Tag Archive for 'Cancer'

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?

Continue reading ‘Saturday Links’

Friday Links

The largest genome-wide association study ever undertaken was published in Nature this week. The appropriately named Genetic Investigation of ANthropocentric Traits (GIANT) consortium combined data from 183,727 individuals and identified around 180 loci influencing human height. The loci were enriched with genes underlying skeletal growth and other relevant biological pathways. Interestingly, these 180 loci are estimated to only account for 10% of the phenotypic variation in height (or around 12.5% of the heritability). [CAA]

Christophe Lambert from Golden Helix has an excellent, thorough post looking at the importance of careful experimental design in large-scale genetic association studies. In particular, Lambert focuses on the need for randomising samples across experimental batches: if you have some batches containing entirely cases and others entirely controls, then the all-too-pervasive spectre of batch effects can easily create false positive associations. In many cases batch effects can be recognised and corrected for post hoc (Lambert cites a good example from the original WTCCC study), but in other cases a failure to perform the right quality controls can have devastating consequences (Lambert cites the recent longevity GWAS paper in Science). I’d be interested to hear from my more GWAS-savvy colleagues (Carl, Jeff) whether randomisation is standard procedure in most large GWAS now. [DM]

We managed to miss this out last week, but the current issue of Nature Genetics has a strange and wonderful paper on breast cancer genetics. The study looked at 2838 individuals with BRCA1 mutations that strongly predispose to breast cancer, and looked for non-BRCA1 variants associations with breast cancer in this group. They found an associated variant of chromosome 19, and replicated it in another 5986 BRCA1 carriers (where do they find this many BRCA1 carriers?). To top it all off, they looked at this variant in another 6800 breast cancer patients without BRCA1 mutations, and found no association. However, when they stratified their samples into ER+ and ER- associations, they found associations in both, but going in opposite directions! The variant predisposes people to ER- cancer, but is protective against ER+, and taken together they pretty much perfectly balance out. [LJ]

Friday Links

Over at Your Genetic Genealogist, CeCe Moore talks about investigating evidence of low-level Ashkenazi Jewish descent in her 23andMe data. What I like about this story is how much digging CeCe did; after one tool threw up a “14% Ashkenazi” result, she looked for similar evidence in 23andMe’s tool. She then did the same analysis on her mother’s DNA, finding no apparant Ashkenazi heritage, and to top it all off got her paternal uncle genotyped, which showed even greater Ashkenazi similarity. [LJ]

A paper out in PLoS Medicine looks at the interaction between genetics and physical activity in obesity. The take-home message is pretty well summarized in the figure to the left; genetic predispositions are less important in determining BMI for those who do frequency physical excercise than for those who remain inactive. This illustrates the importance of including non-genetic risk factors in disease prediction; not only because they are very important in their own right (the paper demonstrates that physical activity is about as predictive of BMI as known genetic factors), but also because information on environmental influences allows better calibration of genetic risk. [LJ]

Trends in Genetics have published an opinion piece in their most recent issue outlining the types of genetic variants we might expect to see for common human diseases (defined by allele frequency and risk), and how exome and whole-genome sequencing could be used to find them.  They give a brief, relatively jargon-free, overview of gene-mapping techniques that have been previously used, and discuss how sequencing can take this research further, particularly for the previously less tractable category of low-frequency variants that confer a moderate level of disease risk. [KIM]

More Sanger shout outs this week; Sanger Institute postdoc Liz Murchison, along with the rest of the Cancer Genome Project, have announced the sequencing of the Tasmanian Devil genome. The CGP is interested in the Tasmanian Devil due to a rare, odd and nasty facial cancer, which is passed from Devil to Devil by biting. In fact, all the tumours are descended from the tumour of one individual; 20 years or so on, and 80% of the Devil population has been wiped out by the disease. As well as a healthy genome, the team also sequenced two tumour genomes, in the hope of learning more about what mutations made the cells go tumours, and what makes the cancer so unique.

I have to say, this isn’t going to be an easy job; assembling a high-quality reference genome of an under-studied organism is a lot of work, especially using Illumina’s short read technology, and identifying and making sense of tumour mutations is equally difficult. Add to this the fact that the tumour genome is from a different individual to the healthy individual, this all adds up to a project of unprecedented scope. On the other hand, the key to saving a species from extinction could rest on this sticky bioinformatics problem, and if anyone is in the position to deal with it, it’s the Cancer Genome Project. [LJ]

Tasmanian Devil image from Wikimedia Commons.

Page optimized by WP Minify WordPress Plugin