## Thursday, March 6, 2014

### Blogging My Genome, episode 2: scratching the surface

After learning about Illumina's Understand Your Genome (UYG) program at ASHG 2013, I decided to sign up to get my genome sequenced. This is the second in a series of blog posts I'll write about my own adventure in very personal genomics!

Three months after shipping my blood sample off to the lab for whole-genome sequencing (WGS), I got the long-awaited message to come in and go over my results. And so on a rainy Friday afternoon I biked over to Stanford for genetic counseling. I was very excited, and yet not without awareness of the ~1% chance I could see one of the known pathogenic findings on the American College of Medical Genetics list for genome sequencing reports, and perhaps up to ~5% chance of some other medically actionable finding.

Fortunately, nothing like that came up. In fact, my report is quite unremarkable, which is of course a good thing:

## Saturday, March 1, 2014

### Blogging My Genome, episode 1: parting with my blood (and treasure)

After learning about Illumina's Understand Your Genome (UYG) program at ASHG 2013, I decided to go ahead and sign up to get my genome sequenced. This is the first in a series of blog posts I'll write about my own adventure in very personal genomics!

UYG gets you:
• "Deep" whole-genome squencing (WGS) from a blood sample
• Bioinformatics and clinical interpretation through Illumina's CLIA lab
• Report sent to your clinician
• Raw data on a portable hard drive
• Day-long workshop with other participants
• iPad with the MyGenome app
...for $5,000, which isn't too bad given what's included. The pricing probably reflects that the program is mainly an outreach effort aimed at subject matter experts. ## Sunday, January 5, 2014 ### Ribosome profiling confirms widespread stop codon readthrough in flies A recent eLife paper from the Weissman lab at UCSF uses high-throughput ribosome profiling to show that many Drosophila melanogaster (fruitfly) genes undergo an unusual translation process called stop codon readthrough - confirming many of, and expanding on, our earlier predictions based on computational comparative genomics. Stop codon readthrough occurs when a translating ribosome reaches an in-frame stop codon in an mRNA but, instead of terminating as usual, continues on with translation - as if the stop codon were a sense codon. This gives rise to a protein isoform with an extended C-terminal region, potentially modifying its function or localization. Stop codon readthrough is a long-known but fairly obscure "recoding" mechanism, which wasn't believed to play a widespread role in metazoan gene expression, save for selenoproteins and a few other intriguing but isolated examples. Now we know that it actually affects hundreds of fly genes - and moreover that, in many cases, the products confer biological functions conserved throughout many millions of years of evolution. ## Sunday, August 11, 2013 ### Building OCaml programs in Cloud9 IDE Cloud9 IDE is one of several new cloud-based products providing the ability to edit, build, test, and deploy code through a collaborative web application. Cloud9 IDE has one especially powerful feature: each workspace (i.e. project or repo) has a Linux home directory persisted along with the code and other settings, and you get a full bash terminal in this directory with modest but usable resource limits. This means it's possible to install and use a full OCaml toolchain inside, much like my previous effort on Travis CI. I prepared a script to automate the process of installing OCaml and OPAM inside a Cloud9 IDE workspace. Enter into the terminal in any workspace: curl -L https://raw.github.com/mlin/c9-ocaml/master/c9-ocaml.sh | bash -ex eval$(opam config env)
The OCaml toolchain and OPAM are then ready to go. Here's a screenshot of compiling and running 'Hello, world!':

## Sunday, July 28, 2013

### The human population harbors 172 mutations per non-lethal genome position. What'll happen to them?

A recent Panda's Thumb post highlighted that, given the size of the human genome, the rate of de novo point mutations, and the total size of the population, every non-lethal position can be expected to vary - meaning that, for every genome position or site, there's very likely at least one person (and usually dozens or more) with a new mutation there, so long as it's non-lethal. It's a trivial calculation and, while we could refine it in various ways, the essential point is clear.

 "We are all, regardless of race,genetically 99.9% the same." Right or wrong?
Still, let's try to understand this a bit further. First, an equally simple, entirely compatible fact which might attenuate our surprise: the existence of a couple hundred people with new mutations in a certain site leaves about seven billion without a new mutation there. Indeed, at the vast majority of sites, almost all people are homozygous for the same allele - identical by descent from the hominid lineage.

In that light, here's a deep question one can ask about all those hundreds of billions of de novo mutations: what will be their ultimate fate? Will they all shuffle through the future human population, making our genome's future evolution look like the reels on a slot machine? Or is it going to be rather more like the pitch drop experiment?