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May 2019

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mRNA Extraction from Gill Tissue for RNA-sequencing
鳃组织mRNA 提取用于RNA测序   

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Abstract

Adaptation is thought to proceed in part through spatial and temporal changes in gene expression. Fish species such as the threespine stickleback are powerful vertebrate models to study the genetic architecture of adaptive changes in gene expression since divergent adaptation to different environments is common, they are abundant and easy to study in the wild and lab, and have well-established genetic and genomic resources. Fish gills, due to their respiratory and osmoregulatory roles, show many physiological adaptations to local water chemistry, including differences in gene expression. However, obtaining high-quality RNA using popular column-based extraction methods can be challenging from small tissue samples high in cartilage and bone such as fish gills. Here, we describe a bead-based mRNA extraction and transcriptome RNA-seq protocol that does not use purification columns. The protocol can be readily scaled according to sample size for the purposes of diverse gene expression experiments using animal or plant tissue.

Keywords: Transcriptome sequencing (转录组测序), Gene regulation (基因调控), Gene expression evolution (基因表达进化), Direct mRNA extraction (直接提取mRNA), Gills (鳃组织)

Background

Transcriptome sequencing (RNA-seq) is used to quantify the expression levels of genes, to identify differences in gene expression levels between groups of samples and to infer gene co-expression. In evolutionary genetics research, RNA-seq can be used as an approach to study the molecular basis of adaptive divergence (e.g., Rougeux et al., 2019; Verta and Jones, 2019), identify candidate genes underlying adaptive phenotypes (e.g., Ferreira et al., 2017), and infer function for unknown genes (e.g., Rawat et al., 2015) among other applications. A key strength of RNA sequencing is that it can be readily applied to almost any species or tissue, and transcriptome sequencing has accelerated evolutionary research by opening non-model species for genomic studies. Obtaining high-quality mRNA is the most important prerequisite for a successful RNA-seq study (Gallego Romero et al., 2014). This can be challenging because RNA is inherently more unstable (and fragile) than more commonly studied DNA. Standard RNA extraction methods typically yield total RNA, comprising mRNA destined to be translated into proteins, as well as non-translated RNA such as ribosomal and regulatory RNAs. Typically, only 1-4% of total RNA is useful for mRNA sequencing and so mRNA yield from small amounts of tissue can be low. In addition, heterogenous tissue samples such as fish gills that consists of both soft epithelia, cartilage and bone, as well as DNA-rich tissue samples, can perform sub-optimally in column-based RNA extraction methods because of physical clogging of column pores and/or DNA precipitation. In such cases direct extraction of mRNA from tissue lysates using oligo-dT coated magnetic beads offer a straightforward and scalable solution for extraction.

Here, we describe such bead-based protocol for rapid (~1-2 h) mRNA extraction from fish gills and RNA-sequencing. The oligo-dT based technique relies on A-T hybridization of mRNA poly-A tails with T-oligonucleotide fragments covalently attached to magnetic beads, allowing for full-length mRNA purification from crude cell lysates. This protocol has been adapted from the original protocol for oligo-dT Dynabeads from Invitrogen and was briefly described in Verta and Jones (2019). Slightly different versions of this protocol were previously used to study gene expression in small plant tissues that comprise of ~1,000-2,000 cells (Verta et al., 2016; Ojeda et al., 2019). Briefly, tissue samples are homogenized and lysed, after which mRNA is captured from tissue lysate using magnetic oligo-dT beads. The bead-mRNA complex is washed and subsequently eluted with water. The protocol yields high-quality mRNA that can be used for applications such as RNA-seq and qPCR. We further provide an example of the steps involving RNA quality-control and quantification, RNA-seq library preparation and data analysis. For general guidelines in RNA-seq study design and best-practices the reader is referred to Conesa et al. (2016).

Materials and Reagents

  1. 1.5 ml RNase-free Safe-Lock Eppendorf tubes
  2. 21 G needles
  3. Micro-Tube polypropylene pestles for 1.5 ml Eppendorf tubes (Bel-Art, catalog number: BAF199230001 )
  4. Qubit Assay tubes (Thermo Fisher, catalog number: Q32856 )
  5. RNase-free PCR strips and caps
  6. Fresh tissue or liquid nitrogen snap-frozen tissue
  7. Tricaine methanesulfonate (MS-222, Sigma-Aldrich, catalog number: E10521 )
  8. Sodium bicarbonate NaHCO3 (Sigma-Aldrich, catalog number: S5761 )
  9. Dynabeads mRNA direct purification kit (Thermo Fisher Invitrogen, catalog number: 61011 )
  10. Turbo DNase-free kit (Thermo Fisher Invitrogen, catalog number: AM1907 )
  11. Bioanalyzer RNA 6000 Nano kit (Agilent, catalog number: 5067-11511 )
  12. Bioanalyzer High Sensitivity DNA kit (Agilent, catalog number: 5067-4626 )
  13. Qubit RNA BR reagents (Thermo Fisher, catalog number: Q10211 )
  14. PrimeScript RT Master Mix (Takara, catalog number: RR036A )
  15. Sybr Select Master Mix for CFX (Thermo Fisher Applied Biosciences, catalog number: 4472942 )
  16. TruSeq stranded mRNA kit (Illumina, catalog number: 20020594 )
  17. SuperScript II reverse transcriptase (Thermo Fisher, catalog number: 18064014 )

Equipment

  1. Scissors (or a blade) and forceps
  2. DynaMag2 magnet (Thermo Fisher Invitrogen, catalog number: 12321D )
  3. PCR cycler (e.g., Bio-Rad C1000 Touch, catalog number: 1851196 )
  4. Qubit fluorometer (Thermo Fisher, catalog number: Q33238 )
  5. CFX96 Touch Real-Time PCR cycler (Bio-Rad, catalog number: 1855195 )
  6. 2100 Bioanalyzer (Agilent, catalog number: G2939BA )

Software

  1. FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
  2. Cutadapt (https://cutadapt.readthedocs.io/en/stable/#)
  3. STAR (Dobin et al., 2013)
  4. Cufflinks (Trapnell et al., 2012)

Procedure

Notes:

  1. For mRNA extraction frozen from stickleback gill tissue (~50 mg) use:
    250 μl of lysis buffer
    100 μl of Dynabeads
    600 μl of wash-A solution (two washes)
    300 μl of wash-B solution
    Elute to 20 μl RNase free water
    Volumes can be scaled in proportion for different size tissue samples.
  2. Procedures B-G are adapted from the original Invitrogen Dynabeads protocol with modifications to solution volumes, sample homogenization and lysis steps. Additional steps H-J not part of original Invitrogen protocol are required to assure the yield of DNA-free and high-quality mRNA.
  3. Procedures B-H should be followed through immediately. Safe stopping points where the experiment can be put to hold are after Procedures A and H.

  1. Dissect whole stickleback gills
    1. Euthanize fish following animal protocol guidelines (e.g., EU Directive 2010-63-eu, and AVMA Guidelines) For example, by anesthetic overdose with NaHCO3-buffered Tricaine methanesulfonate (MS-222, pH 7.5). Note that, appropriate concentrations vary depending on the size of the fish. For sticklebacks we use a 10x solution (1.5 g/L) prepared by dissolving 1.5 g of MS-222 and 3.0 g of NaHCO3 in 1 L of aquarium water.
    2. Remove the head using scalpel and forceps (Figure 1). Working from the ventral side, open the operculum to reveal gill arches. Cut gill arches free from the ventral and dorsal attachment points as shown in Figure 1B. Remove any connective tissue that is not part of the gills.
    3. Collect gill tissue (~50 mg) in 1.5 ml Eppendorf Safe-Lock tubes and immediately snap-freeze in liquid nitrogen.
    4. Store samples in -80 °C.
      SAFE STOPPING POINT


      Figure 1. Dissection of stickleback gills. Whole gill arches are isolated from euthanized fish by removal of head via dissection along the transverse plane (red line, A). Then with a ventral view (B) the gill arches (blue lines) are excised by dissection of the ventral and dorsal attachment points (red lines, B).

  2. Wash and resuspend Dynabeads
    1. Allow Dynabeads and solutions to warm to room temperature.
    2. Prepare one 1.5 ml Eppendorf per tissue sample. Resuspend Dynabeads by gently pipetting up and down, and aliquot 100 μl of Dynabeads into each 1.5 ml Eppendorf tube.
    3. Place tubes on a DynaMag2 magnet and wait approximately 30 s for beads to form a pellet (~30 s).
    4. Remove the supernatant without disturbing the beads.
    5. Remove tubes from magnet and resuspend the Dynabeads in original volume of lysis buffer (100 μl).

  3. Homogenise tissue into a powder using a pestle
    Notes:
    1. Modify Micro-Tube homogenizing pestles for better sample disruption by cutting the round conical surface of the pestles into angular surface with sterile scissors or a blade (Figure 2).


      Figure 2. Modification of homogenizing pestle. For more efficient sample disruption, cut the surface of the pestle (red lines, A) into an angular surface (B) with sterile scissors or scalpel blade.

    2. Cool down the pestle before sample disruption by dipping it to liquid nitrogen.
    3. Remove samples from -80 °C and keep on liquid nitrogen.
    4. Disrupt tissue to powder on liquid nitrogen using a pestle stick in 1.5 ml Eppendorf tubes.
    5. Avoid melting of the sample at all stages before lysis step below. Freezing breaks the cell membranes and exposes RNA to endogenous RNases, which degrade RNA after thawing. Always keep your frozen sample on liquid nitrogen. Once you introduce an RNase inhibiting agent (for example LiCl in the Dynabeads lysis buffer, next step in protocol), RNA degradation is efficiently inhibited and sample can be thawed.

  4. Lyse the cells
    1. Take sample tubes one by one out of the liquid nitrogen, remove pestle but keep it in hand, immediately pipet in 250 μl of lysis buffer and then drop the pestle back into the tube.
    2. Keep the frozen tube in your hand and grind the frozen lysis buffer with the pestle until it melts to ensure the sample is suspended in lysis buffer immediately after thawing.
    3. Repeat for each of the samples.
    4. Discard pestle and shear DNA by passing the lysis mix five times through a 21 gauge needle before proceeding with the protocol.
    Note: Introduce lysis buffer while your tube is still frozen.

  5. Bind mRNA to Dynabeads
    Add 100 μl of washed and resuspended Dynabeads per sample, incubate 5 min at RT with continuing rotation (~500 rpm).
    Note: Continuous mixing during this incubation step is important to reduce the binding of Dynabeads to genomic DNA.

  6. Wash Dynabead-mRNA complex
    1. Place samples on Dynamag magnet and wait for beads to form a pellet (~30 s).
    2. Remove all supernatant from tubes without touching the bead pellet.
    3. Remove tubes from magnet and resuspend beads in 600 μl wash buffer A.
    4. Repeat Steps F1-F3 for a second buffer A-wash.
    5. Remove the buffer and perform final wash using 300 μl of wash buffer B.
    Notes:
    1. Wash buffers should be room temperature before use.
    2. Always resuspend the beads completely in the washing buffers by pipetting solution slowly up and down. Insufficient resuspension leads to increased DNA and ribosomal-RNA contamination. There should be no visible clump of beads after resuspension. Avoid excessive shearing/fragmentation of RNA by using the minimal amount of pipetting necessary to resuspend beads.
    3. You can perform wash A three times for better sample purity.

  7. Elute mRNA from beads
    1. Place samples on magnet and wait for beads to form a pellet (~30 s).
    2. Remove all supernatant from tubes taking care not to leave any residual buffer.
    3. Remove tubes from magnet and resuspend beads in 20 μl of RNase free water.
    4. Incubate samples for 2 min in 65 °C in a thermocycler or thermomixer.
    5. Immediately place samples on the magnet and pipet out the supernatant to a fresh RNase-free 1.5 ml Eppendorf tube.

  8. Treat mRNA extraction with DNase 
    1. To 20 μl of eluted mRNA, add 2 μl of Turbo DNase buffer + 1 μl Turbo DNase.
    2. Incubate at 37 °C for 20 min.
    3. Add 5 μl of inactivation solution, flick tubes and incubate 5 min at RT.
    4. Spin for 1 min 30 s at 10,000 x g and transfer the supernatant to a fresh RNase-free tube.
    5. Snap-freeze final mRNA extraction as smaller aliquots (e.g., 10 μl) on liquid nitrogen and store in -80 °C.
      SAFE STOPPING POINT
    Notes:
    1. Treat the entire 20 μl aliquot of mRNA with DNase right after elution from beads, do not freeze-thaw.
    2. Either quantify and quality-control (e.g., Qubit & BioAnalyzer) your mRNA immediately after DNase treatment or keep an aliquot for these separately. Avoid freeze-thaw cycles of your mRNA sample at all times.
    3. 20-30% ribosomal-RNA contamination of mRNA samples is common. rRNA contamination can be reduced by optimizing the A-wash volume. You can also try heating the lysis buffer to 65 °C or an elution-rebinding cycle in 65 °C while the beads are in the lysis buffer.
    4. The Illumina TruSeq RNA-seq protocols start with mRNA selection, which eliminates the majority of ribosomal-RNA and DNA contamination (Figure 3).


      Figure 3. Testing for genomic DNA contamination in extracted mRNA using qPCR of housekeeping gene. Positive controls (cDNA) and mRNA extractions were amplified using qPCR of housekeeping gene primers (e.g., claudin). Lower Ct values (PCR cycle when fluorescence can be detected above background level, green line) indicate higher abundance of template, which in the case of non reverse-transcribed mRNA extractions represents contamination from genomic DNA. Non DNase-treated Dynabeads mRNA extractions show DNA contamination, which is almost completely eliminated after second mRNA selection step performed at the beginning of Illumina TruSeq RNA-seq protocol. DNase treated mRNA extractions show no amplification and are thus free of DNA.

  9. Verify the absence of genomic-DNA contamination
    1. Design a pair of PCR primers that amplify a housekeeping gene (e.g., claudin), making sure that primers amplify a fragment within a single exon (the PCR fragment should not span an exon-intron boundary). Aim for primers that are specific to the housekeeping gene (verify sequence similarity other genes e.g. using BLAST search), ending in G/C nucleotides and have a melting temperature of 60 °C ± 5 °C. For stickleback gill tissue, we used claudin gene as control (Fwd: 5' ACTTGGTGCCCTATCAAATGAGGTA 3', Rev: 5' AGTTATACACGACGGGAGGATTGAG 3').
    2. Select positive control samples and reverse-transcribe mRNA to cDNA using Takara PrimeScript RT Master Mix.
      1. To 5 μl of mRNA extraction, add 3 μl of water and 2 μl of PrimerScript master-mix.
      2. Incubate for 15 min at 37 °C.
      3. Store in -20 °C.
    3. Prepare qPCR reactions for positive control (cDNA) and selected mRNA extractions for verification.
      10 μl of 2X Sybr select for CFX Master Mix
      1 μl of 10 mM Forward primer
      1 μl of 10 mM Reverse primer
      2 μl water
      1 μl cDNA template
    4. Run samples on qPCR using the following program:
      1. 50 °C 2 min
      2. 95 °C 2 min
      3. 95 °C 30 s
      4. 55-65 °C (primer-specific melting temperature) 30 s
      5. 72 °C 30 s
      6. Return to c. for 39 additional cycles
      7. Hold at 4 °C
    5. Analyze qPCR results (Figure 3). The DNase treated mRNA extractions should not amplify, while the reverse-transcribed cDNA preps should give signal. Amplification in mRNA extractions without reverse-transcription indicates contamination from genomic DNA. In this case re-treat samples with DNase and verify mRNA quality using Bioanalyser.

  10. Verify the quality of extracted mRNA using Bioanalyzer RNA 6000 Nano reagents (Figure 4). For concentrations less than ~5 ng/μl use Bioanalyzer RNA 6000 Pico reagents.
    Note: RNA Integrity Number (RIN) typically calculated for total RNA extractions does not apply for mRNA extractions because the majority of ribosomal RNA used to calculate RNA quality and detect degradation have been removed. Instead, use the distribution of mRNA fragment sizes to determine whether the sample is of good quality (a range of sizes are of high molecular weight) or poor quality (highly degraded RNA of low molecular weight) (Figure 4).


    Figure 4. Verification of mRNA quality using Bioanalyser. Example of good (A) and bad (B) quality mRNA sample analysed with Bioanalyser RNA 6000 Nano reagents. Good-quality mRNA extraction can show some (10-30%) rRNA contamination. First peak at 25 nt corresponds to marker, two prominent peaks in (A) correspond to 18S and 28S rRNAs and the broad hump corresponds to mRNA. Note the left-shift (smaller size fragments) of the mRNA size distribution in the bad-quality sample, indicating that mRNA fragments are degraded.

  11. Construct RNA-seq libraries using Illumina TruSeq kit and kit instructions, with the following exceptions:
    1. Use 150 ng of mRNA as input (quantify using BioAnalyzer RNA Nano or Qubit RNA BR reagents). Dilute with RNase-free water to a final volume of 50 μl. Using adequate amount of input mRNA helps to avoid excessive PCR duplicates in final sequencing library.
    2. Optimize fragmentation time for the sequencing strategy you are going to use. Test the effect of fragmentation time using a time-series and analyze fragment sizes using Bionalyzer High Sensitivity DNA reagents, or refer to page 109 of Illumina TruSeq RNA Sample Preparation v2 Guide. For stickleback gill mRNA sequencing with HiSeq 3000 150 base-pair paired-end reads, we used two minutes (or 2 min) fragmentation to have a final average insert size of ~290 bp.
    3. Use provided indexes to identify samples after sequencing and pool in equimolar amounts for sequencing. Recommended strategy to avoid possible batch effects is to use as many indexes as there are samples and sequence all samples in the same lane. Where experimental design allows, use replicate lanes and combine reads from replicate lanes to reach the sequencing depth required.

Data analysis

The following general example is given for 150 base-pair paired-end RNA-seq reads from gill tissue of threespine stickleback fish analyzed in a Unix/Linux/MacOSX environment with command-line tools. The user is encouraged to modify the paths outlined in the below procedure to match their data, and to execute the code in a terminal window by using shell scripts or copy-paste. Detailed information for the groups of samples tested can be found in Verta and Jones (2019).

  1. Verify read and library quality with FastQC software following the guidelines outlined in FastQC website and manual. (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
    Note: FastQC may report RNA-seq libraries to contain high levels of PCR-duplicates. This does not necessarily mean libraries have undergone excessive PCR because many reads are expected to map to highly abundant transcripts, which FastQC can interpret as PCR duplication.
  2. Trim any Illumina sequencing adapters from the reads using TrimGalore. (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/)
    Note: Alternatively, quality-control and adapter trimming can be performed in one step using the software fastp (Chen et al., 2018).

    trim_galore \
    --path_to_cutadapt cutadapt \
    --illumina \
    --stringency 5 \
    --quality 20 \
    --output_dir out_dir \
    --paired \
    reads_R1_001.fastq.gz \
    reads_R2_001.fastq.gz

  3. Generate STAR genome file (necessary only the first time a given reference genome used).

    STAR \
    --runMode genomeGenerate \
    --runThreadN N \
    --genomeDir genome \
    --genomeFastaFiles gasAcu1.fa \
    --sjdbGTFfile transcript.gtf \
    --sjdbOverhang 149 \
    --genomeChrBinNbits 18

  4. Align RNA-seq reads to the reference genome (e.g., Broad S1, gasAcu1 [Jones et al., 2012]) with STAR aligner–a high performing aligner that addresses many of the challenges associated with aligning spliced RNAseq reads across intron/exon boundaries of the reference genome (Dobin et al., 2013). Use manual two-pass mode for most sensitive detection of novel intron-exon boundaries.
    1. For each sample, perform STAR 1st pass to identify intron/exon boundaries in current sample.

      STAR \
      --readFilesCommand gunzip -c \
      --runThreadN N \
      --outFilterIntronMotifs RemoveNoncanonicalUnannotated \
      --chimSegmentMin 50 \
      --outFilterType BySJout \
      --alignSJDBoverhangMin 1 \
      --alignIntronMin 20 \
      --alignIntronMax 200000 \
      --alignMatesGapMax 200000 \
      --quantMode GeneCounts \
      --outWigType wiggle \
      --outSAMtype BAM SortedByCoordinate \
      --twopassMode None \
      --genomeDir genome \
      --readFilesIn reads_val_1.fq.gz reads_val_2.fq.gz

    2. For each sample, run STAR 2nd pass using intron/exon boundaries identified across samples above to inform read alignment.

      STAR \
      --readFilesCommand gunzip -c \
      --runThreadN N \
      --outFilterIntronMotifs RemoveNoncanonicalUnannotated \
      --chimSegmentMin 50 \
      --outFilterType BySJout \
      --alignSJDBoverhangMin 1 \
      --alignIntronMin 20 \
      --alignIntronMax 200000 \
      --alignMatesGapMax 200000 \
      --quantMode GeneCounts \
      --outWigType wiggle \
      --outSAMtype BAM SortedByCoordinate \
      --twopassMode None \
      --genomeDir genome \
      --limitSjdbInsertNsj 2000000 \
      --readFilesIn reads_val_1.fq.gz reads_val_2.fq.gz \
      --sjdbFileChrStartEnd SJ_1.out.tab \
      --sjdbFileChrStartEnd SJ_2.out.tab \


  5. Use Cufflinks2.2 pipeline (Trapnell et al., 2012) for reference-guided transcriptome assembly and transcript and isoform expression level testing. In order to run in “reference guided” mode, a transcript gtf file describing known gene models is needed. Cufflinks also allows “unguided” de novo transcriptome assemblies if this information is not available.

    cufflinks \
    -p N \
    --min-intron-length 20 \
    --library-type fr-firststrand \
    -o ./cloutGuided \
    --frag-bias-correct gasAcu1.fa \
    --multi-read-correct \
    --min-isoform-fraction 0.15 \
    --min-frags-per-transfrag 20 \
    --max-multiread-fraction 0.5 \
    -g transcript.gtf \
    reads.out.bam

  6. Merge sample-level annotation files together (specified in assembly_list.txt).

    cuffmerge \
    -g transcript.gtf \
    -o merged_assembly \
    -s gasAcu1.fa \
    -p N \
    assembly_list.txt

  7. Quantify RNA-seq read coverage over gene models.

    cuffquant \
    -o out_dir \
    -p N \
    -v \
    -u \
    --library-type fr-firststrand \
    -b gasAcu1.fa \
    merged.gtf \
    reads.out.bam

  8. Normalize read coverages across samples.

    cuffnorm \
    -p N \
    -o out_dir \
    -library-type fr-firststrand \
    --labels sample \
    merged.gtf \
    abundances1a.cxb \
    abundances1b.cxb \
    abundances2a.cxb \
    abundances2b.cxb \


  9. Test for differential expression between groups of samples using the Cufflinks function cuffdiff.

    cuffdiff \
    -p N \
    -o outDir \
    -b gasAcu1.fa \
    -u \
    -dispersion-method per-condition \
    -library-type fr-firststrand \
    --labels Group1,Group2 \
    merged.gtf \
    abundances1a.cxb,abundances1b.cxb \
    abundances2a.cxb,abundances2b.cxb \

Acknowledgments

FJ is funded by the European Research Council (FP7) and the Max Planck Society. This protocol is adapted from Verta and Jones (2019).

Ethics

All animal experiments were done in accordance to EU and state legislation and avoiding unneccessary harm to animals (EU Directive 2010_63_EU).

References

  1. Chen, S., Zhou, Y., Chen, Y. and Gu, J. (2018). Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34(17): i884-i890.
  2. Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., Szczesniak, M. W., Gaffney, D. J., Elo, L. L., Zhang, X. and Mortazavi, A. (2016). A survey of best practices for RNA-seq data analysis. Genome Biol 17: 13.
  3. Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M. and Gingeras, T. R. (2013). STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1): 15-21.
  4. Ferreira, M. S., Alves, P. C., Callahan, C. M., Marques, J. P., Mills, L. S., Good, J. M. and Melo-Ferreira, J. (2017). The transcriptional landscape of seasonal coat colour moult in the snowshoe hare. Mol Ecol 26(16): 4173-4185.
  5. Gallego Romero, I., Pai, A. A., Tung, J. and Gilad, Y. (2014). RNA-seq: impact of RNA degradation on transcript quantification. BMC Biol 12: 42.
  6. Jones, F. C., Grabherr, M. G., Chan, Y. F., Russell, P., Mauceli, E., Johnson, J., Swofford, R., Pirun, M., Zody, M. C., White, S., Birney, E., Searle, S., Schmutz, J., Grimwood, J., Dickson, M. C., Myers, R. M., Miller, C. T., Summers, B. R., Knecht, A. K., Brady, S. D., Zhang, H., Pollen, A. A., Howes, T., Amemiya, C., Broad Institute Genome Sequencing, P., Whole Genome Assembly, T., Baldwin, J., Bloom, T., Jaffe, D. B., Nicol, R., Wilkinson, J., Lander, E. S., Di Palma, F., Lindblad-Toh, K. and Kingsley, D. M. (2012). The genomic basis of adaptive evolution in threespine sticklebacks. Nature 484(7392): 55-61.
  7. Ojeda, D. I., Mattila, T. M., Ruttink, T., Kujala, S. T., Karkkainen, K., Verta, J. P. and Pyhäjärvi, T. (2019). Utilization of tissue ploidy level variation in de novo transcriptome assembly of pinus sylvestris. G3 (Bethesda) 9(10): 3409-3421.
  8. Rawat, V., Abdelsamad, A., Pietzenuk, B., Seymour, D. K., Koenig, D., Weigel, D., Pecinka, A. and Schneeberger, K. (2015). Improving the annotation of Arabidopsis lyrata using RNA-seq data. PLoS One 10(9): e0137391.
  9. Rougeux, C., Gagnaire, P. A., Praebel, K., Seehausen, O. and Bernatchez, L. (2019). Polygenic selection drives the evolution of convergent transcriptomic landscapes across continents within a Nearctic sister species complex. Mol Ecol 41(16): 291.
  10. Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., Pimentel, H., Salzberg, S. L., Rinn, J. L. and Pachter, L. (2012). Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 7(3): 562-578.
  11. Verta, J. P. and Jones, F. C. (2019). Predominance of cis-regulatory changes in parallel expression divergence of sticklebacks. Elife 8: 43785.
  12. Verta, J. P., Landry, C. R. and Mackay, J. (2016). Dissection of expression quantitative trait locus and allele specificity using a haploid/diploid plant system - insights into compensatory evolution of transcriptional regulation within populations. The New Phytologist 211(1): 159-171.

简介

[摘要 ] 适应被认为是部分通过基因表达的时空变化进行的。鱼种如 三脊棘背由于对不同环境的适应性差异很普遍,因此它们是研究基因表达适应性变化的遗传结构的强大脊椎动物模型,它们在野外和实验室中丰富且易于研究,并且具有完善的遗传和基因组资源。鱼g由于其呼吸和渗透调节作用,对局部水化学表现出许多生理适应性,包括基因表达的差异。但是,从流行于软骨和骨骼的小组织样本(例如鱼g)中,使用流行的基于柱的提取方法获得高质量的RNA可能具有挑战性。在这里,我们描述了不使用纯化柱的基于珠子的mRNA提取和转录组RNA-seq协议。为了使用动物或植物组织进行各种基因表达实验,可以根据样品量轻松调整实验方案。

[背景 ] 转录组测序(RNA-seq)用于量化基因的表达水平,鉴定样品组之间基因表达水平的差异并推断基因共表达。在进化遗传学研究,RNA-SEQ可以用来作为一种方法来研究自适应发散的分子基础(例如,Rougeux 等人;,2019 Verta酒店和Jones,2019) ,鉴定候选基因底层自适应的表型(例如,费雷拉等等人,2017),并推断未知基因的功能(例如,Rawat 等人,2015)。RNA测序的关键优势在于它可以轻松应用于几乎任何物种或组织,转录组测序通过开放非模型物种进行基因组研究而加速了进化研究。获得高质量的mRNA是成功进行RNA-seq研究的最重要前提(Gallego Romero 等人,2014)。这可能具有挑战性,因为与天生的DNA相比,RNA本质上更不稳定(也更脆弱)。标准的RNA提取方法通常会产生总RNA,包括注定要翻译成蛋白质的mRNA,以及非翻译的RNA,例如核糖体和调节RNA。通常,只有1-4%的总RNA可用于mRNA测序,因此少量组织的mRNA产量可能较低。此外,由于柱孔和柱孔的物理堵塞,异质组织样品(例如由软上皮,软骨和骨骼组成的鱼g)以及富含DNA的组织样品在基于柱的RNA提取方法中性能可能欠佳。 /或DNA沉淀。在这种情况下,使用oligo-dT包被的磁珠从组织裂解物中直接提取mRNA ,可提供一种直接且可扩展的提取解决方案。

在这里,我们描述了这种基于珠子的协议,用于从鱼g快速提取RNA(约1-2小时)和RNA测序。基于oligo-dT的技术依赖于mRNA poly-A尾巴与共价附着于磁珠的T-oligonucleotide片段的AT杂交,从而可从粗制细胞裂解物中纯化全长mRNA。该协议改编自Invitrogen 寡核苷酸dT Dynabeads 的原始协议,并在Verta 和Jones (2019)中进行了简要描述。该协议的版本略有不同,以前曾被用来研究在约1,000-2,000个细胞组成的小型植物组织中的基因表达(Verta 等人,2016; Ojeda 等人,2019 )。简而言之,将组织样品匀浆并裂解,然后使用磁性oligo-dT磁珠从组织裂解物中捕获mRNA。洗涤珠-mRNA复合物,然后用水洗脱。该协议可产生可用于RNA-seq和qPCR等应用的高质量mRNA。我们进一步提供了涉及RNA质量控制和定量,RNA-seq文库制备和数据分析的步骤示例。有关RNA-seq研究设计和最佳实践的一般指南,请参阅Conesa 等人的文章。(2016)。

关键字:转录组测序, 基因调控, 基因表达进化, 直接提取mRNA, 鳃组织

材料和试剂


 


1.5 ml无RNase的Safe-Lock Eppendorf管
21 G针
用于1.5 ml Eppendorf管的Micro-Tube聚丙烯杵(Bel-Art,目录号:BAF199230001)
量子位分析管(Thermo Fisher,目录号:Q32856)
无RNase的PCR条和盖
新鲜纸巾或液氮速冻纸巾
曲卡因甲磺酸盐(MS-222,Sigma-Aldrich,目录号:E10521)
碳酸氢钠NaHCO 3 (Sigma-Aldrich,目录号:S5761)
的Dynabeads mRNA的直接纯化试剂盒(赛默飞世Invitrogen,目录号:61011)
不含Turbo DNase的试剂盒(Thermo Fisher Invitrogen,目录号:AM1907)
Bioanalyzer RNA 6000 Nano试剂盒(安捷伦,目录号:5067-11511)
生物分析仪高灵敏度DNA试剂盒(安捷伦,目录号:5067-4626)
Qubit RNA BR试剂(Thermo Fisher,目录号:Q10211)
PrimeScript RT 预混液(宝酒,货号:RR036A)
用于CFX的Sybr Select 预混液(Thermo Fisher Applied Biosciences,目录号:4472942)
TruSeq链式mRNA试剂盒(Illumina,目录号:20020594)
SuperScript II逆转录酶(Thermo Fisher,目录号:18064014)
 


设备


 


剪刀(或刀片)和镊子
DynaMag2磁体(赛默飞世在vitrogen,目录号:12321D)
PCR循环仪(例如,Bio - Rad C1000 Touch,目录号:1851196 )
量子比特荧光计(Thermo Fisher,目录号:Q33238)
CFX96 Touch实时PCR循环仪(Bio - Rad,目录号:1855195)
2100生物分析仪(安捷伦,目录号:G2939BA)
 


软件


 


FastQC(https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
Cutadapt(https://cutadapt.readthedocs.io/en/stable/#)
STAR (Dobin 等,2013)
袖扣 (Trapnell et al。,2012)
 


程序


 


笔记:


对于从棘背g组织(?50 mg)冷冻的mRNA提取,请使用:
250 μ 升的裂解缓冲液


100 μ 升的的Dynabeads


600 μ 升的洗涤-A溶液(两次洗涤)


300 μ 升的洗涤-B溶液


è 琵琶?20 μ 升无RNA酶的水


可以针对不同大小的组织样本按比例缩放体积。


程序BG改编自最初的Invitrogen Dynabeads 方案,并修改了溶液体积,样品均质化和裂解步骤。需要额外的步骤HJ(不是Invitrogen原始协议的一部分)来确保无DNA的高质量mRNA的产量。
应立即遵循BH 程序。可以暂停实验的安全停止点是在过程A和H 之后。
 


          解剖整个棘背g
根据动物规程准则(例如,欧盟指令2010-63-eu和AVMA准则)对鱼实施安乐死,例如,用NaHCO 3 缓冲的三卡因甲磺酸盐(MS-222,pH 7.5)麻醉过量。注意,适当的浓度取决于鱼的大小。对于棘背类动物,我们使用10倍溶液(1.5 g / L),该溶液是通过将1.5 g MS-222和3.0 g NaHCO 3 溶解在1 L水族馆水中制得的。  
用手术刀和镊子取下头部(图1)。从腹侧开始,打开腹盖以露出g弓。如图1 B 所示,切出没有腹侧和背侧附着点的腮弓。雷姆OVE任何结缔组织不是鳃的一部分。
将1.5组织(?50 mg)收集在1.5 ml Eppendorf Safe-Lock管中,并立即在液氮中速冻。
将样品储存在-80 °C。
安全停止点


 


D:\ Reformatting \ 2020-1-6 \ 1902789--1295 Jukka-Pekka Verta 793031 \ Figs jpg \ Fig 1.jpg


图1. 刺le的解剖。通过沿横断面(红线,A )解剖取下头部,从安乐死的鱼中分离出整个isolated弓。然后在腹侧视图(B )中,通过解剖腹侧和背侧附着点(红线,B )切除g弓(蓝线)。


 


          洗涤并重悬Dynabeads
使Dynabeads 和溶液温热至室温。
每个组织样本准备一份1.5 ml Eppendorf。重悬的Dynabeads 轻轻吹打向上和向下,并等份100 μ 升的磁珠到每个1.5毫升Eppendorf管。
将试管放在DynaMag2磁铁上,等待约30 s,使磁珠形成沉淀(约30 s)。
除去上清液,不要干扰珠子。
从磁铁上移开试管,然后将Dynabeads重悬于原始体积的裂解缓冲液(100μl )中。
 


           使用杵将组织均质化为粉末
笔记:


通过用无菌剪刀或刀片将杵的圆锥形表面切成有角的表面,来修改Micro-Tube均质杵,以更好地破坏样品(图2)。
 


D:\ Reformatting \ 2020-1-6 \ 1902789--1295 Jukka-Pekka Verta 793031 \ Figs jpg \ Fig 2.jpg


图2. homogeniz的变形荷兰国际集团杵。为了更有效地破坏样品,请用无菌剪刀或手术刀刀片将杵的表面(红线,A )切成有角度的表面(B )。


 


将样品浸入液氮中以冷却杵,然后破坏样品。
从-80°C取出样品,并保持液态氮。
使用1.5 ml Eppendorf管中的研棒在液氮上将组织打成粉末。
在进行以下裂解步骤之前,请避免所有阶段的样品熔化。冷冻会破坏细胞膜并使RNA暴露于内源性RNase中,后者在解冻后会降解RNA。始终将冷冻样品放在液氮中。一旦引入了RNase抑制剂(例如Dynabeads 裂解缓冲液中的LiCl ,方案中的下一步),就可以有效地抑制RNA降解并解冻样品。
 


          裂解细胞
采取样品管直径:NE通过一个出液体氮,取出杵,但在250保持在手里,立即吸管μ 升裂解缓冲液中,然后丢弃该杵回管。
将冷冻管保存在您的手中,并用杵研磨冷冻的裂解缓冲液直至其融化,以确保融化后立即将样品悬浮在裂解缓冲液中。
对每个样本重复。
在进行操作之前,将裂解液通过21号针头移入5次,以弃去杵和剪切DNA。
注意:在您的试管仍然冻结时,引入裂解缓冲液。


 


           将mRNA绑定到Dynabeads
添加100 μ 升洗涤和再悬浮的Dynabead 每个样品,在室温下孵育5分钟,用CONTIN uing旋转(?500 RPM)。


注意:在此孵育步骤中连续混合对于减少Dynabeads 与基因组DNA 的结合非常重要。


 


           洗涤Dynabead -mRNA复合物
将样品放在Dynamag 磁铁上,等待磁珠形成沉淀(约30 s)。
从试管中除去所有上清液,而不接触珠粒。
从磁铁上移开试管,然后将珠重悬于600μl 洗涤缓冲液A中。
重复步骤s F 1- F 3进行第二次缓冲液A洗涤。
去除缓冲液,并使用300执行最后洗涤微升洗涤缓冲液B.
笔记:


使用前,清洗缓冲液应在室温下。
始终通过缓慢上下吹打溶液将珠子完全重悬在洗涤缓冲液中。重悬不足会导致DNA和核糖体RNA污染增加。重悬后应该没有可见的珠子团块。通过使用尽可能减少吸取珠子所需的最小量移液来避免RNA过度剪切/片段化。
您可以执行3 次洗涤A 以获得更好的样品纯度。
 


          从珠子洗脱mRNA
将样品放在磁铁上,等待珠子形成沉淀(约30 s)。
从试管中取出所有上清液,注意不要留下任何残留的缓冲液。
从磁体和r除去管esuspend珠20 微升无RNase水。
在热循环仪或热混合器中于65°C孵育样品2分钟。
立即将样品放在磁体上,然后将上清液移至新的无RNase的1.5 ml Eppendorf管中。
 


          用DNase处理mRNA提取
到20 微升洗脱的mRNA,加入2 微升的Turbo DNA酶缓冲液+ 1 微升的Turbo DNA酶。
在37°C下孵育20分钟。
加入5μl 灭活溶液,轻弹试管,在室温下孵育5分钟。
以10,000 xg 旋转1分钟30 s,并将上清液转移至新鲜的无RNase的试管中。
卡扣冻结最终mRNA提取较小等分试样(例如,10 微升)在液氮中,并存储在-80℃。
安全停止点


笔记:


治疗牛逼他整个20 微升mRNA的等份具有DNA从珠洗脱之后,不冻融。
无论是量化和质量控制(例如,量子比特和生物分析仪)的基因后立即DNA酶treatme NT或单独保留这些等分。始终避免mRNA样品的冻融循环。
mRNA样品中20-30%的核糖体RNA污染很常见。通过优化A洗涤体积,可以减少rRNA污染。您也可以尝试将裂解缓冲液加热至65°C或在珠子位于裂解缓冲液中时于65°C进行洗脱-重新结合循环。
Illumina TruSeq RNA- seq 方案始于mRNA选择,从而消除了大多数核糖体RNA和DNA污染(图3)。
 


D:\ Reformatting \ 2020-1-6 \ 1902789--1295 Jukka-Pekka Verta 793031 \ Figs jpg \ Fig 3.jpg


图3.使用管家基因的qPCR检测提取的mRNA中的基因组DNA污染。阳性对照(cDNA)的和mRNA的提取用的持家基因的引物的qPCR(扩增例如,紧密连接蛋白)。较低的Ct值(PCR周期,当可以检测到高于背景水平的荧光时,绿线)表示模板的丰度较高,在非逆转录mRNA提取的情况下,则表示来自基因组DNA的污染。未经DNase处理的Dynabeads mRNA提取物显示出DNA污染,在Illumina TruSeq RNA- seq 方案开始时执行第二个mRNA选择步骤后,几乎完全消除了DNA污染。经DNase处理的mRNA提取物未显示扩增,因此不含DNA。


 


            验证不存在基因组DNA污染
设计的一对扩增持家基因的PCR引物(例如,紧密连接蛋白),确保引物扩增一个单一的外显子内的片段(PCR片段不应跨越外显子-内含子边界)。目的是针对管家基因特有的引物(例如使用BLAST搜索,验证其他基因的序列相似性),以G / C核苷酸结尾并具有60 °C 的解链温度 ± 5 °C。对于棘背g 组织,我们使用claudin基因作为对照(Fwd:5'ACTTGGTGCCCTATCAAATGAGGTA 3',Rev:5'AGTTATACACGACGGGAGGATTGAG 3')。
选择阳性对照样品,并使用Takara PrimeScript RT Master Mix将mRNA反转录为cDNA 。
到5 微升mRNA提取,加入3 微升的水和2 微升的PrimerScript 主混合物。
在37 °C下孵育15分钟。
储存在-20 °C。
准备用于阳性对照(cDNA)的qPCR反应,并选择用于验证的mRNA提取物。
10 微升的2X 的Sybr 选择CFX主混合物


1 微升10 毫正向引物


1 微升10 毫反向引物


2 微升水


1 微升cDNA模板


使用以下程序在qPCR上运行样品:
50°C 2分钟
95°C 2分钟
95°C 30秒钟
55-65°C(特定于底漆的熔化温度)30 s
72 °C 30秒
[R E打开吨ò ? 。再增加39个周期
高温于4 °C
分析qPCR结果(图3)。经DNase处理的mRNA提取物不应扩增,而逆转录cDNA制备物应发出信号。没有逆转录的mRNA提取扩增表明来自基因组DNA的污染。在这种情况下,用DNase处理样品,并使用Bioanalyser 验证mRNA的质量。
 


            使用Bioanalyzer RNA 6000 Nano试剂验证提取的mRNA的质量(图4)。对于小于?5 ng / μl的浓度,请使用Bioanalyzer RNA 6000 Pico试剂。
注意:通常用于总RNA提取的RNA完整性数(RIN)不适用于mRNA提取,因为已删除了用于计算RNA质量和检测降解的大部分核糖体RNA。取而代之的是,使用mRNA片段大小的分布来确定样品质量好(一定范围的大小是高分子量)还是质量差(低分子量的RNA高度降解)(图4)。


 


D:\ Reformatting \ 2020-1-6 \ 1902789--1295 Jukka-Pekka Verta 793031 \ Figs jpg \ Fig 4.jpg


图4 。用生物分析仪检验mRNA的质量。使用Bioanalyser RNA 6000 Nano试剂分析的高质量(A)和劣质(B)mRNA样品示例。高质量的mRNA提取可显示出rRNA污染程度(10-30%)。25 nt 处的第一个峰对应于标记,(A)中的两个显着峰对应于18S和28S rRNA,宽峰对应于mRNA。请注意,劣质样品中mRNA大小分布的左移(较小大小的片段),表明mRNA片段已降解。


 


          使用Illumina TruSeq 试剂盒和试剂盒说明构建RNA-seq文库,但以下情况除外:
使用150 ng mRNA作为输入(使用BioAnalyzer RNA Nano或Qubit RNA BR试剂进行定量)。用不含RNase的水稀释至最终体积为50μl 。使用足够量的输入mRNA有助于避免最终测序文库中过多的PCR复制。
针对您要使用的测序策略优化片段化时间。使用时间序列测试片段化时间的影响,并使用Bionalyzer High Sensitivity DNA试剂分析片段大小,或参阅Illumina TruSeq RNA样品制备v2指南第109页。对于使用HiSeq 3000 150碱基对配对末端读数的棘背ill mRNA测序,我们使用了2 分钟(或2分钟)的片段化,最终平均插入片段大小约为290 bp。
使用提供的索引来识别测序后的样品,并以等摩尔量进行测序。为避免可能的批量影响,建议的策略是使用与样本数量一样多的索引,并在同一泳道中对所有样本进行排序。在实验设计允许的情况下,使用复制泳道并结合来自复制泳道的读数以达到所需的测序深度。
 


数据分析


 


下面的一般示例是在Unix / Linux / MacOSX 环境中使用命令行工具分析的三脊背棘鱼g 组织的150个碱基对的末端RNA-seq读数。鼓励用户修改以下过程中概述的路径以匹配其数据,并使用Shell脚本或复制粘贴在终端窗口中执行代码。有关测试样品组的详细信息,请参见Verta 和Jones (2019 )。


按照FastQC 网站和手册中概述的准则,使用FastQC 软件验证读取和库的质量。(http://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
注意:FastQC 可能报告RNA- seq 库包含高水平的PCR重复。这并不一定意味着文库已经进行了过多的PCR,因为预计许多读物会映射到高度丰富的转录本,FastQC 可以将其解释为PCR重复。


使用TrimGalore 从读数中修剪所有Illumina测序适配器。(http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/)
注意:或者,可以使用fastp 软件在一个步骤中执行质量控制和适配器修整(Chen et al。,2018)。


 


trim_galore \


- path_to_cutadapt cutadapt \


- 照亮\


-严紧度5 \


-质量20


- OUTPUT_DIR out_dir \


-配对


reads_R1_001.fastq.gz \


reads_R2_001.fastq.gz


 


生成STAR 基因组文件(仅在第一次使用给定的参考基因组时才需要)。
 


STAR \


- runMode genomeGenerate \


- runThreadN ?\


- genomeDir 基因组\


- 基因组FastaFiles gasAcu1.fa \


- sjdbGTFfile transcript.gtf \


- sjdbOverhang 149 \


- 基因组ChrBinNbits 18


 


对齐RNA测序读取到参考基因组(例如,宽S1,gasAcu1 [ 琼斯等人,2012 ] )与STAR aligner- 高执行对准该地址许多的带调心拼接有关的挑战RNA测序跨越内含子/外显子奔读取参考基因组的daries (Dobin 等人,2013年)。使用手动两次通过模式最灵敏地检测新型内含子-外显子边界。
对于每个样品,执行STAR 1 st pass以鉴定当前样品中的内含子/外显子边界。
 


STAR \


- readFilesCommand gunzip解-c \


- runThreadN ?\


- outFilterIntronMotifs RemoveNoncanonicalUnannotated \


- chimSegmentMin 50 \


- outFilterType BySJout \


- alignSJDBoverhangMin 1 \


- alignIntronMin 20 \


- alignIntronMax 200000 \


- alignMatesGapMax 200000 \


- quantMode GeneCounts \


- outWigType 摆动\


- outSAMtype BAM SortedByCoordinate \


- twopassMode 无\


- genomeDir 基因组\


- readFilesIn reads_val_1.fq.gz reads_val_2.fq.gz


 


对于每个样品,运行STAR 2 次使用跨越样本识别的内含子/外显子边界以上通知读对准通过。
 


STAR \


- readFilesCommand gunzip解-c \


- runThreadN ?\


- outFilterIntronMotifs RemoveNoncanonicalUnannotated \


- chimSegmentMin 50 \


- outFilterType BySJout \


- alignSJDBoverhangMin 1 \


- alignIntronMin 20 \


- alignIntronMax 200000 \


- alignMatesGapMax 200000 \


- quantMode GeneCounts \


- outWigType 摆动\


- outSAMtype BAM SortedByCoordinate \


- twopassMode 无\


- genomeDir 基因组\


- limitSjdbInsertNsj 2000000 \


- readFilesIn reads_val_1.fq.gz reads_val_2.fq.gz \


- sjdbFileChrStartEnd SJ_1.out.tab \


- sjdbFileChrStartEnd SJ_2.out.tab \





 


使用Cufflinks2.2 管道(Trapnell 等人,2012)进行参考指导的转录组装配以及转录本和同工型表达水平测试。为了以“参考指导”模式运行,需要描述已知基因模型的转录本gtf 文件。如果此信息不可用,袖扣还允许“无指导的”从头转录组装配。
 


袖扣


-p N \


--min-intron-length 20


--library型FR-firststrand \


- ?./ cloutGuided \


--frag-bias-correct gasAcu1.fa \


--multi-read-correct \


--min-isoform-fraction 0.15 \


--min-frags-per-transfrag 20 \


--max-multiread-fraction 0.5


-g transcript.gtf \


reads.out.bam


 


将样本级别的注释文件合并在一起(在assembly_list.txt中指定)。
 


cuffmerge \


-g transcript.gtf \


-o merged_assembly \


-s gasAcu1.fa \


-p N \


assembly_list.txt


 


量化基因模型上的RNA-seq读取覆盖率。
 


cuffquant \


-o out_dir \


-p N \


-v \


-u \


--library型FR-firststrand \


-b gasAcu1.fa \


merged.gtf \


reads.out.bam


 


标准化样本之间的读取覆盖率。
 


cuffnorm \


-p N \


-o out_dir \


-library型FR-firststrand \


-标签样本


merged.gtf \


abundances1a.cxb \


abundances1b.cxb \


abundances2a.cxb \


abundances2b.cxb \





 


使用Cufflinks 函数cuffdiff 测试样本组之间的差异表达。
 


cuffdiff \


-p N \


-o outDir \


-b gasAcu1.fa \


-u \


-每个条件的分散方法


-library型FR-firststrand \


--labels Group1 ,Group2 \


merged.gtf \


abundances1a.cxb ,abundances1b.cxb \


abundances2a.cxb ,abundances2b.cxb \





 


致谢


 


FJ由欧洲研究委员会(FP7)和马克斯·普朗克学会资助。该协议改编自Verta 和Jones (2019 )。


 


伦理


 


所有动物实验均按照欧盟和国家法规进行,并避免了对动物的不必要伤害(欧盟指令2010_63_EU)。


 


参考文献


 


Chen S.,Zhou Y,Chen,Y. and Gu,J.(2018年)。Fastp:超快速的一体式FASTQ预处理器。生物信息学34(17):i884-i890。
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费雷拉,MS,Alves,PC,卡拉汉,CM,Marques,JP,Mills,LS,Good,JM和Melo-Ferreira,J.(2017)。季节性外套颜色的转录景观在雪兔中蜕变。摩尔Ecol 26(16):4173-4185。
Gallego Romero,I.,Pai,AA,Tung,J.和Gilad,Y.(2014)。RNA-seq:RNA降解对转录物定量的影响。BMC Biol 12:42 。
琼斯,FC,Grabherr ,MG,陈,YF,罗素,P.,Mauceli ,E.,约翰逊,J.,斯沃福德,R.,Pirun ,M.,Zody ,MC,白色,S.,伯尼,E. ,Searle,S.,Schmutz,J.,Grimwood ,J.,Dickson,MC,Myers,RM,Miller,CT,萨默斯,BR,Knecht,AK,布雷迪,SD,Zhang,H。,花粉,AA,Howes ,T.,Amemiya ,C.,Broad Institute Genome Sequencing,P.,Whole Genome Assembly,T.,Baldwin,J.,Bloom,T.,Jaffe,DB,Nicol,R.,Wilkinson,J.,Lander, ES,Di Palma,F.,Lindblad-Toh ,K. and Kingsley,DM(2012)。三脊背棘回适应性进化的基因组基础。自然484(7392):55-61。
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Copyright Verta and Jones. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0).
引用: Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
  1. Verta, J. and Jones, F. (2020). mRNA Extraction from Gill Tissue for RNA-sequencing. Bio-protocol 10(5): e3539. DOI: 10.21769/BioProtoc.3539.
  2. Verta, J. P. and Jones, F. C. (2019). Predominance of cis-regulatory changes in parallel expression divergence of sticklebacks. Elife 8: 43785.
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