Tag Archive for 'molecular biology'

How do variants outside genes influence disease risk?

Over the last several years, the number of genetic variants unambiguously associated with disease risk has grown dramatically. However, interpreting these signals has been extremely difficult—most of the identified variants do not disrupt genes, and indeed many don’t fall anywhere near genes (this observation has even led some to discount these signals entirely). To an investigator interested in following up on these signals, this is somewhat depressing: how can we hope to explore how polymorphisms affect disease risk if they don’t seem to fall in any sort of genome annotation that we understand?

In this context, I thought I’d point to an important paper that, among many other things, gives the first systematic evidence that variants which influence disease are not just randomly scattered across the genome, but instead tend to fall in particular regions—in particular, enhancer elements (regions where DNA-binding proteins interact with DNA to influence gene expression).

The authors rely on the fact that, in the cell, DNA is wrapped around proteins called histones, which control how accessible the DNA is to things like transcription factors (see above figure). These proteins can be chemically modified, and it is now clear that particular patterns of modifications are predictive of the function of the DNA in the region—some modifications indicate transcribed genes, others regions of enhancer activity, others repressed regions, etc.

What the authors did in this study was generate genome-wide maps of several histone modifications in nine different cell types, and use this data to predict the function of each 200 base pair segment of the human genome in each cell type. There are a number of interesting analyses of these “maps” of genome function in the paper, but for our purposes here there’s one of particular interest: the authors took sets of SNPs associated with various diseases and simply asked, are these variants enriched in regions with any particular functional prediction? And indeed, for several phenotypes, there is a striking enrichment of association signals in enhancers elements in a relevant cell type. For example, SNPs which influence lipid levels are enriched in enhancers in a liver cancer cell line, and SNPs which influence the autoimmune disease lupus are enriched in enhancers in a lymphoblastoid cell line.

As these types of functional maps are generated in more cell types, I imagine there will be more stories like this. The problem with interpreting disease association studies, it seems likely, is largely due to our lack of understanding of genome function.

Citation: Ernst et al. (2011) Mapping and analysis of chromatin state dynamics in nine human cell types. Nature. doi:10.1038/nature09906

From GWAS to pathways, the consequences of DTC genetics and screening by sequencing

A paper out in PLoS Genetics this week takes a step towards using genome-wide association data to reconstruct functional pathways. Using protein-protein interaction data and tissue-specific expression data, the authors reconstruct biochemical pathways that underlie various diseases, by looking for variants that interact with genes in GWAS regions. These networks can then tell us about what systems are disrupted by GWAS variants as a whole, as well as identifying potential drug targets. The figure to the right shows the network constructed for Crohn’s disease; large colored circles are genes in GWAS loci, small grey circles are other genes in the network they constructed. As an interesting side note, the GWAS variants were taken from a 2008 study; since then, we have published a new meta-analysis, which implicated a lot of new regions. 10 genes in these regions, marked as small red circles on the figure, were also in the disease network. [LJ]

23andMe customers will be interested in a neat little FireFox plug-in that allows them to view their own genotypes for any 23andMe SNP mentioned on a web page. You can download the plug-in here (you’ll need to have an up-to-date version of FireFox), and I have a brief review of the tool here. [DM]
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Solving Medical Mysteries Using Sequencing

There is a real “wow” paper out in pre-print at the journal Genetics in Medicine. It is a wonderful example of the application of cutting edge sequencing technology to solve a medical mystery. Even better, the authors also include an auxiliary discussion about the medical and ethical issues surrounding the diagnosis, which raises some interesting issues about the transition from research to clinical sequencing.

The Case

A child manifested severe inflammation of the bowel at 15 months; antibiotics failed to clear it up, and he started to lose weight. Standard treatments seemed to have only sporadic effects, and only severe treatment with immunosuppressants, surgery and full bowel clearing could slow down the disease, which is not a long term solution. No cause could be found; the patient’s active immune system seemed to be acting abnormally, but all tests for the known congenital immune deficiencies came back negative. The doctors could try a full bone-marrow transplant, but without knowing what was causing the disease, and where it was localised, they had no way of knowing if such an extreme intervention would be successful.

Such a severe and early onset disease is likely to be genetic, but testing immune genes at random to find the mutation could take years before it turned anything up. Meanwhile, the child was seriously malnourished, and at times required daily wound care under general anaesthetic. A few years ago this might have been the end of the story.

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Saturday Links

Due to a communication breakdown, no-one wrote a Friday Links post yesterday, so today we have a Saturday Links to make up for it.

Steve Hsu has a very appropriately named post, News from the future, about the Beijing Genomics Institute. The BGI is the largest genome sequencing center in China, and one of the largest in the world, and is growing faster than any other, and loading up on a shedload of high-tech HiSeq machines.

Steve reports that the BGI are claiming that their sequencing rate will soon be at 1000 genomes per day, with a cost of about $5k (£3.2k) each. To put a slight downer on these amazing numbers, he clarifies that this might be referring to 10X genomes, which would realistically mean ~300 high quality genomes a day, at $15k (£9.6). Either way, if you want to keep an eye on how fast whole-genome sequencing is progressing, perhaps with an eye to when you’re ready to shell out to get your own done.

A question for the comments: how cheap would a whole-genome sequence have to get before you’d order one?

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How widespread personal genomics could benefit molecular biology

While the majority of the buzz surrounding personal genomics has to do with prediction of disease risk and other medical applications, there’s clearly the potential for these sorts of technologies to influence basic science as well. In this post, I’ll lay out one such potential application: the use of personal genomics in understanding basic molecular biology, in particular the biology of transcriptional regulation in humans.

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