Name: mapping rna-rna interactions globally using biotinylated psoralen
Uploaded: 2017-05-24T13:00:00
Description: Watch this Scientific Journal Video about Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen at JoVE.com

Nous remercions les membres du laboratoire Wan et du laboratoire Nagarajan pour des discussions informatives. N. Nagarajan est soutenu par un financement de A * STAR. Y.Wan est soutenu par le financement de A * STAR et Society in Science-Branco Weiss Fellowship.

1. Traitement des cellules HeLa avec extraction du psoralène biotinylé et de l&#39;ARN <ol><li> Culture Les cellules HeLa dans le milieu d&#39;Eagle modifié par Dulbecco (DMEM) complétées par 10% de sérum bovin fœtal (FBS) et 1% de streptomycine pénicilline (PS) dans une plaque de 10 cm. </li><li> Lavez les cellules HeLa deux fois avec 5 mL de 1x PBS. Égoutter l&#39;excès de PBS complètement du plat en plaçant le plat verticalement pendant 1 min. </li><li> Ajouter 1 ml de PBS contenant 200 uM de psoralène...

<ol>
	<li>Wan, Y., Kertesz, M., Spitale, R. C., Segal, E., Chang, H. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Understanding+the+transcriptome+through+RNA+structure.">Understanding the transcriptome through RNA structure.</a> Nat.Rev.Genet. 12 (9), 641-655 (2011).</li><li>Kertesz, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+measurement+of+RNA+secondary+structure+in+yeast.">Genome-wide measurement of RNA secondary structure in yeast.</a> Nature. 467 (7311), 103-107 (2010).</li><li>Wan, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+Measurement+of+RNA+Folding+Energies.">Genome-wide Measurement of RNA Folding Energies.</a> Mol.Cell. 48 (2), 169-181 (2012).</li><li>Wan, Y., Qu, K., Ouyang, Z., Chang, H. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+mapping+of+RNA+structure+using+nuclease+digestion+and+high-throughput+sequencing.">Genome-wide mapping of RNA structure using nuclease digestion and high-throughput sequencing.</a> Nat.Protoc. 8 (5), 849-869 (2013).</li><li>Wan, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Landscape+and+variation+of+RNA+secondary+structure+across+the+human+transcriptome.">Landscape and variation of RNA secondary structure across the human transcriptome.</a> Nature. 505 (7485), 706-709 (2014).</li><li>Spitale, R. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structural+imprints+in+vivo+decode+RNA+regulatory+mechanisms.">Structural imprints in vivo decode RNA regulatory mechanisms.</a> Nature. 519 (7544), 486-490 (2015).</li><li>Ding, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+genome-wide+profiling+of+RNA+secondary+structure+reveals+novel+regulatory+features.">In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features.</a> Nature. 505 (7485), 696-700 (2014).</li><li>Rouskin, S., Zubradt, M., Washietl, S., Kellis, M., Weissman, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+probing+of+RNA+structure+reveals+active+unfolding+of+mRNA+structures+in+vivo.">Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo.</a> Nature. 505 (7485), 701-705 (2014).</li><li>Kudla, G., Granneman, S., Hahn, D., Beggs, J. D., Tollervey, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cross-linking,+ligation,+and+sequencing+of+hybrids+reveals+RNA-RNA+interactions+in+yeast.">Cross-linking, ligation, and sequencing of hybrids reveals RNA-RNA interactions in yeast.</a> Proc.Natl.Acad.Sci.U.S.A. 108 (24), 10010-10015 (2011).</li><li>Sugimoto, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=hiCLIP+reveals+the+in+vivo+atlas+of+mRNA+secondary+structures+recognized+by+Staufen+1.">hiCLIP reveals the in vivo atlas of mRNA secondary structures recognized by Staufen 1.</a> Nature. 519 (7544), 491-494 (2015).</li><li>Engreitz, J. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-RNA+interactions+enable+specific+targeting+of+noncoding+RNAs+to+nascent+Pre-mRNAs+and+chromatin+sites.">RNA-RNA interactions enable specific targeting of noncoding RNAs to nascent Pre-mRNAs and chromatin sites.</a> Cell. 159 (1), 188-199 (2014).</li><li>Ramani, V., Qiu, R., Shendure, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+determination+of+RNA+structure+by+proximity+ligation.">High-throughput determination of RNA structure by proximity ligation.</a> Nat.Biotechnol. , (2015).</li><li>Lu, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA+Duplex+Map+in+Living+Cells+Reveals+Higher-Order+Transcriptome+Structure.">RNA Duplex Map in Living Cells Reveals Higher-Order Transcriptome Structure.</a> Cell. 165 (5), 1267-1279 (2016).</li><li>Sharma, E., Sterne-Weiler, T., O'Hanlon, D., Blencowe, B. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+Mapping+of+Human+RNA-RNA+Interactions.">Global Mapping of Human RNA-RNA Interactions.</a> Mol.Cell. 62 (4), 618-626 (2016).</li><li>Aw, J. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+Vivo+Mapping+of+Eukaryotic+RNA+Interactomes+Reveals+Principles+of+Higher-Order+Organization+and+Regulation.">In Vivo Mapping of Eukaryotic RNA Interactomes Reveals Principles of Higher-Order Organization and Regulation.</a> Mol.Cell. 62 (4), 603-617 (2016).</li></ol>

Ici, nous décrivons en détail le flux de travail expérimental et informatique pour SPLASH, une méthode qui nous permet d&#39;identifier les interactions ARN en paire d&#39;une manière généreuse. Nous avons utilisé avec succès SPLASH dans les cultures bactériennes, de levure et humaines et prévoyons que la stratégie peut être largement appliquée à divers organismes sous différents états cellulaires. L&#39;une des étapes critiques du protocole consiste à commencer par au moins 20 μg d&#39;ARN réticul?...

Étudier comment les macromolécules se plient et interagissent entre elles est la clé pour comprendre la régulation des gènes dans la cellule. Bien que de nombreux efforts aient été concentrés au cours de la dernière décennie pour comprendre comment l&#39;ADN et les protéines contribuent à la régulation des gènes, on connaît relativement moins de la régulation post-transcriptionnelle de l&#39;expression des gènes. L&#39;ARN porte des informations à la fois dans sa séquence linéaire et dans sa structure secondaire et tertiaire 1 . Sa capacité à baser la paire avec elle-même et avec d&#39;autres est importante pour sa fonction in vivo . Les progrès récents dans la sondage de la structure secondaire de l&#39;ARN à haut débit ont fourni des informations précieuses sur les emplacements des régions à double et simple brin dans le transcriptome 2 , 3 , 4 , 5 , 6 , 7 , 8 , HoweLes informations sur les partenaires d&#39;interaction d&#39;appariement manquent encore. Pour déterminer quelle séquence d&#39;ARN interagit avec une autre région d&#39;ARN dans le transcriptome, nous avons besoin d&#39;informations globales en paire. La cartographie par paire d&#39;interactions ARN d&#39;une manière globale et impartiale a traditionnellement été un défi majeur. Alors que les approches antérieures, telles que CLASH 9 , hiCLIP 10 et RAP 11 , sont utilisées pour identifier les interactions de l&#39;ARN à grande échelle, ces techniques classent généralement l&#39;association de base d&#39;ARN pour un sous-ensemble d&#39;ARN qui interagissent avec une protéine particulière ou des espèces d&#39;ARN. Les développements récents dans l&#39;étude des interactions globales de l&#39;ARN comprennent la méthode RPL 12 , qui ne stabilise pas les interactions de l&#39;ARN in vivo et ne peut donc capturer qu&#39;un sous-ensemble d&#39;interactions in vivo . Pour surmonter ces défis, nous et d&#39;autres avons développé des stratégies à l&#39;échelle du génome et impartiales à maP ARNA interagère in vivo , en utilisant des versions modifiées du réticulant psoralen 13 , 14 , 15 . Dans ce protocole, nous décrivons les détails pour effectuer l&#39;équation de S de P soralen réticulé, L igated et S élués (SPLASH), qui utilise du psoralène biotinylé pour reticuler l&#39;association des ARN in vivo , suivie d&#39;une ligature de proximité et d&#39;un séquençage à haut débit pour Identifiez les partenaires de base de l&#39;ARN au niveau du génome ( Figure 1 ) 15 . Dans ce manuscrit, nous décrivons les étapes pour effectuer SPLASH à l&#39;aide de cellules adhérentes cultivées, dans ce cas, des cellules HeLa. Le même protocole peut être facilement adapté aux cellules de mammifères en suspension et aux cellules de levure et de bactéries. En bref, les cellules HeLa sont traitées avec du psoralène biotinylé et irradiées à 365 nm pour paires de bases d&#39;ARN interactives par liaison croisée in vivo. Les ARN sont ensuite extraits des cellules, fragmentés et enrichis pour les régions de réticulation en utilisant des billes de streptavidine. Les fragments d&#39;ARN interagissant sont ensuite ligaturés ensemble en utilisant une ligature de proximité et transformés en une banque d&#39;ADNc pour un séquençage profond. Lors du séquençage, les ARN chimériques sont mappés sur le transcriptome / génome pour identifier les régions qui interagissent avec l&#39;ARN qui sont couplées l&#39;une à l&#39;autre. Nous avons utilisé SPLASH avec succès pour identifier des milliers d&#39;interactions d&#39;ARN in vivo dans la levure et différentes cellules humaines, y compris le couplage intramoléculaire et intermoleculaire de base d&#39;ARN dans diverses classes d&#39;ARN, tels que snoRNAs, lncRNAs et mRNAs, pour apercevoir l&#39;organisation structurelle et les modèles d&#39;interaction Des ARN dans la cellule.

<table border="0" cellpadding="0" cellspacing="0" width="1136">
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		<col />
		<col span="3" />
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	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:284px;">1 Kb Plus DNA Ladder</td>
			<td style="width:284px;">Life Technologies Holdings Pte Ltd</td>
			<td style="width:284px;">10787026</td>
			<td style="width:284px;">DNA ladder</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">10 bp DNA ladder</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>10821-015</td>
			<td>DNA ladder</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">20 % SDS solution</td>
			<td>First BASE</td>
			<td>BUF-2052-1L&#160;&#160;</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">20x SSC</td>
			<td>First BASE</td>
			<td>BUF-3050-20X1L</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">3.0 M Sodium Acetate Solution</td>
			<td>First BASE</td>
			<td>BUF-1151-1L-pH5.2&#160;&#160;</td>
			<td>Required for nucleic acid precipitation</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">40% Acrylamide/Bis Solution, 19:1</td>
			<td>Bio-Rad</td>
			<td>1610145</td>
			<td>TBE Urea gel component</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ambion Buffer Kit</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>AM9010</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ammonium Persulfate, Molecular Grade&#160;&#160;</td>
			<td>Promega</td>
			<td>V3131&#160;</td>
			<td>TBE Urea gel component</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Bromophenol Blue</td>
			<td>Sigma-Aldrich</td>
			<td>B0126-25G</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Chloroform</td>
			<td>Merck</td>
			<td>1.02445.1000</td>
			<td>RNA extraction</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Single strand DNA ligase</td>
			<td>Epicentre</td>
			<td>CL9025K</td>
			<td>CircLigase II ssDNA Ligase</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Centrifuge tube filters</td>
			<td>Sigma-Aldrich</td>
			<td>CLS8160-96EA</td>
			<td>Costar Spin-X centrifuge tube filters</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">D5628-1G DIGITONIN CRYSTALLINE</td>
			<td>Sigma-Aldrich</td>
			<td>D5628-1G</td>
			<td>For cell treatment</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Dark Reader Transilluminator&#160;</td>
			<td>Clare Chemical Research</td>
			<td>Dark Reader DR89X Transilluminator</td>
			<td>Blue light transilluminator</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DNA Gel Loading Dye (6X)</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>R0611</td>
			<td>Required for agarose gel electroporation</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Dulbecco&#39;s Modified Eagle Medium</td>
			<td>Pan BioTech</td>
			<td>P04-03500</td>
			<td>For Hela cell culture</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Streptavidin magnetic beads</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>65002</td>
			<td>Dynabeads MyOne Streptavidin C1&#160;</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Magnetic stand for 15ml tubes</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>12301D</td>
			<td>DynaMag-15</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Magnetic stand for 15ml tubes</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>&#160;12321D</td>
			<td>DynaMag-2</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">ThermoMixer</td>
			<td>Eppendorf</td>
			<td>5382 000.015</td>
			<td>Eppendorf ThermoMixer&#160;C</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Biotinylated psoralen</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>29986</td>
			<td>EZ-Link Psoralen-PEG3-Biotin</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">F8T5/BL&#160;</td>
			<td>Hitachi</td>
			<td>F8T5/BL&#160;</td>
			<td>365 nm UV bulb</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Fetal Bovine Serum</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>10270106&#160;&#160;</td>
			<td>Components of Hela medium</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Formamide</td>
			<td>Promega</td>
			<td>H5052&#160;&#160;</td>
			<td>Component in hybridization buffer</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">G8T5</td>
			<td>Sankyo-Denki</td>
			<td>G8T5</td>
			<td>254 nm UV bulb</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Glycogen&#160;</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>10814010</td>
			<td>Required for nucleic acid precipitation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Nanodrop</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>Nanodrop 2000</td>
			<td>Spectrophotometer for nucleic acidquantification</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nuclease free water&#160;</td>
			<td>First BASE</td>
			<td>BUF-1180-500ml&#160;&#160;</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Penicillin Streptomycin&#160;&#160;</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>15140122&#160;&#160;</td>
			<td>Components of Hela medium</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">High-Fidelity DNA polymerase (2x)</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>F531L&#160;</td>
			<td>Phusion High-Fidelity PCR Master Mix with HF Buffer (2x)</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Primers Set 1</td>
			<td>New England Biolabs</td>
			<td>E7335L&#160;</td>
			<td>PCR primers</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DNA Gel Extraction Kit</td>
			<td>QIAgen</td>
			<td>28106</td>
			<td>QIAquick Gel Extraction Kit</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Fluorometric Quantification kit</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>Q32854</td>
			<td>Qubit dsDNA HS Assay Kit</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">RNA clean up kit</td>
			<td>Qiagen</td>
			<td>74106</td>
			<td>RNeasy Mini Kit Silica-membrane column</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Rnase Inhibitor</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>AM2696</td>
			<td>SUPERase In</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Reverse transcriptase</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>18080400</td>
			<td>SuperScript III First-Strand Synthesis SuperMix</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nucleic Acid Gel Stain</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>S11494</td>
			<td>SYBR GOLD NUCLEIC ACID 500 UL</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">T4 Polynucleotide Kinase</td>
			<td>New England Biolabs</td>
			<td>M0201L</td>
			<td>End repair enzyme</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">T4 RNA Ligase 1</td>
			<td>New England Biolabs</td>
			<td>M0204L</td>
			<td>Enzyme for proximity ligation</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">T4 RNA Ligase 2, truncated KQ</td>
			<td>New England Biolabs</td>
			<td>M0373L</td>
			<td>Enzyme for adaptor ligation</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Temed</td>
			<td>Bio-Rad</td>
			<td>1610801</td>
			<td>TBE Urea gel component</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Guanidinium thiocyanate-phenol-chloroform</td>
			<td>Life Technologies Holdings Pte Ltd</td>
			<td>15596018</td>
			<td>TRIzol&#174; Reagent for RNA extraction</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Urea</td>
			<td>First BASE</td>
			<td>BIO-2070-5kg&#160;&#160;</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">UV crosslinker</td>
			<td>Stratagene</td>
			<td>400072</td>
			<td>UV Stratalinker 1800</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">UV Transilluminator</td>
			<td>UVP</td>
			<td>95-0417-01</td>
			<td>For visualizing of bands</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Xylene Cyanol FF</td>
			<td>Sigma-Aldrich</td>
			<td>X4126-10G</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DNA cleanup it</td>
			<td>Zymo Research&#160;</td>
			<td>D4004</td>
			<td>Zymo DNA concentrator-5&#160;</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">List of software required</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">FastQC software</td>
			<td>0.11.4</td>
			<td>http://www.bioinformatics.babraham.ac.uk/projects/fastqc/</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SeqPrep software</td>
			<td>1.0.7</td>
			<td>https://github.com/jstjohn/SeqPrep</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BWA software</td>
			<td>0.7.12</td>
			<td>http://bio-bwa.sourceforge.net/</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SAMTOOLS software</td>
			<td>1.2.1</td>
			<td>http://www.htslib.org/</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PULLSEQ software</td>
			<td>1.0.2</td>
			<td>https://github.com/bcthomas/pullseq</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">STAR software</td>
			<td>2.5.0c</td>
			<td>https://github.com/alexdobin/STAR</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">rem_dups.py PYTHON script</td>
			<td>PYTHON 2.7.11</td>
			<td>https://github.com/CSB5/splash/tree/master/src</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">find_chimeras.py PYTHON script</td>
			<td>PYTHON 2.7.11</td>
			<td>https://github.com/CSB5/splash/tree/master/src</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">pickJunctionReads.awk AWK script</td>
			<td>AWK GNU 4.1.2</td>
			<td>https://github.com/CSB5/splash/tree/master/src</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Buffer composition</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Elution buffer:&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">0.3 M sodium acetate</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Lysis Buffer:</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">50 mM Tris-Cl pH 7.0</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">10 mM EDTA</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">1% SDS</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Always add Superase-in fresh before use except when washing beads</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Proteinase K Buffer&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">100 mM NaCl</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">10 mM TrisCl pH 7.0</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">1 mM EDTA</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">0.5% SDS</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Hybridization Buffer</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">750 mM NaCl</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">1% SDS</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">50 mM Tris-Cl pH 7.0</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">1 mM EDTA</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">15% formamide (store in the dark at 4 &#176;C)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Always add Superase-in fresh before use</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">2x SSC Wash Buffer</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">2x NaCl and Sodium citrate (SSC) (diluted from 20x SSC Invitrogen stock)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">0.5% SDS</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">2X RNA fragmentation buffer</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">18mM MgCl2</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">450mM KCl</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">300mM Tris-CL pH 8.3</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">2x RNA loading Dye:</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">95% Formamide</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">0.02% SDS</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">0.02% bromophenol blue</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">0.01% Xylene Cyanol</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">1mM EDTA&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">3&#39; RNA adapter sequence</td>
			<td>5rAppCTGTAGGCACCATCAAT/3ddC</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">RT primer sequence</td>
			<td>AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGC/iSp18/CACTCA/iSp18/TTCAGACGTGTGCTCTTCCGATCTATTGATGGTGCCTACAG</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

mapping rna-rna interactions globally using biotinylated psoralen

Savoir comment les ARN interagissent avec eux-mêmes et avec d&#39;autres sont essentiels à la compréhension de la régulation des gènes basée sur l&#39;ARN dans la cellule. Bien que des exemples d&#39;interactions ARN-ARN telles que les interactions entre ARNm et ARNm aient montré qu&#39;ils régulent l&#39;expression des gènes, la mesure dans laquelle les interactions ARN se produisent dans la cellule est encore inconnue. Les méthodes antérieures pour étudier les interactions de l&#39;ARN ont principalement porté sur des sous-groupes d&#39;ARN qui interagissent avec une protéine particulière ou des espèces d&#39;ARN. Ici, nous détaillons une méthode appelée S équation de P soralen réticulé, L igated et S élués (SPLASH) qui permettent une capture intégrale des interactions de l&#39;ARN dans le génome in vivo de manière impartiale. SPLASH utilise une réticulation in vivo , une ligature de proximité et un séquençage à haut débit pour identifier globalement les partenaires intramoléculaires et intermoleculaires de base d&#39;ARN. SPLASH peut être appliqué à différents organismes, y compris des bactéries, des levures et des cellules humaines, ainsi qu&#39;uneDes conditions cellulaires diverses pour faciliter la compréhension de la dynamique de l&#39;organisation de l&#39;ARN dans divers contextes cellulaires. L&#39;ensemble du protocole SPLASH expérimental prend environ 5 jours pour être complété et le flux de travail informatique prend environ 7 jours pour être complété.

La figure 1 représente le schéma du flux de travail SPLASH. Lors de l&#39;addition de psoralène biotinylé en présence de 0,01% de digitonine et de réticulation UV, l&#39;ARN total est extrait des cellules et un point-tache est réalisé pour s&#39;assurer que la réticulation du biotinylé à l&#39;ARN s&#39;est produite efficacement ( figure 2 ). Nous utilisons des oligos biotinylés de 20 bases comme témoins positifs po...

Watch this Scientific Journal Video about Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen at JoVE.com

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

Ici, nous détaillons la méthode de l&#39;équation de S de P soralen réticulé, L igated et S élués (SPLASH), ce qui permet une cartographie génomique des interactions intra-moléculaires et intermoleculaires d&#39;ARN-ARN in vivo . SPLASH peut être appliqué pour étudier les interactions de l&#39;ARN des organismes, y compris la levure, les bactéries et les humains.

Cartographie des interactions ARN-ARN à l&#39;échelle mondiale à l&#39;aide de psoralène biotinylé

Knowing how RNAs interact with themselves and with others is key to understanding RNA based gene regulation in the cell. While examples of RNA-RNA ...

The overall goal of this video is to describe the method for sequencing of psoralen crosslinked ligated and selected hybrids or SPLASH in which pair-wise in vivo RNA-RNA interactions are mapped in a genome-wide manner. This technique is a simple, high throughput method for mapping the RNA interaction in vivo. This method can help answer key questions in the RNA genomics field such as how do different regions along a single strand of RNA or between different strands of RNAs interact with each other.Though this method can provide insights into yeast and human cells, it can also be applied to studies in other modern organisms including bacteria and membrane in cells. We first had the idea for this method when we wanted to come up with a way to map interaction molecular. Note that the following procedure contains several stopping points.At these times, the experiment can be paused briefly or indefinitely. Details can be found in the accompanying text. Begin this procedure by washing HeLa cells twice with five milliliters of PBS.Place the dish vertically for one minute to completely drain any excess PBS. Next, add one milliliter of PBS containing 200 micromolar biotinylated psoralen and 0.01%digitonin which increases cell permeability. Take care to add the solution evenly over the surface of the cells.Incubate at 37 degrees Celsius for five minutes. Following the incubation, remove the lid of the dish and place it on ice inside a UV Crosslinker three centimeters from the UV bulb. Irradiate with 365 nanometer UV for 20 minutes.After 20 minutes, remove the dish from the Crosslinker and then isolate fragment and precipitate the RNA from HeLa cells according to the instructions in the accompanying document. Load denatured ladder and RNA samples onto a 8.6 centimeter square 6%TBE-urea gel. Size fractionate by electrophoresis at 180 volts for 40 minutes.Stain the gel in 10 milliliters of TBE buffer containing a 1:10, 000 dilution of nucleic acid gel stain for five minutes in the dark. While the gel is staining, use a 24 gauge needle to puncture a clean 0.6 milliliter microfuge tube at the bottom. Place it in a two milliliter microfuge tube.Using a transilluminator, visualize the bands on the post-stained gel and cut a gel slice corresponding to 90 to 110 nucleotides. Transfer the gel slice into the punctured 0.6 milliliter microfuge tube in the two milliliter microfuge tube. Size selection allows us to set the minimal length for the chimeric fragments and to distinguish between ligated products and non-ligated products later on.Centrifuge the gel slices at 12, 000 times g at room temperature for two minutes to shred the gel slice and collect it in the two milliliter microfuge tube. After the spin, discard the empty 0.6 milliliter microfuge tube. To the shredded gel slice, add 700 microliters of elution buffer.Incubate at four degrees Celsius overnight with constant rotation to allow diffusion of the samples into the buffer. Transfer the gel slices and the elution buffer to a centrifuge tube filter and centrifuge at 20, 000 times g for 20 minutes. After the spin, the gel slices will be trapped at the top compartment of the filter which may be discarded.Precipitate and quantify the RNA as described in the accompanying document. Flash freeze and store the RNA at minus 80 degrees Celsius in liquid nitrogen until it is used. To enrich RNA crosslinking regions, begin by adding 100 microliters of lysis buffer containing RNase inhibitor to wash streptavidin-coated magnetic beads in a microfuge tube.To a 15 milliliter conical centrifuge tube, add two milliliters of freshly-prepared hybridization buffer, one milliliter of supplemented lysis buffer, 1.5 micrograms of size fractionated RNA, and 100 microliters of resuspended beads. Vortex the tube gently. Incubate at 37 degrees Celsius for 30 minutes with end-to-end rotation.Following the incubation, wash the beads five times with pre-warmed wash buffer. At the end of the fifth wash, place the microfuge tube containing the beads on the magnet stand for one minute and then remove the wash buffer. Add one milliliter of cold T4 polynucleotide kinase buffer to the washed beads.Incubate the beads for five minutes at four degrees Celsius with end-to-end rotation. Place the microfuge tube containing the beads on the magnetic strip. After one minute, gently remove the buffer.Repeat this step for a total of two washes and remove the buffer after the last wash. Next, follow the instructions in the accompanying document to convert the five prime and three prime ends to be ligation compatible and perform the proximity ligation. After a wash, add 100 microliters of RNA PK buffer to the beads and resuspend them by pipetting up and down.Heat the samples at 95 degrees Celsius for 10 minutes on a heat block. Next, chill the sample on ice for one minute. Add 500 microliters of guanidinium thiocyanate-phenol-chloroform to the sample.Mix by vortexing vigorously for 10 seconds. Incubate the mixture at room temperature for 10 minutes. Following the incubation, use a kit to precipitate, clean up, and recover the RNA, ensure that even small RNAs are retained.Elute the RNA in 100 microliters of nuclease-free water. Transfer 100 microliters of the eluted samples into a well of a 24-well plate on nice. Keeping the sample on ice, UV irradiate it at 254 nanometers for five minutes.Transfer the reverse crosslinked sample to a clean microfuge tube. Add 10 microliters of sodium acetate, one microliter of glycogen, and 300 microliters of 100%ethanol. Precipitate the RNA at minus 20 degrees Celsius for at least one hour.To recover the RNA, centrifuge the precipitated RNA at 20, 000 times g for 30 minutes at four degrees Celsius. After the spin, remove the supernatant and add one milliliter of 70%cold ethanol to wash the RNA pellet. Centrifuge the washed pellet at 20, 000 times g for 15 minutes at four degrees Celsius.Remove the wash buffer and add 4.25 microliters of nuclease-free water to resuspend the RNA. Transfer the RNA to a 0.2 milliliter PCR tube. Finally, reverse transcribe, circularize, and amplify the cDNA according to the instructions in the accompanying document.This schematic depicts the SPLASH workflow. Upon the addition of biotinylated psoralen in the presence of 0.01%digitonin and UV crosslinking, total RNA is extracted from the cells and a dot blot is performed to ensure that crosslinking was efficient. Biotinylated 20 base oligos are then used as positive controls to titrate the amount of biotinylated psoralen to be added to the cells such that approximately one in every 150 bases are crosslinked.Small-scale PCR amplification is then performed using increasing numbers of PCR cycles to determine the minium number of cycles required for deep sequencing. In an efficient library preparation process, a cDNA sequencing library can be amplified from a 1.5 microgram of size selected RNA input in less than 15 cycles of PCR amplification. The library is then sequenced using two 150 base pair reads on a high throughout sequencing machine.The sequencing reads are then processed according to the computational pipeline. The end result is a list of filtered chimeric interactions that includes both intramolecular and intermolecular RNA-RNA interactions in the transcriptome. While attempting this procedure, it is important to remember to check for biotinylated psoralen incorporation when using SPLASH on new organisms.After its development, this technique paved the way for researchers in the field of RNA biology to explore RNA interactions in diverse organisms. After watching this video, you should have a good understanding of how to make a sequencing library that captures pair-wise RNA interactions globally in the cell.

mapping-rna-rna-interactions-globally-using-biotinylated-psoralen

Research

JoVE Journal

Genetics

Conjugative Mating Assays for Sequence-specific Analysis of Transfer Proteins Involved in Bacterial Conjugation

The transfer of genetic material by bacterial conjugation is a process that takes place via complexes formed by specific transfer proteins. In Escherichia coli, these transfer proteins make up a DNA transfer machinery known as the mating pair formation, or DNA transfer complex, which facilitates conjugative plasmid transfer. The objective of this paper is to provide a method that can be used to determine the role of a specific transfer protein that is involved in conjugation using a series of deletions and/or point mutations in combination with mating assays. The target gene is knocked out on the conjugative plasmid and is then provided in trans through the use of a small recovery plasmid harboring the target gene. Mutations affecting the target gene on the recovery plasmid can reveal information about functional aspects of the target protein that result in the alteration of mating efficiency of donor cells harboring the mutated gene. Alterations in mating efficiency provide insight into the role and importance of the particular transfer protein, or a region therein, in facilitating conjugative DNA transfer. Coupling this mating assay with detailed three-dimensional structural studies will provide a comprehensive understanding of the function of the conjugative transfer protein as well as provide a means for identifying and characterizing regions of protein-protein interaction.

Here, we present a protocol to knockout a gene of interest involved in plasmid conjugation and subsequently analyze the impact of its absence using mating assays. The function of the gene is further explored to a specific region of its sequence using deletion or point mutations.

Conjugatif Mating Assays pour l&#39;analyse des protéines de transfert impliqués dans Conjugaison bactérienne spécifique à la séquence

The transfer of genetic material by bacterial conjugation is a process that takes place via complexes formed by specific transfer proteins. In Escherichia ...

Recherche

Génétique

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites.

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Details are presented on how QTL mapping with a whole genome sequence based genetic map can be used to identify a drug resistance gene in Toxoplasma gondii and how this can be verified with the CRISPR/Cas9 system that efficiently edits a genomic target, in this case the drug resistance gene.

Mapping QTL et édition CRISPR / Cas9 pour identifier un gène de résistance aux médicaments<em&gt; Toxoplasma gondii</em

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the ...

Single Molecule Analysis of Laser Localized Psoralen Adducts

The DNA Damage Response (DDR) has been extensively characterized in studies of double strand breaks (DSBs) induced by laser micro beam irradiation in live cells. The DDR to helix distorting covalent DNA modifications, including interstrand DNA crosslinks (ICLs), is not as well defined. We have studied the DDR stimulated by ICLs, localized by laser photoactivation of immunotagged psoralens, in the nuclei of live cells. In order to address fundamental questions about adduct distribution and replication fork encounters, we combined laser localization with two other technologies. DNA fibers are often used to display the progress of replication forks by immunofluorescence of nucleoside analogues incorporated during short pulses. Immunoquantum dots have been widely employed for single molecule imaging. In the new approach, DNA fibers from cells carrying laser localized ICLs are spread onto microscope slides. The tagged ICLs are displayed with immunoquantum dots and the inter-lesion distances determined. Replication fork collisions with ICLs can be visualized and different encounter patterns identified and quantitated.

Lasers are frequently used in studies of the cellular response to DNA damage. However, they generate lesions whose spacing, frequency, and collisions with replication forks are rarely characterized. Here, we describe an approach that enables the determination of these parameters with laser localized interstrand crosslinks.

Analyse des molécule laser Localisés psoralène adduits

The DNA Damage Response (DDR) has been extensively characterized in studies of double strand breaks (DSBs) induced by laser micro beam irradiation in live ...

Genome-wide Mapping of Protein-DNA Interactions with ChEC-seq in Saccharomyces cerevisiae

Genome-wide mapping of protein-DNA interactions is critical for understanding gene regulation, chromatin remodeling, and other chromatin-resident processes. Formaldehyde crosslinking followed by chromatin immunoprecipitation and high-throughput sequencing (X-ChIP-seq) has been used to gain many valuable insights into genome biology. However, X-ChIP-seq has notable limitations linked to crosslinking and sonication. Native ChIP avoids these drawbacks by omitting crosslinking, but often results in poor recovery of chromatin-bound proteins. In addition, all ChIP-based methods are subject to antibody quality considerations. Enzymatic methods for mapping protein-DNA interactions, which involve fusion of a protein of interest to a DNA-modifying enzyme, have also been used to map protein-DNA interactions. We recently combined one such method, chromatin endogenous cleavage (ChEC), with high-throughput sequencing as ChEC-seq. ChEC-seq relies on fusion of a chromatin-associated protein of interest to micrococcal nuclease (MNase) to generate targeted DNA cleavage in the presence of calcium in living cells. ChEC-seq is not based on immunoprecipitation and so circumvents potential concerns with crosslinking, sonication, chromatin solubilization, and antibody quality while providing high resolution mapping with minimal background signal. We envision that ChEC-seq will be a powerful counterpart to ChIP, providing an independent means by which to both validate ChIP-seq findings and discover new insights into genomic regulation.

Genome-wide Mapping of Protein-DNA Interactions with ChEC-seq in Saccharomyces cerevisiae

We describe chromatin endogenous cleavage coupled with high-throughput sequencing (ChEC-seq), a chromatin immunoprecipitation (ChIP)-orthogonal method for mapping protein binding sites genome-wide with micrococcal nuclease (MNase) fusion proteins.

Cartographie génomique des interactions protéine-ADN avec ChEC-seq in<em&gt; Saccharomyces cerevisiae</em

Genome-wide mapping of protein-DNA interactions is critical for understanding gene regulation, chromatin remodeling, and other chromatin-resident ...

Retroviral Scanning: Mapping MLV Integration Sites to Define Cell-specific Regulatory Regions

Moloney murine leukemia (MLV) virus-based retroviral vectors integrate predominantly in acetylated enhancers and promoters. For this reason, mLV integration sites can be used as functional markers of active regulatory elements. Here, we present a retroviral scanning tool, which allows the genome-wide identification of cell-specific enhancers and promoters. Briefly, the target cell population is transduced with an mLV-derived vector and genomic DNA is digested with a frequently cutting restriction enzyme. After ligation of genomic fragments with a compatible DNA linker, linker-mediated polymerase chain reaction (LM-PCR) allows the amplification of the virus-host genome junctions. Massive sequencing of the amplicons is used to define the mLV integration profile genome-wide. Finally, clusters of recurrent integrations are defined to identify cell-specific regulatory regions, responsible for the activation of cell-type specific transcriptional programs.
The retroviral scanning tool allows the genome-wide identification of cell-specific promoters and enhancers in prospectively isolated target cell populations. Notably, retroviral scanning represents an instrumental technique for the retrospective identification of rare populations (e.g. somatic stem cells) that lack robust markers for prospective isolation.

Here, we describe a protocol for genome-wide mapping of the integration sites of Moloney murine leukemia virus-based retroviral vectors in human cells.

Numérisation Retroviral: Mapping des sites d&#39;intégration MLV pour définir des régions réglementaires spécifiques à une cellule

Moloney murine leukemia (MLV) virus-based retroviral vectors integrate predominantly in acetylated enhancers and promoters. For this reason, mLV ...

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions of chromatin. These regions represent regulatory DNA elements (e.g., promoters, enhancers, locus control regions, insulators) to which transcription factors bind. Mapping the accessible chromatin landscape is a powerful approach for uncovering active regulatory elements across the genome. This information serves as an unbiased approach for discovering the network of relevant transcription factors and mechanisms of chromatin structure that govern gene expression programs. ATAC-seq is a robust and sensitive alternative to DNase I hypersensitivity analysis coupled with next-generation sequencing (DNase-seq) and formaldehyde-assisted isolation of regulatory elements (FAIRE-seq) for genome-wide analysis of chromatin accessibility and to the sequencing of micrococcal nuclease-sensitive sites (MNase-seq) to determine nucleosome positioning. We present a detailed ATAC-seq protocol optimized for human primary immune cells i.e. CD4+ lymphocytes (T helper 1 (Th1) and Th2 cells). This comprehensive protocol begins with cell harvest, then describes the molecular procedure of chromatin tagmentation, sample preparation for next-generation sequencing, and also includes methods and considerations for the computational analyses used to interpret the results. Moreover, to save time and money, we introduced quality control measures to assess the ATAC-seq library prior to sequencing. Importantly, the principles presented in this protocol allow its adaptation to other human immune and non-immune primary cells and cell lines. These guidelines will also be useful for laboratories which are not proficient with next-generation sequencing methods.

Assay for Transposase-Accessible Chromatin coupled with high-throughput sequencing (ATAC-seq) is a genome-wide method to uncover accessible chromatin. This is a step-by-step ATAC-seq protocol, from molecular to the final computational analysis, optimized for human lymphocytes (Th1/Th2). This protocol can be adopted by researchers without prior experience in next-generation sequencing methods.

Cartographie de tout le génome de chromatine Accessible dans les Lymphocytes T humains primaires par ATAC-Seq

Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions ...

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Cross-talk between genes, transcripts, and proteins is the key to cellular responses; hence, analysis of molecular levels as distinct entities is slowly being extended to integrative studies to enhance the understanding of molecular dynamics within cells. Current tools for the visualization and integration of proteomics with other omics datasets are inadequate for large-scale studies. Furthermore, they only capture basic sequence identify, discarding post-translational modifications and quantitation. To address these issues, we developed PoGo to map peptides with associated post-translational modifications and quantification to reference genome annotation. In addition, the tool was developed to enable the mapping of peptides identified from customized sequence databases incorporating single amino acid variants. While PoGo is a command line tool, the graphical interface PoGoGUI enables non-bioinformatics researchers to easily map peptides to 25 species supported by Ensembl genome annotation. The generated output borrows file formats from the genomics field and, therefore, visualization is supported in most genome browsers. For large-scale studies, PoGo is supported by TrackHubGenerator to create web-accessible repositories of data mapped to genomes that also enable an easy sharing of proteogenomics data. With little effort, this tool can map millions of peptides to reference genomes within only a few minutes, outperforming other available sequence-identity based tools. This protocol demonstrates the best approaches for proteogenomics mapping through PoGo with publicly available datasets of quantitative and phosphoproteomics, as well as large-scale studies.

Here we present the proteogenomic tool PoGo and protocols for fast, quantitative, post-translational modification and variant enabled mapping of peptides identified through mass spectrometry onto reference genomes. This tool is of use to integrate and visualize proteogenomic and personal proteomic studies interfacing with orthogonal genomics data.

Une méthode rapide et Quantitative pour Modification post-traductionnelle et variante compatible cartographie des Peptides aux génomes

Cross-talk between genes, transcripts, and proteins is the key to cellular responses; hence, analysis of molecular levels as distinct entities is slowly ...

Transcription Start Site Mapping Using Super-low Input Carrier-CAGE

Cap analysis of gene expression (CAGE) is a method used for single-nucleotide resolution detection of RNA polymerase II transcription start sites (TSSs). Accurate detection of TSSs enhances identification and discovery of core promoters. In addition, active enhancers can be detected through signatures of bidirectional transcription initiation. Described here is a protocol for performing super-low input carrier-CAGE (SLIC-CAGE). This SLIC adaptation of the CAGE protocol minimizes RNA losses by artificially increasing the RNA amount through use of an in vitro transcribed RNA carrier mix that is added to the sample of interest, thus enabling library preparation from nanogram-amounts of total RNA (i.e., thousands of cells). The carrier mimics the expected DNA library fragment length distribution, thereby eliminating biases that could be caused by the abundance of a homogenous carrier. In the last stages of the protocol, the carrier is removed through degradation with homing endonucleases and the target library is amplified. The target sample library is protected from degradation, as the homing endonuclease recognition sites are long (between 18 and 27 bp), making the probability of their existence in the eukaryotic genomes very low. The end result is a DNA library ready for next-generation sequencing. All steps in the protocol, up to sequencing, can be completed within 6 days. The carrier preparation requires a full working day; however, it can be prepared in large quantities and kept frozen at -80 &#176;C. Once sequenced, the reads can be processed to obtain genome-wide single-nucleotide resolution TSSs. TSSs can be used for core promoter or enhancer discovery, providing insight into gene regulation. Once aggregated to promoters, the data can also be used for 5&#8217;-centric expression profiling.

Cap Analysis of Gene Expression (CAGE) is a method for genome-wide quantitative mapping of mRNA 5&#8217;ends to capture RNA polymerase II transcription start sites at a single-nucleotide resolution. This work describes a low-input (SLIC-CAGE) protocol for generation of high-quality libraries using nanogram-amounts of total RNA.

Cartographie du site de démarrage de la transcription à l'aide d'un transporteur-CAGE super-faible

Cap analysis of gene expression (CAGE) is a method used for single-nucleotide resolution detection of RNA polymerase II transcription start sites (TSSs). ...

In Vitro Biochemical Assays using Biotin Labels to Study Protein-Nucleic Acid Interactions

Protein-nucleic acid interactions play important roles in biological processes such as transcription, recombination, and RNA metabolism. Experimental methods to study protein-nucleic acid interactions require the use of fluorescent tags, radioactive isotopes, or other labels to detect and analyze specific target molecules. Biotin, a non-radioactive nucleic acid label, is commonly used in electrophoretic mobility shift assays (EMSA) but has not been regularly employed to monitor protein activity during nucleic acid processes. This protocol illustrates the utility of biotin labeling during in vitro enzymatic reactions, demonstrating that this label works well with a range of different biochemical assays. Specifically, in alignment with previous findings using radioisotope 32P-labeled substrates, it is confirmed via biotin-labeled EMSA that MEIOB (a protein specifically involved in the meiotic recombination) is a DNA-binding protein, that MOV10 (an RNA helicase) resolves biotin-labeled RNA duplex structures, and that MEIOB cleaves biotin-labeled single-stranded DNA. This study demonstrates that biotin is capable of substituting 32P in various nucleic acid-related biochemical assays in vitro.&#160;

Presented here are protocols for in vitro biochemical assays using biotin labels that may be widely&#160;applicable for studying protein-nucleic acid interactions.

In Vitro Biochemical Assays using Biotin Labels to Study Protein-Nucleic Acid Interactions In Vitro Biochemical Assays using Biotin Labels to Study Protein-Nucleic Acid Interactions In Vitro Biochemical As

Protein-nucleic acid interactions play important roles in biological processes such as transcription, recombination, and RNA metabolism. Experimental ...

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis

A central goal of modern genetics is to understand how and why organisms in the wild differ in phenotype. To date, the field has advanced largely on the strength of linkage and association mapping methods, which trace the relationship between DNA sequence variants and phenotype across recombinant progeny from matings between individuals of a species. These approaches, although powerful, are not well suited to trait differences between reproductively isolated species. Here we describe a new method for genome-wide dissection of natural trait variation that can be readily applied to incompatible species. Our strategy, RH-seq, is a genome-wide implementation of the reciprocal hemizygote test. We harnessed it to identify the genes responsible for the striking high temperature growth of the yeast Saccharomyces cerevisiae relative to its sister species S. paradoxus. RH-seq utilizes transposon mutagenesis to create a pool of reciprocal hemizygotes, which are then tracked through a high-temperature competition via high-throughput sequencing. Our RH-seq workflow as laid out here provides a rigorous, unbiased way to dissect ancient, complex traits in the budding yeast clade, with the caveat that resource-intensive deep sequencing is needed to ensure genomic coverage for genetic mapping. As sequencing costs drop, this approach holds great promise for future use across eukaryotes.

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis

Reciprocal hemizygosity via sequencing (RH-seq) is a powerful new method to map the genetic basis of a trait difference between species. Pools of hemizygotes are generated by transposon mutagenesis and their fitness is tracked through competitive growth using high-throughout sequencing. Analysis of the resulting data pinpoints genes underlying the trait.

Cartographie génétique des différences de thermotolérance entre les espèces de levure saccharomyces via Genome-Wide Reciprocal Hemizygosity Analysis

A central goal of modern genetics is to understand how and why organisms in the wild differ in phenotype. To date, the field has advanced largely on the ...