I’m sitting in the auditorium of LANGEBIO, a national genomics biodiversity lab in Mexico. Perched towards the middle of a room that holds about 220 people, I’m listening to a day-long series of presentations by doctoral plant geneticists. The bare concrete walls bear streamers of sponsors, such as Illumina, Biosis, and Biosistemas Avanzados. Each speaker strides out onto an overly large stage that dwarfs them as much as the giant overhead screen, across which their presentations flash. The featured species are Zea mays and Arabidopsis thaliana (the first flowering plant to have its genome sequenced), along with varieties of yeast—all well-established model organisms upon and through which genetics steadily advances.

This is my third field stint at LANGEBIO but the first time I get such an overview of the institution. Instead of first catching up with the lab practices of particular researchers, this trip starts with the panoply of projects underway throughout LANGEBIO. So initially I’m overwhelmed and a bit disconcerted. First, I’ve focused entirely on maize and particularly “razas de maíz” or races of corn. So I’m surprised to realize this institute, founded in response to U.S. efforts to sequence the maize genome, features so much work on Arabidopsis—a plant genus with no agricultural value, but whose rapid reproductive cycles are far more conducive to publishing dictates. But I’m also overwhelmed by the slew of genetics techniques on display in the presentation. In the first paper alone (“Search and Description of New Genomic Regions Selected during the Domestication Process of Maize”): a window analysis to assess nucleotide diversity, which leads to a series of comparative studies (one for a gene encoding a S-adenosyl methyltransferase, another for one encoding an ARF-gap zinc finger protein), followed by an experimental analysis looking for genetic sweep selection during domestication, closing with coalescent simulation (CS) and Hudson-Kreitman-Aguade (HKA) statistical tests. Before the second paper (“Delving in bioinformatics of –omics data from a biochemistry background) is finished, I’m feeling unmoored.

What seemed so intelligible in lab settings spiraled quickly beyond my comprehension; due in part to my modest grasp of genetics, but also the detachment of hearing this work rendered in the abstract—that is, removed from routine, material contexts. Perhaps in a mild panic, I fall back on my ethnographic training and ask, ‘What’s cultural here?’ Of course, I turned to metaphor immediately. Even before George Marcus asserted “follow the metaphor” as a basic focus of multisited fieldwork, metaphors have long captivated ethnographers. And they’re plentiful in the presentations. Soon my notebook is jammed full of them: “window,” “signature,” and “downstream,” etc. There were ones that made me hesitate, such as “promoter” and “transcript,” but “housekeeper genes” [see Emily Martin, Flexible Bodies] “genetic architecture” seemed quite clear.

My head was buzzing with all of this during the coffee-break when Jean Philippe Vielle Calzada—the senior researcher who had generously allowed me to do fieldwork in his lab—asked me what I had observed so far. In reply, I blurted out an initial analysis of the metaphorics of genomics. I was neither disappointed nor surprised that it made so little of an impression upon him. After all, this is not an unusual reaction to science studies accounts. What did surprise me is that I experienced a moment of doubt as I heard myself talking. This doubt was amplified further in a string of such conversations with other researchers, that year and on a subsequent visit in 2014, when my words seemed to fall flat or ring hollow, even to myself.

Looking back, I recognize a disparity opened up between the kind of insight I could generate with an attention to metaphor and what the researchers depict about what is happening with these species: how their reproductive behaviors are operating in lab settings, performing in close calibration with that of other model organisms, all aligned via utterly massive comparative genetic databases around the world. For that matter, I recognized my line of analysis ran in one direction, towards ideology and what was going on in the researchers’ heads; and that inexorably this led away from the plants. Following the coffee break, as I listened to more papers, I grew more interested in the life forms they were depicting. Two realizations followed: first, that I needed the geneticists more as guides than as ideological ciphers; second, I had to follow the species (maize, in this case)—follow how its sexual history, reflecting 9,000 years of domestication, is being molded and directed to produce genetic knowledge, not just for greater yields but for insights on how companions species relations have developed and may yet unfold in the future.

John Hartigan (University of Texas, Austin) theorizes culture across species lines at www.aesopsanthropology.com and @aesopsanthro. His guest posts concern ethnography of life forms. Aesop’s Anthropology is also available in e-book format from University of Minnesota Press.

You know that little purple stone that is on the bad guys hammer? THAT IS POWER OF ANTHROPOLOGY? And what does it take fully harness that power? Four brave heroes who EACH REPRESENT ONE OF THE FOUR SUBFIELDS OF ANTHROPOLOGY. They even have to temporarily kill off Groot — who represents the maybe-fifth-subfield of applied anthropology — in order to make it work.

I’m still up in the air on who is what subfield. Right now my thinking is this: Peter Quill is cultural anthropology: The most important but also the spaciest hero. Why is he in charge, other than some sort of default assumption that white guys are the lead hero even when they don’t even do ethnography any more and are just charming con artists. Gamora represents linguistic anthropology: overly-professional, uptight, kinda corky, but actually has much better fighting skills than cultural anthropology. Rocket is archaeology because material culture. Also sometimes he does cultural survey work with Groot. Drax represents bioanth because the guys is super-effective but sometimes you’re like: dude, get up out of the weeds. Some things are social constructs. TO me, Drax seems like the kind of guy who doesn’t understand why you didn’t include a p-value in your abstract.

But I could be wrong. How do you think that metaphor works out?