I learned something interesting today about the SNP arrays used for GWAS. There has been a lot of discussion about the nature of mutations/alleles discovered by GWAS studies in terms of the "common disease: common variant" hypothesis. It is clear that SNP arrays are designed to cover common variants - alleles that are present in at least 2% of the human population (or at least of some population). Contrary-wise, genome sequencing studies tend to focus on rare variants. In fact a number of recent studies show that major diseases such as cancer and autism tend to be associated with novel, very severe mutations in coding regions of genes.
Now this is the interesting part. We took a look at the intersection between the Illumina 2.5 M SNP array and the regions targeted by the Agilent Sure Select exon enrichment kit. It turns out that only about 90K of the Illumina SNPs are in the exon regions. This matches up with Illumina's own annotation file showing that more than 80% of the SNPs on the array are intron or intergenic. My human genetics colleague suggests that the SNP array targets sequence variants (alleles) with small effects, while the exon sequencing strategy targets mutations with large effects. So we can't really replace the SNP array with exome sequencing, they are looking at completely different things.
REDalign – accurate RNA structural alignment using residual encoder-decoder
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RNA molecules are essential for various biological processes, and studying
them helps scientists understand how cells function. A key part of this
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23 hours ago
4 comments:
Seems counterintuitive to say that array targets small effects, given that by doing exome sequencing you target all the potential variants and are not reliant on LD to see effects, what the real difference I see is exome sequencing wis revitalizing the use of families in studies rather than the hodge podge of samples used in many GWAS studies, when you do a family study you really learn what caused the effect in that family this can then be applied to understanding disease in population. In gwas you loose all the subtlety and can only see large effects
Excellent insight.
However, it's important to also state that the converse: "We cannot replace the exome sequencing with SNP arrays. That is, in looking for rare alterations that are strongly associated with human phenotypes (illnesses), there's no substitute for sequencing large numbers of exomes in diagnosed individuals."
thanx for sharing
Well, when we know more about other conserved regions and derive a capture kit that includes them as well as the exome, then microarray chips will then become obsolete.
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