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.

<ol>
	<li>Wang, Z., Gerstein, M., Snyder, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-Seq:+a+revolutionary+tool+for+transcriptomics.">RNA-Seq: a revolutionary tool for transcriptomics.</a> Nat Rev Genet. 10, 57-63 (2009).</li><li>Mercer, T. R., 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=Targeted+sequencing+for+gene+discovery+and+quantification+using+RNA+CaptureSeq.">Targeted sequencing for gene discovery and quantification using RNA CaptureSeq.</a> Nat Protoc. 9, 989-1009 (2014).</li><li>Maher, C. 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=Chimeric+transcript+discovery+by+paired-end+transcriptome+sequencing.">Chimeric transcript discovery by paired-end transcriptome sequencing.</a> Proc Natl Acad Sci U S A. 106, 12353-12358 (2009).</li><li>Piskol, R., Ramaswami, G., Li, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliable+identification+of+genomic+variants+from+RNA-seq+data.">Reliable identification of genomic variants from RNA-seq data.</a> Am J Hum Genet. 93, 641-651 (2013).</li><li>Quinn, E. 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=Development+of+strategies+for+SNP+detection+in+RNA-seq+data:+application+to+lymphoblastoid+cell+lines+and+evaluation+using+1000+Genomes+data.">Development of strategies for SNP detection in RNA-seq data: application to lymphoblastoid cell lines and evaluation using 1000 Genomes data.</a> PLoS One. 8, e58815 (2013).</li><li>Tang, 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=The+eSNV-detect:+a+computational+system+to+identify+expressed+single+nucleotide+variants+from+transcriptome+sequencing+data.">The eSNV-detect: a computational system to identify expressed single nucleotide variants from transcriptome sequencing data.</a> Nucleic Acids Res. 42, e172 (2014).</li><li>. Preparing Libraries for Sequencing on the MiSeq&#174; Available from: <a target="_blank" href="https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/miseq/preparing-libraries-for-sequencing-on-miseq-15039740-d.pdf">https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/miseq/preparing-libraries-for-sequencing-on-miseq-15039740-d.pdf</a> (2013)</li><li>. MiSeq&#174; Reagent Kit v2 Reagen Preparation Guide Available from: <a target="_blank" href="https://support.illumina.com/downloads/miseq_reagent_kit_reagent_preparation_guide.html">https://support.illumina.com/downloads/miseq_reagent_kit_reagent_preparation_guide.html</a> (2012)</li><li>Kim, 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=TopHat2:+accurate+alignment+of+transcriptomes+in+the+presence+of+insertions,+deletions+and+gene+fusions.">TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions.</a> Genome Biol. 14, R36 (2013).</li><li>Li, H., 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=The+Sequence+Alignment/Map+format+and+SAMtools.">The Sequence Alignment/Map format and SAMtools.</a> Bioinformatics. 25, 2078-2079 (2009).</li><li>DeLuca, D. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-SeQC:+RNA-seq+metrics+for+quality+control+and+process+optimization.">RNA-SeQC: RNA-seq metrics for quality control and process optimization.</a> Bioinformatics. 28, 1530-1532 (2012).</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, 15-21 (2013).</li><li>Van der Auwera, G. 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=From+FastQ+data+to+high+confidence+variant+calls:+the+Genome+Analysis+Toolkit+best+practices+pipeline.">From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline.</a> Curr Protoc Bioinformatics. 11, 11.10.1-11.10.33 (2013).</li><li>Trapnell, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transcript+assembly+and+quantification+by+RNA-Seq+reveals+unannotated+transcripts+and+isoform+switching+during+cell+differentiation.">Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation.</a> Nat Biotechnol. 28, 511-515 (2010).</li><li>Iyer, M. K., Chinnaiyan, A. M., Maher, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ChimeraScan:+a+tool+for+identifying+chimeric+transcription+in+sequencing+data.">ChimeraScan: a tool for identifying chimeric transcription in sequencing data.</a> Bioinformatics. 27, 2903-2904 (2011).</li><li>Kim, D., 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=TopHat-Fusion:+an+algorithm+for+discovery+of+novel+fusion+transcripts.">TopHat-Fusion: an algorithm for discovery of novel fusion transcripts.</a> Genome Biol. 12, R72 (2011).</li><li>Fernandez-Cuesta, L., 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+of+novel+fusion+genes+in+lung+cancer+using+breakpoint+assembly+of+transcriptome+sequencing+data.">Identification of novel fusion genes in lung cancer using breakpoint assembly of transcriptome sequencing data.</a> Genome Biol. 16, 7 (2015).</li><li>Shugay, M., Ortiz de Mendibil, ., Vizmanos, I., L, J., Novo, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Oncofuse:+a+computational+framework+for+the+prediction+of+the+oncogenic+potential+of+gene+fusions.">Oncofuse: a computational framework for the prediction of the oncogenic potential of gene fusions.</a> Bioinformatics. 29, 2539-2546 (2013).</li><li>Clark, M. B., 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=Quantitative+gene+profiling+of+long+noncoding+RNAs+with+targeted+RNA+sequencing.">Quantitative gene profiling of long noncoding RNAs with targeted RNA sequencing.</a> Nat Methods. 12, 339-342 (2015).</li><li>Cieslik, 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=The+use+of+exome+capture+RNA-seq+for+highly+degraded+RNA+with+application+to+clinical+cancer+sequencing.">The use of exome capture RNA-seq for highly degraded RNA with application to clinical cancer sequencing.</a> Genome Res. , (2015).</li><li>Cabanski, C. R., 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=cDNA+hybrid+capture+improves+transcriptome+analysis+on+low-input+and+archived+samples.">cDNA hybrid capture improves transcriptome analysis on low-input and archived samples.</a> J Mol Diagn. 16, 440-451 (2014).</li><li>Costa, C., Gimenez-Capitan, A., Karachaliou, N., Rosell, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comprehensive+molecular+screening:+from+the+RT-PCR+to+the+RNA-seq.">Comprehensive molecular screening: from the RT-PCR to the RNA-seq.</a> Transl Lung Cancer Res. 2, 87-91 (2013).</li><li>Zhao, W., 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=Comparison+of+RNA-Seq+by+poly+(A)+capture,+ribosomal+RNA+depletion,+and+DNA+microarray+for+expression+profiling.">Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling.</a> BMC Genomics. 15, 419 (2014).</li></ol>

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.

RNAseq Capture is an intermediate strategy between RNAseq and microarray approaches for evaluating a selected part of the transcriptome. The advantages of Capture include reduced cost, rapid turnaround time on a desktop sequencer, high throughput, and detection of genomic alterations. The method can be adapted to characterize non-coding RNAs23, detect single nucleotide variants4-6, examine RNA splicing, and to identify gene fusions or structural rearrangements24. Further, this approach ca...

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>
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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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			<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>
			<td style="width:143px;"></td>
			<td></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>
		</tr>
		<tr height="40">
			<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>
		</tr>
		<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>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Dynabeads&#174; M-270 Streptavidin</td>
			<td>Life Technologies</td>
			<td>65305</td>
			<td></td>
		</tr>
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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>
		</tr>
		<tr height="20">
			<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>
		</tr>
		<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>
		<tr height="20">
			<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

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding RNAs. Standard RNAseq requires 30 - 100 million sequencing reads and can include multiple RNA products such as mRNA and noncoding RNAs. We demonstrate how targeted RNAseq (capture) permits a focused study on selected RNA products using a desktop sequencer. RNAseq capture can characterize unannotated, low, or transiently expressed transcripts that may otherwise be missed using traditional RNAseq methods. Here we describe the extraction of RNA from cell lines, ribosomal RNA depletion, cDNA synthesis, preparation of barcoded libraries, hybridization and capture of targeted transcripts and multiplex sequencing on a desktop sequencer. We also outline the computational analysis pipeline, which includes quality control assessment, alignment, fusion detection, gene expression quantification and identification of single nucleotide variants. This assay allows for targeted transcript sequencing to characterize gene expression, gene fusions, and mutations.

A schematic highlighting key steps in RNAseq Capture is shown in Figure 1. Four cancer cell lines with known mutations were used to demonstrate the effectiveness of the RNAseq Capture technique (K562 with ABL1 fusion, LC2 with RET fusion, EOL1 with PDGFRalpha fusion and RT-4 with FGFR3 fusion). The four samples were pooled together and sequenced with 2x 100 bp reads on a desktop sequencer, which generates FASTQ files. FASTQ files were r...

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.

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

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10.3K Views.  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.

Video: 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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.