Hi Azeem, There is no difference between RNA-seq and transcriptome sequencing - it's the same. And you are correct, even with NGS you would have to do two (sequencing) runs: the library prep for miRNA/small RNA is different than that for mRNA.

Unless you are dealing with a not well characterized species or want to do discovery work I would re-consider arrays. For the same price you would be able to run many more biological repeats and get descent statistics. Not to mention the much easier and established data analysis... A good comment on this can be found here: http://rna-seqblog.com/information/the-magic-of-rna-seq/

Best - christoph

Hi Azeem, There is no difference between RNA-seq and transcriptome sequencing - it's the same. And you are correct, even with NGS you would have to do two (sequencing) runs: the library prep for miRNA/small RNA is different than that for mRNA.

Unless you are dealing with a not well characterized species or want to do discovery work I would re-consider arrays. For the same price you would be able to run many more biological repeats and get descent statistics. Not to mention the much easier and established data analysis... A good comment on this can be found here: http://rna-seqblog.com/information/the-magic-of-rna-seq/

Best - christoph

Our lab is looking to do the same thing. First, RNA-seq and whole transcriptome sequencing are one in the same. However, whether you can run TOTAL RNA (mRNA + miRNA + everything else) depends on your sequencing platform and your preparation methods. Illumina is the gold standard for this (our sequencing core just got their hands on one, so we've yet to try any samples on it, but have done so for the traditional ABI capillary and 454 sequencers). MicroRNAs normally require a size selection process (usually run them out on a gel and cut out the right size segments, although we do immunoprecipitation of RISC protein Argonaute2 first in order to capture only the mature miRNAs in use as well as all of the transcripts they're targeting) combined with artificial adapter ligations on one or both ends before cDNA synthesis. I've seen some groups do every kind of RNA together, using a universal adapter, but I can't say I trust their results entirely without some initial segregation of sequence types, mostly, because of the sequencing depth afforded by Illumina platforms. Illumina is great, from what I know second-hand (again, we're just getting ready to try this ourselves), for sequencing miRNAs seperately, but throw in longer sequences, especially if you don't have a highly annotated genome like that of mouse or humans, and trying to accurately distinguish miRs from mRNAs in your resultant datasets can be difficult. So, I would say the short of it is to 1. know your platform, 2. decide on the question you're going to be asking specifically, and 3. have your bioinformatics methods worked out thoroughly beforehand so that you know what challenges you'll face given a segregated versus a combined RNA sequencing approach. Sorry if this wasn't much help. We're not too far ahead of you in feeling our way through the process.

Thank you everyone for reply. I feel that when performing transcriptome or RNA -seq, during filteration step miRNA may get deleted/discarded. Also, the bioinformatics methods are still not running parallel to sequencing advancements in my opinion. What I am thinking to do is to perform TOTAL RNA extraction and then use same RNA for separate sequencing runs for miRNA and mRNA which is also called mRNA-seq by illumina. Samples here I am dealing with are human intestine tissues. I aim to obtain parallel expression profiles of miRNA-mRNA and then correlation etc etc. I think that either there should be microarray for both or NGS for both. I personally don't feel that it will be parallel if miRNA will be by NGS and mRNA by microarray or vice versa..any comments please?

Single reactions/wells of next-gen sequencing can not read through whole mRNA length in most cases. With paired-end technology you can have information on which sequences belong together but that can not help reading the middle part. Even if you have a reference genom sequence this isnformation is usually insufficient, especially due to the zillions of possible splice variants, SNPs, homologues and things that can be recognized only by reading each and every nucleotide. Therefore prior to ligating the adaptor to the end(s) of the RNA molecules, the mRNA is usually broken (sonicated, etc.) to smaller parts, so that the overlapping sequences could possibly cover the whole mRNA span. And here comes the problem. If you do not separate miRNA before that, and you do not sequence them separately, then you will never be able if a particular small sequence comes from a mRNA or it was a miRNA in the cell.

The last sentence should read like: "If you do not separate miRNA before that, and you do not sequence them separately, then you will never be able to find out if a particular small sequence comes from a mRNA or it was a miRNA in the cell."

Hi Azeem, each of the systems (sequencing and array) will have their own method based bias. Wether you dare to fuse data from one experimental subset analyyzed on one platform with the other experimentalsubset analyzed on the other platform highly depends on your experimental question. If possible I personnally would prefer to fuse data coming from one technical platform. One major reason would be convenience E.g. if you focus on array data only you would need less datahandling capacity and bioinformatic extraction work. If you use array and sequencing youlose that advantage and have to solve the problems related with both platforms. Irrespective of what platform you select note that you should only compare logfold change data i.e. biological changes -relative expression data. The obtained direct readouts can be only taken as a mere indication of amount, but should not be taken as real amount data as such since it is always biased by the technical platform used.

so what about the mRNA-seq from illumina? http://www.illumina.com/applications/sequencing/rna.ilmn

I also came across some papers in which they have used mRNA-seq for mRNA expression analysis. As I mentioned in my above post that I have to obtain miRNA and mRNA expression profiles from same samples and then correlate. As Jorg mentioned, I also feel the same that there will be bit ease in working with microarrays than NGS but apart from personal choice, I have to perform NGS and at the same time, have to obtain mRNA profiles from same samples also... :| so here comes the issue or bottleneck.

Hi,

If I just a bit to your last entry....I recently performed miRNA expression profile using Exiqon LNA platform and illumina small RNA sequencing (RNA from the same tube were submitted for both analyses)....all the data is not validated yet but I find NGS quantitation to be more reflected in subsequent validation by ABI Taqman qPCRs. I probably will be in position to say more in a few weeks time. Arrays would be cheaper than NGS but I am not sure yet how validatable the data is on qPCR platforms!!!

Regards

Hi Sankar, please keep me updated on the validation! Let me only say that much here that the LNA based platforms can broaden the detection range i.e. also giving you good data from AT rich miRNA which can often be problematic using other platforms due to low tm /stringency. You are welcome to discuss this directly with me so that we do disturbe this thread with an 'off topic' discussion.

Here are a few articles which might help in thinking about cross platform comparisons and validations--PMID: 22144189, 21347261, 19948767, 19176604

Hi Jörg, That would be great, finding out what one can do to handle in problematic regions, such as AT rich, repetitive, or others. So that is by far not OffTopic.

I agree that the two investigations should be done on the same platform, if possible. I may also agree that the chip can be easier to do, especially with respect to the bioinformatic part. NEVERTHELESS, I myself would stick to the sequencing over the chip, as chips usually have only the coding sequences on them, therefore the intergenic regions are not covered, hence it is not really possible to correctly find all possible miRNA, not to mention the non-coding strand. So unless you are sure that your chip covers all possible RNA species that you are interested in, (or: unless you are interested only in RNA molecules [mRNA and miRNA] that are on the chip) you should (I would) possibly refrain from using chip-based method. In my view the greatness of the "next generation" or "new generration" sequencing does not only stem from the high throughput, but even more importantly from its assumption-free nature. Hindered by only those nasty technical problems that are breefly mentioned above.

Hello

RNA-Seq is more wide term. RNA-Seq includes transcriptome sequencing (polyadenylated RNA), "all" RNA sequencing (include rRNA and non-coding RNA) and variant for various non-coding small RNA sequencing. The main difference in a method of probe preparation.

Many Thanks.

LNA based chips are great for high specificity and range of 'known' miRNA pools (offered by Exiqon and Now Dharmacon, ThermoFischer); however as Peter has alluded one can not get the entire miRNA profile. Thus Illumina based NGS profiling is superior to fathom miRNA expression from a tissue RNA sample. Chips make bioinformatics easy, but leave miRNA species that was not printed on the chip.