is indicated by a white arrow. Scale bar: 10 µm.(MOV)Click here for additional data file.Movie S3Representative movie of RNA transcripts moving in living cells. Individual RNA transcripts appear as discrete fluorescence spots. A transcript undergoing directed transport is indicated by a white arrow. Scale bar: 10 µm.(MOV)Click here for additional data file.Movie S4Montage of RNA motions that have been classified as confined, diffusive or directed based on mean squared displacement analysis (MSD) analysis. Scale bar: 5 µm.(MOV)Click here for additional data file.Movie S5Movie of an RNA transcript following a highly curved path. The RNA track is overlaid over the cell image. Scale bar: 10 µm.(MOV)Click here for additional data file.Movie S6Movie of an RNA transcript going from directed to diffusion motion. The RNA track is overlaid over the cell image. Scale bar: 10 µm.(MOV)Click here for additional data file.