This work was supported by R01DK102001 (N.A.Z.), P30DK072488 (N.A.Z.), and T32DK098107 (T.L.H. and J.E.N.).

All animal protocols outlined below are in accordance with and approved by the University of Maryland Institutional Animal Care and Use Committee (IACUC).
1. Embryo Preparation
<ol>
	<li>Generating embryos through natural mating
	<ol>
		<li>Culture embryos to 3 months of age, reproductive maturity5,8.</li>
		<li>Segregate adult male and female fish from the desired strain into divided mating tanks on the evening before embryo collection, and add 2 males and 3 females to each tank. 
		NOTE: Use of the transgenic insulin2a:mCherry fluorescent reporter strain allowed the analysis of pancreatic &#946;-cells.</li>
		<li>Transfer fish to the mating tank with fresh system water and remove the divider immediately after the lights come on the following morning.</li>
		<li>Allow the fish to mate naturally until embryos are observed in bottom tank. Collect embryos in 30 min intervals until the desired amount is collected. Store each collected time point in separate Petri dishes in embryo media at 28.5 &#176;C.</li>
		<li>Perform microinjection of genetic material or placement in experimental culture media6, if desired, and culture the embryos in fresh Hank&#39;s embryo medium8 in 10-cm Petri dishes at 28.5 &#176;C. 
		NOTE: For gene expression analysis in morpholino (MO) injected or mutant animals, note that each manipulation may have incidental impacts on gene expression. Mutants can exhibit genetic compensation at the level of transcription that is not observed by MO-based gene targeting9.</li>
	</ol>
	</li>
	<li>Stage embryos
	<ol>
		<li>Culture the embryos in groups of 50&#8211;75 embryos per 10-cm Petri dish to promote consistent developmental timing of all embryos.</li>
		<li>Monitor the developmental morphology using dissecting microscope at blastomere, epiboly, and somite stages to ensure developmental progression10. 
		NOTE: Remove any dying or malformed embryos to prevent developmental delay in the dish.</li>
		<li>Separate the embryos based on the developmental age. Measure the embryo age using somite number after segmentation (post-gastrulation, 10.33 h post fertilization (hpf)) until approximately 24 hpf. Stage the embryos and larvae using total body length after 24 hpf. 
		NOTE: The somites are the chevron-shaped mesodermal tissue present on the dorsal part of the embryo.</li>
		<li>Place the sorted embryos into a 28.5 &#176;C incubator and allow development to progress to the desired age.</li>
	</ol>
	</li>
</ol>
2. Single-cell Dissociation: Whole Embryo and Sorted Cell Populations
<ol>
	<li>Whole embryo dissociation
	<ol>
		<li>Euthanize the zebrafish embryos at the desired stage by placing the Petri dish on ice for 5-15 min until no movement is observed.</li>
		<li>Transfer a pool of 20 embryos to a labeled 1.5 mL microcentrifuge tube. Remove any excess embryo media from the microcentrifuge tube.</li>
		<li>Add 200 &#181;L lysis reagent (see Table of Materials) to the tube containing embryos. Homogenize the embryos in lysis reagent mechanically using a pestle. Add 800 &#181;L lysis reagent to bring the total volume to 1 mL. Store at -80 &#176;C until RNA extraction.</li>
	</ol>
	</li>
	<li>Flow-sorted cell isolation11
	<ol>
		<li>Transfer the embryos from the Petri dish into a 1.5 mL microcentrifuge tube and remove as much embryo medium as possible. 
		NOTE: Depending on the embryo age, mechanical dissociation may also be required at this step. With embryos &#62; 48 hpf, we recommend the use of a pestle to disrupt embryo integrity before proceeding.</li>
		<li>Incubate the embryos with 1 mL of dissociation buffer 1 (see Table of Materials) in 1.5 mL microcentrifuge tube. Incubate for 15-30 min at room temperature. Triturate the solution by gently pipetting up and down using a P1000 tip to mix every 3-4 min during the incubation step. DO NOT VORTEX.</li>
		<li>Collect the embryos by centrifugation for 3 min at 300 x g and remove the supernatant. Re-suspend the embryos in 1 mL dissociation buffer 2 (see Table of Materials). Incubate for 15-30 min at room temperature with regular pipet trituration.</li>
		<li>Assess the digestion by diluting 1-2 &#181;L of suspension in fluorescence-activated cell sorting (FACS) buffer under microscope. 
		NOTE: Complete digestion has occurred when the examined aliquot shows single cells with minimal cell clusters and pieces of embryonic tissue.</li>
		<li>Collect the cells by centrifugation at 300 x g for 5 min. Remove supernatant. Re-suspend the cells into 1 mL FACS buffer, and gravity filter through a 40 &#181;m cell strainer to remove undigested tissue from the sample.</li>
		<li>Count the cells using a hemocytometer and dilute with FACS buffer to approximately 1x 106 cells/mL in a FACS tube. 
		NOTE: For cell types with a relatively small number per embryo (less than 5% of total), such as pancreatic &#946;-cells, use a minimum of 1,000 stage-matched embryos.</li>
		<li>Provide the FACS sorting facility with the FACS tubes containing 1 mL of cell suspension samples as well as FACS tube containing only lysis reagent or FACS Buffer. Gate the FACS flow-sorter to collect only single cells that express the fluorescent reporter.</li>
		<li>Perform the FACS flow-sorting until the desired cell numbers have been collected. 
		NOTE: To perform RNASeq, there is a minimum total RNA required. We have found that 3,000-5,000 cells are sufficient to isolate high-quality, high-concentration RNA.</li>
		<li>Store the collected cells on ice and proceed immediately to RNA preparation.</li>
	</ol>
	</li>
</ol>
3. RNA Preparation
<ol>
	<li>Extract RNA
	<ol>
		<li>Incubate the collected sample (from step 2) with lysis reagent for 5 min at room temperature.</li>
		<li>Add 0.2 mL of chloroform for each 1.0 mL of lysis reagent used and invert the tubes by hand for 15 s. Incubate for 2-3 min at room temperature. Centrifuge the samples at 12,000 x g for 15 min at 4 &#176;C.</li>
		<li>Transfer the separated, aqueous phase to a fresh tube and add 0.5 mL of isopropanol for each 1.0 mL of lysis reagent used. Incubate for 10 min at room temperature. Centrifuge the samples at 12,000 x g for 10 min at 4 &#176;C.</li>
		<li>Wash with 75% ethanol and centrifuge the samples at 7,500 x g for 5 min at 4 &#176;C. Remove the supernatant completely and allow to air dry at room temperature. Re-suspend the RNA in 15-30 &#181;L diethyl pyrocarbonate (DEPC)-treated water.</li>
	</ol>
	</li>
	<li>Purify high-quality RNA
	<ol>
		<li>Combine the RNA suspension with 1/10 volume 3M sodium acetate (pH 5.5) and 1 volume of isopropanol. Incubate for 20 min at room temperature and centrifuge the samples at 12,500 x g for 10 mins at 4 &#176;C.</li>
		<li>Wash the pellet with ice-cold 70% ethanol in DEPC-treated water and centrifuge the samples at 10,000 x g for 5 min at 4 &#176;C. Repeat the wash step once.</li>
		<li>Remove the supernatant and allow to dry at room temperature. Re-suspend in DEPC-treated water.</li>
		<li>Assay the extracted RNA for the concentration (ng/&#181;L) and purity (260/230 ratio) using an absorption spectrometer. Ensure that the 260/230 value is ~ 2.0 before proceeding with RNASeq. Store at -80 &#176;C until use (up to 6 months).</li>
		<li>Send the RNA samples to a vendor or core for RNASeq and gene expression change analysis based on quantification of sequencing reads. The results returned from the vendor are typically provided as a list of genes exhibiting a significant fold-change in transcript reads between samples. 
		NOTE: A column can be used if the above method yields poor quality RNA. The amount, concentration, and RNA Integrity Number (RIN) for RNA samples should be confirmed with the vendor or core. The vendor or core will also typically assess RIN.</li>
	</ol>
	</li>
</ol>
4. Pathway and GO Term Analysis
NOTE: See Figure 1 for representative output of the gene expression analysis after RNASeq provided by the core or vendor.
<ol>
	<li>Sorting differentially expressed genes
	<ol>
		<li>Comparing a single experimental condition versus control
		<ol>
			<li>Open data (results) in a spreadsheet management software (see Table of Materials).</li>
			<li>Select the drop-down arrow next to the &#39;Sort&#39; button and select &#34;Custom Sort&#34; within the spreadsheet containing the differentially expressed genes in the experimental versus control condition.</li>
			<li>Select the box under &#39;Column&#39; in the window that pops up and choose to sort by the &#39;LFC&#39; column. Ensure &#39;Values&#39; is selected in the &#39;Sort On&#39; column. Select to sort from &#39;Largest to Smallest&#39; in the &#39;Order&#39; column and click &#34;OK&#34;. 
			NOTE: This will sort the differentially expressed genes so that those with increased expression (positive LFC) will appear at the top of the list while those with decreased expression (negative LFC) will appear at the bottom of the list.</li>
		</ol>
		</li>
		<li>Compare the multiple experimental conditions to a single control as follows.
		<ol>
			<li>Select the first cell in an empty column on the Experimental 1 versus Control spreadsheet to determine differentially expressed genes found in two experimental conditions. Type the following equation into the cell: 
			<img alt="Equation" src="/files/ftp_upload/56187/56187eq1.jpg" /> 
			NOTE: This equation is a combination of the IF, ISERROR, and MATCH functions. (i) The MATCH function, MATCH(A1,Experimental2_vs_Control!A:A,0), will look for the value in A1 (the ENSEMBL ID) in the A column (A:A) of the spreadsheet named Experimental2_vs_Control (Experimental2_vs_Control!). The &#34;0&#34; indicates to look for an exact match, and if an exact match is found, the function will return a value of &#34;1&#34;, while if no match is found, the function will return an error &#34;N/A&#34;. (ii) The result of the MATCH function is then input into the ISERROR function, ISERROR(MATCH(A1,Experimental2_vs_Control!A:A,0)), where, if the input is &#34;1&#34; indicating a match was found, it will return &#34;FALSE&#34;, and if the input is &#34;N/A&#34; indicating a match was not found, it will return &#34;TRUE&#34;. (iii) The &#34;TRUE&#34; or &#34;FALSE&#34; result is then input into the IF function, IF(ISERROR(MATCH(A1,Experimental2_vs_Control!A:A,0)),&#34;&#34;,&#34;Duplicate&#34;), where, if the input is &#34;TRUE&#34; indicating a match was not found, it will return the value in between the first set of quotation marks (&#34;&#34;) which is empty, and therefore the cell will be empty. If the input is &#34;FALSE&#34; indicating a match was found, it will return the value in between the second set of quotation marks (&#34;Duplicate&#34;), and the cell will say &#34;Duplicate&#34;.</li>
			<li>Press &#34;Enter&#34; or &#34;Return&#34; to run the equation. Select the cell containing the equation and click the box in the bottom right corner of the cell. Keep the mouse clicked and drag the selected area all the way down the column until the last &#39;Feature ID&#39;, to copy the equation into each cell in the column.</li>
			<li>Select &#34;Custom Sort&#34; again, add a second level of sorting by clicking the &#34;+&#34; icon in the lower left corner. In the first level, &#34;Sort by&#34;, under Column select &#34;Duplicate&#34;, under Sort On select &#39;Values&#39;, and under Order select &#39;Z to A&#39;. In the second level, &#34;Then by&#34;, under Column select &#39;LFC&#39;, under Sort On select &#39;Values&#39;, and under Order select &#39;Largest to Smallest&#39; and select &#34;OK&#34;. 
			NOTE: This will sort the list of genes into 4 groups based upon directionality of expression change. It is important to check the genes found in both experimental conditions to ensure that the change in the expression is in the same direction in both or in opposite directions.</li>
			<li>Remove any parentheses from the gene symbols column before proceeding or the results will not be found in the databases. Select the entire column containing gene symbols. Select &#34;Edit&#34; then &#34;Replace&#34; in the drop-down &#39;File&#39; menu. Type &#34;(*)&#34; in the &#34;Find what:&#34; bar of the Replace window, and leave the &#34;Replace with:&#34; bar empty.Select &#39;Replace All&#39; to remove all instances of parentheses. 
			NOTE: The * represents any number of characters, by placing this character between two parentheses the program is prompted to find any instance in the highlighted cells and any instance of parentheses will be replaced with nothing, thereby removing them.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Determining enriched pathways
	<ol>
		<li>Copy the gene symbols of the set for which one wishes to determine the enriched pathways to the clipboard. Go to ConsensusPathDB12. Select &#34;Gene set analysis&#34; on the left sidebar of the webpage, followed by &#34;Over-representation analysis&#34;.</li>
		<li>Paste the list of genes in the &#34;Paste a list of gene/protein identifiers&#34; box. Select gene symbol in the &#34;Gene/protein identifier type&#34; box and click &#34;Proceed&#34;. Select the box next to &#34;Pathways as defined by pathway databases&#34; under the Pathway-based sets section. 
		NOTE: A number of options for the analysis will appear including the list of available databases to search. We recommend de-selecting all databases except the Kegg and Reactome databases as they are the most established and comprehensive. The minimum overlap with input list and p-value cutoff settings can also be adjusted based on needs. We recommend leaving these settings at the default 2 gene minimum overlap and a 0.01 p-value cutoff.</li>
		<li>Select &#34;Find enriched sets&#34; to obtain the list of pathways containing genes in the input list. 
		NOTE: The output will be in table format including the name of each pathway followed by &#34;Set size&#34; (indicating the number of total genes in the pathway), &#34;Candidates contained&#34; (indicating the number of genes in the input list that are in that pathway), as well as the p-value and q-value (FDR), and the database from which the pathway was identified.</li>
	</ol>
	</li>
	<li>Generation of pathway networks
	<ol>
		<li>Determine enriched pathways as described above.</li>
		<li>Select all of the enriched pathways to visualize in a pathway network by either selecting each box next to the pathway names to be visualized or by clicking &#34;All&#34; under &#34;Select&#34; in the column header above the selection boxes, then select &#34;Visualize selected sets&#34;. 
		NOTE: We recommend visualizing all pathways if there are less than 30; if there are greater than 30 pathways we recommend selecting the top 30 most enriched pathways (those containing the greatest number of genes from the input list).</li>
		<li>Adjust the &#34;relative overlap&#34; and &#34;shared candidates&#34; filters, by selecting either box in the top center of the page and inputting desired percent relative overlap or number of shared candidates, to be more stringent in order to make the more pertinent overlaps within the pathway networks clearer, and select &#34;apply&#34;. 
		NOTE: We recommend a minimum relative overlap of 0.2, indicating a 20% gene overlap between 2 pathways to connect them, and a minimum of 2 shared candidates. The graph legend can be seen by clicking on the graph legend in the upper left of the page.</li>
	</ol>
	</li>
	<li>Determination of enriched GO terms
	<ol>
		<li>Copy the gene symbols of the group for which one wishes to determine the enriched gene ontologies to the clipboard. Go to the &#39;GO Enrichment Analysis tool&#39; in the Gene Ontology Consortium13. Paste the list of gene symbols in the box on the left side of the page under &#34;Your gene IDs here&#8230;&#34;</li>
		<li>Select which set of GO terms to use, listed underneath the gene IDs box: biological process, molecular function, or cellular component. Choose (recommended) &#39;biological process&#39;. Select &#39;Danio rerio&#39; underneath the GO terms box and click &#34;Submit&#34;. 
		NOTE: We recommend using the default p-value cutoff of 0.05.</li>
	</ol>
	</li>
</ol>
5. Verification by qRT-PCR
NOTE: Individual genes identified with significant gene expression changes in RNASeq should be verified by targeted qRT-PCR in replicate experiments.
<ol>
	<li>cDNA synthesis
	<ol>
		<li>Extract the RNA from embryos using the method described in Section 3.1. RNA Extraction.</li>
		<li>Convert 1 &#181;g of RNA to cDNA using cDNA conversion kit (see Table of Materials). Combine RNA, dNTPs, and reverse transcriptase enzyme. Perform the thermocycler reaction according to the manufacturer&#39;s specifications.</li>
		<li>Dilute cDNA 1:3 in DEPC-treated water. Store at 4 &#176;C for up to 1-2 months.</li>
	</ol>
	</li>
	<li>qRT- PCR verification
	<ol>
		<li>Select genes to verify by qRT-PCR from RNA sequencing results. Identify genes with high fold changes in expression. Determine which of these genes also contain high read counts, as this indicates abundant expression.</li>
		<li>Select 10-12 targets from the high fold change, high read count list of genes. Design primers to amplify the target genes that span at least 1 intron-exon boundary.</li>
		<li>Enter the gene or targeted region of the gene into qPCR primer design site14. Select the &#34;design 2 qPCR primers&#34; and prompt the site to create primer set. 
		NOTE: Be sure to include internal control primers, such as &#946;-actin, to normalize comparisons between samples. The &#946;-actin primers are F: 5&#39;-TCGAGCTGTCTTCCCATCCA-3&#39; and R: 5&#39;-TCACCAACGTAGCTGTCTTTCTG-3&#39;.</li>
		<li>Combine the cDNA, forward primer, reverse primer, and polymerase. Perform qRT-PCR amplification to determine the relative expression of genes15.</li>
		<li>Analyze the relative mRNA expression of genes of interest by relative quantification determination15.</li>
		<li>Compare the qRT-PCR to RNASeq results to ensure that the directionality of differential expression is consistent.</li>
	</ol>
	</li>
</ol>

<ol>
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The authors have nothing to disclose.

The approach described in this protocol offers a relatively rapid and cost-effective strategy for transcriptome-level analysis of whole animals or specific sorted cell populations. The zebrafish provides an advantageous model for this type of study because of the ease and rapidity in generating large amounts of starting material, the ease of implementing genetic or environmental experimental conditions, and the availability of a large spectrum of transgenic reporter lines allowing for isolation of cell-type specific and ...

Comparative analysis of global gene expression is a valuable tool to identify novel genes contributing to observed phenotypes. Such analyses typically rely on quantitative assessment of transcript abundance compared between experimental and control samples. Targeted approaches, such as qRT-PCR are relatively rapid and accurate for investigation of single gene expression changes. RNA sequencing (RNASeq) offers a broad, hypothesis-free approach to identify significant changes in gene expression between samples, making it now the standard for such investigations across experimental systems.
Zebrafish have emerged as a prominent model across many disease areas. Originally developed for their utility in developmental biology studies, due to their high fecundity and relatively low cost of maintenance, experimental use of zebrafish has evolved to include a broad range of phenotypes from embryonic to adult stages as well as a wide array of molecular assays1,2,3. Indeed, these advantages make molecular mechanistic studies rapid and cost-effective because of the ease of acquiring large amounts of material combined with the ease of both genetic and environmental manipulation at all stages of life. Moreover, the transparent nature of zebrafish embryos and larvae make it ideal for generating cell- and tissue-specific transgenic reporter lines allowing in vivo visualization of discrete cell populations4. Exploitation of such lines permits global gene expression analysis in specific isolated cell types based on reporter gene expression.
Here we present a comprehensive protocol for global gene expression analysis using RNASeq after culture of zebrafish embryos. Genetic experimental manipulations, including morpholino (MO)-based transient gene knockdown or CRISPR-mediated genome editing, have been presented elsewhere5,6,7. We therefore focus on a detailed protocol for isolation of RNA from whole embryos or sorted transgenic reporter-expressing cells followed by simple computational analysis of RNASeq results using pathway tools and gene ontology (GO) terms. Finally, we have included a strategy for validation of gene expression changes by quantitative reverse transcriptase PCR (qRT-PCR). These protocols are applicable to zebrafish embryos subjected to a wide range of experimental conditions, including comparison of genetic mutants or environmental conditions.

<table><tbody><tr><td>&lt;strong&gt;Commercial Reagents&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>TriZol</td><td>Thermo Scientific</td><td>15596026</td><td>lysis reagent</td></tr><tr><td>TrypLE</td><td>Gibco</td><td>12604013</td><td>dissociation buffer 1</td></tr><tr><td>FACSMax</td><td>Genlantis</td><td>T200100</td><td>dissociation buffer 2</td></tr><tr><td>DEPC-treated water</td><td>Sigma</td><td>95284</td><td></td></tr><tr><td>FirstStrand cDNA conversion</td><td>Thermo Scientific</td><td>K1621</td><td>cDNA conversion kit</td></tr><tr><td>2X SYBR Green Master Mix</td><td>Roche</td><td>4707516001</td><td>qRT-PCR Master Mix</td></tr><tr><td>FACS buffer</td><td>Fisher Scientific</td><td>50-105-9042</td><td></td></tr><tr><td>chloroform</td><td>Sigma Aldrich</td><td>288306</td><td></td></tr><tr><td>sodium acetate</td><td>Sigma Aldrich</td><td>S2889</td><td></td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog Number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;Zebrafish Strains&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Tuebingen</td><td>ZIRC</td><td>ZL57</td><td></td></tr><tr><td>ins2a:mCherry</td><td>ZIRC</td><td>ZL1483</td><td></td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog Number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;Equipment&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>40 micron cell strainer</td><td>Sigma</td><td>CLS431750</td><td></td></tr><tr><td>FACS tube</td><td>BD Falcon</td><td>352063</td><td></td></tr><tr><td>hemocytometer</td><td>Sigma</td><td>Z359629</td><td></td></tr><tr><td>Dissecting Microscope</td><td>Zeiss</td><td></td><td></td></tr><tr><td>Inverted Microscope</td><td>Zeiss</td><td></td><td></td></tr><tr><td>Nanodrop</td><td>Thermo Scientific</td><td></td><td></td></tr><tr><td>Illumina HiSeq</td><td>Illumina</td><td></td><td></td></tr><tr><td>LightCycler 480</td><td>Roche</td><td></td><td></td></tr><tr><td>Mating tanks 1.0L Crossing Tank Set</td><td>Aquaneering</td><td>ZHCT100</td><td></td></tr><tr><td>FACS tube 5 mL polypropylene tube</td><td>BD Falcon</td><td>352063</td><td></td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog Number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;Software&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Excel</td><td>Microsoft</td><td></td><td></td></tr><tr><td>Consensus Path DB</td><td>http://cpdb.molgen.mpg.de/</td><td></td><td></td></tr><tr><td>GO Enrichment Analysis</td><td>http://geneontology.org/page/go-enrichment-analysis</td><td></td><td></td></tr></tbody></table>

sample preparation and analysis of rnaseq-based gene expression data from zebrafish

The analysis of global gene expression changes is a valuable tool for identifying novel pathways underlying observed phenotypes. The zebrafish is an excellent model for rapid assessment of whole transcriptome from whole animal or individual cell populations due to the ease of isolation of RNA from large numbers of animals. Here a protocol for global gene expression analysis in zebrafish embryos using RNA sequencing (RNASeq) is presented. We describe preparation of RNA from whole embryos or from cell populations obtained using cell sorting in transgenic animals. We also describe an approach for analysis of RNASeq data to identify enriched pathways and Gene Ontology (GO) terms in global gene expression data sets. Finally, we provide a protocol for validation of gene expression changes using quantitative reverse transcriptase PCR (qRT-PCR). These protocols can be used for comparative analysis of control and experimental sets of zebrafish to identify novel gene expression changes, and provide molecular insight into phenotypes of interest.

Sorting of Differentially Expressed Genes:
To identify differentially expressed genes in the larval stage of zebrafish models of Alstr&#246;m Syndrome and Bardet-Biedl Syndrome (BBS), we targeted either alms1 or bbs1 transcripts by injecting previously validated splice-blocking MOs into wild-type zebrafish embryos16,17. At 5 days post fertilization (dpf), ...

Watch this Scientific Journal Video about Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish at JoVE.com

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

This protocol presents an approach for whole transcriptome analysis from zebrafish embryos, larvae, or sorted cells. We include isolation of RNA, pathway analysis of RNASeq data, and qRT-PCR-based validation of gene expression changes.

The analysis of global gene expression changes is a valuable tool for identifying novel pathways underlying observed phenotypes. The zebrafish is an ...

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Research

JoVE Journal

Genetics

10.8K Views.  University of Maryland School of Medicine. Dit protocol biedt een aanpak voor de hele transcriptome analyse van zebravis embryo's, larven, of cellen gesorteerd. Wij omvatten isolatie van RNA, pad analyse van RNASeq gegevens en qRT-PCR-gebaseerde validatie van gen expressie veranderingen.

Video: Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Large-scale Zebrafish Embryonic Heart Dissection for Transcriptional Analysis

The zebrafish embryonic heart is composed of only a few hundred cells, representing only a small fraction of the entire embryo. Therefore, to prevent the cardiac transcriptome from being masked by the global embryonic transcriptome, it is necessary to collect sufficient numbers of hearts for further analyses. Furthermore, as zebrafish cardiac development proceeds rapidly, heart collection and RNA extraction methods need to be quick in order to ensure homogeneity of the samples. Here, we present a rapid manual dissection protocol for collecting functional/beating hearts from zebrafish embryos. This is an essential prerequisite for subsequent cardiac-specific RNA extraction to determine cardiac-specific gene expression levels by transcriptome analyses, such as quantitative real-time polymerase chain reaction (RT-qPCR). The method is based on differential adhesive properties of the zebrafish embryonic heart compared with other tissues; this allows for the rapid physical separation of cardiac from extracardiac tissue by a combination of fluidic shear force disruption, stepwise filtration and manual collection of transgenic fluorescently labeled hearts.

To analyse cardiac gene expression profiles during zebrafish heart development, total RNA has to be extracted from isolated hearts. Here, we present a protocol for collecting functional/beating hearts by rapid manual dissection from zebrafish embryos to obtain cardiac-specific mRNA.

The zebrafish embryonic heart is composed of only a few hundred cells, representing only a small fraction of the entire embryo. Therefore, to prevent the ...

Developmental Biology

Profiling DNA Replication Timing Using Zebrafish as an In Vivo Model System

DNA replication timing is an important cellular characteristic, exhibiting significant relationships with chromatin structure, transcription, and DNA mutation rates. Changes in replication timing occur during development and in cancer, but the role replication timing plays in development and disease is not known. Zebrafish were recently established as an in vivo model system to study replication timing. Here is detailed the protocols for using the zebrafish to determine DNA replication timing. After sorting cells from embryos and adult zebrafish, high-resolution genome-wide DNA replication timing patterns can be constructed by determining changes in DNA copy number through analysis of next generation sequencing data. The zebrafish model system allows for evaluation of the replication timing changes that occur in vivo throughout development, and can also be used to assess changes in individual cell types, disease models, or mutant lines. These methods will enable studies investigating the mechanisms and determinants of replication timing establishment and maintenance during development, the role replication timing plays in mutations and tumorigenesis, and the effects of perturbing replication timing on development and disease.

Profiling DNA Replication Timing Using Zebrafish as an In Vivo Model System

Zebrafish were recently used as an in vivo model system to study DNA replication timing during development. Here is detailed the protocols for using zebrafish embryos to profile replication timing. This protocol can be easily adapted to study replication timing in mutants, individual cell types, disease models, and other species.

DNA replication timing is an important cellular characteristic, exhibiting significant relationships with chromatin structure, transcription, and DNA ...

Isolation and Characterization of Single Cells from Zebrafish Embryos

The zebrafish (Danio rerio) is a powerful model organism to study vertebrate development. Though many aspects of zebrafish embryonic development have been described at the morphological level, little is known about the molecular basis of cellular changes that occur as the organism develops. With recent advancements in microfluidics and multiplexing technologies, it is now possible to characterize gene expression in single cells. This allows for investigation of heterogeneity between individual cells of specific cell populations to identify and classify cell subtypes, characterize intermediate states that occur during cell differentiation, and explore differential cellular responses to stimuli. This study describes a protocol to isolate viable, single cells from zebrafish embryos for high throughput multiplexing assays. This method may be rapidly applied to any zebrafish embryonic cell type with fluorescent markers. An extension of this method may also be used in combination with high throughput sequencing technologies to fully characterize the transcriptome of single cells. As proof of principle, the relative abundance of cardiac differentiation markers was assessed in isolated, single cells derived from nkx2.5 positive cardiac progenitors. By evaluation of gene expression at the single cell level and at a single time point, the data support a model in which cardiac progenitors coexist with differentiating progeny. The method and work flow described here is broadly applicable to the zebrafish research community, requiring only a labeled transgenic fish line and access to microfluidics technologies.

This protocol describes a method for isolating single cells from zebrafish embryos, enriching for cells of interest, capturing zebrafish cells in microfluidic based single cell multiplex systems, and assessing gene expression from single cells.

The zebrafish (Danio rerio) is a powerful model organism to study vertebrate development. Though many aspects of zebrafish embryonic development have been ...

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 ...

Biology

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Gene microarray technology permits quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. Gene microarray technology is used in numerous biological disciplines in a variety of applications including global gene expression analysis in relation to developmental stage, to a disease state, and in toxic responses. Herein, we include a demonstration of global gene expression analysis using a comprehensive zebrafish-specific oligonucleotide microarray platform. The zebrafish expression microarray platform contains 385,000 probes, 60 base pairs in length, interrogating 37,157 targets with up to 12 probes per target. For this platform, all cDNA and genomic information available for the zebrafish was collected from various genomic databases including Ensembl (http://www.ensembl.org), VEGA (http://vega.sanger.ac.uk), UCSC (http://genome.ucsc.edu), and ZFIN (http://www.zfin.org). As a result this expression array provides complete coverage of the current zebrafish transcriptome. The zebrafish expression microarray was printed by Roche NimbleGen (Madison, WI). This technical demonstration includes the fluorescent labeling of a cDNA product, hybridization of the labeled cDNA product to the microarray platform, and array scanning for signal acquisition using the one color analysis strategy.  

Gene microarrays are powerful tools in gene expression profiling at a genome-wide level. This technology has application in a variety of biological disciplines including developmental biology and toxicology. In this video, we detail a protocol for global gene expression analysis using a comprehensive oligonucleotide microarray platform for the zebrafish.

Gene microarray technology permits quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. Gene microarray ...

Fluorescent Protein Tagging in Zebrafish Larvae Using CRISPR/Cas9 Knock-In

Fluorescence Labeling to Visualize Low-Expressed Proteins in Zebrafish

CRISPR/Cas9-mediated knock-in (KI) technology allows for easier fluorescent-protein tagging in zebrafish (Danio rerio), a preferred model organism for in vivo imaging due to its transparency during the early developmental stage. Here, we provide a detailed protocol for performing high-efficiency fluorescence gene KI, rapid screening for KI founders, and low-abundance protein tracing in zebrafish larvae, which will lay a critical foundation for subsequent physio-pathological studies in zebrafish. The current protocol includes complete steps for the sgRNA design for the gene of interest, sgRNA in vitro transcription, Cas9 mRNA in vitro transcription, in vivo sgRNA screen for the one with the highest efficiency, donor plasmid design and construction, microinjection in zebrafish larvae, KI founder screen and zebrafish live imaging. Critical steps, troubleshooting tips, quality control methods, and advantages and applications of this protocol are included and discussed. This protocol assures quick and accurate results at a low cost and has been validated by multiple trials.

Here, we present a protocol to label proteins with a fluorescence protein tag in zebrafish larvae, a newly developed and modified in vivo system especially useful for visualizing low-abundance proteins in zebrafish.

CRISPR/Cas9-mediated knock-in (KI) technology allows for easier fluorescent-protein tagging in zebrafish (Danio rerio), a preferred model organism for in ...

Preparation of Small RNA Libraries for Sequencing from Early Mouse Embryos

MicroRNAs (miRNAs) are important for the complex regulation of cell fate decisions and developmental timing. In vivo studies of the contribution of miRNAs during early development are technically challenging due to the limiting cell number. Moreover, many approaches require a miRNA of interest to be defined in assays such as northern blotting, microarray, and qPCR. Therefore, the expression of many miRNAs and their isoforms have not been studied during early development. Here, we demonstrate a protocol for small RNA sequencing of sorted cells from early mouse embryos to enable relatively unbiased profiling of miRNAs in early populations of neural crest cells. We overcome the challenges of low cell input and size selection during library preparation using amplification and gel-based purification. We identify embryonic age as a variable accounting for variation between replicates and stage-matched mouse embryos must be used to accurately profile miRNAs in biological replicates. Our results suggest that this method can be broadly applied to profile the expression of miRNAs from other lineages of cells. In summary, this protocol can be used to study how miRNAs regulate developmental programs in different cell lineages of the early mouse embryo.

We describe a technique for profiling microRNAs in early mouse embryos. This protocol overcomes the challenge of low cell input and small RNA enrichment. This assay can be used to analyze changes in miRNA expression over time in different cell lineages of the early mouse embryo.

MicroRNAs (miRNAs) are important for the complex regulation of cell fate decisions and developmental timing. In vivo studies of the contribution of miRNAs ...

Processing Gut Cells from Zebrafish Larvae for Single-Cell RNA Sequencing

Gut Isolation from Zebrafish Larvae for Single-cell RNA Sequencing

The gastrointestinal (GI) tract performs a range of functions essential for life. Congenital defects affecting its development can lead to enteric neuromuscular disorders, highlighting the importance to understand the molecular mechanisms underlying GI development and dysfunction. In this study, we present a method for gut isolation from zebrafish larvae at 5 days post fertilization to obtain live,&#160;viable cells which can be used for single-cell RNA sequencing (scRNA-seq) analysis. This protocol is based on the manual dissection of the zebrafish intestine, followed by enzymatic dissociation with papain. Subsequently, cells are submitted to fluorescence-activated cell sorting, and viable cells are collected for scRNA-seq. With this method, we were able to successfully identify different intestinal cell types, including epithelial, stromal, blood, muscle, and immune cells, as well as enteric neurons and glia. Therefore, we consider it to be a valuable resource for studying the composition of the GI tract in health and disease, using the zebrafish.

Author Spotlight: Isolating and Analyzing Intestinal Cells of Zebrafish Larvae for Investigating Transcriptomic Aspects of Gastrointestinal Development 

Here, we describe a method for gut isolation from zebrafish larvae at 5 days post fertilization, for single-cell RNA sequencing analysis.

The gastrointestinal (GI) tract performs a range of functions essential for life. Congenital defects affecting its development can lead to enteric ...

Modeling Tuberculosis in Mycobacterium marinum Infected Adult Zebrafish

Mycobacterium tuberculosis is currently the deadliest human pathogen causing 1.7 million deaths and 10.4 million infections every year. Exposure to this bacterium causes a wide disease spectrum in humans ranging from a sterilized infection to an actively progressing deadly disease. The most common form is the latent tuberculosis, which is asymptomatic, but has the potential to reactivate into a fulminant disease. Adult zebrafish and its natural pathogen Mycobacterium marinum have recently proven to be an applicable model to study the wide disease spectrum of tuberculosis. Importantly, spontaneous latency and reactivation as well as adaptive immune responses in the context of mycobacterial infection can be studied in this model. In this article, we describe methods for the experimental infection of adult zebrafish, the collection of internal organs for the extraction of nucleic acids for the measurement of mycobacterial loads and host immune responses by quantitative PCR. The in-house-developed, M. marinum-specific qPCR assay is more sensitive than the traditional plating methods as it also detects DNA from non-dividing, dormant or recently dead mycobacteria. As both DNA and RNA are extracted from the same individual, it is possible to study the relationships between the diseased state, and the host and pathogen gene-expression. The adult zebrafish model for tuberculosis thus presents itself as a highly applicable, non-mammalian in vivo system to study host-pathogen interactions.

Modeling Tuberculosis in Mycobacterium marinum Infected Adult Zebrafish

Here, we present a protocol to model human tuberculosis in an adult zebrafish using its natural pathogen Mycobacterium marinum. Extracted DNA and RNA from the internal organs of infected zebrafish can be used to reveal the total mycobacterial loads in the fish and the host&#39;s immune responses with qPCR.

Mycobacterium tuberculosis is currently the deadliest human pathogen causing 1.7 million deaths and 10.4 million infections every year. Exposure to this ...

Immunology and Infection

An Efficient Protocol to Assess ERK Activity Modulation in Early Zebrafish Noonan Syndrome Models via Live FRET Microscopy and Immunofluorescence

RASopathies are genetic syndromes caused by ERK hyperactivation and resulting in multisystemic diseases that can also lead to cancer predisposition. Despite a broad genetic heterogeneity, germline gain-of-function mutations in key regulators of the RAS-MAPK pathway underlie the majority of the cases, and, thanks to advanced sequencing techniques, potentially pathogenic variants affecting the RAS-MAPK pathway continue to be identified. Functional validation of the pathogenicity of these variants, essential for accurate diagnosis, requires fast and reliable protocols, preferably in vivo. Given the scarcity of effective treatments in early childhood, such protocols, especially if scalable in cost-effective animal models, can be instrumental in offering a preclinical ground for drug repositioning/repurposing. 
Here we describe step-by-step the protocol for rapid generation of transient RASopathy models in zebrafish embryos and direct inspection of live disease-associated ERK activity changes occurring already during gastrulation through real-time multispectral F&#246;rster resonance energy transfer (FRET) imaging. The protocol uses a transgenic ERK reporter recently established and integrated with the hardware of commercial microscopes. We provide an example application for Noonan syndrome (NS) zebrafish models obtained by expression of the Shp2D61G. We describe a straightforward method that enables registration of ERK signal change in the NS fish model before and after pharmacological signal modulation by available low-dose MEK inhibitors. We detail how to generate, retrieve, and assess ratiometric FRET signals from multispectral acquisitions before and after treatment and how to cross-validate the results via classical immunofluorescence on whole embryos at early stages. We then describe how, via examining standard morphometric parameters, to query late changes in embryo shape, indicative of a resulting impairment of gastrulation, in the same embryos whose ERK activity is assessed by live FRET at 6 h post fertilization.

RASopathies are multisystem genetic syndromes caused by RAS-MAPK pathway hyperactivation. Potentially pathogenic variants awaiting validation emerge continuously while poor preclinical evidence limits therapy. Here, we describe our in vivo protocol to test and cross-validate RASopathy-associated ERK activation levels and its pharmacological modulation during embryogenesis by live FRET imaging in Teen-reporter zebrafish.

RASopathies are genetic syndromes caused by ERK hyperactivation and resulting in multisystemic diseases that can also lead to cancer predisposition. ...

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

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