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Conservation Genetics - Science topic

Conservation genetics is an interdisciplinary science that aims to apply genetic methods to the conservation and restoration of biodiversity. Researchers involved in conservation genetics come from a variety of fields including population genetics, molecular ecology, biology, evolutionary biology, and systematics. Genetic diversity is one of the three fundamental levels of biodiversity, so it is directly important in conservation of biodiversity, though genetic factors are also important in the conservation of species and ecosystem diversity. Conservation of genetic variability is important to the overall health of populations because decreased genetic variability leads to increased levels of inbreeding, and reduced fitness.
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According to PowerMarker V3.0 manual, this software has been specifically designed to analyze SSR and SNP data. However, by literature review we find some publications on ISSR markers that used PowerMarker for data analysis. I would be grateful if you could kindly upload a sample input file of 0/1 data for this software.
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Please find attached
Best wishes
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I recently became aware of a published proposal to reintroduce African cheetahs in India by US scientists.
Apart from scientific considerations - I have much to disagree on this proposal - my question is: should it be proposed if the last Asiatic cheetahs lived in Israel or Jordan rather than in Iran, as it is the case? I believe that global organizations should try to support local and national conservation initiatives, not totally disvalue work in Iran that is really critical for the conservation of Asiatic cheetah.
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Dear colleagues,
I calculated an AMOVA using Arlequin (10.000 bt) on a microsatellite dataset (12 sats). There are 4 more or less differentiated subpopulations. The data is fine, I did vast checks and a lot of other analyses.
In my AMOVA however, I end up with the following percentage of variance explained:
Among subpops: 1.69 (significant)
Among inds within subpop: -2.43 (not significant)
Within inds: 100.73 (not significant)
I realise this is a strong indicator for good admixture, and no real subpop strcuture. Yet I am a little confused about the negative value:
  • Is this totally fine, an artefact of computation?
  • Or does it indicate some problems with the AMOVA?
Thank you for your help!
EDIT: formatting
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In this instance, The AMOVA percentage of variance can be explained as:
Among subpops: 1.69 (significant)
This seems Ok.
Among inds within subpop: -2.43 (not significant)
Negative valuesare taken as zero.
Within inds: 100.73 (not significant)
More than 100 , is explained as: as sum of all 3 above values is 100, and as among inds within subpop: -2.43 is taken as zero, so
Within inds is (100- 1.69) 98.31.
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Root exudates
Dear All:
Have you ever measured root exudates to soil?
Would you please mention some techniques?
Thanks in advance, with the best regards,
José
Dr. José Carlos Lorenzo Feijoo
Head, Lab for Plant Breeding and Conservation of Genetic Resources,
Bioplant Centre, University of Ciego de Avila, 69450, Cuba.
Tel. 53 33 225768/212719 www.bioplantas.cu
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Yes I have measured root exudates. In solution culture, but the roots did exude phytosiderophores and we could measure them by HPLC after derivatizing them. https://www.researchgate.net/publication/11538514_Reversed-phase_liquid_chromatographic_determination_of_phytometallophores_from_Strategy_II_Fe-uptake_species_by_9-fluorenylmethyl_chloroformate_fluorescence
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My colleagues and I are investigating the population structure of ruffed lemurs throughout their known distribution. We've already run both a structure analysis and a principal coordinate analysis & it's looking like we've got K=2 populations/genetic clusters. Based on these analyses, it seems as though a large river is likely acting as a dispersal barrier; however, we'd like to be able to test this hypothesis. We've tried SAMOVA and Geneland, but have been unable to get the dataset formatted appropriately (or some other issue -- hard to tell, but we can't get either of the programs working). Can anybody help?! Example input files and/or suggestions for appropriate tests would be extremely helpful! We've got two weeks before the revision is due!
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In addition to the software that you already commented you can use Barrier.
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Has anyone run into a problem with micro checker? I have loaded one genepop data set micro checker and it was successfully loaded. But when I try to load another genepop file that has much more data, micro checker refuses to load, despite the fact that this second file run successfully in genepop.
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This is old, but since I have helped people with the same problem several times already I'm going to leave my answer here. Rohit's answer works because the problem is usually with the line endings and/or other unseen editing options in the file. Always edit such files in proper programming editing tools, such as Komodo Edit, and, with Micro-checker, beware when using other operational systems such as Linux or OSX to edit files, micro-checker only reads files with Windows line endings. So if you edited the files in linux or someone sent you files and you are using their files check in the file preferences whether the line endings are Unix line endings or the Windows line endings. I haven't encountered the same problem in other population genetics tools, however, similar effects can happen with the tab. Some input files have to have all tabs removed and replaced for spaces. Good luck to everyone reading this.
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I'm trying an analysis on HIERFSTAT for the first time using a subset of my data. I have some formatting issue that I can not put my finger on because when attempting to run basic.stats and other analyses I get the message
Error in dimnames(x) <- dn :
length of 'dimnames' [1] not equal to array extent
To get a feel for the program I'm only using a subset of my data for now (one locus). Can anyone advise? I added the file I'm trying to use.
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I figured out getting the data format accepted now sorting through the results of boot.ppfst and the $vc.per.loc tables.
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I analysed my samples for isolation-by-distance using a mantel test in Adegenet package. I am not sure if the histogram below shows that my samples has a clear isolation by distance pattern.
Below is the summary of result from the adegenet.
Summary of results
Monte-Carlo test
Call: mantel.randtest(m1 = Dgen, m2 = Dgeo)
Observation: 0.1486482
Based on 999 replicates
Simulated p-value: 0.009
Alternative hypothesis: greater
Std.Obs: 3.3053629175
Expectation: 0.0009153189
Variance: 0.0019976358
Also, for the second plot I am not really sure if it is a normal result and I am a bit confused how to interpret it. I hope anyone can help me interpret these plots.
Thank you so much.
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I'd like to add a word of caution here. To test whether there is isolation by distance, you need several data points along a geographical range (either several populations or individuals at a range of distances). Because you are testing only two populations, you cannot infer there is a pattern of isolation by distance--your regression line is just connecting the two populations.
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I've been out of the game for a few years and I have a lot to catch up on. I'm working on a wild animal population that is currently crashing (>60% decline over the past two decades). Given the situation, is it appropriate to use a program like Bottleneck to look for previous reductions in the effective population size? Or will the current situation mask previous events? Have there been recent developments in detecting these patterns that I should be aware of? Thank you for your time. :)
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It will depend on how much genetic variation is left in the extant population. If there are several isolated populations left, you might have a chance, but if there is just one small population remaining, probably not.
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I am aware of the pedigree and kinship2 libraries in R, but functionality is limited. Programs like EASYPOP can save pedigree information but are not focused on simulation of pedigree parameters specifically. I am interested in looking at e.g. the impact of founder inbreeding levels (usually assumed to be zero) on kinship estimates in subsequent generations.
I am just asking before trying to do something from scratch. :)
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Use Vortex. You can use your pmx files as input and also provide microsatellite data. We did some simulations assuming different founder assumtions. Worked quite well.
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So far we’ve been doing microsatellite analyses with a capillary sequencer. The machine is getting old and we need to replace it. Since we’re regularly using MiSeq or HiSeq for other approaches (DNA metabarcoding, Rad-seq, Genotyping By sequencing, …), it seems logical to us to switch completely to a high throughput sequencing platform.
We do work a lot on protected and endangered species, often small critters, as a result of which our DNA-sampling needs to be non-lethal and minimally invasive. This means we often have low quantity and low quality DNA.
RAD-sequencing or other reduced representation genome sequencing is often not possible on these types of samples. I am aware of SNP-methods requiring low amounts of DNA (Fluidigm chips for example), but this still requires other hardware.
Microsatellite genotyping is still very useful to us because the information content per locus is about ten times higher than with SNPs. For a lot of our purposes, we don’t need more than 25 microsatellite loci to get the information we need, and with the small amounts of DNA we have at our disposal this works fine.
I’m looking for people who directly sequence microsat loci via high throughput sequencing, and would like to know their first-hand experiences on feasibility, bottlenecks, bio-informatic pipelines, do’s and don’ts.
thanks
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Hello,
yes, you can do genotyping with Miseq, as you can see here.
Also read about the use of Illumina in forensics (Illumina offical website), I found it very useful to see what can be done with low quality human DNA, I guess it should work with any DNA and the rigth PCR primers.
Best, Meta
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A fundamental problem with the effective conservation of (plant) genetic resources is that their natural distribution does in most cases not follow administrative and political borders, they might follow geographical borders, at best. For the development of effective conservation strategies and for the subsequent monitoring procedures we ideally should have a good oversight over and understanding of the distribution of the genetic diversity of the genepool in question and this would require a close collaboration with those countries that are part of the distribution area. Unfortunately, such close collaboration is frequently hindered by political an other constraints. Thus, the question is how we would still be able to develop sound conservation strategies, to implement these and to conduct any monitoring activities in cases collaboration with the identified countries is limited or not existing?
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You’ve identified an urgent problem for virtually all species that aren’t local endemics, and it’s particularly important for agricultural species where the stakes are high for conserving native genetic biodiversity. Fortunately, many of the core elements of conservation strategies are broadly similar across species, and scientific communities within individual countries aren’t necessarily limited by political ideologies or borders. There are good examples of scientific collaboration and exchanges between countries with conflicting ideologies or frosty relations: examples include collaborations between American and Soviet scientific communities on paleontology, fisheries, and climate-related research during the Cold War.
Developing sound conservation strategies is possible as a joint or collaborative scientific endeavor – implementation and/or monitoring programs will likely be much more challenging, but should still be feasible if a reasonable case can be made for a country’s self-interest. In some cases, being able to show the biological value of a country’s biotic resources has been useful for international negotiations, such as Equador’s proposal in 2007 to not develop oil reserves in Yasuni National Park in order to protect the rich local biodiversity, in return for funding from the international community. Even though it didn’t pan out in the end, the recognized value of the local biodiversity was a key driver for the idea. Getting a monitoring program up and running may at first be limited to local efforts through the scientific community, but as their value becomes apparent, larger-scale collaborative efforts are possible. A good example of this is the decline of American eel (Anguilla rostrata) across the species range – observations by scientists, published in the literature and communicated to jurisdictional management agencies, led to a collaborative effort across the species range to try to slow and (hopefully) reverse the species’ decline.
An important facet for building multijurisdictional collaboration is establishing a core set of shared data metrics, preferably collected using agreed-on / standardized sampling methodologies. With that, each study’s (or jurisdiction’s) data can be compiled to build a comprehensive picture from the individual pieces. If you’re looking at genetic biodiversity, there are several good examples in the fisheries literature, especially for Pacific salmon in North America and Russia and the multinational FishPopTrace consortium in Europe.
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Hello everyone,
I would like to use the coancestry-based method to assess some population contributions to overall genetic diversity, as developed by Caballero & Toro (Conservation Genetics 3: 289–299, 2002) and implemented in the software MolKin by Guttiérez (Journal of Heredity 96, Issue 6, 2005)
The only problem is that MolKin only runs under Windows 95/98/200/TN/XP. Before loading a virtual machine to make it work, I was wondering if you would know about another soft or, even better, a R package that would help to implement the Caballero & Toro approach? I don't feel quite confident yet to implement this on my own... better check!
Thank you all and a great year 2018,
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My pressure Chrystelle, good luck with that!
Gregoire, its why I strongly recommend to use R for it, because you just need to add the equations (maybe is a little hard to do, but you'll do it just once) and then run any data set without problem. But of course, the other way (like in a lot of softwares) is to switch to WinXP.
Best!
Alex.
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Considering the fact that crops and their traditional varieties and landraces are widely spread and in most cases do not follow national boundaries it is a given that effective and efficient conservation can only be done through collaboration with neighboring countries. The same applies to the conservation of entire genepools, they typically are widely distributed across farmers' fields, disturbed and natural habitats. Thus, there is a need to involve nature conservationists, genebank curators, botanic gardens, NGOS and farmers that aim at the conservation of genetic resources in farmers' fields, scientists. policy-makers and others to achieve effective approaches. Therefore, networking among all those involved and/or that should be involved seems to be essential to make the efforts sustainable and long-lasting. same applies to the involvement of all stakeholders in the conservation activities, they should have a say in the planning and implementation of the conservation operations.
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Thank you Jacob, very good comments and additions indeed! Herewith a few reflections on your points.
I certainly would agree that a global fund, through whatever sources filled, would be sufficient to ensure adequate conservation and presence of sufficient genetic diversity in the production systems. We will need other approaches such as the ones you suggested, but possibly also political frameworks that allow that to happen! And indeed, global public goods are different from local resources, in many respects (other than the biological dimension). Both will require proper support and stimuli.
Your point about 'linking conservation with local identity, ownership and economic opportunities' is indeed a critical one and is of crucial importance to ensure sustainable conservation approaches and to ensure the required links between 'development' and genetic resources. Consequently, proper representation of the community and consumer level stakeholder groups in any national/governmental conservation efforts and in national, regional or global conservation and use networks seems to be indispensable. Conserving genetic diversity is also conserving and respecting cultural diversity, stakeholders' identity and accepting their traditions and certainly their interests.
Your point on the importance of information and communication is indeed a key aspect to allow and facilitate efficient conservation and use, in particular through the sharing of experiences, knowledge and linking initiatives and players as well as to allow proper linking of the resources with its users. The provision of adequate tools and means to the communities, rural and urban, would allow these opportunities to be used, including to facilitate the needed exchange of knowledge and experiences gained through 'citizen science'.
Yes, we need more possibly a rethink too on how to create more flexible and certainly more dynamic formal and informal networks. Too heavy handed and top-down functioning networks are not the solution and are also not sustainable. Allowing indeed the 'power' over planning and decision-making to the lowest possible level in the society is a key prerequisite. Facilitating rather than dominating is another aspect that is crucial to allow the creation of dynamic, inclusive and open PGRFA (and other) networks!
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While calculating the evolutionary divergence as computing pairwise distance, (using p-distance methods and Maximum Composite Likelihood model), the values ranged between 0.002-0.138 (p-distance) and 0.001-0.109 (ML) for between individuals of the same species, and for different species. I have got these value as distance matrix table using MEGA 7 software by inserting the nucleotide sequence of COI gene of 661 bp length. Can somebody tell me what are the actual threshold values of the evolutionary divergence calculated by the above said methods to delimit the distinct species? I mean at which values of these distances we would say that these two species/individuals are of distinct species?
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I would emphasize even more strongly than the previous respondents that speciation is a process where subpopulations establish their own independent evolutionary trajectories, and any notion of a threshold difference is only a rough approximation at best.  As an example, back in the '90s I was doing a postdoc where I was sequencing mtDNA of macaque monkeys.  At that time we discovered that rhesus monkeys had major haplotypes differing by about 3%.  A very well known evolutionary biologist from the American Museum of Natural History assured me that we had made a mistake because the threshold for species elimination was 1% for mtDNA.  Since then a different species of macaque has been found to contain mtDNA sequences that differ by about 9%.  Macaques have relatively extreme female philopatry, which explains this unusual observation, but it highlights the folly of assuming an arbitrary threshold of difference.
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Hello,
I´m including P. orbignyi in a population analysis for conservation genetic study. In GenBank are a few sequences; but, into them, there is not any sequence from Brazil, where was originally described the distribution of this stingray. And it is important in order to used as a start or reference point f genetic analysis. 
Thanks!!
Angelica
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Andrey, thanks so much! I'm using them...
I´m looking for Tocantins sequences where were described the Holotype
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Hello, 
I'm using  dominant genetic markers to measure genetic differentiation among populations and genetic diversity within populations. Since I'm using dominant markers, I had to calculate allelic frequencies using a bayesian method (Zhivotovsky 1999). There are a lot of measures In the literature (eg. FST; F'ST; GST; G'ST; PhiST; Phi'ST; D) and I want to know which must I choose. I want compare my results with published works with similar species too.
Thank you
P.S. Sorry for my bad english
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Hi João 
Thank you for the paper. I sen you two papers with regard to genetic differentiation which may be helpful.
Good Luck
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I am studying two insular populations of an amphibian species. These insular populations are located in continental islands, which got separated from the mainland following the sea level rise during the Holocene (approximately at 8-10 kya).
I am using an ABC framework to test which demographic scenarios are most supported. Broadly, I am testing two competing scenarios; (1) a scenario of genetic isolation following sea level rise (i.e. vicariance). This scenario implies that these populations already inhabited these islands before their formation due to sea level rise; and (2) a posteriori colonization of these islands from the mainland by few individuals. I am assessing this in DIYABC 2.1 with microsatellite data.
However, I am also interested in testing a third scenario: (3) vicariance but continuous gene flow from the mainland after the formation of islands. DIYABC does not mode explicitly model gene flow, although admixture events can be created. The issue with these admixture events is that they require the creation of an additional population resultant from the admixture of two existing populations. 
To better illustrate what I want to model, please find attached a pdf representing, in a simplistic way, the demographic scenarios. Consider the insular populations N1 and N2 and the mainland population N3. There are three scenarios represented, but the scenario "Vicariance + gene flow" is the one that I cannot include in DIYABC. In the figure I just represented gene flow from mainland (N3) to one insular population (N2).
Do you know if there is a clever way to model this in DIYABC? If not, which software do you recommend to accomplish this using microsatellite data? 
Thank you very much for your help.
Best,
André
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I use Hudson's ms and R for ABC analysis. You can modify some code I have made available at: http://github.com/mnavascues/microsatABC-IM
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I am working on microsatellite data of two endemic amphibians from western ghats
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@Shafagat Mahmudova: thanks a lot 
@ Rosalia Pineiro: I am not able to open the TESS page from github. Thanks anyways
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Is there anyone who knows a program to estimate the new measures of genetic differentiation described in Jost 2008, Hedrick 2005 and Meirmans et al (2011) (or standardized genetic differentiation measures) for DNA sequence data (mitochondrial or nuclear sequences)?
Hedrick 2005 proposes a new standardized method of comparing the indices of population subdivision when we are using different molecular markers (reviewed by Meirmans et al. 2011 for AMOVAs). In this standardized genetic differentiation measure, the magnitude of its value is the proportion of the maximum differentiation possible for the level of subpopulation homozygosity observed. Perceptibly, when using highly polymorphic markers that make the level of homozygosity low, then the maximum GST value must also be greatly reduced. Mainly care must be taken when we are comparing population differentiation indexes using different markers like microsatellites and SNPs, for instance (i.e. highly variable markers). However, I have not found any program that works on sequence data (e.g. mitochondrial DNA).
As was suggested by Meirmans et al. (2011), sequence data are of a different nature than allelic data as they contain information on the evolutionary relationships between haplotypes, and these population differentiation indexes do not take this information into account so their calculation is difficult for sequence data. I think, programs for calculating these parameters (GenoDive, SMOGD, SPADE, RecodeData) cannot be used to calculate these new measures of genetic differentiation for sequence data.
Briefly, is there any researcher who has estimated these indices from DNA sequences using these or other programs? Have you proceeded in any particular way?
Thanks so much
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You are mixing together several different concepts in these papers.  
Jost (2008) claimed that Fst was a useless or perhaps misleading measure of genetic differentiation, a paper that initially caused quite a stir.  Jost was not clear about core assumptions such as biallelelic loci and also fundamentally misunderstood the role of a model of population arrangement such as the finite island model imbedded in Gst.  See the paper by Ryman and Leimar 2009. 
Hedrick 2005 presented the idea that the maximum Gst (or more properly an estimate of the parameter Fst) is a function of allele frequency distribution and may not be 1.0 such as when heterozygosity is very high.  Using a well worn approach (e.g. the standardized coefficient of linkage disequilibrium, D'), he suggested Gst' to standardize an estimate of Gst by its maximum value so that it can be interpreted as a percentage of the maximum.  This approach can be taken with pretty much any statistic where one can compute the maximum value for a given data set.
Sequence data and allelic data are different in some ways, but they can be thought of as a collection of multiple loci if the sites are independent.  At the other extreme, they are a collection of many completely non-independent sites and therefore constitute a single locus.  Both allelic data and sequence data can be treated similarly from a conceptual point of view, but data type usually differ in the types of statistical estimators are used to obtain an estimate of a certain quantity.
What is your main hypothesis of interest? Start there and then ask what types of statistics would provide quantities related to testing that hypotheses. The last thing to think about is the implementation (i.e. software) you need to estimate the statistic of interest. 
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When I try to collect the earthworm specimens in each spot, I found it's really hard to get enough objective samples in some plots, maybe 1 or 2 or 3 specimens in a plot. However, limited specimens mean pretty limited genetic variation, and actually, the number of samples has a strong relationship with genetic diversity.
Could somebody tell me something about your experience?
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I think there is not an "absolute number" however in a simulation it was shown that after 20 specimen heterozygosity does not change much. (doi:10.1371/journal.pone.0045170).
Perhaps it is true for earthworms as well.
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I use 15 specimens from 3 different islands separated by the sea using 17 microsatellite loci. If I can not use the data to assess the genetic diversity, then what can I discuss from data?
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Hi Dragos,
The attached file help me much. Thank you....
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which one is batter 16s/18s rdna or any other....
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Emilio Rolán-Alvarez has given the perfect answer. Additionally though, there are several drawbacks associated with the use of mtDNA in phylogenetic studies which nuclear loci do not suffer from. The following two papers would be a good start to get an overview of these:
Balloux, F., 2010. The worm in the fruit of the mitochondrial DNA tree. Heredity 104, 419-420.
Galtier, N., Nabholz, B., Glemin, S., Hurst, G.D., 2009. Mitochondrial DNA as a marker of molecular diversity: a reappraisal. Molecular Ecology 18, 4541-4550.
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I did RAPD method of one sample. I used 10 primer for that. now I have one image of that result, how can I calculate and interpret result using polymorphism phylogenetic mapping? is there any software?
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@Vivek Vaishnav
You provided a beautiful art work.  Although the density-unweighted algorithms that you aforementioned have been wildly recogniced and used in population genetic studies, these algorithms may not be suitable in many cases of RAPD studies.  There are two specific computational biology prerequisites for use of the density-unweighted algorithms in the studies such as RAPD: (a) all matched DNA pairs in the electrophoretic lanes being compared must have essentially the same densities, as illustrated in the book provided; and (b) all DNA amplicons must be well separated from the adjacent DNA moieties with similar molecular weights and conformations by electrophoresis.  
Ni et al. 2014 (Am J BioMed Sci, 2014, 6(2): 82-104) devolupped the density-weighted algoritms, which is mathematically general with no specific prerequisites and governs all conditions, in contrast to the density-unweighted algorithms that narrow the specific cases under the strict prerequisites (a) and (b) described above.  
Best,
Josh
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I am doing research on Alpine Musk Deer  (Moschus chrysogaster) from Nepal to study genetic diversity and individual identification (later is for latrine site use). I tried to find out the microsatellite markers this for a particular species (Moschus chrysaster) but could do so. However, I have found 15 novel microsatellite markers developed for Forest musk deer (Moschus berezovoskii). Now, I would like to know possibilities of Microsatellite Marker of Moschus berezovoskii for Moschus chrysogaster.
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Hi Paras
You should be aware that cross-species SSRs many times have null alleles, and might suffer other amplification problems.
If you insist to use them, be sure to check the efficiency of your RT-PCR before going on.
Hope this helps
Pablo
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We had already started a research, based on landscape genetics for a resistance animal species. In this study, we used SSR markers for genetic distance parameters such as Fst, Nei distance etc,. Now, is it logic using OWA scenarios to determine habitat suitability between two centroid of animal population?
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Yes, this paper used weighted averages of landscape variables to compare least cost path distances between sites: Rangewide landscape genetics of an endemic Pacific northwestern salamander, Molecular Ecology (2013) doi: 10.1111/mec.12168
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Protecting the right of the local community/country to use their own genetic resources available in  a particular area is an important element of environmental and biodiversity conservation.  However, one of the biggest biodiversity conservation challenges faced by southern peripheral countries is biopiracy and related issues. I am doing some research works regarding that. Could you pleases help me to fin out suitable research works based on that
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It appears that recent real cases of economically significant biopiracy are actually relatively rare. Of the four cases cited by Efferth in the first reply, one represented within-country (cross-cultural) 'piracy' (not applicable to international law), two were for products not yet proven to have any significant economic value, and then there is the decades-old poster child, Madagasar phytophora. The $5.4 billion quoted by the UN is mostly for long past issues (worth resolving, but not relevant to current piracy).
What is rarely discussed is the massive cost to legitimate researchers that result from now-widespread export permit polices that are likely to have very little actual desired impact, and are based more on anecdote and paranoia that on actual cases. For example, current restrictions on bio-material export would have no effect on the ability to patent tumeric (cited by more than one paper above), a cat that got out of that bag centuries ago.
Someone needs to produce a database of (all?) proposed biopiracy events of the last 20 years (since it is current piracy that these policies are meant to prevent), along with estimates of the actual economic loss associated with each, not just someone putting in for a patent that ends up going nowhere (which is the fate of most of the bio-material patents). Maybe such a list is already out there; if so please share it here.
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Hi,
I'm looking for publically available datasets which have genes for which the coalescence times are either known, or have been estimated with a sufficient degree of confidence using one or several coalescence time estimation methods? I'm looking for the data and any accompanying publications, especially those for which the genes, and the times are easily accessible.
Thanks, 
Ben W. 
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Sorry I am not working with genetic aspects of coalescence.
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Hi
I've run Structure to detect population structure in 20 populations of a Mediterranean shrub. I used 6 runs fro each K, with a burn in of 100000 and 1000000 iterations. I then used Structure Harvester to implement the Evanno method and obtained the results observed in the attached graphs.
I wonder whether anyone has any insight regarding the large Delta K obtained. I've never seen anything like this in the literature. Also, if K=2 is the true K, this does not match with the relatively high values of Fst between populations (values up to 0.25).
Any hints or recommendations?
Thanks everyone!
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Hi,
a high Fst can occur with K=2, if the two clusters are well represented and (sub-) populations have low diversity. A method I have used some years ago to verify the numbers of K is to run an AMOVA with the regions defined as the clusters of STRUCTURE. Then see the PhiPT and compare its values for each K. Nowadays I used adegenet (as mentioned above) and Geneland (R). The latter uses a similar algorithm as Structure and defines the optimum K after multiple runs and also can incorporate spatial parameters in the model.
Good luck
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I was wondering if there was a package that helps with RAPD data, specifically population genetics. I heard about "poppr" but I am not sure if it works for this type of marker, it says it works for dominant data but it never specifies.
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Poppr should work for your needs. There are other packages you may want to explore as well though; 'PopGenome', 'Pegas', and 'Adegenet' depending on your needs. A bit more explanation might help narrow it down.
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Dear all,
For studying the genetic diversity of the species within and between its populations, microsatellite or SSR markers is used in different groups of a multiplex. For bin setting and data analysis of the geneMapper report, what is the available software can be used?
with all the best,
Dadamouny
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Dear Mohamed
There are several softwares to use, as STRUCTURE for population structure analysis, genepop, FSTAT and popgene for basic statistics, and also GeneAlex for ANOVA or PCoA analysis, also a excel add-in called MStools will help you to transfer your original data into input format for several softwares. Tassel also could be used for building trees and doing some correlated analysis.
Good luck.
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Prediction capability of Species Distribution Models are generally measured through ‘Area Under Curve (AUC)’ using training data sets. I have developed four distribution models of my study species. All models are in raster format. Training data sets are exact GPS locations of the species. Can anyone help me! How to create AUC using R commands? Which R package can be used? Please share your R codes if available!
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Another alternative would be the "PresenceAbsence" package.
If you have a file called "validate_data" with this structure: 
ID     Observed     Predicted
1      0                 0.15
2      1                 0.86
3      1                 0.92
4      0                 0.26
Just write: 
auc (validate_data) # Get the AUC value. You can specify the sd. 
auc.roc.plot (validate_data) # Plot the ROC
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First, it would be great to try to understand the cause of the HWE deviations. Do you work with  a homogeneous population or kind of mixture?
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I am interested to undertake a study on determination of level of inbreeding in elephant population in an isolated habitat. The nature of study area is thick forest, hence collection of fecal samples  is the relevant approach to study Genetics of elephants. Anybody who is familiar and experienced in designing protocol of collection and analysis of DNA Fecal Samples. The population is not well known, population number is approximated 102 elephants. Thanks
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You have to collect the fresh dung samples for better result. Fresh samples (less than 24 hours freshness) has higher DNA quality than older samples. But you can consider collecting 2/3 days old samples too. You have to collect the dung's outer layer and store in 95% ethanol. 
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I have a list of rat genomic regions. I have liftovered them to human orthologous regions. For the rat regions that can be successfully converted to human orthologs, I want to find out if the matched rat-human regions are conserved. I can use the phastCons score or phyloP score to evaluate the level of conservation, but these values are based on multiple-species alignment (46 species). What I am really interested in is the conservation between human and rat. I wonder how I can obtain that value? using blastn or fasta or something else?
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Hi Jia Zhou , I am doing something similar so if you ever came up with an answer could you let me know the methodology that you followed. Thanks 
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I am working on conservation genetics of some alpine medicinal plants. I have used some dominant markers and co-dominant markers. I am unable to construct network tree by using Splitstree.
Can anybody please help me to construct the input matrix for "Splitstree" or "Neighbournet" using binary data matrix (1,0).
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Hi
You can get binary data, such as for dominant markers like AFLP, into splitstree using this format
#NEXUS
BEGIN Taxa;
 [&&SPECTRONET SN_BLOCKNAME Taxa_2]
 DIMENSIONS NTAX=4;
 TAXLABELS tax1 tax2 tax3 tax4;
END;
BEGIN Characters;
 [&&SPECTRONET SN_BLOCKNAME Characters_1]
 DIMENSIONS NCHAR=10;
 FORMAT DATATYPE=STANDARD GAP=- SYMBOLS = "012345";
 MATRIX
tax1 01010 01010
tax2 11001 00101
tax3 01110 11001
tax4 10101 10101;
END;
For co-dominant markers, you can code the data as binary data by recording the presence/absence of each allele - but this is not a particularly good approach. If you want to combine dominant and co-dominant markers together it will function.
For co-dominant markers alone, it is generally better to use a population genetic software package to generate a distance matrix for the samples/populations and then get that into Splitstree using the format you can find in the examples folder supplied with the software in the file south.nex. Be careful to use an appropriate genetic distance measure in your population genetic software! My experience would suggest being very wary of models that do not treat all alleles as equally related. Typically the Nei (1972) model is a good start.
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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'm working on a fish species with populations distributed across a river network, using microsatellite markers to investigate population genetics and landscape genetics in a conservation context.  I would like to:
1) Tease apart which landscape-based distance variables (distance between, elevation change, count of anthropogenic structures, etc.) are contributing most to fragmentation of identified populations; and
2) If the top contributing types of features are anthropogenic (e.g., dams or road crossings), I would like to identify the individual features within that type that are functioning as the most restrictive barriers.
Any ideas of potentially useful programs, analyses, or references would be appreciated.  Thank you.
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I would suggest looking at the new Bedassle package in R, from Gideon Bradburg, Peter Ralph, and Graham Coop.  It does many of the things you are looking to.  It uses a fairly complex Bayesian framework, and getting it running in R is not trivial.  But it might outperforming other platforms like genalex, spagedi, arlequin, or genodive, that will also do some of the analyses you want.
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like Maxent SDM or any other 
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Hi Husam,
I'm most familiar with the presence-only SDMs like Maxent.  In general for SDMs, you'll want to focus on biologically-relevant environmental factors as your predictor variables.  So feasibly, you could include some sorts of habitat suitability index (HSI) metrics as predictor variables; however, you would need those HSI metrics calculated for every unit you want to predict the species distribution into.  This is why almost every example simply uses larger, publicly-available datasets with large spatial coverage.  If you are interested in using Maxent, I would highly recommend Elith et al. 2011:  
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I work on an ancient protein family that exists in both eukaryotes and prokaryotes and my interest is in elucidating its deeper branches. When I pull down the data from NCBI I get about 6000 sequences. If I use an algorithm to help me cluster similar proteins (e.g. 80% similar) it gets reduced, and if I do my clustering with 50% similarity I get about 550.
The question is, in your experience, which one would you choose:
- use the smaller dataset (or even smaller) and do the most sophisticated, yet computationally intensive, analyses you can hoping that if there is a signal, these analyses would pick it up and thus the deeper branches get better support.
- use a lot of data and hope that then the intermediate evolutionary steps could be inferred more easily and the deeper branches get more support?
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The 2nd option is probably more likely to give a quality answer. If you have the time/computing power I think you should look at the larger dataset, too. If your clustering combines particularly disparate sequences you may be thinning out your taxa distribution and inviting more opportunity for long branch attraction. I would consider comparing the topologies and look for places where lots of relative diversity was collapsed in one area but not in other areas of the tree. If it is even throughout, the smaller dataset is probably much more likely to give a fair answer.
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I have microsat data for 7 loci and overwhelmingly I see a pattern of homozygote excess in all populations.  My microsats were developed using this species and these pops so it is unlikely that the pattern is due to null alleles.  As much as possible I have eliminated likely clones as these are flatworms connected to a host and I have only selected one individual per host.
I am finding some research that has found homozygote excess in non-selfing hermaphroditic species but not much to explain the mechanism of it.  I was just curious as your thoughts on why exactly this is occurring?
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Hi,
despite your msats were developed for the species, it is still likely that some loci can have null alleles. There are a vast number of studies confirming that. If homozygosity excess is repeatedly observed for certain locus (or loci), then null alleles (or allelic drop-out) is more than likely. Also, sometimes short alleles are preferentially amplified during PCR, leading to unbalanced product amount. Then, it is easy to mistakenly interpret heterozygotes as homozygotes. Besides technical problems, mating between relatives may produce significant inbreeding. Another potential source of homozygosity excess is the so-called Wahlund effect, i.e. the effect of treating different gene pools as a single panmictic unit. However, I’m not sure if biparental inbreeding or Wahlund effect is relevant to your species or sampling design, respectively.
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I have demonstrated a project, assessing the genetic diversity of breeds of an animal using SSR markers. I've got the allelic data from GeneMapperv.3.7 but i have no idea how to plot the dendrogram to show the genetic distance and what is the software through which I can calculate the Cophenetic Coefficient for my data? Can anyone guide me through this? 
I have also attached an excel file containing the allelic data.
Thank you
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  • If you have the SSR data in binary matrix (so your object is not diploid), then I supose you to use the Treecon software (as I wrote in my last comment).
  • If you have the SSR data for diploids, then you don't need to convert it to binary matrix, just normalize the geneMapper data and use the Powermarker software
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I want to check the clonal fidelity of a medicinal orchid propagated from the mother plant using axillary branching.Now cross verify the robustness of the protocol I want to use molecular markers to verify its stability. Our lab dont have any MASAP/SSAP or SNP infrastructure. I came through this paper which has applied the identical approach http://www.sciencedirect.com/science/article/pii/S0378111914000493
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Hi there,
since I've received several requests for the HAT-RAPD protocol I will just post it here.
We first published the use of the protocol (without the fancy name :-) ) in  Eimert et al. (2003). Since that journal does not allow the distribution of copies I attach here some later papers describing it.
Basically, the trick is in using decamer primers with higher GC content (70-90%) and or di- or trinucleotide microsatellite-like composition. That gives them kind of inter-simple sequence repeat (ISSR)-anchored primer (Zietkiewicz et al. 1994) or SPAR (Gupta et al. 1994) like properties and allows for the higher annealing temperatures (we usually use TA around 45-50°C). We bought the primer sets 1,4 and 8 from the University of British Columbia for the above mentioned reasons. They don’t sell them anymore, but I attach the primer list here so you can order them from your local suppliers. I also attach a short list of primers we tested successfully for several species (Asparagus, Heuchera, Euonymus, Malus, Phalenopsis, Prunus, Ribes, Vitis, Zinnia) and which turned out to work in most of those reasonably well (some better in one species then in the other). You might want to start with those amplifying well in several species.
You will probably have to optimize the Primer/Mg/TA combination for your species of interest. Using thermocyclers with programmable ramp times, we get very reliable results over different labs and operators (repeated checks after several years give the same patterns). One thing you still have to keep tightly controlled is the enzyme – using different brands of (Taq-) polymerase may result in changes in fingerprint patterns (mostly in intensity, but still … - better not to change suppliers during a running experiment).
Good luck to all of you and feel free to ask any questions :-) !
Klaus
Helpful (hopefully :-) literature:
Eimert et al. (2003) J Agric Sci 141:73–78
Zietkiewicz et al. (1994) Genomics 20:176–183
Gupta et al. (1994) Theor Appl Genet 89:998–1006
And attached:
Ruangsuttapha et al. (2007) Gen Res Crop Evol 54:1565–1572
Eimert et al. (2012) Plant Syst Evol 298 609–618
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I need a software that calculates bias-corrected Nei’s genetic distance (Nei 1978) matrices and perform a Ward’s cluster analysis on the data together with bootstraps.
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Thank you for your suggestion, but unfortunately the software does not perform cluster analyses.
best regards
fabienne
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I have a question concerning the time scale (x-axis) of Bayesian Skyline Plot (BSP) analysis as implemented in BEAST. I am not very familiar with the model underlying this analysis.
I run BSP analyses on three different dataset (one each population) for the mitochondrial COI (537bp). The first population included 97 sequences, the second population 167 sequences, and the third population 48 sequences. The programs (Beauti + BEAST + Tracer) produced 3 BSPs with different time scales: the first population, 0 to 450 Kya; second population, 0 to 1800 Kya; and third population 0 to 350 Kya. My question is “how the more ancient value of x-axis is obtained? It seems related to the number of sequences in the original dataset, does it? If so, which is the relation between the number of sequences and the length of x-axis (time) of the BSP?
Any suggestion will be greatly appreciated.
Ciao
Ferruccio
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The paper by Atkinson et al (Proc Roy Soc B, 276:367-373, 2009) shed light on the problem addressed in my question. The answer is that Bayesian Skyline Plots are truncated to the median estimate of each population's TMRCA. Problem fixed! Thanks!
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The coulour variants of many species have in recent years being bred as a separate group or individuals. This is either a a result of their easthetic value or economic gain. Whether the separate or exclusive breeding has an impact on the natural population genetics is the question?
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"Whether the separate or exclusive breeding has an impact on the natural population genetics is the question?"
1. If they are really bred separately and you have evidence for this, than it is a separate species and no colour variation any longer. 
2. In my groups the colour variation depends on photoperiodism: length of day and night during their photosensitive phases. In these group there is no trend to be separated as different species.
Some of these species:
Pachynematus clitellatus Serville: Tenthredinidae, insect spec. of seed grasses, sometimes reported on wheat. 3 generation per day, the larval colours are different, very likely due to the photophasis-scotophasis during their photosensitive phase (early larval instars. )
Eutomostethus ephippium Panzer: southern colour variation with red thorax and northern colour variation entirely black. probably this colour differences is also caused the difference between night and day in South and North.Sawfly living on grasses. 
Cimbex femoratus L. has black, brown and gold colour variations. probably the same situation since the flying period pretty long It needs further research.  
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I used DNeasy (Qiagen) and invitrogen DNA mini extraction kits with digestion modification, but I am not getting DNA's. So please anyone can give me the protocol or kit to extract DNA from 50 to 100 years old museum preserved/dried bird samples. Thanking you.
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Dear all: see Paredes in the attached document
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What is the best marker/technique (microsatellite loci, RAPD etc) to investigate the maternal and paternal origin of captive chelonians? Also, is the same marker valuable for addressing genetic inbreeding on captive animals? Is there an optimal number of markers to use?
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Hi André,
An inbreed population can certainly lead to issues with your data, like elevated linkage among loci, and it can be difficult to characterize this without a reference population. However, you can assess the quality of your marker set for your application by generating statistics like probability of identity (PID) and by using distance measures that don't assume HW equilibrium and are appropriate for individual to individual comparisons (Rousset’s distance). For paternity assessments, your greatest power generally comes from excluding a potential parent rather then assigning a parent with 100% confidence.
Hope that helps, and best of luck with your project,
-TAY
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when I am doing linkage mapping including  distorted marker, such distorted marker are coming in  different groups. is it needed to remove such markers or need to add to same linkage group?
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Yes, you can, but...
My recommendation is you first make the map without the distorted markers and then add them to the available linkage groups.
Hope this helps
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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 have a long list of human proteins. Is there an online tool or resource material that can be used to determine the conservation of these proteins across the eukaryotic phylogenetic tree?
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Yes, I wanted to determine the relative degree of conservation e.g. the Human eEF2 protein is 76% identical to Yeast eEF2 protein while Human DNA polymerase III protein is 82% identical to Yeast DNA polymerase III protein?
I've got a long list of human proteins-of-interest. So manually identifying their ortho- or paralogs across various eukaryotic species and doing alignments seems a bit insane. 
I was hoping there might be an online tool with such functionality.
Re: determining evolutionary age: I have used 'ProteinHistorian' to estimate the evolutionary age of the protein set ... it's a great tool.
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S. apetala germinates and grows several inches but then cann't survive in the planted forest. Its natural regeneration is a worldwide problem. I have worked on soil physico-chemical properties, now focusing on genetic diversity of the sp. Any more suggestion?
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Dear Sir
For further surprises please read following papers which show S. apetala found to be naturally regenerated in coastal shores of Bangladesh like in Sitakunda, Mirersarai and Hatia.
Latif MA, Del Castillo RA. 1990. Growth and yield of keora (Sonneratia apetala) in coastal Plantations of Bangladesh. Bangladesh J Forest Sci. 19:11–18.
Haque SMS, Hossain MK, Kabir MA. 2000. Performance of some common mangrove species in Sitakunda and Mirersarai Forest Ranges under Chittagong Coastal Afforestation Division. The Chittagong Univ J Sci. 24(2):1–10
Uddin MM, Hossain MK. 2013. Status of coastal plantations and its impact on soil PH, salinity and land stabilization at Nolchira range of Hatiya Island, Bangladesh. IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS). 3 (4):7–15
Siddiqi NA, Khan MAS. 1990. Growth performance of mangrove trees along the coastal belt of Bangladesh. Mangrove Ecosystem Occasional papers. No. 8 UNDP/UNESCO/RAS/86/120. Thomas Press, Delhi, pp. 5–14.
Thank you.
Mr. Siddiq
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This kind of comparison seems tricky and polemic, however, still very necessary!
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I'm not sure if this is what you are looking for, but I recently read a paper by Geraldes et al. (http://onlinelibrary.wiley.com/doi/10.1111/evo.12497/abstract) that used SNP chips to genotype Populus trees. They had a nice supplementary figure (S3)  that presented Fst and Hs from each of their target populations in a pretty intuitive way. (http://onlinelibrary.wiley.com/store/10.1111/evo.12497/asset/supinfo/evo12497-sup-0001-FigureS1.pdf?v=1&s=838895939296cf9680278d71d2284b79cdec9da8).
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Hi
I am working on identifying the origin of an invasive anuran using mtDNA genetic markers and have found only two similar papers. These are the phylogeography of Bufo marinus (=Rhinella marina) (Slade and Moritz 1998) and a more recent paper by Kuraishi et al 2009 looking at the origin of Polypedates leucostymax in Japan. Does anyone know of similar studies on other invasive anurans such as Lithobates catesbeianus or Eleutherodactylus coqui?
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I thought this review article was useful:
Estoup, A., & Guillemaud, T. (2010). Reconstructing routes of invasion using genetic data: why, how and so what?. Molecular Ecology, 19(19), 4113-4130.
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Thank you in advance for your answers.
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Interesting question! Basically there should be no fundamental difference in utility for terrestrial vs. marine systems. However, keep in mind the long - standing notion (assumption) that there *tends* to be more gene flow, fewer obvious physical barriers to gene flow in the three dimensional marine ecosystem, especially for vagile and/or broadcast spawning taxa. 
But recently, the role of mitochondrial DNA (mtDNA) sequences in taxonomy and phylogenetic inference has become quite contentious:  two extreme viewpoints have
emerged. One which criticizes the use of mtDNA because the marker suggests 'misleading patterns of variation'; specifically, phylogenies that
are inconsistent with those derived from nuclear gene
sequences in the context of species relationships among
closely related taxa (Ballard and Whitlock, 2004; Shaw,
2002). The other extreme, the DNA “barcode” movement,
espouses the sole use of small fragments of a single
mtDNA gene, cytochrome c oxidase I (COI), to identify
most of life (Hebert et al., 2003).
In a review paper my colleague Dan Rubinoff and i published a few years back we present the disadvantages of these two extreme
viewpoints and argue for an integrated role for
mtDNA, one that takes advantage of mtDNA’s strengths
but also accounts for its shortcomings by using it in concert
with other independent data sources (e.g., nuclear
DNA, cytosystematic, morphological, behavioral). We
are against the abolition of the use of mtDNA in phylogenetics
but also against its narrow use in barcoding as currently
defined. We try to show why neither viewpoint
is particularly productive and emphasize how analysis
of mtDNA can be an important tool in the context of both
taxonomic and phylogenetic studies, and I would say equally for marine versus terrestrial organism systematics.  (for our review on this debate in general see:
Rubinoff, D. & B.S. Holland. 2005.  Between the two extremes: Mitochondrial DNA is neither the panacea nor the nemesis of phylogenetic and taxonomic inference. Systematic Biology, 54(6): 952-961). 
For a couple of additional papers that used mtDNA markers to examine and evaluate  systematic boundaries in closely related marine taxa:
Bird, C.E., B.S. Holland, B.W. Bowen & R.J. Toonen. 2011.  Diversification in broadcast-spawning sympatric Hawaiian limpets (Cellana spp.). Molecular Ecology. 20: 2128-2141
Bird, C.E., B.S. Holland, B.W. Bowen & R.J. Toonen. 2007. Contrasting phylogeography in three endemic Hawaiian limpets (Cellana spp.) with similar life histories. Molecular Ecology, 16(15): 3173-3187
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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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I know a value of 1.8 is the purest form of DNA.
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The ratio has no effect. How could it?
A lower ratio indicates that the DNA sample does not only contain DNA (or, more precisely: nucleic acids) but also things that have an absorption maximum above 260 nm. Typical suspects are proteins (aromatic amino acids, especially phenylalanine, absorb maximally around 280 nm) and phenole (often residing from the extraction buffers). Protein contaminations are no problem. Often, the PCR works even better when some proteins are present. Many PCR mixes contain BSA (some protein mixture without enzymatic activities) to enhance the PCR. Phenol is the bad guy, since this inhibits most of the polymerases. The DNA sample should be free of contaminations of phenole (and other phenolic components). As far as I know, the OD 260/280 ratio is usually done to check for contaminating phenole.
If I removed proteins using a phenole-chlorophorm extraction, a low ratio likely indicates residing phenole that will casue problems in a subsequent PCR.
In contrast, if I have a phenole-free solution that may contain proteins, then this presumably has a low ratio, but this won't mean trouble for a subsequent PCR.
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Don't know, please answer 
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Dear P.K Panday
    I am using the primer to amplify the DNA of  mammal and the primers used are that of a reptilia. amplyfying cyto b gene.
    I dont collect the feces from the zoo.they were collected in wild.
   In my past work i got amplification from the samples but not now...
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Hi everyone I am running Structure programme smoothly. I scored data as o and 1and perform analysis but in the result files are empty at the end of the simulation. I tried both window 7 and 8 for running structure version 2.3.3 and 2.3.4 but the problem is still there. The data file I prepared as a binary matrix and species is assumed haploid input format is when uploaded with structure and programme were set with length of burning period 20000 and number of MCMC100000, using Admixture model with correlated allele frequency assuming set of population of 10. I set K=2 to K=10 the programme run smoothly but I could not get result file even after so many change. One more thing want to share that I am getting the value of Ln Like= --- and Ln PD = 0 is this the reason of no results. and if this the reason then how I can remove it Kindly suggest what is needed to be done exactly
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i solved the problem  replacing / with comma (5000,50000) in  naming the parameter set
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I am considering to design species specific primers to identify species from fecal samples. Would you like to suggest me which software is the best ?
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you may want to use ecoprimers http://www.grenoble.prabi.fr/trac/ecoPrimers
Check out the metabarcoding.org page for more info. 
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Hi everyone,
Can you suggest a best protocol to bombard a gene on soft petal (such as Lilies)? What is the best shooting pressure and distance? Also, I have a problem with tissues browning and eventually cell death happened after bombardment. Any suggestion? Thank you.
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Some tissue death is to be expected, especially at the center of the bombarded area.  You could try conditions used for onion epidermal peels (a delicate sample type) as a starting point and modify the protocol from there. 
If you're  not set on doing particle bombardment you could try transient expression by Agro. infiltration.  It may result in less tissue damage.
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Can anyone provide reliable information on species pairs (fishes are preferable) that have clear differences in morphological characters but show a little or no difference on the DNA level?
Species names in Latin would be nice.
References would be great.
Thank you!
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Coulson et al 2011 (DNA barcoding of Canada’s skates, Molecular Ecology Resources (2011) 11, 968–978) noted that here was a lack of genetic differences between Amblyraja hyperborea and Amblyraja jenseni. However, while very similar in appearance, morphology and most meristics, upper jaw tooth count is different between these "sibling" species. They also appear to have different growth and maturity and I am presently examining that aspect. They are largely geographically separate and what we may be observing is a recent separation. I agree that DNA bar coding is a useful tool but is not in itself definitive in defining species.
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I did a genomic DNA extraction of fungal tissue using a CTAB/phenol based automated extraction. To my knowledge the samples were not treated with prot K or RNAase during the process.
When I look at the genomic DNA on a gel, I see unexplained smeared bands below 50bp, with additional smearing below that. I ran the attached gel in attached image too long, and the smear bled into the wells below. The 1.5% gel was stained with GelRed, and run at 100v for 40min.
Does anyone know what this low molecular weight band and smearing could be?
 
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I think its probably degraded RNA. Treating with RNase will sort this out. You can just add say 4 microlitres of 100 mg/ml RNaseA to 100 ul of DNA extract for a few minutes and then stick it the sample through a column clean up then run some more on the gel to see what it looks like. Good luck!
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We are looking for a neuropeptide in ants and we need to do slides of 10-12µm for MALDY and inmunohistochemistry. I froze the animal and try to get the slides, but the results are very poor. Does anyone know what we can do next?
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Thank you for your answer. What I mean with poor results is that when I make the slices the ant cuticle is almost always broken and the tissues are torn. In some slices the ant tissue separates of the rest of the slice (there is a hole in the place where the ant should be). I think it is because of the hardness of the cuticle. I also used a pepsin to get a softer cuticle, but it doesn't work very well. I use the usual procotol: the ants are frozen and then I embed them in tissue tek and make the slices.
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In the study several genetic sex determination methodologies were investigated, compared, and discussed.
Thank you so much!
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I would recommend considering PeerJ (peerj.com).
They are fully open access, fast (~ 3 weeks to respond) , inexpensive (pay a one time $99 fee and publish for free for the rest of your career), indexed (pubmed etc) . No impact factor yet (started last year) but rapidly growing.
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D loop can be used as they are conserved sequences?
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Not sure what you mean. there's no reason the markeers should work in turtles but not in deer. However, if you wonder whether you can use the same primers to amplify the region: try to align the primers with the mt genome of the deer (or any species closely related to your target species) and make adjustments where necessary.
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Hi,
I am interested in studying the phylogenetic relations of a C. elgans enzyme that is conserved from yeast to mammals. I have generated a phylogentic tree representing over 100 eukaryotes and found the C. elegans enzyme at the base of the tree. It seems as though there are not enough sequences of species between yeast and C. elegans , i.e. I found no homologous sequences in Cnidaria, Porifera, Placozoa and other lower eukaryotes. I wonder if my enzyme is situated at the base of the tree due to the lack of annotation of early eukaryotes. Is this a known problem in phylogeny?
Thanks for your help!
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well what i say is there may be a homologous sequence in platyhelminthes or in other trematodes try to look for it. It must not be the case that all of sudden the sequence via mutation or gene transmission got into nematode. if you are right annotation is a problem in doing phylogency if you are working in something new.
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And if so kindly mention a reliable method.
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Hi, are you working on population study of endangered species? Non invasive samples have been a quite good source for DNA genotyping when collected fresh. You can see some examples on the elephant study by Lori Eggert (University of Missoury).
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see above
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Hello Inayat.
I guess the non-invasive samples are feces. Starch (as well as BSA) reduces the quantity of bile acids and bile salts, that inhibits PCR. Sometimes it works, sometimes it does not. There are kits to specifically extract DNA from feces, that use to work well. Whatever you follow for DNA extraction, my advise is to do PCR (if you have to) with Hemo Klen Taq (New England Biolabs). I use Hemo Klen Taq when working on feces. This enzyme is not inhibet by bile, heglobin or heparine.
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Quigen using. From fecal matter of red deer.
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It really depends on your objective (microsatellites, mtDNA, etc.) and, of course, your sample. You are already using non-invasive samples, therefore you are already expecting DNA with lower quality, yield and concentration. Additionally, faeces can also have different DNA outputs depending on their preservation, before and after collection. Taking this into account, most companies, including Qiagen, have specialised kits for this kind of extractions, but you also have to be more careful with contaminations. If you do not have good results with a standard kit, either you try to optimize the protocol or you try more specialised but usually more expensive kits.
Good luck!
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I have been trying and did set data as well, but Arlequin shows error/warning message. I am using mtDNA D-loop marker.
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Dear Ahasan,
I suggest you to use "Isolation by Distance Web Service" (http://ibdws.sdsu.edu/~ibdws/). Together with the matrix of geographic distances, you can give raw sequences or genetic distance matrix as input file. Examples of input files are available on that page. Many statistical options are also available. Good luck!
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High haplotype diversity could be driven by large population sizes and gene exchange with larval admixture from different genetic pools. I would like to know some proposed explanations for genetic diversity hotspots in marine species.
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You reminded me about a recent article in BMC Evolutionary Biology. In this case the authors wanted to know how the strategy of the larvae cycle (dispersive planktonic or benthic non-dispersive larvae) can influence temporal genetic structure in polychaete. As Farhat suggests, these authors work with microsatellite analyses. I hope it's useful to you. Anyway it's an interesting paper:
Temporal genetic structure in a poecilogonous polychaete: the interplay of developmental mode and environmental stochasticity
Jenni E Kesäniemi, Marina Mustonen, Christoffer Boström, Benni W Hansen, K KnottBMC Evolutionary Biology 2014, 14:12 (22 January 2014)
Regards,
Antoni
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Mitochondrial DNA.
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As you are working on population genetics I agree on the use of microsatellite markers and/or mtDNA. With regard to the use of AFLPs, these are rarely used in animal population genetics when one aims to publish their data. Nevertheless, quit a few published articles in the last year measured the levels of genetic diversity and delineated population genetic structure in several elasmobranch species using AFLPs. Then again as said by our colleagues it depends on your research question.
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We are having problems in PCR amplification of DNA extracted from fish eggs (tuna). DNA extracted from muscle tissue using the same methodolgy works fine. Any help would be really appreciated.
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Did you resolve your problem with amplification of microsatellites from tuna eggs?
One crucial step that improved our DNA extraction protocol from fish eggs was to rinse the egg in water (if stored in alcohol) and then use a sterile tip to burst the egg inside the extraction tube prior to the next step. I hope this helps. Luca