On the 30th Anniversary of DNA Sequencing in Population Genetics
30 years ago today, the “struggle to measure genetic variation” in natural populations was finally won. In a paper entitled “Nucleotide polymorphism at the alcohol dehydrogenase locus of Drosophila melanogaster” (published on 4 Aug 1983), Martin Kreitman reported the first effort to use DNA sequencing to study genetic variation at the ultimate level of resolution possible. Kreitman (1983) was instantly recognized as a major advance and became a textbook example in population genetics by the end of the 1980s. John Gillespie refers to this paper as “a milestone in evolutionary genetics”. Jeff Powell in his brief history of molecular population genetics goes so far as to say “It would be difficult to overestimate the importance of this paper”.
Arguably, the importance of Kreitman (1983) is perhaps greater now than ever, in that it provides both the technical and conceptual foundations for the modern gold rush in population genomics, including important global initiatives such as the 1000 Genomes Project. However, I suspect this paper is less well know to the increasing number of researchers who have come to studying molecular variation from routes other than through a training in population genetics. For those not familiar with this landmark paper, it is worth taking the time to read it or Nathan Pearson’s excellent summary over on Genomena.
Go to the original and you’ll see that those paragraphs are full of links: On the 30th Anniversary of DNA Sequencing in Population Genetics. As are the later paragraphs. Casey Bergman includes a statement from Kreitman’s PhD supervisor, Richard Lewontin. Here’s a little piece of it:
My sole contribution to Marty’s proposal was to say “It sounds like a great idea.” I had never thought of the idea before but it became immediately obvious to me that it was a marvelous idea.
Read the whole thing, follow some links. These are some interesting scientists who can write in a way that bicycle mechanics can understand. One of them tweeted this:
Fellow scientists, we already have simple words for high-depth (deep), low-efficiency (inefficient), &c. Use them. #needlessnominalization
Good advice for English majors, too.