The cp values are too high for ribosomal. Normally you should need to dillute the sample at least 1000 times.

I think the pcr is not performing well. To discard this possibility, try a pcr with the same mix and sample, but with a dna (plasmid?) with known concentration (spiked or external control), and thus, copy nr. 

If the cp is not that expected, then the sample or some component is inhibiting the pcr. 

Hi da,

RT-ve means, no reverse transcriptase? and, you use random hexamers for cDNA synthesis right? Also, do you use SyBR green or TaqMan probes?

Hi Carrasco. Thank you for the response. Yes I get that but do you think you should/will get a Cp value even in the case of no reverse transcriptase [I meant these samples had no RT during cDNA synthesis]? My test primers had no Cp values [as expected] but my 18S primers had Cp between 30-35. Contamination could be ruled out as my water controls also had no Cp values. I hope I am not confusing you!! Sorry..

Hi Devdu!! Yup RT-ve is no reverse transcriptase and I use oligodT as primers for cDNA and I use SYBR green!!! But what effect would that have on my results??

Hi da! usually 35+ Cp values are not considered with confidence. And, as far as I know, only mRNAs have polyA tail. rRNAs need not have polyA, for you to use oligodT. So how are the Cp values for you actual samples? And, which instrument do you use (different makes calculate Cp differently)? 

Hi da!! I guess 35+ would be of less confidence if I it was for 40 cycles. But I ran it for 50 cycles. But still, it is a pretty good point about using oligodT  for cDNA syn and 18S as internal control for qRT. Probably I should change the controls!! And for RT+, I get values around 27-29.. I also found this site "http://www.protocol-online.org/biology-forums-2/posts/28704.html" just now and it discusses about 18S as internal control, oligodT for cDNA  syn but in the case of human cells.. I wonder how it is for mouse cell lines!! I used Roche Light cycler 480 da..

We didn´t talk about melting courves yet. A Cp value can be obtained just by artifacts due to primer dimer, for example. Please, tell me how do the melting courves look like. A single peak?

Yes I thought about that and looked at my melting curves and found it to be a single peak.. Also, I think I will have to change my internal control.. As mentioned by Devi Prasad, using 18S rRNA for a cDNA obtained using oligodT primers doesn't seem to be logically right.. I will have to use a different internal control (Actin/GAPDH)... Please let me know your views on that too.. Thanks.. 

I was about to cite this paper that talks about polyadenylation in a population of rRNA in humans (http://nar.oxfordjournals.org/content/34/10/2966).

Beyond 35 cycles, some non-specific amplifications may crop up from tiny amounts of template, no matter what the final total number of cycles is. So whether the total number of cycles matter for considering values >35, I'm not sure.

Secondly, for a 1:2 diluted cDNA from 1 microgram of mouse total RNA, I get Cp values of 19-21 for GAPDH. But given that rRNA is in large abundance, you should be getting a much lesser Cp value, instead of 27-29. So you might want to verify that. 

I have a few more questions: What is your amplicon size? and are you getting an expected Tm from the melt curve? Since you're using oligodT, one possibility of a single melt curve could even be primer dimers; were primer sequences analysed? Did you have a control with all components same, but water instead of template? If nothing appeared in that, did you do a primer blast against the mouse RNA database for non-specific targets? Do you do DNase treatment before RT?

With 18S, you are merely adding too much sample to the qPCR - 18S is so abundant that it shuts down the reaction by template inhibition.  Dilute all samples (being analyzed for 18S) by another 1:500 or 1:1000 and then you will start to get signal in the right range.  Dust in every room will always give you a Cq value for 18S in your negative controls at ~36 to 38 Cq, since it is so ubiquitous and hyper-abundant.  As long as your intended 18S Cq values are greater than 6 cycles earlier than the contaminating 18S signal, you have very little to worry about.

Yeah da! I too had a look at it.. But it was in humans and I am not sure if the same can be applicable to mouse. Well yeah that is true but people here consider anything above 40-42 with less confidence. Besides, I diluted the cDNA at 1:20 dilution and not 1:2 but still I would expect the Cp values of 18S to come earlier knowing about its abundance. Besides, the problem of using GAPDH/Actin is that they are not present in the same amounts in all cell types and they might have some effect on different treatments as compared to 18S. I am thinking of doing a cDNA syn with random hex and then using diff internal controls to see which would be a better fit!!

Since there are different genes that I am assaying for KD, I have different primer pairs for each. All these primer sequences were from journal articles and so they should be good. And when I was analyzing my RT+, I noticed few of my primers did not work (which probably could be due to Tm). I did do a blast before ordering the primers and they looked pretty much specific. But I should have had a looked at the Tm as when I did a primer blast yesterday, each of the primers had a different Tm. I did have water controls and they had no peaks!! Nope, I didnt do a DNase treatment before RT.. Probably I might do that when I do RT next time!!! 

Hi Jack, thank you for the response.. Well that might explain the reason why I have got Cp values for my negative controls. I did a 1:20 dilution of cDNA for qRT and yes many have suggested to do a dilution of 1:1000 for 18S samples. Anyways I feel, I should be using a different internal control for my RT and I will probably try another PCR with different internal controls (Actin and GAPDH) just to know which would work better!! 

Remember mus musculus has a psuedogene for GA3PDH in the genome - so you'll want to be sure to DNase treat your RNAs very well to avoid gDNA signal for that.  And b-actin has been seen to vary from 4 to 7-fold even in the absence of treatments...  18S can behave like a model prisoner if diluted appropriately.  Dust is everywhere... and dust is a large part sloughed human skin; rife with 18S... what a playing field, eh?

Okay da. As Jack had pointed out too, Cp values above 35 could be, but need not be, from a desired template. And I hope you have repeatedly got similar results. DNase treatment before cDNA synthesis is important since the primers meant for specific binding in RNA library need not be specific in genomic DNA. Also, if you did not get peaks in water control (no template control), that prompts to me that it is some non-specific amplification from either RNA or genomic DNA. Try doing a primer blast against the mouse nr (not just refseq rna), with strict parameters. 

When you refer primer sequences from research papers, take them with the a pinch of salt. Analyse them yourself before using ,since I have found 'not very great primers' in some papers. Update your results once you try the variations. Good luck!

Hi Jack and Devdu!! Sorry for getting back so late on your replies!! As you guys said, I have treated my RNA samples with DNase and have converted them to cDNA using random hexamers. I am planning to do a primer standardization tomorrow just to know which primer would be a better fit after which I will do a proper qRT and hopefully they should work.

And devdu, I did do a primer blast of the primers before ordering with refseq rna but not with nr and apparentely I did get some non-specific when I did a blast with nr and I am not sure can be done as the primers have arrived already.. Btw, what is this nr? I have never used them for checking my primers before.. 

And Should I order new primers?? 

Food for thought:  In Appendix 12 of the attached paper I stated (after looking into this topic at great length):

"Appendix 12

Given the following assumptions that: 1.) typical eukaryotic cells contain about 20 pg of total RNA, that 2.) 83% of total cellular RNA is ribosomal RNA (28S, 18S, 5.8S and 5S rRNA), 15% is transfer (tRNA), 2% is messenger RNA (mRNA), that 3.) 24% of all rRNA is 18S rRNA, that 4.) the average eukaryotic mRNA size is ~2000 bases, and that 5.) the average nucleotide MW = 330 g/mole, one can calculate (using Avagadro’s number as 6.02214199 x 1023 transcripts/mole) that there are roughly 360,000 total mRNA transcripts per cell at any given moment. Further, if one assumes that ~25,000 differently-encoded mRNAs co-exist at any time, one can calculate that there are about 105.4 more 18S rRNA transcripts present than there are of any specific type of target mRNA (using a MW of 624 kDa for the human 18S rRNA transcript based on NCBI Accession #M10098). This clearly explains why 18S rRNA often generates real-time qPCR Cq values up to 18 cycles earlier than most other mRNA targets, and why RNA samples must be diluted so extensively in order to measure 18S RNA signal appropriately by qPCR. Other endogenous redundantly-copied housekeeping genes also exhibit relatively earlier-appearing Cq values, but none so dramatic as 18S rRNA."  See the attached publication... p 109.

@Anu, nr is nucleotide collection which contains genomic DNA entries, cloned libraries, RNA, etc; while refseq_rna is just the transcripts. So in case you have gDNA contamination in your sample, the non-specific amplicons in nr BLAST might end up being amplified. That's why the DNase treatment. Also, qPCR primers need to be designed spanning an intron wherever possible, such that even if gDNA contamination is there, the primers will not amplify the large genomic fragment under the cycling conditions. You might want to try the qPCR once with your new cDNA (without gDNA) and see if you get a similar profile, before doubting your primers.

This is from the NCBI website:

nr = The nucleotide collection consists of GenBank+EMBL+DDBJ+PDB+RefSeq sequences, but excludes EST, STS, GSS, WGS, TSA, patent sequences as well as phase 0, 1, and 2 HTGS sequences. The database is non-redundant. Identical sequences have been merged into one entry, while preserving the accession, GI, title and taxonomy information for each entry.

refseq_rna = NCBI Transcript Reference Sequences

Yeah I have designed the primers for qRT before just like you mentioned! Probably should have done that! Anyways let me do it and get back to you!! Thanks da and I hope they work.. Paakalam.. Fingers crossed..!!

ha ha! all the best!

Hey guys!! my internal control seems to be working good.. I am using 18S and diluting them to 1:500.. getting Cp values between 25-26.. But my target primers are not working.. Trying to use different temperature.. Planning to do a gradient next week if it doesnt work!! Fingers crossed.. Thank you so much :)

I was wondering... By calculation, between your previous 1:20 dilution and the current 1:500 dilution, there should be a Cp difference of 4.5. So with the 1:20 diluted cDNA, you should have got Cp of 20-22. Not sure how it works!

For your target gene, hope it is efficiently reverse transcribed with random hexamers. Also, hope you aren't using the diluted template for your target gene qPCR.

Hi da.. In my earlier experiment, where I used 1:20, the cDNA was obtained by oligodT.. But now I am using random hexamers.. But yeah, I did get Cp values between 20-22 for all my samples when I did it yesterday (did two trials) and the melting curves looked good!! I will have to check if they give the correct band by running them.. I thought I would do one more trial and then do that!! And for target genes, I am using 1:10 dilution since I used only 500ng of RNA to make cDNA.. I usually use 1:20 if I use 1ug of RNA for cDNA synthesis!!!

oh that's cool then! so how do you plan to incorporate the differential dilutions of target and control genes, while calculating delta delta Ct?

The different dynamic ranges of some targets necessitate their dilution (standard curve-wise and individual sample assessment-wise) to different ranges and/or singular concentrations to be assessed within their valid dynamic dilution ranges wherein amplification efficiency is the highest and responds log-linearly to dilution.  The key is, for each single sample target assessment, is to make sure that the samples, per each target, are loaded identically (ng/uL-wise) per each reaction on a per target basis. In the best case scenarios, all targets share the same homo-dynamic dilution range, but, when using 18S as a target (as a reference gene), this hope cannot hold.  Assessing for 18S always requires diluting all samples much more before it can be assessed within its valid range for qPCR.  The attached paper discusses this fairly usual dilemma.  All resulting Cq values using this approach are assessed by all delta Cq and/or delta delta Cq methods as usual.  Accounting for different dilutions [of the same target] is dealt with by observedCq + logbase Eamp of the (dilution factor difference) is all.

@Devi, the way I actually thought was, since 18S is very abundant, the number of targets for 18S would be extremely high when you do a 1 in 20 dilution which wouldnt be equal to other samples with same dilutions as they wouldn be having the same amount of starting target molecules.. When I do 1:500 dilution for 18S and 1:20 dilution for other samples, the number of starting target molecules are equal and hence you don't need to account for different dilutions!!! Hope I didn confuse you!!.

@Jack, thanks for the paper.. Very informative and complex too, atleast for me!! Tried hard to understand few concepts!!

@anu, That part I'm not sure since we cannot arbitrarily equate 1:20 in one case to 1:500 in the other. As I understand, the formula Jack suggested will give you the expected Cq value of the diluted template, given the Cq of the undiluted sample (or the other way). For this, you need the efficiencies of the amplifications. Have you done standard curves for the qPCR amplifications?

In my opinion, if you are doing a relative quantification using delta delta Cq method, you do not have to worry about the dilutions because the apparent shifts in the Cq values will get cancelled. i.e.,

[observedCq of ref gene in test sample + logbase Eamp of the (dilution factor difference of ref gene)] - [observedCq of ref gene in control sample + logbase Eamp of the (dilution factor difference of ref gene)]

=[observedCq of ref gene in test sample] - [observedCq of ref gene in control sample]

The log term gets cancelled in the calculations. This is, hoping I haven't made a mistake!

Yeah.. I understood Jack's explanation but that was what I thought initially before going through the paper!! And nope I havent done the standard curves.. and I am doing relative quantification using delta delta Ct method..

The reason I mentioned standard curves is, in delta delta Ct method, the derivation of the formula 2^(-delta delta Ct) assumes that both the efficiencies are equal to 100%. If not, one needs to optimise the eff. using primer concentrations, or substitute the existing eff. in a previous version of the formula.