Ringraziamo i membri del laboratorio di Wan e il laboratorio di Nagarajan per le discussioni informative. N.Nagarajan è supportato da finanziamenti da A * STAR. Y.Wan è sostenuto da finanziamenti da A * STAR e dalla Società in borsa Science-Branco Weiss.

<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>

Gli autori non hanno interessi finanziari concorrenti.

Qui descriviamo in dettaglio il flusso di lavoro sperimentale e computazionale per SPLASH, un metodo che ci permette di identificare le interazioni RNA a due mani in modo genico-wide. Abbiamo utilizzato con successo SPLASH nelle colture batteriche, lieviti e umane e anticipo che la strategia possa essere ampiamente applicata a organismi diversi in diversi stati cellulari. Uno dei passaggi critici del protocollo è quello di iniziare con almeno 20 μg di RNA reticolato per avere materiale adeguato per i processi a valle....

Studiare come macromolecole si piegano e interagiscono tra loro è la chiave per comprendere la regolazione del gene nella cellula. Mentre molti sforzi sono stati focalizzati nell&#39;ultimo decennio per comprendere come il DNA e le proteine ​​contribuiscono alla regolazione del gene, è relativamente meno noto circa la regolazione post-trascrizionale dell&#39;espressione genica. L&#39;RNA trasporta informazioni sia nella sequenza lineare che nella struttura secondaria e terziaria 1 . La sua capacità di fondare la coppia con se stessa e con gli altri è importante per la sua funzione in vivo . I progressi recenti nel sondaggio della struttura secondaria RNA a elevata produttività hanno fornito preziosi approfondimenti sulle posizioni delle regioni a doppia e singola banda nel transcriptoma 2 , 3 , 4 , 5 , 6 , 7 , 8 , howeVer le informazioni sui partner di interazione di coppia sono ancora in gran parte mancanti. Per determinare quale sequenza RNA interagisce con un&#39;altra regione RNA nel trascrittoma, abbiamo bisogno di informazioni globali a livello di coppia. La mappatura delle interazioni RNA in coppia in maniera globale e imparziale è stata tradizionalmente una grande sfida. Mentre gli approcci precedenti, come CLASH 9 , hiCLIP 10 e RAP 11 , vengono utilizzati per identificare le interazioni RNA in modo scalare, queste tecniche tipicamente mappano l&#39;accoppiamento base di RNA per un sottoinsieme di RNA che interagiscono con una particolare specie di proteine ​​o RNA. Gli sviluppi recenti nello studio delle interazioni globali di RNA includono il metodo RPL 12 , che non stabilizza le interazioni RNA in vivo e quindi può solo catturare un sottoinsieme di interazioni in vivo . Per superare queste sfide, noi e gli altri abbiamo sviluppato strategie prive di genoma e maestoseP interazioni di RNA in vivo , utilizzando versioni modificate del psoralen 13 , 14 , 15 del reticolatore. In questo protocollo, descriviamo i dettagli per eseguire l&#39;equilibrio di S di P soralen incrociato, L igato e S eligibriti (SPLASH), che utilizza il psoralene biotinilato in RNA in accoppiamento a base di collegamento in vivo in seguito alla legatura di prossimità e ad alta sequenza di throughput a Individuare i partner RNA base-pairing in tutto il genoma ( Figura 1 ) 15 . In questo manoscritto descriviamo i passaggi per eseguire SPLASH utilizzando cellule aderenti colte, in questo caso le cellule HeLa. Lo stesso protocollo può essere facilmente adattato alle cellule di mammiferi di sospensione e alle cellule di lievito e batteri. In breve, le cellule HeLa vengono trattate con psoralene biotinilato e irradiati a 365 nm per incrociare in coppia le coppie di RNA interattive in vivo. I RNA vengono quindi estratti dalle cellule, frammentati e arricchiti per le regioni di reticolazione usando perline di streptavidina. I frammenti RNA interattivi vengono quindi legati insieme usando la legatura di prossimità e fatti in una libreria di cDNA per la sequenza profonda. Al sequenziamento, gli RNA chimerici vengono mappati sul transcriptome / genoma per identificare le regioni interagenti RNA che sono accoppiate tra loro. Abbiamo utilizzato con successo SPLASH per identificare migliaia di interazioni RNA in vivo in lieviti e diverse cellule umane, tra cui l&#39;accoppiamento base di RNA intramolecolare e intermolecolare in diverse classi di RNA, come snoRNA, lncRNA e mRNA, per intravedere nell&#39;organizzazione strutturale e nei modelli di interazione Di RNA nella cella.

<table border="0" cellpadding="0" cellspacing="0" width="1136">
	<colgroup>
		<col />
		<col span="3" />
	</colgroup>
	<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

Sapere come i RNA interagiscono con se stessi e con gli altri è fondamentale per capire la regolazione del gene basato su RNA nella cellula. Mentre esempi di interazioni RNA-RNA come le interazioni di microRNA-mRNA sono state dimostrate per regolare l&#39;espressione genica, l&#39;intero grado in cui si verificano interazioni RNA nella cella è ancora sconosciuto. I metodi precedenti per studiare le interazioni di RNA si sono concentrati principalmente su subsets di RNA che interagiscono con una particolare proteina o specie di RNA. Qui, abbiamo dettagliato un metodo denominato S equencing di P soralen crosslinked, L igated, e S eletti H ybrids (SPLASH) che consente la cattura genoma di interazioni RNA in vivo in modo imparziale. SPLASH utilizza la reticolazione in vivo , la legatura di prossimità e il sequenziamento ad alta velocità per identificare partner globalmente associati alla base di RNA intramolecolare e intermolecolare. SPLASH può essere applicato a diversi organismi, compresi batteri, lieviti e cellule umane, nonché aS diverse condizioni cellulari per facilitare la comprensione della dinamica dell&#39;organizzazione di RNA in diversi contesti cellulari. L&#39;intero protocollo sperimentale SPLASH richiede circa 5 giorni per completare e il flusso di lavoro computazionale richiede circa 7 giorni per completare.

La figura 1 rappresenta lo schema del flusso di lavoro SPLASH. Dopo l&#39;aggiunta di psoralene biotinilato in presenza di 0,01% di digitonina e di reticolazione UV, viene estratto un totale di RNA dalle cellule e viene eseguita una macchia di punti per assicurare che il collegamento a biotinilato con l&#39;RNA sia accaduto in modo efficace ( Figura 2 ). Utilizziamo oligosini biotinilati 20 come controlli positivi per titolare l...

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

Qui, abbiamo dettagliato il metodo di equilibrio di P soralen crosslinked, L igated e S elected H ybrids (SPLASH), che consente mapping a livello genomico delle interazioni RNA-RNA intramolecolari e intermolecolari in vivo . SPLASH può essere applicato per studiare interagenti RNA di organismi compresi lieviti, batteri e umani.

Mappatura delle interazioni RNA-RNA globalmente utilizzando Psoralen biotinilato

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 ...

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

Research

JoVE Journal

Genetics

11.9K Views.  A*STAR.  Qui, abbiamo dettagliato il metodo di equilibrio di P soralen crosslinked, L igated e S elected H ybrids (SPLASH), che consente mapping a livello genomico delle interazioni RNA-RNA intramolecolari e intermolecolari in vivo . SPLASH può essere applicato per studiare interagenti RNA di organismi compresi lieviti, batteri e umani. 

Video: Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

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.

Coniugazione saggi di accoppiamento per l&#39;analisi specifica per sequenza di proteine ​​di trasferimento relativi coniugazione batterica

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

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Genetica

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 e modifica CRISPR / Cas9 per identificare un gene di resistenza alla droga in<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.

Singolo Analisi Molecola di laser localizzati psoraleni addotti

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.

Mappatura di interazioni proteine-DNA con ChEC-seq nel gene-wide<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.

Scansione retrovirale: Mappatura dei siti di integrazione MLV per definire regioni regolatori specifiche per le 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.

Mappatura del genoma della cromatina accessibile in linfociti T umani primari da ATAC-Seq

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

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.

DNA regulatory elements, such as enhancers, control gene expression by physically contacting target gene promoters, often through long-range chromosomal interactions spanning large genomic distances. Promoter Capture Hi-C (PCHi-C) identifies significant interactions between promoters and distal regions, enabling the assignment of potential regulatory sequences to their target genes.

Promotore cattura Ciao-c: Ad alta risoluzione, Genome-wide profilatura delle interazioni del promotore

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the ...

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.

Un metodo veloce e quantitativo per la modificazione post-traduzionale e variante attivato Mapping dei peptidi di genomi

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.

Trascrizione Inizio mapping del sito utilizzando vettore-CAGE di input super-basso

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.

Analisi biochimiche in Vitro che utilizzano etichette di biotina per studiare le interazioni proteina-nucleica dell'acido

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