|
|
|
 |
microRNA Microarray Service - Frequently Asked Questions |
Have more questions?
Call Email Chat
|
|
||||||||||||||||
|
GeneralMicroarray Design
Custom Sequences
Sample Preparation
Sample Submission
Sample Preparation and Labeling
Array ResultsData Analysis
Additional Questions
Answers - GeneralMicroRNAs (miRNAs) are a new 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. References: 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). Microarray DesignWhat is the array platform used by LC Sciences? These are not spotted arrays! Our microRNA microarray synthesis is based on a proprietary µParaflo® microfluidic chip technology developed by our partner, Atactic Technologies. This flexible technology enables fast, on chip synthesis of microarrays when ordered. (vs. an off-the-shelf spotted array) Please see our µParaflo® technology bulletin for further information. LC Sciences offers the most comprehensive line of standard microRNA detection arrays – all species for which sequence data exist in the Sanger miRBase Sequence Database. Although the sequence database is being continually updated as new sequences are experimentally verified, the contents of our standard arrays are updated in synchronization with the Sanger miRBase. This synchronization is made possible by our flexible µParaflo® microfluidic chip technology We also offer a NO-COST option to add up to 100 probes (of 25 nt or shorter) of your own design on each array. This option gives you the opportunity for discovering new small RNAs, adding internal controls, verifying hypothesis, or achieving any other enhancement that you would like to have. We also offer totally custom arrays at a very reasonable cost. This service gives you total freedom for the choice of probes up to 3,918 sequences. For example, you can screen for new microRNAs by adding predicted mature microRNA sequences or performing sequence walks along certain sequences sections. You can combine microRNA sequences of different species to identify cross-species conservations, add controls for the detection of customer-added spiking RNA sequences, or add probes for the detection of siRNAs and/or other small non-coding RNAs. Please talk to our customer support about your requirements. What is the Sanger miRBase Sequence Database? miRBase is a sequence database that has been established by the Sanger Institute. Each entry in the microRNA Registry represents a predicted hairpin portion of a microRNA transcript (termed mir in the database), with information on the location and sequence of the mature microRNA sequence (termed miR). The database was established with two broad aims:
When was the latest update of array sequences? The content of our microarrays was updated to miRBase Release 11.0 in April 2008. How many redundancies of each sequence are on the array? We include a minimum of three redundancies of each miRNA probe on the array. Our current standard Human miRNA Arrays contains seven redundancies. What is the makeup of the detection probes on the array? Do they vary in length? Each of our detection probes contains a coding segment and a spacer. The coding segment is a nucleotide sequence involving proprietary chemical modification for enhancing the detection of target transcripts. The spacer is a non-nucleotide molecule that extends the detection probe away from substrate and therefore further enhances the binding between the probe and the target. The length of the detection probes varies according to different targets. Are the Tms of the probes balanced? How? Yes, the Tms of our detection probes are balanced. By varying the number of modified nucleotides in each probe, we adjust the Tm of that probe. Our array detection signals are more uniform due to balanced Tms. Does the presence of modified nucleotides negatively affect the specificity of binding to the probes? No, we have done extensive studies and verified that these chemical modifications enhance weak signals without sacrificing binding specificity. We use specificity control probes on every chip and we show a perfect match to mismatch ratio of more than 10 for a spike-in control RNA sequence. Customers can easily examine the binding specificity of their array results by looking at control signals in the data they receive from us. Do I need to perform replicate arrays for more confidence in my results? We synthesize all sequences in a minimum of triplicate on the chip and our intra chip variability is very low. For single species arrays, more replicates can be added upon your request. Further, because our chips are based on the µParaflo® technology, the spot uniformity is excellent both within the chip and from chip to chip. The decision of how many replicate chips to run is up to you. Generally, customers will run a single chip and make an assessment to determine if experimental design is OK or needs to be altered before multiple chips are run to validate results. If you think there might be variability in your sample, you may want to run multiple (3) arrays. What quality control is used for manufacture of the array? Probes on our arrays are synthesized using chemical reagents of the highest quality. Every array produced has to pass a rigorous QC process which involves the hybridization with two testing DNA oligos labeled with Cy3 and Cy5, respectively. There are 16 sets of control probes on each array for the production QC. Our QC criteria include a across-array uniformity at a spot-to-spot CV less than 15%, a minimum hybridization intensity at a predetermined testing oligo concentration, and a match to (single-base substitution) mismatch ratio of larger than 10. What experimental controls are on the array? We spike a 20 mer control RNA into each sample followed by labeling and hybridization. The control RNA has been computationally and experimentally verified not to cross-hybridize with the probes of any known miRNA transcript. On each array there are 16 sets of control probes spatially distributed across the array. Each set contains a perfect match and a single-base-substitution mismatch for the control RNA. Chip and assay qualities, such as uniformity and specificity, can be assessed by examining the signal intensities of these control probes. Typically, the CV of the spot-to-spot intensities of the perfect match probes is less than 15% and the intensity ratio of perfect match to mismatch probes is larger than 10. Custom SequencesCan I add my own sequences to the array? How many? What is the cost? Yes, you can add custom sequences to any of the standard miRNA arrays. Assuming that your longest custom sequence is less than 25 nt, there is no charge for adding up to100 additional sequences to the array. What is the cost for adding longer oligos? If any of your sequences are longer than 25 nt (it doesn’t matter how many), there will be $5.25 charge for each additional nucleotide over 25 (count from the longest oligo). What if I want to add more than 100 sequences? We can fit approximately 1,500 additional sequences on each array. This number will vary slightly as each species array contains a different number of miRNA probes. Please talk to our customer support about your requirements. How much does it cost to add a large number of custom sequences? If more than 100 custom sequences are needed, we treat the array as if it is a custom array. See our custom microRNA microarray pricing page for details. How many redundancies of each custom sequence do you recommend? We recommend triplets although this will reduce the total number of sequences you can add to the array. Sample PreparationHow much sample do I need to send to LC Sciences? We recommend sending in at least 5µg total RNA of each sample per array. We prefer that you send total RNA but if you have already done the enrichment for microRNA, we ask that you try to send 2µg of microRNA. If you have difficulty in obtaining the above quantities, please call and talk to our customer support. We can use an optional amplification procedure and achieve results starting from as little as 0.1 µg total RNA, provided the RNA is very high quality. It is very important to use a total RNA preparation procedure that does not remove the low molecular weight RNA fractions. We recommend you to use one of the several commercially available RNA extraction kits that are specifically developed for micro RNA studies. Please refer to corresponding manufacturer's manuals. Use only one type of extraction kit for all the samples of your project. If this is your first time to perform total RNA extraction for a miRNA study or if you do not already have a preference for the extraction kit, we recommend the use of miRNeasy Mini Kit from Qiagen. Please make sure to choose “miRNeasy” and NOT “RNeasy”. 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 will perform small RNA enrichment in our own lab when we receive your sample. We can accept fractionated microRNA but in this case, certain controls can not be included in your experiment. 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. Is there a way I can check for the presence of small RNA in my total RNA sample before sending in the sample? Yes, but remember, QC of the RNA sample is included in our “Total RNA to Data” comprehensive service. We will not proceed with the array if we find the sample is inadequate. One quick way to check the presence of small RNAs is to use the Bioanalyzer from Agilent or run PAGE. You want to make sure that you see a clear band around 79 nt (tRNA) in your sample. Additionally, you need to 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. What if my sample does not pass quality control? We have found that sample failure is often related to the method of sample preparation used. There are several different proven methods and commercial kits now available however, some researchers may be very comfortable with one procedure but not with another. If your sample fails quality control, we recommend not to try to re-extract the RNA using the same method, but instead try one of the other methods available. If your RNA sample fails one of our quality control checks, we will not proceed with the array, but there will be a small processing charge to cover costs incurred to that point in the process. Sample SubmissionWhat is required for sample submission? Please complete a sample submission form prior to sending your sample to us. We request that you email the form to us beforehand AND place a copy of the form in the package along with your sample. We cannot begin work on your array without a PO Number or Credit Card Number. See our sample submission page for further information. How do I pack and ship my sample? Please transfer your sample to a 1.5ml microcentrifuge tube for shipment (0.5 ml or smaller PCR tubes can crack when frozen). If you want to seal the tubes or hold them in a rack, please don't use tape (it will crack when frozen), use parafilm. Pack the sample with dry ice in a thermal insulated shipping box. Ship by overnight carrier for delivery the next day. Note: Do not ship samples on Friday as they will sit over the week-end and deteriorate. Wait until the following Monday to ship the package for Tuesday delivery. Mail your package to:
Attn: microRNA Array Sample Can I send LC Sciences a sample from overseas? Yes, please download a copy of our International Shipping Instructions. Can samples be returned to me? Yes, we can return unused sample to you upon request. Please note that samples will be stored for a maximum of six months after your experiment has been completed. Sample Preparation and LabelingDo you isolate the small RNA from my total RNA sample? Yes, our standard service includes isolation of small RNA. We have compared the miRNA array results using isolated small RNA or total RNA samples. They are comparable and we found no loss of small RNA in isolation which is a simple filtration step performed with a size exclusion centrifugal filter (< 300nt is isolated). Since total RNA is a more complex sample and it costs you, the customer nothing extra for the isolation, we chose to offer our customers the highest quality service by isolating small RNA before labeling and hybridization. In short, isolation of small RNA is not a necessary step but it does offer cleaner results; as our customer, you can choose to process your sample either way. Currently we do not amplify the sample but instead we use a signal amplification strategy to detect small amounts of miRNA. We use a proprietary labeling method which utilizes an affinity tag for signal amplification after miRNA hybridization to the chip. In the case of a dual-sample experiment, the two sets of RNA sequences are labeled with different affinity tags to allow simultaneous detection of both samples. What does dual sample or dual color mean? By “dual sample” we mean that you can hybridize two samples at the same time to a single array chip. Each sample would be detected with a different fluorescent dye so that when hybridized, array spots appear red or green or yellow in a ratio image. For example, when a Cy3 labeled transcript is abundant, its corresponding spot (probe) would appear in green color. When a Cy5 labeled transcript is abundant, its corresponding spot would appear in red color. When a transcript has similar express levels in both Cy3 and Cy5 labeled samples, its corresponding spot would appear in yellow color. This is very useful whenever comparison of two samples is needed such as wildtype vs. mutant or samples treated in two different ways. “Color reversal” involves two chips. On the first chip you would label your sample “A” with Cy5 and your sample “B” with Cy3, respectively. On the second chip you would reverse the color by labeling your sample “A” with Cy3 and your sample “B” with Cy5, respectively. By correlating the results from two chips you would be able to eliminate or cancel most of the labeling, handling, and system related biases and therefore narrow down your calls to true biological differences. The color reversal method significantly improves the reliability of your results and will save you time, effort, and money from looking at falsely called genes or transcripts in any following up studies. Therefore, we strongly recommend the use of this method for any significant experiments. Array ResultsHow long will it take to get results? We can generally have data back to you about 2-3 weeks from the date we receive your total RNA sample. For each array, you will receive the original and processed microarray scan images, an array layout file, a raw intensity data file in Excel, a fully processed data file in Excel, and a list of up and down regulated transcripts that are called based on a statistical analysis. (dual sample arrays only) Additionally, for each batch of samples, you will receive a Data Summary containing a catalog of data files, images of representative regions of corresponding arrays, and descriptions of specific features of the arrays. The above files will be stored on a CD and will be delivered to you by express mail. View and download Example Data Files. Data AnalysisDoes the comprehensive service include data analysis? Yes, full data analysis is included for each chip in the comprehensive service. What is involved in the data analysis and what type of analysis results will I receive? Data will be corrected by subtracting background and normalized to the statistical median of all detectable transcripts. The data may also be normalized to one or a group of house-keeping genes that are added to the array as an option selected by customers. The data analysis also includes the calculation of p-values. Based on the p-value, a list of differentially expressed transcripts is produced. When a color reversal experiment is performed, two lists of differentially expressed transcripts from the two reverse labeled arrays are merged into one list. The differentially expressed transcripts having consistent calls on both arrays are grouped together in the merged list. You should focus mainly on this group of transcripts in your further studies. We have in house software for routine array data processing that follows the common practices of DNA array data treatment.4-7 The data are processed in a MS Excel spreadsheet using a program routine that performs raw signal background subtraction using a local regression method (Xiaochuan Zhou, unpublished results; note that the photolithographically fabricated arrays do not have peripheral areas for background values) Data normalization, using a cyclic LOWESS (Locally-weighted Regression) method8 is used to remove system related variations, such as sample amount variations, dye labeling bias, and signal gain differences between scanners, so that biological relevant variations can be faithfully revealed. Detected signals greater than background plus 3 times the standard deviation will be derived for each color channel; the mean and the co-variance (CV = stdev x100/replicate mean) of each probe having a detected signal will be calculated. For two color experiments, the ratio (log transformed) of the two sets of detected signals, and p-values of the t-test, will be calculated. Differentially detected signals are generally accepted as true when the ratios of the p value is less than 0.01. References: 4 Ball, C. A.; Sherlock, G.; Parkinson, H.; Rocca-Sera, P.; Brooksbank, C.; Causton, H. C.; Cavalieri, D.; Gaasterland, T.; Hingamp, P.; Holstege, F.; Ringwald, M.; Spellman, P.; Stoeckert, C. J., Jr.; Stewart, J. E.; Taylor, R.; Brazma, A.; Quackenbush, J. (2002) Standards for microarray data. Science 298, 539. 5. Quackenbush, J. (2001) Computational analysis of microarray data. Nature Rev. Genet. 2, 418-27. 6. Quackenbush, J. (2002) Microarray data normalization and transformation Nature Genet Suppl., 496-501. 7. Sturn, A.; Quackenbush, J.; Trajanoski, Z. (2002) Genesis: cluster analysis of microarray data. Bioinformatics 18, 207-8. 8 Bolstad, B. M.; Irizarry, R. A.; Astrand, M.; Speed, T. P.(2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185-93 p-value is a statistic parameter that measures the similarity of Cy3 and Cy5 labeled transcripts. The smaller the p-value is, the less possible the Cy3 and Cy5 labeled transcripts are similar. If a spot has a p-value less than 0.01, the Cy3 and Cy5 labeled transcripts detected by this spot are considered to be deferentially expressed in the two corresponding samples. Is clustering analysis available for multiple chip orders? Yes, for clustering analysis of multiple datasets, data adjustment includes data filtering, Log2 transformation, and gene centering and normalization. Data filtering will remove clustering values from the data set (detected signals or detected ratios that are below a threshold value) Data centering and normalization will transform Log2 values using the mean and the standard deviation for individual miRNA across all samples We will perform clustering with a hierarchical method using average linkage and Euclidean distance metric. The clustering data can be visualized using one of the several microarray programs, such as TIGR MeV (Multiple Experimental Viewer) (the Institute for Genomic Research). Yes, the data package that we send to you contains sufficient raw data and array layout information for you to carry out you own data analysis. Additional QuestionsCurrently the array chips are not available for separate purchase without the service. Our technology utilizes a microfluidics chip that requires additional liquid handling equipment not available outside our lab. In the future we hope to be providing this equipment so that users may perform their own experiments. We have a very well-trained and knowledgeable staff of scientists here at LC Sciences. If there is some specific experimental work you need done, we would be more than happy to put together custom service package designed specifically for your research needs. Yes, they are listed on our publications page. There are currently several other groups working on manuscripts that will include data from LC Sciences arrays. We expect these to be published in the near future. Can LC Sciences provide assistance with summarizing the microRNA microarray expression assay for my publications? Sure, below is a suggestions: Microarray assay was performed using a service provider (LC Sciences). The assay started from 2 to 5 µg total RNA sample, which was size fractionated using a YM-100 Microcon centrifugal filter (from Millipore) and the small RNAs (< 300 nt) isolated were 3’-extended with a poly(A) tail using poly(A) polymerase. An oligonucleotide tag was then ligated to the poly(A) tail for later fluorescent dye staining; two different tags were used for the two RNA samples in dual-sample experiments. Hybridization was performed overnight on a µParaflo microfluidic chip using a micro-circulation pump (Atactic Technologies)9. On the microfluidic chip, each detection probe consisted of a chemically modified nucleotide coding segment complementary to target microRNA (from miRBase, http://microrna.sanger.ac.uk/sequences/) or other RNA (control or customer defined sequences) and a spacer segment of polyethylene glycol to extend the coding segment away from the substrate. The detection probes were made by in situ synthesis using PGR (photogenerated reagent) chemistry. The hybridization melting temperatures were balanced by chemical modifications of the detection probes. Hybridization used 100 µL 6xSSPE buffer (0.90 M NaCl, 60 mM Na2HPO4, 6 mM EDTA, pH 6.8) containing 25% formamide at 34 °C. After hybridization detection used fluorescence labeling using tag-specific Cy3 and Cy5 dyes. Hybridization images were collected using a laser scanner (GenePix 4000B, Molecular Device) and digitized using Array-Pro image analysis software (Media Cybernetics). Data were analyzed by first subtracting the background and then normalizing the signals using a LOWESS filter10 (Locally-weighted Regression. For two color experiments, the ratio of the two sets of detected signals (log2 transformed, balanced) and p-values of the t-test were calculated; differentially detected signals were those with less than 0.01 p-values. References: 9. (a) Gao, X., Gulari, E., and Zhou, X. (2004) In situ synthesis of oligonucleotide microarrays. Biopolymers 73, 579-596; (b) Zhu, Q., Hong, A., Sheng, N., Zhang, X., Jun, K.-Y., Srivannavit, O., Gulari, E., Gao, X., and Zhou, X. (2006) Microfluidic biochip for nucleic acid and protein analysis. in Methods Mol. Biol. Ed. Rampal, J. B. in press. 10. Bolstad, B. M., Irizarry, R. A., Astrandand, M., Speed, T. P. (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinfo. 19, 185-193. For other questions please send us an email at service@lcsciences.com or call us at 1-888-528-8818
|
|
Sitemap • Privacy • Terms of Use • Disclaimer |
Copyright © 2008, LC Sciences |