On which SNPs (regulatory or nsSNPs) should we focus when looking for SNPs responsible for a disease?
On which SNPs (regulatory or nsSNPs) should we focus when looking for SNPs responsible for a disease?
To quote from a paper 'exome sequencing identifies the cause of a mendelian disorder'
"the clear majority of alleleic variants known to underlie Mendelian disorders disrupt protein-coding sequences. Splice acceptor and donor sites represent an additional class of sequences that are enriched for highly functional variation...a large fraction of rare non synonymous variants in the human genome are predicted to be deleterious. This contrasts with non coding sequences where variants are more likely to have neutral or weak effects on phenotype"
However when considering a complex multigenic disease such as diabetes I don't think it wold be prudent to focus on exonic variants.
This is also interesting about synonymous SNPs
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I guess that depends whether the disease is likely to be caused by mutations in a protein, or disruption of transcriptional control. There is no good answer to this question if the answer is 'both'.
This question is ill posed as nsSNPs can also be regulatory (yeah, regulation inside exons). So, it's not possible to analyse them separately. You should specify what kind of regulatory SNPs and where.
What should be the take for diseases like Diabetes....
It doesn't make any difference what the disease is, it's a matter of the causal mechanism. As you're asking about diabetes, you're probably aware there are regulatory SNPs associated with HNF4 that play a role in type 2 diabetes. This was (for me) one of the first times a regulatory SNP had crossed my path.
If I am correct, you are saying, "in multigenic disorders regulatory SNPs play bigger role compared to missense mutations"?
No I am saying nothing of the sort! There is no answer to this question!
By regulatory SNPs I was referring to SNPs present in TFBS, miRNA binding sites, ESS sequence and ESE sequence. Secondly, only missense mutations can be judged (using computational tools) for their functional influence.