We thank Erin Zoller, Jessica Bene, and Lindsey Hays for input and direction in protocol development. MTW was supported in part by NIH R21 HG008186 and a Trustee Award grant from the Cincinnati Children's Hospital Research Foundation. ZHP was supported in part by T32 GM063483-13.

1. Preparation of Solutions and Reagents
<ol>
	<li>Order custom DNA oligonucleotide probes for use in EMSA and DAPA.
	<ol>
		<li>To reduce non-specific protein binding, design short oligos (between 35-45 base pairs (bp) in length)30, and place the variant of interest directly in the center flanked by its 17 bp endogenous genomic sequence. For EMSA oligos, add a 5&#39; fluorophore. For DAPA oligos, add a 5&#39; biotin tag.</li>
		<li>Order both the sense strand and its reverse complement strand. Alternatively, order duplex (pre-annealed) oligos. When naming the oligos, base the nomenclature on an established reference genome. 
		Note: &#34;Risk&#34; and &#34;non-risk&#34; designation can be disease and project specific, while &#34;reference&#34; and &#34;non-reference&#34; are more universally relevant.</li>
		<li>Upon arrival of the oligos, briefly spin down the contents and resuspend in nuclease-free water to a final concentration of 100 &#181;M. Store resuspended stock at -20 &#176;C. Protect oligos tagged with a fluorophore from light by wrapping with aluminum foil.</li>
	</ol>
	</li>
</ol>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Name</td>
			<td>Sequence</td>
		</tr>
		<tr>
			<td>rs76562819_REF_FOR</td>
			<td>GTAATGCCTTAATGAGAGAGAGTTAGTCATCTTCTCACTTC</td>
		</tr>
		<tr>
			<td>rs76562819_REF_REV</td>
			<td>GAAGTGAGAAGATGACTAACTCTCTCTCATTAAGGCATTAC</td>
		</tr>
		<tr>
			<td>rs76562819_NONREF_FOR</td>
			<td>GTAATGCCTTAATGAGAGAGGGTTAGTCATCTTCTCACTTC</td>
		</tr>
		<tr>
			<td>rs76562819_NONREF_REV</td>
			<td>GAAGTGAGAAGATGACTAACCCTCTCTCATTAAGGCATTAC</td>
		</tr>
	</tbody>
</table>
Table 1: Example EMSA/DAPA oligonucleotide design to test a SNP for differential binding. &#34;REF&#34; stands for the reference allele, while &#34;NONREF&#34; stands for the non-reference allele. &#34;FOR&#34; stands for the forward strand, while &#34;REV&#34; indicates its complement. The SNP is seen in red. 
<ol start="2">
	<li>Prepare cytoplasmic extraction (CE) buffer with a final concentration of 10 mM HEPES (pH 7.9), 10 mM KCl, and 0.1 mM EDTA in deionized water.</li>
	<li>Prepare nuclear extraction (NE) buffer with a final concentration of 20 mM HEPES (pH 7.9), 0.4 M NaCl, and 1 mM EDTA in deionized water.</li>
	<li>Prepare annealing buffer with a final concentration of 10 mM Tris (pH 7.5-8.0), 50 mM NaCl, and 1 mM EDTA in deionized water.</li>
</ol>
2. Preparation of Nuclear Lysate from Cultured Cells
Note: This experimental protocol was optimized using B-lymphoblastoid cell lines, but has been tested in several other unrelated adherent/ suspension cell lines and works universally.
<ol>
	<li>Culture B-lymphoblastoid cells in Roswell Park Memorial Institute (RPMI) 1640 with 2 mM L-glutamine, 10% fetal bovine serum, and 1x antibiotic-antimycotic containing 100 units/ml of penicillin, 100 &#181;g/ml of streptomycin, and 250 ng/ml of amphotericin B.
	<ol>
		<li>Seed at a range of 200,000-500,000 viable cells/ml and incubate flasks at 37 &#176;C with 5% carbon dioxide in an upright position with vented or loose caps. 
		Note: The growth of B-lymphoblastoid cells slows when they reach over 1,000,000 cells/ml. Break up cell blasts by pipetting up and down several times and return cells to 200,000-500,000 cells/ml to maintain a rapid rate of growth.</li>
	</ol>
	</li>
	<li>Wash cultured cells twice with 10 ml ice cold phosphate buffered saline (PBS), spin down at 4 &#176;C, 300 x g for 5 min and remove PBS via aspiration.</li>
	<li>Count cells using a hemocytometer and resuspend pellet as 1 ml ice cold PBS per 107 cells. 
	Note: For example, if lysing 2 x 107 cells, resuspend in 2 ml PBS.</li>
	<li>Aliquot 1 ml to 1.5 ml microcentrifuge tubes so that each tube contains 107 cells in PBS. Centrifuge at 3,300 x g for 2 min 4 &#176;C and aspirate off PBS.</li>
	<li>Prior to use, add 1 mM dithiothreitol (DTT), 1x phosphatase inhibitor, and 1x protease inhibitor to a working stock of CE buffer. Resuspend cell pellet with 400 &#181;l of CE buffer and incubate on ice for 15 minutes.</li>
	<li>Add 25 &#181;l of 10% Nonidet P-40 and mix by pipetting. Centrifuge at 4 &#176;C, max speed for 3 min. Decant and discard the supernatant.</li>
	<li>Prior to use, add 1 mM DTT, 1x phosphatase inhibitor, and 1x protease inhibitor&#160;to a working stock of NE buffer. Resuspend cell pellet with 30 &#181;l of NE buffer and mix by vortexing.</li>
	<li>Incubate at 4 &#176;C in a tube rotator or on ice for 10 min. Centrifuge 3,300 x g for 2 min 4 &#176;C.</li>
	<li>Collect the clear supernatant (nuclear lysate) and aliquot before storing at -80 &#176;C to avoid multiple freeze-thaw cycles that may degrade the protein. Leave a 10 &#181;l aliquot to measure protein concentration using the bichoninic acid assay (BCA)31.</li>
</ol>
3. Electrophoretic Mobility Shift Assay (EMSA)
<ol>
	<li>Prepare Oligo Working Stock and EMSA Gel.
	<ol>
		<li>If oligos were ordered in duplex, thaw the 100 &#181;M stock and dilute 1:2,000 in annealing buffer to achieve a 50 nM working stock.</li>
		<li>If oligos were ordered single-stranded, thaw the 100 &#181;M stocks and dilute 1:10 in annealing buffer to achieve 100 nM working stocks. Combine 100 &#181;l of the 100 nM complement strand solution with each other in a microcentrifuge tube.
		<ol>
			<li>Place in a heat block at 95 &#176;C for 5 min. Turn off the heat block and allow the oligos to slowly cool down to room temperature for at least one hour prior to use.</li>
		</ol>
		</li>
		<li>Pre-run the EMSA Gel.
		<ol>
			<li>Remove the slide from a pre-cast 6% TBE gel and rinse under deionized water several times to remove any buffer from the wells. Prepare 1 L of 0.5x TBE buffer by adding 50 mL of 10x TBE to 950 ml of deionized water.</li>
			<li>Assemble the gel electrophoresis apparatus and check for leaks by filling the inner chamber with 0.5x TBE buffer. If no buffer leaks into the outer chamber, fill the outer chamber roughly two thirds of the way.</li>
			<li>Pre-run the gel at 100 V for 60 min.</li>
			<li>Flush each well with 200 &#181;l of 0.5x TBE buffer.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Prepare Binding Buffer Master Mix.
	<ol>
		<li>Prepare 10x binding buffer with a final concentration of 100 mM Tris, 500 mM KCl, 10 mM DTT; pH 7.5 in deionized water.</li>
		<li>In a microcentrifuge tube, create a master mix consisting of the reagents common to all reactions (10 &#181;l 10x binding buffer, 10 &#181;l DTT/polysorbate, 5 &#181;l Poly d(I-C), and 2.5 &#181;l salmon sperm DNA; Table 2). Prepare an additional 10% to account for volume loss due to pipetting.</li>
	</ol>
	</li>
</ol>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Final Conc.</td>
			<td>Rxn #1</td>
			<td>Rxn #2</td>
			<td>Rxn #3</td>
			<td>Rxn #4</td>
		</tr>
		<tr>
			<td>Ultrapure Water</td>
			<td>to 20 &#181;l vol.</td>
			<td>13.5 &#181;l</td>
			<td>11.98 &#181;l</td>
			<td>13.5&#181;l</td>
			<td>11.98 &#181;l</td>
		</tr>
		<tr>
			<td>10x Binding Buffer</td>
			<td>1x</td>
			<td>2 &#956;l</td>
			<td>2 &#956;l</td>
			<td>2 &#956;l</td>
			<td>2 &#181;l</td>
		</tr>
		<tr>
			<td>DTT/TW-20</td>
			<td>1x</td>
			<td>2 &#956;l</td>
			<td>2 &#956;l</td>
			<td>2 &#956;l</td>
			<td>2 &#956;l</td>
		</tr>
		<tr>
			<td>Salmon Sperm DNA</td>
			<td>500 ng/&#956;l</td>
			<td>0.5 &#956;l</td>
			<td>0.5 &#956;l</td>
			<td>0.5 &#956;l</td>
			<td>0.5 &#956;l</td>
		</tr>
		<tr>
			<td>1&#956;g/&#956;l Poly d(I-C)</td>
			<td>1 &#956;g</td>
			<td>1 &#956;l</td>
			<td>1 &#956;l</td>
			<td>1 &#956;l</td>
			<td>1 &#956;l</td>
		</tr>
		<tr>
			<td>Nuclear Extract (5.26 ug/&#181;l)</td>
			<td>8 &#956;g</td>
			<td>-</td>
			<td>1.52 &#956;l</td>
			<td>-</td>
			<td>1.52 &#956;l</td>
		</tr>
		<tr>
			<td>NE Buffer</td>
			<td></td>
			<td>1.52 &#956;l</td>
			<td>-</td>
			<td>1.52 &#956;l</td>
			<td>-</td>
		</tr>
		<tr>
			<td>Reference allele oligo</td>
			<td>50 fmol</td>
			<td>1 &#956;l</td>
			<td>1 &#956;l</td>
			<td>-</td>
			<td>-</td>
		</tr>
		<tr>
			<td>Non-Reference allele oligo</td>
			<td>50 fmol</td>
			<td>-</td>
			<td>-</td>
			<td>1 &#956;l</td>
			<td>1 &#956;l</td>
		</tr>
	</tbody>
</table>
Table 2: Example EMSA reaction setup. The table illustrates an example EMSA to test the hypothesis that there is genotype-dependent binding of TFs to a specific SNP.
<ol start="3">
	<li>Add nuclease-free water to each microcentrifuge tube such that the final volume following addition of all reagents will be 20 &#181;l.</li>
	<li>Add the appropriate amount (5.5 &#181;l) of master mix to each microcentrifuge tube.</li>
	<li>Add 8 &#181;g of nuclear lysate to the appropriate microcentrifuge tubes. Include tubes containing the oligo without nuclear extract as negative controls (e.g. Table 2, Rxn #1 and Rxn #3). 
	Note: The optimal amount of lysate per reaction must be determined experimentally by titration. Generally, titrating a range of 2-10 &#181;g of lysate is sufficient.</li>
	<li>Add 50 fmol of oligo to the appropriate microcentrifuge tubes. Flick to mix and briefly spin the contents to the bottom of the tube. Incubate for 20 min at room temperature. 
	Note: If attempting a supershift, incubate the lysate mixture with antibody for 20 min at room temperature prior to the addition of oligos. It is recommended to use 1 &#181;g of a ChIP-grade antibody for best results.</li>
	<li>Add 2 &#181;l of 10x Orange Loading Dye to each microcentrifuge tube. Pipette up and down to mix.</li>
	<li>Load the samples into the pre-run 6% TBE gel by pipetting up and down to mix and then expelling each sample into a separate well. Run the gel at 80 V until the orange dye has migrated 2/3 to 3/4 of the way down the gel. This should take approximately 60-75 min.</li>
	<li>Remove the gel from the plastic cassette by prying it open with a gel knife and place the gel in a container with 0.5% TBE buffer to keep it from drying out.</li>
	<li>Place the gel on the surface of an infrared and chemiluminescence imaging system, being sure to eliminate any bubbles or contaminants that will disrupt the image.</li>
	<li>Using the scanning system software, click the &#34;Acquire&#34; tab and then select &#34;Draw New&#34; to draw a box around the area corresponding to where the gel is located on the surface of the scanner.</li>
	<li>In the &#34;Channels&#34; section of the &#34;Acquire&#34; tab, select the channel corresponding to the wavelength of the fluorophore tag on the oligo. In the &#34;Scanner&#34; section, click &#34;preview&#34; to get a low-quality preview scan. Adjust the scan area by dragging the blue box surrounding the acquired preview image down to the portion of the gel to be imaged. 
	Note: For example, if using oligos labeled with a 700 nm fluorophore, make sure the &#34;700 nm&#34; channel is selected before scanning.</li>
	<li>In the &#34;Scan Controls&#34; section, select the &#34;84 &#181;M&#34; resolution option and the &#34;Medium&#34; quality option. Set the focus to offset to half the thickness of the gel. Note: For example, a 1 mm gel would use a 0.5 mm focus offset.</li>
	<li>In the &#34;Scanner&#34; section, click &#34;Start&#34; to begin the scan. 
	Note: During the scan, the brightness, contrast, and color scheme can often be adjusted manually depending on the manufacturer of the scanning system.</li>
	<li>After the scan has finished, select the &#34;Image&#34; tab and click &#34;Rotate or Flip&#34; in the &#34;Create&#34; section to correct the orientation. Save the image file by clicking &#34;Export&#34; in the main menu and then select &#34;Single Image View.&#34;</li>
</ol>
4. DNA Affinity Purification Assay (DAPA)
<ol>
	<li>Preparation of 5 &#181;M Oligo Working Stock.
	<ol>
		<li>If oligos were ordered in duplex, thaw the 100 &#181;M stock and dilute 1:20 in annealing buffer to achieve a 5 &#181;M working stock.</li>
		<li>If oligos were ordered single-stranded, thaw the 100 &#181;M stocks and dilute 1:10 in annealing buffer to achieve 10 &#181;M working stocks. Combine 10 &#181;l of the 10 &#181;M complementary strands with each other. Place in a heat block at 95 &#176;C for 5 min. Turn off the heat block and allow the oligos to slowly cool down to room temperature prior to use.</li>
	</ol>
	</li>
	<li>Before starting, warm the binding buffer, low stringency wash buffer, high stringency wash buffer, and elution buffer to room temperature. 
	Note: A final concentration of 50 ng/mL Poly d(I-C) can be added to the binding buffer, low stringency wash buffer, and high stringency wash buffer to reduce potential non-specific binding of proteins to the oligos.</li>
	<li>Prepare the binding mixtures for each variant.
	<ol>
		<li>Mix 1 volume of nuclear lysate with 2 volumes of binding buffer. 
		Note: The required amount of lysate must be determined experimentally due to varying abundance of TFs. Using between 100-250 &#181;g of nuclear lysate per column is sufficient in most cases.</li>
		<li>Add 1x phosphatase inhibitor,&#160;1x protease inhibitor, and 1x binding enhancer (optional) and mix by flicking the tube several times. 
		Note: 100x binding enhancer consists of 750 mM MgCl2 and 300mM ZnCl2. Add binding enhancer if the binding of the TF to DNA depends on cofactors or reducing agents. If this information is not known, add the binding enhancer.</li>
		<li>Add 10 &#181;l of 5 &#181;M biotinylated capture DNA (50 pmol) to each respective binding mixture. Incubate for 20 min at room temperature. 
		Note: Incubation time and temperature may vary depending on the TF. The optimal values need to be determined experimentally.</li>
	</ol>
	</li>
	<li>Add 100 &#181;l of streptavidin microbeads. Incubate for 10 min at room temperature.</li>
	<li>For each oligo probe being tested, place a binding column in the magnetic separator. Place a microcentrifuge tube directly under each binding column and apply 100 &#181;l of binding buffer to rinse the column.</li>
	<li>Pipette the contents of each binding mixture into separate columns and allow the liquid to flow completely through the column into the microcentrifuge tube before proceeding. Make sure to label the columns with the variant oligo that was used in the binding mixture. Label the flow-through samples and replace with new microcentrifuge tubes to collect the low-stringency washes.</li>
	<li>Apply 100 &#181;l of low-stringency wash buffer to the column; wait until the column reservoir is empty. Repeat wash 4x. Label the low-stringency wash samples and replace with new microcentrifuge tubes to collect the high-stringency washes.</li>
	<li>Apply 100 &#181;l of high-stringency wash buffer to the column; wait until the column reservoir is empty. Repeat wash 4x. Label the high-stringency wash samples and replace with new microcentrifuge tubes to collect the pre-elution.</li>
	<li>Add 30 &#181;l of native elution buffer to the column and let stand for 5 min. Label the pre-elution samples and replace with new microcentrifuge tubes to collect the elution. 
	Note: This does not elute the bound protein; it washes the remaining high-stringency buffer out of the column and replaces it with elution buffer to maximize the efficiency of the elution.</li>
	<li>Add an additional 50 &#181;l native elution buffer to elute the bound TFs. For a higher yield but less concentrated eluate, add an additional 50 &#181;l of native elution buffer and collect the flow-through. 
	Note: Analyze elution samples through mass spectrometry to determine the identity of the bound TFs32. Afterwards, verify the proteomic results through sodium dodecyl sulfite polyacrylamide gel electrophoresis (SDS-PAGE) followed by a Western blot33. If mass spectrometry is not available, run a silver stain using standard technique instead of a Western blot to determine the size of the protein(s) showing genotype-dependent binding. Use this information to narrow down the list of predicted TFs from the computational approaches detailed in the introduction.</li>
</ol>

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R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Complex+roles+of+Stat1+in+regulating+gene+expression.">Complex roles of Stat1 in regulating gene expression.</a> Oncogene. 19 (21), 2619-2627 (2000).</li><li>Fillebeen, C., Wilkinson, N., Pantopoulos, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electrophoretic+Mobility+Shift+Assay+(EMSA)+for+the+Study+of+RNA-Protein+Interactions:+The+IRE/IRP+Example.">Electrophoretic Mobility Shift Assay (EMSA) for the Study of RNA-Protein Interactions: The IRE/IRP Example.</a> J. Vis. Exp. (94), e52230 (2014).</li><li>Heng, T. S., Painter, M. 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The authors have nothing to disclose.

Although advances in sequencing and genotyping technologies have greatly enhanced our capacity to identify genetic variants associated with disease, our ability to understand the functional mechanisms impacted by these variants is lagging. A major source of the problem is that many disease-associated variants are located in n on-coding regions of the genome, which likely affect harder-to-predict mechanisms controlling gene expression. Here, we present a protocol based on the EMSA and DAPA techniques, valuable molecular t...

Sequencing and genotyping based studies, including Genome-Wide Association Studies (GWAS), candidate locus studies, and deep-sequencing studies, have identified many genetic variants that are statistically associated with a disease, trait, or phenotype. Contrary to early predictions, most of these variants (85-93%) are located in non-coding regions and do not change the amino acid sequence of proteins1,2. Interpreting the function of these non-coding variants and determining the biological mechanisms connecting them to the associated disease, trait, or phenotype has proven challenging3-6. We have developed a general strategy to identify the molecular mechanisms that link variants to an important intermediate phenotype &#160;&#8211; gene expression. This pipeline is specifically designed to identify modulation of TF binding by genetic variants. This strategy combines computational approaches and molecular biology techniques aimed to predict biological effects of candidate variants in silico, and verify these predictions empirically (Figure 1).
<img alt="Figure 1" src="/files/ftp_upload/54093/54093fig1.jpg" /> 
Figure 1: Strategic approach for the analysis of non-coding genetic variants. Steps that are not included in the detailed protocol associated with this manuscript are shaded in grey. <a href="https://www.jove.com/files/ftp_upload/54093/54093fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In many cases, it is important to begin by expanding the list of variants to include all those in high linkage-disequilibrium (LD) with each statistically associated variant. LD is a measure of non-random association of alleles at two different chromosomal positions, which can be measured by the r2 statistic7. r2 is a measure of the linkage disequilibrium between two variants, with an r2 = 1 denoting perfect linkage between two variants. Alleles in high LD are found to co-segregate on the chromosome across ancestral populations. Current genotyping arrays do not include all known variants in the human genome. Instead, they exploit the LD within the human genome and include a subset of the known variants that act as proxies for other variants within a particular region of LD8. Thus, a variant without any biological consequence may be associated with a particular disease because it is in LD with the causal variant-the variant with a meaningful biological effect. Procedurally, it is recommended to convert the latest release of the 1,000 genomes project9 variant call files (vcf) into binary files compatible with PLINK10,11, an open-source tool for whole genome association analysis. Subsequently, all other genetic variants with LD r2 &#62;0.8 with each input genetic variant can be identified as candidates. It is important to use the appropriate reference population for this step- e.g., if a variant was identified in subjects of European ancestry, data from subjects of similar ancestry should be used for LD expansion.
LD expansion often results in dozens of candidate variants, and it is likely that only a small fraction of these contribute to disease mechanism. Often, it is infeasible to experimentally examine each of these variants individually. It is therefore useful to leverage the thousands of publically available functional genomic datasets as a filter to prioritize the variants. For example, the ENCODE consortium12 has performed thousands of ChIP-seq experiments describing the binding of TFs and co-factors, and histone marks in a wide range of contexts, along with chromatin accessibility data from technologies such as DNase-seq13, ATAC-seq14, and FAIRE-seq15. Databases and web servers such as the UCSC Genome Browser16, Roadmap Epigenomics17, Blueprint Epigenome18, Cistrome19, and ReMap20 provide free access to data produced by these and other experimental techniques across a wide range of cell types and conditions. When there are too many variants to examine experimentally, these data can be used to prioritize those located within likely regulatory regions in relevant cell and tissue types. Further, in cases where a variant is within a ChIP-seq peak for a specific protein, these data can provide potential leads as to the specific TF(s) or co-factors whose binding might be affecting.
Next, the resulting prioritized variants are screened experimentally to validate predicted genotype-dependent protein binding using EMSA21,22. EMSA measures the change in the migration of the oligo on a non-reducing TBE gel. Fluorescently labeled oligo is incubated with the nuclear lysate, and binding of nuclear factors will retard the movement of the oligo on the gel. In this manner, oligo that has bound more nuclear factors will present as a stronger fluorescent signal upon scanning. Notably, EMSA does not require predictions about the specific proteins whose binding will be affected.
Once variants are identified that are located within predicted regulatory regions and are capable of differentially binding nuclear factors, computational methods are employed to predict the specific TF(s) whose binding they might affect. We prefer to use CIS-BP23,24, RegulomeDB25, UniProbe26, and JASPAR27. Once candidate TFs are identified, these predictions can be specifically tested using antibodies against these TFs (EMSA-supershifts and DAPA-Westerns). An EMSA-supershift involves the addition of a TF-specific antibody to the nuclear lysate and oligo. A positive result in an EMSA-supershift is represented as a further shift in the EMSA band, or a loss of the band (reviewed in reference28). In the complementary DAPA, a 5&#39;-biotinylated oligo duplex containing the variant and the 20 base-pair flanking nucleotides are incubated with nuclear lysate from relevant cell type(s) to capture any nuclear factors specifically binding the oligos. The oligo duplex-nuclear factor complex is immobilized by streptavidin microbeads in a magnetic column. The bound nuclear factors are collected directly through elution29,48. Binding predictions can then be assessed by a Western blot using antibodies specific for the protein. In cases where there are no obvious predictions, or too many predictions, the elutions from variant pull-downs of the DAPA experiments can be sent to a proteomics core to identify candidate TFs using mass-spectrometry, which can subsequently be validated using these previously described methods.
In the remainder of the article, the detailed protocol for EMSA and DAPA analysis of genetic variants is provided.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Custom DNA Oligonucleotides</td>
			<td>Integrated DNA Technologies</td>
			<td></td>
			<td>http://www.idtdna.com/site/order/oligoentry</td>
		</tr>
		<tr>
			<td>Potassium Chloride</td>
			<td>Fisher Scientific</td>
			<td>BP366-500</td>
			<td>KCl, for CE buffer</td>
		</tr>
		<tr>
			<td>HEPES (1M)</td>
			<td>Fisher Scientific</td>
			<td>15630-080</td>
			<td>For CE and NE buffer</td>
		</tr>
		<tr>
			<td>EDTA (0.5M), pH 8.0</td>
			<td>Life Technologies</td>
			<td>R1021</td>
			<td>For CE, NE, and annealing buffer</td>
		</tr>
		<tr>
			<td>Sodium Chloride</td>
			<td>Fisher Scientific</td>
			<td>BP358-1</td>
			<td>NaCl, for NE buffer</td>
		</tr>
		<tr>
			<td>Tris-HCl (1M), pH 8.0</td>
			<td>Invitrogen</td>
			<td>BP1756-100</td>
			<td>For annealing buffer</td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (1X)</td>
			<td>Fisher Scientific</td>
			<td>MT21040CM</td>
			<td>PBS, for cell wash</td>
		</tr>
		<tr>
			<td>DL-Dithiothreitol solution (1M)</td>
			<td>Sigma</td>
			<td>646563</td>
			<td>Reducing agent</td>
		</tr>
		<tr>
			<td>PMSF</td>
			<td>Thermo Scientific</td>
			<td>36978</td>
			<td>Protease Inhibitor</td>
		</tr>
		<tr>
			<td>Phosphatase Inhibitor Cocktail&#160;</td>
			<td>Thermo Scientific</td>
			<td>78420</td>
			<td>Prevents dephosphorylation of TFs</td>
		</tr>
		<tr>
			<td>Nonidet P-40 Substitute</td>
			<td>IBI Scientific</td>
			<td>IB01140</td>
			<td>NP-40, for nuclear extraction</td>
		</tr>
		<tr>
			<td>BCA Protein Assay Kit</td>
			<td>Thermo Scientific</td>
			<td>23225</td>
			<td>For measuring protein concentration</td>
		</tr>
		<tr>
			<td>Odyssey EMSA Buffer Kit</td>
			<td>Licor</td>
			<td>829-07910</td>
			<td>Contains all necessary EMSA buffers</td>
		</tr>
		<tr>
			<td>TBE Gels, 6%, 12 Wells</td>
			<td>Invitrogen</td>
			<td>EC6265BOX</td>
			<td>For EMSA</td>
		</tr>
		<tr>
			<td>TBE Buffer (10X)</td>
			<td>Thermo Scientific</td>
			<td>B52</td>
			<td>For EMSA</td>
		</tr>
		<tr>
			<td>FactorFinder Starting Kit</td>
			<td>Miltenyi Biotec</td>
			<td>130-092-318</td>
			<td>Contains all necessary DAPA buffers</td>
		</tr>
		<tr>
			<td>Licor Odyssey CLx</td>
			<td>Licor</td>
			<td></td>
			<td>Recommended scanner for DAPA/EMSA</td>
		</tr>
		<tr>
			<td>Antibiotic-Antimycotic</td>
			<td>Gibco</td>
			<td>15240-062</td>
			<td>Contains 10,000 units/mL of penicillin, 10,000 &#181;g/mL of streptomycin, and 25 &#181;g/mL of Fungizone&#174; Antimycotic</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum</td>
			<td>Gibco</td>
			<td>26140-079</td>
			<td>FBS, for culture media</td>
		</tr>
		<tr>
			<td>RPMI 1640 Medium</td>
			<td>Gibco</td>
			<td>22400-071</td>
			<td>Contains L-glutamine and 25mM HEPES</td>
		</tr>
	</tbody>
</table>

screening for functional non-coding genetic variants using electrophoretic mobility shift assay (emsa) and dna-affinity precipitation assay (dapa)

Population and family-based genetic studies typically result in the identification of genetic variants that are statistically associated with a clinical disease or phenotype. For many diseases and traits, most variants are non-coding, and are thus likely to act by impacting subtle, comparatively hard to predict mechanisms controlling gene expression. Here, we describe a general strategic approach to prioritize non-coding variants, and screen them for their function. This approach involves computational prioritization using functional genomic databases followed by experimental analysis of differential binding of transcription factors (TFs) to risk and non-risk alleles. For both electrophoretic mobility shift assay (EMSA) and DNA affinity precipitation assay (DAPA) analysis of genetic variants, a synthetic DNA oligonucleotide (oligo) is used to identify factors in the nuclear lysate of disease or phenotype-relevant cells. For EMSA, the oligonucleotides with or without bound nuclear factors (often TFs) are analyzed by non-denaturing electrophoresis on a tris-borate-EDTA (TBE) polyacrylamide gel. For DAPA, the oligonucleotides are bound to a magnetic column and the nuclear factors that specifically bind the DNA sequence are eluted and analyzed through mass spectrometry or with a reducing sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) followed by Western blot analysis. This general approach can be widely used to study the function of non-coding genetic variants associated with any disease, trait, or phenotype.

In this section, representative results of what to expect are provided when performing an EMSA or DAPA, and the variability with regards to the quality of lysate is characterized. For example, it has been suggested that freezing and thawing protein samples multiple times may result in denaturation. In order to explore the reproducibility of EMSA analysis in the context of these &#34;freeze-thaw&#34; cycles, two 35 bp oligos differing at one genetic variant were incubated with a single bat...

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

We present a strategic plan and protocol for identifying non-coding genetic variants affecting transcription factor (TF) DNA binding. A detailed experimental protocol is provided for electrophoretic mobility shift assay (EMSA) and DNA affinity precipitation assay (DAPA) analysis of genotype-dependent TF DNA binding.

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Population and family-based genetic studies typically result in the identification of genetic variants that are statistically associated with a clinical ...

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12.9K Views.  Cincinnati Children's Hospital. We present a strategic plan and protocol for identifying non-coding genetic variants affecting transcription factor (TF) DNA binding. A detailed experimental protocol is provided for electrophoretic mobility shift assay (EMSA) and DNA affinity precipitation assay (DAPA) analysis of genotype-dependent TF DNA binding.

Video: Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Light/dark Transition Test for Mice

Although all of the mouse genome sequences have been determined, we do not yet know the functions of most of these genes. Gene-targeting techniques, however, can be used to delete or manipulate a specific gene in mice. The influence of a given gene on a specific behavior can then be determined by conducting behavioral analyses of the mutant mice. As a test for behavioral phenotyping of mutant mice, the light/dark transition test is one of the most widely used tests to measure anxiety-like behavior in mice. The test is based on the natural aversion of mice to brightly illuminated areas and on their spontaneous exploratory behavior in novel environments. The test is sensitive to anxiolytic drug treatment. The apparatus consists of a dark chamber and a brightly illuminated chamber. Mice are allowed to move freely between the two chambers. The number of entries into the bright chamber and the duration of time spent there are indices of bright-space anxiety in mice. To obtain phenotyping results of a strain of mutant mice that can be readily reproduced and compared with those of other mutants, the behavioral test methods should be as identical as possible between laboratories. The procedural differences that exist between laboratories, however, make it difficult to replicate or compare the results among laboratories. Here, we present our protocol for the light/dark transition test as a movie so that the details of the protocol can be demonstrated. In our laboratory, we have assessed more than 60 strains of mutant mice using the protocol shown in the movie. Those data will be disclosed as a part of a public database that we are now constructing.

Visualization of the protocol will facilitate understanding of the details of the entire experimental procedure, allowing for standardization of the protocols used across laboratories and comparisons of the behavioral phenotypes of various strains of mutant mice assessed using this test.

The light/dark transition test is one of the most widely used tests to measure anxiety-like behavior in mice. Here, we present a movie that shows detailed procedures on how we conduct the test.

Although all of the mouse genome sequences have been determined, we do not yet know the functions of most of these genes. Gene-targeting techniques, ...

Assay for Neural Induction in the Chick Embryo

The chick embryo is a valuable tool in the study of early embryonic development. Its transparency, accessibility and ease of manipulation, make it an ideal tool for studying the formation and initial patterning of the nervous system. This video demonstrates how to graft organizer tissue into a host, a method by which Hensen s node (the organizer in the chick embryo) is grafted to a host competent ectoderm. The organizer graft instructs overlying na ve tissue to adopt a neural fate via neural inducing signals. This mechanism is referred to as neural induction, and constitutes the initial step in the formation of brain and spinal cord in amniotes. This method is essentially used for the characterization of putative neural inducing molecules in chick. This video demonstrates the different steps in the assay for neural induction; First, the donnor embryo is explanted and pinned on a dish. Then, the host embryo is prepared for New culture. The graft is excised and transplanted to the host area pellucida margin. The host is cultured for 18-22 hrs. The assembly is fixed and processed for further applications (e.g. in situ hybridization). This method was originally devised by Waddington 1,2 and Gallera 3,4.

Neural induction is the first step in the formation of the brain. It is a mechanism by which Hensen's node (organizer), instructs adjacent tissue to adopt a neural fate, i.e. to give rise to the nervous system. This video demonstrates an assay for neural induction in chick embryo.

The chick embryo is a valuable tool in the study of early embryonic development. Its transparency, accessibility and ease of manipulation, make it an ...

Elevated Plus Maze for Mice

Although the mouse genome is now completely sequenced, the functions of most of the genes expressed in the brain are not known. The influence of a given gene on a specific behavior can be determined by behavioral analysis of mutant mice. If a target gene is expressed in the brain, behavioral phenotype of the mutant mice could elucidate the genetic mechanism of normal behaviors. The elevated plus maze test is one of the most widely used tests for measuring anxiety-like behavior. The test is based on the natural aversion of mice for open and elevated areas, as well as on their natural spontaneous exploratory behavior in novel environments. The apparatus consists of open arms and closed arms, crossed in the middle perpendicularly to each other, and a center area. Mice are given access to all of the arms and are allowed to move freely between them. The number of entries into the open arms and the time spent in the open arms are used as indices of open space-induced anxiety in mice. Unfortunately, the procedural differences that exist between laboratories make it difficult to duplicate and compare results among laboratories. Here, we present a detailed movie demonstrating our protocol for the elevated plus maze test. In our laboratory, we have assessed more than 90 strains of mutant mice using the protocol shown in the movie. These data will be disclosed as a part of a public database that we are now constructing.
Visualization of the protocol will promote better understanding of the details of the entire experimental procedure, allowing for standardization of the protocols used in different laboratories and comparisons of the behavioral phenotypes of various strains of mutant mice assessed using this test. 


The elevated plus maze test is one of the most widely used tests for measuring anxiety-like behavior in mice. Here, we present a movie showing the detailed procedures for conducting the test.

Although the mouse genome is now completely sequenced, the functions of most of the genes expressed in the brain are not known. The influence of a given ...

Dissection of Hippocampal Dentate Gyrus from Adult Mouse

The hippocampus is one of the most widely studied areas in the brain because of its important functional role in memory processing and learning, its remarkable neuronal cell plasticity, and its involvement in epilepsy, neurodegenerative diseases, and psychiatric disorders. The hippocampus is composed of distinct regions; the dentate gyrus, which comprises mainly granule neurons, and Ammon's horn, which comprises mainly pyramidal neurons, and the two regions are connected by both anatomic and functional circuits. Many different mRNAs and proteins are selectively expressed in the dentate gyrus, and the dentate gyrus is a site of adult neurogenesis; that is, new neurons are continually generated in the adult dentate gyrus. To investigate mRNA and protein expression specific to the dentate gyrus, laser capture microdissection is often used. This method has some limitations, however, such as the need for special apparatuses and complicated handling procedures. In this video-recorded protocol, we demonstrate a dissection technique for removing the dentate gyrus from adult mouse under a stereomicroscope. Dentate gyrus samples prepared using this technique are suitable for any assay, including transcriptomic, proteomic, and cell biology analyses. We confirmed that the dissected tissue is dentate gyrus by conducting real-time PCR of dentate gyrus-specific genes, tryptophan 2,3-dioxygenase (TDO2) and desmoplakin (Dsp), and Ammon's horn enriched genes, Meis-related gene 1b (Mrg1b) and TYRO3 protein tyrosine kinase 3 (Tyro3). The mRNA expressions of TDO2 and Dsp in the dentate gyrus samples were detected at obviously higher levels, whereas Mrg1b and Tyro3 were lower levels, than those in the Ammon's horn samples. To demonstrate the advantage of this method, we performed DNA microarray analysis using samples of whole hippocampus and dentate gyrus. The mRNA expression of TDO2 and Dsp, which are expressed selectively in the dentate gyrus, in the whole hippocampus of alpha-CaMKII+/- mice, exhibited 0.037 and 0.10-fold changes compared to that of wild-type mice, respectively. In the isolated dentate gyrus, however, these expressions exhibited 0.011 and 0.021-fold changes compared to that of wild-type mice, demonstrating that gene expression changes in dentate gyrus can be detected with greater sensitivity. Taken together, this convenient and accurate dissection technique can be reliably used for studies focused on the dentate gyrus.

A dissection technique for removal of the dentate gyrus from adult mouse under a stereomicroscope was demonstrated in this video-recorded protocol.

The hippocampus is one of the most widely studied areas in the brain because of its important functional role in memory processing and learning, its ...

Crystallizing Membrane Proteins for Structure Determination using Lipidic Mesophases

A detailed protocol for crystallizing membrane proteins by using lipidic mesophases is described. This method has variously been referred to as the lipidic cubic phase or in meso method. The method has been shown to be quite versatile in that it has been used to solve X-ray crystallographic structures of prokaryotic and eukaryotic proteins, proteins that are monomeric, homo- and hetero-multimeric, chromophore-containing and chromophore-free, and alpha-helical and beta-barrel proteins. Recent successes using in meso crystallization are the human engineered beta2-adrenergic and adenosine A2a G protein-coupled receptors. Protocols are presented for reconstituting the membrane protein into the monoolein-based mesophase, and for setting up crystallizations in the manual mode. Additional steps in the overall process, such as crystal harvesting, are to be addressed in future video articles. The time required to prepare the protein-loaded mesophase and to set up a crystallization plate manually is about one hour.

Herein is described the procedure implemented in the Caffrey Membrane Structural and Functional Biology Group to set up manually crystallization trials of membrane proteins in lipidic mesophases.

A detailed protocol for crystallizing membrane proteins by using lipidic mesophases is described. This method has variously been referred to as the ...

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

The number of significant genetic associations with common complex traits is constantly increasing. However, most of these associations have not been understood at molecular level. One of the mechanisms mediating the effect of DNA variants on phenotypes is gene expression, which has been shown to be particularly relevant for complex traits1.
This method tests in a cellular context the effect of specific DNA sequences on gene expression. The principle is to measure the relative abundance of transcripts arising from the two alleles of a gene, analysing cells which carry one copy of the DNA sequences associated with disease (the risk variants)2,3. Therefore, the cells used for this method should meet two fundamental genotypic requirements: they have to be heterozygous both for DNA risk variants and for DNA markers, typically coding polymorphisms, which can distinguish transcripts based on their chromosomal origin (Figure 1). DNA risk variants and DNA markers do not need to have the same allele frequency but the phase (haplotypic) relationship of the genetic markers needs to be understood. It is also important to choose cell types which express the gene of interest. This protocol refers specifically to the procedure adopted to extract nucleic acids from fibroblasts but the method is equally applicable to other cells types including primary cells.
DNA and RNA are extracted from the selected cell lines and cDNA is generated. DNA and cDNA are analysed with a primer extension assay, designed to target the coding DNA markers4. The primer extension assay is carried out using the MassARRAY (Sequenom)5 platform according to the manufacturer's specifications. Primer extension products are then analysed by matrix-assisted laser desorption/ionization time of-flight mass spectrometry (MALDI-TOF/MS). Because the selected markers are heterozygous they will generate two peaks on the MS profiles. The area of each peak is proportional to the transcript abundance and can be measured with a function of the MassARRAY Typer software to generate an allelic ratio (allele 1: allele 2) calculation. The allelic ratio obtained for cDNA is normalized using that measured from genomic DNA, where the allelic ratio is expected to be 1:1 to correct for technical artifacts. Markers with a normalised allelic ratio significantly different to 1 indicate that the amount of transcript generated from the two chromosomes in the same cell is different, suggesting that the DNA variants associated with the phenotype have an effect on gene expression. Experimental controls should be used to confirm the results.

Genetic associations often remain unexplained at a functional level. This method aims to assess the effect of phenotype-associated genetic markers on gene expression by analyzing cells heterozygous for transcribed SNPs. The technology allows accurate measurement by MALDI-TOF mass spectrometry to quantify allele-specific primer extension products.

The number of significant genetic associations with common complex traits is constantly increasing. However, most of these associations have not been ...

A Fluorescent Screening Assay for Identifying Modulators of GIRK Channels

G protein-gated inward rectifier K+ (GIRK) channels function as cellular mediators of a wide range of hormones and neurotransmitters and are expressed in the brain, heart, skeletal muscle and endocrine tissue1,2. GIRK channels become activated following the binding of ligands (neurotransmitters, hormones, drugs, etc.) to their plasma membrane-bound, G protein-coupled receptors (GPCRs). This binding causes the stimulation of G proteins (Gi and Go) which subsequently bind to and activate the GIRK channel. Once opened the GIRK channel allows the movement of K+ out of the cell causing the resting membrane potential to become more negative. As a consequence, GIRK channel activation in neurons decreases spontaneous action potential formation and inhibits the release of excitatory neurotransmitters. In the heart, activation of the GIRK channel inhibits pacemaker activity thereby slowing the heart rate.
GIRK channels represent novel targets for the development of new therapeutic agents for the treatment neuropathic pain, drug addiction, cardiac arrhythmias and other disorders3. However, the pharmacology of these channels remains largely unexplored. Although a number of drugs including anti-arrhythmic agents, antipsychotic drugs and antidepressants block the GIRK channel, this inhibition is not selective and occurs at relatively high drug concentrations3.
Here, we describe a real-time screening assay for identifying new modulators of GIRK channels. In this assay, neuronal AtT20 cells, expressing GIRK channels, are loaded with membrane potential-sensitive fluorescent dyes such as bis-(1,3-dibutylbarbituric acid) trimethine oxonol [DiBAC4(3)] or HLB 021-152 (Figure 1). The dye molecules become strongly fluorescent following uptake into the cells (Figure 1). Treatment of the cells with GPCR ligands stimulates the GIRK channels to open. The resulting K+ efflux out of the cell causes the membrane potential to become more negative and the fluorescent signal to decrease (Figure 1). Thus, drugs that modulate K+ efflux through the GIRK channel can be assayed using a fluorescent plate reader. Unlike other ion channel screening assays, such atomic absorption spectrometry4 or radiotracer analysis5, the GIRK channel fluorescent assay provides a fast, real-time and inexpensive screening procedure.

A real-time screening procedure for identifying drugs that interact with G protein-gated inward rectifier K+ (GIRK) channels is described. The assay utilizes membrane potential-sensitive fluorescent dyes to measure GIRK channel activity. This technique is adaptable for use on a number of cell lines.

G protein-gated inward rectifier K+ (GIRK) channels function as cellular mediators of a wide range of hormones and neurotransmitters and are expressed in ...

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10.
Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Systematic, large-scale synthetic genetic (gene-gene or epistasis) interaction screens can be used to explore genetic redundancy and pathway cross-talk. Here, we describe a high-throughput quantitative synthetic genetic array screening technology, termed eSGA that we developed for elucidating epistatic relationships and exploring genetic interaction networks in Escherichia coli.

Phenotypes  are determined by a complex series of physical (e.g. protein-protein) and  functional (e.g. gene-gene or genetic) interactions (GI)1. While ...

High-throughput Functional Screening using a Homemade Dual-glow Luciferase Assay

We present a rapid and inexpensive high-throughput screening protocol to identify transcriptional regulators of alpha-synuclein, a gene associated with Parkinson&#39;s disease. 293T cells are transiently transfected with plasmids from an arrayed ORF expression library, together with luciferase reporter plasmids, in a one-gene-per-well microplate format. Firefly luciferase activity is assayed after 48 hr to determine the effects of each library gene upon alpha-synuclein transcription, normalized to expression from an internal control construct (a hCMV promoter directing Renilla luciferase). This protocol is facilitated by a bench-top robot enclosed in a biosafety cabinet, which performs aseptic liquid handling in 96-well format. Our automated transfection protocol is readily adaptable to high-throughput lentiviral library production or other functional screening protocols requiring triple-transfections of large numbers of unique library plasmids in conjunction with a common set of helper plasmids. We also present an inexpensive and validated alternative to commercially-available, dual luciferase reagents which employs PTC124, EDTA, and pyrophosphate to suppress firefly luciferase activity prior to measurement of Renilla luciferase. Using these methods, we screened 7,670 human genes and identified 68 regulators of alpha-synuclein. This protocol is easily modifiable to target other genes of interest.

We present a rapid and inexpensive screening method for identifying transcriptional regulators using high-throughput robotic transfections and a homemade dual-glow luciferase assay. This protocol rapidly generates direct side-by-side functional data for thousands of genes and is easily modifiable to target any gene of interest.

We present a rapid and inexpensive high-throughput screening protocol to identify transcriptional regulators of alpha-synuclein, a gene associated with ...

Electrophoretic Mobility Shift Assay (EMSA) for the Study of RNA-Protein Interactions: The IRE/IRP Example

RNA/protein interactions are critical for post-transcriptional regulatory pathways. Among the best-characterized cytosolic RNA-binding proteins are iron regulatory proteins, IRP1 and IRP2. They bind to iron responsive elements (IREs) within the untranslated regions (UTRs) of several target mRNAs, thereby controlling the mRNAs translation or stability. IRE/IRP interactions have been widely studied by EMSA. Here, we describe the EMSA protocol for analyzing the IRE-binding activity of IRP1 and IRP2, which can be generalized to assess the activity of other RNA-binding proteins as well. A crude protein lysate containing an RNA-binding protein, or a purified preparation of this protein, is incubated with an excess of32 P-labeled RNA probe, allowing for complex formation. Heparin is added to preclude non-specific protein to probe binding. Subsequently, the mixture is analyzed by non-denaturing electrophoresis on a polyacrylamide gel. The free probe migrates fast, while the RNA/protein complex exhibits retarded mobility; hence, the procedure is also called &#8220;gel retardation&#8221; or &#8220;bandshift&#8221; assay. After completion of the electrophoresis, the gel is dried and RNA/protein complexes, as well as free probe, are detected by autoradiography. The overall goal of the protocol is to detect and quantify IRE/IRP and other RNA/protein interactions. Moreover, EMSA can also be used to determine specificity, binding affinity, and stoichiometry of the RNA/protein interaction under investigation.

Electrophoretic Mobility Shift Assay EMSA for the Study of RNA-Protein Interactions: The IRE/IRP Example

Here we present a protocol to analyze RNA/protein interactions. The electrophoretic mobility shift assay (EMSA) is based on the differential migration of RNA/protein complexes and free RNA during native gel electrophoresis. By using a radiolabeled RNA probe, RNA/protein complexes can be visualized by autoradiography.

RNA/protein interactions are critical for post-transcriptional regulatory pathways. Among the best-characterized cytosolic RNA-binding proteins are iron ...