Indel through to AminoAcid change

Hello
I am paused at a part in my project of analysing a genome from a rare neurological presentation (extremely rare- prevalence of only a few in the literature). The rare part being the symptom which is visual in nature, the neuroradiological etiology being very common in neurological disorders- white matter degradation.
Ive found a gene of particular interest. The mutations in this gene are all indels.
To ascertain whether its pathological i need to work out if the change leads to a loss or gain of a cysteine residue within one of the EGFRs of NOTCH3 extracellular domain.
Ive found 7 mutations within the 23 exons which code for the epidermal growth factor-like repeat domains, im wondering if someone could please give me an indication as to how i advance further on this to work out if they lead to a loss or gain of cysteine residue.
Thanks
Mikey

Answers

  • bhanuGandhambhanuGandham Member, Administrator, Broadie, Moderator admin

    HI @Mikey

    In this forum we tackle specific GATK usage related questions. I am afraid I can not help you with an experimental design question unless it is related to GATK. Apologies.

    Regards
    Bhanu

  • MikeyMikey Member

    Sure no problem Bhanu. Thanks for your answer, is there anywhere you can suggest i can post this question too?

  • bhanuGandhambhanuGandham Member, Administrator, Broadie, Moderator admin

    Hi @Mikey

    You could try Seqanswers and Biostar forums for genomics experimental design questions.

  • SkyWarriorSkyWarrior TurkeyMember ✭✭✭

    I will give a brief answer though it is not GATK related but I will redirect you to possible direction.

    1- Use Ensembl VEP. Upload your variants to VEP web interface and get proper annotation.
    2- Once you get your annotations go back to your bam and vcf file for visual check.
    3- Use Varsome at any place where you cannot decide if that variant is potentially disease causing or not.
    4- Never forget to check ACMG criteria to judge your variants in terms of pathogenicity. Not an ultimate source but at least gives you an idea where to go.
    5- Check the nature of the mutations and see if they would fit the molecular mechanism underlying the disease. (e.g. expecting gain of function but a total loss of function is present or a potential dominant negative effect is expected but you have a gain of function? Maybe the mutation is in a mutation hot spot or not etc... Don't forget potential splice effects of synonymous ones.)

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