evolution – bioliteracy / biofundamentals

W. F. R. Weldon’s Critique of Mendel’s Work: Biological Relevance and Context.

A RAG-ChatGPT written backgrounder (checked and edited by Mike Klymkowsky ) for the excessively curious – in support of biofundamentals – 1 August 2025

Weldon’s Background and Perspective: Walter F. R. Weldon (1860–1906) was a British zoologist and a pioneer of biometry – the statistical study of biological variation. He believed that evolution operated through numerous small, continuous variations rather than abrupt, either-or traits. In his studies of creatures like shrimps and crabs, Weldon found that even traits which appeared dimorphic at first could grade into one another when large enough samples were measured [link]. He and his colleague Karl Pearson (1857-1936) argued that Darwin’s theory of natural selection was best tested with quantitative methods: “the questions raised by the Darwinian hypothesis are purely statistical, and the statistical method is the only one at present obvious by which that hypothesis can be experimentally checked” [link]. This emphasis on gradual variation and statistical analysis set Weldon at odds with the emerging Mendelian school of genetics, led by William Bateson (1861-1926) that focused on discrete traits and sudden changes. By 1902, the scientific community had split into two camps – the biometricians (Weldon and Pearson in London) versus the Mendelians (Bateson and allies in Cambridge) – reflecting deep disagreements over the nature of heredity [link]. This was the charged backdrop against which Weldon evaluated Gregor Mendel’s pea-breeding experiments.

Critique of Mendel’s Pea Traits and Categories Weldon’s photographic plate of peas illustrating continuous variation in seed color. (This figure from his 1902 paper shows pea seeds ranging from green to yellow in a smooth gradient, contradicting the clear-cut “green vs. yellow” categories assumed by Mendel [link]. Images 1–6 and 7–12 (top rows) display the range of cotyledon colors in two different pea varieties after the seed coats were removed [link]. Instead of all seeds being simply green or yellow, Weldon documented many intermediate shades. He even found seeds whose two cotyledons (halves) differed in color, underscoring that Mendel’s binary categories were oversimplifications of a more complex reality [link].

Weldon closely re-examined the seven pea traits Mendel had chosen (such as seed color and seed shape) and argued that Mendel’s tidy classifications did not reflect biological reality in peas. In Mendel’s account, peas were either “green” or “yellow” and produced either “round, smooth” or “wrinkled” seeds, with nothing in between. Weldon showed this was an artifact of Mendel’s experimental design. He gathered peas from diverse sources and found continuous variation rather than strict binary types. For example, a supposedly pure “round-seeded” variety produced seeds with varying degrees of roundness and wrinkling [link]. Likewise, seeds that would be classified as “green” or “yellow” in Mendel’s scheme actually exhibited a spectrum of color tones from deep green through greenish-yellow to bright yellow [link]. Weldon’s observations were impossible to reconcile with a simple either/or trait definition [link].

Weldon concluded that Mendel had deliberately picked atypical pea strains with stark, discontinuous traits, and that Mendel’s category labels (e.g. “green vs. yellow” seeds) obscured the true, much more variable nature of those characters [link]. In Weldon’s view, the neat ratios Mendel obtained were only achievable because Mendel worked with artificially generated lines of peas, bred to eliminate intermediate forms [link]. In ordinary pea populations that a farmer or naturalist might encounter, such clear-cut divisions virtually disappeared: “Many races of peas are exceedingly variable, both in colour and in shape,” Weldon noted, “so that both the category ‘round and smooth’ and the category ‘wrinkled and irregular’ include a considerable range of varieties.” [link] In short, he felt Mendel’s chosen traits were too simple and unrepresentative. The crisp binary traits in Mendel’s experiments were the exception, not the rule, in nature. Weldon’s extensive survey of pea varieties led him to believe that Mendel’s results “had no validity beyond the artificially “purified”in-bred” races Mendel worked with,” because the binary categories “obscured a far more variable reality.”[link]

Mendel’s Conclusions and Real-World Heredity. Weldon went beyond critiquing Mendel’s choice of traits – he questioned whether Mendel’s conclusions about heredity were biologically meaningful for understanding inheritance in real populations. Based on his empirical findings and evolutionary perspective, Weldon doubted that Mendel’s laws could serve as general laws of heredity. Some of his major biological objections were:

– Traits are seldom purely binary in nature: Outside the monk’s garden, most characteristics do not sort into a few discrete classes. Instead, they form continuous gradations. Weldon realized that Mendel’s insistence on traits segregating neatly into “either/or” categories “simply wasn’t true,” even for peas [link]. Mendel’s clear ratios were achieved by excluding the normal range of variation; in the wild, peas varied continuously from yellow to green with every shade in between [link]. What Mendel presented as unitary “characters” were, in Weldon’s eyes, extremes picked from a continuum.

– Mendel’s results were an artifact of pure-breeding: Weldon argued that the famous 3:1 ratios and other patterns were only apparent because Mendel had used highly inbred, “pure” varieties. By extensive inbreeding and selection, Mendel stripped away intermediate variants [link]. The artificially uniform parent strains used in Mendel’s experiments do not reflect natural populations. Weldon concluded that the seeming universality of Mendel’s laws was misleading – they described those special pea strains, not peas (or other organisms) at large [link]. In a letter, he even mused whether Mendel’s remarkably clean data were “too good” to be true, hinting that real-world data would rarely align so perfectly [link].

– Dominance is not an absolute property: A cornerstone of Mendelism was that one trait form is dominant over the other (e.g. yellow dominates green). Weldon questioned this simplistic view. He gathered evidence that whether a given trait appears dominant or recessive can depend on context – on the plant’s overall genetic background and environmental conditions [link]. For example, a seed color might behave as dominant in one cross but not in another, if other genetic factors differ. Weldon argued that Mendel’s concept of dominance was “oversimplified” because it treated dominance as inherent to a trait, independent of development or ancestry [link]. In reality (as Weldon emphasized), “the effect of the same bit of chromosome can be different depending on the hereditary background and the wider environmental conditions”, so an inherited character’s expression isn’t fixed as purely dominant or recessive [link]. This questioned the biological generality of Mendel’s one-size-fits-all dominance rule.

– Atavism and ancestral influence: Perhaps most intriguing was Weldon’s concern with reversion (atavism) – cases where an offspring exhibits a trait of a distant ancestor that had seemingly disappeared in intervening generations. Breeders of plants and animals had long reported that occasionally a “throwback” individual would appear, showing an old parental form or color after many generations of absence. To Weldon, such phenomena implied that heredity isn’t solely about the immediate parents’ genes, but can be influenced by more remote ancestral contributions [link]. “Mendel treats such characters as if the condition in two given parents determined the condition in all their offspring,” Weldon wrote, but breeders know that “the condition of an organism does not as a rule depend upon [any one pair of ancestors] alone, but in varying degrees upon the condition of all its ancestors in every past generation” [link]. In other words, the influence of a trait could accumulate or skip generations. This idea directly conflicted with Mendel’s theory as presented in 1900, which only considered inheritance from the two parents and had no mechanism for latent ancestral traits resurfacing after several generations. Weldon concluded from examples of reversion that Mendel’s framework was biologically incomplete – there had to be “more going on” in heredity than Mendel’s laws acknowledged [link].

In sum, Weldon found Mendel’s laws too limited and idealized to account for the messy realities of inheritance in natural populations. Mendel had demonstrated elegant numerical ratios with a few pea characters, but Weldon did not believe those results scaled up to the complex heredity of most traits or species. Variation, continuity, and context were central in Weldon’s view of biology, whereas Mendel’s work (as interpreted by Mendel’s supporters) seemed to ignore those factors. Thus, Weldon saw Mendel’s conclusions as at best a special case – interesting, but not the whole story of heredity in the real world [link][link].

Weldon’s Legacy

Weldon’s critiques came at a time of intense debate between the “Mendelians” and the “Biometricians.” William Bateson, the chief Mendelian, vehemently defended Mendel’s theory against Weldon’s attacks. In 1902, Bateson published a lengthy rebuttal titled Mendel’s Principles of Heredity: A Defense, including a 100-page polemic aimed squarely at “defending Mendel from Professor Weldon”[link]. Bateson and his allies believed Weldon had misinterpreted Mendel and that discrete Mendelian factors really were the key to heredity. The clash between Weldon and Bateson grew increasingly personal and public. By 1904 the feud had become so heated that the editor of Nature refused to publish any further exchanges between the two sides [link]. At a 1904 British Association meeting, a debate between Bateson and Weldon on evolution and heredity became a shouting match, emblematic of how divisive the issue had become [link][link].

Although Weldon’s objections were rooted in biological observations, many contemporaries saw the dispute as one of old guard vs. new ideas. Tragically, Weldon died in 1906 at the age of 46, with a major manuscript on inheritance still unfinished [link]. In that unpublished work, he had gathered experimental data to support a more nuanced theory reconciling heredity with development and ancestral effects [link][link]. With his early death, much of Weldon’s larger critique faded from the spotlight. Mendelian genetics, championed by Bateson and later enriched by the chromosome theory, surged ahead. Nevertheless, in hindsight many of Weldon’s points were remarkably prescient. His insistence on looking at population-level variation and the importance of multiple factors and environment foreshadowed the modern understanding that Mendelian genes can interact in complex ways (for example, polygenic inheritance and gene-by-environment effects). As one historian noted, Weldon’s critiques of Mendelian principles were “100 years ahead of his time” [link]. In the context of his era, Weldon doubted the biological relevance of Mendel’s peas for the broader canvas of life – and while Mendel’s laws did prove fundamental, Weldon was correct that real-world heredity is more intricate than simple pea traits. His challenge to Mendelism ultimately pushed geneticists to grapple with continuous variation and population dynamics, helping lay the groundwork for the synthesis of Mendelian genetics with biometry in the decades after his death[link][link].

Sources: Weldon’s 1902 paper in Biometrika and historical analyses [link][link][link][link][link][link][link]provide the basis for the above summary. These document Weldon’s arguments that Mendel’s pea traits were overly simplistic and his laws of heredity not universally applicable to natural populations, especially in light of continuous variation, context-dependent trait expression, and atavistic reversions. The debate between Weldon and the Mendelians is detailed in contemporary accounts and later historical reviews [link][link], illustrating the scientific and conceptual rift that formed around Mendel’s rediscovered work.

Introductory genetics: one way by which determinism creeps into biology students’ heads.

background: I have long been interested in students’ (and the public’s) misconceptions about biology (see this & that). More and more, it appears to me that part of the problem arises when conventional biology (and science courses in general) leave underlying scientific principles unrecognized and/or unexplained. In biology, there is a understandable temptation to present processes in simple unambiguous ways, often by ignoring the intrinsic complexity and underlying molecular scale of these systems. The result is widespread confusion among the public, a confusion often exploited by various social “influencers”, some (rather depressingly) currently in positions of power within the US.

After attending a recent Ray Troll and Kirk Johnson roadshow on fossils, art, and public engagement at the Denver Museum of Nature and Science (DMNS), I got to thinking. As a new hobby, in advance of retirement, perhaps I can work on evolving the tone of my writing to become less “academical” and more impactful, engaging, and entertaining (at least to some) while staying scientifically accurate and comprehensible. So here goes an attempt (helped out by genAI).

A common misconception, promoted by some “science popularizers” is that biological systems, including humans, are “determined” or “super-determined” (what ever that means) by various factors, particularly by the versions of genes, known as alleles, they inherited from their parents. While there is no question that biological systems are influenced and constrained by a number of factors (critical to “stay’n alive), the idea of determinism seems problematic (considered here). So where would a belief in biological determinism come from? One possibility, that emerged in the “Teaching and Learning Biology” course taught with Will Lindsay@CU Boulder, is the way basic genetics is often presented to students. The specific topic that caught my attention was the way the outcome of genetic crosses (matings) was presented, specifically through the use of what are known as Punnett’s squares.

In a typical sexually reproducing organism, the parents with different mating types or sexes, e.g. male and female, have two copies of each gene (mostly) – they are termed “diploid”. The two versions of a particular gene can be the same, in which case the organism is said to be “homozygous” or different, when it is termed “heterozygous” for that gene. The allele(s) carried by one parent can be the same or different from the allele(s) carried by the other. Molecular analysis of the alleles present in a population has been key to determining who, back in the day, was mating with Neanderthals (see wikipedia). Each gamete (egg or sperm) produced contains one or the other version of each gene – they are termed “haploid”. When sperm and egg fuse, a new diploid organism is generated.

Much of what is described above was figured out by Gregor Mendel (wikipedia). The good monk employed a few tricks that enabled him to recognize (deduce) key genetic “rules”. First, he worked with peas, Pisum sativum and related species. He used plants grown by commercial plant breeders to have specific versions of a particular trait. In his studies, he focussed on plants that displayed versions of traits that were unambiguously distinguishable from one another. Such pairs of traits are termed dichotomous; they exist in one or the other unambiguously recognizable form, without overlapping intermediates. The majority of traits are continuous rather than dichotomous.

As part of the process of generating “predictable plants”, breeders select male and female plants with the traits that they seek and discard others. After many generations the result are plants with reproducible and predictable traits. Does this mean that the plants are identical? Nope! There is still variability between individual plants of the same “strain”. For example, Mendel used strains of “tall” and “short” pea plants; the tall plants had stem lengths of between ~6 to 7 feet while the short plants had stem lengths between ~0.75 to 1.5 feet (a two-fold variation)(see Curtis, 2023). He put them into tall and short classes, ignoring these differences. But these plants were different. Such differences arise through stochastic processes and responses to developmental and environmental effects that impact height in various ways (discussed in a past post). Mendel began his studies with 22 strains of pea plants but only 7 exhibited the dichotomous behaviors he wanted. If he had included the others, it is likely he would have been confused and never would have arrived at his clean genetic rules. In fact, after he published his studies on peas, he took the advice of Carl Nägeli (see wikipedia) and began studies using Hieracium (hawkweeds), which differs in its reproductive strategy from Pisum (Nogler 2006). Nägeli’s suggestion and Mendel studies lead to uncertainty about the universality of Mendel’s rules. Mendel’s experiences reflect a key feature of scientific studies: simplify, get interpretable data, and then extend observations / systems leading to confirmation or revision.

The variation inherent in biological systems is nicely illustrated by what is (or should be) a classic study by Vogt et al (2008) who described the variations that occur within populations of genetically identical shrimp raised in identical conditions. The variation between genetically similar organisms (or identical twins) found in the wild (natural populations) is much greater. Why? because in breeder supplied plants most of the allelic variation present in the wild population is lost, discarded in the process of selecting and breeding organisms for specific traits. We see these “genetic background” effects when looking at genetically determined traits in humans as well. Consider cystic fibrous, a human genetic disease associated with the inheritance of altered versions of the CFTR gene (more on cystic fibrosis). People who inherit two disease-associated alleles of the CFTR gene develop cystic fibrosis, but as noted by Corvol et al (2015) “patients who have the same variants in CFTR exhibit substantial variation in the severity of lung disease” and this variation is associated (explained by) genetic background effects, together with stochastic effects and their developmental and environmental histories. In any of a number of studies, whenever populations of organisms are analyzed based on their genotype (which alleles they carry) the result is inevitably a distribution of responses, even when the average responses are different (for a good example see Löscher 2024).

In the case of the traits Mendel studied, he concluded that the trait was determined by the presence of different versions (alleles) of a genetic “factor”, that each organism contained two alleles, that these alleles could be the same (homozygous) or different (heterozygous), and that one allele was “dominant” to the other (“recessive”). If the dominant allele were present, it would determine the form of the trait observed. Only if both versions of the alleles present were recessive would the organism display the associated trait. The other rule was that all of the gametes produced by homozygous organism carried the same “trait-producing” allele, while heterozygous organisms produced gametes containing one or the other allele.

In 1905 Reginald Punnett introduced a way of thinking about Mendel’s matings, a diagram now known as a Punnett’s square (see wikipedia). In this figure (left below) ↓ the outcome of a mating between a male homozygous for a dominant allele and a female homozygous for a recessive allele is illustrated. All of the offspring will be heterozygous, but it is worth keeping in mind, however, that does not mean that they will be identical – they will display a similar level of variation in the trait seen in populations of the parental plants (see above). Again, this variation arises from the impact of environmental effects on developmental processes together with the influence of stochastic effects. The variation associated with the particular set of alleles present in an organism is captured by what is known as variable penetrance and expressivity of a gene-influenced trait (see link for molecular details). Ignoring the variations observed between organisms carrying the same allele(s) of a gene (or the same genotype in identical twins or clones can encourage or reinforce the idea that the details of an organism (its phenotype) are determined by the alleles it carries.

Another way students’ belief in genetic determinism can be reinforced is perhaps unintentional. Typically the result of the original mating between homozygous recessive and dominant parents (the P generation) is termed the first filial or F1 generation. Often the next type of genetic cross presented to students involves crossing male and female F1 individuals to produce the second filial or F2 generation (see figure – right above ↑). Such as F1 cross is predicted to produce organisms that display the dominant to recessive trait in a ratio of 3 to 1. What is often missing is that reproducible observation of this ratio requires that large numbers of F2 organisms are examined. The result of any particular F1 (heterozygous) cross is unpredictable; it can vary anywhere from 0 to 4 dominant to recessive trait displaying organisms to 4 to 0 trait dominant to recessive trait displaying organisms, and anything in between. This behavior is characteristic of a stochastic process; predictable when large numbers of events are considered and unpredictable when small numbers of events are considered. Stochastic behaviors are common in biological organisms, given the small numbers of particular molecules, and specifically particular genes, they contain (a GoldLabSymposium talk on the topic). In the context of organisms, there is room for something like “free will” (consideredhere). Whether Elon “knows” he is giving something that closely resembles a Nazi salute or not, we can presume that he is, at least partially, responsible for his actions and by implication their ramifications.

Why are the results of a mating stochastic? Because which gamete contains which trait-associated allele occurs by chance, while which gametes fuse together to produce the embryo is again a chance event. Some analyses of the numbers Mendel originally reported led to suggestions that his numbers were “too good”, and the perhaps he fudged them (for a good summary see Radick 2022). The bottom line – subsequent studies have repeatedly confirmed Mendel’s conclusions with the important caution that the link between genotype and phenotype is typically complex and does not obey strictly deterministic rules.

Nota bene: This is not mean to be a lesson in genetics; if interested in going deeper I would recommend you read Jamieson & Radick (2013) and the genetics section of biofundamentals.

Literature cited:

Corvol et al., (2015). Genome-wide association meta-analysis identifies five modifier loci of lung disease severity in cystic fibrosis. Nature communications, 6, 8382.

Curtis (2023). Mendel did not study common, naturally occurring phenotypes. Journal of Genetics, 102(2), 48.

Jamieson & Radick (2013). Putting Mendel in his place: How curriculum reform in genetics and counterfactual history of science can work together. In The philosophy of biology: A companion for educators (pp. 577-595). Dordrecht: Springer Netherlands.

Löscher (2024). Of Mice and Men: The Inter-individual Variability of the Brain’s Response to Drugs. Eneuro, 11(2).

Nogler (2006). The lesser-known Mendel: his experiments on Hieracium. Genetics, 172(1), 1-6.

Radick (2022). Mendel the fraud? A social history of truth in genetics. Studies in History and Philosophy of Science, 93, 39-46.

van Heyningen (2024). Stochasticity in genetics and gene regulation. Philosophical Transactions of the Royal Society B, 379(1900), 20230476.

Vogt et al., (2008). Production of different phenotypes from the same genotype in the same environment by developmental variation. Journal of Experimental Biology, 211, 510-523.

Visualizing and teaching evolution through synteny

Embracing the rationalist and empirically-based perspective of science is not easy. Modern science generates disconcerting ideas that can be difficult to accept and often upsetting to philosophical or religious views of what gives meaning to existence [link]. In the context of biological evolutionary mechanisms, the fact that variation is generated by random (stochastic) events, unpredictable at the level of the individual or within small populations, led to the rejection of Darwinian principles by many working scientists around the turn of the 20th century (see Bowler’s The Eclipse of Darwinism + link). Educational research studies, such as our own “Understanding randomness and its impact on student learning“, reinforce the fact that ideas involving stochastic processes relevant to evolutionary, as well as cellular and molecular, biology, are inherently difficult for people to accept (see also: Why being human makes evolution hard to understand). Yet there is no escape from the science-based conclusion that stochastic events provide the raw material upon which evolutionary mechanisms act, as well as playing a key role in a wide range of molecular and cellular level processes, including the origin of various diseases, particularly cancer [Cancer is partly caused by bad luck](1).

Teach Evolution

All of which leaves the critical question, at least for educators, of how to best teach students about evolutionary mechanisms and outcomes. The problem becomes all the more urgent given the anti-science posturing of politicians and public “intellectuals”, on both the right and the left, together with various overt and covert attacks on the integrity of science education, such as a new Florida law that lets “anyone in Florida challenge what’s taught in schools”.

Just to be clear, we are not looking for students to simply “believe” in the role of evolutionary processes in generating the diversity of life on Earth, but rather that they develop an understanding of how such processes work and how they make a wide range of observations scientifically intelligible. Of course the end result, unless you are prepared to abandon science altogether, is that you will find yourself forced to seriously consider the implications of inescapable scientific conclusions, no matter how weird and disconcerting they may be.

There are a number of educational strategies, in part depending upon one’s disciplinary perspective, on how to approach teaching evolutionary processes. Here I consider one, based on my background in cell and molecular biology. Genomicus is a web tool that “enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversely across different species, and chronologically along evolutionary time.” It is one of a number of web-based resources that make it possible to use the avalanche of DNA (gene and genomic) sequence data being generated by the scientific community. For example, the ExAC/Gnomad Browser enables one to examine genetic variation in over 60,000 unrelated people. Such tools supplement and extend the range of tools accessible through the U.S. National Library of Medicine / NIH / National Center for Biotechnology Information (NCBI) web portal (PubMed).

In the biofundamentals / coreBio course (with an evolving text available here), we originally used the observation that members of our subfamily of primates, the Haplorhini or dry nose primates, are, unlike most mammals, dependent on the presence of vitamin C (ascorbic acid) in their diet. Without vitamin C we develop scurvy, a potentially lethal condition. While there may be positive reasons for vitamin C dependence, in biofundamentals we present this observation in the context of small population size and a forgiving environment. A plausible scenario is that the ancestral Haplorhini population the lost the L-gulonolactone oxidase (GULO) gene (see OMIM) necessary for vitamin C synthesis. The remains of the GULO gene found in humans and other Haplorhini genomes is mutated and non-functional, resulting in our requirement for dietary vitamin C.

How, you might ask, can we be so sure? Because we can transfer a functional mouse GULO gene into human cells; the result is that vitamin C dependent human cells become vitamin C independent (see: Functional rescue of vitamin C synthesis deficiency in human cells). This is yet another experimental result, similar to the ability of bacteria to accurately decode a human insulin gene), that supports the explanatory power of an evolutionary perspective (2).

In an environment in which vitamin C is plentiful in a population’s diet, the mutational loss of the GULO gene would be benign, that is, not strongly selected against. In a small population, the stochastic effects of genetic drift can lead to the loss of genetic variants that are not strongly selected for. More to the point, once a gene’s function has been lost due to mutation, it is unlikely, although not impossible, that a subsequent mutation will lead to the repair of the gene. Why? Because there are many more ways to break a molecular machine, such as the GULO enzyme, but only a few ways to repair it. As the ancestor of the Haplorhini diverged from the ancestor of the vitamin C independent Strepsirrhini (wet-nose) group of primates, an event estimated to have occurred around 65 million years ago, its ancestors had to deal with their dietary dependence on vitamin C either by remaining within their original (vitamin C-rich) environment or by adjusting their diet to include an adequate source of vitamin C.

At this point we can start to use Genomicus to examine the results of evolutionary processes (see a YouTube video on using Genomicus)(3). In Genomicus a gene is indicated by a pointed box ; for simplicity all genes are drawn as if they are the same size (they are not); different genes get different colors and the direction of the box indicates the direction of RNA synthesis, the first stage of gene expression. Each horizontal line in the diagram below represents a segment of a chromosome from a particular species, while the blue lines to the left represent phylogenic (evolutionary) relationships. If we search for the GULO gene in the mouse, we find it and we discover that its orthologs (closely related genes) are found in a wide range of eukaryotes, that is, organisms whose cells have a nucleus (humans are eukaryotes).

We find a version of the GULO gene in single-celled eukaryotes, such as baker’s yeast, that appear to have diverged from other eukaryotes about ~1.500,000,000 years ago (1500 million years ago, abbreviated Mya). Among the mammalian genomes sequenced to date, the genes surrounding the GULO gene are (largely) the same, a situation known as synteny (mammals are estimated to have shared a common ancestor about 184 Mya). Since genes can move around in a genome without necessarily disrupting their normal function(s), a topic for another day, synteny between distinct organisms is assumed to reflect the organization of genes in their common ancestor. The synteny around the GULO gene, and the presence of a GULO gene in yeast and other distantly related organisms, suggests that the ability to synthesize vitamin C is a trait conserved from the earliest eukaryotic ancestors. GULO phylogeny mouse
Now a careful examination of this map (↑) reveals the absence of humans (Homo sapiens) and other Haplorhini primates – Whoa!!! what gives? The explanation is, it turns out, rather simple. Because of mutation, presumably in their common ancestor, there is no functional GULO gene in Haplorhini primates. But the Haplorhini are related to the rest of the mammals, aren’t they? We can test this assumption (and circumvent the absence of a functional GULO gene) by exploiting synteny – we search for other genes present in the syntenic region (↓). What do we find? We find that this region, with the exception of GULO, is present and conserved in the Haplorhini: the syntenic region around the GULO gene lies on human chromosome 8 (highlighted by the red box); the black box indicates the GULO region in the mouse. Similar syntenic regions are found in the homologous (evolutionarily-related) chromosomes of other Haplorhini primates. synteny-GULO region

The end result of our Genomicus exercise is a set of molecular level observations, unknown to those who built the original anatomy-based classification scheme, that support the evolutionary relationship between the Haplorhini and more broadly among mammals. Based on these observations, we can make a number of unambiguous and readily testable predictions. A newly discovered Haplorhini primate would be predicted to share a similar syntenic region and to be missing a functional GULO gene, whereas a newly discovered Strepsirrhini primate (or any mammal that does not require dietary ascorbic acid) should have a functional GULO gene within this syntenic region. Similarly, we can explain the genomic similarities between those primates closely related to humans, such as the gorilla, gibbon, orangutan, and chimpanzee, as well as to make testable predictions about the genomic organization of extinct relatives, such as Neanderthals and Denisovians, using DNA recovered from fossils [link].

It remains to be seen how best to use these tools in a classroom context and whether having students use such tools influences their working understanding, and more generally, their acceptance of evolutionary mechanisms. That said, this is an approach that enables students to explore real data and to develop plausible and predictive explanations for a range of genomic discoveries, likely to be relevant both to understanding how humans came to be, and in answering pragmatic questions about the roles of specific mutations and allelic variations in behavior, anatomy, and disease susceptibility.

Some footnotes (figures reinserted 2 November 2020, with minor edits)

(1) Interested in a magnetic bumper image? visit: http://www.cafepress.com/bioliteracy

(2) An insight completely missing (unpredicted and unexplained) by any creationist / intelligent design approach to biology.

(3) Note, I have no connection that I know of with the Genomicus team, but I thank Tyler Square (now at UC Berkeley) for bringing it to my attention.

In an age of rampant narcissism and social cheating – the importance of teaching social evolutionary mechanisms.

As socioeconomic inequality grows, the publicly acknowledged importance of traits such as honesty, loyalty, self-sacrifice, and reciprocity appears to have fallen out of favor with some of our socio-economic and political elites. How many people condemn a person as dishonest one day and embrace them the next? Dishonesty and selfishness no longer appear to be taboo, or a source of shame that needs to be expurgated (perhaps my Roman Catholic upbringing is bubbling to the surface here). A disavowal of shame and guilt and the lack of serious social censure appears to be on the rise, particularly within the excessively wealthy and privileged, as if the society from which they extracted their wealth and fame does not deserve their active participation and support [link: Hutton, 2009]. They have embraced a “winning takes all” strategy.

If an understanding of evolutionary mechanisms is weak within the general population [link], the situation is likely to be much worse when it comes to an understanding of the role and outcomes of social evolutionary mechanisms. Yet, the evolutionary origins of social systems, and the mechanisms by which such systems are maintained against the effects of what are known as “social cheaters”, are critical to understanding and defending, human social behaviors such as honesty, cooperation, loyalty, self-sacrifice, self-restraint, mutual respect, responsibility and kindness.

While evolutionary processes are often caricatured as favoring selfish behaviors, the facts tell a more complex, organism-specific story [link: Aktipis 2016]. Cooperation between organisms underlies a wide range of behaviors, from sexual reproduction and the formation of multicellular organisms (animals, plants, and people) to social systems, ranging from microbial films to bee colonies and construction companies [see Bourke, 2011: Principles of Social Evolution] [Wikipedia link].

One of the best studied of social systems involves the cellular slime mold Dictyostelium discoideum [Wikipedia link]. When life is good, that is when the world is moist and bacteria, the food of these organisms, are plentiful, D. discoideum live and reproduce happily as single celled amoeba-like individuals in soil. Given their small size (~5 μm diameter), they cannot travel far, but that does not matter as long as their environment is hospitable. When the environment turns hostile, however, an important survival strategy is to migrate to a new location – but what is a little guy to do? The answer in this species is to cooperate. Individual amoeba begin to secrete a chemical that acts to attract others; eventually thousands of individuals aggregate to form a multicellular “slug”; slugs migrate around to find a hospitable place and then differentiate into a fruiting body that stands ~1mm (20x the size of an individual amoeba) above the ground. To form the stalk that lifts the “fruiting body” into the air, a subset of cells (once independent individuals) change shape. These stalk cells die, while the rest of the cells form the fruiting body, which consists of spores – cells specialized to survive dehydration. Spores are released into the air where they float and are dispersed over a wide range. Those spores that land in a happy place (moist and verdant), revert to the amoeboid life style, eat, grow, divide and generate a new (clonal) population of amoeboid cells: they have escaped from a hostile environment to inhabit a new world, a migration made possible by the sacrifice of the cells that became the stalk (and died in the process). Similar types of behavior occur in a wide range of macroscopic organisms [Scrambling to the top: link]. Normally, who becomes a stalk cell and who becomes a spore is a stochastic process [see previous PLoS blog post on stochastics and biology education].

Cheaters in the slime mold system are individuals who take part in the aggregation process (they respond to the migration signal and become part of the slug), but have altered their behavior to avoid becoming a stalk cell – no self-sacrifice for them. Instead they become spores. In the short run, such a strategy can be beneficial to the individual, after all it has a better chance of survival if it can escape a hostile environment. But imagine a population made up only of cheaters – no self-sacrifice, no stalk, no survival advantage = death [see link: Strassmann & Queller, 2009].

A classic example of social cheating with immediate relevance to the human situation is cancer. Within a sexually reproducing multicellular organism, reproduction is strictly restricted to the cells of the germ line – eggs and sperm. The other cells of the organism, known collectively as somatic cells, have ceded their reproductive rights to the organism as a whole. While somatic cells can divide, they divide in a controlled and strictly regulated (unselfish) way. Somatic cells do not survive the death of the organism – only germ line cells (sperm and eggs) are able to produce a new organism. In the end cellular cooperation has been a productive strategy, as witness the number of different types of multicellular organisms, including humans. If a somatic cell breaks the social contract and cheats, that is, begins to divide (asexually) in an independent manner, it can lead to the formation of a tumor and later, if the cells of the tumor start to migrate within the organism, to metastatic cancer. More rarely (apparently) such cells can migrate between organisms, as in the case of transmissible cancers in dogs, Tasmanian Devils, and clams [see links: Murchison 2009 and Ujvari et al 2016). The growth and evolution of the tumor cell leads to the death of the organism and the cancer cells’ own extinction, another example of the myopic nature of evolutionary processes.

In the case of cancer the organism’s defenses against social cheaters comes in two forms, intrinsic to the individual cheater cells, in the form of cell suicide (known through a number of technical terms including apoptosis, anoikis and necroptosis)[link: Su et al., 2015] and extrinsic and organismic processes, such as the ability of the organism’s immune system to identify and kill cancer cells – a phenomena with therapeutically relevant implications [link: Ledford, 2014]. We can think of these two processes as guilt + shame (leading to cellular suicide) and policing + punishment (leading to immune system killing). For a cell to escape growth control and to evolve to produce metastatic disease, it needs to inactivate or ignore intrinsic cell death systems and to evade the immune system.

To consider another example, social systems are based on cooperation, often involving the sharing of resources with those in need. A recent example is the sharing of food (blood) between vampire bats [see link: Carter & Wilkinson, 2013]. The rules, as noted by Aktipis, are simple, 1) ask only when in need and 2) give when asked and able. In this context, we can identify two types of social cheaters – those who ask when they do not need and those you fail to give when asked and able. People who refuse to work even when they can and when jobs are available fall into the first group, the rich who avoid taxes and fail to donate significant funds to charities the other. It is an interesting question of how to characterize those who borrow money and fail to repay it. Bankruptcy laws that protect the wealth of the borrower while leading to losses to the lender might be seen as acting to undermine the social contract (clearly philosophers’ and economists’ comments here would be relevant).

Given that social systems at all levels are based on potentially costly traits, such as honesty, loyalty, self-sacrifice, and reciprocity, the evolutionary origins of social systems must lie in their ability to increase reproductive success, either directly or through effects on relatives, a phenomena known as inclusive fitness [Wikipedia link]. Evolutionary processes also render social systems vulnerable to cheating and so have driven the development of a range of defenses against various forms of social cheaters (see above). But recent political and cultural events appear to be acting to erode and/or ignore society’s defenses.

So what to do? Revolution? From a PLoS Science education perspective, one strategy suggests itself: to encourage (require) that students and the broader public be introduced to effective instruction on social evolutionary mechanisms, the traits they can generate (various forms of altruism and cooperation), the reality and pernicious effects of social cheaters, and the importance of defenses against them. In this light, it appears that social evolutionary processes are missing from the Next Generation Science Standards [NGSS link]. Understanding the biology, together with effective courses in civics [see link: Teaching Civics in the Year of The Donald] might serve to bolster the defense of civil society.

December 22, 2016, minor update 23 October 2020 – Mike Klymkowsky

Featured image is used with permission from Matthew Lutz (Princeton University).

Army ants’ ‘living’ bridges span collective intelligence, ‘swarm’ robotics (PNAS)