What are the advantages of using RNA-seq over microarrays? Is the cost significantly higher?
The upfront cost of performing a microarray-based experiment will cost less than an RNA-seq based experiment. However, consider these advantages of using RNA-seq over microarray before making your final experimental decision:
- How sensitive does your assay need to be? In RNA-seq, background noise is eliminated during analysis steps.
- What are you hoping to discover? RNA-seq has the ability to detect new and unknown transcripts, including instances where no reference genome exists using de novo analysis.
- What is the range of expression levels you are hoping to detect? RNA-seq has a much larger dynamic range of absolute expression levels that can be detected.
If any of these three areas is a consideration in your experiment, it may be cheaper and faster to start with RNA-seq, rather than starting with a microarray and switching to RNA-seq at a later date. You also have the option of doing an exploratory pilot study in which the number of reads per sample (and possibly the number of transcripts detected) is lower, say 10 million instead of 30 million. In this way, you skim the surface of your sample’s transcriptome before taking a deeper dive. For much more information than can be captured here, check out our most popular blog post on the subject!
What sequencing platform does Cofactor use for RNA-seq?
Your RNA-seq experiment will be sequenced using the Illumina platform, a sequencing-by-synthesis method. The Illumina high-throughput sequencing platform enables us to maximize experimental flexibility and sequencing accuracy to meet a wide range of experimental needs, at a cost per base that makes your experiment affordable to you.
Over the years, we have used many different sequencing platforms. At one time, we were the only shop in the world running 4 of the most widely available NGS platforms: Illumina, Applied Biosystems SOLiD, Roche 454, and Ion Torrent. Since that time we have sharpened our focus, but continue to evaluate new platforms to meet your needs.
Interested in longer reads for RNA or DNA applications? We also have experience with the PacBio platform.
What is the cost per sample for RNA-seq services?
To make things easier for you, we offer several production grade services that represent our most frequently sought after experimental parameters. On our Discovery Services page, you will find a comprehensive list of these services with the lowest prices and fastest turnaround times we offer. What’s even better is these prices include our standard comparative expression analysis!
If your experiment does not fit one of these services, or you are looking for something a little more custom, don’t hesitate to reach out to a Project Scientist through our web portal. We know that sometimes you will require tweaks to the type and number of libraries, the number of reads generated, the quality and quantity of the RNA, and a host of other factors. We are willing to work with you to design an RNA-seq experiment that exactly fits your needs.
What starting material do you accept?
All of our library sequencing services begin with total RNA. However, we know that getting to that step can sometimes prevent you from submitting your sample for RNA-seq. So, we try to take away that hurdle. We have partnered with a vetted RNA extraction service, that requires no additional work on your part. Further, for picoRNA projects, we do accept sorted cells. See our Sample Submission page for more specific guidelines regarding the starting material for your experiment.
What RNA library kits do you use?
Our Project Scientists are available to work with you to identify the appropriate sequencing library preparation to meet your experimental needs.
- sample quantity
- sample quality
- experimental goals
Interested in just mRNA? Consider mRNAble or picoRNA. These products use poly-A specific selections steps during the library prep.
Want to sequence intergenic, intronic, or other long non-coding RNA species? Total RNAble might be your best fit. Ribosomal RNAs are selectively removed, leaving the host of other cellular RNA species intact for sequencing.
Sample is low quality? FFPExact or RNAccess would be good choices! Both of these protocols evaluate sample quality based on DV200, rather than RIN score (DV200 is the percent of the RNA sample that is larger than 200 bp).
Each of our protocols starts with a commercially-available kit, which is then put through our rigorous testing, optimization, and validation. This ensures that we provide you with the most reproducible, high-quality data.
What is the minimum amount of total RNA required for sequencing?
We have RNA-seq options for a wide range of RNA quantities and qualities. An overview of these options are summarized in the figure on our Discovery Services page.
The minimum amount required for a successful RNA sequencing experiment depends on your experimental goals and the Cofactor Genomics sequencing product you have chosen to move forward with. See our Sample Submission Guidelines for more specific information regarding the minimum amount and concentration required for each protocol. For sample types with very low-input (>100 pg) but excellent quality RNA, picoRNA is an excellent option. We also have protocols for standard inputs (100 ng – 1000 ng), for low-quality (FFPE and degraded samples), and specific capture protocols.
How do you measure the quality of RNA we send you? What other quality control steps are in your pipeline?
For all samples that arrive in house, we use RIN scores (or DV200) to determine the RNA integrity (on an Agilent Bioanalyzer or TapeStation). We use UV spectroscopy (NanoDrop) to determine potential contamination (organics, DNA, etc), and we confirm the quantity by fluorometric-quantification (Qubit).
At each stage of our workflow (samples –> libraries –> sequencing –> analysis), the resulting material or data is passed through specific quality control metrics. Any anomalies or failures are reported to the customer immediately.
Following library preparation, we will again evaluate the integrity and quantity of the resulting material by Bioanalyzer/TapeStation and Qubit.
Following sequencing, we rigorously evaluate the resulting data prior to delivery. We’ll confirm quality and provide you with FASTQC Quality Plots, transcript coverage, saturation analysis, and replicate plots. For more information on these metrics, visit the ActiveSite help page.
What is the difference between poly-A enrichment and ribo-depletion?
PolyA amplification uses an oligo-dT primed amplification step to preferentially amplify the mRNA in a sample.
Ribo-depletion uses a probe-based method specific for the ribosomal content of the transcriptome from the organism under investigation. We use saturating amounts of these probes to remove a majority of the ribosomal RNA from the total RNA sample before cDNA is made. However, some rRNAs may remain in solution. For this reason, ribo-depleted RNA-seq data may contain more rRNA reads than than polyA amplified RNA-seq data.
How many reads do I need?
The number of sequencing reads required is highly dependent on your experimental goals.
If you’re looking to identify very highly differentially expressed genes, then skim (10 million single-end reads) coverage may be sufficient for you. If you know that your transcripts of interest are lower-level expressers, then we’ll want to sequence deeper to gain additional coverage of these molecules.
Importantly – deeper is not always needed. Dr. Jarret Glasscock speaks briefly about this in his blog post titled – Stop Sequencing!
For years, Cofactor has been evaluating “sequencing saturation” or how much of the transcriptome you’ve covered in your experiment. We can provide guidance based on your organism, your goals, and your sample quality. Importantly, sometimes the best bet is to do a small pilot project (see next FAQ below).
Why would I want to run a pilot project?
If this is your first RNA-seq experiment, or your first time working with Cofactor, you may wish to run a small pilot project. These small projects (8-20 samples) allow us to better understand the organism/samples you’re working with, and to demonstrate the value we provide.
A few other reasons to run a pilot include:
- To determine the best tissue/cell isolation technique and RNA purification technique for your sample type
- Set baselines for RNA quantity and purity
- Ultimately to determine the appropriate level of sequencing depth for the complexity of your samples.
Contact us to discuss how a pilot might fit into your experimental plans!
What kinds of controls or reference standards do you use?
Cofactor uses both internal and external controls in our RNA-seq experiments.
These include External RNA Control Consortium (ERCC) spike-ins (learn more in this Blog post), which may be used to monitor performance, and a human brain reference RNA mixture.
Additionally, assay-specific controls may also be employed (for experiments such as Pinnacle which require fusion-detection validation).
We routinely monitor the performance of these controls to ensure that the following variables: date, operator, reagent lots, etc. to ensure that these are not affecting our data output.
What kits do you recommend for RNA extraction?
We recommend the mirVana extraction kit from Ambion or the RNeasy kit from Qiagen to ensure high quality material. <link> For customers who are hesitant to conduct their own RNA extraction, we have partnered with an external lab to perform those extractions for you. An additional cost will be included in the initial quote, but otherwise this process requires no additional steps on your part.
I want to sequence miRNA. How do I modify the extractions to allow retention of small RNAs?
Small RNA sequencing requires total RNA as the starting material. Total RNA including small RNAs can be efficiently purified using a miRNA specific kit or eliminating the column purification step from a standard RNA extraction kit.
What are the advantages of paired-end vs. single-end sequencing reads? How does this affect the cost?
Single-end sequencing is ideal for comparative expression (transcript counting). With Illumina reads averaging 50-75 bp, we have sufficient bases for unique alignments to the transcriptome.
Paired-end sequencing is most useful for fusion detection, splice-variant, or structural characterization. We may also recommend paired-end sequencing for novel transcriptome assemblies.
Paired end sequencing does add additional cost to an experiment. You can expect it to be just under 2x the cost of a single-end price/sample, and add a bit more time to our quoted turnaround. If you’re not sure what you really need, our Project Scientist team is happy to walk through the advantages and disadvantages of each approach in more detail
My organism of interest doesn’t have a published reference genome or transcriptome. Can you assemble a novel transcriptome for me?
Certainly! We’ve assembled and annotated novel transcriptomes for a number of unique organisms.
Contact [email protected] to discuss how to best approach this type of experiment.
Can you provide me with a list of publications that you’ve been cited in?
Does Cofactor accept ready-to-sequence libraries?
Cofactor is able to accept client-prepared libraries in the form of either individual libraries for QC and pooling, or already pooled libraries ready for sequencing. However, we are unable to make any guarantees on libraries not made by our internal lab team. Please Contact Us to discuss your specific needs.
How do you deliver data? Is my data secure?
For clinical projects, we deliver a user-friend report. Please Contact Us for an example and to discuss your clinical needs in more detail.
What sorts of guarantees do you provide with your data?
Cofactor guarantees that we will deliver the number of reads quoted within 10%. Thanks to our exceptional QC checkpoints, we have a very low failure rate for samples that enter our library preparation pipeline. And, we are often able to predict poorly performing libraries even before sequencing, so we can feed this information back to you prior to delivery.
Within the ActiveSite dashboard, you’ll be able to see FASTQC quality plots which demonstrate the quality of data provided, transcript coverage plots which demonstrate the quality of libraries prepared, along with saturation analysis and replicate comparison plots, which allow you to identify biological outliers. Our goal is to ensure you have good quality data for downstream analysis, interpretation and validation.
Do you have customers that would be willing to provide a reference or recommendation?
Yes, please contact [email protected] and we’ll be happy to make an introduction to one of our clients for a reference.