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I have a big problem in my transcription. After taking my cDNA and PCR of my gene of interest, I did purification and miniprep. My results shown everything are great (nanodrop and agarose gel). But I can't have my RNA. In my agarose gel, I see a trail.
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Hi!
I found my mistake and now I have my RNA.
Thank you for your help!
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We have a gene with two isoforms, one with a longer 5' UTR and one with a shorter 5' UTR. It's been demonstrated that which isoform is predominant changes over development.
We want to study how the UTR might influence the translational efficiency of the transcripts. In the past, we tried to create a luciferase fused construct that had our UTR, our gene, and luciferase. However, the results were somewhat messy and hard to interpret and we questioned whether the luciferase construct itself was affecting translation.
Does anyone have any experience with alternative methods of studying 5' UTR's effect on translation, or have better experience with luciferase constructs?
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Don't use luciferase because too many variables affect the assay. Transfection efficiency, reaction times, substrate availability, etc. Just do western blots to examine protein levels directly. Control for transfection efficiency by using a second control plasmid, such as GFP.
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I recently did a transcriptome assembly using Trinity and I got one Fasta file. I want to do further analyses on unigenes only. My question is how do I identify the unigenes from the transcripts and have a Fasta file of unigenes only?
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Pleasure to you Lungelo Khanyile enjoy the downstream analysis of transcriptome data.
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Dear community,
does anybody have experience with cloning two genes in opposing reading direction so that the genes theoretically could share just one bGH polyA signal.
I think the inverted polyA signal for one of them should not make a problem, since the polyA has no "direction". I am just concerned that the polymerases might sterically "crash" when both genes are transcribed at the same time but wouldn't that also terminate the transcription? :D
prom->tDTomato->bGHpoly(A)<-PuroR<-prom
Best!
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PolyA signal is not directional. There are consensus AATAAA sequence, cleavage site (CA), followed by GT rich region.
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I am not able to visualize anything on agarose gel except primers and gene ladder.
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i have included a control as well and it is amplifying with a good intensity
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Hi to all.
My question is how can I optimize my RTqPCR if the cDNA dilutions ended up in similar Cq?
I synthesized my cDNA from 350 ng total RNA, assuming 1:1 production I should have 350 ng cDNA in 20 ul right? Then I did a dilution of 1/2, 1/5, 1/10 and 1/20 (I know the first three are consider quite a lot to be used in the run) and used them in a 20 ul run. The gene is a ref. gene: GAPDH. Interestingly the Cq values aren't that different between the dilutions (~29, ~30, ~31 and ~30). Obviously these aren't good values but I don't know what can I do to optimize the run.
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Thanks for the additional detail. Regarding RIN, yes! A low RIN is indicative of RNA degradation, and fragmented RNA isn't good for downstream applications.
Clean, degraded RNA will give near identical 260/280 and 260/230 ratios to clean, non-degraded RNA, but only the latter is likely to provide viable cDNA.
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Hi everyone,
Please correct me if the information mentioned here is incorrect. In the animal mitochondrial genome, there are no introns coding sequences.
I was wondering whether the primers designed for a mitochondrial gene (DNA sequence) work for the cDNA for its mitochondrial transcript?
Looking forward to a discussion!
Thanks in advance.
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That's great Saurabh Tiwari
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Why is there a bright smear below my RNA band from in vitro transcription?
I have only observed it for my longer transcript.
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Your reaction looks pretty good for 5 kb. I would not worry about that smear, it is less than 5%. Load less sample and you would not even see it.
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I am conducting a qualitative study with three different groups: patients, community health activists and doctors, and I use two different interview guides, one for patients and another for the latter groups. As I am analysing the data and elaborating the results, I am considering what is the most appropriate approach to present the data and triangulate it?
There is a small overlap in the results. Some codes that emerged in the transcripts with activists and doctors help understand and discuss the results that emerged from the interviews with patients.
Thank you for any response and support.
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Given the differences in your questions and codebooks, I agree that you should concentrate your comparisons in the Discussion section.
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I want to publish the (qualitative) data that is associated with my research paper and have explored journals like Data in Brief and Scientific Data published by Elsevier and Springer respectively but they could not consider the data (descriptor) manuscript I submitted to them due to technical and situational reasons. Other journals I have seen are not suitable as many of them either consider other types of data or are based subjects different from mine. The data based on social research and consists of the interview transcript on pandemic policing and public (compliant) behaviour.
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Extending the answer fron Mahdi Movahed-Abtahi , your work might be adapted according to various other publication types to increase chances of publication. A letter
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Are there any bioinformatics tools or software available that allow verifying if the processed transcript acts as a lncRNA?
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Hi! I think the LatchBio console tools should work for this. I've used the platform before, and it is really easy to use.
I hope that helps!
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It is about Molecular Biology. Please answer up. Thanks
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There are two mechanisms responsible for proper transcript termination: in E.coli intrinsic termination and Rho-dependent termination. The Intrinsic termination is mediated by signals directly encoded within the DNA template and nascent RNA, whereas Rho-dependent termination relies upon the adenosine triphosphate-dependent RNA translocase Rho, which binds nascent RNA transcripts and dissociates the elongation complex. Although significant progress has been made in understanding these pathways, fundamental details remain undetermined. Among those that remain unresolved are the existence of an inactivated intermediate in the intrinsic termination pathway, the role of Rho–RNAP interactions in Rho-dependent termination, and the mechanisms by which accessory factors and nucleoid-associated proteins affect termination as reported on Annual Review of Biochemistry about six years ago
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The primers designed should be allele specific so as to amplify either my WT or Mutant transcript and not both.
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The best way to address this question is with ddPCR:
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I've been trying to do invitro transcription of 70 bp long DNA oligo using T7 RNA polymerase to figure out formation of G-quadruplex structure. The following components are added to the master mix for 20uL reaction volume:
1. 200nM ds DNA (prepared in 50mM tris and 10mM MgCl2),
2. Transcription buffer {trisCl (pH 8), 2mM spermidine, 50mM KCl, 10mM MgCl2, 10mM DTT} followed by
3. 40% PEG 200 and at last 2mM NTP .
I have successfully carried out transcription using this method earlier but now gradually the transcription seems to be having an issue.
The problem is when NTP is added to mixture having peg 200 , it immediately forms white precipitate. I tried repeating this in absence of peg and seen that there is no ppt formation. Not able to understand why is it happening. Is there any report of interaction of peg 200 with NTP?
After EDTA addition, the precipitate disappears. To check if DNA is precipitating due to Mg2+ chelation, I have also made the reaction mixture in absence of DNA , still I can see precipitate formation.
Can someone please help.
Note: I have assembled the reaction in room temperature.
Thanks in advance.
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It is the magnesium precipitation with phosphate or pyrophosphate. When the transcription happens, pyrophosphate is generated, if you don't add pyrophosphatase, then Mg will form insoluble magnesium pyrophosphate with it. if you add PPase, Mg will form Magnesium sulphates with the monophosphate. And the precipitation should be a sign for successful transcription.
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Hello,
We are currently evaluating software for the analysis of transcribed video recordings of dialogues. Coding units are episodes, and we want to quantify codings as duration of time. In previous studies, we successfully used Transana for similar analysis.
We are now evaluating to use MAXQDA instead, which does not assist reports of time duration of codings on transcripts, but only number of characters. For the export of duration data, coding has to be on the video, which does not meet standards for linguistic discourse analysis.
Does anybody know studies and/or have experiences with number of characters instead of duration as value for the quantification of transcript-based coding of dialogues?
Thank you for sharing your knowledge and experience!
Kind regards, Annelies Kreis
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I wrote the CLASS program to accomplish your goal. See http://class.wceruw.org/index.html & http://class.wceruw.org/class.html.
Good luck.
Martin Nystrand
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Im using mMESSAGE mMACHINE T7 ULTRA Transcription Kit to transcribe my DNA. It produced 30 ng/ul which is 750 ng although the kit promises to yield atleast 15-20 ug of RNA. Even the control DNA provided in the kit produced 6.2 ug RNA. I followed the protocol as it was instructed. Kindly share tips to increase the yield upto 10 ug atleast. TIA!
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That kit normally delivers. Have you tried extending the IVT reaction? I normally do 6 hours +.
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I am trying to express a short RNA sequences in the nucleus in Drosophila. Are there any UAS-based expression vectors in flies that do not have PAS in the 3'? Or on the other hand, is it possible to just express a transcription termination sequence at the 3' of my transcript so that my transcript terminates before reaching the PAS? I don't want to have to mess with the vector backbone itself (removing PAS...etc.). I am quite new to molecular work regarding vectors, so if I am missing something important, under a misunderstanding of sorts, or if you have good suggestions, please let me know. Thank you!
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Talk with folks in your lab. Just because you want to do something doesn't mean it's possible or practical. Do what you know will work.
As my Ph.D advisor said "you can't rush quality".
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Hi, does anyone know of any post-transcriptional mechanisms that could explain no change of the transcript (mRNA) but still impact the protein?
so modifications that may show the protein's expression low in mRNA but the protein is still expressed in high amounts after translation?
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Malcolm Nobre thank you this helps
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I have in my RNA-seq quantification data from Arabidopsis obtained by mRNA-seq polyA enrichment library transcripts encoded by chloroplast and mitochondrial genes in significant DEG. How is it possible, if chloroplast and mitochondrial transcripts do not have poly-A tail? Are these data reliable or contaminants which should be ignored?
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I checked it and I probably found the response: Moreover, polyadenylation is often
a degradation signal in organelles, meaning that researchers
using poly(A)-selected RNA-Seq for measuring differential
expression in organelle systems may, in some instances,
be measuring the opposite: differential degradation (Smith and Lima, 2016).
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Hi guys,
I'm currently doing a research in BCR-ABL. I'm trying construct the Fusion transcripts that causes philadelphia chromosome. For example, presence of fusion transcript e1a2 leads to ALL. In order to create the fusion transcript, I designed primers to amplify the exonic regions of BCR and ABL individually and once amplified, to fuse the amplicons using BCR/Forward and ABL/Reverse primer.
Unfortunately, the individual gene amplifications hasn't worked and it just gives smeared appearance for a specific temperature. The template for the PCR is cDNA synthesized using MMLV.
Appreciate if anyone could help me with troubleshooting this issue.
The PCR cycle is,
Initial denaturation 95c/5min/1cycle
Denaturation 95c/30secs
Annealing 60c/64c/67c/ 30secs
Extension 72c/1minute
Final extension 72c/5minutes/1cycle
Hold 4c/infinity
Denaturation, annealing and extention went for 35 cycles in veriflex.
The gel image is attached for reference.
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How big is your expected product? The general rule is 1 min extension for every 1000 bp of DNA. You also might want to try a gradient of annealing temperatures to see what works best.
Good luck!
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Hello! I have been trying to produce IVTs from gBlocks, starting amount is ca. 100/120 ng of DNA.
When the reaction is done, I do a DNAse step, purification on column and then go to Nanodrop. When I measured the samples, I had a concentration of 1000-2000 ng/ul and a A260/A280 of more than 2.20.
I found this very weird, so I repeated the DNAse step on the IVT sample and purification again, but the situation didn´t change. I then did a third DNAse step, with a different DNAse, and again purification but even so I always have similar results.
My question is, can it really be that I have this much RNA? How can I check whether in my sample there´s RNA, DNA or a mix of both?
Thank you!
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Depending on the volume in which you eluted your RNA the concentration is not out of the realm of possible.
However, you should remember that nanodrop will also detect small fragments and possibly even nucleotides carried over from the template. You can measure your RNA using Qubit which is specific and will only detect the RNA.
You should also run a little bit on a gel to verify you get a clean band at the right size.
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I use some applications, but I seek more useful options. I wonder you're the applications that you are used to and your experiences with them. Thanks for your replies in advance.
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Good day
Best regards
Ph.D. Ingrid del Valle García Carreno
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I have ready collected several transcription data of tissues from patient(almost have metastatic region) with typical cancer . Is it OK for me to only compare the original cancer site v.s. metastatic sites for genes promoting metastasis? For that I have seen many researchers for similar purpose choose to compare original sites' data of patient with or without metastatic region, which is quite different from mine.
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Metastatic sites may share many of the transcriptome of the original tumor. I do not think that your comparison between primary tumor and metastasis will lead you to identify metastogenes. Remember that metastasis can also originate further metastasis.
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Hi all,
I'm working with an RNA-seq data set consisting of a large number of samples, sequenced at around 50-80M reads. There's a bit of uncertainty as to what the precise experimental workflow was for generating these data, but my best understanding at the moment is that the TruSeq RNA sample preparation kit was used (https://www.illumina.com/documents/products/datasheets/datasheet_truseq_sample_prep_kits.pdf).
This kit starts with total RNA, uses oligo-dT beads to bind polyA+ mRNA, then fragments the mRNA and carries out cDNA synthesis with random hexamer primers.
The data I've seen thus far show a very strong bias towards the 3' end of transcripts, in some cases so extreme that only the exons at the very 3' end are covered, with the rest of the regions having close to no reads at all. This bias is particularly pronounced in genes with long transcripts.
I'm aware that using oligo-dT priming is known to introduce a 3' bias into RNA-seq data as the reverse transcriptase will not always be processive enough to reverse transcribe in one go, but I'm at a loss to explain why the approach above might generate 3' bias if random hexamers were used.
Could anyone suggest any ideas as to what the possible causes of 3' bias in RNA-seq data might be? Are there any causes other than oligo-dT priming?
Would also really appreciate a link to a paper if one exists. Thank you!
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This could be due to the mRNA being somewhat fragmented even before the polyA+ capture. RNA is fragile stuff.
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In Sanger sequence, after having sequencer output (ab1 file), I would like to apply a free software to check the mutation on level of transcript. I was already working with “mutation Surveyor” software, but it is not freeL. Is there any free software? Thanks a lot.
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Check DNA Baser tool
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I am doing an experiment where I have to treat the organoids with insulin, harvest RNA and then perform RNA-seq. But I am not sure how long should the insulin treatment be to see an effect on transcription? Any insights on this would be helpful. Thanks!
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This depends on what you are looking for. At best, you could do a time course to look for early and late responsive genes. Are you interested in direct targets of the insulin signaling pathway or genes responding to changes in glucose or metabolism? For direct transcriptional targets you should consider using cyclohexamide to inhibit translation and thus any RNA increases are direct.
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Can you please suggest what could be the possible reasons for the confirmation of only 4 out of 13 genes (by qPCR), not all 13? Have anyone observed the same ChIP-qPCR validation issues? Any PubMed suggestion would be great. Thank you for your help in advance.
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Hi Amit
getting results from one experiment and failing to reproduce in an other experiment can allow you the differences and biases from both techniques. maybe you could look at the specificities of all your primers and see what's different in the 9 remaining genes. for instance you can check for specificity by testing your primers in silico at the UCSC website (http://genome.ucsc.edu/cgi-bin/hgPcr).
all the best
fred
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Hello everyone,
I am creating transcriptional reporters by cloning a promotor to a modified GFP in a plasmid. The GFP is modified by the addition of 13 amino acids at the end of it to render it less stable (if interest, see paper DOI: 10.1128/AEM.64.6.2240-2246.1998 ). I get the plasmid with the insert (promotor + GFP), but, there are always nucleotides' substitution in the 13 amino-acids tail added to the GFP. The mutations vary within the clones sent for sequencing. I have send the PCR product of the modified GFP used before the cloning, it does not have any mutation.
Where do the nucleotides' substitutions come from ? Any idea ?
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I had a similar problem with a protein that was apparently lethal to E coli. No matter what I did there were always indels and my transformation efficiency was super low. Try using a new bacteria strain with pLysS to prevent accidental transcription. Or supplement with 1% glucose in the media. Or do what I did and just screen a looot of colonies.
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I performed a CTmax experiment on Broad Whitefish at two acclimation temperatures and harvested liver and muscle tissue to perform HSP70 quantification in addition to acquiring a full transcriptome dataset for each tissue sample. After RNA-seq analysis, I quantified the transcripts using Salmon with Rainbow Trout and Northern Pike cDNA as the target transcriptome (there is currently no transcriptome dataset for Broad Whitefish). My goal is to find HSP70 specific transcripts and determine if there is a significant difference in upregulation between the two acclimation temperatures. I'm currently on Ensmbl and I have the reference names for specific HSP70 transcripts from the northern pike and rainbow trout, and I'm filtering the Broad Whitefish transcripts to find these reference names in the files and what the respective TPM values are. I'm wondering if there is a better way to quantify the HSP70 transcripts? Thanks in advance for nay help!
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You can map your reads against HSP70 directly, instead of a genome. You will not have a count per million, since you will only quantify this gene. But for comparison between samples, I think that there is no need!
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In allotetraploid B.napus plant transcriptome, Based on pacBio 3rd generation sequencing, one gene has evidence of Alternative splicing (AS) in it. This gene has four exons and produces 2 distinct transcripts. The structural analysis of two transcripts shows that transcript 1 is produced by using only exon 1 and 2 of gene, whereas, the transcript 2 is produced from exon 3 and 4. Therefore, these two transcripts have no overlapping sequences between them. I have to verify the presence of these two transcripts. Is there any other other strategy  to amplify the these two transcripts at once and show the evidence that these two transcripts are definitely transcribed from the specific gene, except using the transcript specific primer for each transcript (using transcript specific primer will just help me detect that transcript but will not provide enough evidence that it is originating from this specific gene.)?
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You have to design 2 sets of transcripts specific primers i.e. Primer set 1 including exon 1& 2 for transcript 1 and Primer set 2 including exon 3&4. Use the multiplex PCR to amplify both in a single reaction.
For multiplex PCR prepare the primers as nearby Tm.
I think it will help you more.
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Dear all, I have found white precipitate in my transcription buffer which is expired 6 months ago (Promega ribomax sp6 kit). I used the buffer to synthesis mRNA and run a luciferase assay. Unfortunately, I didn't get any luminescence signals.is it because of my transcription buffer or any other issues?
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The precipitate was DTT. Just be patient to dissolve it. If you don't trust the buffer, make your own batch (you can find the buffer composition in the kit's manual). Have you quantified your RNA or visualised it otherwise prior to translation reaction?
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There are so many DNA polymerase and they have many activities like polymerase activity, gap filling, proof reading activity, and DNA repair activities. Which one DNA polymerase does not have DNA repair activity?
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I agree with Malcolm Nobre
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In a recent study, RLB (RICE LATERAL BRANCH) gene were demonstrated to control the plant height of rice. A loss-function mutation of the gene led to reduced stature. However, when the authors overexpressed the gene, the transgenic lines also showed reduced plant height. The authors further determined the expression levels of endogenous and transformed RLB copies, and found that both of them were decreased to very low levels.
Question: RLB gene was proofed to positively regulate the plant height of rice, we expected that overexpression of RLB may cause overaccumulation of the RLB gene transcription and increase to some extent, at least not reduce, the plant height. Why overexpression of RLB resulted in reduced transcription for both endogenous and transformed RLB copies and caused the similar phenotype with the mutant? Based on the knowledge we have learned about small RNA biogenesis and functions, please:
1) give the possible explanation of the phenomena;
2) describe the mechanism may cause the above phenomena;
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Use your class notes to answer your homework. This is a site to ask questions about research projects, not a place for students to cheat on their assignments.
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I would like to study correlation between four transcripts (fold changes of mRNA expression) at different time intervals (5 time points). How can I perform this analysis?
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Try Correlation matrix on R Programming. Try corrplot( ) package in R
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I want to differentiate between mutant transcripts and WT that differ by one insertion.
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If you have access to a qPCR machine, you can also try "high resolution melting" to look for the presence of both transcripts.
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I'm trying to figure out how long (hours? minutes?) it would take to sufficiently stop transcription using 100ug/mL of alpha-amanitin in HEK-293T cell line?
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This paper has time points after alpha-amanitin in the cell line. If you check with Pubmed, there will be more you could find papers.
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I have planned to do a qualitative reaserch based on health belief model on betal chewing using focus groups. I have collected few data. In the ibnterpretationj how am I to analyse this. My plan was to get constructs of the theory as themes and find matching codes from the transcripts. Is that deductive apparoch or am I wrong?
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Hi Sameera, yes, from what you describe, you use a deductive approach to analyzing your data. From theory to data. Regarding this approach, I recommend you review texts on qualitative content analysis by Philipp Mayring, in which you can find out how from predefined categories you analyze your data. However, I also recommend adopting an abductive approach to analysis, which would allow you to go from theory to data and from data to theory, in a game of constant interpretation.
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I recently performed RNA sequencing on wildtype and knockout mice and have identified several differentially expressed genes (over 1,400 DEGs), and I'm interested in identifying what transcription factors are known or predicted to influence the transcription of these genes. Are there any bioinformatic tools or databases that can help me identify or predict those transcription factors? I've heard of AltAnalyst while attending a conference, but I can't seem to find it or any documentation. Any help would be appreciated!
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I prefer the hESlincRNABrower- you can use it
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Which is the best free software for coding of qualitative data in a doctoral study?
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Hello, I used Nvivo for qualitative analysis. I recommend it to you too. It is not a free program. However, the school you are a student at can provide you with this for your study. This is how it is mostly done in Turkey.
Best wishes
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Hi everyone,
some students of mine are having trouble exporting their transcription as a tab delimited file on ELAN. At the time of saving their files a message of "access denied" occurs.
It doesn not seem to be a problem related to their anti-virus.
Actually, I do not think this is a specific ELAN problem.
Does anyone have any idea of the reason behind this problem?
Thanks for your help,
Manuela
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Hi Manuela Frontera,
I don't think it's related to ELAN... Are they using a file you shared with them? If so, make sure they first extracted it from the compressed folder or downloaded it from the sharing paltform you are using (if it is the case) and stored it in their computers... If they are using a file of their own, do they have admin permissions in the computers they are using? I think this might be related to this type of technical issues... Hope this helps you!
Regards,
Marisa
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Hi,
I am designing siRNA for a gene knockdown study and was wondering if an siRNA designed for one transcript variant of a gene also targets other transcript variants. Is this the case?
Thank you all for your help!
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If the siRNA target sequence is present in both transcript isoforms, you can assume that the siRNA will target both. If you are trying to target one isoform specifically, then you need to select a target site that is unique to that isoform (e.g. a exon-exon junction not present in another isoform).
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Hi all,
I have been interested in validating our RNAseq data and have noticed some discrepancies with qPCR or droplet digital PCR for mature (exonic-exonic based probes). Does DESeq distinguish between intronic and exonic transcript counts? Is there another package that can only look at mature transcript counts in RNAseq data?
Thank you!
Lisa
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Thank you Andres-I will take a look at featureCounts. I got the data from someone else, but can ask those questions.
The gene I am investigating is not annotated completely in Gencode, and a deleted exon (which is annotated) is not impacting the DGE analysis. (Even though by ddPCR it is the highest exon expressed at that age.) I've done deep sequencing on it and still confirmed high expression for this exon so I think their is something strange about the DGE analysis. Do you think there could be anything else that might account for the difference?
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Recently, I order the seeds of the T-DNA-inserted mutant (1.5 kb gene), which has in the mid one lncRNA sequence roundabout (331 bp) in the genome. I confirm the mutant by genotyping, it's fine. But, when I tried with different pairs of RT-PCR primers (full- For + Rev, mid- For + Full Rev, and full-For and mid-Rev) to see the mRNA level, the transcript is still there. Does anyone suggest what should I do with this?
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Hi Shah,
I can tell you to see at the UCSC database (http://genome.ucsc.edu), there is a genome browser for lot of species, including human for which there is an option in hg19 to see published sets of primers for transcriptome purposes.
all the best
fred
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We wish to inactivate RNAP in E. coli, specifically the transcription elongation phase, and preferably without disassembly of the transcription elongation complex. The well-known rifampicin is inhibiting the initiation step allowing run-out of the existing transcriptions. We used previously streptolydigin that inhibits the elongation, it worked well with B. subtilis but does not penetrate the E. coli envelope (and is anyway not manufactured presently). Can anybody recommend another antibiotic with the required properties or a suitable temperature-sensitive RNAP mutant?
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Hi Itzhak, check the Microcin J25; it should inhibit transcription by binding within and obstructing the RNAP secondary channel - acting essentially as a "cork in a bottle", preventing NTPs to get in the active centre. But I am not sure about penetration to different organisms.
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Can deiodinase 1 gene that codes for deiodinase enzyme, contains a sequence of noncoding transcript?
If yes, what is the function of this noncoding transcript? Does noncoding transcript found within a coding sequence of DNA? or they have their own defined sequence in the genom?
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1. Noncoding DNA contains sequences that act as regulatory elements (see attached file), determining when and where genes are turned on and off. Such elements provide sites for specialized proteins (called transcription factors) to attach (bind) and either activate or repress the process by which the information from genes is turned into proteins (transcription). Noncoding DNA contains many types of regulatory elements:
Promoters provide binding sites for the protein machinery that carries out transcription. Promoters are typically found just ahead of the gene on the DNA strand.
Enhancers provide binding sites for proteins that help activate transcription. Enhancers can be found on the DNA strand before or after the gene they control, sometimes far away.
Silencers provide binding sites for proteins that repress transcription. Like enhancers, silencers can be found before or after the gene they control and can be some distance away on the DNA strand.
Insulators provide binding sites for proteins that control transcription in a number of ways. Some prevent enhancers from aiding in transcription (enhancer-blocker insulators). Others prevent structural changes in the DNA that repress gene activity (barrier insulators). Some insulators can function as both an enhancer blocker and a barrier.
2. For DOI1, It is a selenoprotein, containing the rare amino acid selenocysteine (Sec) at its active site. Sec is encoded by the UGA codon, which normally signals translation termination. The 3' UTRs of selenoprotein mRNAs contain a conserved stem-loop structure, designated the Sec insertion sequence (SECIS) element, that is necessary for the recognition of UGA as a Sec codon, rather than as a stop signal. Alternatively spliced transcript variants have been found for this gene (source: https://www.ncbi.nlm.nih.gov/gene/1733/)
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When you use RNAseq I understand that it must follow certain conditions when you use it.
One of the conditions it must be the adding of a polyA tail, which is recommended for stability. However, there are certain groups which already include polyA. Some need to be inserted, but this is not always the case. Sometimes the sample is not adequate for its direct use on RNAseq. Modern techniques of RNAseq include modifications or changes to the original technique on RNAseq, however, some of them depend on the sample, some of them depend on the technique.
I guess one of them is the change of the polyA for its use for more samples, although I am not sure. Maybe the change is the use of a polyU but I am not sure.
What do you have to do to the sample for it to be admitted on RNAseq, no matter the origin? Do you have to exclude some groups? Can you allow all groups? I understand either prokaryotes or eukaryotes are the hardest or the most difficult, even though I am not sure. Are there any peculiarities depending on the group?
What happens to the peptide signal on eukaryotes or prokaryotes? I understand peptide signals on prokaryotes are S-Met. Does it make a difference?
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Yes, this is my question. What kind of change would the rest of the samples need?
Jaba Tkemaladze
Artur Burzynski
Thank you for your
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Dear all,
I am looking for a primer set for qRT_PCR with SYBR Green for detecting the fusion transcript BCR-ABL1 p210 (B2-A2) in KCL22 cell lines.
Do you know any databse of oligos where I can find the optimal primer set?
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Thank you Jochen!
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For my Masters dissertation I am planning to use CA as my research methodology. I have collected all the relevant data I could find to my topic, which includes transcripts of speeches made by government officials and reports. The main problem I am having is that none of the data is relative to each other, yet it is all relative to my research question. Therefore, my difficulty is in finding themes that are common amongst the data, that I can comment on for similarities and differences. I am able to draw out themes and concepts from the transcripts individually and irrespective of one another that are eligible to use in my discussion, but am unable to find patterns amongst the data. My question is; could I apply principles of CA to each piece of data separate from one another and draw things out that I can critically analyse, without having to be too comparative?
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For an inductive approach, I recommend that you check out Braun & Clarke's Thematic Analysis.
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I worked on microRNA and after transcription into cDNA and going into Real time PCR, I used different concentrations of cDNA. I noticed that diluted samples give better results and lower CT in most of cases but results were not consistent all the time.
So I want to know is it necessary to dilute cDNA for microRNA work and if yes, why?
Is this applicable also to any work on RNA?
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Hi Ahmed
Totally agree with the opinions already showed. qPCR for miRNAs is very similar to the protocol applied to other RNAs. I experienced the same behavior like you described, where the cDNA must be diluted prior to qPCR.
For miRNAs from cells or tissues, I routinely use a dilution of 1/5 to 1/10 depending on the initial RNA concentration to ensure a final cDNA amount around 10-100 ng per reaction.
Note that if you are working with circulating miRNAs in biofluids like plasma or serum, you should also dilute the initial RNA sample prior RT reaction due to the presence of RT inhibitors.
Best of luck
Cheers. Paco
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Dear colleagues,
I will appreciate your advice on choosing a protocol to conduct the differential gene expression analysis between species. We have RNA-Seq data from 5 different species, and we would like to explore genes with a species-specific signature. We are aware of the issues in doing that regarding differences in transcripts length, libraries deep, transcripts sequence divergence, etc. Thus, we will appreciate any recommendation to go ahead with our work.
Greetings,
Roberto
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Yes or you can use a log transform, the important poit is that the rows of the matrix (statistical units) of the different species (columns) are correspondent
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Suggest some softwares other than Nvivo, which will automatically detect the factors from the transcripts.
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There are a number of software programs that are specifically devoted to "text mining," of which Leximancer is one of the better know.
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Hello,
I want to study a transcription-related phenomenon. For this I need to induce the transcription of a subset of genes in a timely manner. I immediately thought of ISGs as I have heard that they can be induced upon HIV infection. Can I use commercial interferons to induce the transcription of ISGs in HEK293 cells? If yes, which interferon is most likely to give the highest transcription response?
Are there other gene subsets that you might think of? Like oestrogen inducible genes? or heat-shock response?
Thank you for your help.
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I'm also using HEK293 cells and want to pick a few ISG to measure with qPCR after treating with IFN-beta. I tried OAS1 which worked nicely but Mx1 wasn't induced as potently. I wonder if you have any advice on this? Thank you!
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I was wondering whether it is possible to turn off the expression of a transcription factor that is expressed by CD8 T cells, and if yes, how?
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Yes it us possible. You can design a sgRNA and then use CRISPR can system to knock out either the promoter region or the main gene of the transcription factor employing NHEJ mechanism of cells which is error prone and induces INDELs
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I conducted a semi structured interview to parents about their experiences as modular facilitators during the pandemic. I would like to ask that when transcribing the recorded interview, is there a need to also include the follow up questions in the transcript along with their answers, or I will just include their answers to the follow up questions in the original set of questions validated by the evaluators?
Thank you in advance!
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Simon Stephens Thanks for your valuable suggestion. Mel Nano Thanks for asking this question.
Regards,
Nandan
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I'm analyzing RNA-seq data using the Kallisto/Sleuth pipeline on R. I'm using Sleuth to compare transcript abundances between two populations of oysters under different conditions and one of the Sleuth outputs is this volcano plot. I've seen other volcano plots but haven't seen one that has discernible horizontal line at qvalue (y-axis) of 1.5 where a bunch of transcripts appear to congregate. Is there any reason for this? I've searched around and haven't seen another volcano plot like this.
Any feedback is appreciated! Thank you.
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Sharp lines like that are usually indicative of a processing error. I would double check the QC plots for each sample, perhaps one (or more) of them was not properly analyzed.
Another concern is the huge number of differentially expressed transcripts you are seeing between your groups. By eye it almost seems that there are more significantly different transcripts than not. It's going to be very difficult to determine which of these changes might be meaningful.
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Dear Friends,
Does anyone know an institution/university which hold #workshops or #courses on single cell RNA sequencing (either online or in site)? thank you in advance, #singlecell #singlecellsequencing #RNAseq #sequencing #cellsorting #RNA #transcriptomics #omics #transcript
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The book Orchestrating Single-Cell Analysis with Bioconductor (https://bioconductor.org/books/release/OSCA/) is one of the best reference for single-cell analysis.
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I have identified 12 transcript variants of my gene of interest from ensembl and I want to find the expression of these transcripts in body tissues using GTEx. I think to do this however, I need to have the rs number for the transcript variants. I was wondering if anyone can suggest the best way to go about finding this information out as I am struggling?
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I would also say that you are confusing concepts, in GTEx you will find eQTLs or sQTLs in which the presence of an SNP (rs) is correlated with the expression of a gene (eQTL) or with the expression of the isoforms of a gene (sQTLs). Therefore, if you have the Ensembl ID of the transcripts of a gene and you want to compare it with the GTEx database, you will possibly get the SNP that is correlated with it. I don't know if I made myself clear.
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Hello,
It's been a while since I've come across this idea of abortive rnas having a function other than instant repression, or at least, 'function' regarding the initiation of transcription. There's no data available about this short transcripts being part of metabolic pathways of any kind, neither about the 'macro' repercussion of having lots of very short rna transcripts 'swarming' the nucleus.
Does anyone think we are failing to approach a wider understanding of these little rnas (if proven that there's a possible 'wider' scenario), or maybe, that these rnas may have an incredible meta-function, such as those of mirnas, sirna, etc?
Thank you for reading this!
Diego
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Abortive initiation, also known as abortive transcription, is an early process of genetic transcription in which RNA polymerase binds to a DNA promoter and enters into cycles of synthesis of short mRNA transcripts which are released before the transcription complex leaves the promoter. ‘Abortive initiation’ is characterized by the repetitive synthesis of small oligomeric transcripts near the start site of transcription, and these abortive products are released from the transcribing complex without release of the polymerase or initiation factors. The abortive transcripts have the same nucleotide length as the primers employed in DNA synthesis (i.e. about 8 nucleotide bases). It appears that abortive transcripts are a fall out of evolutionary primitive RNA polymerase reaction which could do both transcription and priming of DNA replication. Abortive cycling would therefore play an important role in evolution for the emergence of the DNA world. In the DNA world, speculations are that abortive transcripts may play a role in as determinants of promoter strength, of RNA polymerase function, and a target of regulation by transcription factor GreA. Abortive transcripts may also have functional, physiologically important roles in regulating gene expression in vivo
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I am a member of international research team conducting research based on qualitative approach working on individual interviews. After gathering data by each researcher in its native language we have transcripts in three languages. I should also say that we communicate in English. When it comes to analysis I am wondering if it better to translate all transcripts into English and perform analysis in English or analyse transcripts in its own language and then compare findings and translate data that is going to be cited in the article. Do you have any experience in such research teams? What is the best way? I appreciate all comments. Best regards dear friends.
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Just use English. But the analysis and results don't depend on language if translated accurately :)
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I recently came across a gene which had 5 alternatively spliced versions, where only two had protein coding transcripts based on ENSMBL and 3 processed transcripts. Does this mean that the other 3 do not code for protein? If they do not code for protein, why do these transcripts get expressed?
My primers detect 3 out of the 5 spliced versions (the two protein coding and one processed transcripts). I am worried that an increase in gene expression could be linked to a change in a none protein coding transcript.
Do you have any experience regarding this? What is the relevance of such expression towards RNA seq data we get? Would like a discussion surrounding this.
Thank you
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Dear Harshani,
without knowing which gene we are talking about, the question can't be properly answered, but it might very well be that you have 5 transcripts of which only 2 are protein coding.
The non productive transcripts might be expressed due to a number of reasons, which one might broadly sum up as "regulatory". It is known that some genes have negative feedback loops:
Gene X is transcribed at a constant rate. While the protein X concentration is low, the productive transcript is produced, leading to higher levels of protein X. At a certain concentration, the protein (directly or indirectly) induces a change in alternative splicing, so that the nonproductive isoform is produced. This leads to a lower protein expression. Shameless link to my own publication regarding this topic:
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I want to synchronize mouse embryonic stem cells in G2/M phase in order to study transcription of a gene of interest during mitosis and throughout the cell cycle but I'm a having a hard time finding a protocol for this.
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I am trying to use this theory in my research, and I need some kind of advice on what aspects I need to focus on in the transcripts of my participants. Please share with me any books or articles that can be helpful.
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Ellen Rooney's The Cambridge Companion to Feminist Literary Theory is the most approachable guide available for both literature students and those new to field.
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I am frustrated that I cannot find an answer in the literature to this as it's a simple question and the information must be out there - I need to confirm the direction of replication for plasmid pSC101. I've found lots of references about the characteristics of the origin and replication protein but have been unable to find information that makes be 100% sure of the direction. I believe it is in the opposite oritentation to transcription of the Rep protein (from a plasmid map in Hashimoto-Gotoh (2000) v241p185), which would mean in the opposite direction to the iteron Direct repeats in the origin (as in Sugiura (1993) J.Bact. v175p5993).
I am really want to confirm the direction in relation to the origin features (rather than the Rep protein).
Thanks in advance.
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Hello Chris Co
Your question is a year old now, so you've probably found the answer. But just in case, and because I undertook the same frustrating search, pSC101 replicates unidirectionally in the opposite direction to transcription of its repA gene. I have this on the semi-authority of a few sources but the only actual data I could find was Cabello et al Nature, 1976, where they find exactly where the ori is relative to the EcoRI site used to oritent their molecules, but couldn't really tell the direction because the site and the origin are diametrically opposite ! I'll settle for the consensus .... provisionally. I'm not sure origin features are a reliable guide.
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I know the theory says that transcription starts at +1. However, sometimes transcription can start at a different position (see for instance the article "RNA Polymerase II Activity of Type 3 Pol III Promoters", where the H1 promoter starts transcription at position -8).
Someone told me that this was also the case with CMV promoters: they would sometimes start transcription later than +1, so skipping the first nt of the 5'UTR. Can anybody confirm this?
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I think it is more than +1, as the TATA box located just at the end of CMV
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Transcript abundance is often used as a proxy for the abundance of protein isoforms, though proteomics experiments using gel electrophoresis and mass spectrometry have demonstrated that the correlation between transcript and protein counts is often low and that one protein isoform is usually dominant. My question is as follows: Does designation "Isoform 1" stand for the most dominant/abundant isoform, considering data from the NCBI database? If not, is there any easy way how to find a dominant isoform for any gene and organism?
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What are the best assistive software that you're using to facilitate the transcription of qualitative data? I use soundscriber (a free tool). I am looking for better options.
Thanks.
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I've found NVivo to be quite intuitive and easy to master. This gentleman offers a series of easy-to-follow tutorials on the program: https://www.youtube.com/watch?v=LnavhMQCrRU.
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Hi,
I will be interviewing some students and staff as part of my Masters Thesis on partial absences in secondary school. I am looking for suggestions for software to allow me to create transcripts and to analyse the transcripts. It could be one software or two individual pieces. I am willing to pay a little( small budget!) if needs be.
Thanks.
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For transcribing, I have had good results with otter.ai, and others have recommended Trint and HappyScribe.
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In my project, I want to study the effect of stress on the differentially expressed transcripts in zebrafish and identify the affected cluster of genes. I will be using the Illumina platform (Nextseq High output). We kind of decided to go with 20 million reads/sample. We find that the single-ended 75 bp option is cheaper but we are wondering whether we choose this over 2x75 bp or not. So, a single-ended 75 bp and 20 million reads/sample would be powerful enough for my purpose?
Also, I would appreciate any suggestions regarding Zebrafish RNAseq since I am a novice here!
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Hello
I recommend using paired end, it would give your more confident results also a chance to find novel transcripts.
Good luck
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I am looking for transcripts and other forms of qualitative data on burnout, but I can only find open-source quantitative data. Is there anywhere I can look or anyone I can contact to find such data? Any help would be greatly appreciated
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I suggest you to formulate open ended questions for an interview as a method of collecting qualitative data then upload it on linked in so as to get professionals feedback
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Hi, I have a question regarding the intronic region in transcript data. After the transcriptome assembly and reconstruction using StringTie, I get 5 coverage files using ballgown (with -e parameter) that are ( e_data.ctab , i_data.ctab , t_data.ctab, e2t.ctab and i2t.ctab ). I want to know why we get intron files (i_data.ctab and i2t.ctab) from transcriptome data(which has s processed transcripts sequences).
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There are several reasons, some are biological:
1) RNA-seq experiments often generate reads derived from pre-mRNA in addition to ones from mature RNA transcripts, even if you enrich for PolyA.
2) You may have contamination from DNA (even slight)
3) Some Introns (real or predicted) may be retained in you transcripts because of alternative splicing or because they produce functional non-coding RNAs.
Some are bioinformatical:
The introns you find depends also on how you prepare the libraries (if you enrich your RNA etc.) and how you bioinformatically clean your data (trimming...). It is also important which reference genome and with which gene model annotation (the GTF or GFF file that defines known exons and introns) you are using with HISAT2 and later stringtie.
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Dear RNA researchers
I would like to know the difference of transcription of Norad lncRNA between my control and knockdown cells. Would you recommend the appropriate method to evaluate transcriptional efficiencies in both cells? Initially, I thought that pre-mRNA qPCR (often used for mRNAs) is an appropriate one, which seems that it is not a good method for lncRNAs.
I appreciate if you would provide me with constructive suggestions.
Best regards,
Akiko
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I recommend reading the following articles to get the answer to your question.
Best Wishes,
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I have a dataset with 96 individuals and 1496 transcripts of interest. I have analyzed the experiment by multiway ANOVA in the Permanova platform of Primer-E. I am satisfied that I have figured out how to do this and test my experimental hypotheses. However, it occurs to me that I can also run some kind of cluster analysis to identify and examine clusters of similar individuals. What might be the best Primer-E method to accomplish this?
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LDM
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Hello,
I would like to compare the expression levels of several genes in insects, so I prepared standard curves and estimated copy numbers of each sequence in my samples. But for one of the genes, I tried to use two primer pairs (amplifying the same transcript) and got quite different results (24x factor between the two estimations). I looked at primer efficiency: 1.95 and 1.94 respectively, which I assumed to be good enough...
So I was wondering if some of you has tried to amplify and quantify one transcript with two or more primer pairs to check the robustness of the results ? For all the other genes, I used only one pair but I'm starting to wonder if I would get the same results with additional primer pairs...
Thanks !
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Assuming that:
1) no one made a math or pipetting error in making the standard curves
and
2) your primers can't be amplifying other targets in the genome or in any contaminating bacteria/fungi/whatever
and
3) you aren't accidentally amplifying genomic DNA with one primer pair
then you have something weird.
My money is on either genomic DNA amplification or math error.
What do your controls look like?
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Du type NVivo, etc? Y-a t-il des programmes français performants?
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Peut être que vous trouves cette article util.
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using ballgown, i have extracted expression values and sorted based on the pval of 0.05 and based on fold change classifying >1 as up and <1 for downregulation.
for some genes, two transcripts have different fold change values (for example two transcripts of ODF2 are showing 0.009 and 41.5)
so which one should i consider either up or down regulated and what basis should i select.
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While you are comparing between the two contrasting samples and the resultant expression values you can roughly choose isofarm giving 41.5. While aligning your sample reads against the reference, you will get isofarm (genes), which you can again mark for SNPs on the map (for this gene' s neighborhood). If the SNP is assynonimous ( different alleles but for same amino acid) you can accept this value. Another computational approach for accuracy is Normalization of the value, which is proportional to mean length of given transcript under RPKM estimation.
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I'm looking for ways to automate the transcription of interview data.
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Yo uso para El portugues easypronunciation, pero tambien IPA oferece la transcripcion....
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Assays for bacterial small RNA sequencing
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Thank Kyle Skalenko and Aymeric Fouquier d'Hérouël for your contributions. Appreciated.
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An operon in a bacterium contains several genes. The transcriptional level of first gene is ten-folds higher than following genes.
Possible reaons for this?
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How are you measuring the transcriptional level? Is it a direct read out or is it protein levels? If it is protein levels it could be a premature stop codon.
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Hello everyone,
I'm doing polysome profiling to answer a specific question.
I study a gene which produce an alternative transcript and it's translation is controversial (extremely lucky if you can see the truncated protein by western blotting after a harch MG132 treatment).
I know the unspliced transcrit is well translated and I want to know if the spliced one is translated as well.
So I transfected cells to express the two transcripts and I realised a polysome profiling experiment. And the transcripts are exactly in the same fractions at the same percentage.
To confirm this result, I did the same experiment but with transcripts with no ATG and I also find the same results... (noATG transcripts are in the same fractions as normal transcripts).
I was expecting the noATG transcirpts to be in the free RNA fraction but they are in the monosome ans polysome as well.
Anyone has an explanation ?
Thanks for the help you can provide !
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Thanks for your answer Uwe Borgmeyer !
My transcript also has 13 AUG in total and I only mutated two of them.
Even if my deltaAUG transcript is not translated, maybe ribosomes recognize the other AUG at a given time. And the CHX treatment before polysome profiling could make them stay on my deltaAUG transcript.
Anyway those deltaAUG transcript don't seem to be good negative controle for this experiment...