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The STR markers I am working on are linked to Cystic Fibrosis Transmembrane (CFTR) gene and I wonder where should I check if these STR have previously been reported or not.
Cheers,
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Katie A Burnette I realized that the NCBI Probe database is not available anymore. Through the UCSC Genome Browser, I managed to find di- and tri-nucleotide microsatellites.
Have you got any clue how can I find tetranucleotide STR markers that have previously been reported for my gene of interest, CFTR?
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I am trying to determine the usefulness of the marker shown in the attached photo. You will see that in one sample there appears to be 3 alleles (this is a diploid, or more precisely a dikayotic spore). I have seen this in other samples too and have eliminated the possibility that it is DNA contamination by looking at other markers that don't show this pattern.
I have already gone through the step of Pig-tailed reverse primer (these are the results for this) and a longer final extension in the PCR (30 minutes) to try to eliminate stutter on the 'rooster comb' peaks you see. Any other suggestion, or just don't use this marker?
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Hi Vick, I wouldn't worry about that if I was you. Amy gave you some interesting tips and you can go ahead if you want to, but I think this one you are seeing is just a technical artifact. Some florescence reading chambers, as those from ABI3500, are too sentitive to florescence signals in fragment runs and some times very strong signals extrapolate the notation of one length wave to another. Therefore, we usually see a reading from, let's say NED- fluorescence at the exactly same location in the FAM or HEX (standard ABI chemicals).
If you are loking at a multiple samples view, they seem real peaks, but if you see that at multiple flourecence view (all length waves from the same individuals) you will probably find out that your individual has coincident peaks in multiple florescences at the same time. It should be hugely high at the original flourecence but smaller than the actual ones at the others.
If you did a single-flourescence run, it is also possible to be a neighbor signal noise noted to another sample.
I've seeing that a hundred of times with different samples and different organisms and repeating PCR with different flourecence or getting less florescence at the run make the strange peaks gone. You might also test it by diluting your pcr product a bit more before the run.
Try to check this out before doing more tests. If you still getting such a peak then you can think about other possibilities. If you have any questions about specificities, feel free to message me.
Hope it might be helpful.
Best
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Most of my microsatellite markers are dinucleotides, therefore they show stuttering. In regular stuttering is easy to identify the allele, which is the highest peak on the right, after the shorter stutter peaks (Fig. A). But in some samples, usually in larger alleles, the highest peak varies the position or all peaks show similar highs (Figs. B, C, D, E). In these cases, what is the allele: the highest peak (independently of position) or the peak on the right (following the position pattern)? Fig. E is an extreme case, with confusing peaks. In a specific marker, some samples show a central highest peak with two other shorter peaks: one ~30 pb smaller and the other ~30 pb larger (Fig. F). Is one of the shorter peaks a true allele or are both a type of artifact ("ghost peaks")? Finally, can I consider weak amplifications? Probably these shorter peaks are because of low quantity/quality of DNA or due to large allele dropout (Fig. G). I am scoring microsatellite data manually in Peak Scanner 1.0 (labels show height (H) and size (S) of peaks). In the PCRs, was used Platinum Taq DNA Polymerase, cycles with 30 min of final extension and primers forward tailed with M13. Due to limitations of time and resources, we won't be able to rerun the fragment analysis. Thanks for your attention.
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Thanks for sharing the links!
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I would like to know if anyone knows about other software other than Genemapper/Genamarker to visualise peaks, or whether there is any online platform available? Thanks in advance.
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I do agree with mr. Rileys suggestions. Or try to collaborate with a gp that hsa the ABI tools
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I've run a couple hundred samples using a microsatellite panel, and recently some of the runs show very exaggerated stutter peaks smaller than the true allele size. To troubleshoot the issue, I've rerun the same PCR product multiple times on our ABI 3500. The problem appears to arise from the fragment analysis, rather than the PCR step, since the same product produces very different results from run to run. Some samples look fine in one run but the same PCR product shows the mystery peaks on a second run. Since some of them are showing up in each run, and the peaks are often much larger than the true allele peak (sometimes the true allele is even absent), this makes accurate scoring impossible.
I've posted three examples from three different samples and 3 different loci. The lower run for each is the one depicting the correct alleles, the upper run shows the large stutter peaks and small true peaks. In one case, the ghost peaks are 4bp smaller for a 4bp repeat, but in the other two they are 10.5bp smaller and 7bp smaller for a 3bp and 4bp repeat, respectively.
I've never had this problem before, but also am relatively new to running the ABI machine myself. I'm loading:
7ul of MClab orange size standard in SuperDi
1ul each of 3 PCR products (topped with mineral oil). They are diluted 2x first before loading.
the product was stored for ~1wk in the fridge before loading.
I've tried heating the plate to 95deg for 5 min then chilling and loading, to no avail. I've also tried re-running PCRs and the problem returns. Some plates look fine, and others are all bad.
Any suggestions on what is going on or how to fix it?
Thanks!
Kevin
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SOLVED: I believe i've figured this out. I tried again with fresh PCR product, my old size standard and formamide, and a different batch of size standard and formamide. Fresh formamide + size standard fixed the problem. The old size standard/formamide mix also worked if I denatured the plate at 95 degrees C for 5 minutes followed by snap cooling at 4 deg c for 5 min.
I found this issue described here, for other's future reference, on slide 58:
Basically, it looks like my DNA was hybridizing, probably because the old formamide was bad and couldn't sufficiently denature the fragments. Looks like I just rediscovered a common problem, but hopefully this'll help someone else more quickly find the solution.
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Dear
I'm in process to do a big data microsatellites analysis about all cattle breeds around a world. I'm very gratitude for all researchers accept help me in this project; sure any researcher participate in this work seen his name like an author at the paper.
Some researchers can ask why I can compil the result in the fact the result don't provided with the same laboratory? don't woried I can do the merging after transforme the result.
Best regards
Suheil
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Hi, this article may help you
Bovine and ovine DNA microsatellites from the EMBL and GENBANK databases
DOI: 10.1111/j.1365-2052.1992.tb02168.x
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A study was conducted on a kind of endemic marine mammal in a land locked sea. The coastal line is about 1000 km from West to East. 20 microsatellite markers had used and the results of DPAC analysis using adegenet (R package) Fig 1 and STRUCTURE software (1000000 MCMC, 10% burnin) Fig 2 were shown two different populations of this species. The results reinforce the hypothesis that there is more than one population in this closed sea. Now, I've three questions here:
a) Is there any possibility to have two populations for mentioned species in a land locked sea with 400000 km2 area?
b) With these results, can we conclude that there was a gene influence form the east population to the west population?
c) How about interpretation for DAPC graph with two curves?
P.S: In both barplots, red cluster represents west population individuals, while green cluster indicates East population individuals.
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Hmm, without knowing the species and a bit about its distribution/dispersal ability it is hard to say. What you are showing could be the result of 2 diverging populations, or it could be the result of sampling 2 locations within a single population that are far-enough apart that isolation by distance accounts for the depicted differences. If the "populations" are discontinuous, I then begin to wonder if this is a natural process, or a relic of anthropogenic pressures (hunting, etc) fragmenting a once-continuous population - then drift, etc between the two "populations" resulting in the observed patterns. I'm curious what the pairwise FST, expected heterozygosity, and observed heterozygosity are? These should prove useful in determining down-stream analyses. Also, I assume no complimentary mitochondrial or SNP data is available?
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When you got the raw data from an SSR marker survey it is presented as length (number of base pairs) of alleles. Typically, a matrix with samples in rows and allele length in columns. However, how do I build a matrix for calculating neighbour joining or UPGMA dendrogram from these lengths? As I understand I must “translate” the data to binary 1/0 data?
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The POPPR and APE packages in R work great for this as well, especially for co-dominant SSRs.
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Hello everyone , I'm working on microsatellite analysis of Saccharomyces cerevisiae. I started with ScAAT1 locus. Here is the raw data of the first isolate shown on the chromatograph (DNA Size Standard in red and PCR products in blue). My question is to know first if I have to consider all bands as alleles and then what sofware is appropiate for this kind of analysis.
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With microsatellite regions that have been optimized you should only get one peak (homozygous) or two peaks (heterozygous). If you have multiple products you are looking at non-specific binding. You need to go back and optimize the PCR conditions so you get a single product.
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Working on a pilot project so funds are limited. Has anyone used the Green BioResearch Plant Genomic DNA isolation miniprep kits for downstream microsatellite analysis? Everyone I know uses Qiagen, but the cost is prohibitive. Any feedback, advice welcome!
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If funds are limited, you can go classical and use phenol:chloroform method or CTAB method for genomic DNA isolation from plants.
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Can we use binary data of SSR markers for diversity analysis using PowerMarker 3.25 software. What is data format?
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While using Power marker for SSR data analysis, binary data format (0 or 1) is not appropriate. Genotypic data format (AA, AB, AC, BB, BC, CC) similar to that required for co-dominant marker analysis using Popgene software is appropriate.
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Now,I  assessed 8 SSR markers. I see others often calculate the  Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium . But the species I studied is a haploid. Can  I often do these things?
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I amplified a repetitive sequence in blood and brain tissues and performed microsatellite analysis. Is this sufficient to demonstrate mosaicism? What analyses should I perform to differentiate real alleles due to mosaicism from stutter peaks? Thank you very much for your time.
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follow
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Hey everyone,
So i am using Peakscanner for Microsatellite Analysis with LIZ600 size standard. From one day to another, peakscanner didnt recognize my samples. While on capillary Viewer on our sequencer you can easily see the size standard and the sample peaks, but if you open the files with peakscanner, it wont show any peaks. Neither a Fail or quationsmark on "quality" tab. (see the picture)
I couldn't find any help or troubleshooting in the guides.
Opening a file that worked and a file that doesn't on BioEdit shows every Peak where it should be. Sadly you can't use Bioedit to differ between Size Standard and Sample.
Anyone got some ideas?
thanks, Fabian
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Maybe we already have the answer. Looks like the LIZ600 Marker is broken. We are testing it right now, but it looks like, AB send us a broken one.
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I have two data sets, one chloroplast SSR and one nuclear SSR, both with 20 populations and I would like to run a Barrier analysis (Barrier 2.2) separately once on nuclear and once on chloroplast. as I know I need a Fst or Gst matrix and a bootstrap matrix and GPS coordinates of the pops. Unfortunately, I don't know R software, so I need a something which can create these matrices from my data set. Any suggestions?
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Dear Alfredo López Caamal ,
I attache here the MICROSAT software version 1 and 2. But, I would recommend to generate the distance matrices with a different software called Microsatellite Analyzer (MSA). This software is simple and runs under newer operation systems such as Win 8.1 and 10. I used this to calculate DA the Nei's chord distance, which used in several studies for Barrier analysis. This also capable to generate over 100 bootstrap matrices. If you check my publication Tóth et al. 2017 in Tree Genetics and Genomes I used this software in it. It is available for several platforms, including Mac, Win...etc.:
I hope you find it useful!
Best wishes;
Endre
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I collected samples using a baited adhesive tape which was crossed by different animals in the wild.
Because I can’t know if different hairs I have on my tape are from different individuals I just use single ones for DNA Isolation. I incubate with cell lysis solution (100µl), proteinase k (0,5µl) on 55°C, protein precipitation solution, isopropanol and wash with ethanol leaving a rest of ethanol in the tube because I can’t see a pellet. I add 20µl hydration buffer.
Then I try a pcr (35cycles) with primer pairs for species specific microsats. After analyzing the product on an polyacrylamide gel I mostly just get multiple bands on the full length of the lane.
The dna purity is low (around 1 instead of 1.8) as well as the concentration, measured by photospectrometer (~4-12ng).
I don’t really know where the problem may come from because I get a pcr product. Maybe the primers are damaged because I defrosted them too often? Or can I do anything to earn more and more pure dna from a single hair? I didn’t try something like washing it before isolation. Maybe it is contaminated. The glue from the adhesive tape could also damage the dna?
I hope somebody has helpful answers to the topic. Thank you even now.
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Checking primers would help, and you can work on annealing temperature to get better picture. If your primers work well, no worry about your DNA :-)
Good luck in your experiment...
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I am looking for a way to build a haplotype network using SSR data. I have been using Poppr R package before, but I want to see the distance between isolates in nodes/steps. In Poppr the network uses gray scale method of showing how closely related isolates are, but using this approach it is hard to interpret how many steps are between individuals (I need this information). I can't find how to change it in poppr and looking for another solution. So far I have found few packages for sequence data using SNPs but not SSRs.
Will greatly appreciate any advice or ideas.
Thank you!
Olga
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Hi Olga,
Good luck!
Conny
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I collected fecal samples from fresh bear scat last summer. I used sterile swabs and stored them in 100% EtOH. They have been kept at -20C. Does anybody have any idea what the best method of isolating the DNA is? They will be used in microsatellite analysis. I tried using the AquaGenomics kit (first time using it, but another lab uses it and they have good luck with it using fecal pellets).  I am not having luck amplifying DNA from this method.  I don't think this was the best collection method, but now I have hundreds of samples that need to be processed...
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Hi Jenn,
we have protocols for this on our website www.starworms.org
Piet
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Hi all,
I've run 6 rounds multiplex PCR of 21 self-designed microsatellite primers on bear samples. I have pooled all the pcr products, purified the amplicons and sent for NGS sequencing.
I have Geneious software and also Linux workstation. Upon receiving the sequencing data, I hope the experts in ngs data analysis can help me with suggested workflow or commands to:
1. Isolate the sequence reads according to the microsatellite primers 
2. Calculate the tandem repeats in each microsatellite loci sequenced in order to select suitable primers for genotyping of more samples
Thank you in advance.
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Hi wai
as arthur said, multiplexing PCR without habving barcoding them means that at the end you have a pool of sequences, therefore impossible to address to samples.
but if you did it, you'll need first to align the sequences to the bear genome. from fastq files you'll get bam files, you can vizualize on some softs as IGV.
fred
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I have data from nine microsatellite loci and MHC class II gene data where I cannot assign alleles to loci (however I know that I have multiple loci in individuals because I can amplify up to 8 MHC alleles with my primers). I want to compare FST values of fish from different populations using both markers. To do so (following the literature), I have to calculate FST values using binary-encoded data with each allele considered as separate dominant locus (present 1 / absent 0). Again following the literature, calculating FST values based on these binary data should be possible using ARLEQUIN. However I have problems with my input file. I have used ARLEQUIN quite often to calculate pairwise FST values or do ANOVAS with "normal" microsatellte data or allele frequencies but I just do not know how an input file with binary data for microsatellites (or MHC) should look like??? Or is there a program that can be used to convert to binary data?
Does anybody have experience with this kind of analysis and can help me or would be willing to share an input file for ARLEQUIN so that I have an idea how this should look like?
Looking forward to your answers
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Hi Jasminca
Although previous answers are Ok. I thought you might need to understand the process of converting SSRs to binary data (although it is the same for your MCH loci, if you can not distinguish one from another)..
First, make a list of all your alleles for each locus. Then, the genotypes of your individuals will be 1 if they carry the allele, 0 otherwise. Thus, if your 1st locus has 10 alleles, you need 10 columns, etc. Note that you will end up with haplotype-like data.
For the MHC loci, consider all the bands in your gels and follow the same procedure
Hope this helps
Pablo
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I generated the distances from microsatelite data using GeneAlex and used the "export to MEGA" option to create a .MEG file. Now when i want to using this file to MEGA a number of errors have been coming up. The most persistent one is the " pairwise distances of atleast 3 taxa should be included in the file". I took it to our Lab and no solution yet. We tried converting it to a Nexus or phylip file but the same error persist. I have attached the file and distances generated in GeneAlex below. Thank guys
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May i know how was it solved??
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Repetitive elements are very prolific throughout the human genome (up to 60% of the HG). SNPs are annotated by their position, not by their flanking sequences. I would be very interested in finding SNPs that are located in conserved repetitive elements (e.g. pseudogenes) throughout the genome. Would there be a database which specialises in 'repetitive SNPs' as defined by their location in REs. I'm aware this could be done using the UCSC GB/Ensembl, but that wouldn't be as clear.
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Thought it may be a tricky one. Could it be speculated that distant SNPs with high linkage disequillibrium may lie in repetitive elements. Hard to figure out
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I'm using VarEff to calculate the Effective population size using the function NatSizeDist. 'It calculates the estimates of effective size (Ne)
at a number of times from 0 to a certain time ago (given by the user), plots and
saves results on files.' According to what I've read it seems that one should use the harmonic mean to determine the Ne, but my harmonic mean does not change between runs using different mutation rates (I'm using microsats). The mean, however, does fluctuate. Could someone perhaps tell me why this could be the case and could one use the mean instead ( the mean values make biological sense)?
Any help would be appreciated!
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Harmonic mean is often used to average speed or time, when data are heavily influenced by small values. But when a variable value is close to zero or zero, then harmonic mean can not be calculated. Harmonic mean also gives large values less weight, while gives small values greater weight than that given for the arithmetic mean. 
Check if there is any zero value on your Ne data affecting harmonic mean calculations. Biologically seems for me that Ne zero values shouldn't have sense.
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Hi,
Im doing a HUMARA assay to investigate X-chromosome inactivation. Right now the shorter allele has a great advantage in my PCR resulting in very different allele frequncies for my microsatellites in control patients that "should" have a 1:1 ratio between the two alleles. How can I make sure that the longer allele is amplified as good as the shorter one?
In other words, how can one optimize a PCR so that a longer allele is not less amplified then a shorter one.
These are my conditions at the moment in a 20ul reaction:
Buffer              2ul
dNTP 1μl of 2mM (0.1mM)
F and R primers 0.5μl of 1μM (25nM)
MgCl2 1μl of 25mM (1.25mM)
DNA               50ng/2ul
Taq                0.2ml of 5U/ml (0.05U/ml)
95° 5’, for 20 cycles (95° 20’’, 60-50° 30'’, 72° 30'’) and 25 cycles (95° 20’’, 55° 30'’, 72°).
Thanks!
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Hi all, Thank you for your answers.
Katie, what do you mean with including a different forward or reversed? That I should include an extra primer in my reaction or change on of the two? Why would this help? Thank you!
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I used Micro-checker to assess my microsat amplification. I have 17 localities, of which 5 have null alleles. The null alleles are, however, not only in 1 or 2 microsats, but vary according to the locality. Hence, I do not want to discard the microsats in question, but am not sure how to proceed. Do I use the adjusted genotypes calculated by Microchecker to change these localities, and if so, how do I know which new genotype corresponds to which sample number, as Microchecker states "Genotypes are ordered by allele size. Note: Row numbers do not correspond to the original sample numbers". 
Any help will be appreciated.
Regards
Genevieve
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What do you want to do with the genotypes? For parentage analysis, we do calculations using both scenarios: either the observed homozygotes are truly homozygous, or observed homozygotes are heterozygous null, and then take the conservative result for parentage. E.g. If one of these methods gives a match, then consider the genotypes matching (or if using likelihood methods, take the one with the higher likelihood). This is done for each trio or pair being compared.
If you are doing some sort of population genetics, then you might just need allele frequencies (which micro-checker gives?).
I can't sign off without putting a plug in for genotyping by sequencing (GBS) methods which we think are a much better approach, at least for species without SNP chips available.
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I need to analyze Microsatellite of C. albicans (CAI, CAIII, CDC3 and HIS3), C. glabrata (MTI, ERG3,GLM4 and GLM5), C. parapsilosis (CP1, CP4 and CP6) and C. tropicalis (URA3 and CT14).
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Hi Pablo and Ibrahim,
the machine is ABI, so I will try the GeneMapper.
Thank you so much!
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I am trying to multiplex pcrs for microsatellite analysis but it will take time to determine which combinations are best. In the meantime, I don't want to waste money on labeled primers that may not end up working well together (so that I may have to switch combinations and change the label dye, ordering new sets). Can I buy unlabeled primers and add the labels myself with each trial? How else do you test out multiplex combinations without having to change up dyes on the primers and ordering new ones? Thanks!
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You can buy a single, hexyne modified oligo and then click any azide modified dye onto a small portion of the oligo stock. If you want to go copper-free - since it has an effect on enzyme activity - you can order a DBCO-modified oligo.
If you buy a 5' amino-modified oligo, you can add dyes through NHS ester chemistry. However, the yields are much lower.
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I am planning a potential RADSeq project (my first one). I've heard from some people that RADSeq requires quality DNA samples (very high molecular weight, very clean, high concentration)- specifically that a column-based kit like Quiagen (etc) must be used. Others say that RADSeq can be performed using DNA from 'homemade' extraction procedures like CTAB/ chloroform (no columns).  There are various suggestions on clean-up as well.
Have you had experience with RADSeq and if yes, what DNA extraction method did you use? How quality was your DNA (what size on a gel, and what wavelength spectrometer reading). I am specifically interested in plant material or other tough material that is either degraded or full of secondary compounds. Any advice you have on this topic is much appreciated!
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We have done RAD-based libraries with samples which were extracted using PureGene, Qiagen, Phenol-chloroform... I don't think it really matters as long as you have pure DNA of a high molecular weight. You will also need fairly high yields as you will only recover a small proportion of fragments following size selection, and after ampure cleanup, which removes the very small fragments (usually we digest 1,000 ng and recover 10-30% after digest and ampure). Typically we use extractions with most fragments greater than several kb...
Another consideration is the purity of the DNA.. Many restriction enzymes are salt-inhibited, I have had some extractions which failed to digest.. This was easily fixed by purifying those samples (Ampure XP)- but this does create more work.
Degredation is an issue in that it decreases efficiency of shearing, but also in that highly fragmentary extractions decrease the probability of recovering homologous stretches of DNA across individuals... Additionally you would expect to generate on average smaller contigs... However I do not think that you necessarily need "super quality" DNA as I would think the method should be robust to moderate degredation.
What yields and quality do you expect from your extractions? Do you have some extracted sampled on-hand?
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Dears,
I'm trying to use the Samova software, but on the site there is only the example file to DNA sequence.
Someone would have a example file for multi loci microsatellite?
I tried to generate the file by GenAlEx but was not compatible.
Thank you!
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To run SAMOVA you need two files, one with microsatellite data, and another one with geographival positions of your populations studied. Please, see attached files. Order of populations in the geo file has to be the same like in the arp file. 
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I have a set of 10 SSRs primers designed to amplify Tamarix species. The primers were designed on T. ramosissima and successfully amplified its closely related species T. chinensis (attached is the paper). I am using the same markers to genotype the same species with an additional one plus hybrids but i am getting picks that are falling outside of the expected range (published ranges) and there is no consistency in picks within and among species. 
I can't find any good explanation for that. May you please provide some advice on what i can do about this problem.
Your help will be of paramount importance to my research.
Kind Regards
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First what I'd do is to sequence the PCR products, to see if they really contain microsatellites or if it's perhaps some unspecific amplification.
Then in another species, the microsatellite loci might have a different size, this would at least explain differences between species but not within the species. To tackle this last point, you should try several replicate genotypings with one individual (or a few) to see if you can replicate the results (sizes) with always the same template or not. 
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I want to test the coalescent theory for a dataset of microssatelite and cyb B genes. Does anyone know the best software that works in windows? 
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Try MIGRATE, DYABC, IMa, PopABC
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Is there any specific format for the input data?
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You can use the software "Network" (http://www.fluxus-engineering.com/sharenet.htm ) as referenced by Artur. However, Network is designed for non-recombing molecules such as plastid DNA sequence data. You can code microsatellite data to be binary, but that is artificial when dealing with heterzygotes.
I would recommend using EDENetworks (http://becs.aalto.fi/edenetworks/). I generates networks based on various measures of genetic distance at the individual or population level and easily accepts microsatellite 
An additional option is that you can use SplitsTree (http://www.splitstree.org). With splits tree you would need to generate a matrix of pairwise genetic distances using a basic genetic program and then input that as your data file.
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We are evaluating to buy "Bioptic Qsep 100 Fragment Analyser" to microsatellite analysis. If anybody did use or know about something it, could you share wit us.
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Hello,
This is Dr. Priyanka from QTLomics technologies Pvt. Ltd. We are using "Bioptic Qsep 100 Fragment Analyser" . We have done some SSR projects on it and have successfully completed it.
If you need to know more about our experience, kindly contact me on priyanka.v@qtlomics.com (Dr. Priyanka Verma, Scientist) or krishnaprasad.s@qtlomics.com (Dr. Krishna Prasad, COO)
With Regards
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I'm working with a set of microsatellite markers, and the high number of polymorphisms result in artificially low ɸst values. I calculated G"st and Rst using GenAlEx, and I want to compare these against ɸ'st. From what I can tell GenAlEx has support for ɸst, but not ɸ'st.
Are there more recent programs that support ɸ'st?
Alternately, is there a way to calculate ɸmax in GenAlEx?
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Hello Anthony,
I am also using the ARLEQUIN software and it has the ɸ'st feature. You can explore other options and it is easy to navigate.
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Iam upto doing the microsatellite analysis in my research. can we visualize microsatellite bands using ordinary AGE/PAGE? Is  capillary electrophoresis essential?
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Thank you for the answers. I will make a try.
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Can we make a tree using allele frequency based genetic distance data obtained through microsatellite analysis? Which will be the best software?
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Thank you Øystein Lofthus for giving useful information.
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We plan to extract DNA from a butterfly (Maculinea alcon) egg for microsatellite analysis. The egg is too small to separate the eggshell from the tiny caterpillar inside of it. Does the eggshell contains maternal DNA and should we expect amplification of maternal alleles beside the alleles of the caterpillar?
For some insects, genome rearrangements occur during development. Is there also evidence for genome rearrangements during the developmental stages of butterflies?
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An Vanden Broeck,
It is possible that the chorion in lepidopterans would have some small amount of residual maternal DNA from fragments of adhering follicle cells, as these to remain in close juxtaposition as the chorion is produced.  The paper I've noted below is on a trichopteran, which is closely related to the Lepidoptera and has very similar egg chamber structure and development.  Please note in the electron micrographs the external location of the follicle cells, which are entirely of maternal (rather than post-meiotic germinal) origin.
Good luck with your work!
Bruce
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Hello. everyone! I want to design some SSR markers based on the genome released on the internet. How should I do?  I designed some markers with the software SSR Locators, but when I check the SSR markers, I found that there are some markers like: (ATAGAC)xAx ,(AT)x- (AT)and  (ATAGAC)x-(TTATGC)x. I want to know whether the SSR marker above are suitable to be used in the experiment or not. Thank you!!
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Absolutely yes. In my experience a compound repeat is no more (or less) likely to be polymorphic than a simple repeat. Primer design, annealing specificity and amplification conditions are far more important in designing good quality SSR markers than repeat type. Even then it may be monomorphic in your population, that point you can't predict or control. 
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I am checking the genetic stability of my isolated stem cells and I am using a genetic analyzer to detect any MSI. I am using five microsatellite markers; two mononucleotide repeats (BAT25,BAT26) and three dinucleotide repeats (D5S346,D2S123, and  D17S250).
I need to know the exact procedures, from extracting DNA from cells to getting the PCR product that can be sequenced.
Thank you in advance.
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Dear Vladimir,
Thank you so much for the useful link
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My mtDNA analyses supports 2 clades while the microsatellite analysis support 3 clades, one being non-monophyletic in regard to mtDNA. Can the third clade be resulting from introgression and back-crossing?
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What kind of analysis was done on the microsatellites? Which criteria are used to define the number of clades? Without this information it is difficult to interpret this supposed discordance.
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I'm studying the population genetics of an intestinal nematode (raccoon roundworm) using microsatellites.  An analysis using GenePop shows significant LD in 20 out of 28 possible comparisons between loci (!).  Is this a reflection of how highly partitioned the worm populations are between hosts, or an indication that the loci are somehow problematic vis-a-vis making population genetic inferences?
More broadly, what does finding (or not finding) LD tell us in the context of a PopGen analysis?  Seems like checking for LD is almost a ritual feature in the MM of articles, but I'm unclear on its purpose.  As a newcomer to the field, any insights would be welcomed.  --Thanks
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LD results from a non-random association among alleles at 2 or more loci. This may be a result of physical linkage: the alleles are on the same chromosome, perhaps very close together, or in some cases, 2 loci considered to be different are actually the same (b/c two differing primer sets were constructed that amplify the same locus). Assuming physical linkage is not the cause, LD can arise through drift, selection, and/or gene flow. Popgen programs like STRUCTURE assume that data is in Linkage equilibrium, and loci that are in LD can lead to the program overstating popgen structure. See: http://www.nature.com/hdy/journal/v99/n4/full/6801010a.html
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I am trying to amplify seven SSR loci, that I used to genotype my study species individuals, in 2 out-group species (within same genus and within same family). I am getting amplification for 2 loci in individuals belonging to the same family using the same protocol that I optimize before but other 5 loci are not amplifying. Also, no loci amplified in individuals belonging to the same genus. DNA concentration for out-group individuals within the same genus = 5ng/ul and within same family = 3 ng/ul. I would appreciate it if anyone could suggest anything about this problem.
Note: I have already tried touchdown PCR annealing temperature variable
Thanks
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It is possible that you still need to do some adjustment of the PCR conditions for samples that do not amplify. You should try to move/change each componenet of your PCR. You should try to change e.g. amount of template DNA, number of cycles, amount of polymerase, try also different polymerases and so on. If you will not notice any improvement, then it is probable that you have „null alleles“ in those species for those loci. It is possible that there is a mutation on the primer-site region (one or more nucleotides are changed and the primers are not perfectly complementary to DNA strands). Than the PCR is not successful. If this is your case, you will not get the products from those loci. Or, you can try to design new primers with several degenerate nucleotides at different position.
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What is the difference between major and minor satellite in human? Do either of them contain alpha-satellite DNA? Do they form distinct domains?
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If I remember it correctly, the minor and major satellite are the DNA sequence in mouse centromere and peri-centromere. However human centromere mainly comprises of high order structural alpha satellite as well as the peri-centromere is constitute of monomer alpha satellite and other classical satellite, for instance satellite 2 and 3. Besides, the alpha satellite is primate specific, which means the mouse doesn't have this satellite in centromere. In sequence level, the most closed repeat element to major satellite is GSAT or what ? I forgot it. But thinking of the role in centromere formation and the functional relevance, the alpha satellite is very similar to minor satellite, which containing a CENPA chromatin and is responsible for kinetochore assembly.  
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My data revealed a non-significant but high negative correlation between the FST and geographic distance using microsatellites in Anopheles population. Should I consider it as no correlation? 
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Dear Arvind: That is the purpose of significance tests. Significance depends not only on the correlation values, but on the number of samples etc. Anyhow, if the test is non-significant, you can not assume there is correlation.
Hope this helps
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Hey all,
I was wondering if any of you could provide some insight as to why my bands are not separating on Metaphor agarose. I have successfully separated bands using the same primers/DNA/gel before but now it has stopped working and I cannot figure out why... Ideas?
Thanks
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If your materials are the same, check your work steps again(including instruments).
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I would like to have an alternative for AppliedBiosystems microsatellite fragment analysis (genotyping) software GeneMapper as I want to be able to work at home. What would be your suggestions for a free downloadable alternative or demo version for at least 30 days? Peak Scanner doesn't have genotyping function so I don't like it at all as I work with polyploids.
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Dear Asta,
  I highly recommend Geneious http://geneious.com/  It has a free 30 day trial, and the microsatellite plug-in is fantastic.  I have used it for all of my microsatellite analyses and have been very happy with it.  Please feel free to e-mail me if you run into any problems, and I'll do my best to help you.
Jeremy
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I have frozen vials of HEK 293T cells. Before using it in my experiments, I want to characterize it. Normally we can go for STR analysis but I want to do something less expensive yet standard such as PCR markers for HEK 293T cells or IHC for markers.  
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293T cells contain the SV40 T-antigen, so you can probably have some level of confirmation based on that by PCR.
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It has been suggested to me that microsatellite data collected on so-called ´manual´ polyacrylamide gels - with silver-staining - is generally not acceptable to the majority of journals now. We have a couple of projects starting up on limited budgets, and are thinking of using manual gels. Surely if the data are collected in a controlled and systematic manner, a MS cannot be rejected solely based on detection technique. What experiences have others had?
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I have used silver staining and also SybrGold to stain my PAGE gels. The SybrGold was far more efficient and sensitive, without the mess and time of silver staining, and without worrying about over exposure. We simply added 1ul of SybrGold to 10ml of ddH2O, spread this over the gel and left it in darkness for around 30mins. The tricky part is visualizing, and depending on your GelDoc this could get really fiddly... let me know if you want details! (if you have the money you could just buy non-UV absorbing glass for your plates and then this step becomes a lot easier)
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I have performed a test to identify microsatellite loci as possible candidates to selection. I have analysed 11 loci on 6 population and following the LnRH test (Kauer et al., 2003; Genetics, 165: 1137-1148) I was able to define LnRH values on 15 pairwise comparisons.
I know that 99% loci under neutrality should have LnRH values between -2.58 and +2.58. Now, I have to define more stringent thresholds and I would like to calculate on the basis of my 15 pairwise comparisons, the false discovery rate ( Benjamini & Yekutieli, 2001;The Annals of Statistics, 29: 1165-1188) and the Bonferroni correction values. Can anyone help me with this computation?
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Ok, I will follow your suggestion and I will forward my question about the false discovery rate correction to Dr Lertola. Thank you again!
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I need to get samples from tree stumps and was wondering which part of the stump (bark, core wood,...) is likely to get me some extractable DNA for microsatellite screening? Also are there any extraction protocols that seem to work particularly well for wood?
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In have an article with wood DNA isolation: Brezna et al. A novel real-time polymerase chain reaction (PCR) method for the detection of walnuts in food. European Food Research and Technology 2006, 223(3):373-377. I worked with small branches of wood (that is a combination of thin bark and core wood, I guess ?) and also with nut-shells. Samples were ground to a fine powder using emery (rasp paper). DNA was isolated with GeneSpin kit (GeneScan, Freiburg, Germany), which is today sold under different name Nucleospin Food Kit (Macherey Nagel). Food kits must handle a lot of terrible materials, because food is often loaded with inhibitors, so I hoped, the kit would work on wood as well. It worked for us, but we needed only short amplicons to amplify (under 100 bp).
You can see my article here:
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My colleagues and I had a disscusion about this case. They say, that this peak is not countable as an allele. The problem is that it is present in majority of an individuals, which are polyploid. Should I ignore this peak or count as real allele?
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Beautiful peak to me;)
Did you run a negative control (no DNA)? You could discard it If you find the same peak in the negative control...
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My lab just finished gathering the phylogenetic microsatellite data on several populations of a plant species. After a quick and dirty initial analysis with GenAlex, we found six alleles across all the populations showing high mean heterozygosity and low mean Fis (negative values). The seventh allele is showing exactly the opposite with 100% homozygosity in every individual and population. I am just curious if anyone has ever come across this phenomenon before and what a reasonable genetic explanation may be for this fixation. Since we are speaking about microsatellite markers, I do not expect selection and genetic fixation of an allele at all, let alone across every population examined.
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I am guessing you mean 7 loci and not alleles. For the locus that is 100 percent homozygous, is it fixed for the same repeat in all populations? If so, that just means it is not variable and therefore doesn't provide any information.
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I am interested in the use of microsatellites and how they're used to identify a species. Especially if you have a population of an indeterminate species and would like to compare it with two possible options of nearby populations.
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I agree with Karl. Bayesian statistic is a good choice (Structure, Genland or BAPS), you can perform admixture analyses or population grouping/subdivision. These methods were for ex. sucesfully used in a wide ranging and diverse species of turtles. You need of course a database for populations you want to compare. Standard procedure is to complement microsatellite analyses with mtDNA analysis, I mean a species specific mtDNA region.
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I am involved in a microsatellite project as part of an integrative taxonomy study of multiple plant species. We originally developed the primers from three species but are now using 15 of the microsat markers across all six species, with multiple populations and subspecies. As one might expect, not all primers work for each species. Consequently, the fact that a primer does not work in a species is informative for us and we would like to somehow include that information in the analysis. In other words, there are cases in which data are missing for a species for an entire marker, not because the samples did not work per se (or because of a scoring error), but because a primer annealing site may have mutated for that particular group of samples. We have been working with programs like GDA, GenAlEx, etc. but do not wish to interpolate or ignore the missing data, but treat it as useful in analyses such as genetic distances and PCA. We have yet to use Bayesian programs such as structure. Any other ideas out there?
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I am a little bit late, but if it can help....
When you are sure that your sequence is not amplified because the target is not present or mutated (and it is not a failed PCR) you can use the allele size "0" which is considered as an allele by most software. It will allow defining a frequency for this allele in your population and thus use the info for the genetic distance calculation. However, you will not be able to discriminate the different "0" alleles, meaning that many different events can cause this no amplification from deletion of the locus to mutation in the primer binding sites.