Quantitative RT-PCR - Science method

I am analyzing the differential expression of splicing variants, through capillary electrophoresis, of a DNA repair gene after treatment with a DNA-damaging drug. I am using gene-specific primers for cDNA synthesis, which makes it challenging to identify a suitable internal control. Using another region of the same gene might also be affected by the drug, while choosing a housekeeping gene would require a separate cDNA synthesis step and introduce variability. What would be the most appropriate internal control to ensure accurate normalization in this setup?

Dear researchers,

I’m working on an Norovirus GI and GII qPCR assay with TaqMan probes. Recently, I experienced an issue with “multiplexing”. Briefly, the aim is to develop an assay for simultaneous detection of two targets (HuNoV GI and GII) using FAM and HEX reporters.

Single PCR, when the probes are used separately, works well. While in multiplex (when four primers, two probes are mixed per reaction), we get a low signal for one of the targets in several independent runs. On the other hand, in electrophoresis the DNA yield seems the same for different combinations. I tried to change probes concentrations and it seems that reducing probe amount for one target increases signal for the other target, but I guess that it may affect my results for competing target. I would appreciate any suggestion to optimize this assay, including good manulal about assay development. What to do in this kind of situation?

Thank you!

Technical details:

Concentrations of primers 400 nM, probes 200 nM, Mg 3 mM.

Cycling conditions: hot start at 95⁰C for 5 minutes, then 45 cycles of denaturation at 95⁰C for 15 seconds, annealing and elongation at 60⁰C for 1 minute.

Instrument: ABI StepOne Plus

Hi, I recently did a thermal shift assay using the intrinsic fluorescence of tryptophan. Therefore, i use no dye whatsoever. I use Biorad CFX96 and use the available thermal shift assay protocol online. My problem is the high pre transition RFU. What could possibly cause this? I have centrifuged my samples to precipitate any possible aggregates. The y -axis is the fluorescence reading while the x axis is the temperature.

Dear All,

mirna primer showing some problem in the melting curve? any idea why? As attached is the melting curve. The forward sequence is obtained from miRBase and reverse primer is universal.

I ask because biomolecular water or TE doesn’t maintain DNA integrity as expected.

Hello all,

I am working on a project of quantifying viral titer. I read some paper, and there are different units for viral titer. Among of them are TCID50 value, GC/ml and VP/ml. I do not understand much about the differences between them. Can anyone please give some explanation about this?

Hello, I've extracted RNA from A549 cells and I've done nanodrop to determin the RNA concentration. And then I meet the problem. I have no idea about the concentration and the quality of cDNA after doing reverse transcripataion.

I searched some information and know that I can make a stand curve to determin the concentration, but I don't have standard product.

I want to ask is there othre method to the concentration of cDNA with RT-qPCR. I have and idea about using internal control (like TBP), but I'm not very sure about how to connect the Ct value of TBP to the concentration of cDNA.

Hope someone give me advice!

THANK YOU

I am using three biological replicates. Their DNA concentrations measured by Qubit were different. I diluted all samples using an online calculator to ensure each sample had a concentration of 2.5 ng/μL. I used 2 μL of each sample in the qPCR, resulting in 5 ng/ul of DNA per well.

After performing qPCR, I noticed a slight difference in the Ct values of the biological replicates. I wondered why there was this difference. When I rechecked the DNA concentrations of my diluted biological replicates, I found slight variations i-e: 2.36 ng/μL, 1.98 ng/μL, 2.4 ng/μL, etc. This explained the observed differences in the Ct values during qPCR.

My question is: how can I ensure equal DNA concentrations in all samples?

Hi,

I found more monocytes in the heart in treated group accoring to the FACS data. And I did qpcr to validate this result.

First I checked CCL2 (or MCP-1) and other cytokines/chemokines because CCL2 plays an important role in monocytes recruitment in many research papers. But there's no significance among different groups.

Then I found the TGFb1 gene expression level significantly increased in treated group. But I couldn't find too much information about TGFb1 inducing the infiltrating of monocytes to the heart.

Does anyone have any ideas about TGFb1 and monocytes? And what else for monocytes recruitment?

Many thanks.

Hi,

I have done 3 experiments (may be called biological replicates in this scenario) with the same cell line to measure gene expression of "XYZ" on days (D)4, 6, and 8.

For obtaining RNA, I have cultured cells in 6 wells (say replicates) for experiment-1. Pooled only 2 wells together at D4 and extracted RNA for qPCR analysis. qPCR experiment had three technical replicates. This way I got qPCR data for D4 for experiment-1. I did the same procedure for D6 and D8 to get qPCR data for D6 and D8 respectively for experiment-1.

In the same manner I repeated experiment-2 and experiment-3.

I wish to compare 3 time points D4 D6 D8 to see if increase or decrease of "gene A" expression is significant.

Is my data paired or unpaired? Could you please explain why so?

My assumption: My understanding is that the data is paired. Graphpad tests show some data sets to be distributed normally and some are not. Considering low sample number (n=3), I assume all the data to not follow gaussian distribution and therefore use non-parametric tests.

Can I compare with Friedman test with Dunn's post-hoc for XYZ at D4 D6 D8? Or should I use Wilcoxon testing two time points (like D4vsD6, D4vsD8 and D6vsD8)?

Hi. I want to synthesize this blaTEM gene. This is the FASTA sequence, but I don't know which part is related to coding sequence, Can anyone help me?

(my major isn't related to microbiology or genetic, so I don't know the exact procedure of genetic basics,)

and one more thing, after synthesis how can I know how many copy numbers are there in my sample to generate qPCR standard curve based on that?

Hello!

I am optimizing conditions of stem-loop RT-PCR to compare the expression of miRNAs in different cell lines.

Now I'm performing the reaction in one step: RT with stem-loop primer and subsequent real-time PCR with a pair of primers and SYBR Green - all in one reaction. So my reaction mix contains three types of primers, heat-inactivated reverse transcriptase, hot-start Taq polymerase, SYBR and all the nessesary components such as ddNTPs and Mg2+.

I use synthetic miRNA and total RNA from human cells as matrices.

When working with synthetic miRNA, everything goes well (Figures 1 and 2), amplification plot is ok and there is a single peak in the melting curve.

But with total RNA I observe a decline of fluorescence in the plateu phase of amplification (Figure 3) and 2 product peak in the melting curve (Figure 4).

Reference gene amplification plot doesn't have such issues.

What are the reasons of the decline of fluorescence after the 30th cycle?

What are the possible variants of the second product here? Primer-dimers observed in no-template control have Tm = 80 degrees C.

I'm trying to detecte very small amounts of a mutant-type mtDNA using SYBR green qPCR. I can't really use a higher concentration of gDNA because my wild-type and housekeeping genes already have a low ct around 17. My negative controls show some primer dimers and are around a ct of 33. However, some samples show a specific melting curve peak identical to the one in my positive control, but with a Ct higher than my negative control (33,34,35) while some samples with the same Ct show a melting curve similar to the negative control, so all over the place or at the primer dimers temperature.

Should I consider aller samples with a higher Ct than my negative control as an absence of the target sequence or should I evaluate each melting curve separately and those showing a specific amplification peak are considered as containing the mutant-type, while others with not showing this peak are considered as homplasmic? If not, is there another way to rigorously discriminate my samples with absence/presence of my target gene?

Hi, I am doing qPCR experiments. When the reaction finished, I obtain the Ct value of my samples is zero, but they have a peak with my expected Tm. Furthermore, I run the gel electrophoresis, the result also shows that these samples appear a band at my expected target size. But why the Ct value is zero?

Hi, I am designing primers to discriminate SNP alelle, which is 2 forward primer specific for each allele. To improved the discrimination of SNP, what is the acceptable delta G value of the primer?

The context of my qPCR experiment:

i) three individuals, one of which used as a control

ii) three replicates of each reaction (a total of 18 reactions, including the GOI and endogenous control, excluding the negative controls)

iii) calculation of relative quantification of gene of interest (GOI) transcripts with the Pfaffl (efficiency) method. (NOT the ΔΔCt method!)

iii) I get a fold difference number, and create a classic bar graph according to the ratios.

What do I do to add standard error bars to the graph? Are they even needed for such a small amount of data? Please help me, I cannot figure this one out.

Anna Vatzika, MSc Student

When we perform statistical analysis on qPCR data, do we use fold change or ΔCt?

I have done 3 blind passages to concentrate the viral stock in the supernatant without adding TPCK Trypsin. After passage 1 my Ct value for INF A was 36.96. After P2 the value decreased to 33.36. However, I was expecting a much lower value in the mid-20s. I am freeze-thawing the flasks at -20 degrees to lyse the cells and release the virus into the medium. Is it the correct approach? and can I get a much higher titre without adding TPCK Trypsin?

So I used CRISPR-Cas9 system to knock out the protein of interest. I sequenced the modified region, and then I analyzed and there are 2 KO clones according to my results (deletion-causing stop codons). Next step was western blot to detect the protein level, but when I did the chemiluminescence detection and applied long exposure time I got faint bands- 2 faint bands... I think my antibody is not perfect, because it is a polyclonal antibody.. might be same other protein in that band, beacuse my antibody is not so specific and it could recognise other proteins and bind to them?? What do you think? I checked my clones with RT-qPCR too, and I got amplification in the KO clones too, same as the wild type... what do you think about this? I am confused and try to find out a good answer to this phenomenom.. my ideai is the mRNA is transcribed and the (mutated) protein is traslated , but after that it is degradated, because the protein is truncated or the folding is not good.. but why I see faint bands? might be the antibody? What should I do?

I am looking forward your theories and answers.. Thank you so much :)

Loretta

Hi!

I notice that reverse transcriptases can be used for both cDNA library construction with template switching (eg. surescript II etc.), and downstream qPCR. To quality-control my library construction, I would like to do a qPCR of focused gene with the first strand cDNA, but reverse transcripted with template switching. However, even with the same reverse transcriptase, will the activation of template switching, as well as the addition of adaptor-UMI before poly T in primer?

Thank you!

I'm working on RT-qPCR optimization for gene expression. In melting curve analysis, the 5x primer negative control has a peak that resembles the samples peak but looks shorter. 10x and 2.5 have no curve, and when I applied the gel for verification, no product was seen. Why does 5x primer have this melting curve but no product in gel?

I am treating human cells with an AAV vector encoding for my gene of interest tagged by FLAG. I want to quantify the mRNA expression of my gene of interest via qPCR to discriminate the endogenous and exogenous expression. I think that if I design primers spanning the junction between FLAG and my gene only the exogenous mRNA will be amplified. Am I correct in thinking this might work? Am I missing something?

I have never worked with FLAG tag so any recommendation would be highly appreciated

(I am also checking for the protein but wanted to combine mRNA and protein quantification)

I performed a nucleic acid extraction using 2 protocols for RNA extraction (Dengue Virus) and one parameter I need to evaluate is the integrity of my RNA samples. In this case, I can't use a RNA ladder. Also, I recently performed a RT-qPCR for the same RNA samples and I have the cDNA.

What is the best way to get the qPCR software, REST 2009, to work with Windows 10/11? The software was originally designed to run on a 32bit operating system (Windows XP) and will not open in Windows 11. Other than finding an older computer that still has Windows XP, does anyone have suggestions to make the software compatible? I already tried running the troubleshooter and changing the compatibility settings in the properties window. Any other suggestions? Thank you https://www.gene-quantification.de/rest-2009.html

I'm doing a 3C analysis shown in the picture linked and attached below with the Bait fragments labeled and the target fragments that will be tested for interaction with the bait labeled with numbers. The picture shows two possible 3c maps based on two different restriction enzyme digests of the same region.

A, B, C, and D are regions we are considering for analysis in the future to determine if they interact with each other and with the target fragments.

Assuming we can find restriction enzymes that can digest and separate the regions shown is it possible to test between the fragments as shown for interaction or are some of them too small/too close together?

Hello everyone! My PI would like me to measure the amount of mitochondrial DNA in multiple cell lines using qPCR targeting COXI and COXIV. However, I have never done a qPCR that measures mitochondrial genes. Does anyone have any primer recommendations for these genes?

Also, should I use cDNA or gDNA for this experiment?

I have a question regarding target miRNA expression after transfection with antisense miRNA (miRNA inhibitor). I understand that the expression of the target miRNA will increase after mimic transfection using qPCR. However, should the level decrease after inhibitor transfection? Since the antisense will bind to the target miRNA and reduce its function but not its expression level, I think the expression would be the same between the negative control and the inhibitor-transfected samples. However, some papers show reduced miRNA levels after inhibitor transfection. Which one is correct?

So I'm using TRIzol for RNA extraction, but suddenly I'm getting no pellet during the isopropanol step *even though I added glycogen.*

A few weeks ago I:

1. Took a large quantity of bacteria

2. Resuspended in TRIzol

3. Made a bunch of aliquots

4. Stored them all at -80

And those couple weeks ago, I was getting~50 ug of RNA per aliquot (with good RINs, and they looked great on RNA gels).

Yesterday, I took another aliquot and tried to prep it using the exact same process, and got nothing. No pellet appeared during the isopropanol precipitation step even though I added GlycoBlue.

I continued the purification to see if the pellet was just hard to see: ~0 ng/uL by nanodrop

Did I just make a pipetting error? Was my isopropanol bad? No: I repeated the repeated the process *again* with completely new sample, completely new isopropanol, and still no pellet at all.

I'm confident I'm lysing my samples well. I optimized the lysis a while ago, but even before optimization, my yields were never this bad.

I'm sure I added the GlycoBlue. I watched it diffuse into my sample.

I'm sure I added isopropanol. I watched the alcohol/water mix and used brand new isopropanol.

I'm sure I mixed the isopropanol/aqueous phase. I watched it carefully.

I'm sure I actually spun my samples. I tried it over and over.

Protocol:

1. Take bacteria+TRIzol aliquot from -80 (which used to give ~50 ug)

2. Lyse via bead beating (same beads, same bead beater, same settings, same duration that gave 50 ug in the past)

3. Add 0.2 V chloroform

4. Centrifuge 12k xg for 15 min

5. Take upper, colorless aqueous phase

6. Add 1 V of RT isopropanol

7. Add ~30 ug GlycoBlue

8. Invert a bunch of times to mix well

9. Incubate 10 min RT

10. Centrifuge ~20k xg for 10 min

Nothing. No pellet at all. Even with glycogen.

I tried spinning again: No pellet

How is this possible?

Hi,

I am growing Caco2 cells in 24 Transwell cell inserts. I am planning to induce gut leakage by LPS and want to study gene expressions. My concern is to isolate the RNA from transwell inserts since those are very tiny and hard to use cell scrapper. Any protocol or suggestions would be greatly appreciated

Hi all,

I am planning to do a RT-PCR followed by qPCR starting from 100 ng of total RNA. The way we do it in our lab is we dilute the 20 uL of RT reaction containing 1 ug of total RNA 1:4 and use 2 uL of it per 12.5 uL of reaction per well for a 96-well plate for qPCR. Will this protocol work for 100 ng of starting RNA conc.? Will it be too low to detect? We use myScript Sybr Green kits from Bio-Rad. Also, I am starting with low amount of total RNA conc, (in the range of 6-30 ng/uL).

Please tell me your opinions! Thank you!

Hi.

I’ve been unsuccessfully trying to isolate DNA from neurons extracted from adult mouse brains for further downstream analysis.

First I’ve tried sorting neuronal nuclei (Approx. 10⁵ NeuN+ nuclei/sample) (protocol by Nott et al Nat Protoc 2021), followed by DNA isolation and qPCR analysis. However, my PTHrP levels were always undetectable.

Then I moved to commercial kits, and bought the adult neuron isolation kit from Miltenyi. As I read, one would expect approx. 10⁵ isolated neurons per adult brain. I did the whole trinity from Miltenyi: 1. Adult Brain Dissociation Kit, 2. Myelin Removal Beads II, 3. Adult Neuron Isolation Kit. However, again after following the protocols, and immediately isolating the DNA (Nucleospin tissue from MN) I did qPCR (sybr green) and again I did not detect PTHrP in my samples!

I’ve preformed DNA isolation for high yield and concentration in a final 60ul elution volume. Following DNA isolation, the samples were stored at +4C, and the qPCR was done the next morning.

In my control samples from other tissue, I can detect PTHrP which means the qPCR protocol and primers are working fine.

I would be grateful for any help!

Best,

Hi ResearchGate community,

I have been trying to learn more about the optical differences between block-based real-time PCR machines like ABI StepOne versus rotor-based machines such as MIC or RotorGene systems.

I understand that some systems rely on ROX as a passive reference dye while others state that it is optional to incorporate it and others do not need such a factor at all.

My question is if you add this fluorescent dye to your master mix, would it interfere with the detection when it is being amplified using one of the systems that do not need such normalization?

Highly appreciate any insight in this regard.

Best,

Negar

Greetings. Probably the question is not complex at all, but can't find an answer.

If I have RT-qPCR data of gene expression in a sample with multiple analitycal replicates - to compare it to data obtained in other experiments I need to normalize the expression of genes of interest to the expression of reference gene (which is constitutievely expressed)..

How to perform it if there are replicates and expression of both genes of interest and reference gene are in a form of Expression and Standard Error of the Mean?

Is there a formula to adjust GOI SEM using RG SEM?

We would like to purchase around 10 thousand DNA oligos in a 96 well format (25 nmol). The cost per base is coming to around Rs 14-15. We wonder if there is any economical option available in the market.

Thank you

qPCR was performed on the same environmental DNA samples, first using a primer pair targeting the archaeal 16S gene, and subsequently, another qPCR was performed using primer pairs targeting the 16S gene of Lokiarchaeota, Bathyarchaeota, and Woesearchaeota, respectively. BLAST confirmed that the primer designed to target the common archaeal 16S gene also indeed binds to the 16S site for Loki-/ Bathy-/ Woese- archaeota. I want to know if it is okay to process this data as follows:

Total Remaining Archaeal gene copies = Archaeal gene copies - Lokiarchaeota gene copies - Bathyarchaeota gene copies - Woesearchaeota gene copies

Hello Researchgate community,

I recently ran into a bizarre (at least I've never thought it could happen). We selected a few DEGs from the scRNA seq dataset and run q-PCR to validate the results (heart tissue).

One particular DEG of interest was DOWNregulated in cardiomyocytes only, but no change in other cardiac cell types, and no change as a whole after combining data from all cells. However the q-PCR data suggested there is a big UPregulation in the whole heart under the exact same experimental condition.

What could be the causes of near-opposite data from RNAseq vs. q-PCR? How should I interpret it, and what's a logical next step here?

Thank you very much!! Any input is much appreciated!!!

I have raw qPCR data. 2 samples "1 control and 1 with gene knock out". I made a serial dilution of each sample and performed a qPCR using 2 reference genes and 3 genes of interest. Now I have the raw data “the CT and average CT of each sample. I want to present the data as a chart. What exactly do I put in the chart. The delta delta CT? Or the 2^-delta delta CT? Or something else?

and do I put all the dilutions in the chart? or just the undiluted original sample? or calculate an average or a geomean of the sample and the diluted samples?

Another question. When I have more than one house keeping gene or reference gene, can I take the geomean of the average CT of both genes to calculate the delta CT?

Hi ALL,

I am using a pair of primers to amplify a region in my gene of interest from cDNA samples. The cDNA samples are extracted from tissues of mouse of different ages. The gene is known to have decerased expression level when mouse ages. However, I did not see any change of the RT-PCR amplicon band intensities on agarose gel, indicating no change for the transcript level. I did not saturate the PCR products as I tried different cycle numbers (from 23 to 30 cycles). What could be the possible reasons? Should I design new primers targeting a different regions in my gene? Thank you for the help!

I'm conducting a time course study on gene expression using RT-q PCR for samples treated with 4 conditions: vehicle, RA agonist, Calcitriol agonist or a combination of both agonists over 6 hours. I'm expecting to observe a gradual increase in expression over time for the combined treatment condition due to an additive effect of the ligands. Indeed, I have observed that for all of the time points except for the last one where the Ct value for my combined treatment is 30 while my untreated control at zero hour has a Ct value of around 28.85. Even the Ct value for the vehicle condition for my last time point is around 28.65 so, why am I getting such Ct for the combined treatment?

Basically, I would like to quantitatively detect total bacteria in mice feces. How can I obtain a standard curve to reveal total bacteria quantitatively?

By the way, I have one bacterial species that I grew in a suitable medium, and I obtained a standard curve by making serial dilutions, and I found that bacteria in the DNA whose amount I did not know by substituting it in the Ct equation (obtained from the standard curve). But I don't know how to quantify total bacteria. I would be glad if you help.

I run qPCR to titer the AAV ( which i got by transfection in 100mm dish). I make four dilution of my sample ( 12 well and triplicate). I take GFP plasmid as a standard and were diluted to 1ng/ul, accordingly, 8 dilution to 0.05ng/ul (24 well and triplicate). Now i got the Ct, Ct Mean, Ct SD, and quantity. I need to calculate the the quantity in picogram/well, picogram/ml, genome copy and genome copy per ml. kindly pls suggest me any way, how to calculate it. Thanks.

Hello,

I am trying to quantify the expression level of different snoRNAs between control and CRISPR samples, to know if the knock-out of my gene has an effect on these small RNAs.

A colleague did a first RTqPCR, one-step, and found that they were mostly overexpressed in the CRISPR samples.

I repeated the RTqPCR several times but as a two-step RTqPCR using random primers, and found everytime that they were mostly downregulated in the CRISPR samples which was quite surprising.

I am a bit puzzled that there is so much different between the results, in my opinion if the random primers are less efficient for RT they should be equally less efficient in the control and CRISPR samples so the dCt should not change.

The experiments have been repeated multiple times, I attached the file summarizing my results for 2 replicates of the CRISPR experiment (sample 1 and 2) for 4 different snoRNAs (A to D), for which we have the most technical replicates. The variation between replicates is not really high so it cannot explain such differences between the conditions.

dCt is the average Ct value of the control sample - the average Ct value of the CRISPR sample.

If anybody has a suggestion why we see such results I would be happy to hear it.

Thanks in advance for your help :)

Best regards,

Violette Charteau

I have performed 3 RNA isolations on Jurkat cells using the phenol-chloroform principle, using Omega Bio-Tek RNA Solv® & following the protocol. I took care in not disturbing the separated phases when removing two thirds of the aqeous phases but the data I get when I measure the 260/280 & 260'/230nm absorbance ratios lead me to suspect contamination of the samples with phenol or other reagents.

Most of the samples have a 260/280 ratio below 1,6 and only one sample has a 260/230 ratio that comes close to 2 (1,84 to be exact). Subsequent cDNA synthesis & RT-qPCR have not resulted in genes of interest to show any fluoresence at all, only the housekeeping genes in 2 of 7 samples showed up. Problems with primers & RT-qPCR were ruled out as the same setup yielded viable results previously.

Thanks in advance!

When I ran qPCR on my samples, some of them returned N/A results (I replicated it twice, and the replicated sample returned Cq value results), so I decided to run qPCR on the same samples again. The sample that previously gave N/A results turned out to have Cq values. What does this mean? And what are the possible issues that cause the first run to return N/A results in some samples?

 

 

Example (because I am not fluent in English, using the example will make it easier to understand that we are on the same page):

 

Sample A:

Gene A -> Cq: N/A

Gene B -> Cq: 36.55

Gene C -> Cq: 35.75

Sample A (replicated):

Gene A -> Cq: 34.78

Gene B -> Cq: 35.97

Gene C -> Cq: 36.12

 

And because gene A of sample A gave N/A as a result, I decided to run qPCR with the same sample again (to see if it could give me a Cq value).

Sample A:

Gene A -> Cq: 35.04

Gene B -> Cq: N/A

Gene C -> Cq: N/A

 

Sample A (replicated):

Gene A -> Cq: N/A

Gene B -> Cq: N/A

Gene C -> Cq: N/A

We are working on the expression of resistance genes in potatoes using the LightCycler ® 480. There are two ways to evaluation of the results: basic (that use ΔΔCT method) and

advanced (that use E-Method). I know that the second one is more precise, but I can't find an explanation for the differences in the size of units: for the same data we get values 1,57E-06 (basic) and 0,706 (advanced). The reaction efficiency is very close to 2.

How can such differences in the size of the results be explained?

Hi everyone,

i was running a real-time PCR in two different machine but using the same protocol and kit. How is it possible? Can anyone explain this to me

Something went wrong with our cell incubator over the weekend so to my knowledge the cells inside were deprived of a sufficient level of Carbon Dioxide for about 24 hours. The photo attached shows the state of the cells.

The cells are NTERA-D2 cells. Passage number 16.

Magnification is 10X.

Cells were passaged 3 days ago into a T-25 flask.

My question is; Can I salvage these cells so they can be used for rtq-PCR and colony formation assays? Or should I just thaw a new vial of NTERA cells?

I'm self-studying RNA expression, and I'm quite confused with the difference between Reference gene and Calibrator gene in calculating the relative quantification of RNA expression.

Furthermore, if a GAPDH (housekeeping gene) is used as a reference gene. Would the value of the reference gene be taken from the sample of the treated groups or the control groups?

Example:

if I were to study the expression of IL-8 in fibroblasts, would the value of the GAPDH as the reference gene, be taken from treated groups or negative control groups?

During work for my undergrad thesis, I've examined and compared gene expression of stress-induced genes in plants challenged with a fungal infection.

I have calculated the relative fold change and wondered: How high does my fold change have to be for it to actually make a difference?

For example:

The log2 RFC between Group A and Group C is 0.63.

According to ANOVA, this difference is significant.

I'm wondering if this difference is enough to change the plants' stress response.

Is there a certain value that I can see as a "threshold" or is mere statistical significance enough to confirm the change in the plant?

Thank you in advance .)

Hi y'all,

I am running into some difficulties with qPCR (SYBR). To give y'all a brief background summary, I transfected some cells (ASO) and am running qPCR to see its effect on known genes using qRT-PCR. The first time I ran a qPCR, I saw little to no amplification. I re-ran it again and this time I went back to the beginning (RT-PCR from the original RNA) and was able to get some data. However, I am running another qRT-PCR but this time it's not working at all, as in I am seeing zero amplification, which is weird because, again, we know for a fact that some of the genes are supposed to show up in abundance. I was very careful throughout the whole process, so I don't think there was any human error. I haven't run a gel yet, so that's something that I have in my mind. I just wanted to see if y'all have faced similar problems.

Thanks in advance!

What are the validation timelines for quantative real time PCR and western blotting results, is it 24 hours for qpcr and 48 hours for western blotting if so! Why then!?

After trying different protocols I was able to extract RNA from old olive tree leaves with a phenol / chloroform : IAA protocol. Nanodrop measurments of the samples gave 260/280 rate ranging between 1.25-1.42 and 260/230 from 1.04-1.55 and a content of 100 - 200 ng/ul. I proceeded creating cDNA using 200ng of RNA template for a 20 ul cDNA volume. Then a qPCR was performed with the Kapa SYBR FAST qPCR Master MIx (2x) with the use of 1ul of the created cDNA for a 10ul reaction. The amplification plot looked like the attached. I am actually inexperienced but i was told that the refrence gene i am using (actin) is showing up late (30-35+ cycles)

I think that there is probably a phenol contamination in my samples and that is the cause for this bad qPCR. But i am also thinking about the quantity of the RNA that was used. Maybe it was too little, explaining the late amplification or too much taken the fact i didn't dilute my cDNA. Thank you very much in advance!

I have nhe6 KO mice, confirmed via genotyping from their tail clips. I isolated BAT, iWAT, and gWAT from three controls and three KO mice. RNA isolation followed by cDNA preparation was performed from these isolated tissues. On running qPCR, I expected low ct values (high nhe6 expression) in controls and high ct values or undetermined ct values (may be?) for KO samples. However, shockingly! I got similar ct values (30-32) for both- controls and KO.

The questions here is-

Is it correct to perform qPCR on genomic knockouts? AND WHY?

Hello fellow researchers,

I'm currently conducting a qPCR experiment and have encountered an issue with varying PCR efficiency between my reference and target genes. Some of the reactions are showing efficiencies above 110%. Initially, I had planned to employ the ΔΔCT method, but these efficiency differences have raised concerns.

I've taken steps to troubleshoot the issue by thoroughly checking melt curves and running agarose gels to confirm the quality of my samples, and everything appears to be in order.

To provide a better understanding of my situation, I've attached a picture of one of the efficiency calculations for your reference.

Now, I'm considering switching to the relative standard curve method to analyze my qPCR data. However, I'm curious to know if the efficiency of the reaction still plays a critical role in this approach. Are there any potential pitfalls or considerations when using the relative standard curve method, especially when dealing with varying PCR efficiencies?

Thank you for your help!

Hellow fellow academics

I am currently in a dilemma and I would really appreciate some suggestions/guidance on the matter.

I have overexpressed my gene of interest (GOI) from wheat in Arabidopsis using the floral dip method and with strict screening on MS-Hygromycin, obtained my T3 transgenics. Now the problem is that while the selection, on the media has been successful, I am not able to get a band of my GOI on agarose gel after doing semi- RT-PCR. Initially, I thought that maybe my overexpression was unsuccessful so I took the T3 seeds to screen again on the media, but, the result was the same; the overexpression was successful and met the segregation ratio requirement of 100% germination. As this is my first time working with transgenics, please enlighten me on where I could be going wrong.

Please advise. Thank you for your time in advance.

Dee

Is there anyone who has done TaqMan assays using average regular use PCR mastermix (not the TaqMan assay specific mastermixe) using cDNA as template for the qPCR test? I wanted to know the ins and outs of the procedure and the optimization you did to get accurate results.

Thanks in advance.

I have an unusual question: I am working on a Erasmus internship project with Drosophila mutants at 2 different timepoints and with WT, KO and KI condition. A company analyzed the data using DESeq2 and I have only got loads of PDFs and the results_apeglm.xlsx file.

This contains: Transcripts per million for each gene, replicate and timepoint with the comparison for looking at DEGs - so I have a padj and log2FC value. A snippet is attached as an example.

I now want to construct a graph and clustering where genes that are going in changing directions between WT and KO over time become visible out of the hundreds of candidate DEGs. With this I want to narrow down the long list to make it verifiable with qPCR and serve as a marker for transformation from presymptomatic to symptomatic.

I am setting up my analysis in R and want to use the degPatterns() function from DEGReport, as it gives a nice visual output and clusters the genes for me.

How can I now transform my Excel sheets, to a matrix format that I can use with degPatterns()? The example with the Summarized Experiment given in the vignette is not really helpful to me, sadly.

Thank you all for reading, pondering and helping with my question! I would be very happy if there´s a way to solve my data wrangling issue.

All the best,

Paul

I am optimizing qPCR assay using a pooled cDNA sample. I have several target genes (100-200bp).

current template dilution: 1:30 (30x)

final primer concentrationn: 0.27 uM

annealing temp: 60C

extension temp: 72C

Ct values I get using this template dilution range from 32 to 35, which I think are too high (aren't they?). Increasing the template to 1:10 (10x) and decreasing the annealing temp close to primer Tm (55C) didn't do much.

All melt curves show single peaks at expected Tm. No problem with primer dimers and specificity.

Do you think I should increase the primer concentration to 0.5 uM to lower the Cts?

Trying to design my first set of methylated primers. Ran a temperature gradient and think I’ve narrowed down a functional range of annealing temperatures across primer concentrations.

Now, I wanted to finally test efficiency across a few annealing more select temperatures. However, I’m realizing that in my labs qPCR protocols, most of them don’t carry an extension step, only the annealing and denature step.

My understanding is that since the templates and products are small (100bp) the copy is usually completed during the ramp up to the denature step. I’ll add that my Tms are approximately 64C, and my estimated annealing is consequently in the 55-61C range. We are using IQ sybr green super mix (iTAQ polymerase).

Just wanted to inquire if this was indeed the case, and if I should rerun my temperature gradient with an added extension step or just proceed with piloting.

On an agarose gel, I didn’t see any double banding across temperatures (suggesting high primer specificity?) albeit brighter bands were detected at specific temperatures, within 2C-6C of the Tm, so I wanted to run sample dilutions across a few degrees to maximize efficiency.

thanks for any help!

Hello, I am working on microRNA expression studies on Regeneration. I isolated RNA from my sample and converted it into cDNA using Poly A polymerase and Reverse transcriptase enzyme. Previously I designed a miRNA-specific Forward primer at the melting temperature of 60°C. For Reverse primer, I used Universal Reverse primer from a commercial kit. But now I need to design a miRNA reverse primer for myself. Kindly suggest me method to design a reverse primer for Poly A-tailed miRNA. Thanks in advance.

Is it possible that the amplification failure products can be visualized in electrophoresis? Due to the failed amplification results it shows bands in my electrophoresis with bands that are quite clear. My amplification curve clearly shows amplification failure, but when I look back at it with electrophoresis there are some obvious bands, how is that possible?

Hi everyone. I have searched all around the internet and literature for the answer to this question but haven’t been able to find any info regarding my specific situation.

I have multiple experiments consisting of qPCR data but can’t figure out how to best analyse it. I have WT and KO cells which I apply 3 treatments to and I have a control (no treatment) for both genotypes, and I check 15 genes. What I really want to show is if the genes are up/downregulated when I add a treatment in ko vs wt, so I want to make my comparison between the genotypes. But I can’t compare them directly, because at baseline they have quite different expression levels already, so I want to take the control for each into consideration. Before I was plotting -Dct (normalised to housekeeping gene only) and would compare each treatment in each genotype to its own control. But my group didn’t like this, which I understand, because the graphs are cluttered and I don’t show the comparison I’m really trying to make. I worked with a bioinformatician with my idea to normalise the Dct for each genotype/treatment to its own control and in that way make DDct, and then I compare the -DDct between genotypes for each treatment using an unpaired t-test. I don’t do fold change. These graphs are much nicer to look at, but my supervisor says it doesn’t make statistical sense this way, and wants to keep the graphs the original way.

can anyone help me out? What is the best way to analyse and graph my data?