RNA Sequencing Frequently Asked Questions

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/Kinnex Full-Length RNA.

Standard, Strand-Specific, Single-Cell, Small, and Ultra-Low Input RNA-Seq use short-read sequencing on Illumina® platforms. Iso-Seq/Kinnex Full-Length RNA uses long-read sequencing on the PacBio® platforms.

For more information, visit our NGS Platforms webpage.

The most common starting material is extracted 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. Read our Sample Submission Guidelines for more information.

Since ribosomal RNA (rRNA) makes up most of the 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. 

Due to the anticipated poor quality and integrity of FFPE samples, we recommend using a library preparation with rRNA depletion or a targeted RNA exome library preparation (if applicable).

We recommend using a library preparation with rRNA depletion and globin depletion to improve the detection of low-expression transcripts.

Yes, within your GENEWIZ account, 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.

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.

ERCC stands for the External RNA Controls Consortium. The ERCC is a group of researchers and organizations that have developed a set of synthetic RNA molecules to standardize RNA quantification in gene expression profiling. The use of ERCC spike-ins can help standardize RNA quantification across different experiments. Using the read counts of the ERCC controls, researchers can determine the sensitivity (i.e., the limit of detection), dynamic range, linearity, and accuracy of an RNA-Seq experiment. They can also control technical variations between runs. 

When requested, GENEWIZ will use ERCC Spike-in Mix. The ERCC spike-in mix contains 92 transcripts of known concentration. The set is organized into four subgroups, each containing 23 controls that span six logs of dynamic range in concentration. Unless otherwise requested, spike-in across samples will be performed in a checkerboard pattern (assuming at least 1 sample between). 

We do not recommend utilizing ERCC spike-in on samples of low concentration.

Libraries usually undergo PCR amplification to boost the number of low-abundance transcripts in the sample, increasing the chances they’ll be read during sequencing. However, PCR does not copy DNA with perfect fidelity; it’s usually biased, as some molecules in a library are amplified more efficiently than others. PCR can also introduce errors, or mutations, when making copies. As a result, the sequencing data may not accurately represent the original population of RNA molecules. In other words, the relative abundance of reads differs from that of the input RNA. 

UMIs can correct the bias and errors caused by PCR amplification. By tagging the original cDNA molecule with a UMI, all its PCR copies will carry the same barcode. We recommend using UMIs with deep sequencing (>50 million reads/sample) or samples with low-input for library preparation. 

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.

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
• Custom analysis

View our demo bioinformatics report.

GENEWIZ can perform gene ontology analysis on the species in the following link. If the species is not listed, we reserve the right to remove gene ontology analysis from the project at the client’s discretion.

Yes, multiple comparative analyses can be performed. Depending on the complexity and number of comparisons, additional charges may apply and would be communicated prior to the work being performed.

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).

The GENEWIZ 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.

Our team prioritizes fast turnaround times and provide a timeline based on first-pass processing. The turnaround time listed within the quote is inclusive of all steps quoted, unless otherwise noted. If repeat processing is required, the turnaround may be subject to change and will be proactively communicated to the client.

If the scope of a project changes after project initiation or if sample or project clarification is required after sample receipt, GENEWIZ may reassess the turnaround time based on the subsequent communications and modifications (if applicable).

All extraction kits and reagents are routinely updated to remain best-in-class. Please proactively contact GENEWIZ if you would like historical versions, which may be available on a case-by-case basis.

Extractions are performed to the best of our ability and are unable to guarantee yield due to multiple variables that may affect sample yield and quality. Costs to cover the work performed will be applied, regardless of the outcome.

All extraction kits and reagents are routinely updated to remain best-in-class. Please proactively contact GENEWIZ if you would like historical versions, which may be available on a case-by-case basis.

For most of the services, an initial sample QC is included within the fee of the project for all samples that will proceed to the next processing stage (e.g. library preparation or sequencing) unless otherwise noted within the quotation. Resubmissions or additional, optional samples may incur a nominal fee for QC. 

Most services include an initial sample QC within the project fee for samples proceeding to the next stage (e.g., library preparation or sequencing). Resubmissions or additional samples may incur a small QC fee unless noted otherwise in the quotation. 

Initial sample QC can include: 

• Assessing RNA concentration and integrity 

• Assessing DNA concentration and DNA size (for select projects) 

• Assessing premade library size and concentration 

• Assessing cryopreserved cells by cell count and viability 

The sequencing platform will be listed within the Service Description of the quotation. 

Unless specifically noted in the quotation, GENEWIZ reserves the right to choose between equivalent instruments depending on the target read depth and configuration requested. If a specific instrument is required, please add special comments in your quote/order and notify our NGS team prior to project initiation.  

Illumina-based projects

For samples that pass QC and libraries prepared at GENEWIZ:

Data Quality

• NovaSeq 2x150bp: ≥85% of bases ≥Q30 

• NovaSeq 2x250bp: ≥80% of bases ≥Q30 

• MiSeq 2x150bp: ≥80% of bases ≥Q30 

• MiSeq 2x250bp: ≥75% of bases ≥Q30 

Data Yield

• Within 10% of total data target yield per lane or flowcell, unless otherwise noted 

• Within 20% of per sample target yield, unless otherwise noted 

Quality and yield for samples that do not pass QC and are processed at best effort are not guaranteed. Premade libraries/library pools submitted for sequencing only quality and yield are evaluated on a case-by-case basis. 

Multiplexing is performed to the best of our ability to ensure relatively even data distribution amongst samples. 

PacBio-based projects

Due to various sample-related factors that may influence long-read sequencing yield and quality, GENEWIZ cannot guarantee overall data output and quality. However, based on extensive experience with long-read workflows, GENEWIZ has established target metrics based on the PacBio system based on the sample submitted and library type. If a project does not meet these targets, a thorough review of the processing will be performed. If the issue is determined to be unrelated to the sample, a repeat or top-off will be performed as necessary.  

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

• Secure File Transfer Protocol (sFTP) - additional charges may apply 

• Customer Cloud Account - AWS, Microsoft Azure, Google Cloud 

• Hard Drive - additional charges may apply

By default, results are sent via a secure File Transfer Protocol (sFTP). Please refer to our sFTP Data Download Guide for instructions on how to download your data and troubleshooting tips. Additional charges may be applicable for large data transfers. 

Please refer to the delivery email sent from GENEWIZ for detailed information on the transfer and consult with your IT department to ensure compliance with your institution’s policies.