Friday Links

Two exciting-looking new science blogging collectives have been announced this week. The Public Library of Science launched a new blogging collective, including personal genomics blogger Misha Angrist, and the Guardian newspaper has launched its Guardian Science Blogs network, including Dr Evan Harris, ex-MP for Oxford West and long time supporter of the role of science in public policy. I’m pretty excited about these new blogs, but it does stand to increase my RSS load significantly. [LJ]

In this month’s issue of European Journal of Human Genetics, Yang, Visscher and Wray contribute to the discussion around the aetiology of common complex diseases.  They demonstrate that the existence of a large number of sporadic cases (instances where a patient has no first, second, or third-degree relatives with the disease) is not incompatible with a polygenic model of disease.  A little less hot-off-the-press are two opinion pieces on genetic testing regulation from the August issue of Nature.  Arthur Beaudet argues that stringent government regulation should be applied to genotyping/sequencing, and interpretation should be the exclusive domain of the medical profession.  Gail Javitt takes a different view, arguing that genetic tests to be treated in the same way as other medical tests and that the level of regulation imposed should be determined by medical relevance of the outcome. [KIM]

Finally, Procreation News; our very own Daniel MacArthur and Ilana Fisher have recently given birth to a baby boy (the picture to the left may be a little out of date). Daniel made the announcement on Twitter, and also had this to say:

After careful inspection, I’ve decided that my six-day-old son is the most remarkable human being to have ever lived.

Due to double blinding, neither we nor Daniel know whether he has an actual or placebo baby, so we can’t yet assess the significance of this claim. Watch this space! [LJ]

Basics: Second-Generation Sequencing

This is an edited repost of a year-old article from my blog Genetic Inference. It explains how the state-of-the-art Second Generation sequencing works, and how it is being used to sequence thousands of genomes per day. I also try to explain some of the distinctions between First, Second and Third Generation sequencing.

This post follows on from an even older post that explained First Generation sequencing; the tech that was used in the Human Genome Project.

Recap: What are we trying to do?

In a previous post, we saw how DNA is made up of little strings of nucleotides, and we used different shapes to represent different base pairs (A = triangle, C = diamond, G = circle, T = pentagon). For instance, stage20_1 is GCAT.

We looked at how the DNA polymerase enzyme can be used to amplify up DNA, using the Polymerase Chain Reaction, and how we can determine the sequence of DNA using ddNTPs; nucleotides that, when incorporated into DNA, stop the polymerase working.

In First Generation (Sanger) sequencing, we run a PCR reaction in the presence of a bunch of ddNTPs, with each different base pair dyed a different colour. We then measure the length and colour of the resulting fragments of DNA, and use that to work out the sequence; a bit of DNA 35 base pairs long ending in a blue ddNTP tells us that the sequence has a “C” at the 35th position.

The problem with this method is that it requires a lot of space; you need a place to run the reaction, and then you need a capillary tube or a gel to determine the length of the DNA. As a result, you could only run perhaps a hundred of these reactions at any one time. There are 3 billion base pairs of DNA in the human genome, meaning about 6 million 500-base pair fragments of DNA; it would take a very long time to sequence all of these if you had to do them one hundred at a time.

Second Generation sequencing techniques overcome this restriction by finding ways to sequence the DNA without having to move it around. You stick the bit of DNA you want to sequence in a little dot, called a cluster, and you do the sequencing there; as a result, you can pack many millions of clusters into one machine. Sequencing a strand of DNA while keeping it held in place is tricky, and requires a lot of cleverness. I’ll explain how Illumina‘s Second Generation technology achieves this, as it is the most similar to Sanger sequencing.

Continue reading ‘Basics: Second-Generation Sequencing’

Friday links

Welcome to the inaugural Friday links post. We’ll be using these posts to share interesting articles stumbled across by Unzipped members during the week.

We’re still tweaking the format, but the basic idea will be a brief paragraph of commentary followed by the initials of the person who wrote it.

Dan Koboldt reviews a recent paper reporting the use of whole-genome sequencing to find the mutation responsible for a severe genetic disease. Interestingly, in this case the disease was undiagnosed, and the causal variant was used to produce a diagnosis of sitosterolemia; more interestingly, this diagnosis had already been ruled out by another test, that was shown to be a false negative. [DM]

Sitting Bull Stamp ScienceNews reports that researchers from the University of Copenhagen have got permission to sequence the genome of Sitting Bull, the native American war chief that led the battle of Little Bighorn. I don’t know exactly what they intend to learn from the genome scientifically, but it seems like this might serve primarily as a monument to a major figure in native American resistance. So the question I have is this: how can we go from a genome sequence (which is generally just a text file on a computer) to a public rememberance, something akin to the 1989 postage stamp shown to the left? [LJ]

Two papers in the current issue of Nature Genetics highlight recent inroads made in understanding the genetics of infectious disease susceptibility. The first found an association between risk of meningococcal disease and CFH, a gene previously implicated in age related macular degeneration. The second identified a susceptibility locus for tuberculosis in African samples. Paul de Bakker and Amalio Telenti have a nice News and Views piece about them as well, remarking on this welcome advance not only in understanding infection, but also in using GWAS to gain insight about disease risk in non-Europeans. [JCB]

Update: Dan Frost from the GoldenHelix blog has drawn our attention to a thought-provoking post on the future of GWAS studies. The post suggests that much of the missing heritability in complex disease is hiding in the set of variants that are badly tagged by existing chips, and proposes that GWAS studies in the future may include a sequencing phase to discover new variants in cases, followed by genotyping using custom genotype chips to capture this variation. The question, from my point of view, is how many common SNPs are there that aren’t well tagged by existing chips, and thus how much heritability could be hidden there? This is exactly the sort of question that the 1000 Genomes dataset was designed to answer. [LJ]

Dude, where are my copy number variants?

The genome scans currently offered by major personal genomics companies provide information about only one kind of genetic variation: single nucleotide polymorphisms, or SNPs. However, SNPs are just one end of a size spectrum of variation, reaching all the way up to large duplications or deletions of DNA known as copy number variants (CNVs). Over the last decade we have learned that CNVs are a surprisingly common form of variation in humans, and they span a formidable chunk of the genome. While there are about 3M-3.5M bases of variation due to SNPs within an individual genome (in say, a typical person of European descent), there are at least 50-60M variable bases due to CNVs.

For the personal genome enthusiast with their SNP chip data from 23andMe or deCODEme in hand, there are two important practical questions: (1) can I learn about my CNVs using SNP chip data; and (2) will that information be useful?

Continue reading ‘Dude, where are my copy number variants?’

Excessive regulation of DTC genomics will come at a cost

Caroline and I have an opinion piece in this week’s New Scientist arguing that regulators should consider the benefits of personal genomics (in terms of increasing genetic literacy and innovation) before imposing excessive regulation on the direct-to-consumer genetic testing industry. Here’s the take-home message:

We don’t yet know what role personal genomics will play in the future of medicine. However, we do know that it has great potential for innovation and education, and we must ensure that neither excessive regulation nor medical paternalism get in the way.

Unfortunately due to space restrictions several sections of our argument were cut – for instance, we spent some time arguing against the idea of arbitrary divisions of tests into “medical” and “non-medical” categories, with the former requiring supervision of a medical professional to receive results. Here’s the original wording:

Unlike many commentators, including the HGC, we do not support an unsustainable division of tests into separate categories, one for health-related tests that require counselling from a medical professional and another for everything else with no such requirement. It is hard to justify the argument that results suggesting a mildly elevated predisposition to obesity require a professional intermediary to provide support, while those indicating unexpected paternity do not.

In general, we would argue that people should be free to access their own genetic data unless there is good reason to believe that doing so will cause them real harm – and as long as the information is accurate and transparent. Companies should ensure that customers have access to expert advice if they want it, but medical supervision should not be a requirement for access to your own genome.

In a similar vein, if you missed the editorial on DTC genetics in last week’s Economist, you should go read it now. The final two paragraphs warrant quoting in full:

But three things argue against wholesale regulation. First, the level of interference needs to be based on the level of risk a test represents. The government does not need to be involved if someone decides to trace his ancestry or discover what type of earwax he has. Second, the laws on fraud should be sufficient to deal with the snake-oil salesmen who promise to predict, say, whether a child might be a sporting champion. And third, science is changing very fast. Fairly soon, a customer’s whole genome will be sequenced, not merely the parts thought to be medically relevant that the testing companies now concentrate on, and he will then be able to crank the results through open-source interpretation software downloadable from anywhere on the planet. That will create problems, but the only way to stop that happening would be to make it illegal for someone to have his genome sequenced—and nobody is seriously suggesting that illiberal restriction.

Instead, then, of reacting in a hostile fashion to the trend for people to take genetic tests, governments should be asking themselves how they can make best use of this new source of information. Restricting access to tests that inform people about bad reactions to drugs could do harm. The real question is not who controls access, but how to minimise the risks and maximise the rewards of a useful revolution.

It’s great to see these issues getting sensible discussion in the wider media; let’s hope the FDA is paying attention.

A missed opportunity: what the GAO report could have told us about DTC genetic testing

The recent United States Government Accountability Office report on direct-to-consumer (DTC) genetic tests was the star attraction of a bruising Congressional hearing into the DTC industry, and sparked widespread headlines about “bogus” results from the genetic testing industry.

The report is prefaced by the statement:

GAO did not conduct a scientific study but instead documented observations that could be made by any consumer.

While it is the GAO’s prerogative to conduct their study as they see fit, we believe that they missed a valuable opportunity to survey the DTC genetic testing industry and systematically evaluate what is and isn’t being done well. In this post, we discuss how the discoveries that the GAO reported were already largely known, and assess the opportunities that the GAO missed to provide genuine insight. What could the data they collected have told us if they had decided to add a little more scientific rigour to their investigation?  

Continue reading ‘A missed opportunity: what the GAO report could have told us about DTC genetic testing’

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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Setting the record straight

The current issue of Cell has some important correspondence in response to an essay published by Jon McClellan and Mary Claire King in April. Daniel covered the original piece and hosted a guest post from Kai Wang which detailed some of the more obvious flaws in their argument. Now, Wang and his colleagues from Philadelphia have published an official response in Cell, in parallel with a similar letter from Robert Klein and colleagues from New York. Accompanying these is a further reply from McClellan and King. Read on for an overview of three contentious statements made in the original piece, and the rebuttals to each.

Continue reading ‘Setting the record straight’

The past, present and future of DTC genetic testing regulation

(Newsweek reporter Mary Carmichael has a DNA dilemma: should she buy a direct-to-consumer genetic test? To help answer that question, she’s recruited people with expertise in various areas related to personal genomics – and a diverse range of opinions about the industry – to address specific areas of concern. At the end of the week she’ll announce her decision.

This post is a brief version of Dan Vorhaus’ response to one of Mary’s questions: how should these tests be regulated? Check out the Newsweek website for other answers to the question, as well as a fantastic extended interview with two senior FDA officials. The full version of Dan’s response is now up at Genomics Law Report.

For other Unzipped contributions to Mary’s project, see Jeff Barrett’s post about risk predictions on Tuesday, and my post on test reliability and the balance between knowledge and fear yesterday. –DM)

The regulation of DTC genetic testing has been consistently characterized as confusing, incomplete and irregularly applied. Recent events – Pathway and Walgreens, a bevy of ominous FDA letters, a Congressional Hearing and a GAO report criticizing DTC genetic tests – indicate that the tide may finally be turning. Yet a brief historical review discloses that DTC has actually been down this road before. A GAO report decrying the evils of DTC genetic testing and a subsequent Congressional hearing? 2010 and 2006. Threatening regulatory letters to DTC companies? 2010 and 2008. DTC genetic testing has faced down the specter of heightened regulation before, and over the long term I am confident it will continue to do so.

Nevertheless, in the short term it is possible that DTC genetic testing will be subjected to a substantially more restrictive regulatory framework. Will DTC continue unchanged while regulators and companies engage in protracted negotiations? Will oversight weed out the ‘snake oil salesmen’ and permit legitimate companies to flourish? Or will it drive all genetic testing (temporarily) out of the hands of consumers?

I cannot advise you to take the test or not, but I can say that if you want to proceed there is no time like the present, for there is no guarantee that the option will still be on the table tomorrow.