In our laboratory, I am analyzing genetic diseases related genes. Sometime, I found nucleotide changes causing amino acid changes but it was not contained in the reported SNP list of NCBI. Therefore, it is difficult to differentiate whether it was disease causing mutation or novel SNP. For such a case, I usually perform mainly 3 things; 1. compare with other organisms and check whether that amino acid is important (conservative) or not in all organisms, 2. check by using in silico software such as Sift (http://sift.jcvi.org/) or Poly-phen (http://genetics.bwh.harvard.edu/pph2/) and 3. depending on the gene, sometime I performed in-vitro experiments using plasmids to check the functional changes. But number 3 is usually difficult to check for all genes. Can anyone suggest any additional important analysis?
Hi Banyar,
you cal also check if your variant appears in 1000G (www.1000genomes.org).
Good luck!
Hi Banyar
For differentiating SNP and a mutation a a site....one factor will be its frequency in the organism....Mutation will have very low frequency compared to an SNP...Conventionally for a variation to classify as SNP the cut off is taken a 1%...You can see the sequence in that region from more organisms in the population to decide whethe it is a polymorphic site also observed in other organisms or a rare mutation
bye
Hi, Ajay, thank you very much. I also check that one. Your suggestion is my number 1 analysis point. But in order to check the frequency, we need to analyze many samples at the same position, which may cause a lot. I sometime check the frequency at the same position for patient with strong clinical genetic symptoms using Small Amplicon Genotyping (SAG) method.
Hi Banyar,
You are right...for importance of the mutation or the amino acid you may check in other organisms ,however for frequency of this variation you need to check in many organisms of the same population (both patients and npn-patients)...by any mehtod full gene sequencing or SAG....
and for linking it to the disease you will need to do a linkage analysis with good statisticl support for linkage...
bye
Hi Banyar,
you cal also check if your variant appears in 1000G (www.1000genomes.org).
Good luck!
Hi Banyar,
Rebeca is right. One can use 1000 genomes project data.
We try to check for variation for a particular gene based on frequency of SNP for a human population. Naturally the frequency of the mutation will be lower than the healthy variant.
Maybe one can browse a gene with the mutation in the 1000 genomes browser and check if the mutation at a particular location is contributing as the frequency required for an SNP.
Try to enter your gene name in the 1000 genome browser based on HUGO gene nomenclature.
http://www.ncbi.nlm.nih.gov/variation/tools/1000genomes/
All the best.
Hi Banyar,
You can check that your variant is not present in the exome variant server http://evs.gs.washington.edu/EVS/. Moreover, try to perform prediction analyses using SIFT, Polyphen2, mutationtaster etc.
All the best!
well, it depends on the purpose of the analysis... If it is used for setting up/confirmation of a diagnosis usually there is no way of to skip functional analysis. It is obvious, that the consequences of the analysis may be far reaching, and someone must take the responsibility for the therapeutic decisions. Of course the functional analysis can be very challenging, you must have a facility set up for it, otherwise you must find a specialized lab for doing that work for you. The presence of a not harmful looking, unknown mutation with specific clinical signs is just the sign for starting the functional experiments. Family analysis, linkage analysis sometimes may be helpful. The estimation based on mutation frequency in healthy population can be very misleading, disease specific databases are much more helpful. It is not an easy task.
Just for fun, check how may times remained unnoticed the progeria causing silent mutation (p.G608G)..... just because no amino acid change occured...
Good luck!
And one more thing, whatever it means:
http://www.sciencemag.org/content/342/6164/1367.abstract
The tool of SNPs can help understand the alteration in the amino-acid sequence of the encoded protein and make a common cause of pharmacologically relevant functional variation. The multitude of SNPs help in understanding gene pharmacokinetic (PK) or pharmacodynamic (PD) pathways.
For details you may follow this article
http://www.sciencedirect.com/science/article/pii/S1110863012000687
Are you studying a specific disease? If that is the case, I suggest family studies or case/control comparisons. If you don`t really know the subject's phenotype, a variation might be meaningless. You may found many of such type of rare variants in any healthy subject. But if you insist in determining whether or not it is a deleterious mutation a good practice would be observing the type of aminoacid substitution. For instance if a hydrophobic aa is substituted by an hydrophilic one, the protein folding would be compromised. I also agree in comparing with 1000G and other species to assess the degree of conservation through phylogeny.
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