RNA Sequencing Frequently Asked Questions

General Questions

1. What is RNA-Seq?

RNA-Seq is a method for transcriptome profiling that uses next generation sequencing technologies. RNA-Seq provides a comprehensive, quantitative, and unbiased view of RNA sequences within every sample, and is the most powerful tool currently available for analyzing gene expression.

For more information, download our eBook A Guide to RNA-Seq or read our article Which RNA-Seq Technique Should I Use?

2. What are the technical details of your RNA-Seq services?

Please download our Technical Specifications Sheet for a summary of our Standard, Strand-Specific, Small, and Ultra-Low Input RNA-Seq services. Visit the following pages for more information about Single-Cell RNA-Seq and Iso-Seq.

3. What starting materials are accepted?

We recommend starting with total RNA. However, we have extensive experience performing extractions from a wide variety of materials, including cell pellets, fresh frozen tissue, blood, and FFPE slides. We also accept sorted cells for Ultra-Low Input RNA-Seq. Check out our Sample Submission Guidelines for more information.

4. What method is used to remove ribosomal RNA?

Since ribosomal RNA (rRNA) makes up the majority of total RNA, its removal is necessary for efficient sequencing of other RNA species, such as mRNA, long non-coding RNA (lncRNA), and small RNA.

  • For Standard and Strand-Specific RNA-Seq, you can select either poly-A selection or rRNA depletion methods. Poly-A selection is sufficient for studying mRNA in eukaryotes. Analysis of lncRNA or bacterial transcripts requires rRNA depletion.
  • For Ultra-Low Input RNA-Seq, the default is to use poly-A selection. However, if your project requires analysis of lncRNA in addition to mRNA, please make a comment on the quote request form, and we can discuss the available options.

5. How many reads do I need for my experiment?

The number of reads required depends upon the genome size, the number of known genes, and transcripts. Generally, we recommend 5-10 million reads per sample for small genomes (e.g. bacteria) and 20-30 million reads per sample for large genomes (e.g. human, mouse). Medium genomes often depend on the project, but we would generally recommend between 15-20 million reads per sample. For de novo transcriptome assembly projects, we recommend 100 million reads per sample.

6. What bioinformatics services are available for RNA-Seq projects?

We provide raw data as FASTQ files for all projects. We also have advanced bioinformatics capabilities to provide optional data analysis services, including:

  • Standard RNA Analysis Package: mapping, differential gene expression, alternative splicing, and gene ontology analysis
  • Gene fusion discovery
  • SNP/INDEL detection
  • Novel transcript discovery
  • De novo transcriptome assembly for sequences that do not have a reference

View our demo bioinformatics report.

7. How does Single-Cell RNA-Seq differ from Standard and Ultra-Low Input RNA-Seq?

Standard RNA-Seq produces a representative snapshot of the transcriptional state averaged across all cells. The caveat with traditional RNA-Seq is the resolution of individual cells and cellular subpopulations are lost. Single-Cell RNA-Seq allows researchers to not only identify cellular subpopulations, but to fully interrogate them at the single-cell level within a heterogeneous sample.

Similar to Standard RNA-Seq, Ultra-Low Input RNA-Seq provides bulk expression analysis of the entire cell population; however, as the name implies, a very limited amount of starting material is used, as low as 10 pg or a few cells. Single-Cell RNA-Seq requires at least 50,000 cells (1 million is recommended) as an input.

For more information, read our articles:

Top 3 Factors to Consider for Single-Cell Sequencing

How Single-Cell Sequencing Works

8. What sequencing platforms are used for RNA-Seq?

Standard, Strand-Specific, Single-Cell, Small, and Ultra-Low Input RNA-Seq use short-read sequencing on Illumina® platforms, such as the NovaSeq and HiSeq. Iso-Seq uses long-read sequencing on the PacBio® Sequel®.

9. How does Illumina-based RNA-Seq compare to Iso-Seq on PacBio?

Generally, Iso-Seq is superior to Illumina approaches when qualitative endpoints are of interest, such as alternative splicing, alternative polyadenylation, genome annotation, and novel transcript detection. For quantitative assessment (e.g. expression of transcript A vs B in one sample, or expression of transcript C in sample 1 vs sample 2), short-read-approaches are recommended due to the greater number of reads that can be obtained.

10. Can you analyze small RNA or miRNA?

Yes, select our Small RNA-Seq service. Please note that our library preparation for Small RNA-Seq uses kits that specifically recognize the 5’ and 3’ ends of RNA after processing by DICER. A different library preparation method is used for Standard RNA-Seq projects for analysis of mRNA and lncRNA.

11. Can you prepare small and standard RNA libraries from the same total RNA preparation?

Yes, if enough input material is provided and the total RNA preparation contains small RNAs. Since Standard RNA-Seq and Small RNA-Seq use different library preparation methods, the total RNA sample must be split.

12. Do you offer RIP-Seq (RNA immunoprecipitation with sequencing)?

We can accept immunoprecipitated RNA for our ultra-low input RNA-Seq service. Please note that we do not perform the immunoprecipitation step.

13. How do I contact Azenta for a technical consultation about my project?

Azenta's NGS Team is composed of Ph.D. scientists who can help you optimize your project design and provide consultation. You can contact the team by submitting an inquiry here.

14. Can you recommend the best data delivery option?

Yes, we can recommend the best data delivery option based on the platform and project details. Options include:

  • Secure File Transfer Protocol (SFTP)
  • Customer Cloud Account
  • Hard Drive (additional charges may apply)

15. How will my data be delivered?

If your results are being shipped to you via hard drive, you can track its shipment using the tracking number provided to you in the delivery email sent from Azenta.

If your results are being delivered via another data delivery method, such as AWS S3, Aspera, or other cloud-based methods, please refer to the delivery email sent from Azenta for detailed information on the transfer, and consult with your IT department to ensure compliance with your institution’s policies.

If your results are being sent via a secure File Transfer Protocol (sFTP), please refer to Azenta's sFTP Data Download Guide for instructions on how to download your data and troubleshooting tips.

16. What is the price for RNA-Seq?

Please submit a quote request to receive accurate pricing information, as the cost depends on the details of the project.

17. What are the differences between the Service Packages?

The packages differ in price and turnaround time:

  • Value is the most economical: ~10% less in cost and ~2 weeks longer than Preferred
  • Preferred offers a balance of speed and cost, leveraging our optimized processes for industry-leading turnaround time at an affordable price
  • Express is the fastest: ~1 week faster and ~20% more in cost than Preferred

Furthermore, Preferred and Express options include guaranteed turnaround time and dedicated project managers. The package type can be revised after receiving your initial quote. For more information, visit our selection guide.

Note: Service packages are not available for all services, projects, or institutions. Single-Cell RNA-Seq and Iso-Seq are excluded.

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Sample Preparation

18. How should I prepare and send my samples?

View our Sample Submission Guidelines for instructions on preparing and sending your samples for RNA-Seq. Ship samples directly to our facility. Use the shipping address listed on the order receipt.

19. What happens if my samples do not meet your starting material requirements?

Please reach out to us by submitting an inquiry here.

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Order & Processing

20. How do I request a quote?

For a quick tutorial, watch the video below.

21. How do I confirm a quote?

For a quick tutorial, watch the video below.

22. How can I monitor the progress of my project?

The status of your order, including an estimated date of delivery, can be viewed anytime through your Azenta account. Visit the Order Summary page of your project to find the current order status.

23. How long do you hold samples?

We hold samples for 1 year after project completion. Please contact us if you would like samples retained for a longer period of time or shipped back to you.

24. How do I use UMIs to de-duplicate data for my RNA-Seq experiment?

We use the Twist UMI system by default. UMIs are sequenced in-line and each pair of reads is structured as 5bp UMI + 2bp spacer + subsequent read sequence:

For UMI extraction together with quality/adapter trimming, we recommend using the fastp tool found here: https://github.com/OpenGene/fastp. Please download and install the tool before proceeding. Detailed instructions on how to process your data with UMIs can be found on the git page under session ‘unique molecular identifier (UMI) processing’ and the corresponding example.

UMI extraction will be enabled with the -U or --umi option in the command line.

For UMI deduplication, it can be performed in a one-line command together with the previous step by enabling deduplication in fastp (specifically -D or --dedup).

After trimming and deduplication, the resulting reads can be aligned to your reference genome. You can also proceed with downstream analysis including hit count calculation as normal.

The raw reads we provide can also be processed with other UMI extraction and deduplication tools such as umis tool and umi-tools, depending on your preference. The processing order will be different compared to fastp, as the deduplication step will need to be performed after UMI extraction, trimming, and alignment. More details can be found in the user instructions for the umis tool (https://github.com/vals/umis) and umi-tools (https://umi-tools.readthedocs.io/en/latest/index.html).


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