We give special thanks to Ezra Lyon, Eliot Zhu, Michele Wing, Esko Kautto and Eric Samorodnitsky for technical support. We would also like to thank Jenny Badillo for her administrative support for our team. We acknowledge the Ohio Supercomputer Center (OSC) for providing disk space, processing capacity, and support to run our analyses. We thank the Comprehensive Cancer Center (CCC) at The Ohio State University Wexner Medical Center for their administrative support of this work. S.R. and Team are supported by the American Cancer Society (MRSG-12-194-01-TBG), a Prostate Cancer Foundation Young Investigator Award, NHGRI (UM1HG006508-01A1), Fore Cancer Research Foundation, American Lung Association, and Pelotonia.

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S.R. receives funding from Novartis and Ariad Pharmaceuticals for conduct of clinical trials. S.R. immediate family members own stock in Johnson and Johnson.

RNA-Seq Capture é uma estratégia intermediária entre RNA-Seq e microarray abordagens para avaliar uma parte selecionada do transcriptoma. As vantagens de captura incluem o custo, tempo de resposta rápido reduzida num sequenciador de mesa, de alto rendimento, e a detecção de alterações genómicas. O método pode ser adaptado para caracterizar ARN não codificadoras 23, um único nucleótido detectar variantes 4-6, examinar o RNA splicing, e para identificar fusões de genes ou de rearranjos estruturais 24. Além disso, esta abordagem pode ser aplicada a amostras clínicas ou processados ​​que tenham sido submetidos a fixação com formalina e embebidos em blocos de parafina 24,25. Existem várias vantagens significativas de captura de RNA-Seq, em comparação com microarray, PCR em tempo real quantitativo, de Sanger de sequenciação e sequenciação de ADN. Microarray é limitado por um fundo elevado devido à hibridação cruzada e ligação não específica de sondas. Quantificação de genes com Lexpressão ow é restrita devido ao ruído de fundo, enquanto medições de genes altamente expressos são afetados pela saturação de sinal 1. Comparado a captura de RNA-Seq, PCR em tempo real prova difícil de reproduzir. Além disso, RNA-Seq permite a detecção de novos transcritos, exige menos material de partida de entrada e pode detectar splicing alternativo 26 .Em contraste com Sanger de sequenciação, RNA-Seq permite um maior rendimento e a análise de baixo miARN expressa. Seqüenciamento Sanger provou ser uma ferramenta valiosa para a verificação da fusões com junções exão-exão conhecidos e mutações no DNA somáticas, no entanto identificação de novos fusões é dificultada por exigências de um ponto de interrupção candidato priori. sequenciamento de DNA não é custo eficiente, requer maior espaço de armazenamento para os dados, e é incapaz de detecção de modificações pós-transcricional. Há vários passos críticos envolvidos na captura de RNA-Seq. Em primeiro lugar, para melhorar o rendimento de produtos de biblioteca doRNA / cDNA contas paramagnéticas específica e esferas paramagnéticas durante lavagens, ser cauteloso para não mais secar as contas, o que levará à perda de rendimento. Também não, fazer sub-secar os grânulos, garantir todo o etanol é removido dos tubos de amostra, tal como o etanol pode reduzir o rendimento de ADNc. Em segundo lugar, a hibridação de bibliotecas de ADNc com sondas complementares é dependente da temperatura consistente, recomendamos aquecimento tampão de lavagem I e rigoroso para Tampão 65 ° C durante pelo menos duas horas de antecedência. Além disso, após a hibridação é essencial para manter a 65 ° C durante os passos de ligação e de lavagem. As sondas utilizadas aqui foram projetados para os exons de genes de interesse para o desenvolvimento de drogas, incluindo quinases, genes envolvidos em rearranjos comuns, como fatores de transcrição, e arrumação genes. Além disso, o conteúdo gene é personalizável e tamanhos de painéis de captura pode variar. Além disso, como nova informação sobre regiões genómicas surge, as sondas complementares podem ser concebidos e adicionou-se tEle painel de captura existente. Avaliação de métricas de alinhamento, especificamente taxa on-alvo, fornece informações sobre quão bem a região alvo foi enriquecido. Uma taxa baixa no-alvo pode ser devido a uma falha de hibridação e de captura, em que a região alvo desejado não foi capturado e enriquecido. Neste caso, uma re-hibridação e a captura do conjunto de biblioteca devem ser executadas. Uma taxa baixa no-alvo também pode ser devido a uma falha de esgotar rRNA, que pode ser confirmada através do cálculo da percentagem de ARNr nas amostras. alta porcentagem de rRNA dentro da amostra vai exigir re-preparação da amostra começando com depleção de rRNA. Além disso, se a concentração de biblioteca desce abaixo dos requisitos para a hibridação e de captura, seria aconselhável para optimizar a quantidade de entrada de partida para o tipo de amostra e a qualidade (gama: 50-1.000 ng). Embora existam várias vantagens para aplicações de RNA-Seq direcionados, também há limitações paraconsiderar. As amostras com má qualidade RNA baseado em RIN ou grau de fragmentação não pode produzir bibliotecas de qualidade para sequenciação. Vários grupos têm demonstrado sucesso com amostras embebidos em parafina fixadas em formalina, no entanto, existem amostras que não vai passar para o sequenciamento 24,25,27. Além disso, como RNA-Seq captura concentra-se em transcrições conhecidos, ele perde os benefícios de RNA-Seq imparcial para romance ou transcrições não anotadas. Além disso, para a detecção de SNP, métodos RNA-Seq só pode detectar mutações de transcritos expressos. oportunidades futuras de captura de RNA-Seq incluem a investigação e aplicações clínicas. Recente descoberta de milhares de longo ARN não codificante e o seu papel na biologia exigirá caracterização focado. Na clínica, RNA-Seq Captura pode estender-se para além dos testes de pesquisa e traduzir-se em ensaios clínicos para caracterizar doenças humanas, como o cancro, as doenças infecciosas, e teste não-invasivo. Em conjunto com genômica approa sequenciaçãoChes, RNA-Seq captura pode ser integrado para estudar e caracterizar o genoma expresso.

Whole transcriptome or RNA sequencing (RNAseq) is an unbiased sequencing method to assess all RNA products. The goal of targeted RNAseq (Capture) is a focused evaluation of selected transcripts with increased sensitivity, dynamic range, reduced cost or scale, and increased throughput compared to standard RNAseq. Similar to standard RNAseq, targeted enrichment approaches can be used to evaluate gene expression, multiple RNA species such as mRNA, microRNA (miRNA), lncRNA1, other noncoding RNAs2, gene fusions3, and mutations4-6.
Capture involves hybridization of complementary oligonucleotides to enrich cDNA libraries for sequencing. The rationale for RNAseq Capture is similar to microarray approaches where complementary oligonucleotides or probes are hybridized to samples and then measured for relative abundance. For microarray technologies, expression is based on relative signal measured for transcripts binding to these probes. Microarrays are thus limited by range, potential background noise from non-specific binding, and cross-hybridization of probes. Furthermore, arrays have limited dynamic range for low and highly expressed transcripts compared to RNAseq1. Microarrays are widely utilized due to their reduced cost and high throughput capacity compared to RNAseq. 
Here, we demonstrate a method for RNAseq Capture that offers a middle ground between RNAseq and microarray approaches for evaluating the transcriptome. RNAseq Capture has intermediate throughput, greater dynamic range and sensitivity, and is scaled for fast turnaround on desktop sequencers. RNAseq Capture also requires reduced computational resources in terms of storage space and data processing.

<table border="0" cellpadding="0" cellspacing="0" width="870">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:407px;">Thermomixer R</td>
			<td style="width:153px;">Eppendorf</td>
			<td style="width:143px;">21516-166</td>
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			<td height="20" style="height:20px;">Centrifuge 5417R</td>
			<td style="width:153px;">Eppendorf</td>
			<td style="width:143px;">5417R</td>
			<td></td>
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			<td height="20" style="height:20px;">miRNeasy Mini Kit</td>
			<td style="width:153px;">Qiagen</td>
			<td style="width:143px;">217004</td>
			<td></td>
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			<td height="20" style="height:20px;">Molecular Biology Grade Ethanol</td>
			<td>Sigma Aldrich</td>
			<td>E7023-6X500ML</td>
			<td></td>
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		<tr height="20">
			<td height="20" style="height:20px;width:407px;">Thermoblock 24 X 1.5ml</td>
			<td style="width:153px;">Eppendorf</td>
			<td style="width:143px;">21516-166</td>
			<td></td>
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			<td height="20" style="height:20px;width:407px;">MiSeq Reagent Kit v2 (300-cycles)</td>
			<td style="width:153px;">Illumina</td>
			<td style="width:143px;">MS-102-2002</td>
			<td></td>
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			<td height="20" style="height:20px;width:407px;">MiSeq Desktop Sequencer</td>
			<td style="width:153px;">Illumina</td>
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			<td height="20" style="height:20px;width:407px;">PhiX Control v3</td>
			<td style="width:153px;">Illumina</td>
			<td style="width:143px;">FC-110-3001</td>
			<td></td>
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			<td height="40" style="height:40px;width:407px;">TruSeq Stranded Total RNA Kit with RiboZero Gold SetA</td>
			<td style="width:153px;">Illumina</td>
			<td style="width:143px;">RS-122-2301</td>
			<td></td>
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			<td height="20" style="height:20px;">25 rxn xGen&#174; Universal Blocking Oligo - TS-p5</td>
			<td style="width:153px;">IDT</td>
			<td>127040822</td>
			<td></td>
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		<tr height="20">
			<td height="20" style="height:20px;">25 rxn xGen&#174; Universal Blocking Oligo - TS-p7(6nt)</td>
			<td style="width:153px;">IDT</td>
			<td>127040823</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">25 rxn xGen&#174; Universal Blocking Oligo - TS-p7(8nt)</td>
			<td style="width:153px;">IDT</td>
			<td>127040824</td>
			<td></td>
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			<td height="20" style="height:20px;">Agencourt&#174; AMPure&#174; XP - PCR Purification beads&#160;</td>
			<td>Beckman-Coulter</td>
			<td>A63880</td>
			<td></td>
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			<td height="20" style="height:20px;">Dynabeads&#174; M-270 Streptavidin</td>
			<td>Life Technologies</td>
			<td>65305</td>
			<td></td>
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			<td height="20" style="height:20px;">COT Human DNA, Fluorometric Grade, 1mg</td>
			<td>Roche Applied Science</td>
			<td>05480647001</td>
			<td></td>
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			<td height="20" style="height:20px;">Qubit&#174; Assay Tubes&#160;</td>
			<td>Life Technologies</td>
			<td>Q32856</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit&#174; dsDNA HS Assay Kit</td>
			<td>Life Technologies</td>
			<td>Q32851</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">SeqCap&#174; EZ Hybridization and Wash Kits&#160; (24 or 96 reactions)</td>
			<td>Roche NimbleGen&#160;</td>
			<td>05634261001 or 05634253001&#160;</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit&#174; 2.0 Fluorometer&#160;</td>
			<td>Life Technologies</td>
			<td>Q32866</td>
			<td></td>
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		<tr height="20">
			<td height="20" style="height:20px;width:407px;">10 x 2 ml IDTE pH 8.0 (1X TE Solution)</td>
			<td style="width:153px;">IDT</td>
			<td style="width:143px;"></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Tween20 BioXtra</td>
			<td style="width:153px;">Sigma</td>
			<td>P7949-500ML</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nuclease Free Water</td>
			<td>Life Technologies</td>
			<td>AM9937</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">C1000 Touch&#8482; Thermal Cycler with 96&#8211;Well Fast Rection Module</td>
			<td style="width:153px;">Biorad</td>
			<td style="width:143px;">185-1196</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">SeqCap EZ Hybridization and Wash Kits</td>
			<td>Roche Applied Science</td>
			<td>05634253001</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">SuperScript II Reverse Transcription 200U/ul</td>
			<td>Life Technologies</td>
			<td>18064-014</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">D1000 ScreenTape</td>
			<td>Agilent Technol. Inc.</td>
			<td>5067-5582</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Agencourt RNAClean XP -40ml</td>
			<td>Beckman Coulter Inc</td>
			<td>A63987</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">RNA ScreenTape</td>
			<td>Agilent Technol. Inc.</td>
			<td>5067-5576</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">RNA ScreenTape Ladder</td>
			<td>Agilent Technol. Inc.</td>
			<td>5067-5578</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">RNA ScreenTape Sample Buffer</td>
			<td>Agilent Technol. Inc.</td>
			<td>5067-5577</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Sodium Hydroxide</td>
			<td>Sigma</td>
			<td align="left">72068-100ML</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DynaBeads MyOne Streptavidin T1</td>
			<td>Life Technologies</td>
			<td>65602</td>
			<td></td>
		</tr>
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			<td height="20" style="height:20px;">DYNAMAG -96 SIDE EACH</td>
			<td>Life Technologies</td>
			<td>12331D</td>
			<td></td>
		</tr>
		<tr>
			<td>Chloroform</td>
			<td>Sigma</td>
			<td>C2432-1L</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">KAPA HotStart ReadyMix</td>
			<td>KAPA Biosystems</td>
			<td>KK2602</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:407px;">NanoDrop 2000 Spectrophotometer</td>
			<td style="width:153px;">Thermo Scientific</td>
			<td style="width:143px;"></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:407px;">My Block Mini Dry Bath</td>
			<td style="width:153px;">Benchmark</td>
			<td>BSH200</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">D1000 Reagents</td>
			<td style="width:153px;">Agilent Technol. Inc.</td>
			<td>5067- 5583</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:407px;">Vacufuge Plus</td>
			<td style="width:153px;">Eppendorf</td>
			<td style="width:143px;">022829861&#160;</td>
			<td></td>
		</tr>
	</tbody>
</table>

targeted rna sequencing assay to characterize gene expression and genomic alterations

sequenciação de ARN (RNA-Seq) é um método versátil que pode ser utilizado para detectar e caracterizar a expressão do gene, mutações, fusões de genes, e RNAs não codificantes. Padrão RNA-Seq requer 30-100.000.000 sequenciamento lê e pode incluir vários produtos de RNA, tais como mRNA e RNAs não codificantes. Demonstramos como alvejado RNA-Seq (captura) permite um estudo focado em produtos de RNA selecionados usando um sequenciador de desktop. captura de RNA-Seq pode caracterizar transcrições não anotadas, baixa ou transitoriamente expressas que podem de outra forma ser atendidas através de métodos RNA-Seq tradicionais. Aqui nós descrevemos a extração de RNA a partir de linhas celulares, depleção de RNA ribossomal, síntese de cDNA, a preparação de bibliotecas de código de barras, hibridação e captura de transcritos alvo e sequenciamento multiplex num sequenciador desktop. Nós também destacar o pipeline de análise computacional, que inclui a avaliação de controle de qualidade, o alinhamento, a detecção de fusão, a quantificação expressão genética e identificação de único nucvariantes leotide. Este ensaio permite a sequenciação transcrição direccionada para caracterizar a expressão do gene, fusões de genes e mutações.

A destacando esquemática passos chave na captura de RNA-Seq é mostrado na Figura 1. Quatro linhas celulares de cancro com mutações conhecidas foram usadas para demonstrar a eficácia da técnica de captura de RNA-Seq (K562 com ABL1 fusão, LC2 com fusão Ret, EOL1 com PDGFRalpha fusão e RT- 4 com a fusão FGFR3). As quatro amostras foram reunidas e sequenciados com 2x 100 pb lê num sequenciador de desktop, que gera arquivos FASTQ. arquivos FASTQ foram executados através de um gasoduto análise de RNA-Seq, que inclui cinco componentes principais: 1) avaliação do controle de qualidade, 2) o alinhamento com transcriptoma humano, 3) quantificação de expressão gênica, 4) de chamada de fusão, e 5) chamada variante. O arquivo de alinhamento (BAM) é usado para chamar variantes de nucleotídeo único e calcular a expressão do gene. Fusões são chamados usando chamadas de fusão, tais como Fusão TopHat (efectuando o seu próprio alinhamento) ea saída é anotada using software de detecção de fusão. Comparação da expressão de genes a partir de RNA-Seq captura e demonstra o enriquecimento dos transcritos alvo de 10 a 1000 vezes utilizando o método de captura (Figura 2A). Além disso, a Figura 2B mostra um aumento na percentagem de leituras de mapeamento para as regiões de transcrição-alvo utilizando a captura em comparação com RNA-Seq. Avaliação de medidas de controle de qualidade é representado na Figura 3. Capturar e RNA-Seq desempenho igualmente em termos de alinhamento para o transcriptoma (3A, 94% vs. 93%) e tamanho médio de inserção (3B, 174 pb contra 162 pb). Usando o método de captura, um percentual maior de regiões exï¿½icas são sequenciados (3C, 77% vs. 60%), e, inversamente, uma menor percentagem de regiões intrônicas são sequenciados (3D, 4% vs. 20%). As contagens totais de leitura por amostra estão representadas na 3E </strong&gt;, e como esperado, RNA-Seq gerou mais de 50 vezes mais leituras do que a captura. Finalmente, a percentagem de sequências de rRNA presentes em cada amostra foi inferior usando o método de captura quando comparado com RNA-Seq (3F, 4% vs 15%). Saída de detecção de fusão mostrado na Tabela 1 é gerado com fusão normalizada apoio lê. Captura de RNA-Seq foi bem sucedida na detecção de fusões para todas as quatro linhas celulares. Comparação das variantes de nucleotídeos únicos chamados em regiões de captura e RNA-Seq sobreposição é exibida na Figura 4. Isso demonstra uma alta concordância de variantes entre Captura e RNA-Seq dentro da região de destino. <img alt="figura 1" src="/files/ftp_upload/54090/54090fig1.jpg" /> Figura 1. Esquema de RNA-Seq captura Passos. Nesta demonstração experimental, o RNA é o primeiro depleTed de ARN ribossomal, seguido por fragmentação química e síntese de DNA complementar (cDNA), utilizando transcriptase inversa. Em seguida, o ADNc é poliadenilado e ligado em ambas as extremidades para adaptadores específicos da plataforma para gerar uma biblioteca. Somente bibliotecas de cDNA com adaptadores adequados são, em seguida, amplificado por PCR. As bibliotecas são então hibridados com sondas de oligonucleótidos personalizados e capturados usando esferas magnéticas. Esta pequena quantidade de biblioteca capturado deva ser amplificado por uma segunda vez para ter o suficiente para o próximo sequenciamento geração. Várias bibliotecas pode então ser sequenciados em paralelo. Dados de sequenciamento é analisado para eventos de ARN de interesse, tais como fusões de genes, expressão ou mutações. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54090/54090fig1large.jpg" target="_blank">Por favor clique aqui para ver uma versão maior desta figura.</a> <img alt="Figura 2" src="/files/ftp_upload/54090/54090fig2.jpg" /> Figura 2. COMPARAÇÃO de genes alvo na captura contra o RNA-Seq. A, a comparação da expressão gênica entre Captura e RNA-Seq em quatro linhas celulares de cancro K562, LC2, EOL1 e RT-4 medidos por leituras por quilobases por milhão mapeados lê (FPKM) (Log escala). Genes específicos de interesse são enriquecidos (azul) em comparação com genes não-alvo (cinza). B, Percentagem de lê mapeamento para a região alvo é aumentada em captura contra bibliotecas RNA-Seq em quatro linhas celulares de cancro. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54090/54090fig2large.jpg" target="_blank">Por favor clique aqui para ver uma versão maior esta figura.</a> <img alt="Figura 3" src="/files/ftp_upload/54090/54090fig3.jpg" /> Figura 3. Sequenciação Métricas de Captura contra o RNA-Seq em linhas celulares de cancro da Quatro Representante. A, Percentagem de lê mapeamento para o transcriptoma, <strong&gt; B, a média de tamanho de inserção de bibliotecas. C, percentagem de leituras em regiões exï¿½icas. D, porcentagem de leituras em regiões intrônicas. E, sequenciamento total lê. F, Percentagem de lê mapeamento para RNA ribossomal. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54090/54090fig3large.jpg" target="_blank">Por favor clique aqui para ver uma versão maior desta figura.</a> <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td rowspan="2"> Linha celular </td><td rowspan="2"> Fusão </td><td rowspan="2"> Type Library </td><td rowspan="2"> total de Lê </td><td rowspan="2"> No alvo Lê </td><td colspan="3"> Fusão normalizada Apoio Lê (NFSR) </td></tr><tr><td> TophatFusion </td><td> ChimeraScan </td><td> TRACIMA </td></tr><tr><td> K562 </td><td> BCR-ABL </td><td> RNA-Seq </td><td> 150300482 </td><td> 279438 </td><td> 0 </td><td> 438 </td><td> 0 </td></tr><tr><td></td><td></td><td> Capturar </td><td> 9.341.148 </td><td> 7.566.087 </td><td> 598 </td><td> 343 </td><td> 0 </td></tr><tr><td> LC2 </td><td> CCDC6-RET </td><td> RNA-Seq </td><td> 128861790 </td><td> 307566 </td><td> 0 </td><td> 97 </td><td> 0 </td></tr><tr><td></td><td></td><td> Capturar </td><td> 12320692 </td><td> 10314284 </td><td> 71 </td><td> 44 </td><td> 6 </td></tr><tr><td> EOL1 </td><td> FIP1L1-PDGFRA </td><td> RNA-Seq </td><td> 135321406 </td><td> 225222 </td><td> 0 </td><td> 0 </td><td> 170 </td></tr><tr><td></td><td></td><td> Capturar </td><td> 9.317.418 </td><td> 7.680.818 </td><td> 143 </td><td> 0 </td><td> 7 </td></tr><tr><td> RT4 </td><td> FGFR3<html> -TACC3 </td><td> RNA-Seq </td><td> 161350024 </td><td> 208741 </td><td> 0 </td><td> 131 </td><td> 469 </td></tr><tr><td></td><td></td><td> Capturar </td><td> 8.305.950 </td><td> 6.563.574 </td><td> 358 </td><td> 88 </td><td> 34 </td></tr></tbody></table> Tabela 1. Detecção Fusion for captura contra o RNA-Seq de K562, LC2, EOL1 e RT-4. Esta tabela exibe quatro linhas celulares de cancro e três algoritmos de detecção de fusão diferentes, TopHat2, ChimeraScan e TRUP utilizados nesta demonstração. Esta tabela demonstra a capacidade para detectar fusões com captura utilizando menos do que 10 milhões Total de leituras em comparação com mais de 60 milhões lê utilizado para a RNA-Seq. Fusão suportando leituras foram calculados dividindo-se a fusão de apoio lê por quinase lê, multiplicado por um milhão. <img alt="&lt;/ Html">&quot;Figura 4&quot; src = &quot;/ files / ftp_upload / 54090 / 54090fig4.jpg&quot; /&gt; Figura 4. SNV ligando para captura contra RNA-Seq. Estes diagramas de Venn mostra o número de variantes de um Único Nucleótido (SNVS) que foram detectados por captura e RNA-Seq para cada uma das quatro linhas celulares (K562, LC2, EOL1 e RT-4). Isto ilustra alta concordância do SNVS entre Captura e RNA-Seq dentro segmentada por região:. K562 (81,3%), LC2 (78,3%), EOL1 (89,5%) e RT-4 (73,9%) <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54090/54090fig4large.jpg" target="_blank">Por favor clique aqui para ver uma versão maior esta figura.</a>

Watch this Scientific Journal Video about Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations at JoVE.com

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

We describe a targeted RNA sequencing-based method that includes preparation of indexed cDNA libraries, hybridization and capture with custom probes and data analysis to interrogate selected transcripts for gene expression, mutations, and gene fusions. Targeted RNAseq permits cost-effective, rapid evaluation of selected transcripts on a desktop sequencer.

Targeted RNA Sequenciação Ensaio para Caracterizar expressão gênica e genômica Alterações

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding ...

targeted-rna-sequencing-assay-to-characterize-gene-expression-genomic

Nanyang Technological University

Research

JoVE Journal

Biology

10.3K visualizações.  The Ohio State University. We describe a targeted RNA sequencing-based method that includes preparation of indexed cDNA libraries, hybridization and capture with custom probes and data analysis to interrogate selected transcripts for gene expression, mutations, and gene fusions. Targeted RNAseq permits cost-effective, rapid evaluation of selected transcripts on a desktop sequencer.

Vídeo: Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

The Preparation of Primary Hematopoietic Cell Cultures From Murine Bone Marrow for Electroporation

It is becoming increasingly apparent that electroporation is the most effective way to introduce plasmid DNA or siRNA into primary cells. The Gene Pulser MXcell  electroporation system and Gene Pulser  electroporation buffer were specifically developed to transfect nucleic acids into mammalian cells and difficult-to-transfect cells, such as primary and stem cells.This video demonstrates how to establish primary hematopoietic cell cultures from murine bone marrow, and then prepare them for electroporation in the MXcell system. We begin by isolating femur and tibia. Bone marrow from both femur and tibia are then harvested and cultures are established. Cultured bone marrow cells are then transfected and analyzed.

This procedure describes how to establish primary hematopoietic cell cultures from murine bone marrow and is followed by transfection using the Gene Pulser MXCell electroporation system.

Elaboração de culturas de células primárias hematopoéticas de medula óssea de camundongos para Eletroporação

It is becoming increasingly apparent that electroporation is the most effective way to introduce plasmid DNA or siRNA into primary cells. The Gene Pulser ...

Biologia

RNA Isolation from Embryonic Zebrafish and cDNA Synthesis for Gene Expression Analysis

Many important and complex laboratory procedures require an input of high quality, intact RNA.  A degraded sample or the presence of impurities can lead to disastrous results in downstream experimental applications.  It is therefore, of utmost importance to use solid techniques with numerous safeguards and quality control checks to ensure a superior sample.  Herein, we detail a protocol to isolate total RNA from whole zebrafish embryos using a commercially available chemical denaturant and subsequent cleanup to remove traces of DNA and impurities using a commercial RNA isolation kit. As RNA is relatively unstable and easily prone to cleavage by RNAses, most protocols assay gene expression using a cDNA product that is directly synthesized from an RNA template. We detail a procedure to convert RNA into the more stable cDNA product using a commercially available kit. Throughout these procedures there are numerous quality control checks to ensure that the sample is not degraded or contaminated.  The end product of these protocols is cDNA that is suitable for microarray analysis, RT-PCR or long-term storage.    

The isolation of high quality, intact RNA is an essential step in many laboratory protocols. Here, we demonstrate RNA extraction from whole zebrafish embryos and cDNA synthesis for subsequent application in various experimental procedures including gene expression microarray analysis.

Isolamento de RNA Síntese Zebrafish e cDNA embrionárias para Análise de Expressão Gênica

Many important and complex laboratory procedures require an input of high quality, intact RNA.  A degraded sample or the presence of impurities can lead ...

Using the Gene Pulser MXcell Electroporation System to Transfect Primary Cells with High Efficiency

It is becoming increasingly apparent that electroporation is the most effective way to introduce plasmid DNA or siRNA into primary cells. The Gene Pulser MXcell electroporation system and Gene Pulser electroporation buffer (Bio-Rad) were specifically developed to easily transfect nucleic acids into mammalian cells and difficult-to-transfect cells, such as primary and stem cells. We will demonstrate how to perform a simple experiment to quickly identify the best electroporation conditions. We will demonstrate how to run several samples through a range of electroporation conditions so that an experiment can be conducted at the same time as optimization is performed. We will also show how optimal conditions identified using 96-well electroporation plates can be used with standard electroporation cuvettes, facilitating the switch from electroporation plates to electroporation cuvettes while maintaining the same electroporation efficiency. In the video, we will also discuss some of the key factors that can lead to the success or failure of electroporation experiments.

This procedure shows how to use the Gene Pulser MXcell electroporation system to rapidly and easily identify the best electroporation conditions for mouse embryonic fibroblasts (MEFs) or other primary cells. Considerations for troubleshooting are also discussed in the associated video.

Usando o Sistema de Eletroporação Gene Pulser MXcell para transfectar pilhas com Alta Eficiência

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

The use of siRNA mediated gene knockdown is continuing to be an important tool in studies of gene expression.  siRNA studies are being conducted not only to study the effects of downregulating single genes, but also to interrogate signaling pathways and other complex interaction networks.  These pathway analyses require both the use of relevant cellular models and methods that cause less perturbation to the cellular physiology.  Electroporation is increasingly being used as an effective way to introduce siRNA and other nucleic acids into difficult to transfect cell lines and primary cells without altering the signaling pathway under investigation. There are multiple critical steps to a successful siRNA experiment, and there are ways to simplify the work while improving the data quality at several experimental stages.  To help you get started with your siRNA mediated gene knockdown project, we will demonstrate how to perform a pathway study complete from collecting and counting the cells prior to electroporation through post transfection real-time PCR gene expression analysis.  The following study investigates the role of the transcriptional activator STAT6 in IL-4 dependent gene expression of CCL17 in a Burkitt lymphoma cell line (Namalwa).  The techniques demonstrated are useful for a wide range of siRNA-based experiments on both adherent and suspension cells.  We will also show how to streamline cell counting with the TC10 automated cell counter, how to electroporate multiple samples simultaneously using the MXcell electroporation system, and how to simultaneously assess RNA quality and quantity with the Experion automated electrophoresis system.

This procedure describes a quick and easy workflow to introduce siRNA into difficult to transfect cell lines and follow gene expression by real-time PCR. Use of an automated cell counter, multi-well electroporation plate, and automated electrophoresis station provide quick and reliable results without the need for expensive robotic handling.

Usando um contador de células automatizadas para simplificar Estudos da Expressão Gênica: Knockdown siRNA de Expressão IL-4 Gene Dependente em células NAMALWA

The use of siRNA mediated gene knockdown is continuing to be an important tool in studies of gene expression.  siRNA studies are being conducted not only ...

Paraffin-Embedded and Frozen Sections of Drosophila Adult Muscles

The molecular characterization of muscular dystrophies and myopathies in humans has revealed the complexity of muscle disease and genetic analysis of muscle specification, formation and function in model systems has provided valuable insight into muscle physiology. Therefore, identifying and characterizing molecular mechanisms that underlie muscle damage is critical. The structure of adult Drosophila multi-fiber muscles resemble vertebrate striated muscles 1 and the genetic tractability of Drosophila has made it a great system to analyze dystrophic muscle morphology and characterize the processes affecting muscular function in ageing adult flies 2. Here we present the histological technique for preparing paraffin-embedded and frozen sections of Drosophila thoracic muscles. These preparations allow for the tissue to be stained with classical histological stains and labeled with protein detecting dyes, and specifically cryosections are ideal for immunohistochemical detection of proteins in intact muscles. This allows for analysis of muscle tissue structure, identification of morphological defects, and detection of the expression pattern for muscle/neuron-specific proteins in Drosophila adult muscles. These techniques can also be slightly modified for sectioning of other body parts.

Paraffin-Embedded and Frozen Sections of Drosophila Adult Muscles

Identification of mechanisms underlying muscle damage is crucial. Here we present the histological technique for preparing paraffin-embedded and frozen sections of Drosophila thoracic muscles. This allows analysis of muscle morphology and localization of protein and other muscle cell components.

Seções incluído em parafina e congelados de Drosophila Músculos Adulto

The molecular characterization of muscular dystrophies and myopathies in humans has revealed the complexity of muscle disease and genetic analysis of ...

In vitro Reconstitution of the Active T. castaneum Telomerase

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more than a decade. Here, we present methods for the isolation of the recombinant Tribolium castaneum TERT (TcTERT) and the reconstitution of the active T. castaneum telomerase ribonucleoprotein (RNP) complex in vitro.
Telomerase is a specialized reverse transcriptase1 that adds short DNA repeats, called telomeres, to the 3' end of linear chromosomes2 that serve to protect them from end-to-end fusion and degradation. Following DNA replication, a short segment is lost at the end of the chromosome3 and without telomerase, cells continue dividing until eventually reaching their Hayflick Limit4. Additionally, telomerase is dormant in most somatic cells5 in adults, but is active in cancer cells6 where it promotes cell immortality7.
The minimal telomerase enzyme consists of two core components: the protein subunit (TERT), which comprises the catalytic subunit of the enzyme and an integral RNA component (TER), which contains the template TERT uses to synthesize telomeres8,9. Prior to 2008, only structures for individual telomerase domains had been solved10,11. A major breakthrough in this field came from the determination of the crystal structure of the active12, catalytic subunit of T. castaneum telomerase, TcTERT1.
Here, we present methods for producing large quantities of the active, soluble TcTERT for structural and biochemical studies, and the reconstitution of the telomerase RNP complex in vitro for telomerase activity assays. An overview of the experimental methods used is shown in Figure 1.

In vitro Reconstitution of the Active T. castaneum Telomerase

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more than a decade. Here, we present methods for the isolation of the recombinant Tribolium castaneum TERT (TcTERT) and the reconstitution of the active T. castaneum telomerase ribonucleoprotein (RNP) complex in vitro.

Na reconstituição in vitro da atividade T. Telomerase castaneum

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more ...

Competitive Genomic Screens of Barcoded Yeast Libraries

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily. The tempo of these advances is accelerating, promising greater depth and breadth. In light of these extraordinary advances, the need for fast, parallel methods to define gene function becomes ever more important. Collections of genome-wide deletion mutants in yeasts and E. coli have served as workhorses for functional characterization of gene function, but this approach is not scalable, current gene-deletion approaches require each of the thousands of genes that comprise a genome to be deleted and verified. Only after this work is complete can we pursue high-throughput phenotyping. Over the past decade, our laboratory has refined a portfolio of competitive, miniaturized, high-throughput genome-wide assays that can be performed in parallel. This parallelization is possible because of the inclusion of DNA 'tags', or 'barcodes,' into each mutant, with the barcode serving as a proxy for the mutation and one can measure the barcode abundance to assess mutant fitness. In this study, we seek to fill the gap between DNA sequence and barcoded mutant collections. To accomplish this we introduce a combined transposon disruption-barcoding approach that opens up parallel barcode assays to newly sequenced, but poorly characterized microbes. To illustrate this approach we present a new Candida albicans barcoded disruption collection and describe how both microarray-based and next generation sequencing-based platforms can be used to collect 10,000 - 1,000,000 gene-gene and drug-gene interactions in a single experiment.

We have developed comprehensive, unbiased genome-wide screens to understand gene-drug and gene-environment interactions. Methods for screening these mutant collections are presented.

Competitiva Screens Genomic de Bibliotecas Yeast Barcoded

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily.  The tempo of these advances is ...

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Efforts to detect and investigate key oncogenic mutations have proven valuable to facilitate the appropriate treatment for cancer patients. The establishment of high-throughput, massively parallel "next-generation" sequencing has aided the discovery of many such mutations. To enhance the clinical and translational utility of this technology, platforms must be high-throughput, cost-effective, and compatible with formalin-fixed paraffin embedded (FFPE) tissue samples that may yield small amounts of degraded or damaged DNA. Here, we describe the preparation of barcoded and multiplexed DNA libraries followed by hybridization-based capture of targeted exons for the detection of cancer-associated mutations in fresh frozen and FFPE tumors by massively parallel sequencing. This method enables the identification of sequence mutations, copy number alterations, and select structural rearrangements involving all targeted genes. Targeted exon sequencing offers the benefits of high throughput, low cost, and deep sequence coverage, thus conferring high sensitivity for detecting low frequency mutations.

We describe the preparation of barcoded DNA libraries and subsequent hybridization-based exon capture for detection of key cancer-associated mutations in clinical tumor specimens by massively parallel "next generation" sequencing. Targeted exon sequencing offers the benefits of high throughput, low cost, and deep sequence coverage, thus yielding high sensitivity for detecting low frequency mutations.

Detectando somáticas Genéticos Alterações em amostras de tumor por Exon Captura e Seqüenciamento Massively Parallel

Efforts  to detect and investigate key oncogenic mutations have proven valuable to  facilitate the appropriate treatment for cancer patients. The ...

Analysis of Global RNA Synthesis at the Single Cell Level following Hypoxia

Hypoxia or lowering of the oxygen availability is involved in many physiological and pathological processes. At the molecular level, cells initiate a particular transcriptional program in order to mount an appropriate and coordinated cellular response. The cell possesses several oxygen sensor enzymes that require molecular oxygen as cofactor for their activity. These range from prolyl-hydroxylases to histone demethylases. The majority of studies analyzing cellular responses to hypoxia are based on cellular populations and average studies, and as such single cell analysis of hypoxic cells are seldom performed. Here we describe a method of analysis of global RNA synthesis at the single cell level in hypoxia by using Click-iT RNA imaging kits in an oxygen controlled workstation, followed by microscopy analysis and quantification.&nbsp; Using cancer cells exposed to hypoxia for different lengths of time, RNA is labeled and measured in each cell. This analysis allows the visualization of temporal and cell-to-cell changes in global RNA synthesis following hypoxic stress.

We describe a technique for analysis of global RNA synthesis in hypoxia using imaging. Click-chemistry labeling of RNA has not previously been performed under hypoxia and allows visualization of global RNA changes at the single cell level. This approach complements the existing averaged RNA techniques, allowing direct visualization of cell-to-cell changes in global RNA synthesis.

Análise da Global RNA Síntese no nível da célula única seguinte hipóxia

Hypoxia or lowering of the oxygen availability is involved in many physiological and pathological processes. At the molecular level, cells initiate a ...

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

One of the major questions in microbial ecology is &#8220;who is there?&#8221; This question can be answered using various tools, but one of the long-lasting gold standards is to sequence 16S ribosomal RNA (rRNA) gene amplicons generated by domain-level PCR reactions amplifying from genomic DNA. Traditionally, this was performed by cloning and Sanger (capillary electrophoresis) sequencing of PCR amplicons. The advent of next-generation sequencing has tremendously simplified and increased the sequencing depth for 16S rRNA gene sequencing. The introduction of benchtop sequencers now allows small labs to perform their 16S rRNA sequencing in-house in a matter of days. Here, an approach for 16S rRNA gene amplicon sequencing using a benchtop next-generation sequencer is detailed. The environmental DNA is first amplified by PCR using primers that contain sequencing adapters and barcodes. They are then coupled to spherical particles via emulsion PCR. The particles are loaded on a disposable chip and the chip is inserted in the sequencing machine after which the sequencing is performed. The sequences are retrieved in fastq format, filtered and the barcodes are used to establish the sample membership of the reads. The filtered and binned reads are then further analyzed using publically available tools. An example analysis where the reads were classified with a taxonomy-finding algorithm within the software package Mothur is given. The method outlined here is simple, inexpensive and straightforward and should help smaller labs to take advantage from the ongoing genomic revolution.

Characterizing microbial community has been a longstanding goal in environmental microbiology. Next-generation sequencing methods now allow for the characterization of microbial communities at an unprecedented depth with minimal cost and labor. We detail here our approach to sequence bacterial 16S ribosomal RNA genes using a benchtop sequencer.