update on the collaborative article on Post-GWAS functional characterization

Here it is a resume on the new paragraphs/addition that have been made to the collaborative WikiGene paper in the past two weeks.

For those who have not been following: the manuscript is a perspective on approaches and good practices to study the function of a variant identified in a GWAS.
It happens too often that, after a GWAS is successful in identifying a relationship between a tag SNP and a disease, these results are not followed by a study on the biological mechanism behind the association, or by studies on the exact location of the causal variant.

Resume of changes (sorry if I forgot anything):

  • added references to the Uk10K project, and improved the description of 1000genomes
  • created a chapter on computational methods to predict the function of a variant. We described: the databases that annotate information on SNPs or other association studies, tools like GRAIL to analyze the literature, cited the utility of genome browser like UCSC’s, cited a study where the authors have described a pipeline to predict the effect of a non-synonymous SNP on the structure of a protein (the author of the paper have been contacted and will contribute to the paper) and we will describe how to predict pseudogenes or functional elements, and a bit about pathway approaches.
  • described how alternative splicing can add complexity to eQTL association studies
  • described the complexity of using RNA-Seq and microarrays (also in table 1), plus a few details on Zinc-Finger technologies
  • described that it is important to take into account the interactions between chromatine fibres when studying the effect of a SNP. Different genotypes can be associated with a different chromatine network, which adds a whole level of complexity when predicting the effect of a SNP on the phenotype.
  • differences between studying SNPs and CNVs
  • discussed the usage of BRCA1 cancers as models to validate GWAS
  • added some motivations on why animal models are not perfect to reproduce the effect of a SNP in human.

There are still 11 days left to make additions, so if you can make other contributions you will be welcome.

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