From the Library of Prof. William B. Provine

I just saw the sad news that Will Provine, historian of population genetics, died peacefully at his home at the age of 73. Others will no doubt write of Provine’s legacy as a scholar and orator of the highest calibre, a fervent proponent of atheism and evolution that only a preacher’s son could be. I’m moved by his death to recall my experience of having Provine as a lecturer during my undergrad days at Cornell 20 years ago, where his dramatic and entertaining style drew me fully into evolutionary biology, both as a philosophy and as a profession. I can’t say I knew Provine well, but I can say our interactions left a deep impression on me.  He was an incredibly kind and engaging, pulling you onto what he called the “slippery slope” where religious belief must yield to rationalism.

I vividly recall Provine giving me a hard cover copy of the compendium of Dobzhansky’s papers he co-edited on our first meeting after class (pulled from a half-full box at the ready near his desk), and discussing the then-recent death of Motoo Kimura, who he was researching for his as-yet-unpublished history of the Neutral Theory. We met and talked about population genetics and molecular evolution several times after that, and for reasons I can’t quite recall, Provine ended up offering me keys to his personal library in the basement of Corson Hall. I’ll never forget the first time he showed me his library, with bookshelves lining what would have been a lab space, filled with various version of classic works in Genetics, Evolution, Development and History of Science. The delight he had in showing me his shelf of various editions of the Origin of Species was only matched by the impish pleasure he had in showing me the error in chromosome segregation on the spine of the first edition of Dobzhansky’s Genetics and the Origin of Species, or how to decode the edits to text of Fisher’s Genetical Theory of Natural Selection (see figure below).


In my first tour of his library, Provine showed me how to decode the revisions to the 1958 second edition of Fisher’s Genetical Theory of Natural Selection. Notice how the font in paragraph 2 is smaller that in paragraphs 1 and 3. Text in this font was added to the original plates prior to the second printing. Provine then handed me one of the many copies of this book he had on his shelf for me to keep, which is one of my few prized possessions.

His reprint collection was equally impressive (inherited from Sewall Wright from what I understand), with many copies signed, with compliments of the author, by the founders of the Modern Synthesis. Provine’s reprint collection was surpassed in value only by the FlyBase reprint collection in the Dept of Genetics in Cambridge, in my experience. I used Provine’s library to study quite often in my last year or so at Cornell, interrupting work on Alex Kondrashov’s problem sets by browsing early 20th century biology texts. Being able to immerse myself in this trove of incredible books left a lasting effect on me, and I have no doubt was a major factor in deciding to pursue academic research in evolution and genetics. Sadly while no longer physically intact, I am very glad to know the 5,000+ items in Provine’s library have been contributed to the Cornell Library, possibly the best place for the spirit of an atheist and historian to live on.

Incentivising open data & reproducible research through pre-publication private access to NGS data at EBI

Yesterday Ewan Birney posted a series of tweets expressing surprise that more people don’t take advantage of ENA’s programmatic access to submit and store next-generation sequencing (NGS) data to EBI, that I tried to respond to in broken twitter English. This post attempts to clarify how I think ENA’s system could be improved in ways that I think would benefit both data archiving and reproducible research, and possibly increase uptake and sustainability of the service.

I’ve been a heavy consumer of NGS data from EBI for a couple of years, mainly thanks to their plain-vanilla fastq.gz downloads and clean REST interface for extracting NGS metadata. But I’ve only just recently gone through the process of submitting NGS data to ENA myself, first using their web portal and more recently taking advantage of REST-based programmatic access. Aside from the issue of how best to transfer many big files to EBI in an automatic way (which I’ve blogged about here), I’ve been quite impressed by how well-documented and efficient ENA’s NGS submission process is. For those who’ve had bad experiences submitting to SRA, I agree with Ewan that ENA provides a great service, and I’d suggest giving EBI a try.

In brief, the current ENA submission process entails:

  1. transfer of user’s NGS data to EBI’s “dropbox”, which is basically a private storage area on EBI’s servers that requires user/password authentication (done by user).
  2. creation and submission of metadata files with information about runs and samples (done by user)
  3. validation of data/metadata and creation of accession numbers for the projects/experiments/samples/runs (done by EBI)
  4. conversion of submitted NGS data to EBI formatted version, giving new IDs to each read and connecting appropriate metadata to each NGS data file (done by EBI)
  5. public release of accession-number based annotated data (done by EBI on the user’s release date or after publication)

Where I see the biggest room for improvement is in the “hupped” phase when data is submitted but private.  During this phase, I can store data at EBI privately for up to two years, and thus keep a remote back-up of my data for free, which is great, but only in its original submitted format  I can’t, however, access the exact version of my data that will ultimately become public, i.e. using the REST interface with what will be the published accession numbers on data with converted read IDs.  For these reasons, I can’t write pipelines that use the exact data that will be referenced in a paper, and thus I cannot fully verify that the results I publish can be reproduced by someone else. Additionally, I can’t “proof” what my submission looks like, and thus I have to wait until the submission is live to make any corrections to my data/metadata if they haven’t been converted as intended. As a work around, I’ve been releasing data pre-publication, doing data checks and programming around the live data to ensure that my pipelines and results are reproducible. I suspect not all labs would be comfortable doing this, mainly for fear of getting scooped using their own data.

In experiencing ENA’s data submission system from the twin viewpoints of a data producer and consumer, I’ve had a few thoughts about how to improve the system that could also address the issue of wider community uptake. The first change I would suggest as a simple improvement to EBI’s current service would be to allow REST/browser access to a private, live version of formatted NGS data/metadata during the “hupped” phase with simple HTTP-based password authentication.  This would allow users to submit and store their data privately, but also to have access to the “final” product prior to release. This small change could have many benefits, including:

  • incentivising submission of NGS data early in the life-cycle of a project rather than as an after-thought during publication,
  • reducing the risk of local data loss or failure to submit NGS data at the time of publication,
  • allowing distributed project partners to access big data files from a single, high-bandwith, secure location,
  • allowing quality checks on final version of data/metadata prior to publication/data release, and
  • allowing analysis pipelines to use the final archived version of data/metadata, ensuring complete reproducibility and unified integration with other public datasets.

A second change, which I suspect is more difficult to implement, would be to allow users to pay to store their data for longer than a fixed period of time. I’d say two years is around the lower time limit from when data comes off a sequencer to a paper being published. Thus, I suspect there are many users who are reluctant to submit and store data at ENA prior to paper submission, since their data might be made public before they are ready to share. But if users could pay a modest monthly/quarterly fee to store their data privately past the free period up until publication, this might encourage them to deposit early and gain the benefits of storing/checking/using the live data, without fear that their data will be released earlier than they would like. This change could also lead to a new, low-risk funding stream for EBI, since they would only be charging for more time to private access for data already that is already on disk.

The extended pay-for-privacy model works well for both the user and the community, and could ultimately encourage more early open data release. Paying users will benefit from replicated, offsite storage in publication-ready formats without fear of getting scooped. This will come as a great benefit to many users who are currently struggling with local NGS data storage issues. Reciprocally, the community benefits because contributors who want to pay for extended private data end up supporting common infrastructure disproportionately more than those who release data publicly early. And since it becomes increasingly costly to keep your data private, there is ultimately an incentive to make your data public. This scheme would especially benefit preservation of the large amounts of usable data that go stale or never see the light of day because of delays or failures to write up and thus never get submitted to ENA. And of course, once published, private data would be made openly available immediately, all in a well-formatted and curated manner that the community can benefit from. What’s not to like?

Thoughts on if, or how, these half-baked ideas could be turned into reality are much appreciated in the comments below.

Multi-sample SNP calling circa 1994

Last November, when news of Fred Sanger‘s death was making its way around scientific circles, so too were many images of Sanger DNA sequencing reactions visualized as autoradiograms. These images brought back memories of a style of Sanger sequencing gel that I first saw in an undergraduate class on population genetics taught by Charles (“Chip”) Aquadro at Cornell University in the autumn of 1994, which left a deep impression on me. My personal photograph 51, if you will.

At the time, I was on course to be a high-school biology teacher, a plan that was scuppered by being introduced to the then-emerging field of molecular population genetics covered in Aquadro’s class. I distinctly remember Aquadro putting up a transparency on the overhead showing an image of a Sanger gel where each of the four bases were run in sets that included each individual in the sample, allowing single nucleotide polymorphisms (“SNPs”) to be easily identified by eye. This image made an extremely strong impression on me, transforming the abstract A and a alleles typically discussed in population genetics into concrete molecular entities. Together with the rest of the material in Aquadro’s class, this image convinced me to pursue a career in evolutionary genetics.

I emailed Aquadro around that time last year to see if he had such an image digitized, and he said he’d try to dig one out. A few weeks ago he sent me the following image, which shows the state-of-the-art in multi-sample SNP calling circa 1994:


Multi-sample Sanger sequencing gel of a fragment of the Drosophila melanogaster rosy (Xdh) gene (credit: Charles Aquadro). The first four lanes represent the four bases of the “reference” sequence, followed by four sets of lanes (one for each base) containing sequencing reactions for each individual in the sample. Notice how when a band is missing from a set for one individual, it is present in a different set for that same individual. This format allowed the position and identity of variable sites in a sample to be identified quickly, without having to read off the complete sequence for each individual.

For those of us who now perform multi-sample SNP calling at the whole-genome scale using something like a Illumina->BWA->SAMtools pipeline, it is sometimes hard to comprehend how far things have progressed technologically in the last 20 years.

Perhaps equally dramatic are the changes in the larger social and scientific value placed on the use of sequence analysis and the identification of variation in natural populations. At that time, the Aquadro lab was referred to in a friendly, if somewhat disparaging, way as the “Sequence and Think Lab” by others in the department (because “all they do in that lab is sequence and think”). As the identification of natural molecular variation in humans quickly becomes the basis for personalized medicine, and as next-generation sequencing is incorporated into more basic molecular biological techniques, it is impressive to see how quickly the “sequence and think” model has moved from a peripheral to a central role in modern biology.


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 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.

As with other landmark scientific efforts, I am intrigued by how such projects and papers come together. Powell’s “brief history” describes how Kreitman arrived at using DNA to study variation in Adh, including some direct quotes from Kreitman (p. 145). However, this account leaves out an interesting story about the publication of this paper that I had heard bits and pieces of over time. Hard as it may be to imagine in today’s post-genomic sequence-everything world, using DNA sequencing to study genetic variation in natural populations was not immediately recognized as being of fundamental importance, at least by the editors of Nature where it was ultimately published.

To better understand the events of the publication of this work, I recently asked Richard Lewontin, Kreitman’s PhD supervisor, to provide his recollections on this project and the paper. Here is what he had to say by email (12 July 2013):

Dear Casey Bergman

I am delighted that you are commemorating Marty’s 1983 paper that changed the whole face of experimental population genetics. The story of the paper is as follows.

It was always the policy in our lab group that graduate students invented their own theses. My view was (and still is) that someone who cannot come up with an idea for a research program and a plan for carrying it out should not be a graduate student. Marty is a wonderful example of what a graduate student can do without being told what to do by his or her professor. Marty came to us from a zoology background and one day not very long after he became a member of the group he came to me and asked how I would feel about his investigating the genetic variation in Drosophila populations by looking at DNA sequence variation rather than the usual molecular method of looking at proteins which then occupied our lab. 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.  So Marty went over on his own initiative, to Wally Gilbert’s lab and learned all the methodology from George Church who was then in the Gilbert lab.

After Marty’s work was finished and he was to get his degree, he wrote a paper based on his thesis and, with my encouragement, sent the paper to Nature. He offered to make me a co-author, but I refused on long-standing principle. Since the idea and the work were entirely his, he was the sole author, a policy that was general in our group. I had no doubt that it was the most important work done in experimental population genetics  in many years and Nature was an obvious choice for this pathbreaking work.

The paper was soon returned by the Editor saying that they were not interested because they already had so many papers that gave the DNA sequence of various genes that they really did not want yet another one! Obviously they missed the point. My immediate reaction was to have Marty send the paper to a leading influential British Drosophila geneticist who would obviously understand its importance, asking him to retransmit the paper to Nature with his recommendation. He did so and the Editor of Nature then accepted it for publication. The rest is history.

Our own lab very quickly converted from protein electrophoresis to DNA sequencing, and I spent a lot of time using and updating the computer interface with the gel reading process, starting from  Marty’s original programs for reading gels and outputting sequences. We never went back to protein electrophoresis. While protein gel electrophoresis certainly revolutionized population genetics, Marty’s introduction of DNA sequencing as the method for evolutionary genetic investigation of population genetic issues was a much more powerful one and made possible the testing of a  variety of evolutionary questions for which protein gel electrophoresis was inadequate. Marty deserves to be considered as one of the major developers of evolutionary and population genetics studies.

Yours ,

Dick Lewontin

Some may argue that Kreitman (1983) did not reveal all forms of genetic variation at the molecular level (e.g. large-scale structural variants) and therefore does not truly represent the “end” of the struggle to measure variation. What is clear, however, is that Kreitman (1983) does indeed represent the beginning of the “struggle to interpret genetic variation” at the fundamental genetic level, a struggle that may ultimately take longer then measuring variation itself. According to Maynard Olson interpreting (human) genomic variation will be a multi-generational effort “like building the European cathedrals“. 30 years in, Olson’s assessment is proving to be remarkably accurate. Here’s to Kreitman (1983) for laying the first stone!

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Calvin Bridges, Automotive Pioneer

Calvin Bridges in 1935 (Photo Credit: Smithsonian Institution Collections SIA Acc. 90-105 [SIA2008-0022])

Calvin Bridges (1889-1938) is perhaps best known as one of the original Drosophila geneticists in world. As an original member of Thomas Hunt Morgan’s Fly Room at Columbia University, Bridges made fundamental contributions to classical genetics, notably contributing the first paper ever published in the journal Genetics. The historical record on Bridges is scant, since Morgan and Alfred Sturtevant destroyed Bridges’ papers after his death to preserve the name of their dear friend whose politics and attitudes to free love were radical in many ways. Morgan’s biographical memoir of Bridges presented to the National Academy of Sciences in 1940 contains very little detail on Bridges’ life, and this historical black hole has piqued my curiosity for some time.

Recently, I stumbled across a listing in the New York Times for an exhibit in Brooklyn recreating the original Columbia Fly Room, which will be used as a set in an upcoming film of the same name directed by Alexis Gambis. Gambis’ film approaches the Fly Room from the perspective of a visit to the lab by one of Bridges children, Betsy Bridges. I recommend other Drosophila enthusiasts to check out The Fly Room website and follow @theflyroom and @alexisgambis on Twitter for updates about the project.

In digging around more about this project, I found a link to the Kickstarter page that was used to raise funds for the film. This page includes an amazing story about Bridges that I had never heard about previously. Apparently, after Morgan and his group moved to Caltech in 1928, Bridges built from scratch a futuristic car of his own design called “The Lightening Bug”. This initially came a big surprise to me, but on reflection it is in keeping with Bridge’s role as the main technical innovator for the original Drosophila group. For example, Bridges introduced the binocular dissecting scope, the etherizer, the controlled temperature incubator, and agar-based fly food into the Drosophilist’s toolkit.

Here is a clipping from Modern Mechanix from Aug 1936 describing the Lightening Bug:

Coverage of Calvin Bridge’s Lightning Bug in Modern Mechanix (Aug 1936).

Bridge’s Lightening Bug was notable enough to be written up in Time Magazine in May 1936, which described his car as follows:

It is almost perfectly streamlined, even the license plates and tail-lamp being recessed into the body and covered with Pyralin windows flush with the streamlining. There are no door handles; the doors must be opened with special keys. Dr. Bridges pronounced the Lightning Bug crash-proof and carbon-monoxide-proof. “My whole aim,” said he, “was to show what could be done to attain safety, economy and readability in a small car.”

Newshawks discovered that for months, when he got tired of looking at fruit flies, the geneticist had retired to a garage, put on a greasy jumper and worked on his car far into the night, hammering, welding, machining parts on a lathe. Now & then, the foreman reported, Dr. Bridges hit his thumb with a hammer. Once he had to visit a hospital to have removed some tiny bits of steel which flew into his eyes. It was Calvin Bridges’ splendid eyesight which first attracted Dr. Morgan’s interest in him when Bridges was a shaggy, enthusiastic student at Columbia.

Calvin Bridges next to the Lightening Bug (Time Magazine, 4 May 1936).

Gambis has also posted a video of the Lightening Bug being driven by Bridges taken by Pathé News. Gambis estimates this clip was from around 1938, but it is probably from 1936/7 since Bridges died in Dec 1938 and by the time Ed Novitski started graduate school at CalTech in the autumn of 1938 Bridges was terminally ill, but appears fit in this clip.  This clip clearly shows the design of Bridges’ Lightening Bug was years ahead of its time in comparison to the other cars in the background. I also would wager this is the only video footage in existence of Calvin Bridges.

The only other information I could find on the web about the Lightening Bug was a small news clipping that was making the rounds in local new April/May 1936:


Interestingly, the only mention I can find of this story in historical accounts of the Drosophila group is one parenthetical note by Shine and Wrobel in their 1976 biography of Morgan that had previously escaped my notice. On page 120, they discuss how Morgan handled the receipt of his 1933 Nobel Prize in Physiology or Medicine (emphasis mine):

…Morgan was very modest about the honor. He frequently pointed out that it was a tribute to experimental biology than to any one man….As Morgan acknowledged the joint nature of the work, he divided the tax-free $40,000 award equally among his own children and those of Bridges and Sturtevant (but not of Muller’s). He gave no reason; in the letter to Sturtevant for example, he said merely I’m enclosing some money for your children. (Bridges, however, is said to have used his to build a new car.)

So there you have it: Calvin Bridges, Drosophila geneticist, was also an unsung automotive pioneer whose foray into designing futuristic cars was likely funded in part by the proceeds of the 1933 Nobel Prize!

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Directed Genome Sequencing: the Key to Deciphering the Fabric of Life in 1993

Seeing the #AAASmtg hashtag flowing on my twitter stream over the last few days reminded my that my former post-doc advisor Sue Celniker must be enjoying her well-deserved election to the American Association for the Advancement of Science (AAAS). Sue has made a number of major contributions to Drosophila genomics, and I personally owe her for the chance to spend my journeyman years with her and so many other talented people in the Berkeley Drosophila Genome Project. I even would go so far as to say that it was Sue’s 1995 paper with Ed Lewis on the “Complete sequence of the bithorax complex of Drosophila” that first got me interested in “genomics.” I remember being completely in awe of the Genbank accession from this paper which was over 300,000 bp long! Man, this had to be the future. (In fact the accession number for the BX-C region, U31961, is etched in my brain like some telephone numbers from my childhood.) By the time I arrived at BDGP in 2001, the sequencing of the BX-C was already ancient history, as was the directed sequencing strategy used for this project.  These rapid changes made discovery of a set of discarded propaganda posters collecting dust in Reed George’s office that were made at the time (circa 1993) extolling the virtues of “Directed Genome Sequencing” as the key to “Deciphering the Fabric of Life” all the more poignant. I dug a photo I took of one of these posters today to commemerate the recognition of this pioneering effort (below). Here’s to a bygone era, and hats off to pioneers like Sue who paved the road for the rest of us in (Drosophila) genomics!


From Electron to Retrotransposon: “-on” the Origin of a Common Suffix in Molecular Biology

Over the last year or so, I have become increasingly interested in understanding the origin of major concepts in genetics and molecular biology. This is driven by several motivating factors, primarily to cure my ignorance/satisfy my curiosity but also to be able to answer student queries more authoritatively and unearth unsolved questions in biology. One of the more interesting stories I have stumbled across relates to why so many terms in molecular biology (e.g. codon, replicon, exon, intron, transposon, etc.) end with the suffix “-on”? While nowhere as pervasive the “-ome” suffix that has contaminated biological parlance of late,  the suffix “-on” has clearly left its mark in some of the most frequently used terms the lexicon of molecular biology.

According to Brenner (1996) [1], the common use of the suffix “-on” in molecular biological terms can be traced to Seymour Benzer’s dissection of the fine structure of the rII locus in bacteriophage T4, which overturned the classical idea that a gene is an indivisible unit:

To mark this new view of the gene, Seymour invented new terms for the now different units of mutation, recombination and function. As he was a physicist, he modelled his terms on those of physics and just as electrons, protons and neutrons replaced the once indivisible atom, so genes came to be composed of mutons, recons and cistrons. The the unit of function, the cistron was based on the cis–trans complementation test, of which only the trans part is usually done…Of these terms, only cistron came to be widely used. It is conjectured that the other two, the muton and the recon, disappeared because Seymour failed to follow the first rule for inventing new words, which is to check what they may mean in other languages…Seymour’s pioneering invention of units was followed by a spate of other new names not all of which will survive. One that seems to have taken root is codon, which I invented in 1957; and the terms intron and exon, coined by Walter Gilbert, are certain to survive as well. Operon is moot; it is still frequently used in prokaryotic genetics but as the weight of research shifts to eukaryotes, which do not have such units of regulation, it may be lost. Replicon, invented by Francis Jacob and myself in 1962, seems also to have survived, despite the fact that we paid insufficient attention to how it sounded in other languages.

Thus, the fact that many molecular biological terms end in “-on” (initiated by Benzer) owes its origin to patterns of nomenclature in chemistry/nuclear physics (which itself began with Stoney’s proposal of the term electron in 1894) and the desire to identify “fundamental units” of biological structure and function.

While Brenner’s commentary provides a crucial first-hand account to understand the origin of these terms, it does not provide any primary references concerning the coining of these terms. So I’ve spent some time digging out the original usage for a number of more common molecular biology “-ons”, which I thought many be of use or interest to others.

The terms reconmuton and cistron were defined by Benzer (1957) [2] as follows:

  • Recon: “The unit of recombination will be defined as the smallest element in the one-dimensional array that is interchangeable (but not divisible) by genetic recombination. One such element will be referred to as a “recon.””
  • Muton: “The unit of mutation, the “muton” will be defined as the smallest element that, when altered, can give rise to a mutant form of the organism.”
  • Cistron: “A unit of function can be defined genetically, independent of biochemical information, by means of the elegant cistrans comparison devised by [Ed] Lewis…Such a map segment, corresponding to a function which is unitary as defined by the cistrans test applied to the heterocaryon, will be defined as a cistron.”

I have not been able to find a definitive first reference that defines the term codon the fundamental unit of the genetic code. According to Brenner (1996) [1] and US National Library of Medicine’s Profiles in Science webpage on Marshall Nirenberg [2], the term codon was introduced by Brenner in 1957 “to describe the fundamental units engaged in protein synthesis, even though the units had yet to be fully determined. Francis Crick popularized the term in 1959. After 1962, Nirenberg began to use “codon” to characterize the three-letter RNA code words” [3].

The term operon was introduced by Jacob et al. (1960) [4] and defined as follows (italics theirs):

  • Operon: “Celle-ci comprendrait des unités d’expression coordonée (opérons) constituées par un opérateur et le group de gènes de structure coodoneés par lui.”

The term replicon was introduced by Jacob and Brenner (1963) [4] and defined as follows (italics theirs):

  • Replicon: “Il est donc clair qu’un chromosome (de bactérie ou de phage) ou un épisome constitue une unité de réplication indépendante ou réplicon, dont la reproduction est régie par la présence et l’activité de certain déterminants qu’il porte. Les caractères des réplicons exigent qu’ils déterminent des systèmes spécifique gouvernant leur propre réplication.”

Near and dear to my heart is the term transposon, which was first introduced by Hedges and Jacob (1974) [7] (italics theirs):

  • Transposon: “We designate DNA sequences with transposition potential as transposons (units of transposition)”

The very commonly used terms intron and exon were defined by Gilbert (1978) [6] as follows:

  • Intron & Exon: “The notion of the cistron, the genetic unit of function that one thought to correspond to a polypeptide chain, must be replaced by that of a transcription unit containing regions which will be lost from the mature messenger – which I suggest we call introns (for intragenic regions) – alternating with regions which will be expressed – exons.”

And finally, Boeke et al. (1985) [8] defined the term retrotransposon in the following passage (italics theirs):

  • Retrotransposon: “These observations, together with the finding that introns are spliced out of the Ty upon transposition, suggest that reverse transcription is a step in the transposition of Ty elements…We therefore propose the term retrotransposon  for Ty and related elements.”

So there you have it, from electron to retrotransposon in just a few steps. I’ve left out some lesser used terms with this suffix for the moment (e.g. regulon, stimulon, modulon), so as not to let this post go -on and -on. If anyone has any major terms to add here or corrections to my reading of the tea leaves, please let me know in the comments below.

[1] Brenner, S. (1995) “Loose end: Molecular biology by numbers… one.” Current Biology 5(8): 964.
[2] Benzer, S. (1957) “The Elementary Units of Heredity.” in Symposium on the Chemical Basis of Heredity p. 70–93.  Johns Hopkins University Press
[4] Jacob, F., et al. (1960) “L’opéron: groupe de gènes à expression coordonnée par un opérateur.” C.R. Acad. Sci. Paris 250: 1727-1729.
[5] Jacob, F., and S. Brenner. (1963) “Sur la regulation de la synthese du DNA chez les bacteries: l’hypothese du replicon.” C. R. Acad. Sci 246: 298-300.
[6] Gilbert, W. (1978) “Why genes in pieces?.” Nature 271(5645): 501.
[7] Hedges, R. W., and A. E. Jacob. (1974) “Transposition of ampicillin resistance from RP4 to other replicons.” Molecular and General Genetics MGG 132(1): 31-40.
[8] Boeke, J.D., et al. (1985) “Ty elements transpose through an RNA intermediate.” Cell 40(3): 491.
Jim Shapiro (University of Chicago) gave very helpful pointers to possible places where the term “transposon” might have originally have been introduced.