MicroRNAs (miRNAs) are a class of small non-coding RNAs that are recently found to be negative regulators of gene expression in eukaryotic organisms. Newly synthesized primary miRNA transcripts (pri-miRNAs) are processed by RNase III like enzyme, Dicer, to generate ~70 to 100 nucleotide (nt) hairpin precursors (Pre-miRNAs). Pre-miRNAs which are further processed by another RNase III like enzyme, yield mature miRNAs, averaging 21-23 nt in length. miRNAs are incorporated into the RNA interference (RNAi) effector complex, RISC, and target specific messenger RNAs for translational repression or mRNA cleavage. MicroRNAs show distinct expression patterns in different organisms, cell development stages, and disease models. Therefore, miRNAs play an important role in regulating gene expression 1-3.
1. Bartel, D. P. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–-297 (2004).
2. Ambros, V. The functions of animal microRNAs. Nature 431, 350–-355 (2004).
3. He, L. & Hannon, G. J. MicroRNAs: small RNAs with a big role in gene regulation. Nature Rev. Genet. 5, 522–-531 (2004).
- RNA-Seq provides a more comprehensive view of the transcriptome with a single experiment. RNA-Seq enables us to sequence and profile all species of transcripts in your total RNA samples.
- RNA-Seq is not necessarily dependent on any prior sequence knowledge. There is no need for design of probes that must be based on prior sequence or secondary structure information. Therefore, transcriptome profiling in any species is possible which makes this method particularly attractive for non-model species. Additionally, RNA-Seq data can be used to build de novo gene models.
- RNA-Seq has increased dynamic range and sensitivity. RNA-Seq enables you to achieve “digital” transcript expression analysis meaning that expression level data are based on each individual transcript that is sequenced and counted. By increasing the sequencing depth, a potentially unlimited dynamic range can be reached making RNA-Seq an ideal tool for detection of rare transcripts.
- RNA-Seq provides information of sequence variation in transcripts. RNA-Seq yields a rich data set including information about post transcriptional mutations and their genomic context. Because RNA-Seq data yields information about how exons are connected, it can reveal sequence variations in the transcripts due to alternative splicing events and provide allele-specific or isoform-specific gene expression information. Additionally, RNA-Seq data is useful for gene mapping functions such as describing the length of UTRs and exon boundaries.
We use the Illumina next-generation sequencing platform. Illumina’s industry-leading RNA sequencing methods enable discovery and profiling of RNAs in any organism without prior genome annotation, and allow for the most accurate detection and quantification of rare RNA sequences.
We recommend 1-3 µg total RNA as the starting amount for the RNA-seq library preparation. The minimum amount of total RNA we require to perform the sequencing service is 10 ng. If possible, we ask that you try to send more. Total RNA should be shipped in DEPC treated water at a concentration >100 ng/µl.
Make sure to use one of the commercially available column based RNA extraction kits that are specifically developed for RNA extraction for microRNA studies such as Norgen Biotek, Qiagen miRNeasy or Ambion miRVana kits. Please refer to corresponding manufacturer’s manuals. If you have multiple samples, make sure to use only one type of extraction kit for all the samples of your project.
Many laboratories have obtained excellent results from total RNA samples extracted using Trizol methods. However, skills, experiences and sometime sample types may become critical factors in obtaining consistently good sample qualities. According to our statistics, the method has an overall higher failure rate than column-based commercial methods, although the rate varies among different laboratories. If you must use a Trizol method, we recommend modifying precipitation step by doubling the usual isopropanol volume and leaving the RNA at -80°C for 10-20 minutes so as to ensure the precipitation of small nucleic acids. Some laboratories perform the precipitation step twice and/or perform a post-precipitation wash twice in order to clean up the sample. You will need to perform some tests in order to find a proper protocol for your sample.
There is no need to perform a small RNA enrichment step. We can accept fractionated microRNA but in this case, certain controls can not be included in your experiment and therefore, we cannot guarantee the quality of the data.
Please transfer your sample to a 1.5ml microcentrifuge tube for shipment (smaller tubes can crack when frozen). Be sure the tube labels match those listed on your sample submission form.
High quality results are dependent on high quality samples. There are several methods you can use to check the total RNA quality before shipping:
You can check the RNA quality with a Bioanalyzer, or a 1-1.5% agarose gel. High quality RNA will show a 28S rRNA band at 4.5kb that should be twice the intensity of the 18S rRNA band at 1.9kb. Excessive smearing indicates degraded RNA.
Additionally, you can check the UV spectrum of your sample and make sure that the 260 nm/230 nm intensity ratio is above 1.0 and that the 260 nm/280 nm ratio is above 1.8. (See exception for blood/plasma samples)
We can sequence up to 12 samples in 1 lane with the Illumina multiplexing protocol.
Sample: We use a combination of Bioanalyzer, spectrophotometer, and gel electrophoresis to determine initial quality of the samples received from the customer and to check the progress of the library preparation at various steps.
Library: We use a combination of gel electrophoresis and Qbit fluorometer to ensure the library is at an acceptable fragment size and concentration.
Sequencing: We check the number of clusters generated per tile for the first cycle of sequencing to make sure that it is within an acceptable density level to be sure chemistry is functioning properly. The total number of raw reads is also an indication of run performance and quality. Additionally, one of the sequencing lanes may be reserved for a quality control sample. The data from this lane must meet certain quality criteria in order for the run to be deemed successful.
Data: There is a standard Illumina base calling and data filtering program that is applied to the raw data to remove low quality reads. Additionally, we apply an LC Sciences developed analysis program to further filter the reads and reduce data to a final set of good quality mappable reads. The percentage of raw reads that are mappable is also a good indicator of run success.
Yes, the Illumina platform is very flexible and the “tunability” of coverage is one of the great advantages of new RNA-technologies. This enables us to achieve just the right amount of coverage that is required for your application.
Standard Data Analysis
- Illumina base-calling and analysis
- LC Sciences analysis and quality filtering. Processed data is reduced to mappable reads.
- Customer data report – includes a list of unique sequences and their copy numbers
- Custom construction of reference database(s) – miRBase, genome, etc and mapping of all quality reads
- Alignment, classification, & functional annotation of all mapped reads
- Prediction of possible novel miRs
- Biostatistical analysis – expression analysis, multi-parameter data analysis, length distribution, transcript copy number comparisons, etc
- Customer data report – includes a summary of methods and all statistic analysis
Custom Project Level Analysis
Custom project level service by LC Sciences microRNA experts providing integrated sequencing and custom microarray assays to serve the various needs of researchers from the research and biomedical fields. May include: differential expression and clustering analysis, pathway analysis (KEGG), GO term report, biomarker analysis, target prediction. Please contact us to learn how we can help get you the results you need to keep your research moving ahead.
RNA-Seq yields a rich transcriptome-wide data set including information about post transcriptional mutations and their genomic context. It can reveal sequence variations in the transcripts due to alternative splicing events and provide allele-specific or isoform-specific gene expression information. Microarrays are proven gene expression analysis tools that routinely deliver results rapidly, reproducibly, and cost effectively. So there is a trade-off. While RNA-Seq provides a more comprehensive view of the transcriptome and information about sequence variants, it is more expensive and lower throughput than microarrays, and bias could be introduced during extensive sample preparation steps effecting expression data.
The decision to use one method or the other depends on the specifics of your project. If you are working with a species whose genome is not well known or annotated, and your research is focused on discovery, we would recommend sequencing as the method for transcriptome profiling. If you are working with human samples or a model species whose genome is well annotated, and your goal is to systematically profile and compare the gene expression of many samples in various conditions or disease states, then we would recommend microarray profiling.
In many cases, a combination of the technologies is appropriate as they are quite complementary. Please see our Seq-ArraySM service for more information.