Guest post by Charles H. Langley.

Dic, hospes, doctis caelebs animalculum obisse

hicque iacere physis legibus conveniens.

(Stranger, tell the learned that the celibate little animal has passed away, and lies here, conforming to the laws of nature.)

—John Rundin, with apologies to Simonides and Cicero

Thirty-five years ago, in a celebrated News & Views (1986) John Maynard Smith shared his well-developed thoughts about the evolutionary forces that may have maintained sex in the surviving lineages of eukaryotes. While parthenogenesis appears to be widespread, phylogenetic analyses were establishing that the overwhelming majority of the ancient and successful lineages retained sex in all its biological richness. Simple population genetic theory had long raised the question: what is the evolutionary mechanism(s) that overcomes that clear two-fold Malthusian advantage of an asexual mode of reproduction? After highlighting a number of interesting asexual species, Maynard Smith disposed of all of these as young and likely to be evolutionary dead ends. One hundred years earlier, before the rediscovery of Mendel and the development of population genetic foundations for natural selection Weismann (1887) had already surmised that natural selection favoring sexuality in multicellular organisms must be strong.

Maynard Smith cast the bdelloid rotifers as the exceptions, being perhaps 40 million years on the earth, and even after centuries of study these beloved and easily collected and cultured micro-animals had not yielded a male. Maynard Smith’s reference to the bdelloid as “something of an evolutionary scandal” energized efforts to address this assertion. Perhaps the early rotifers had evolved a creative evasion of the strong evolutionary forces maintaining sex in other eukaryotic lineages? Or were bdelloids simply ‘modest,’ pursuing sexual reproduction rarely and/or in the most obscure environments? Both these hypotheses appeared tenable, although the force of the first depends on negation of the latter.

Over the ensuing decades the natural history and systematics of bdelloids improved yet no evidence of sex emerged. Meanwhile molecular geneticist Matt Meselson and colleagues proceeded to look at the bdelloid genomes. Ancient duplications were discovered. And then Nowell et al. (2018) found evidence for the conservation in bdelloids of genes associated with meiosis throughout all eukaryotes. For unknown reasons, the simple inference of sex in the population genetics of bdelloid rotifer species was only recently addressed. Independently two research groups have now reported evidence of sex in the recent descent of distinct bdelloid species (Vakhrusheva et al. 2020) and (Laine et al. 2021). Variants at genomic locations far apart or on different chromosomes occur in combinations that strictly asexual reproduction precludes, but mere occasional sexual reproduction strongly predicts. They concluded that, despite the lack of observed mating or even of “males,” these bdelloid rotifers must have had recent sexual common ancestors. Thus the ‘scandal’ of evolutionary biology is transformed into the latest evidence driving what is perhaps the most significant and controversial question in evolutionary genetics, what force(s) maintains sex in eukaryotes.

The lifting of a scandal often engenders rectification of respect and the drawing of lessons, if not morals. The generality of the observed conservation of sex is, indeed, bolstered by the new evidence in bdelloid rotifer. It also raises other questions. Should the study of the reproductive biology of rotifers have been given tenfold more resources and talent? After all it took 35 years. Or can one suggest that this decisive evidence of bdelloid sexuality would have come in the same amount of time without the impetus of the ‘scandal?’

The real substance of Maynard Smith’s short discussion was, of course, the mechanism of the natural selection that maintained sex. The accepted competing hypotheses rest on the indirect selection induced by linkage among loci under selection. As R.A. Fisher and H.J. Muller noted in the 1930s, in the complete absence of sex, strongly favored rare variants (mutations) must arise and go to fixation in a sequential order. In contrast, sexual reproduction allows unlinked variants to respond to natural selection independently. Thus, sexual populations can more readily adapt to changing environments. And that’s what we observe, i.e., asexual lineages go extinct.

However, as H.J. Muller always wanted us to remember, the great majority of mutations are deleterious and much, if not most, of natural selection is committed to their eventual purging from the population. What Maynard Smith was at that time just beginning to appreciate and in the ensuing decades has become widely recognized, is that linkage also impedes this mode of natural selection. Thus, the selection on deleterious mutations can indirectly select in favor of sexual individuals and thereby maintain this most conserved of eukaryotic life history traits. Happily, the charming bdelloid now stands proudly at the center of inquiry into the evolutionary impact of natural selection.

Literature Cited 

Laine V. N., T. Sackton, and M. Meselson, 2021 Genomic Signature of Sexual Reproduction in the Bdelloid Rotifer Macrotrachella quadricornifera. GENETICS https://doi.org/10.1093/genetics/iyab221

Maynard Smith J., 1986 Evolution: Contemplating life without sex. Nature 324: 300–301. https://doi.org/10.1038/324300a0

Nowell R. W., P. Almeida, C. G. Wilson, T. P. Smith, D. Fontaneto, A. Crisp, G. Micklem, A. Tunnacliffe, C. Boschetti, and T. G. Barraclough, 2018 Comparative genomics of bdelloid rotifers: Insights from desiccating and nondesiccating species, (C. Tyler-Smith, Ed.). PLOS Biol. 16: e2004830. https://doi.org/10.1371/journal.pbio.2004830

Vakhrusheva O. A., E. A. Mnatsakanova, Y. R. Galimov, T. V. Neretina, E. S. Gerasimov, S. A. Naumenko, S. G. Ozerova, A. O. Zalevsky, I. A. Yushenova, F. Rodriguez, I. R. Arkhipova, A. A. Penin, M. D. Logacheva, G. A. Bazykin, and A. S. Kondrashov, 2020 Genomic signatures of recombination in a natural population of the bdelloid rotifer Adineta vaga. Nat. Commun. 11: 6421. https://doi.org/10.1038/s41467-020-19614-y

Weismann A., 1887 On the signification of the polar globules. Nature. 36:607–609. https://doi.org/10.1038/036607a0

About the author:

Charles H. Langley is Distinguished Professor of Genetics at the University of California, Davis.

From a Kyoto garden to scientific discoveries. 

Since the 17^th century, medaka fish have been bred for their beautiful colors. Shortly after the 1900 re-discovery of Mendel’s laws of inheritance, medaka began to be used for genetic studies. Recessive inheritance of the orange-red (b) and white (r) variants, female-limited appearance of the white phenotype, and an additional allele on the b locus causing variegation (B′) were reported by three professors publishing in Japanese [1–3]. The first medaka article written in English was published in 1921 by Tatsuo Aida (1872-1957). One hundred years after publication of this landmark article in GENETICS, we reflect on Aida’s work and legacy.

When he was four years old, Aida’s samurai father cut off a thief’s arm, which remained a traumatic memory throughout his life. He liked playing in a neighboring farm in Kyoto, where he nursed his interests in zoology. He studied development and phylogeny of Chaetognaths at Tokyo Imperial University, but, due to a conflict with his supervisor, left there before getting his PhD and became a teacher in a high school in Kumamoto, where Soseki Natsume, a Japanese novelist, worked as a colleague. Besides his daily duties, he studied Larvaceans for five years and reported four new species [4]. 

When his father died, Aida returned to Kyoto in 1903. Teaching at Kyoto Higher Technical School, he started genetic studies in 1913 in his own home. He chose medaka because the fish could be bred en masse in small flowerpots, sex could be determined from appearance, and color variants were available from local fanciers. Studies of plants or mice would have required much larger spaces. Supported by Genzo Shimazu (a president of Shimadzu Corporation, where Aida was a counselor for zoological specimens), he constructed a breeding farm at his home consisting of 40 concrete tanks of 60 x 60 x 45 cm and 200 Yuzen dyeing pots of 30 cm diameter x 10 cm depth. Recording weather and air/water temperatures every day, he continued his research until 1954 at an age of 83. 

His results were published as three articles in GENETICS. In the first [5], Aida performed a total of 22 crosses of two generations, recorded body color of 17,281 fish (5,304 of which were also analyzed for sex) and demonstrated:

1. Mendelian-recessive and independent inheritance of the b and r phenotypes, 
2. dominant hierarchy of three alleles on the b locus, 
3. female-limited (i.e., sex-linked) inheritance of the r phenotype, and 
4. recombination between the X and Y chromosome. 

These findings, particularly the fourth, impressed the editor, William Castle, who expressly added a footnote and even paid color charges for Aida’s illustrations (Fig. 1). Richard Goldschmidt, also being impressed by this article, visited Aida’s breeding farm during his stay in Japan in 1924. 

Figure 1: Handpainted illustrations from Aida 1921, showing orange-red, white variegated with black, white, brown-black (wild form), orange-red variegated with black, and bIue-black medaka varieties.

In the second article [6], Aida analyzed nine fish (out of 13,065) with exceptional color and sex phenotypes and found that their descendants (16,385 in total) were variously unbalanced in sex ratios. He discussed this phenomenon from a viewpoint of non-disjunction of the sex chromosomes and suggested physiological differences between the X and Y chromosomes cause “one-sided crossing over”; i.e., dominant (functional) alleles tend to be lost from the Y chromosome rather than gained from the X chromosome. He also described new dwarf mutants, fused and wavy, analyzing their 8,930 inter- or back-crossed siblings.

In the third article, color and sex of 14,958 fish were analyzed [7], and Aida reconsidered the second article from a viewpoint of sex reversal, proposing a new hypothesis for sex determination, i.e., the total sum of “sexual exciters” on the X and Y chromosomes determines sex, and the potency of exciters fluctuates at various degrees (either positively or negatively) depending on inner (e.g., recombination or mutation) or outer (e.g., temperature) conditions. At that period, various opinions on sex determinants existed among researchers (e.g., Goldschmidt, Kosswig, Winge, and Bridges). It should be noted that Aida’s hypothesis was intrinsically correct and could explain sex-determining phenomena in other animals. 

These monumental achievements by Aida clearly showed the usefulness and effectiveness of medaka as a research model. Having a non-academic position, however, Aida had no students or colleagues to take over his studies or fish stocks. It was miraculous that in 1954 when Aida stopped his research due to illness, an undergraduate student at Okayama University, Tetsuro Takeuchi (1932-), visited him and became Aida’s first and last student. Aida proposed Takeuchi study a new body-color mutant, color interfere (ci), which was confusing him with its “interfering” phenotype. Aida died in 1957 and Takeuchi was awarded a PhD degree in 1968 for studying ci. Teaching at a college, Takeuchi constructed a breeding farm at his home and kept the ci and other Aida’s strains until now. Without his devoted efforts for decades, Aida’s fish, including the rare recombinants and new mutants, would not have survived to the present. 

After a long dormancy, the medaka color and sex genetics research that Aida initiated a century ago came into bloom. The color genes (b and ci, but still not r) and the male determinant (the Dmy gene) were unveiled [8–10]. An inbred strain derived from Aida’s collection (Hd-rR) enabled quick sequencing of the whole genome [11]. Knowledge of the molecular bases of color perception and mating preference is accumulating [12, 13]. Takeuchi, on reaching the age of 89, decided to close his farm in this memorial year and deposited all strains he had kept for 67 years to the Medaka bioresource project (NBRP Medaka). He also gifted the authors a pair of Aida’s Yuzen dyeing pots.（Figure 2). The NBRP Medaka was initiated in 2002 and has continued for 20 years. Now over 800 strains and 895000 BAC/Fosmid/cDNA clones and other information are available (https://shigen.nig.ac.jp/medaka/top/top.jsp) [14]. This blooming time may not last long in Japan [15], but the number of medaka researchers has markedly increased worldwide in the last 100 years. We imagine even more medaka researchers will appreciate Aida’s work next century, on the 200th anniversary, hopefully alongside important works from today’s era of medaka research. 

You can learn more about Aida’s life and work in an account from Dr. Takeuchi here. Note that the site can be translated into multiple languages using the Google Translate menu on the page.

Figure 3. Photos of Tatsuo Aida and his medaka nursery, courtesy of Tetsuro Takeuchi and Kiyoshi Naruse.

About the authors:

Shoji Fukamachi, Professor, Department of Chemical and Biological Sciences, Japan Women’s University.

Kiyoshi Naruse, Specially appointed Professor, National Institute for Basic Biology. Head of National BioResource Project Medaka, Japan.

REFERENCES

1. Ishikawa, C., 1913 Dobutsugaku Kogi [Zoological Lectures] Vol.1: pp 372. 
2. Toyama, K., 1916 Ichinino Mendel-Seishitsu ni tsuite. [On some Mendelian characters.] Nippon Ikushugakkai Hokoku [Report of Japanese Breeding Society] 1: 1-9.
3. Ishiwara, M., 1917 On the inheritance of body-color in Oryzias latipes. Mitteilungen aus der medizinischen Fakultät Kyushu 4: 43-51.
4. Aida, T., 1907 Appendicularia of Japanese waters. The journal of the College of Science, Imperial University of Tokyo, Japan 23: 1-25. 
5. Aida, T., 1921 On the inheritance of color in a fresh-water fish Aplocheilus latipes Temmick and Schlegel, with special reference to sex-linked inheritance. Genetics 6: 554-573.
6. Aida, T., 1930 Further genetical studies of Aplocheilus latipes. Genetics 15: 1-16.
7. Aida, T., 1936 Sex reversal in Aplocheilus latipes and a new explanation of sex differentiation. Genetics 21: 136-153.
8. Fukamachi, S., Shimada, A., & Shima, A., 2001 Mutations in the gene encoding B, a novel transporter protein, reduce melanin content in medaka. Nature Genetics 28: 381-385.
9. Matsuda, M., Nagahama, Y., Shinomiya, A., Sato, T., Matsuda, C., et al., 2002 DMY is a Y-specific DM-domain gene required for male development in the medaka fish. Nature 417: 559-563.
10. Fukamachi, S., Sugimoto, M., Mitani, H., & Shima, A., 2004 Somatolactin selectively regulates proliferation and morphogenesis of neural-crest derived pigment cells in medaka. Proceedings of the National Academy of Sciences of the United States of America 101: 10661-10666.
11. Kasahara, M., Naruse, K., Sasaki, S., Nakatani, Y., Qu, W., et al., 2007 The medaka draft genome and insights into vertebrate genome evolution. Nature 447: 714-719.
12. Okuyama, T., Yokoi, S., Abe, H., Isoe, Y., Suehiro, Y., et al., 2014 A neural mechanism underlying mating preferences for familiar individuals in medaka fish. Science 343: 91-94.
13. Shimmura, T., Nakayama, T., Shinomiya, A., Fukamachi, S., Yasugi, M., et al., 2017 Dynamic plasticity in phototransduction regulates seasonal changes in color perception. Nature Communications 8: 412.
14. Sasado, T., Tanaka, M., Kobayashi, K., Sato, T., Sakaizumi, M. and Naruse, K. 2010  The National BioResource Project Medaka (NBRP Medaka), An integrated bioresource for biological and biomedical sciences. Experimental Animals 59, 13-23.
15. Fuyuno, I., 2017 What price will science pay for austerity? Nature 543: S10-S15.

Guest post by Michele Markstein and Gregory Davis.

A summary of the May 26, 2020 TAGC 2020 Online workshop, “Raising a Woke Generation of Geneticists: How and Why to Include Eugenics History in Genetics Classes.”

In the wake of George Floyd’s murder by Minnesota police officers, the nation has been wrestling with how to identify and combat systemic racism. As geneticists, it is clear that our field has much work to do, as we have an appallingly small number of Black geneticist colleagues. As solutions are discussed and implemented at the levels of departments, schools, and professional societies, there is a step forward that we can take right away as teachers of genetics: we can include the history of eugenics in our classrooms. This can make our classrooms more inclusive and our discipline more inviting to people it has traditionally alienated. Additionally, teaching eugenics history can help our students learn to combat racist ideology cloaked as “science,” and it can make the next generation of geneticists less likely to repeat the racist mistakes of our past.

If you do not feel equipped to teach eugenics history, you are not alone. It is conspicuously absent from modern genetics textbooks. For this reason and with the support of the GSA, we convened a virtual workshop at the TAGC2020 conference titled, “Raising a Woke Generation of Geneticists: How and Why to Include Eugenics History in Genetics Classes.”

At the workshop it became apparent that many geneticists who are interested in teaching eugenics history shy away from it for two common reasons: (1) they do not feel qualified to teach history, a subject outside their field, and (2) they do not want to risk creating an uncomfortable classroom environment.

We therefore offer the following advice to help you get started:

1. If you are apprehensive about teaching outside of your field of expertise, invite a colleague from across campus to give a guest lecture. Most likely there will be an expert in eugenics history in departments of African-American studies, anthropology, history, legal studies, sociology, and women and gender studies. This is a great way to forge an interdisciplinary relationship on your campus and can be a lot of fun.
2. If you are worried that you cannot navigate “uncomfortable” conversations, don’t worry, there are some simple steps you can take to help everyone in the room. First, everyone in the room does better when there is a reminder at the start that conversations about eugenics are likely to bring up uncomfortable feelings in different ways for different people and that this is OK. Second, students tend to be their best selves when ground rules or guardrails are specified to remind them that we are in this together and that everyone is expected to treat one other with compassion, empathy, and respect. For more tips on creating an inclusive environment, we recommend guidelines from Vanderbilt’s Center for Teaching: “Teaching Race: Pedagogy and Practice.” Another helpful article was recommended by participants at the meeting: “Signaling inclusivity in undergraduate biology courses through deliberate framing of genetics topics relevant to gender identity, disability, and race” by Karen Hales.

Additionally, we welcome you to download all the materials from the workshop: a list of recommended resources on eugenics history, a summary of participant survey responses, and panelist slide decks as summarized below. We look forward to the community’s continued interest and work in the field, and a future in which teaching eugenics history in genetics is as commonplace as teaching Punnett squares.

Summary of workshop materials:

1. A list of recommended resources compiled from panelist and participant input: If you need to catch up on the history of eugenics, take a look at the recommended resource list. A good place to start is with the 10-minute clip from the Ken Burns PBS documentary, The Gene–an Intimate History, and the 3-minute trailer for No Más Bebés by Renee Tajima-Pena and Virginia Espino which documents non-consensual sterilizations of Mexican immigrants in California. In addition, the list has links to lesson plans, websites, videos, podcasts, articles, and books that delve into to the history of eugenics.
2. Results from the Workshop Survey: A summary of participant advice, concerns, and recommendations for the future. The entire set of survey responses is included.
3. Panelist slide decks:
   • Marnie Gelbart, Personal Genetics Education Project, pgEd: Gelbart’s session provided a brief overview of the history of eugenics, through a short clip from the Ken Burns documentary, The Gene: An Intimate History and pgEd’s curriculum on “Genetics, History, and the American Eugenics Movement”, which was reframed in the past 12 months, thanks to support from the NIH Science Education Partnership Award program. This lesson plan looks at the history of eugenics as a lens for examining recent advances in precision medicine and genome editing with an eye towards safeguarding against future injustices. pgEd has heard from educators across the country that this curriculum fills a content gap in the science classroom and gives teachers some of the tools required to feel confident in tackling a sensitive topic related to the misuse of genetic arguments. In the session, Gelbart presented pgEd’s recent work to reframe its curricula to center the people who fought back against racist and discriminatory policies and practices in genetics and medicine. This is part of pgEd’s larger efforts to truly integrate a broader spectrum of topics and include the experiences and voices of historically marginalized peoples into the biology classroom.
   • Gregory Davis, Bryn Mawr College: Davis shared a vignette about an approach he has taken with students interested in the history of eugenics who’ve taken his undergraduate course in the history of genetics and embryology, which he teaches in the Biology Department at Bryn Mawr College. He focused on the advantages and caveats of co- and re-discovering the history of one’s own institution with students by examining primary sources—in this case, papers presented by both geneticists and eugenicists at the Second International Eugenics Congress in 1921.
   • Michele Markstein, UMass Amherst: Markstein’s presentation focused on two approaches that she has used in teaching eugenics history to large undergraduate classes: (1) inviting her colleague, Dr. Laura Lovett from the History Department to guest lecture and (2) presenting the material herself in a blended approach that enables students to review scientific topics from earlier in the semester (e.g., pedigree analysis, DNA sequencing, SNP genotyping, pleiotropy, human evolution and migration) while exploring ethical considerations in deciding to eliminate a SNP associated with “pathogenic” body odor from the human population. At the end of this lecture, most students in her white-majority class learn that they likely have the “pathogenic” SNP. In Markstein’s experience, both approaches resonate especially well with Black and Latinx students.
   • John Novembre, University of Chicago: Novembre’s presentation focused on teaching about the interface of genetics and society in a graduate curriculum. The importance of this type of teaching is supported from the National Academy of Science’s recent report on Graduate Education for the 21st Century, and he shared some of the practices he and his colleagues have been experimenting with at the University of Chicago. These include activities around teaching about genetics and race, as well as the history of eugenics. He concluded with sharing some challenges to this work and highlighting the need for more resources and educational research in this area.

Guest author Rori Rohlfs describes a unique classroom project for exploring the eugenic history of our field.

I was a fourth-year graduate student when I found myself asking a librarian for the archives of the journal The Annals of Eugenics. I got to that point by climbing back through a chain of references on fundamental statistical measures in my field of population genetics. I held the journal and flipped through the article titles and familiar author names, realizing that my field wasn’t so far removed from the turn-of-the-century eugenics movement. Feeling somewhat nauseous, I photocopied the article I was looking for and returned the journal quickly.

Now as a faculty member at San Francisco State University (SFSU), a public institution that puts social justice at the center of its mission, I continue to struggle with my field’s limited reckoning with our eugenic past. Can folks like me, who have built careers that grow from eugenics science, hold ourselves accountable for these roots as we continue scientific research? These questions become increasingly important in a political landscape where scientific ideas about genetic variation and difference are weaponized to support devastating policies, and the atrocities of racial injustice are staring us in the face.

As unarmed Black people are killed by police, and Black, Latinx, and Native American communities are disproportionately decimated by COVID19, masses of powerful voices are speaking out against racial injustice. We cannot let this moment pass us by without making substantive changes to eliminate institutional violence against Black people, people of color, and all marginalized groups. There is a particular need for those of us at the intersection of white privilege and scientific/educational privilege to listen to Black voices as we reflect on our personal and professional relationships to racism in terms of 1) how we benefit from racism, 2) how we contribute to racism and patterns of racialization, and 3) how we can take accountability for harms done. By understanding the harm caused, we are better positioned to address it.

In an effort to investigate that harm, I worked with SFSU students to explore the role of eugenics in the history of our field and institution. While the road to accountability will be long and arduous, I hope that this work sparks other scientists to action and brings us a bit further down that road.

The entangled roots of eugenics, statistics, and population genetics

The term eugenics was coined in 1883 by Francis Galton, a fellow of the Royal Society who’s credited with laying down foundational ideas in statistics, psychology, and criminology. Galton championed the emerging scientific field of eugenics and the political eugenics movement. Eugenics is rooted in the idea that a person’s genes determine their traits (e.g. height, disability, intelligence, sexuality, criminality), and that some trait variants are more valuable than others. This idea is inseparable from the idea that human trait diversity can be categorized into biologically distinct races, which follow a natural hierarchical order.  In Angela Saini’s book Superior (2019), she clearly lays out the political implications: If a person’s station in life is determined by their own genetics, rather than social experience and access to resources, then inequities in power and wealth would be natural and inevitable. This brand of genetic determinism has been used to justify slavery, colonization, and other manifestations of racism and ableism for centuries. With this deterministic theoretical underpinning, eugenics seeks to “improve” the human species through selective breeding, specific immigration standards, and other social policies

Far from being a fringe pseudoscience, the field of eugenics was widely accepted in science. In 1910 Charles Davenport established the Eugenics Record Office at the renowned research institute of Cold Spring Harbor Laboratory. Through 1939, the Eugenics Record Office collected and published data to support eugenic policies of forced sterilization and immigration restrictions targeting people who were disabled, people of color, and/or poor. The results of eugenics research needed a reputable peer-reviewed academic journal venue. So in 1925, Karl Pearson, creator of the chi-squared test, p-value, and principal component analysis, established a prestigious journal for the field: The Annals of Eugenics.  Other influential members of the academic elite aligned themselves with the eugenics movement, including central figures in the history of evolution theory like R.A. Fisher, Julian Huxley, and J.B.S. Haldane.

We still see the impact today through lines of reasoning and linguistic footprints. An emblematic example is statistical regression analysis. In his efforts towards the “improvement of the human breed,” Galton performed calculations intended to determine to what degree parents with a desired trait, such as “civic worth,” would reliably produce children with the same trait. These calculations needed to account for an observation that troubled Galton: offspring of parents with extreme trait values have, on average, less extreme traits than their parents [1]. The name he gave to his observation— “regression towards mediocrity”, now usually called regression to the mean—suggests his value judgment about the “quality of parentages” that go “far back towards mediocrity.” Galton’s term regression now describes the class of statistical techniques referred to as regression analysis, which continues to be central in statistics, and is used across disciplines from biology to economics to sociology.

Shifting names for the study of the genetic basis of human traits

Eugenic science and policy, largely developed in the United States and England, were implemented in the extreme by Nazi Germany. The explicit scientific field of eugenics lost support as the specific atrocities of the Nazi Holocaust came to light. Because of this, we may like to think that present-day fields like population and human genetics have totally departed from their eugenic predecessors. Yet, it’s easy to find threads of research continuing under different names. For example, in 1954 Annals of Eugenics changed its title to the Annals of Human Genetics, which is still publishing in 2020. Saini notes that the same individual scientists who performed genetic research “gently maneuver[ed] themselves out of eugenics into allied fields that studied human difference in less controversial and more rigorous ways, such as genetics.” Intentional tactics like these have led to a cultivated amnesia about our academic history. Yet, these individuals are our academic ancestors, and we cannot avoid being influenced by their intellectual legacy. These connections are seldom discussed, to the extent that they are unknown to most present-day geneticists. It was only through an accident that I stumbled on a connection, this when I had nearly earned a PhD. How can we be accountable for our past when we don’t know the history of our own fields?

Today, we are seeing a surge of well-funded studies seeking to determine the genetic basis of traits with clear, well-studied environmental influences like height, intelligence, sexual behavior, and income.  These analyses have received numerous technical critiques that call into question the validity of the scientific inferences, noting that “while the benefits are far from obvious, the risks of such results being misinterpreted and misused are quite clear.” Yet, the persistence of these lines of inquiry belies a familiar preoccupation with inborn differences for traits of social consequence. As in the past, there are ideological stakes in these studies: if these studies did in fact prove that differences in income, for example, are fixed by genetics (genetic association studies are incapable of proving that), then egalitarian economic policies would be futile. The legacy of eugenics is apparent today in both our scientific research and our political context. Prestigious journals are publishing these studies as the political landscape includes openly eugenicist ideas and policies based on the alleged inferiority of some nations of individuals, backed up with horrific restrictive immigration policies, at a time when it needs to be said that Black Lives Matter.

Because genetic determinism is an implicit and stealth component of our academic inheritance, even well-meaning scientists working at respected institutions can unwittingly pursue research that supports eugenicist arguments. To avoid incurring more harm, it is crucial that we scientists understand and reckon with our past. Saini makes a compelling call-to-action: “Without ever really looking back to the past and asking how and where the idea of race [and eugenics] had been constructed in the first place, why it had been relentlessly abused—without questioning the motives of scientists such as Francis Galton, Karl Pearson, [R.A. Fischer, Julian Huxley, and J.B.S. Haldane]—in this glaring ‘absence of introspection,’ old ideas of race [and eugenics] could never completely disappear.” As a test case in examining an institution’s relationship with its eugenic past, three undergraduates and I embarked on a self-reflective history of the topic at San Francisco State University.

The “Eugenics” course was offered at SFSU until 1952, when “Human genetics” was first offered

The students went to the library to pore over archived paper copies of university bulletins. As amateur historians, we had a learning experience in the nature of archival records. Bulletins were not available for every year, and over time the information they included varied dramatically. Nonetheless, we found that “Eugenics” was offered through the Biology Department at SFSU starting at latest in 1926. The course description is informative: “Study of the facts and problems of human heredity and possibility of race betterment.” At the time, SFSU was San Francisco State Teachers College, so graduates were expected to use their education to teach the next generation. Positioning teachers to improve public support of eugenic principles was important to the mission of eugenics. Instilling eugenic reasoning into the broader population must have been highly valued as it was one of only 12 upper division elective courses.

“Eugenics” was offered for the last time in 1951, six years after the end of World War II. This lag time demonstrates how the academic community held on to eugenics, well after the genocide in Nazi Germany became public knowledge. Let’s take a moment to think about the impact of over a quarter-century of teaching students about “the facts and problems of human heredity and the possibility of race betterment.” Most of these students became teachers themselves, disseminating eugenic reasoning on to their students. It’s hard to say how many thousands of people were influenced by the ideas in this course. While my privilege prevents me from being able to speak to the experience of scientists of color who endured the course, I will speculate about the impact for white students. For white students, how did the scientific reasoning (however flawed) presented in this class bolster racism and internal bias over generations? How do those ingrained racist ideas influence a white police officer seeing a Black man? A white city planner deciding whether to zone for toxic industry in a Latinx neighborhood? A white scientist designing a curriculum for a genetics class today?

While “Eugenics” was not offered after 1951, a new course appeared in 1952, “Human genetics,” described as “Principle of inheritance as applied to man; the role of heredity and environment; population genetics.” From these course descriptions, we see consistent interest in human heredity with movement away from blatant race science, towards population genetics and environmental factors. We’re very curious about the specific comparative curricula of these courses, but syllabi were not archived.

Beginning to envision an accountable scientific future

Some might be surprised to find this connection at SFSU, a university with a history rooted in progressivism, as evidenced in its mission statement that centers an “unwavering commitment to social justice.” Yet, eugenic thinking has pervaded the political spectrum, including progressive supporters like W.E.B. Du Bois and Margaret Sanger. Far from unique, the trajectory of the eugenics course at SFSU is likely common. We hope that this project inspires researchers at other universities to look into their own institutional histories. This type of research into university archives is quite feasible for a small team of dedicated undergraduates, perhaps especially those looking for a senior thesis or capstone project. A set of projects at different universities would illuminate the landscape and impact of eugenics course offerings.

While our findings confirmed my suspicions, it’s still jarring to see this history at my institution, conceptually related to the very Genetics class that I teach today. Once we are aware of these connections, what can we do to be accountable as well-intended, anti-racist heirs of this legacy? Our scientific training has provided us powerful tools of critical examination, tools which we can direct to investigate the ways our research, teaching, and scientific culture are influenced by our eugenic roots.  Our small exploration here has led me to question ideas central to both my population genetics training (why is it so common for evolutionary models to assume a single fixed optimum value for a trait?), and the institutional legacy of how we teach genetics (why do we emphasize inheritance of Mendelian traits when we know the vast majority of traits are polygenic and influenced by environmental factors?).

By grappling with questions like these, we can begin a process of accountability, squaring up with our scientific past, and intentionally shaping our future. As one small step, I now attempt to address some of the harm caused by my university’s historic eugenics course in my own genetics course by explicitly discussing eugenics within a broader anti-racist and anti-eugenics curriculum. While we cannot sever the connections to our institutional and academic roots in eugenics, with a better understanding of our history, we will be better equipped to both respond to eugenic ideas as they re-emerge, and to create a scientific culture that values justice.

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About the author:

Rori Rohlfs is an Assistant Professor in the Department of Biology at San Francisco State University.

Guest post by C. Brandon Ogbunugafor, Assistant Professor at Brown University.

John Maynard Smith, born in London on January 6, 1920, was one of the great iconoclasts of the post neo-Darwinian synthesis era, a cult figure whose life was defined by notable contributions across a wide breadth of subfields [1]. He not only authored numerous foundational texts in several areas of theoretical biology, he was fully engaged in the promotion of science. For example, he is well known as an ardent proponent of Darwinian evolution, a title he earned in part from his famous public debates against creationists [2]. 

John Maynard Smith, Wikimedia Commons

His work and career have profoundly influenced my own. I was introduced to John Maynard Smith through a concept called evolutionary game theory. I learned about it from a manuscript entitled Prisoner’s dilemma in an RNA virus by Paul Turner and Lin Chao. In it, Turner and Chao described how social dynamics between viruses infecting a cell display properties of game theory, and specifically, an example called the prisoner’s dilemma [3].  

At the time (the early 2000s), Paul Turner was an Assistant Professor in the Department of Ecology and Evolutionary Biology at Yale University (now the Rachel Carson Professor of Ecology and Evolution). I was a recent college graduate, a US Fulbright Scholar studying at the International Center of Insect Physiology and Ecology in Kenya, and a soon-to-be medical student at Yale. I didn’t know anything about game theory and surely didn’t know the origin of its use in biology. Between field trips across Kenya studying mosquito ecology, I learned of these roots, soon discovering Maynard Smith’s manuscript The Logic of Animal Conflict [4]. This manuscript, written with mathematician George Price, brought ideas from game theory into the context of conflict and decision-making in ecology and evolution. Maynard Smith would later publish the authoritative text on evolution and game theory with Evolution and the Theory of Games (Cambridge, 1982) [5]. Consequently, I owe much of my early interest in virus evolution to the work of John Maynard Smith. It became my eventual dissertation topic (which I completed with Paul Turner, no less), and an area that remains a central interest of mine.

As a graduate student, I would also engage Maynard Smith’s work on evolutionary genetics [6] and the evolution of sex [7], two areas in which I was also a novice. What was most rewarding about my experiences with Maynard Smith’s work was that he used a signature style: whatever the idea, Maynard Smith used simple mathematical formalism and walked the reader through the concepts step-by-step.

While Maynard Smith’s work in game theory, evolutionary genetics, and the evolution of sex was an important part of my education, it is another of Maynard Smith’s manuscripts — a “one-off” publication (as in, one that he didn’t follow up on with a grand treatise or text) on protein evolution — that would end up directly changing my career forever. In 1970, Maynard Smith published Natural Selection and the Concept of a Protein Space [8], which introduced an analogy for understanding the incremental nature of adaptive evolution in the context of proteins. It was short, clearly-written, and wielded the power of analogy in a way that I had never seen. When I first read it, I was a graduate student studying virus evolution and evolutionary medicine and was not specifically interested in protein evolution. It wasn’t until my postdoctoral work with Daniel Hartl, where I studied the evolution of drug resistance, that I reengaged this concept in the form of the protein fitness landscape. It transformed how I understood and studied several cutting-edge topics in the evolution of drug resistance, such as higher-order epistasis between mutations in enzyme drug targets [9]. The concept of Protein Space has been so influential to me that it has inspired me to develop tools for education [10]. Now that I am an Assistant Professor, protein evolution remains an integral part of my research program, which I can connect directly to the work of John Maynard Smith.  

The manuscript introducing Protein Space was published in 1970. It is fitting and especially meaningful to me that in 2020 we can celebrate both the centennial of Maynard Smith’s birth and the golden anniversary of the great manuscript that changed my career. In the April 2020 issue of GENETICS, readers can find a Perspectives article entitled A Reflection on 50 Years of John Maynard Smith’s Protein Space, in which I discuss the history and great legacy of this manuscript and the lessons it embodies [11]. 

While he has touched the lives of many through his work and words, Maynard Smith’s cult status derives from more than just accomplishments. His legend is colored by anecdotes that communicate a grand personality that matched the scope of his intellect. He is described as being quick-witted, sharp-tongued, and always willing to (or even preferring to) exchange thoughts over a pint of beer. 

The source of my fascination with Maynard Smith may reside in how unafraid he was to engage any number of topics. Many scientists in our era, because of the practical need to secure funding and earn status as a “world expert,” can feel pressured into pruning many side interests, under the premise that these will distract us from the presumptive goal of excellence on singular topics.  

While I am early in my career, I have decided to push back against this sentiment and defy it by building a research program that proudly embraces a wide number of ideas (e.g., evolutionary medicine, epidemiology, protein evolution, diversity and inclusion, etc.). I do this because I’ve concluded that what makes being a scientist enjoyable is the ability to continuously engage, feed, and grow our curiosities. 

John Maynard Smith’s story signals that using curiosity and rigor as guiding lights can generate a life of scientific radiance. In perilous times, when the future of society rests in the hands of science, we should especially appreciate the legacy of those who contributed through more than their formal work. John Maynard Smith set an example that encourages future thinkers to remain vigorous, as there are many ways to positively influence others.

Citations

1. Charlesworth, Brian. “John Maynard Smith: January 6, 1920–April 19, 2004.” Genetics 168.3 (2004): 1105-1109.
2. Piel, Helen. “‘The Most Bogus Ideas’: Science, Religion and Creationism in the John Maynard Smith Archive.” Electronic British Library Journal 2019 (2019).
3. Turner, Paul E., and Lin Chao. “Prisoner’s dilemma in an RNA virus.” Nature 398.6726 (1999): 441-443.
4. Maynard Smith, John, and George R. Price. “The logic of animal conflict.” Nature 246.5427 (1973): 15-18.
5. Maynard Smith, John. Evolution and the Theory of Games. Cambridge university press, 1982
6. Maynard Smith, John. Evolutionary genetics. Oxford University Press, 1989.
7. Maynard Smith, John. The evolution of sex. Vol. 4. Cambridge: Cambridge University Press, 1978.
8. Maynard Smith, John. “Natural selection and the concept of a protein space.” Nature 225.5232 (1970): 563-564.
9. Guerrero, Rafael F., et al. “Proteostasis environment shapes higher-order epistasis operating on antibiotic resistance.” Genetics 212.2 
10. Ogbunugafor, C. Brandon, and Daniel L. Hartl. “A new take on John Maynard Smith’s concept of protein space for understanding molecular evolution.” PLoS computational biology 12.10 (2016).
11. Ogbunugafor, C. Brandon. “A Reflection on 50 Years of John Maynard Smith’s ‘Protein Space’.” Genetics 214 (2020): 749-754.

About the Author

C. Brandon Ogbunugafor is an Assistant Professor in the Department of Ecology and Evolutionary Biology at Brown University. He is an evolutionary systems biologist, and uses experimental evolution, mathematical modeling, and computational biology to better understand the underlying causes and consequences of disease, across scales: from the biophysics of proteins involved in drug resistance to the social determinants underlying disease.

An interview with one of the “acknowledged programmers” whose contributions to early computational population genetics have been examined by an analysis of article acknowledgment sections.

Guest post by Emilia Huerta Sanchez and Rori Rohlfs.

Margaret Wu, Professor Emeritus at the University of Melbourne, is a leader in the field of education statistics, having published 80 articles, chapters, and books (and counting!). She made her start in the 1970s as a research assistant at Monash University, programming statistical analyses. In that position, Wu designed and programmed statistical analyses for numerous publications across disciplines. Like other women research assistants in that era, Wu’s contributions were recognized in acknowledgements, rather than with authorship (Dung et al., 2019).

We want to visibilize both the technical contributions and career paths of scientists like Dr. Wu. She generously provided some insight into her work as a research assistant and subsequent career path. These are edited excerpts from that conversation.

First, with all of your different areas of expertise, how would you define yourself?
I would definitely define myself as a statistician, and the programming is the tool to do things. But nowadays, it almost seems to me programming is the important part of doing statistics. We can’t do statistics without programming. But I would define myself as a statistician.

You went from being a research assistant in a math department to being a professor emeritus in an education department. Let’s start with your first job: could you please describe how you got the job and what it entailed?
My very first job was as a research assistant at Monash University. That was in the mathematics department, which includes the statistics department. I had finished an undergraduate degree in statistics from University of Melbourne, and I had done quite well. A professor who had moved to Monash University [from University of Melbourne] recommended me for the research position. My job was to support any project that any researcher had a need for. I remember the work consisted of programming lots of things, basic statistical programming. When professors needed help on their research projects, they would explain the problem to me, and I would work on the solution. Sometimes that involved finding parameter estimates, coming up with a reasonable algorithm to find numerical estimates, and dealing with numerical issues. When I was hired, I actually had no programming experience at all so I had to learn programming on the job.

Were you happy with your job?
I was very happy. Yes, I was seeing this as my first job after I finished university, and I really wanted to find a job. That was the first time I earned an income—before that I had odd jobs here and there.

Did you know other female research assistants?
Yes, I did. They also helped with programming, and sometimes they needed a little bit more instructions about how to write code, but they still did the code themselves. But there were others who pretty much just did the data entry part of it. And they were at all different levels depending on the capabilities of the people employed.

Did you know PhD students when you were a research assistant? How was your work different from theirs?
I knew a couple of people who actually went to University of Melbourne [as undergraduates in statistics] with me, who were then PhD students at Monash when I was there as a research assistant. While I had to work on any project that a researcher had a need for, they were much more focused on their thesis topic. I was being paid as an employee, and graduate students were on scholarships. In those days, I think graduate students pretty much worked independently on their own project, on their own topic, and there wasn’t much collaboration.

Were you ever encouraged to do a PhD as a research assistant, and would you have considered it?
No, not that I recall. I think I could possibly have found that attractive. I’m not quite sure at this point, thinking back now, but because I come from a somewhat academic family, and because my father was a lecturer at the university, being in academia was very highly regarded from the family point of view. But at that very time, I think I just needed to have an income since I wasn’t living at home.
And the second thing is that I really had a fear for public speaking which I thought probably all academics had to do. So, that also really put me off. But had someone suggested that I do it, I possibly would have found that an attractive idea.

How much time did you work as a research assistant, and what did you do next?
I was there for about three years, and then I moved to another organization, called CSIRO. It’s the Commonwealth Scientific and Industrial Research Organization, which consists of many, many departments, including basic science and biological science. Their statistics division really did support all the other divisions. After about three more years at CSIRO, I was pregnant with twins. And that pretty much meant breaking the career, because I was thinking about having to care for two kids. So, probably it would have been pretty much impossible to continue to work. I had a break for about two, three years after my daughters were born.

How did this happen? Did you feel encouragement or pressure?
I think it was my decision and no one else’s. I decided that actually, motherhood is important. I thought when the children are younger, I should bring up my own kids myself. I did find that quite tough as well—quite immensely not stimulating. I did that for one year, then I went and took a computing course to get out of the house a little bit. After a couple years I started doing a little bit of part-time work in the statistical consulting center at University of Melbourne again.

So, you had been a research assistant at Monash, and then CSIRO, and then what were the next steps in your career path?
Then an opportunity came up for a maths teacher and a Chinese teacher at a private girls school. I was approached, and it was very short notice. A friend’s friend just said, “Would you like to come and help us out?” I thought that was a good job for a mother, so I got into teaching secondary school for three years. It was still very part-time until my daughters started high school, that’s when I thought I could go back to a full-time job. But I didn’t like teaching in high school. I found that the discipline part was very difficult. You have to pretend you have a lot of authority in front of the kids, or else you’ll be in trouble. So that was very good training. So, besides the fact that I didn’t like the job, I think I’ve learned a lot from it about how to teach. It’s interesting, when I just finished university I was terrified about speaking in public. I think that three years teaching the high school trained me out of it.

After that experience, you thought you’d get back into statistics?
That’s when I applied for a job at ACER, which is the Australian Council for Educational Research, to run an international study project for the Third International Mathematics and Science Study. I applied for the job—I didn’t get it. But a couple of months later, they had an opening for someone with statistical skills, whereas that first job that I applied for was more administrative. So, then they contacted me. That’s how, when I just turned 40, I got the job at ACER. And got into more statistics.

You’re doing this research and you thought maybe you would be interested to pursue your PhD?
Actually, I started not directly to a PhD, I started by doing a masters degree. One of the things I was doing at ACER was developing new methods to develop fit statistics for certain estimation models. Someone just said, “Oh, why don’t you write it up, and make it a master’s degree thesis.” So, I did that.

You had some encouragement this time?
Definitely. Yes, I did. I think people at ACER were quite well qualified academically, so I was encouraged to consider higher degrees.

And they recognized that the work that you had already done actually constituted a master’s thesis?
Yes. It’s very interesting actually. I had to do the master’s degree at a university. So, I went to Melbourne University, and I approached a supervisor, and basically, I never saw the supervisor the whole time. When I completed the thesis he said, “Well, you’re very easy to supervise,” he said, “I’ve never even talked to you once.” There was actually no one at Melbourne University with relevant expertise anyway. So, I pretty much just did my work and submitted it there. My thesis actually won an award at the university.

How did you get into your PhD?
Melbourne University had a program where they collaborated with industries. They had an industrial partner to develop an assessment in problem solving. They were looking for PhD candidates. By then I aspired to get a higher degree, and I really got interested in research. I decided I was going to pursue that. So, I started the PhD, actually working part-time at ACER and part-time doing the PhD.

How old were your kids at this stage?
They would have been about 20 already when I started the PhD.

How did you get a faculty position after your PhD?
I was doing a PhD, but I was probably better qualified than most PhD students at that time, thanks to my working experience and background. I was in the position to be able to teach already. So, that’s how it started. Then I decided the university was a better environment to continue researching. I think I was very lucky that I was able to do lots of research at ACER. But we didn’t have as much freedom with the subject matter.

Can you say a few words about some of the research that you were doing?
We basically modeled student assessment data. We model the underlying student abilities as latent variables. They’re latent, because they’re not observable. The whole idea about latent variables actually is applied in what they call psychometrics. It’s actually quite a wide field.

Did you always enjoy the programming you did?
There are always two sides to it. I got frustrated in programming because sometimes I couldn’t do simple things. But I had to learn it. It’s quite rewarding. Sometimes you have to learn something, but the reward comes later. I think that’s the same as learning music. The practice is never enjoyable, but once you learn something, it then becomes enjoyable.

How does it feel to look back on your career path?
My career trajectory just happened in ways that I didn’t really plan, but there was a little bit of hope. Opportunities came up for me, and I was very fortunate. Even at this stage, I feel that everything I did in my working life was useful. Whether it was just doing simple things, or very low-level programming, they all built up my understanding. I’m finding them all very useful now. Although, after I entered ACER, I found research, models, information procedures, and writing software very, very interesting. From that point, I decided to pursue academic research.

What would you tell your younger self?
That is a hard question. I’ve learned a lot of lessons through my life. Not every job was the greatest, there were difficulties. But I think that the perseverance part is important. For example, when I first graduated I didn’t think I could do public speaking, and that can be overcome. So, now I’ve learned to believe in myself a lot better—that I can do things that I couldn’t when I was younger. In fact everyone can overcome a lot of things. I always feel that everyone has the capacity to do things when they put their mind to it.

You’re a super accomplished data scientist and statistician. What advice do you have for students coming up now? Any advice for women students in particular?
I don’t really know if I have such authority in giving people advice. I think personally, opportunities just come along. If things don’t work out, having a brighter outlook is always a good thing. I started my career quite late. But everything that I did, I found, was helpful to me later in life. So, don’t get discouraged. Things work out, and something you did a long time ago can come and help you later in life.

The other thing I found very helpful was to always try to put in an effort in whatever you do. I put in the effort out to become a proficient data entry operator. I think that helped me a lot in learning to type later. In fact, once I could type, I became more efficient in a lot of things. I think putting the effort into learning things is building small blocks for your life in the future.

Be positive and optimistic about life, really. And enjoy life while you’re living.

About the Authors:

Emilia Huerta Sanchez and Rori Rohlfs are Assistant Professors at Brown University and San Francisco State University, respectively. They want to change both the narrative and reality of who does science by highlighting women’s under-acknowledged roles in computational science.

Guest author Amir Teicher discusses how the concept of “genetic load” traces its roots back to eugenic thinking, as described in his recent Perspectives article in GENETICS.

The possibilities opened up by advances in genome sequencing have recently spurred discussions on the burden, or cost, that mutations pose to organisms and populations. Does the relaxation of selection pressure, especially among humans in modern, industrial society, mean deleterious mutations will keep on cropping up and accumulating, ultimately leading to a catastrophic genetic price that later generations would be forced to pay?

Hermann J Muller—the Nobel laureate who discovered in 1927 that radiation causes mutation—thought so. It was he who introduced the term “genetic load”, in a 1950 paper called Our Load of Mutations. Radiation anxiety following World War II seemed to justify Muller’s concern over the accumulation of mutations in human populations. His ideas were eagerly taken up by geneticists during the following three decades. In reality, however, Muller’s concept did not originate solely from his concerns over the hazards of nuclear energy or the overuse of X-rays in medicine, but had much earlier roots in eugenic thinking.

In fact, the term “genetic load” itself was far from novel. In Germany, discussions on erbliche Belastung—literally, hereditary burden, or load—were common from the late nineteenth century onwards, especially among psychiatrists (Muller spoke fluent German and was acquainted with these discussions). In most cases, the term was used to designate the pathological endowment that the mentally ill transfer to their family members. Practically speaking, anyone with a mentally ill relative was considered, to some degree, ‘hereditarily burdened’.

During the 1920s, studies on these alleged hereditary burdens became statistically more sophisticated, absorbing Mendelian concepts and providing robust proof on the heritability of mental diseases and neurological disorders. After the Nazis seized power, talk of the burden that the mentally ill posed was omnipresent and led to the mass sterilization, and later annihilation, of people with mental and physical disabilities. The ambiguity of the term was found useful: it conveyed simultaneously a hereditary burden, a social, and an economic one.

Muller was a vehement anti-Nazi, but he was also a devoted eugenicist. Using the fear of radiation as a pretext, he introduced into population genetics a concept whose roots lay in eugenic thinking, and whose implications were eugenic, too. This fact was recognized by some of his colleagues (and opponents) at the time. Some not only argued against the mathematical implications of the concept, but also advocated changing the terminology itself, which they saw as impregnated with eugenic connotations.

As recent works on genetic load indicate, not only did the term remain in force; some of its own related assumptions are still with us, too. Discussion of genetic load can easily lead to suggestions for top-down management of reproduction, in the name of future generations, wherein those with lesser genetic value would be politely requested to limit their procreation, for the common good. Awareness of the history of this scientific concept therefore might not be a mere curiosity, but an important reminder for the range of meanings that accompany it – indeed, for the kind of load that it, too, carries along.

Newly uncovered newspaper articles shed light on Mendel’s motivations.

Gregor Mendel is considered by many to be the father of genetics. Yet, because his work was not fully appreciated in its time, little is known about Mendel himself. Primary sources, such as letters he wrote, are rare; only a few dozen pieces of his correspondence remain—in contrast, over 15,000 of Charles Darwin’s letters survive. Without adequate source material to settle the subject, Mendel’s intentions in studying plants have long been the subject of debate. In GENETICS, van Dijk et al. report on two newly unearthed newspaper articles that provide some insight into Mendel’s motivations.

Standard interpretations of Mendel’s intentions agree that he was trying to figure out the rules of inheritance. However, others have argued that this explanation is biased by a modern perspective that knows his eventual findings, rather than truly considering what prompted him to begin his experiments in the first place. Some versions of this “revisionist” view hold that Mendel was primarily concerned with whether new species could be produced from hybridization. Although strong feelings exist in each camp, with so few primary sources, Mendel’s motives have remained primarily a matter of speculation.

Van Dijk and his colleagues found two previously overlooked articles in a database of scanned newspapers. The first, published on July 26, 1861, is a glowing account of Mendel performing “very instructive experiments, which are aimed at improving the vegetable and flower varieties cultivated in our region.” It discusses the “truly surprising” results of his work with artificial fertilization, including the production of “towering vegetable bushes” bearing plentiful (and tasty) fruit.

The second article was a rather pointed response to the first, published just four days later: “Without wanting to offend Professor Mendl [sic], for we honor every endeavor to approach truth in a practical manner, we must make [the newspaper’s] readers aware of the true value of the matter, which the reporter has somewhat exaggerated.”

The authors of the response then detail some of the ways the original newspaper report distorted the practical implications of Mendel’s work. For example: “Concerning the bastardization of beans, peas or fisols and cucurbits; the seed catalogs from France, England and Germany list so many varieties of excellent quality that it is hardly noteworthy to mention the economic importance of these very small scale experiments.” In other words, it might be interesting science, but the immediate implications were considered minimal at the time.

In some ways, these two articles are reminiscent of a phenomenon that continues to occur in science communication today: the ramifications of new science can be over-exaggerated when reported to a broad audience. Notably, however, the second article suggests that Mendel was actively seeking to answer a scientific question. Combining the new evidence with scholarship on Mendel’s scientific and horticultural influences, the authors make the case that Mendel’s motivations evolved: his practical interests in breeding sowed the seeds of a pursuit of pure science.

CITATION:

How Mendel’s Interest in Inheritance Grew out of Plant Improvement

Peter J. van Dijk, Franz J. Weissing, T. H. Noel Ellis

GENETICS October 1, 2018 210: 347-355; https://doi.org/10.1534/genetics.118.300916

http://www.genetics.org/content/210/2/347

As night fell, astronomer Jean Jacques d’Ortous de Mairan watched a plant’s leaves, symmetrically arranged side-by-side on a stem, clamp shut. It was 1729, and he was studying the dramatic nocturnal movement of Mimosa pudica. Strangely, he found that the plant behaved the same way even when it wasn’t exposed to natural cycles of light and dark, making his observation the first known example of a circadian rhythm that didn’t depend on external stimuli. Circadian rhythms are biological cycles that repeat daily, matching one full rotation of Earth. After this discovery in a weedy creeper, the planet would rotate tens of thousands more times before scientists studying the daily habits of a household insect exposed the mechanics of the biological clock.

This year’s Nobel Prize in Physiology or Medicine was awarded to Jeffrey C. Hall, Michael Rosbash, and Michael W. Young for their studies of the circadian clock in fruit flies. But their discoveries weren’t just insect idiosyncrasies—they held true across much of the living world, from animals to plants and even some bacteria. And, as many researchers building on their work have found, circadian rhythms have immense importance in human health.

This story is not an isolated example: it’s the sixth time a Nobel Prize has been awarded for the study of fruit flies. In fact, a surprising number of Nobels—along with the insights and practical outcomes of biological research—have emerged from a few seemingly insignificant species: vermin, creepy-crawlies, and microscopic blobs. Alex Cagan’s artwork below samples just a few recent examples.

Sometimes, such research has been ridiculed—notably by politicians looking for examples of wasteful spending. In some ways, this is understandable. Research with clear, immediate applications is the easiest type to justify to the public. But the type of science that instead aims to fill gaps in our understanding of the world—known as “basic” or “foundational” research—doesn’t focus on specific applications, like a disease cure or a drought-resistant crop, so no one can predict the real-world impact of any individual line of inquiry. However, understanding the world we live in and the creatures we share it with has proven an essential fuel for technological, agricultural, and medical advances.

Art by Alex Cagan, @ATJCagan. Click to see a larger version. For more information on these Nobel prize-winning studies see: (1) Aplysia sea slugs, (2) Caenorhabditis elegans worms,  (3) Tetrahymena ciliates, (4) Drosophila melanogaster fruit flies,  (5) Saccharomyces cerevisiae yeast

From fruit flies to cancer drugs

The most well-studied species on the planet are called model organisms, creatures chosen for intensive research because they are particularly suited to laboratory studies. Fruit flies, for example, have played a crucial role in unraveling the principles of genetics and evolution. Such fundamental insights can eventually lead to human health and other applications, but not in a predictable way.

For instance, in the late 1970s, scientists undertook an epic hunt for genes that affect the development of fruit fly larvae. This work uncovered several important biological pathways that govern how simple eggs transform into complex animals and earned Eric Wieschaus and Christiane Nüsslein-Volhard the Nobel Prize. Among the genes discovered was Hedgehog, named for the spiky embryos that result when it is mutated. Related genes were identified in mammals, and decades of work eventually revealed their connections to cancer and other diseases. 

Since 2012, two drugs that specifically inhibit tumor growth by targeting the Hedgehog pathway have been approved by the FDA to treat basal cell carcinoma, giving patients with advanced cases of this type of skin cancer a better chance of survival. Yet Wieschaus and Nüsslein-Volhard hadn’t set out to cure a disease—they were simply trying to understand how life works.

From dung gnats to developmental disorders

Different model organisms cater to different scientific needs. For example, mice and rats are mammals, like humans, which means we share much of our biology. The stripy zebrafish has a transparent embryo that allows scientists to watch development happen in real time. The nematode worm Caenorhabditis elegans can be rapidly grown in dishes, and because its cell divisions can be individually tracked through a precisely defined ballet, it’s another good choice for studying development. The mustard cress Arabidopsis thaliana is a fast-growing weed with a tiny genome that is much easier to study than the massive genomes of key crops like wheat and corn.

Without knowing why scientists choose particular species, model organism research can appear frivolous—and some creatures scientists choose to study may even seem disgusting. Take, for example, the dung gnat Sciara coprophila. Studies on this poop-loving insect revealed the phenomenon of genomic imprinting, in which genes are turned on or off depending on whether they were inherited from the father or the mother.

As it turns out, imprinting exists in humans—and has important consequences. For example, there is a stretch of chromosome 15 that is turned off in the copy inherited from the mother but turned on in the paternal copy. If the paternal copy of chromosome 15 is missing or has a mutation in the imprinted region, the result is Prader-Willi syndrome. This serious disease is characterized by cognitive disabilities and constant hunger, often leading to obesity and type 2 diabetes.

Another nearby region of the chromosome shows the opposite pattern: the maternal genes are normally activated while the paternal ones are turned off. Individuals missing the maternal copy of these genes have Angelman syndrome, which causes developmental delays, seizures, and frequent smiling and laughing.

Insights from model organisms have long helped scientists understand the biology behind such genetic diseases, but in recent years model organism researchers have become even more directly involved in diagnosing the millions of people affected—and in searching for treatments.

Lessons from microbes

Some model organisms differ even more from us than insects do. For example, humans and the yeast cells we use to make bread and beer last shared a common ancestor a billion years ago. Yet brewer’s yeast, Saccharomyces cerevisiae, is one of the most thoroughly studied organisms on the planet. These single-celled microbes share many characteristics with human cells, but they can be rapidly grown in great numbers in a flask or petri dish, and they have a life cycle and genome that make their genetics easier to study.

Several Nobel Prizes have been awarded for research on yeast, including the 2016 Nobel Prize for Medicine or Physiology, awarded to Yoshimori Ohsumi. The prize was for his work on autophagy, a kind of cellular housekeeping that helps clear the cell of damaged proteins and other potentially toxic debris. The role of this recycling and disposal system in human disease was not appreciated until Ohsumi and his colleagues’ work in the 1990s revealed the yeast genes that orchestrate the process. Thanks to the knowledge and tools made possible by this basic research, studies of autophagy in animals have exploded since the 2000s, revealing its complex roles in embryonic development, cell starvation, infection defense, neurodegenerative disease, and cancer.

The road from a discovery to its impact on society is rarely straight. Few of the scientists in these stories could have predicted how their work might one day be applied. Every day in labs across the country, scientists start down new paths that could eventually lead to the next cancer drug or technique for controlling disease-carrying pests. But it will only be possible to follow these new paths if we, as a society, continue to support the pursuit of knowledge—with or without clear applications.

This post was co-authored by Nicole Haloupek and Cristy Gelling based on an article we wrote for the March for Science blog. The text has been revised and updated to include the 2017 Nobel Prize in Physiology or Medicine.

In the genomic era, population geneticists are flooded with molecular data on the evolution of natural populations. This deluge started in 1966 as a trickle of data from protein electrophoresis studies, including the landmark GENETICS papers published by Richard Lewontin and John Hubby. As Lewontin is honored this week at the Annual Drosophila Research Conference with the Thomas Hunt Morgan Medal, the latest chapter of FlyBook looks back over the fifty years of insights into molecular evolution since fruit flies first burst open the field. Casillas and Barbadilla provide a stunningly thorough journey through the history of molecular populations genetics with an emphasis on the contributions of Drosophila. 

Richard Lewontin is the winner of the 2017 Morgan Medal.

Beginning in the late 1910s, population genetics unified the work of Darwin and Mendel, leading to a rich theoretical body of work by the 1960s. Population geneticists used mathematical modeling to describe how the forces of natural selection, migration, mutation, and genetic drift work together to shape patterns of genetic variation in nature. However, this theoretical framework remained untested until the arrival of allozymes—protein variants encoded by different alleles of the same gene. Due to differences in their amino acid content, allozymes travel through a gel at different rates when a current is applied, allowing them to be differentiated from one another. Lewontin and Hubby’s 1966 papers surveyed allozyme variation at several different loci in natural populations of D. pseudoobscura, a wild North American fruit fly. It quickly became common practice to survey natural populations for allozyme variation in known proteins, allowing scientists to quantify genetic variation was actually present.

These studies revealed that genetic variation was plentiful in the wild—much more plentiful than had been predicted. This discovery created a conundrum that was eventually solved by Motoo Kimura’s Neutral Theory, which stated that the majority of variation present in a population has no effect on organismal fitness and that allele frequencies are shaped by the random effects of genetic drift. Following soon after, Tomoko Ohta’s Nearly Neutral Theory incorporated effective population size into the model to predict that in small populations, mildly deleterious mutations would behave as if they were neutral. Though debate continues today about the relative importance of neutral genetic drift vs natural selection, the stage was set by these first studies with allozymes.

The limitations of allozyme studies were well known, however; only amino acid differences that caused a change in the overall charge of the protein could be surveyed. The hunt was on for a more comprehensive way to measure genetic variation. The first population genetic survey of nucleotide variation was carried out in 1983 by Marty Kreitman at the Adh locus in 11 D. melanogaster individuals. This locus had two well-known allozyme alleles, and just one of the 43 SNPs he identified caused the electrophoretic difference between them.

Drosophila can be found in their natural habitats in enormous numbers. Photo by John Tann via Flickr.

Directly sequencing nucleotides opened up entirely new areas of study, particularly in examining different functional sites like introns, UTRs, and coding sequences. Advances in sequencing technology placed more data within reach of more scientists, leading to many breakthroughs in our understanding of the dynamics of genetic variation in populations. Nucleotide substitutions that changed a protein’s amino acid sequence were found to be mostly deleterious and generally rare, whereas synonymous variation appeared mostly neutral but more common. The critical role of recombination in maintaining genetic variation was discovered, and methods for detecting the signatures of natural selection were developed.

Though nucleotide sequencing offered scientists a glimpse of the fundamental structure of genetic variation, focusing on a small handful of genes was still a limited and biased way of sampling polymorphism. After all, a single gene is typically kilobases long, while an entire genome can have billions of bases. After whole genome sequencing came to prominence around the new millennium, population genomics began to grow. In 2000, D. melanogaster was the third eukaryote to have its entire genome sequence published, and in 2007 the first true population genomics study was carried out in the closely related D. simulans by David Begun and colleagues. They used whole genome shotgun sequencing to examine unbiased variation in seven different lines of D. simulans, showing how polymorphism varied according to chromosomal location and functional region.

The DGRP lines were collected at the State Farmer’s Market in Raleigh, NC.

As next generation sequencing technologies emerged, studies on whole genome variation became more common and brought a flood of new data. In 2012, Trudy Mackay and colleagues presented the population genomics community with a crucial new resource: The Drosophila Genome Reference Panel, a set of fully sequenced genomes of over 200 D. melanogaster individuals from a single population in Raleigh, NC. This remains the most comprehensive population genetic study of any single species to date. Population genomic studies have shed light on many important evolutionary questions, including the role of recombination, mutation, and natural selection in maintaining and generating polymorphism across genomes. Drosophila species, with their typically enormous effective population sizes, have proven to be an excellent model for detecting genomic signatures of selection.

Just 50 years after the first allozyme studies were performed, population genomics has produced an astounding bounty of data on natural genetic polymorphism. Yet as usual, more data brings more questions, and many important avenues of discovery remain. One outstanding challenge is connecting the layers between phenotype and genotype. Natural selection acts on the outward traits of an organism, and these changes are assumed to be reflected in the genotype—how does selection affect the variation in transient structures like the transcriptome and methylome, and how are those changes translated into the genome? We look forward to the many presentations at the 58th Annual Drosophila Research Conference that are seeking answers to these questions and more.

http://www.genetics.org/content/205/3/1003

Casillas, S., & Barbadilla, A. (2017). Molecular Population Genetics. GENETICS, 205(3), 1003-1035. DOI: https://doi.org/10.1534/genetics.116.196493