Scientists Complete Map of Human Genetic Variation

UltimaGuy writes "A major scientific step in the field of genetics is set to speed up the search for the causes of common illnesses ranging from heart disease and cancer to Alzheimer's and asthma. Scientists have mapped patterns of tiny DNA differences that distinguish one person from another, a step that will speed up the search for genes that promote common illnesses such as heart disease and diabetes."

Comments

Podcast from nature

[Oxen]

Here is a link to the mp3 of the Nature podcast on this.

I always think it is ridiculous how these genomic announcements happen. They choose to announce that they have ONE MILLION SNPs with big press release, but this data is available online as soon as its sequenced.

Re:Podcast from nature

[mr_stinky_britches]

Parent makes an interesting point. Here is a link a website where one can find additional information and even tab-delimited datafiles of SNPs variation and linkage.

Here is an additional site with even more information and datasets available. I'm going to download these and see what I can find.

They only analyzed DNA of 269 people

[backslashdot]

so if there are SNP mutations that only have a 1 in 270 or lesser chance of being present ..it's not going to be in their Map. You could be walking around with an SNP they missed cause the mutation happened recently (unique to you or maybe your grandparents etc) or is rare or whatever.

Re:They only analyzed DNA of 269 people

[espressojim]

You can measure SNPs that are undetected by this method by measuring haplotypes that those rare snps might occur on. Once you see an effect, then you can home in on the causal SNP.

Something that's interesting about your statement: if you look at a very rare SNP (less than 1%, for example), then you have very little power to see an effect on disease for this SNP. By definition, 99% of your sample size is not contributing power to your study. Thus, you can't statistically find effects unless you have a) massive sample size or b) massive mendelian effects.

The goal of this data is to study COMMON polymorphisms. That's why it's callled the common variant hypothesis.

And yes, I do work with these people.

RTFHM

[Anonymous Coward]

Read the friendly Haplotype Map, that is:
http://www.hapmap.org/.
You can even browse the project data: Gbrowse

Re:Great

[jrau]

Biotech companies get special compensation by the U.S. government to develop treatments for so called "orphan" diseases. They get tax breaks and exclusive market rights if they develop drugs for these conditions, and as a result there are really quite a few advancements in the treatment of rare diseases when it normally wouldn't be monetarily feasible... but of course there are tons of different wierd conditions that people have. Here is a link for the FDA website discussing this: http://www.fda.gov/fdac/features/2003/603_orphan.h tml

Re:Then what?

[temojen]

Nature finds a way to keep the population from getting too out-of-control

No, it doesn't. Organisms that survive create slightly different offspring. Those that survive create slightly different offspring. That some of these organisms create toxic secretions, block airways, kill mucous membranes, etc. is just a side effect of diversity.

Re:Patented

[lockefire]

First of all, most SNPs are free information. dbSNP contains ~5 million validated SNPs and ~27 million reported SNPs in humans. Celera owns a lot of SNP finds, but most are junk (sequencing errors) and they will be giving them to the free databases soon.

However, the importance of this article has nothing to do with the number of SNPs available or the fact that the SNPs are common (because of the low sample size). The whole point is to have SNPs that exist in ~50% of the population so that the haplotype can be determined. The Haplotype shows which segments of the genome tend to be inherited together. This can be traced back for multiple generations of inheritance - essentially there are ancient haplotypes and more modern haplotypes. The importance of looking at haplotypes is that it allows researchers to see which region an important mutation relating to a disease may occur in. Note that just by knowing which haplotype the disease causing mutation occurs in does not let us know which SNP or insertion/deletion event causes the disease.

Re:AGCT

[Spy der Mann]

AAAAGGUATCUCGCUAGCUAUTCGGGCA...GTAC, please step forward!

Uh... let's see... C...G...A...T... is that "U" a phonetic aid? Otherwise no one will step forward. Oh wait, so THAT's how they caught the undercover martian!

Genetics & drugs: good news/bad news

[G4from128k]

Genetic variations affect how people absorb drugs, metabolize drugs, are helped by drugs, or have dangerous reactions to drugs. People can vary more that 10000:1 in the rate of deactivating (or retaining) drugs and drug metabolites. This variation impacts clinic testing and drug approvals. The result is that some promising medications are knocked out by clinical testing when too few people are helped or too many people are hurt. Genetic testing would help determine which drugs work for which people. Already doctors use 3 different drugs for childhood leukemia as determined by a genetic test (the wrong drug can be lethal). Increasing use of genetic testing will have good and bad effects.

The good news: drug companies might be able to resurrect some failed medications if they can determine which genetic variants are helped by the drug versus being harmed by the drug. Some promising but previously unapproved medications will make it on to the market.

The bad news: Current drug development focuses on blockbusters. Finding something that millions of people will need to take. This pushes development to help the greatest number of people. If the treatment works for most people (based on genetic screening), there's little reason to develop a cure for genetic minority populations. Genetic orphan populations will be marginalized.

Re:Genetics & drugs: good news/bad news

[amacbride]

If you're interested in seeing a resource dedicated to exactly this (pharmacogenomics), check out PharmGKB -- we have some interesting pathway diagrams that link individual variations to different drug responses and clinical outcomes.

A Human Geneticist's Point Of View

[kid_icarus75]

There are so many things incorrectly implied about this finding that it's almost hard to begin:

1) The headline and idea: "New DNA Map Will Help Find Bad Genes". There are no bad genes. Evolution didn't just come around and place some miscreant gene in your body just to give you a hard time after living off a diet of pizza and Mt. Dew for ten years. Every gene has its own function. Genetic research is based more upon finding which variation of a gene is more beneficial to an individual and how to change/block the non-beneficial variations. Genes are either more or less successful, but definitely (minus the case or rare genetic diseases) not evil or bad.

2) "The project analyzed DNA samples from 269 people from Nigeria, Beijing, Tokyo and Utah." Well, this would be fine if everyone was of a direct Nigeria, Beijing, Tokyo or Utah decent similar to the test subjects. As for real world population, they probably contain mutations not near those found in any of these people. A native american, a man from agentina, and a guy from India I guarantee you would have completely different results. And that's assuming pure-bread people. Where would someone like Tiger Woods fit in? As an interesting side note, why do you think they picked Utah? Could it be that one of the principal investigators of the study is Mormon and thought it might be nice to bring government funds to his own people? I think that most of us can agree that politics and science rarely mix to give good results...

3) 269 People? You're telling me that out of 3 billion DNA basepairs, we can find all the parts that have changed over the last few hundred thousand (and more) years in only 269 people?

4) "This clustering greatly simplifies the task of analyzing what variations a person carries, because not all of them have to be identified." and "A person with one particular version of a SNP is highly likely to carry particular versions of other SNPs as well." When you begin to think about the error rates contained in "highly likely" and then start to cluster those rates togeter, your model falls apart.

Basically, from my own experience of working with data of thousands of whites, blacks, both male and female, the rates at which certain areas of DNA are linked vary directly upon the strata one looks at and the number of individuals in that strata. This project is a neat theorhetical idea, but until we can sequence the entire genomes of thousands of people overnight for a small fee, there is not enough realy data to really do anything with.

Re:A Human Geneticist's Point Of View

[espressojim]

I suggest that you
a) Read the paper.
b) Read the followup papers that also discuss in more detail how to use this data to perform analysis.

Q#2: If you're interested in how well this data transfers over to people from other populations, then read the "tag transfer" paper, which should be out in a month or so. Paul de Bakker will have a paper comming out that studies how to apply this data to other populations. The quick summary: you can use this data for other populations. By studying groups like Yoruba (african) populations, you're capturing the most human variation that we all derive from. After the population bottleneck (40,000 years ago), we split into multiple groups, so we included european descent (utah, it's complicated, it's mormons), and chinese and japanese samples. That gets MOST variation.

The new hapmap has already been release at 5x the density.

#3 See answer #2, but yes, you can find MOST of the variation. With the current map, you can indirectly measure 90% of variation in humans. See a paper by Itsik Pe'er for more information.

#4 No. When you have highly correlated R^2 values, and you have more than one, you can predict things. You also probably don't understand how mutations are organised on haplotypes, and how these ancestral chuncks of DNA essentially keep the same set of bases together. Yes, these haplotypes are broken down over time (the african ones are smaller than the european ones, again because the effective population size is smaller in europe and because of the bottleneck event), but still allow for prediction.

I gotta wonder who you work for...I spend a fair amount of my time at the Broad, where most of this research has gone on, so I might have quite a bit more insight into it than outsiders (having seen the work as it was developed, having talked to the researches, etc.)

Re:A Human Geneticist's Point Of View

[espressojim]

Do yourself a favor and look at David Reich's papers on Admixture mapping. That might be what you're referring to, or it might not. I'd agree with you that there's a lot of population structure (and substructure!) that most studies don't take into account.

You can use that (admixture mapping), or you can try to reduce that.

By the way, those 80-1000 SNP models are becomming very old school (if you're using a candidate gene approach, the one thing we know about candidate gene approaches is that we're horrible about picking the right genes.) We're starting to get data back on our Affy 500,000 SNP chips (actually 2 250K chips) done across thousands of individuals. The real problem is processing all that data...but the next year or so is going to be VERY exciting for a bunch of different initiatives like diabetes (type II), bipolar disorder, etc.

We are not trying to trick nature.

[hackwrench]

Nature doesn't have goals to be tricked out of. Nature doesn't have beliefs to be fooled out of believing.

Coordinators

Abh

No rare alleles in data

[John Hawks]

Actually, the HapMap is basically useless for "rare" genetic variants, because it intentionally is screening for common ones. Hence, it may actually be useful for common susceptibility alleles for heart disease or stroke but it isn't going to find the rare variants that affect only a few people.

From my weblog:

The HapMap is an incredible step forward in characterizing human genetic variation. It's a challenging dataset to work with, though. It's like an old map showing continent margins and little else -- we can see many of the common SNPs, but for most we have no idea which ones are functional or what they might do.

--John

Another article on mapping genes...

[Lord Satri]

Here's another study regarding mapping genes. There's a lot of research being done and it is being more and more interdisciplinary, which is a good thing if you want a big picture to find clues and solutions.

GeoPlace reports a story on project METAFUNCTIONS from Informationsdienst Wissenschaft about mapping environmental clues to decipher the function of genes. "Another innovative aspect of this project [METAFUNCTIONS] is the use of geographic information systems (GIS). GIS tools provide for the simulation and analysis of events from a geographical or spatial perspective. Novel patterns - for example, the physical clustering of genes within a genome - will be correlated to the contextual habitat data."