Wan 연구원과 Nagarajan 연구원에게 유익한 토론에 감사드립니다. N.Nagarajan은 A * STAR의 자금 지원을받습니다. Y.Wan은 A * STAR 및 Society in Science-Branco Weiss Fellowship의 지원을받습니다.

<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. 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저자는 경쟁적인 금전적 이해 관계가 없습니다.

여기서 우리는 게놈 전체에서 pair-wise RNA 상호 작용을 확인하는 방법 인 SPLASH의 실험 및 계산 워크 플로우에 대해 자세히 설명합니다. 우리는 박테리아, 효모 및 인간 문화에서 SPLASH를 성공적으로 활용했으며 전략이 다양한 세포 상태에서 다양한 유기체에 광범위하게 적용될 수있을 것으로 기대합니다. 프로토콜의 중요한 단계 중 하나는 하류 공정에 적합한 물질을 가지기 위해 적어도 20 μg의 가?...

거대 분자들이 서로 어떻게 접히고 상호 작용하는지 연구하는 것은 세포에서의 유전자 조절을 이해하는 열쇠입니다. 지난 수십 년간 DNA와 단백질이 유전자 조절에 어떻게 기여하는지에 대한 많은 노력이 집중되어 왔지만, 유전자 발현의 전사 후 조절에 관해서는 알려진 바가 상대적으로 적다. RNA는 선형 서열과 2 차 및 3 차 구조 모두에서 정보를 전달한다. 생체 내에서 자신과 다른 사람과 쌍을 이루는 능력이 중요합니다. 고 처리량 RNA 2 차 구조 탐색에서의 최근의 진보는 트랜스 크립 풋 2 , 3 , 4 , 5 , 6 , 7 , 8 , howe에서 이중 및 단일 가닥 영역의 위치에 대한 가치있는 통찰을 제공했다페어링 상호 작용 파트너에 대한 ver 정보가 아직 많이 누락되었습니다. transcriptome에서 어떤 RNA 서열이 다른 RNA 영역과 상호 작용 하는지를 결정하기 위해, 우리는 전구 쌍방향 정보가 필요합니다. 쌍방향의 RNA 상호 작용을 전지구하고 공평하지 않은 방식으로 매핑하는 것은 전통적으로 중요한 과제였습니다. CLASH 9 , hiCLIP 10 및 RAP 11 과 같은 이전의 접근법은 대규모 방식으로 RNA 상호 작용을 확인하는 데 사용되지만 이러한 기술은 일반적으로 특정 단백질 또는 RNA 종과 상호 작용하는 RNA의 하위 집합에 대해 RNA 염기쌍을 매핑합니다. 세계적 RNA 상호 작용을 연구하는 최근의 연구에는 생체 내에서 RNA 상호 작용 을 안정화시키지 않는 생체 내 상호 작용의 부분 집합 만 포착 할 수있는 RPL 12 방법이 포함된다. 이러한 어려움을 극복하기 위해 우리와 다른 사람들은 게놈 전반에 걸친 공평한 전략을 개발하여p RNA interactomes 를 in vivo 에서 사용하여 crosslinker psoralen 13 , 14 , 15 의 변형 된 버전을 사용했습니다. 이 프로토콜에서는 생체 내에서 염기쌍 결합 RNA를 가교 결합시킨 비 오티 닐화 된 소 랄렌을 사용하여 근접 결합 및 높은 처리량 시퀀싱을 수행 한 P soralen crosslinked, Ligated 및 Sided H ybrids (SPLASH)의 S equencing을 수행하기위한 세부 사항을 설명합니다. 게놈 전체 RNA base-pairing 파트너를 확인하십시오 ( 그림 1 ). 이 원고에서 배양 된 접착 세포,이 경우에는 HeLa 세포를 사용하여 SPLASH를 수행하는 단계를 설명합니다. 동일한 프로토콜은 포유 동물 현탁액 및 효모 및 박테리아 세포에 쉽게 적용될 수 있습니다. 간략하게, HeLa 세포를 바이오 티 닐화 된 소 랄렌으로 처리하고 생체 내에서 상호 작용하는 RNA 염기 쌍을 가교 결합시키기 위해 365 nm에서 조사 하였다. 그런 다음 RNA를 세포에서 추출하고 스트렙 트 아비딘 (streptavidin) 구슬을 사용하여 가교 결합 영역을 강화하고 단편화합니다. 인터랙 팅 RNA 단편은 근접 결합을 사용하여 함께 결찰되고 심층 시퀀싱을위한 cDNA 라이브러리로 만들어진다. 시퀀싱시 키메라 RNA는 transcriptome / genome에 매핑되어 서로 쌍을 이루는 RNA 상호 작용 영역을 식별합니다. 우리는 SPLASH를 이용하여 snoRNA, lncRNA 및 mRNA와 같은 RNA의 다양한 부류에서 분자 내 및 분자간 RNA 염기 쌍 형성을 비롯하여 구조 조직 및 상호 작용 패턴을 엿볼 수있는 효모 및 다른 인간 세포 에서 생체 내 에서 수천 건의 RNA 상호 작용을 확인했습니다 세포에서 RNA의.

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	<colgroup>
		<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

RNA가 어떻게 상호 작용 하는지를 아는 것은 세포에서 RNA 기반의 유전자 조절을 이해하는 데 중요합니다. microRNA-mRNA 상호 작용과 같은 RNA-RNA 상호 작용의 예가 유전자 발현을 조절하는 것으로 나타 났지만 RNA 상호 작용이 세포에서 일어나는 전체 범위는 아직 알려지지 않았습니다. RNA 상호 작용을 연구하기위한 이전의 방법은 주로 특정 단백질 또는 RNA 종과 상호 작용하는 RNA의 부분 집합에 초점을 맞추었다. 여기에서는 P soralen crosslinked, Ligated 및 S elected H ybrids (SPLASH)라는 이름의 방법을 상세히 설명합니다.이 방법을 사용하면 생체 내 에서 RNA 상호 작용 을 편파적으로 캡처 할 수 있습니다. SPLASH는 생체 내 교차 결합, 근접 결합 및 높은 처리량 시퀀싱을 사용하여 분자 내 및 분자간 RNA 염기쌍 파트너를 세계적으로 확인합니다. SPLASH는 박테리아, 효모 및 인간 세포를 포함한 다른 유기체에 적용 할 수 있습니다.다양한 세포 환경에서 RNA 조직의 역 동성을 이해하는 데 도움이되는 다양한 세포 조건을 제공합니다. 전체 실험 SPLASH 프로토콜은 완료하는 데 약 5 일이 걸리고 계산 워크 플로는 완료하는 데 약 7 일이 걸립니다.

그림 1 은 SPLASH 워크 플로우의 개략도입니다. 0.01 % digitonin 존재 하에서 biotinylated psoralen을 첨가하고 UV 가교 결합시 total RNA를 세포에서 추출하고 dot blot을 수행하여 RNA에 대한 biotinylated crosslinking이 효율적으로 일어 났는지 확인합니다 ( 그림 2 ). 우리는 biotinylated 20 base oligos를 양성 대조군으로 사용하여 biotinylated psoralen의 양을 ?...

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

여기에서는 생체 내에서 분자 내 및 분자간 RNA-RNA 상호 작용의 게놈 전체 매핑을 가능하게하는 P soralen crosslinked, Ligated 및 S - selected Hysbrids (SL)의 S equencing 방법을 자세히 설명합니다. SPLASH는 효모, 박테리아 및 인간을 포함한 유기체의 RNA 상호 작용을 연구하는 데 적용 할 수 있습니다.

Biotinylated Psoralen을 사용하여 RNA-RNA 상호 작용을 세계적으로 매핑

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 조회수.  A*STAR.  여기에서는 생체 내에서 분자 내 및 분자간 RNA-RNA 상호 작용의 게놈 전체 매핑을 가능하게하는 P soralen crosslinked, Ligated 및 S - selected Hysbrids (SL)의 S equencing 방법을 자세히 설명합니다. SPLASH는 효모, 박테리아 및 인간을 포함한 유기체의 RNA 상호 작용을 연구하는 데 적용 할 수 있습니다. 

비디오: 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.

접합에 참여 전송 단백질의 서열 별 분석을위한 공역 결합 분석 실험

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

연구

유전학

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.

약물 저항 유전자를 확인하기위한 QTL 매핑 및 CRISPR / Cas9 편집<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.

레이저 지역화 소라렌 부가 물의 단일 분자 분석

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.

ChEC-seq와의 단백질 - DNA 상호 작용의 게놈 전체 매핑<em&gt; 사카로 마이 세스 세레 비시 애</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.

레트로 바이러스 스캐닝 : MLV 통합 사이트 맵핑으로 세포 특정 규제 지역 정의

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.

ATAC Seq에 의해 기본 인간 T 림프 톨에 게놈 넓은 접근 Chromatin 매핑

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.

발기인 캡처 안녕-c: 고해상도, 게놈 넓은 발기인 상호 작용의 프로 파일링

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.

포스트 번역 상 수정 및 변형에 대 한 신속 하 고 양적 방법 사용의 펩 티 드 유전자에 매핑

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.

초저입력 캐리어-CAGE를 사용한 전사 시작 사이트 매핑

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.

비오틴 라벨을 사용하여 단백질-핵산 상호 작용을 연구하는 생체외 생화학 적 분석을 통해

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