This study was partly supported by the Basic Science and Platform Technology Program for Innovative Biological Medicine, no. 17am0301014, from the Japan Agency for Medical Research and Development (AMED), Research Grant from MEXT to the RIKEN Center for Life Science Technologies and a Research Grant from MEXT to the RIKEN IMS. We thank members of the PC lab and of the SINEUP network (SISSA, University of Eastern Piedmont and RIKEN) for thought-provoking discussions. We thank Dr. Matthew Valentine for proofreading.

1. Design of BDs of SINEUP Constructs for Target mRNAs
<ol>
	<li>Check transcription starting site (TSS) and translation starting site of target mRNAs in the cells of interest. Acquire TSS data from both the ENCODE and FANTOM projects (cap analysis of gene expression, CAGE) (ZENBU: http://fantom.gsc.riken.jp/zenbu/).</li>
	<li>Open the browser, search genes of interest and check TSS by CAGE peaks.</li>
	<li>Consult the example analysis of cell and tissue specific TSS of Parkinson disease protein 7 (PARK7) mRNA shown in Figure 2.</li>
	<li>Design BD sequences of several different lengths corresponding to 40 bases upstream and 32 bases downstream of the first methionine (AUG), 72 nt in total.</li>
	<li>Custom order the designed BDs in SINEUP expression vector (see Table of Materials). 
	NOTE: Check the sequence specificity by basic local alignment search tool (BLAST) to avoid off-target effects26.</li>
</ol>
2. Cell Culture and SINEUP Transfection
<ol>
	<li>Seed cells of interest in a 6 well-plate or 24 well-plate for 24 h before transfection of SINEUPs. In the case of human embryonic kidney cell line (HEK293T/17) (see Table of Materials), seed 0.5 x 106 cells per well of a 6 well-plate or 1.5 x 105 cells per well of a poly-D-lysine coated 24 well-plate (see Table of Materials). It becomes 70% confluent after 24 h.</li>
	<li>After 24 h, change the medium to 1.5 mL of fresh medium for a 6 well-plate or 0.4 mL of fresh medium for a 24 well-plate. In case of SINEUP-GFP, transfect 0.6 &#181;g of pEGFP-C2 (see Table of Materials) and 3.4 &#181;g of SINEUP-GFP in one well of a 6 well-plate or 130 ng of pEGFP-C2 and 670 ng of SINEUP-GFP in one well of a 24 well-plate with transfection reagent (10 &#181;L in 6 well-plate and 3 &#181;L in 24 well-plate) by following the manufacturer&#8217;s instructions (see Table of Materials), and incubate at 37 &#176;C in a 5% CO2 incubator for 24 h.</li>
	<li>Wash cells with 2 mL of phosphate buffer saline (PBS) (37 mM NaCl, 8 mM Na2HPO4, 2.6 mM KCl and 1.5 mM KH2PO4) in each well of a 6 well-plate or 0.5 mL of PBS in each well of a 24 well-plate. Only for poly-D-lysine coated 24 well-plate, add 25 &#181;L of 0.05% weight per volume Trypsin, incubate in a 5% CO2 incubator for 5 min and add 275 &#181;L of cell medium per well. In case of 6 well-plate, add 2 mL of PBS in each well. Pipet up and down to harvest 3/4 of cells (1.5 mL for a 6 well-plate or 225 &#181;L for a 24 well-plate) from 1 well for protein extraction (go to protocol 3 for protein extraction) and 1/4 of cells (0.5 mL for a 6 well-plate or 75 &#181;L for a 24 well-plate) for RNA extraction and&#160; centrifuge at 6,000 x g for 5 min at 4 &#176;C (go to step 5 for RNA extraction). 
	NOTE:&#160;Analyze the effect of SINEUP-GFP in a poly-D-lysine coated 24 well-plate by imaging. Go to step 7 (imaging analysis).</li>
</ol>
3. Protein Extraction
<ol>
	<li>Carefully aspirate 1.5 mL of PBS and add 140 &#181;L of lysis solution (20 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1 mM Na2EDTA, 1 mM EGTA, 1% (w/v) Triton, 2.5 mM sodium pyrophosphate, 1 mM &#946;-glycerophosphate, 1 mM Na3VO4, 1 &#956;g/mL leupeptin, and 0.005% (w/v) phenylmethylsulfonyl fluoride (PMSF)) (see Table of Materials) for a 6 well-plate or 60 &#181;L for a 24 well-plate to the cell pellets.</li>
	<li>Mix by pipetting and then mix thoroughly by rotating at slow speed for 1 h at 4 &#176;C. Collect supernatant by centrifugation at 14,000 x g for 10 min at 4 &#176;C.</li>
	<li>Check protein concentration by colorimetric assay (see Table of Materials). Prepare all the reactions at room temperature.
	<ol>
		<li>Prepare 5-6 times dilution of bovine serum albumin (BSA) protein standard in ultrapure water with concentrations ranging from 0.2-1.5 mg/mL protein. Prepare fresh standards each time.</li>
		<li>Prepare working reagent A&#697; by mixing 1 mL of reagent A (alkaline copper tartrate solution) with 20 &#181;L of reagent S (surfactant solution).</li>
		<li>Load 5 &#181;L of water (negative control), BSA standard (protein standard and positive control) or protein sample in each well of a 96-well-plate.</li>
		<li>Add 25 &#181;L of reagent A&#697; in each well. Carefully add 200 &#181;L of reagent B (Folin reagent) per well avoiding any bubble formation. Cover the plate with aluminum foil and wait for 5-10 min.</li>
		<li>Measure the protein absorbance at 750 nm with a spectrophotometer. The absorbance is stable for at least 1 h.</li>
		<li>Prepare standard curve by plotting BSA standard protein concentrations (mg/mL) on the x-axis and their respective absorbance on the y-axis. Calculate sample protein concentration by applying standard curve equation. 
		NOTE: Pause the protocol at this step if needed or go to step 4. For long-term storage, snap freeze protein samples in liquid nitrogen and store at -80 &#176;C.</li>
	</ol>
	</li>
</ol>
4. Protein Separation by SDS-PAGE and Detection of Target Proteins with Antibodies (Western-blot Analysis)
<ol>
	<li>Add one volume of 2x loading dye (0.1 M Tris-HCl (pH 6.8), 4% SDS, 20% glycerol, 1.42% 2-mercaptethanol and 0.2% bromophenol blue) to each volume of protein sample from step 3.3. Heat at 90 &#176;C for 5 min and immediately cool on ice for 1 min.</li>
	<li>Load 10-20 &#181;g of protein samples to 10% SDS poly-acrylamide gel and separate at 100-150 V) (see Table of Materials).</li>
	<li>Transfer protein from gel to 0.45-&#181;m nitrocellulose membrane (see Table of Materials) by semi-dry transfer instrument with transfer buffer (25 mM Tris, 192 mM glycine and 20% methanol) at 25 V for 30 min.</li>
	<li>Add blocking solution (5% non-fat dry milk in 1x TBST buffer (137 mM NaCl, 20 mM Tris-HCl (pH 7.6), 0.1% Tween-20)) (see Table of Materials) to the container until the membrane is completely soaked and incubate it at room temperature for 30 min.</li>
	<li>In the case of SINEUP-GFP, hybridize the protein with anti-GFP antibody (diluted 1:2000 in blocking solution) (see Table of Materials) by incubating the membrane for 30 min with shaking at room temperature. As an internal control protein, detect &#946;-actin protein by hybridizing with Anti-&#946;-Actin antibody (diluted 1:2000 in blocking solution) (see Table of Materials) for 30 min with shaking at room temperature.</li>
	<li>Add 1x TBST buffer to the container until the membrane is completely soaked and wash for 5 min at room temperature. Repeat the wash step two more times (a total of three washes).</li>
	<li>Hybridize GFP protein to diluted (1:1000 in blocking solution) anti-rabbit antibody conjugated with horseradish peroxidase (HRP), and hybridize &#946;-actin protein to diluted (1:1000 in blocking solution) anti-mouse antibody conjugated with HRP on the membrane for 30 min with shaking at room temperature.</li>
	<li>Wash membrane with 1x TBST buffer for 5 min at room temperature. Repeat the wash step two more times (a total of three washes).</li>
	<li>Mix equal volume of HRP-enhanced chemiluminescence (ECL) detection reagent 1 and 2 (see Table of Materials). Transfer the membrane to 2 mL ECL reagent mix, cover the box with aluminum foil and let it incubate for 1-2 min at room temperature. Carefully remove the membrane from ECL reagent mix and expose using a luminescence imaging instrument.</li>
</ol>
5. RNA Extraction and DNase Treatment
<ol>
	<li>Extract total RNA following the standard protocol for RNA extraction from cells grown in a monolayer27 or alternatively use a commercially available RNA extraction kit (see Table of Materials). To state in brief, add any monophasic lysis reagent (MLR) of guanidine isothiocyanate and phenol to the harvested cells in step 2.3 (1 mL MLR per ~5 million cells)27. 
	NOTE: Change gloves frequently. Use RNase-free reagents, and diethylpyrocarbonate (DEPC)-treated plastic ware and glassware to prevent RNA degradation. Pause the protocol at this step if needed. Store extracted RNA at -80 &#176;C.</li>
	<li>Add 0.1 volume of 10x DNase buffer and 2 U of DNase to the purified RNA from step 5.1 (see Table of Materials).</li>
	<li>Set the reaction volume to 50 &#181;L with nuclease-free water and mix gently. Incubate at 37 &#176;C for 30 min.</li>
	<li>Add 0.1 volume of re-suspended DNase inactivation reagent and mix well (see Table of Materials). Incubate for 5 min at room temperature with gentle shaking.</li>
	<li>Centrifuge at 10,000 x g for 90 s. Transfer the supernatant (DNA-free RNA) to a fresh RNase-free 1.5 mL tube. Be careful not to touch the pellet because this can cause carry-over of DNase which is troublesome for downstream steps.</li>
	<li>Quantitate RNA by measuring A260 and A260/A280 ratio (for pure RNA, the range is 1.8-2.0) in a UV spectrophotometer.</li>
</ol>
6. First Strand cDNA Synthesis and qRT-PCR Analysis
<ol>
	<li>Perform first strand cDNA synthesis following a standard cDNA synthesis protocol as below (see Table of Materials).
	<ol>
		<li>Mix 0.75 &#181;M oligo dT primer, 4.3 &#181;M random primer, dNTPs (10 mM each) with 200-500 ng total RNA (from steps 5-8) in 10 &#181;L of total reaction volume. Incubate at 65 &#176;C for 5 min and then immediately put on ice.</li>
		<li>Mix 1x reverse transcriptase buffer, 1 U of RNase inhibitor, 10 U of reverse transcriptase, and add to 10 &#181;L RNA-primer mix from 6.1.1.</li>
		<li>Set the total reaction volume to 20 &#181;L with nuclease-free water if required. Mix gently and incubate the reaction mix at 30 &#176;C for 10 min, then at 42 &#176;C for 60 min, and finally at 95 &#176;C for 5 min to inactivate the enzyme. Cool the tubes on ice. 
		NOTE: Thaw RNA samples and all the reagents on ice and prepare the reaction mix on ice. If target RNAs are only polyA RNAs, use oligo dT primer only (2.5 &#181;M). Pause the protocol if needed. Store synthesized cDNA at -20 &#176;C.</li>
	</ol>
	</li>
	<li>Perform qRT-PCR in technical triplicates (n=3, C&#1090; standard deviation &#62; 0.2) and within biological replicates (n &#8805; 3) using 1 &#181;L of 10 ng cDNA, 0.4 &#181;L of reverse primer (10 &#181;M), 0.4 &#181;L of forward primer (10 &#181;M), 10 &#181;L of mixture solution of DNA polymerase, 0.4 &#181;L of double-strand DNA staining dye, 10 &#181;L of nuclease-free water (reaction volume was 20 &#181;L) to detect PCR products using following conditions; hold stage (1 cycle) for 30 s at 95 &#176;C, cycling stage (40 cycles) for 5 s at 95 &#176;C and for 30 s at 60 &#176;C, melt curve stage. Primer examples are for Human Gapdh_Fw: TCTCTGCTCCTCCTGTTC, Human Gapdh_Rv: GCCCAATACGACCAAATCC, EGFP_Fw: GCCCGACAACCACTACCTGAG, EGFP_Rv: CGGCGGTCACGAACTCCAG, SINEUP-GFP_Fw: CTGGTGTGTATTATCTCTTATG and SINEUP-GFP_Rv: CTCCCGAGTCTCTGTAGC. See Table of Materials. Analyze quantitative RNA expression with 2-&#8710;&#8710;Ct &#177; SD method28.</li>
</ol>
7. Imaging Analysis of SINEUPs by Semi-automated Detection Method
<ol>
	<li>Wash cells with 0.5 mL of PBS for one well of a 24 well-plate.</li>
	<li>Add 2.0 &#956;g of Hoechst 33342 (see Table of Materials) (dissolving in 500 &#956;L of PBS) to each well of the 24-well-plate and incubate cells at 37 &#176;C for 20 min to stain the nucleus.</li>
	<li>Measure Hoechst stained cells to count the total number of cells at a blue emission maximum of 461 nm, and intensity of green fluorescence to count number of GFP positive cells at a green emission maximum of 510 nm by using a high-throughput micro-well image cytometer (see Table of Materials). Analyze protein up-regulatory effect of the SINEUPs by calculating GFP integrated intensity, which is the sum of all pixel intensities displaying signal in segmented objects calculated for each channel, using Imaging software29.</li>
	<li>Harvest cells to check RNA expression (back to steps 5 and 6).</li>
</ol>

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The corresponding author Piero Carninci is one of the founders of TransSINE Technologies Co. Ltd. that holds intellectual property on filed patent (EP2691522A4 and JP2017169573A), and granted patent (US9353370B2) for SINEUP technology.

We described here a protocol to specifically enhance protein production of a target mRNA by means of a SINE-containing non-coding RNA, called SINEUPs. As a representative example, optimum synthetic SINEUP-GFP is shown to up-regulate the translation of GFP mRNA 2.6-fold as measured by Western-blot analysis.
Designing an optimum BD is crucial to ensure SINEUP specificity and potency (extent of protein up-regulation). Previously, we screened 17 BDs of SINEUP-GFP by Western-blot analysis15 and found that the optimum BD overlaps the AUG-KOZAK sequence of GFP mRNA, though it may not be the case with other mRNAs and should be verified for each case. Another independent group also screened the BD using a different method31. As screening many BDs can be quite time-consuming and cumbersome, we introduced a high-throughput SINEUP detection method here. This method measures relative changes in GFP integrated density in SINEUP transfected-cells compared to the control vector transfected-cells. To ensure that cells in a particular well of a culture plate are transfected equally and GFP signal is not concentrated to only a certain region of the well, it is very important to distribute the cells equally in the wells in step 2.1. For this purpose, gently shake the plate 10 times back and forth (&#8593;&#8595;) after seeding the cells inside a clean bench and repeat in the 5% CO2 incubator before starting the incubation.
Another critical step is the calculation of protein concentration in step 3.3. Miscalculations here can lead to the loading of an erroneous amount of protein during Western-blot analysis, consequently preventing detection of small changes in protein expression by some of the weak SINEUPs or generating false positives from overloading. It is recommended to freshly prepare the protein standard curve every time, making sure that equal amounts of standards and protein samples are measured in step 3.3.3. The protocol described here focuses on SINEUP-GFP, but Western-blot analysis can be used for any target mRNA of interest. The incubation time and concentration of antibodies should be optimized for each target to get the best result.
One of the unique features of SINEUPs is that target-mRNA expression level remains unaffected. It is important to treat RNA with DNase to avoid detection of transfected SINEUPs and genomic DNA by qRT-PCR. SINEUP RNAs and target mRNA expression should be measured by qRT-PCR to confirm the success of both transfection and SINEUP activity. SINEUPs contain a SINE sequence, which is abundant throughout both the human and mouse genomes. To avoid non-specific detection of SINE sequences, it is not recommended to design qRT-PCR primers to the SINE sequence.
In this protocol we used human cell lines, but SINEUPs are efficacious in a number of cell lines from several different species12,13,14,18,19. The cell culture and transfection conditions can be modified according to different cell lines as long as these maintain transfection efficiency of the SINEUP vectors. Moreover, alternative methods of RNA extraction, cDNA synthesis, and protein concentration checking can be employed, given that they preserve the required RNA and protein quality for qRT-PCR and Western-blot analysis. While we used a specific high-throughput micro-well cytometer, which enabled detection of GFP fluorescence across the entire well, other cytometers with a similar detection range can be used31. It is to be noted that if the distribution of cells and transfection are equal throughout a well, then it is not necessary to scan the whole well for GFP fluorescence: half or one-quarter of the area of a well might be enough to discern SINEUP effect depending on experimental skills.
Establishing a high-throughput SINEUP detection protocol allows for simultaneous screening of multiple BDs targeting a given mRNA in cultured cells. This is important as the rules governing optimum targeting by the BD are still unclear. Such a multiplex screening system allows for large-scale testing of many SINEUPs against different genes, useful for targeting multiple genes involved in a particular signaling pathway for instance. Furthermore, it can be utilized to expand the search for effective SINEUPs targeting several mRNAs, designing different SINEUP BDs around AUG-Kozak region (see Figure 1), co-transfecting full length target mRNAs (5&#697; UTR-CDS-3&#697; UTR) fused with GFP mRNA in cultured cells to find the optimum SINEUPs, and subsequently testing BD candidates against endogenous mRNA in cultured cells and in vivo model animals, from humans and mice to other animal and plant species.
This screening protocol is very fast. We do not need to fix and collect cells, but just need to place the living cell culture plate in the imaging instrument. We propose to use this high-throughput screening protocol to select optimum BDs of SINEUPs and evaluate potential candidates by Western-blot analysis. Thus, selected candidates with optimum BDs can be applied to increase antibody production18,19,21. Currently, the RNA therapeutic field is dramatically growing. For instance, siRNA, ASO, mRNA, and CRISPR RNA therapies, are widely employed to control mRNA expression of their respective targets9,32. In this context, SINEUPs are in their infancy, but so far none of the studied SINEUPs changed expression of target mRNAs. In addition, SINEUPs do not edit target mRNA, but only up-regulate translation of mRNA. Furthermore, loss-of-function diseases resulting from haploinsufficiency can be targeted by SINEUP therapy, achieving a 2-fold induction of the deficient protein17,33. Although off-target effects need to be further studied, SINEUPs potentially and specifically target a single, expressed mRNA with a complementary sequence to the BD.
A limitation of this high-throughput protocol is that it is not suitable to screen BDs of SINEUPs in in vivo mouse models because the protocol measures the GFP integrated intensity only. As SINEUPs are natural antisense lncRNAs that act post-transcriptionally, they cannot be applied when the target mRNA is missing in the cells or tissue samples.
Nevertheless, SINEUPs can be applied to gain-of-function studies, to enhance antibody production, and as an RNA therapy to up-regulate expression of deficient proteins within the range of 1.5-3.0-fold. The methods described here present a useful guide to target and detect SINEUP-induced translation enhancement of desired mRNA and provide a new tool for post-transcriptional gene regulation.

In the post-genomic era, many insights have been gained into the gene regulatory roles of non-coding antisense transcripts owing to the development of next-generation sequencing technologies1,2,3 and gene-editing tools. This category of transcripts, which was previously considered to be &#34;transcriptional trash&#34;, is now established as a key player of genetic regulation. Antisense transcripts are reported to modulate chromatin and control stability and expression of their cognate protein-coding sense mRNA4,5. In most cases, this mode of regulation is negative and antisense transcripts silence their sense counterparts through RNA-RNA interactions6,7. This trait of natural antisense transcripts has been utilized to downregulate desired genes in the form of synthetic small interfering RNA (siRNA), microRNA (miRNA), and antisense oligos (ASO)8,9,10,11 leaving a technological void for targeted gene up-regulation.
One intriguing study changed the perspective of the antisense RNA field by demonstrating that antisense long non-coding RNAs (AS lncRNAs) of the genes Uchl1 (ubiquitin C-terminal hydrolase L1) and Uxt (ubiquitously-expressed transcript) positively regulate translation of their cognate sense mRNA at the post-transcriptional level in mice12. The 5&#697; end of these AS lncRNAs overlaps with several bases in the 5&#697; untranslated region (5&#697; UTR) of their corresponding sense transcripts, and the non-overlapping 3&#697; end contains an inverted repeat of a retrotransposon belonging to the short interspersed nuclear element (SINE) family. Interestingly, we found that the main driving force behind this translational up-regulation is the embedded SINE repeat and it is not limited to mouse SINE repeats only. Human Alu repeat-containing AS lncRNAs also enhanced translation of target sense mRNAs, reinforcing the idea of a novel class of SINE-driven regulatory antisense non-coding RNAs, appropriately named SINEUPs13. Recent studies showed that the potential of natural SINEUPs is preserved in synthetic SINEUPs designed to specifically target various endogenous and exogenous genes14,15. SINEUPs have two important features: first the &#34;binding domain&#34; (BD) which is generally the 5&#697; end region complementary to the sequence encompassing the primary start codon of a protein-coding mRNA, and second the &#34;effector domain&#34; (ED) as it incorporates an inverted repeat of SINE which is a prerequisite for SINEUP function14 (Figure 1). SINEUPs can be customized to design a BD specifically targeting a gene of choice. This can then be harnessed to dissect the function of a particular gene involved in a biological pathway, as a better alternative to a conventional mRNA overexpression strategy. In addition, this versatile tool can be applied to boost antibody production, and as a drug to treat haploinsufficient diseases caused by insufficient dosages of functional proteins16,17,18,19,20,21.
The advantages of SINEUP technology are manifold. It does not alter the expression of the target at the transcriptional level. Longer BDs provide more specificity to SINEUPs, while not inducing a dsRNA-dependent stress response15. The protein induction is maintained within the normal physiological range of the cell, preventing any deleterious effect due to aberrant or excessive protein expression. SINEUPs are compatible with a wide variety of mouse, human, and hamster cultured cell lines, for instance, HEK293T/17, HepG2, HeLa, CHO, MN9D, and many more12,13,14,15,18,19. SINEUPs can efficiently target endogenous genes, transiently overexpressed genes, and FLAG-tagged or luciferase-fusion genes, eliminating the need of gene-specific antibodies14,18. The basic SINEUP analysis requires routine cell culture, transfection, sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), real time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) instruments and settings, and expertise can be gained in a short time.
Here, we describe a method for targeting genes with synthetic SINEUPs to up-regulate translation, an effect contrary to other technologies such as RNA interference9 and ASO gapmers11,22,23. A widely-used method for RNA-guided gene activation is clustered regularly interspaced short palindromic repeats-based activation (CRISPRa), where the gene expression is triggered at the transcriptional level24. This method, though simple and fast, requires multiple single guide RNAs (sgRNAs) targeting the same gene for higher efficiency, thereby increasing the chances of off-target binding25. In addition, the key enzyme of the CRISPRa system, the catalytically dead CRISPR-associated protein 9 (dCas9) has low binding specificity and sgRNAs targeting bi-directional promoter regions can non-specifically up-regulate nearby genes25. Conversely, SINEUPs bind to target mRNA at a single binding region with high specificity and do not affect expression of nearby genes. We discuss the basic steps involved in SINEUP design, transfection, protein and RNA expression analyses. Furthermore, we present a semi-automated, high-throughput imaging system to screen multiple SINEUPs at once, which is useful for detection of optimum SINEUPs.

<table>
	<tbody>
		<tr>
			<td>Synthetic SINEUP</td>
			<td>Cell Guidance Systems Ltd. in UK and K.K.DNAFORM in Japan</td>
			<td>https://www.cellgs.com/items/sineupand8482.html and https://www.dnaform.jp/en/information/20130320</td>
			<td>Step 1.5.</td>
		</tr>
		<tr>
			<td>HEK293T/17</td>
			<td>ATCC</td>
			<td>ATCC CRL-11268</td>
			<td>Step 2.1.</td>
		</tr>
		<tr>
			<td>Falcon Multiwell Plate For Cell Culture 6 well plate</td>
			<td>Corning</td>
			<td>6902A01</td>
			<td>Step 2.1.</td>
		</tr>
		<tr>
			<td>Corning BioCoat Poly-D-Lysine 24 well Plate</td>
			<td>Corning</td>
			<td>08-774-124</td>
			<td>Step 2.1.</td>
		</tr>
		<tr>
			<td>Lipofectamine 2000 Transfection Reagent</td>
			<td>Thermo Fisher Scientific</td>
			<td>11668027</td>
			<td>Step 2.2.</td>
		</tr>
		<tr>
			<td>pEGFP-C2</td>
			<td>Clontech</td>
			<td>#6083-1</td>
			<td>Step 2.2.</td>
		</tr>
		<tr>
			<td>Cell Lysis Buffer (10x)</td>
			<td>Cell Signaling Technology</td>
			<td>#9803S</td>
			<td>Step 3.1. This is pre-mixed cell lysis solution.</td>
		</tr>
		<tr>
			<td>PMSF</td>
			<td>Cell Signaling Technology</td>
			<td>#8553S</td>
			<td>Step 3.1. To complete cell lysis buffer, add 0.005% (w/v) PMSF to 1 x cell lysis buffer.</td>
		</tr>
		<tr>
			<td>DC protein assay kit II</td>
			<td>BIO RAD</td>
			<td>#5000112JA</td>
			<td>Step 3.3.</td>
		</tr>
		<tr>
			<td>10% Mini-PROTEAN TGX Precast Protein Gels, 12-well, 20 &#181;l</td>
			<td>BIO RAD</td>
			<td>#4561035</td>
			<td>Step 4.2.</td>
		</tr>
		<tr>
			<td>Amersham Protran Premium NC 0.45 (150 mm&#215;4 m)</td>
			<td>Amasham</td>
			<td>10600013</td>
			<td>Step 4.3., This is a 0.45 &#181;m nitrocellulose membrane.</td>
		</tr>
		<tr>
			<td>Nonfat Dry Milk</td>
			<td>Cell Signaling Technology</td>
			<td>#9999S</td>
			<td>Step 4.4. A component of the blocking solution.</td>
		</tr>
		<tr>
			<td>GFP Tag Antibody</td>
			<td>Thermo Fisher Scientific</td>
			<td>A-6455</td>
			<td>Step 4.5. Lot number: 1495850, RRID: AB_221570</td>
		</tr>
		<tr>
			<td>Monoclonal Anti-&#946;-Actin antibody produced in mouse</td>
			<td>SIGMA</td>
			<td>A5441</td>
			<td>Step 4.5. Lot number: 026M4780V, RRID: AB_476744</td>
		</tr>
		<tr>
			<td>Polyclonal Goat Anti Rabbit Immunoglobulins</td>
			<td>Dako</td>
			<td>P0448</td>
			<td>Step 4.5. This is secondary antibody conjugating with HRP for anti GFP antibody. Lot number: 20017525, RRID:AB_2617138</td>
		</tr>
		<tr>
			<td>Polyclonal Goat Anti mouse Immunoglobulins</td>
			<td>Dako</td>
			<td>P0447</td>
			<td>Step 4.5. This is secondary antibody conjugating with HRP for anti &#946;-Actin antibody. Lot number: 20019698, RRID:AB_2617137</td>
		</tr>
		<tr>
			<td>ECL Western Blotting Detection Reagents</td>
			<td>Amersham</td>
			<td>RPN2109</td>
			<td>Step 4.9.</td>
		</tr>
		<tr>
			<td>Maxwell Rapid Sample Concentrator (RSC) Instrument</td>
			<td>Promega</td>
			<td>AS4500</td>
			<td>Step 5.1. This is commercially available RNA exreaction instrument.</td>
		</tr>
		<tr>
			<td>Maxwell RSC simplyRNA Cells Kit</td>
			<td>Promega</td>
			<td>AS1390</td>
			<td>Step 5.1. This is commercially available RNA exreaction kit.</td>
		</tr>
		<tr>
			<td>TURBO DNA-free Kit</td>
			<td>ambion</td>
			<td>AM1907</td>
			<td>Step 5.2 and 5.4. The kit contains DNase, DNase buffer and inactivation reagent.</td>
		</tr>
		<tr>
			<td>PrimeScrip 1st strand cDNA Synthesis Kit</td>
			<td>TaKaRa</td>
			<td>6110A</td>
			<td>Step 6.1. The kit contains reagents of first strand cDNA synthesis.</td>
		</tr>
		<tr>
			<td>TB Green Premix Ex Taq II</td>
			<td>TaKaRa</td>
			<td>RR820A</td>
			<td>Step 6.2.</td>
		</tr>
		<tr>
			<td>Hoechst3342</td>
			<td>Thermo Fisher Scientific</td>
			<td>H3570</td>
			<td>Step 7.2.</td>
		</tr>
		<tr>
			<td>Celigo S</td>
			<td>Nexcelom Bioscience</td>
			<td>200-BFFL-S</td>
			<td>Step 7.3. This is a high throughput micro-well image cytometer.</td>
		</tr>
	</tbody>
</table>

cell based assays of sineup non-coding rnas that can specifically enhance mrna translation

Targeted-protein enhancement is of importance not only for the study of biological processes but also for therapeutic and biotechnological applications. Here, we present a method to selectively up-regulate protein expression of desired genes in cultured cells by means of synthetic antisense non-coding RNAs known as SINEUPs. This positive control of gene expression is at the post-transcriptional level and exerted by an inverted short interspersed nuclear element (SINE) repeat at the 3&#697; end of SINEUPs that comprises its effector domain (ED). SINEUPs can specifically bind to any protein-coding mRNA of choice through its binding domain (BD), a region designed to complement the sequence within the 5&#697; untranslated region (5&#697; UTR) and around the start codon of the mRNA. Target-specific SINEUPs designed in this manner are transfected to cultured cells, and protein and RNA are extracted for downstream analyses, generally 24-48 h post-transfection. SINEUP-induced protein up-regulation is detected by Western-blot analysis and RNA expression is measured using real-time quantitative reverse transcription PCR. We have observed that BD design is critical for achieving optimum SINEUP activity and that testing different BD sizes and positions with respect to the start codon of the target mRNA is recommended. Therefore, we describe here a semi-automated high-throughput imaging method based on fluorescence detection that can be implemented to target mRNA fused with green fluorescent protein (GFP). SINEUPs specifically enhance translation within normal physiological range of the cell, without altering the target transcript level. This method has been successfully employed against a range of endogenous and exogenous targets, in a wide variety of human, mouse, and insect cell lines along with in vivo systems. Moreover, SINEUPs have been reported to increase antibody production and work as an RNA therapeutic against haploinsufficient genes. The versatile and modular nature of SINEUPs makes them a suitable tool for gene-specific translational control.

SINEUP-GFP is a synthetic SINEUP containing both an optimum BD (-28/+4 overlap to GFP mRNA) and an ED (inverted SINE B2 from AS-Uchl1) that can up-regulate GFP mRNA translation (Figure 3A and 3B) without changing the expression of GFP mRNA (Figure 3C and 3D). To screen optimum BDs and EDs for SINEUPs, we developed a protocol of semi-automated image analysis that improved detection time and increased the number of samples being simultaneously screened compared with a conventional Western-blot analysis15. As shown in Figure 4, this high-throughput imaging system took 3 days (Western-blot analysis took 2 weeks for 48 SINEUPs). Having demonstrated that SINEUP-GFP increases GFP translation, we detected GFP integrated intensity by the image cytometer. The optimum BD of SINEUP-GFP induced a 1.4-fold increase in GFP protein expression. Although we observed compression of signals from 2.6-fold (Western-blot analysis, see Figure 3A) to 1.4-fold (Imaging analysis, see Figure 5), the difference might be due to the calibration of the imaging instrument software. Nevertheless, we detected significantly higher levels of GFP fluorescence compared with the control (Figure 5A and 5B).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58627/58627fig1.jpg" /> 
Figure 1: Basic design of the synthetic SINEUPs. BD = binding domain to target mRNA, ED = effector domain containing an inverted SINE sequence. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58627/58627fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58627/58627fig2.jpg" /> 
Figure 2: Transcription starting sites (TSSs) of human Parkinson disease protein 7 (PARK7) mRNA in specific tissues and cells as detected by CAGE analysis. (A) A snapshot showing a TSS search result for human PARK7 mRNA using an omics data integration and interactive visualization system30. The horizontal green arrow in the Entrez gene hg19 track indicates the genomic position of the reference human PARK7 mRNA and the vertical green bars in the FANTOM5 CAGE 1 and 2 tracks indicate the sum of TSSs (measured as transcripts per million (tpm)) from 1,829 types of tissues and cells. (B) Zoom in of the marked region of the TSS in panel A (1/354 scale: 35.4 kb to 100 bp). Grey shaded area in the FANTOM5 CAGE phase 1 and 2 tracks indicates the TSS of 6 specific cells out of the total 1,829, which are listed at the bottom of the figure. The numbers (11.369, 4.998, 4.304, 3.509, 3.477, and 3.055) corresponding to these listed cells indicate transcripts per million for each specific cell at the grey shaded positions of the TSS. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58627/58627fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58627/58627fig3.jpg" /> 
Figure 3: Western-blot analysis confirming up-regulation of translation by SINEUP-GFP. (A) SINEUP-GFP was examined by Western-blot with anti-GFP antibody. (B) Results were normalized to the intensity of the &#946;-actin protein band. (C) GFP mRNA and (D) SINEUP RNAs expression were detected by qRT-PCR. ***p &#60; 0.0005, n = 3, two-tailed student&#39;s t-test, error bars are standard deviation. This figure has been modified from Takahashi et al.15. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58627/58627fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/58627/58627fig4.jpg" /> 
Figure 4: Schematic of SINEUP semi-automated image analysis. Day 1: Seed cells of interest in a 24 well-plate. Day 2: Transfect GFP and SINEUP-GFP. Day 3: Analyze the effect of SINEUPs by measuring GFP integrated intensity. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58627/58627fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/58627/58627fig5.jpg" /> 
Figure 5: High-throughput analysis of translation up-regulation by SINEUP-GFP. (A) Comparison of GFP fluorescence between control and SINEUP-GFP transfected cells15. Scale bar = 2 mm. (B) GFP integrated intensity was normalized to the total cell number counted by nuclear staining with Hoechst 33342. ***p &#60; 0.0005, n = 3, two-tailed student&#39;s t-test, error bars are standard deviation. FOV: field of view. This figure has been modified from Takahashi et al.15. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/58627/58627fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Cell Based Assays of SINEUP Non-coding RNAs That Can Specifically Enhance mRNA Translation at JoVE.com

Cell Based Assays of SINEUP Non-coding RNAs That Can Specifically Enhance mRNA Translation

SINEUPs are synthetic antisense non-coding RNAs, which contain a binding domain (BD) and an effector domain (ED) and up-regulate translation of target mRNA. Here, we describe detection methods for SINEUPs in cultured cell lines, analysis of their translation-promoting activity by Western-blot and a semi-automated high throughput imaging system.

Targeted-protein enhancement is of importance not only for the study of biological processes but also for therapeutic and biotechnological applications. ...

cell-based-assays-sineup-non-coding-rnas-that-can-specifically

Universidad de Cartagena UDEC

Research

JoVE Journal

Genetics

8.3K Views.  RIKEN Center for Integrative Medical Sciences. SINEUPs are synthetic antisense non-coding RNAs, which contain a binding domain (BD) and an effector domain (ED) and up-regulate translation of target mRNA. Here, we describe detection methods for SINEUPs in cultured cell lines, analysis of their translation-promoting activity by Western-blot and a semi-automated high throughput imaging system.

Video: Cell Based Assays of SINEUP Non-coding RNAs That Can Specifically Enhance mRNA Translation

Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells

The processing of most eukaryotic RNAs is mediated by RNA Binding Proteins (RBPs) with modular configurations, including an RNA recognition module, which specifically binds the pre-mRNA target and an effector domain. Previously, we have taken advantage of the unique RNA binding mode of the PUF domain in human Pumilio 1 to generate a programmable RNA binding scaffold, which was used to engineer various artificial RBPs to manipulate RNA metabolism. Here, a detailed protocol is described to construct Engineered Splicing Factors (ESFs) that are specifically designed to modulate the alternative splicing of target genes. The protocol includes how to design and construct a customized PUF scaffold for a specific RNA target, how to construct an ESF expression plasmid by fusing a designer PUF domain and an effector domain, and how to use ESFs to manipulate the splicing of target genes. In the representative results of this method, we have also described the common assays of ESF activities using splicing reporters, the application of ESF in cultured human cells, and the subsequent effect of splicing changes. By following the detailed protocols in this report, it is possible to design and generate ESFs for the regulation of different types of Alternative Splicing (AS), providing a new strategy to study splicing regulation and the function of different splicing isoforms. Moreover, by fusing different functional domains with a designed PUF domain, researchers can engineer artificial factors that target specific RNAs to manipulate various steps of RNA processing.

This report describes a bioengineering method to design and construct novel Artificial Splicing Factors (ASFs) that specifically modulate the splicing of target genes in mammalian cells. This method can be further expanded to engineer various artificial factors to manipulate other aspects of RNA metabolism.

The processing of most eukaryotic RNAs is mediated by RNA Binding Proteins (RBPs) with modular configurations, including an RNA recognition module, which ...

Sequence-specific and Selective Recognition of Double-stranded RNAs over Single-stranded RNAs by Chemically Modified Peptide Nucleic Acids

RNAs are emerging as important biomarkers and therapeutic targets. Thus, there is great potential in developing chemical probes and therapeutic ligands for the recognition of RNA sequence and structure. Chemically modified Peptide Nucleic Acid (PNA) oligomers have been recently developed that can recognize RNA duplexes in a sequence-specific manner. PNAs are chemically stable with a neutral peptide-like backbone. PNAs can be synthesized relatively easily by the manual Boc-chemistry solid-phase peptide synthesis method. PNAs are purified by reverse-phase HPLC, followed by molecular weight characterization by matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF). Non-denaturing polyacrylamide gel electrophoresis (PAGE) technique facilitates the imaging of the triplex formation, because carefully designed free RNA duplex constructs and PNA bound triplexes often show different migration rates. Non-denaturing PAGE with ethidium bromide post staining is often an easy and informative technique for characterizing the binding affinities and specificities of PNA oligomers. Typically, multiple RNA hairpins or duplexes with single base pair mutations can be used to characterize PNA binding properties, such as binding affinities and specificities. 2-Aminopurine is an isomer of adenine (6-aminopurine); the 2-aminopurine fluorescence intensity is sensitive to local structural environment changes, and is suitable for the monitoring of triplex formation with the 2-aminopurine residue incorporated near the PNA binding site. 2-Aminopurine fluorescence titration can also be used to confirm the binding selectivity of modified PNAs towards targeted double-stranded RNAs (dsRNAs) over single-stranded RNAs (ssRNAs). UV-absorbance-detected thermal melting experiments allow the measurement of the thermal stability of PNA-RNA duplexes and PNA&#183;RNA2 triplexes. Here, we describe the synthesis and purification of PNA oligomers incorporating modified residues, and describe biochemical and biophysical methods for characterization of the recognition of RNA duplexes by the modified PNAs.

We report the protocols for the synthesis and purification of Peptide Nucleic Acid (PNA) oligomers incorporating modified residues. The biochemical and biophysical methods for the characterization of the recognition of RNA duplexes by the modified PNAs are described.

RNAs are emerging as important biomarkers and therapeutic targets. Thus, there is great potential in developing chemical probes and therapeutic ligands ...

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for protein synthesis by translating codons in mRNA into amino acid sequences. tRNAs were long considered as house-keeping molecules that lacked regulatory functions. However, a growing body of evidence indicates that cellular tRNA levels fluctuate in correspondence to varying conditions such as cell type, environment, and stress. The fluctuation of tRNA expression directly influences gene translation, favoring or repressing the expression of particular proteins. Ultimately comprehending the dynamic of protein synthesis requires the development of methods able to deliver high-quality tRNA profiles. The method that we present here is named SPOt, which stands for Streamlined Platform for Observing tRNA. SPOt consists of three steps starting with metabolic labeling of cell cultures with radioactive orthophosphate, followed by guanidinium thiocyanate-phenol-chloroform extraction of radioactive total RNAs and finally hybridization on in-house printed macroarrays. tRNA levels are estimated by quantifying the radioactivity intensities at each probe spot. In the protocol presented here we profile tRNAs in Mycobacterium smegmatis mc2155, a nonpathogenic bacterium often used as a model organism to study tuberculosis.

We describe an original transfer RNA analysis platform named SPOt (Streamlined Platform for Observing tRNA). SPOt simultaneously measures cellular levels of all tRNAs in biological samples, in only three steps, and in less than 24 hours.

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for ...

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

Long non-coding RNA (lncRNA), which are sequences of more than 200 nucleotides without a defined reading frame, belong to the regulatory non-coding RNA&#39;s family. Although their biological functions remain largely unknown, the number of these lncRNAs has steadily increased and it is now estimated that humans may have more than 10,000 such transcripts. Some of these are known to be involved in important regulatory pathways of gene expression which take place at the transcriptional level, but also at different steps of RNA co- and post-transcriptional maturation. In the latter cases, RNAs that are targeted by the lncRNA have to be identified. That&#39;s the reason why it is useful to develop a method enabling the identification of RNAs associated directly or indirectly with a lncRNA of interest.
This protocol, which was inspired by previously published protocols allowing the isolation of a lncRNA together with its associated chromatin sequences, was adapted to permit the isolation of associated RNAs. We determined that two steps are critical for the efficiency of this protocol. The first is the design of specific anti-sense DNA oligonucleotide probes able to hybridize to the lncRNA of interest. To this end, the lncRNA secondary structure was predicted by bioinformatics and anti-sense oligonucleotide probes were designed with a strong affinity for regions that display a low probability of internal base pairing. The second crucial step of the procedure relies on the fixative conditions of the tissue or cultured cells that have to preserve the network between all molecular partners. Coupled with high throughput RNA sequencing, this RNA pull-down protocol can provide the whole RNA interactome of a lncRNA of interest.

This RNA pull-down method allows identifying the RNA targets of a long non-coding RNA (lncRNA). Based on the hybridization of home-made, designed anti-sense DNA oligonucleotide probes specific to this lncRNA in an appropriately fixed tissue or cell line, it efficiently allows the capture of all RNA targets of the lncRNA.

Long non-coding RNA (lncRNA), which are sequences of more than 200 nucleotides without a defined reading frame, belong to the regulatory non-coding ...

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally regulate cellular gene expression. MiRNAs bind to the 3&#39; untranslated region (UTR) of target mRNA to inhibit protein translation or in some instances cause mRNA degradation. The binding of the miRNA to the 3&#39; UTR of the target mRNA is mediated by a 2&#8211;8 nucleotide seed sequence at the 5&#39; end of miRNA. While the role of miRNAs as cellular regulatory molecules is well established, identification of the target mRNAs with functional relevance remains a challenge. Bioinformatic tools have been employed to predict sequences within the 3&#39; UTR of mRNAs as potential targets for miRNA binding. These tools have also been utilized to determine the evolutionary conservation of such sequences among related species in an attempt to predict functional role. However, these computational methods often generate false positive results and are limited to predicting canonical interaction between miRNA and mRNA. Therefore, experimental procedures that measure direct binding of miRNA to its mRNA target are necessary to establish functional interaction. In this report, we describe a sensitive method for validating direct interaction between the cellular miRNA miR-125b and the 3&#39; UTR of PARP-1 mRNA. We elaborate a protocol in which synthetic biotinylated-miRNA mimics were transfected into mammalian cells and the miRNA-mRNA complex in the cellular lysate was pulled down with streptavidin-coated magnetic beads. Finally, the target mRNA in the pulled-down nucleic acid complex was quantified using a qPCR-based strategy.

This report describes a fast and reliable method for validating mRNA targets of cellular miRNAs. The method uses synthetic biotinylated Locked Nucleic Acid (LNA)-based miRNA mimics to capture target mRNA. Subsequently, streptavidin-coated magnetic beads are employed to pulldown the target mRNA for quantification by qPCR polymerase chain reaction.

MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally regulate cellular gene expression. MiRNAs bind to the 3&#39; ...

Isolation, Characterization and MicroRNA-based Genetic Modification of Human Dental Follicle Stem Cells

To date, several stem cell types at different developmental stages are in the focus for the treatment of degenerative diseases. Yet, certain aspects, such as initial massive cell death and low therapeutic effects, impaired their broad clinical translation. Genetic engineering of stem cells prior to transplantation emerged as a promising method to optimize therapeutic stem cell effects. However, safe and efficient gene delivery systems are still lacking. Therefore, the development of suitable methods may provide an approach to resolve current challenges in stem cell-based therapies.
The present protocol describes the extraction and characterization of human dental follicle stem cells (hDFSCs) as well as their non-viral genetic modification. The postnatal dental follicle unveiled as a promising and easily accessible source for harvesting adult multipotent stem cells possessing high proliferation potential. The described isolation procedure presents a simple and reliable method to harvest hDFSCs from impacted wisdom teeth. Also this protocol comprises methods to define stem cell characteristics of isolated cells. For genetic engineering of hDFSCs, an optimized cationic lipid-based transfection strategy is presented enabling highly efficient microRNA introduction without causing cytotoxic effects. MicroRNAs are suitable candidates for transient cell manipulation, as these small translational regulators control the fate and behavior of stem cells without the hazard of stable genome integration. Thus, this protocol represents a safe and efficient procedure for engineering of hDFSCs that may become important for optimizing their therapeutic efficacy.

This protocol describes the transient genetic engineering of dental stem cells extracted from the human dental follicle. The applied non-viral modification strategy may become a basis for the improvement of therapeutic stem cell products.

To date, several stem cell types at different developmental stages are in the focus for the treatment of degenerative diseases. Yet, certain aspects, such ...

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria

Dictyostelium discoideum is an intriguing model organism for the study of cell differentiation processes during development, cell signaling, and other important cellular biology questions. The technologies available to genetically manipulate Dictyostelium cells are well-developed. Transfections can be performed using different selectable markers and marker re-cycling, including homologous recombination and insertional mutagenesis. This is supported by a well-annotated genome. However, these approaches are optimized for axenic cell lines growing in liquid cultures and are difficult to apply to non-axenic wild-type cells, which feed only on bacteria. The mutations that are present in axenic strains disturb Ras signaling, causing excessive macropinocytosis required for feeding, and impair cell migration, which confounds the interpretation of signal transduction and chemotaxis experiments in those strains. Earlier attempts to genetically manipulate non-axenic cells have lacked efficiency and required complex experimental procedures. We have developed a simple transfection protocol that, for the first time, overcomes these limitations. Those series of large improvements to Dictyostelium molecular genetics allow wild-type cells to be manipulated as easily as standard laboratory strains. In addition to the advantages for studying uncorrupted signaling and motility processes, mutants that disrupt macropinocytosis-based growth can now be readily isolated. Furthermore, the entire transfection workflow is greatly accelerated, with recombinant cells that can be generated in days rather than weeks. Another advantage is that molecular genetics can further be performed with freshly isolated wild-type Dictyostelium samples from the environment. This can help to extend the scope of approaches used in these research areas.

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria

Dictyostelium discoideum is a popular model organism to study complex cellular processes such as cell migration, endocytosis, and development. The utility of the organism is dependent on the feasibility of genetic manipulation. Here, we present methods to transfect Dictyostelium discoideum cells that overcome existing limitations of culturing cells in liquid media.

Dictyostelium discoideum is an intriguing model organism for the study of cell differentiation processes during development, cell signaling, and other ...

Overexpressing Long Noncoding RNAs Using Gene-activating CRISPR

Long noncoding RNA (lncRNA) biology is a new and exciting field of research, with the number of publications from this field growing exponentially since 2007. These studies have confirmed that lncRNAs are altered in almost all diseases. However, studying the functional roles for lncRNAs in the context of disease remains difficult due to the lack of protein products, tissue-specific expression, low expression levels, complexities in splice forms, and lack of conservation among species. Given the species-specific expression, lncRNA studies are often restricted to human research contexts when studying disease processes. Since lncRNAs function at the molecular level, one way to dissect lncRNA biology is to either remove the lncRNA or overexpress the lncRNA and measure cellular effects. In this article, a written and visualized protocol to overexpress lncRNAs in vitro is presented. As a representative experiment, an lncRNA associated with inflammatory bowel disease, Interferon Gamma Antisense 1 (IFNG-AS1), is shown to be overexpressed in a Jurkat T-cell model. To accomplish this, the activating clustered regularly interspaced short palindromic repeats (CRISPR) technique is used to enable overexpression at the endogenous genomic loci. The activating CRISPR technique targets a set of transcription factors to the transcriptional start site of a gene, enabling a robust overexpression of multiple lncRNA splice forms. This procedure will be broken down into three steps, namely (i) guide RNA (gRNA) design and vector construction, (ii) virus generation and transduction, and (iii) colony screening for overexpression. For this representative experiment, a greater than 20-fold enhancement in IFNG-AS1 in Jurkat T cells was observed.

Traditional cDNA-based overexpression techniques have a limited applicability for the overexpression of long noncoding RNAs due to their multiple splice forms with potential functionality. This review reports a protocol using CRISPR technology to overexpress multiple splice variants of a long noncoding RNA.

Long noncoding RNA (lncRNA) biology is a new and exciting field of research, with the number of publications from this field growing exponentially since ...

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, and was deployed to West Africa during the recent Ebola virus epidemic, highlighting this possibility. In addition to its practical advantages (low cost, ease of equipment transport and use), this technology also provides fundamental advantages over second-generation sequencing approaches, particularly the very long read length, ability to directly sequence RNA, and real-time availability of data. Raw read accuracy is lower than with other sequencing platforms, which represents the main limitation of this technology; however, this can be partially mitigated by the high read depth generated. Here, we present a field-compatible protocol for sequencing of the mRNAs encoding for Niemann-Pick C1, which is the cellular receptor for ebolaviruses. This protocol encompasses extraction of RNA from animal blood samples, followed by RT-PCR for target enrichment, barcoding, library preparation, and the sequencing run itself, and can be easily adapted for use with other DNA or RNA targets.

Nanopore sequencing is a novel technology that allows cost-effective sequencing in remote locations and resource-poor settings. Here, we present a protocol for sequencing of mRNAs from whole blood that is compatible with such conditions.

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, ...

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Through whole-exome/genome sequencing, human geneticists identify rare variants that segregate with disease phenotypes. To assess if a specific variant is pathogenic, one must query many databases to determine whether the gene of interest is linked to a genetic disease, whether the specific variant has been reported before, and what functional data is available in model organism databases that may provide clues about the gene&#8217;s function in human. MARRVEL (Model organism Aggregated Resources for Rare Variant ExpLoration) is a one-stop data collection tool for human genes and variants and their orthologous genes in seven model organisms including in mouse, rat, zebrafish, fruit fly, nematode worm, fission yeast, and budding yeast. In this Protocol, we provide an overview of what MARRVEL can be used for and discuss how different datasets can be used to assess whether a variant of unknown significance (VUS) in a known disease-causing gene or a variant in a gene of uncertain significance (GUS) may be pathogenic. This protocol will guide a user through searching multiple human databases simultaneously starting with a human gene with or without a variant of interest. We also discuss how to utilize data from OMIM, ExAC/gnomAD, ClinVar, Geno2MP, DGV and DECHIPHER. Moreover, we illustrate how to interpret a list of ortholog candidate genes, expression patterns, and GO terms in model organisms associated with each human gene. Furthermore, we discuss the value protein structural domain annotations provided and explain how to use the multiple species protein alignment feature to assess whether a variant of interest affects an evolutionarily conserved domain or amino acid. Finally, we will discuss three different use-cases of this website. MARRVEL is an easily accessible open access website designed for both clinical and basic researchers and serves as a starting point to design experiments for functional studies.

Here, we present a protocol to access and analyze many human and model organism databases efficiently. This protocol demonstrates the use of MARRVEL to analyze candidate disease-causing variants identified from next-generation sequencing efforts.

Through whole-exome/genome sequencing, human geneticists identify rare variants that segregate with disease phenotypes. To assess if a specific variant is ...

Cell Based Assays of SINEUP Non-coding RNAs That Can Specifically Enhance mRNA Translation

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Chapters in this video

Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells

Sequence-specific and Selective Recognition of Double-stranded RNAs over Single-stranded RNAs by Chemically Modified Peptide Nucleic Acids

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Isolation, Characterization and MicroRNA-based Genetic Modification of Human Dental Follicle Stem Cells

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria

Overexpressing Long Noncoding RNAs Using Gene-activating CRISPR

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information