Name: optimization for sequencing and analysis of degraded ffpe-rna samples
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Description: Watch this Scientific Journal Video about Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples at JoVE.com

Somos gratos à Dra. Danielle Carrick (Divisão de Controle do Câncer e Ciências Populacionais do Instituto Nacional de Câncer) por ajuda contínua, especialmente por iniciar este estudo, fornecendo-nos as amostras e sugestões úteis durante a análise de dados. Agradecemos sinceramente a todos os membros do Centro de Sequenciamento da CCR no Laboratório Nacional de Pesquisa do Câncer de Frederick por sua ajuda durante a preparação e sequenciamento da amostra, especialmente Brenda Ho pela assistência na amostra QC, Oksana German para a biblioteca QC, Tatyana Smirnova para executar os sequenciadores. Também gostaríamos de agradecer a Tsai-wei Shen e Ashley Walton no Sequencing Facility Bioinformatics Group por ajudar na análise de dados e na implementação do pipeline RNA-seq. Agradecemos também à CCBR e à NCBR pela assistência com o pipeline de análise da RNaseq e o desenvolvimento de melhores práticas.

1. Avaliação de quantidade e qualidade do RNA
<ol><li>Selecione as amostras de FFPE de acordo com critérios predefinidos e extraia RNA utilizando um método apropriado (por exemplo, kit de extração de ácido FFPE-nuclei, Tabela de Materiais). NOTA: Existem vários métodos diferentes disponíveis para extração ffpe-RNA, incluindo os métodos mais novos de microdisseção que podem trabalhar com muito pouco tecido e extrair RNA de boa qualidade12,,<sup class=...

<ol>
	<li>Carrick, D. 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=Robustness+of+Next+Generation+Sequencing+on+Older+Formalin-Fixed+Paraffin-Embedded+Tissue.">Robustness of Next Generation Sequencing on Older Formalin-Fixed Paraffin-Embedded Tissue.</a> PLoS One. 10 (7), 0127353 (2015).</li><li>Hedegaard, J., 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=Next-generation+sequencing+of+RNA+and+DNA+isolated+from+paired+fresh-frozen+and+formalin-fixed+paraffin-embedded+samples+of+human+cancer+and+normal+tissue.">Next-generation sequencing of RNA and DNA isolated from paired fresh-frozen and formalin-fixed paraffin-embedded samples of human cancer and normal tissue.</a> PLoS One. 9 (5), 98187 (2014).</li><li>Zhang, P., Lehmann, B. D., Shyr, Y., Guo, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Utilization+of+Formalin+Fixed-Paraffin-Embedded+Specimens+in+High+Throughput+Genomic+Studies.">The Utilization of Formalin Fixed-Paraffin-Embedded Specimens in High Throughput Genomic Studies.</a> International Journal of Genomics. 2017, 1926304 (2017).</li><li>Srinivasan, M., Sedmak, D., Jewell, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+fixatives+and+tissue+processing+on+the+content+and+integrity+of+nucleic+acids.">Effect of fixatives and tissue processing on the content and integrity of nucleic acids.</a> American Journal of Pathology. 161 (6), 1961-1971 (2002).</li><li>von Ahlfen, S., Missel, A., Bendrat, K., Schlumpberger, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determinants+of+RNA+quality+from+FFPE+samples.">Determinants of RNA quality from FFPE samples.</a> PLoS One. 2 (12), 1261 (2007).</li><li>Esteve-Codina, A., 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=A+Comparison+of+RNA-Seq+Results+from+Paired+Formalin-Fixed+Paraffin-Embedded+and+Fresh-Frozen+Glioblastoma+Tissue+Samples.">A Comparison of RNA-Seq Results from Paired Formalin-Fixed Paraffin-Embedded and Fresh-Frozen Glioblastoma Tissue Samples.</a> PLoS One. 12 (1), 0170632 (2017).</li><li>Vukmirovic, 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=Identification+and+validation+of+differentially+expressed+transcripts+by+RNA-sequencing+of+formalin-fixed,+paraffin-embedded+(FFPE)+lung+tissue+from+patients+with+Idiopathic+Pulmonary+Fibrosis.">Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis.</a> BMC Pulmonary Medicine. 17 (1), 15 (2017).</li><li>Adiconis, X., 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=Comparative+analysis+of+RNA+sequencing+methods+for+degraded+or+low-input+samples.">Comparative analysis of RNA sequencing methods for degraded or low-input samples.</a> Nature Methods. 10 (7), 623-629 (2013).</li><li>Sinicropi, D., 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=Whole+transcriptome+RNA-Seq+analysis+of+breast+cancer+recurrence+risk+using+formalin-fixed+paraffin-embedded+tumor+tissue.">Whole transcriptome RNA-Seq analysis of breast cancer recurrence risk using formalin-fixed paraffin-embedded tumor tissue.</a> PLoS One. 7 (7), 40092 (2012).</li><li>Altekruse, S. F., 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=SEER+cancer+registry+biospecimen+research:+yesterday+and+tomorrow.">SEER cancer registry biospecimen research: yesterday and tomorrow.</a> Cancer Epidemiology, Biomarkers &amp; Prevention. 23 (12), 2681-2687 (2014).</li><li>Zhao, 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=Robustness+of+RNA+sequencing+on+older+formalin-fixed+paraffin-embedded+tissue+from+high-grade+ovarian+serous+adenocarcinomas.">Robustness of RNA sequencing on older formalin-fixed paraffin-embedded tissue from high-grade ovarian serous adenocarcinomas.</a> PLoS One. 14 (5), 0216050 (2019).</li><li>Amini, P., 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=An+optimised+protocol+for+isolation+of+RNA+from+small+sections+of+laser-capture+microdissected+FFPE+tissue+amenable+for+next-generation+sequencing.">An optimised protocol for isolation of RNA from small sections of laser-capture microdissected FFPE tissue amenable for next-generation sequencing.</a> BMC Molecular Biology. 18 (1), 22 (2017).</li><li>Amini, P., Nassiri, S., Ettlin, J., Malbon, A., Markkanen, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Next-generation+RNA+sequencing+of+FFPE+subsections+reveals+highly+conserved+stromal+reprogramming+between+canine+and+human+mammary+carcinoma.">Next-generation RNA sequencing of FFPE subsections reveals highly conserved stromal reprogramming between canine and human mammary carcinoma.</a> Disease Models and Mechanisms. 12 (8), (2019).</li><li>Wimmer, I., 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=Systematic+evaluation+of+RNA+quality,+microarray+data+reliability+and+pathway+analysis+in+fresh,+fresh+frozen+and+formalin-fixed+paraffin-embedded+tissue+samples.">Systematic evaluation of RNA quality, microarray data reliability and pathway analysis in fresh, fresh frozen and formalin-fixed paraffin-embedded tissue samples.</a> Scientific Reports. 8 (1), 6351 (2018).</li><li>. Babraham Bioinformatics Available from: <a target="_blank" href="https://www.bioinformatics.babraham.ac.uk/projects/fastqc/">https://www.bioinformatics.babraham.ac.uk/projects/fastqc/</a> (2019)</li><li>Martin, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cutadapt+removes+adapter+sequences+from+high-throughput+sequencing+reads.">Cutadapt removes adapter sequences from high-throughput sequencing reads.</a> EMBnet.journal. 17 (1), 10-12 (2011).</li><li>Bolger, A. M., Lohse, M., Usadel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trimmomatic:+a+flexible+trimmer+for+Illumina+sequence+data.">Trimmomatic: a flexible trimmer for Illumina sequence data.</a> Bioinformatics. 30 (15), 2114-2120 (2014).</li><li>. Babraham Bioinformatics Available from: <a target="_blank" href="https://www.bioinformatics.babraham.ac.uk/projects/fastq_screen/">https://www.bioinformatics.babraham.ac.uk/projects/fastq_screen/</a> (2019)</li><li>Wood, D. E., Salzberg, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kraken:+ultrafast+metagenomic+sequence+classification+using+exact+alignments.">Kraken: ultrafast metagenomic sequence classification using exact alignments.</a> Genome Biology. 15 (3), 46 (2014).</li><li>Dobin, A., 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=STAR:+ultrafast+universal+RNA-seq+aligner.">STAR: ultrafast universal RNA-seq aligner.</a> Bioinformatics. 29 (1), 15-21 (2013).</li><li>Wang, L., Wang, S., Li, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RSeQC:+quality+control+of+RNA-seq+experiments.">RSeQC: quality control of RNA-seq experiments.</a> Bioinformatics. 28 (16), 2184-2185 (2012).</li><li>Ewels, P., Magnusson, M., Lundin, S., Kaller, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MultiQC:+summarize+analysis+results+for+multiple+tools+and+samples+in+a+single+report.">MultiQC: summarize analysis results for multiple tools and samples in a single report.</a> Bioinformatics. 32 (19), 3047-3048 (2016).</li><li>Li, B., Dewey, C. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RSEM:+accurate+transcript+quantification+from+RNA-Seq+data+with+or+without+a+reference+genome.">RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.</a> BMC Bioinformatics. 12, 323 (2011).</li><li>Son, K., Yu, S., Shin, W., Han, K., Kang, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Simple+Guideline+to+Assess+the+Characteristics+of+RNA-Seq+Data.">A Simple Guideline to Assess the Characteristics of RNA-Seq Data.</a> BioMed Research International. 2018, 2906292 (2018).</li><li>McCarthy, D. J., Chen, Y., Smyth, G. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+expression+analysis+of+multifactor+RNA-Seq+experiments+with+respect+to+biological+variation.">Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.</a> Nucleic Acids Research. 40 (10), 4288-4297 (2012).</li><li>Robinson, M. D., McCarthy, D. J., Smyth, G. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=edgeR:+a+Bioconductor+package+for+differential+expression+analysis+of+digital+gene+expression+data.">edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.</a> Bioinformatics. 26 (1), 139-140 (2010).</li><li>Ritchie, M. E., 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=limma+powers+differential+expression+analyses+for+RNA-sequencing+and+microarray+studies.">limma powers differential expression analyses for RNA-sequencing and microarray studies.</a> Nucleic Acids Research. 43 (7), 47 (2015).</li><li>Subramanian, A., 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=Gene+set+enrichment+analysis:+a+knowledge-based+approach+for+interpreting+genome-wide+expression+profiles.">Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.</a> Proceedings of the National Academy of Sciences of the United States of America U S A. 102 (43), 15545-15550 (2005).</li><li>Mootha, V. K., 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=PGC-1alpha-responsive+genes+involved+in+oxidative+phosphorylation+are+coordinately+downregulated+in+human+diabetes.">PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.</a> Nature Genetics. 34 (3), 267-273 (2003).</li><li>Ashburner, 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=Gene+ontology:+tool+for+the+unification+of+biology.+The+Gene+Ontology+Consortium.">Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.</a> Nature Genetics. 25 (1), 25-29 (2000).</li><li>Huang da, W., Sherman, B. T., Lempicki, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systematic+and+integrative+analysis+of+large+gene+lists+using+DAVID+bioinformatics+resources.">Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.</a> Nature Protocols. 4 (1), 44-57 (2009).</li><li>Huang da, W., Sherman, B. T., Lempicki, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bioinformatics+enrichment+tools:+paths+toward+the+comprehensive+functional+analysis+of+large+gene+lists.">Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists.</a> Nucleic Acids Research. 37 (1), 1-13 (2009).</li><li>Evaluating RNA Quality from FFPE Samples. Illumina Available from: <a target="_blank" href="https://www.illumina.com/content/dam/illumina-marketing/documents/products/technotes/evaluating-rna-quality-from-ffpe-samples-technical-note-470-2014-001.pdf">https://www.illumina.com/content/dam/illumina-marketing/documents/products/technotes/evaluating-rna-quality-from-ffpe-samples-technical-note-470-2014-001.pdf</a> (2016)</li></ol>

O método descrito aqui descreve as principais etapas necessárias para obter bons dados de sequência de amostras de FFPE-RNA. Os principais pontos a serem considerados com este método são: (1) Certifique-se de que o RNA seja preservado da melhor forma possível após a extração, minimizando os ciclos de manuseio e congelamento e descongelamento da amostra. Alíquotas separadas do QC são muito úteis. (2) Use uma métrica QC que seja melhor para o conjunto amostral dado. Os valores rin e DV200 muitas vez...

O uso de abordagens de sequenciamento de última geração nos permitiu obter uma riqueza de informações de vários tipos de amostras. No entanto, amostras antigas e mal preservadas permanecem inviáveis para os métodos comumente utilizados de geração de dados de sequência e muitas vezes requerem modificações em protocolos bem estabelecidos. Os tecidos FFPE representam um tipo de amostra que tem sido amplamente utilizado para as amostras clínicas1,,2,3. Enquanto a preservação do FFPE mantém a morfologia tecidual, os ácidos nucleicos nos tecidos FFPE geralmente exibem uma ampla gama de danos e degradação, dificultando a recuperação das informações genômicas que podem levar a importantes insights sobre mecanismos moleculares subjacentes a vários distúrbios.
Os dados de expressão genética gerados pelo sequenciamento de RNA são frequentemente fundamentais no estudo de mecanismos de doença e resistência e complementam a análise da mutação do DNA. No entanto, o RNA é mais suscetível à degradação, tornando mais desafiador gerar dados precisos de expressão genética a partir de tecidos FFPE. Além disso, como a ampla disponibilidade e a acessibilidade do sequenciamento são relativamente recentes, os espécimes mais antigos muitas vezes não eram armazenados em condições necessárias para preservar a integridade do RNA. Algumas das questões para amostras de FFPE incluem a degradação do RNA devido à incorporação em parafina, modificação química do RNA levando à fragmentação ou refractoridade a processos enzimáticos necessários para sequenciamento, e perda das caudas poli-A, limitando a aplicabilidade do oligo-dT como uma cartilha para transcrição reversa4. Outro desafio é o manuseio/armazenamento de amostras de FFPE em condições subótimas, o que pode levar a uma maior degradação de moléculas labile, como o RNA nos tecidos5. Isso é especialmente relevante para amostras mais antigas que podem ter sido coletadas em um momento em que a análise da expressão genética pelo sequenciamento de RNA não foi antecipada para as amostras. Tudo isso leva à diminuição da qualidade e quantidade do RNA extraído disponível para gerar dados de sequência úteis. A baixa probabilidade de sucesso, combinada com o alto custo do sequenciamento, dissuadiu muitos pesquisadores de tentar gerar e analisar dados de expressão genética a partir de amostras de FFPE potencialmente úteis. Alguns estudos nos últimos anos demonstraram a usabilidade dos tecidos FFPE para análise de expressão genética2,,6,,7,,8,9, embora para amostras menores e/ou mais recentes.
Como estudo de viabilidade, utilizamos o RNA extraído de amostras de tecido tumoral FFPE de três repositórios de tecido residual de registros de câncer de Vigilância, Epidemiologia e Resultados Finais (SEER) para sequenciamento de RNA e análise de expressão genética10. Obtidos a partir de laboratórios de patologia clínica, os tecidos FFPE de adenocarcinomas sêmulas ovarianas de alto grau foram armazenados de 7 a 32 anos em condições variadas antes da extração do RNA. Como na maioria dos casos esses blocos foram armazenados em diferentes locais durante anos sem a expectativa de qualquer análise genética sensível no futuro, pouco cuidado havia sido tomado para preservar os ácidos nucleicos. Assim, a maioria das amostras apresentava RNA de má qualidade, com grande proporção de amostras contaminadas com bactérias. No entanto, conseguimos realizar quantificação genética, medir a uniformidade e a continuidade da cobertura genética e realizar a análise de correlação de Pearson entre réplicas biológicas para medir a reprodutibilidade. Com base em um conjunto de painéis genéticos de assinatura chave, comparamos as amostras em nosso estudo com os dados do Atlas do Genoma do Câncer (TCGA) e confirmamos que aproximadamente 60% das amostras tinham perfis de expressão genética comparáveis11. Com base na correlação entre vários resultados de QC e metadados amostrais, identificamos métricas-chave de QC que têm bom valor preditivo para identificar amostras mais propensas a gerar dados de sequência utilizáveis11.
Descrevemos aqui a metodologia utilizada para avaliação da qualidade ffpe-RNA, geração de bibliotecas de sequenciamento a partir de amostras de RNA extraídas e análise bioinformática dos dados de sequenciamento.

<table>
	<tbody>
		<tr>
			<td>2100 Bioanalyzer</td>
			<td>Agilent</td>
			<td>G2939BA</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent DNA 7500 Kit</td>
			<td>Agilent</td>
			<td>5067-1506</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent High Sensitivity DNA Kit</td>
			<td>Agilent</td>
			<td>5067-4626</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent RNA 6000 Nano Kit</td>
			<td>Agilent</td>
			<td>5067-1511</td>
			<td></td>
		</tr>
		<tr>
			<td>AllPrep DNA/RNA FFPE Kit</td>
			<td>Qiagen</td>
			<td>80234</td>
			<td></td>
		</tr>
		<tr>
			<td>CFX96 Touch System</td>
			<td>Bio-Rad</td>
			<td>1855195</td>
			<td></td>
		</tr>
		<tr>
			<td>Library Quantification kit v2-Illumina</td>
			<td>KapaBiosystems</td>
			<td>KK4824</td>
			<td></td>
		</tr>
		<tr>
			<td>NEBNext Ultra II Directional RNA Library Prep Kit for Illumina</td>
			<td>New England Biolabs</td>
			<td>E7765S</td>
			<td>https://www.neb.com/protocols/2017/02/07/protocol-for-use-with-ffpe-rna-nebnext-rrna-depletion-kit</td>
		</tr>
		<tr>
			<td>NEBNext rRNA Depletion Kit (Human/Mouse/Rat)</td>
			<td>New England Biolabs</td>
			<td>E6310L</td>
			<td></td>
		</tr>
		<tr>
			<td>NextSeq 500 Sequencing System</td>
			<td>Illumina</td>
			<td>SY-415-1001</td>
			<td>NextSeq 500 System guide: https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/nextseq/nextseq-500-system-guide-15046563-06.pdf</td>
		</tr>
		<tr>
			<td>NextSeq PhiX Control Kit</td>
			<td>Illumina</td>
			<td>FC-110-3002</td>
			<td></td>
		</tr>
		<tr>
			<td>NSQ 500/550 Hi Output KT v2.5 (150 CYS)</td>
			<td>Illumina</td>
			<td>20024907</td>
			<td></td>
		</tr>
		<tr>
			<td>10X Genomics Magnetic Separator</td>
			<td>10X Genomics</td>
			<td>120250</td>
			<td></td>
		</tr>
		<tr>
			<td>Rotator Multimixer</td>
			<td>VWR</td>
			<td>13916-822</td>
			<td></td>
		</tr>
		<tr>
			<td>C1000 Touch Thermal Cycler</td>
			<td>Bio-Rad</td>
			<td>1851197</td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing reagent kit</td>
			<td>Illumina</td>
			<td>20024907</td>
			<td></td>
		</tr>
		<tr>
			<td>Flow cell package</td>
			<td>Illumina</td>
			<td>20024907</td>
			<td></td>
		</tr>
		<tr>
			<td>Buffer cartridge and the reagent cartridge</td>
			<td>Illumina</td>
			<td>20024907</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium hydroxide solution (0.2N)</td>
			<td>Millipore Sigma</td>
			<td>SX0607D-6</td>
			<td></td>
		</tr>
		<tr>
			<td>TRIS-HCL Buffer 1.0M, pH 7.0</td>
			<td>Fisher Scientific</td>
			<td>50-151-871</td>
			<td></td>
		</tr>
	</tbody>
</table>

optimization for sequencing and analysis of degraded ffpe-rna samples

A análise da expressão genética pelo sequenciamento de RNA (RNA-seq) permite insights únicos em amostras clínicas que podem potencialmente levar à compreensão mecanicista da base de várias doenças, bem como mecanismos de resistência e/ou suscetibilidade. No entanto, os tecidos FFPE, que representam o método mais comum para preservar a morfologia tecidual em amostras clínicas, não são as melhores fontes para a análise de perfil de expressão genética. O RNA obtido a partir dessas amostras é muitas vezes degradado, fragmentado e quimicamente modificado, o que leva a bibliotecas de sequenciamento subótimo. Por sua vez, estes geram dados de sequência de baixa qualidade que podem não ser confiáveis para análise de expressão genética e descoberta de mutação. Para aproveitar ao máximo as amostras de FFPE e obter os melhores dados possíveis a partir de amostras de baixa qualidade, é importante tomar certas precauções enquanto planeja o projeto experimental, preparando bibliotecas de sequenciamento e durante a análise de dados. Isso inclui o uso de métricas apropriadas para controle preciso de qualidade de amostra (QC), identificando os melhores métodos para várias etapas durante a geração da biblioteca de sequenciamento e o QC cuidadoso da biblioteca. Além disso, a aplicação de ferramentas e parâmetros de software corretos para análise de dados de sequência é fundamental para identificar artefatos em dados RNA-seq, filtrar a contaminação e leituras de baixa qualidade, avaliar a uniformidade da cobertura genética e medir a reprodutibilidade dos perfis de expressão genética entre as réplicas biológicas. Essas etapas podem garantir alta precisão e reprodutibilidade para o perfil de amostras de RNA muito heterogêneas. Aqui descrevemos as várias etapas para a amostra QC, preparação da biblioteca e QC, sequenciamento e análise de dados que podem ajudar a aumentar a quantidade de dados úteis obtidos a partir de RNA de baixa qualidade, como o obtido a partir de tecidos FFPE-RNA.

A metodologia descrita acima foi aplicada a 67 amostras de FFPE armazenadas sob uma variedade de condições diferentes durante 7-32 anos (o tempo médio de armazenamento amostral foi de 17,5 anos). Os resultados de conjunto de dados e análise aqui apresentados foram previamente descritos e publicados em Zhao et al.11. Ao verificar a qualidade da amostra descrita anteriormente (ou seja, traços de exemplo na Figura 2), o DV100 foi considerado mais útil do...

Watch this Scientific Journal Video about Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples at JoVE.com

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Este método descreve as etapas para melhorar a qualidade e a quantidade de dados sequenciais que podem ser obtidos a partir de amostras de RNA incorporadas à parafina fixa-formalina (FFPE). Descrevemos a metodologia para avaliar com mais precisão a qualidade das amostras de FFPE-RNA, preparar bibliotecas de sequenciamento e analisar os dados das amostras de FFPE-RNA.

Otimização para Sequenciamento e Análise de Amostras de RNA FFPE-RNA degradadas

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding ...

Nosso protocolo pode ser usado para melhorar a qualidade e a quantidade de dados de expressão genética gerados a partir de amostras de RNA derivadas do FFPE, especialmente em amostras de qualidade subótima. Esta técnica avalia a qualidade do RNA dentro das amostras de tecido FFPE e permite a otimização de seu processamento a jusante para melhorar a quantidade e a qualidade dos dados de sequenciamento da amostra. Este método permite a caracterização abrangente de uma transcrição em amostra biológica e clínica e pode fornecer insights sobre elementos funcionais do genoma em desenvolvimento e doenças.A degradação do FFPE-RNA e a seleção dos métodos para QC amostral, preparação da biblioteca e análise de dados podem ser muito complicadas. Seja meticuloso ao selecionar os métodos certos e controles apropriados. A demonstração visual permite que os espectadores observem as pequenas modificações sutis e precauções necessárias durante o planejamento, avaliação e o processo de sequenciamento especialmente para amostras de FFPE mal preservadas.Para verificar a qualidade da amostra de RNA, execute a amostra em um sistema RNA QC de acordo com as instruções do fabricante e use o software de bioanálise apropriado para analisar a distribuição dos fragmentos de RNA dentro da amostra e calcular a proporção de fragmentos maiores que 100 e 200 nucleotídeos. Com base nas métricas do QC, identifique as amostras com menos de 40% dos fragmentos com mais de 100 nucleotídeos para permitir a exclusão dessas amostras do processamento. Para sequenciamento, descongele os kits apropriados de sequenciamento de reagente de acordo com os parâmetros de execução em um banho de água de temperatura ambiente e coloque a bandeja de reagente a quatro graus Celsius após o descongelamento.Coloque o pacote da célula de fluxo em temperatura ambiente por 30 minutos. Enquanto o pacote estiver aquecendo, abra o aplicativo Illumina Experiment Manager e selecione Criar folha de amostra. Selecione o sequenciador a ser usado e clique em Next.Digite o código de barras do kit de reagente e os outros parâmetros apropriados de fluxo de trabalho. Em seguida, carregue uma folha de amostra criada de acordo com os critérios de sequência de Illumina. Para preparar a biblioteca de amostras e a biblioteca de controle PhiX, desnaturar e diluir as bibliotecas para as concentrações apropriadas e misturar as bibliotecas de controle amostral e PhiX para obter uma razão de volume de controle PhiX de 5%.Quando as células de fluxo estiverem prontas, remova o embrulho, limpe a superfície do vidro com um lenço de álcool sem fiapos e seque o vidro com um tecido de laboratório de fiapos baixos. Remova o cartucho de reagente de quatro graus Celsius de armazenamento e inverta o cartucho cinco vezes para misturar os reagentes. Toque suavemente o cartucho no banco para reduzir as bolhas de ar e carregue a amostra desnaturada e diluída no cartucho de reagente no reservatório designado.Carregue a célula de fluxo, o cartucho tampão e o cartucho do reagente no sistema. Em seguida, realize uma verificação automatizada e revise a saída para garantir que os parâmetros de execução passem pela verificação do sistema. Quando a verificação automatizada estiver concluída, selecione iniciar a execução de sequenciamento.Para visualizar os resultados de QC pré-processamento e QC pós-alinhamento, execute vários QCs para gerar um relatório agregado em formato HTML. Para determinar os efeitos em lote e avaliar o mapa de qualidade do conjunto de dados dado, use um script R para executar uma análise de componente principal. A análise da correlação amostral pode então ser realizada utilizando-se a correlação de Pearson entre diferentes amostras.A estimativa da proporção de fragmentos com mais de 100 nucleotídeos é mais útil do que uma estimativa dos fragmentos com mais de 200 nucleotídeos, pois é mais sensível para medir com precisão a proporção de tamanhos de fragmentos menores para amostras de RNA altamente degradadas. Dado o alto grau de degradação no conjunto amostral, recomenda-se um método total de preparação da biblioteca de RNA. Por exemplo, aqui são mostradas bibliotecas de sequenciamento preparadas a partir de quatro amostras diferentes.Aqui, são mostradas visões gerais da qualidade de sequenciamento de arquivos FastQ bruta e conteúdo do adaptador de amostra. A triagem fastqc pode ajudar a detectar contaminação, como contaminação bacteriana ou de camundongos dentro das amostras. O alinhamento estelar pode ser usado para determinar a proporção de leituras mapeadas para o genoma de referência, a porcentagem de leituras mapeadas exclusivamente para o genoma de referência, e a proporção de leituras que não foram mapeadas, ou que foram mapeadas para vários loci.As estatísticas do cartão e do RSeQC podem ser usadas para determinar a porcentagem de RNAs mensageiros, bases intronicas e intergênicas presentes nas leituras mapeadas. Para essas análises representativas, algumas bibliotecas degradadas tinham um viés de três primos em que mais leituras foram mapeadas mais perto dos três primos do que do fim cinco primos. Além disso, a análise dos componentes principais pode ser realizada para determinar a porcentagem da variação total capturada pelos componentes principais para as réplicas biológicas de cada amostra.Tome cuidado para evitar a degradação da amostra, prepare réplicas e vários casacos para cada amostra, use as métricas apropriadas para avaliar a qualidade da amostra e use o método de preparação da biblioteca correta. Utilizando essa metodologia, estudos maiores de NGS podem ser realizados com amostras de FFPE anteriormente inutilizáveis com diferentes tempos de armazenamento e condições para obter insights sobre uma variedade de diferentes estados da doença. Essa técnica abriu caminho para os pesquisadores estudarem grandes arquivos existentes da amostra FFPE com informações clínicas ricas e podem melhorar muito os estudos sobre câncer de base populacional.

optimization-for-sequencing-and-analysis-of-degraded-ffpe-rna-samples

Research

JoVE Journal

Genetics

Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically comprise less than 1% of the tumor mass. Material derived from bulk tumor contains tumor content at a concentration insufficient for characterization. Therefore, fluorescence activated cell sorting using eight antibodies, as well as side- and forward-scatter, is described here as a method of rapidly separating and concentrating with high purity thousands of HRS cells from the tumor for subsequent study. At the same time, because standard protocols for exome sequencing typically require 100-1,000 ng of input DNA, which is often too high, even with flow sorting, we also provide an optimized, low-input library construction protocol capable of producing high-quality data from as little as 10 ng of input DNA. This combination is capable of producing next-generation libraries suitable for hybridization capture of whole-exome baits or more focused targeted panels, as desired. Exome sequencing of the HRS cells, when compared against healthy intratumor T or B cells, can identify somatic alterations, including mutations, insertions and deletions, and copy number alterations. These findings elucidate the molecular biology of HRS cells and may reveal avenues for targeted drug treatments.

Here, we describe a combined flow cytometric cell sorting and low-input, next-generation library construction protocol designed to produce high-quality, whole-exome data from the Hodgkin Reed-Sternberg (HRS) cells of classical Hodgkin lymphoma (CHL).

Classificação de fluxo e sequenciação Exome das células de Reed-Sternberg do linfoma de Hodgkin clássico

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically ...

Genética

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and microbial populations. Traditional methods for assessing genetic heterogeneity have been limited by low resolution, low sensitivity, and/or low specificity. Single cell sequencing has emerged as a powerful tool for detecting genetic heterogeneity with high resolution, high sensitivity and, when appropriately analyzed, high specificity. Here we provide a protocol for the isolation, whole genome amplification, sequencing, and analysis of single cells. Our approach allows for the reliable identification of megabase-scale copy number variants in single cells. However, aspects of this protocol can also be applied to investigate other types of genetic alterations in single cells.

Single cell sequencing is an increasingly popular and accessible tool for addressing genomic changes at high resolution. We provide a protocol that uses single cell sequencing to identify copy number alterations in single cells.

Detecção de Copy Number Alterações Usando Sequencing única célula

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and ...

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic fragments. Organellar genomes also exist in admixtures within a given cell or tissue type (heteroplasmy), and an abundance of subtypes may change throughout development or when under stress (sub-stoichiometric shifting). Next-generation sequencing (NGS) technologies are required to obtain deeper understanding of organellar genome structure and function. Traditional sequencing studies use several methods to obtain organellar DNA: (1) If a large amount of starting tissue is used, it is homogenized and subjected to differential centrifugation and/or gradient purification. (2) If a smaller amount of tissue is used (i.e., if seeds, material, or space is limited), the same process is performed as in (1), followed by whole-genome amplification to obtain sufficient DNA. (3) Bioinformatics analysis can be used to sequence the total genomic DNA and to parse out organellar reads. All these methods have inherent challenges and tradeoffs. In (1), it may be difficult to obtain such a large amount of starting tissue; in (2), whole-genome amplification could introduce a sequencing bias; and in (3), homology between nuclear and organellar genomes could interfere with assembly and analysis. In plants with large nuclear genomes, it is advantageous to enrich for organellar DNA to reduce sequencing costs and sequence complexity for bioinformatics analyses. Here, we compare a traditional differential centrifugation method with a fourth method, an adapted CpG-methyl pulldown approach, to separate the total genomic DNA into nuclear and organellar fractions. Both methods yield sufficient DNA for NGS, DNA that is highly enriched for organellar sequences, albeit at different ratios in mitochondria and chloroplasts. We present the optimization of these methods for wheat leaf tissue and discuss major advantages and disadvantages of each approach in the context of sample input, protocol ease, and downstream application.

The comparison and optimization of two plant organellar DNA enrichment methods are presented: traditional differential centrifugation and fractionation of the total gDNA based on methylation status. We assess the resulting DNA quantity and quality, demonstrate performance in short-read next-generation sequencing, and discuss the potential for use in long-read single-molecule sequencing.

Otimização e Análise Comparativa de Métodos de Enriquecimento de DNA de Plantas Organizadas Adequado para Seqüenciamento de Próxima Geração

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic ...

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution based analysis methodology (nucleosome density ChIP-seq; ndChIP-seq) that enables the generation of combined measurements of micrococcal nuclease (MNase) accessibility with histone modification genome-wide. Nucleosome position and local density, and the posttranslational modification of their histone subunits, act in concert to regulate local transcription states. Combinatorial measurements of nucleosome accessibility with histone modification generated by ndChIP-seq allows for the simultaneous interrogation of these features. The ndChIP-seq methodology is applicable to small numbers of primary cells inaccessible to cross-linking based ChIP-seq protocols. Taken together, ndChIP-seq enables the measurement of histone modification in combination with local nucleosome density to obtain new insights into shared mechanisms that regulate RNA transcription within rare primary cell populations.

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) methodology for the generation of sequence datasets suitable for a nucleosome density ChIP-seq analytical framework integrating micrococcal nuclease (MNase) accessibility with histone modification measurements.

Geração de imunoprecipitação da cromatina nativa sequenciamento de bibliotecas para análise da densidade nucleossoma

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution ...

Chromatin Immunoprecipitation (ChIP) Protocol for Low-abundance Embryonic Samples

Chromatin immunoprecipitation (ChIP) is a widely-used technique for mapping the localization of post-translationally modified histones, histone variants, transcription factors, or chromatin-modifying enzymes at a given locus or on a genome-wide scale. The combination of ChIP assays with next-generation sequencing (i.e., ChIP-Seq) is a powerful approach to globally uncover gene regulatory networks and to improve the functional annotation of genomes, especially of non-coding regulatory sequences. ChIP protocols normally require large amounts of cellular material, thus precluding the applicability of this method to investigating rare cell types or small tissue biopsies. In order to make the ChIP assay compatible with the amount of biological material that can typically be obtained in vivo during early vertebrate embryogenesis, we describe here a simplified ChIP protocol in which the number of steps required to complete the assay were reduced to minimize sample loss. This ChIP protocol has been successfully used to investigate different histone modifications in various embryonic chicken and adult mouse tissues using low to medium cell numbers (5 x 104 - 5 x 105 cells). Importantly, this protocol is compatible with ChIP-seq technology using standard library preparation methods, thus providing global epigenomic maps in highly relevant embryonic tissues.

Chromatin Immunoprecipitation ChIP Protocol for Low-abundance Embryonic Samples

Here, we describe a chromatin immunoprecipitation (ChIP) and ChIP-seq library preparation protocol to generate global epigenomic profiles from low-abundance chicken embryonic samples.

Cromatina (ChIP) imunoprecipitação para baixo-abundância embrionárias amostras

Chromatin immunoprecipitation (ChIP) is a widely-used technique for mapping the localization of post-translationally modified histones, histone variants, ...

Robust DNA Isolation and High-throughput Sequencing Library Construction for Herbarium Specimens

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

Isolamento do DNA robusto e construção de biblioteca de sequenciamento de alto rendimento para espécimes de herbário

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been used to analyze the spectrum of clonal mutations in malignancy. Though far more efficient than traditional Sanger methods, NGS struggles with identifying rare clonal and subclonal mutations due to its high error rate of ~0.5&#8211;2.0%. Thus, standard NGS has a limit of detection for mutations that are &#62;0.02 variant allele fraction (VAF). While the clinical significance for mutations this rare in patients without known disease remains unclear, patients treated for leukemia have significantly improved outcomes when residual disease is &#60;0.0001 by flow cytometry. In order to mitigate this artefactual background of NGS, numerous methods have been developed. Here we describe a method for Error-corrected DNA and RNA Sequencing (ECS), which involves tagging individual molecules with both a 16 bp random index for error-correction and an 8 bp patient-specific index for multiplexing. Our method can detect and track clonal mutations at variant allele fractions (VAFs) two orders of magnitude lower than the detection limit of NGS and as rare as 0.0001 VAF.

Next-generation sequencing (NGS) is a powerful tool for genomic characterization that is limited by the high error rate of the platform (~0.5&#8211;2.0%). We describe our methods of error-corrected sequencing that allow us to obviate the NGS error rate and detect mutations at variant allele fractions as rare as 0.0001.

Deteção de evento raro usando o DNA de correção de erro e a sequenciação do ARN

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been ...

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near full-length (intact and defective), HIV-1 proviruses. FLIPS allows determination of the genetic composition of integrated HIV-1 within a cell population. Through identifying defects within HIV-1 proviral sequences that arise during reverse transcription, such as large internal deletions, deleterious stop codons/hypermutation, frameshift mutations, and mutations/deletions in cis acting elements required for virion maturation, FLIPS can identify integrated proviruses incapable of replication. The FLIPS assay can be utilized to identify HIV-1 proviruses that lack these defects and are&#160;therefore potentially replication-competent. The FLIPS protocol involves: lysis of HIV-1 infected cells, nested PCR of near full-length HIV-1 proviruses (using primers targeted to the HIV-1 5&#39; and 3&#39; LTR), DNA purification and quantification, library preparation for Next-generation Sequencing (NGS), NGS, de novo assembly of proviral contigs, and a simple process of elimination for identifying replication-competent proviruses. FLIPS provides advantages over traditional methods designed to sequence integrated HIV-1 proviruses, such as single-proviral sequencing. FLIPS amplifies and sequences near full-length proviruses enabling replication competency to be determined, and also uses fewer amplification primers, preventing the consequences of primer mismatches. FLIPS is a useful tool for understanding the genetic landscape of integrated HIV-1 proviruses, especially within the latent reservoir, however, its utilization can extend to any application in which the genetic composition of integrated HIV-1 is required.

Full-length individual proviral sequencing (FLIPS) provides an efficient and high-throughput method for the amplification and sequencing of single, near full-length (intact and defective) HIV-1 proviruses and allows for determination of their potential replication-competency. FLIPS overcomes limitations of previous assays designed to sequence the latent HIV-1 reservoir.

Amplificação de perto completos provírus HIV-1 para a próxima geração de sequenciamento

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near ...

Semiconductor Sequencing for Preimplantation Genetic Testing for Aneuploidy

Chromosomal aneuploidy, one of the main causes leading to embryonic development arrest, implantation failure, or pregnancy loss, has been well documented in human embryos. Preimplantation genetic testing for aneuploidy (PGT-A) is a genetic test that significantly improves reproductive outcomes by detecting chromosomal abnormalities of embryos. Next-generation sequencing (NGS) provides a high-throughput and cost-effective approach for genetic analysis and has shown clinical applicability in PGT-A. Here, we present a rapid and low-cost semiconductor sequencing-based NGS method for screening of aneuploidy in embryos. The first step of the workflow is whole genome amplification (WGA) of the biopsied embryo specimen, followed by construction of sequencing library, and subsequent sequencing on the semiconductor sequencing system. Generally, for a PGT-A application, 24 samples can be loaded and sequenced on each chip generating 60&#8722;80 million reads at an average read length of 150 base pairs. The method provides a refined protocol for performing template amplification and enrichment of sequencing library, making the PGT-A detection reproducible, high-throughput, cost-efficient, and timesaving. The running time of this semiconductor sequencer is only 2&#8722;4 hours, shortening the turnaround time from receiving samples to issuing reports into 5 days. All these advantages make this assay an ideal method to detect chromosomal aneuploidies from embryos and thus, facilitate its wide application in PGT-A.

Here, we introduce a semiconductor sequencing method for preimplantation genetic testing for aneuploidy (PGT-A) with the advantages of short turnaround time, low cost, and high throughput.

Sequenciamento de semicondutores para teste genético pré-implante para aneuploidia

Chromosomal aneuploidy, one of the main causes leading to embryonic development arrest, implantation failure, or pregnancy loss, has been well documented ...

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, and was deployed to West Africa during the recent Ebola virus epidemic, highlighting this possibility. In addition to its practical advantages (low cost, ease of equipment transport and use), this technology also provides fundamental advantages over second-generation sequencing approaches, particularly the very long read length, ability to directly sequence RNA, and real-time availability of data. Raw read accuracy is lower than with other sequencing platforms, which represents the main limitation of this technology; however, this can be partially mitigated by the high read depth generated. Here, we present a field-compatible protocol for sequencing of the mRNAs encoding for Niemann-Pick C1, which is the cellular receptor for ebolaviruses. This protocol encompasses extraction of RNA from animal blood samples, followed by RT-PCR for target enrichment, barcoding, library preparation, and the sequencing run itself, and can be easily adapted for use with other DNA or RNA targets.

Nanopore sequencing is a novel technology that allows cost-effective sequencing in remote locations and resource-poor settings. Here, we present a protocol for sequencing of mRNAs from whole blood that is compatible with such conditions.

Sequenciamento de mRNA de sangue total usando sequenciamento de nanoporos

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, ...