Thanks for visiting my blog - I have now moved to a new location at Nature Networks. Url: - Please come visit my blog there.

Friday, February 6, 2009

Keynote: Richard Gibbs, Baylor College of Medicine - “Genome Sequencing to Health and Biological Insight”

Repetitive things coming up in genomics, and comments about the knowledge pipeline. Picture of snake that ate two lightbulbs.... [random, no explanation]

“cyclic” meeting history: used to be GSAC, then stopped when it became too industrial. Then switched to AMS, and then transitioned to AGBT. We're coming back to the same position, but it's much more healthy this time.

We should be more honest about our conflicts.

The pressing promise infront of us – making genomics accessible. Get yourself genotyped... (he did), the information presented is just “completely useless!”

We know it can be really fruitful to find variants. So how do we go do that operationally? Targeted sequencing versus whole genome. What platform (compared to coke vs. Pepsi.)

They use much less Solexa, historically. They just had good experiences with the other two platforms.

16% of watson snps are novel, 15% of venter snps are novel. ~10,500 novel variants.(?) [not clear on slide]

Mutations in Human gene mutation database. We already know the database just aren't ready yet.. not for functional use.

Switch to talking about SOLiD platform:

SNP detection and validation. Validation is difficult – but having two platforms do the same thing, it's MUCH easier to knock out false positives. Same thing on indels. You get much higher confidence data. Two platforms is better than one.

Another cyclic event: Sanger, then next-gen then base-error modelling. We used to say “just do both strands”, and now it's coming back to “just sequence it twice”. (calls it “just do it twice” sequencing.)

Knowledge chain value: sequencing was the problem, then it became the data management, and soon, it'll shift back to sequence again.

Capture: it's finally “getting there”. Exon capture and nimblegen work very well in their hands. Coverage is looking very well.

Candidate mutation for ataxia mutaion. In one week got to a list. Of course, they're still working on the list itself.

How to make genotyping useful?
1.develop physicians and genetics connection
2.retain faith in genotypic effects
3.need to develop knowledge of *every* base.
4.Example, function, orthology...and...

Other issues that have to do with the history of each base. MapMap3/Encode. Sanger based methods, about 1Mb each patient. Bottom line: found a lot of singletons. They found a few sites that were mutated independently, not heritable.

Other is MiCorTex. 15,200 people (2 loci). Looking for athlerosclerosis. Bottom line: we find a lot of low frequency variants. Sequenced so many people, you can make predictions (“The coalescent”). Sample size is now a significant fraction of population, so the statistics change. All done with Sanger!

Change error modeling – went back to original sequencing and got more information on nature of calls. Decoupling of Ne and Mu in a large sample data.

In the works: represent Snp error rates estimates with genotype likelihood.
1000 genomes pilot 3 project. If high penetrance variants are out there, wouldn't it be nice to know what they're doing and how. 250 samples accumulated so far.

Some early data: propensity for non-sense mutations.
Methods have evolved considerably
whole exome
variants will be converted to assays
data merged with other functional variants.

Both whole genome and capture are both doing well.
Focus is now back on rare variants
platform comparison also good
Db's still need work
site specific info is growing
major challenge of variants understanding can be achieved by ongoing functional studies and improve context.



Post a Comment

<< Home