The human race(s)? Perspectives from genetics

The genetic testing of race

In one form or another, you may have been (unfortunately) exposed to the notion of ‘testing for someone’s race using genetics.’ In one sense, this is part of the motivation and platform of ‘23andMe’, which maps the genetic variants across the human genome back to likely origin populations to determine the relative ancestry of a person. In a much darker sense, the connection between genetic identity and race is the basis of eugenics, by suggesting genetic “purity” (this concept is utter nonsense, for reference) of a population as justification for some racist hierarchy. Typically, this is associated with Hitler’s Nazism, but more subversive versions of this association still exist in the world: for Australian readers, most notably when the far-right conservative minor party One Nation suggested that people claiming to be Indigenous should be subjected to genetic testing to verify their race.

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A simplified overview of how DNA Ancestry methods work, by associating particular genetic variants within your genome to likely regions of origin. Note the geographic imprecision in the method on the map on the right, as well as the clear gaps. Source: Ancestry blog.

The biological concept of a ‘race’

Beyond the apparent ethical and moral objections to the invasive nature of demanding genetic testing for Indigenous peoples, a crucial question is one of feasibility: even if you decided to genetically test for race, is this possible? It might come as a surprise to non-geneticists that actually, from a genetic perspective, race is not a particularly stable concept.

The notion of races based on genetics has been a highly controversial topic throughout the development of genetic theory and research. Even recently, James Watson (as in of Watson & Crick, who were credited with the discovery of the structure of DNA) was stripped of several titles (including Chancellor Emeritus) following some controversial (and scientifically invalid) comments on the nature of race, genetics and intelligence. Comfortingly, the vast majority of the scientific community opposed his viewpoints on the matter, and in fact it has long been held that a ‘genetic race’ is not a scientifically stable concept.

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James Watson himself. I bet Rosalind Franklin never said anything like this… Source: Wikipedia.

You might ask: why is that? There are perceivable differences in the various peoples of the world, surely some of those could be related to both a ‘race’ and a ‘genetic identity’, right? Well, the issue is primarily due to the lack of identifiability of genetic variants that can be associated with a race. Decades of research in genetic variation across the global human population indicates that, due to the massive size of the human population and levels of genetic variation, it is functionally impossible to pinpoint down genetic variants that uniquely identify a ‘race’. Human genetic variation is such a beautiful spectrum of alleles that it becomes impossible to reliably determine where one end of the spectrum ends or begins, or to identify a strict number of ‘races’ within the kaleidoscope of the human genome.

How does this relate to 23AndMe?

How does this relate to your ‘23AndMe’ results? Well, chances are that some genetic variants might be able to be traced back to a particular region (e.g. Europe, somewhere). But naturally, there’s a significant number of limitations to this kind of inference; notably, that we don’t have reliable references from ancient history to draw upon very often. This, combined with the fact that humans have mixed among ourselves (and even with other species) for millennia, means that tracing back individual alleles is exceedingly difficult.

Genetic variation and non-identifiability of race figure
A diagram of exactly why identifying a genetic basis for race is impossible in humans. A) The ‘idealised’ version of race; people are easily classified by their genetic identity, with some variation within each classification (in this case, race) but still distinctiveness between them. B) The reality of human genetic variation, which makes it exceedingly difficult to make any robust or solid boundaries between groups of people due to the sheer amount of variation. Source: Harvard University blog.

This is exponentially difficult for people who might have fewer sequenced ancestors or relatives; without the reference for genetic variation, it can be even harder to trace their genetic ancestry. Such is the case for Indigenous Australians, for which there is a distinct lack of available genetic data (especially compared to European-descended Australians).

The non-genetic components

The genetic non-identifiability of race is but one aspect which contradicts the rationality of genetic race testing. As we discussed in the previous post on The G-CAT, the connection between genetic underpinning and physicality is not always clear or linear. The role of the environment on both the expression of genetic variation, as well as the general influence of environment on aspects such as behaviour, philosophy, and culture necessitate that more than the genome contributes to a person’s identity. For any given person, how they express and identify themselves is often more strongly associated with their non-genetic traits such as beliefs and culture.

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A comparison of genetic vs. cultural inheritance, which demonstrates (as an example) how other factors (in this case, other people) influence the passing on of cultural traits. Remember that this but one aspect of the factors that determine culture and identity, and equally (probably more) complex networks exist for other influences such as environment and development. Source: Creanza et al. (2017), PNAS.

These factors cannot reliably be tested under a genetic framework. While there may be some influence of genes on how a person’s psychology develops, it is unlikely to be able to predict the lifestyle, culture and complete identity of said person. For Indigenous Australians, this has been confounded by the corruption and disruption of their identity through the Stolen Generation. As a result, many Indigenous descendants may not appear (from a genetic point of view) to be purely Indigenous but their identity and culture as an Indigenous person is valid. To suggest that their genetic ancestry more strongly determines their identity than anything else is not only naïve from a scientific perspective, but nothing short of a horrific simplification and degradation of those seeking to reclaim their identity and culture.

The non-identifiability of genetic race

The science of genetics overwhelmingly suggests that there is no fundamental genetic underpinning of ‘race’ that can be reliably used. Furthermore, the impact of non-genetic factors on determining the more important aspects of personal identity, such as culture, tradition and beliefs, demonstrates that attempts to delineate people into subcategories by genetic identity is an unreliable method. Instead, genetic research and biological history fully acknowledges and embraces the diversity of the global human population. As it stands, the phrase ‘human race’ might be the most biologically-sound classification of people: we are all the same.

When “getting it wrong” is ‘right’

The nature of science

Over the course of the (relatively brief) history of this blog, I’ve covered a number of varied topics. Many of these have been challenging to write about – either because they are technically-inclined and thus require significant effort to distill down to sensibility and without jargon; or because they address personal issues related to mental health or artistic expression. But despite the nature of these posts, this week’s blog has proven to be one of the most difficult to write, largely because it demands a level of personal vulnerability, acceptance of personality flaws and a potentially self-deprecating message. Alas, I find myself unable to ignore my own perceived importance of the topic.

It should come as no surprise to any reader, whether scientifically trained or not, that the expectation of scientific research is one of total objectivity, clarity and accuracy. Scientific research that is seen not to meet determined quotas of these aspects is undoubtedly labelled ‘bad science’. Naturally, of course, we aim to maximise the value of our research by addressing these as best as can be conceivably possible. Therein, however, lies the limitation: we cannot ever truly be totally objective, nor clear, nor accurate with research, and acceptance and discussion of the limitations of research is a vital aspect of any paper.

The imperfections of science

The basic underpinning of this disjunction lies with the people that conduct the science. Because while the scientific method has been developed and improved over centuries to be as objective, factual and robust as possible, the underlying researchers will always be plagued to some degree by subjectivism. Whether we consciously mean to or not, our prior beliefs, perceptions and history influence the way we conduct or perceive science (hopefully, only to a minor extent).

Inherent biases figure
How the different aspects of ourselves can influence our research. The scientific method directly addresses the more objective aspects (highlighted in green arrows), but other subjective concepts may cause bias. Ideally, however, the objective parts outweigh the subjective ones (indicated by the size of the arrows), and is helped by peer-review as a process.

 

Additionally, one of the drawbacks of being mortal is that we are prone to making mistakes. Biology is never perfect, and the particularly complex tasks and ideas we assign ourselves to research inevitably involve some level of incorrectness. But while that may seem to fundamentally contradict the nature of science, I argue that is in fact not just a reality of scientific research, but also a necessity for progression.

Impostor syndrome

One widely realised manifestation of this disjunction between idealistic science and practical science, and one particularly felt by researchers in training such as post-graduate students, is referred to as ‘impostor syndrome’. This involves the sometimes subversive (and sometimes more overtly) feeling of inadequacy when we compare ourselves to a wider crowd. It is the feeling of not belonging in a particular social or professional group due to a lack of experience, talent or other ‘right’ characteristics. This is particularly pervasive in postgraduate students as we inevitably interact and compare ourselves to those we aspire to be like – postdoctoral researchers, professors, or other more established researchers – who are naturally more experienced in the field. The jarring disjunction of our own capability, often inaccurately assumed to be a proxy of intelligence, leads many to feel incapable or inadequate to be a ‘real’ scientist.

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I’d explain impostor syndrome as “feeling like being three kids stacked in a lab coat instead of a ‘real scientist’.”

It cannot be overstated that impostor syndrome is often the result of mental health issues and a high-pressure, demanding academic system, and rarely a rational perception. In many cases, we see only the best aspects of scientific research (both for academic students and the general public), a rose-coloured view of process. What we don’t see, however, is the series of failures and missteps that have led to even the best of scientific outcomes, and may assume that they didn’t happen. This is absolutely false.

Analysis paralysis

Other tangible impacts of impostor syndrome and self-induced perfectionism is the suppression of progressive work. By this I mean the typical ‘procrastinating’ behaviour that comes about from perfectionism: that we often prevent ourselves from moving forward if we perceive that there might be (however minor) issues with our work. Within science, this often involves inane amounts of reading and preparing on how to run an analysis without actually running anything. This is what has been called ‘analysis paralysis’, and disguises inactivity under the pretence that the student is still learning the ropes.

The reality is that trying to predict the multitude of factors and problems one can run into when conducting an analysis is a monolithic task. Some aspects relevant to a particular dataset or analysis are unlikely to be discussed or clearly referenced in the literature, and thus difficult to anticipate. Problem solving is often more effective as a reactive, rather than proactive, measure by allowing researchers to respond to an issue when it arises instead of getting bogged down in the astronomical realm of “things that could possibly go wrong.”

Drawing on personal experience, this has led to literal months of reading and preparing data for running models only to have the first dozens of attempts not run or run incorrectly due to something as trivial as formatting. The lesson learnt is that I should have just tried to run the analysis early, stuffed it all up, and learnt from the mistakes with a little problem solving. No matter how much reading I did, or ever could do, some of these mistakes would never have been able to be explicitly predicted a priori.

analysis error messages collage.jpg
Sometimes it feels like analysis is 90% “why didn’t this work?!” I think that’s realistic, though.

Why failure is conducive to better research

While we should always strive to be as accurate and objective as possible, sometimes this can be counteractive to our own learning progress. The rabbit holes of “things that could possibly go wrong” run very, very deep and if you fall down them, you’ll surely end up in a bizarre world full of odd distractions, leaps of logic and insanity. Under this circumstance, I suggest allowing yourself to get it wrong: although repeated failures are undoubtedly damaging to the ego and confidence, giving ourselves the opportunity to make mistakes and grow from them ultimately allows us to become more productive and educated than if we avoided them altogether.

Alice in Wonderland analogy
“We’re all mad here.”

Speaking at least from a personal anecdote (although my story appears corroborated with other students’ experiences), some level of failure is critical to the learning process and important for scientific development generally. Although cliché, “learning from our mistakes” is inevitably one of the most effective and quickest ways to learn and allowing ourselves to be imperfect, a little inaccurate or at time foolish is conducive to better science.

Allow yourself to stuff things up. You’ll do it way less in the future if you do.

Mr. Gorbachev, tear down this (pay)wall

The dreaded paywall

For anyone who absorbs their news and media through the Internet (hello, welcome to the 21st Century), you would undoubtedly be familiar with a few frustrating and disingenuous aspects of media such as clickbait headlines and targeted advertising. Another one that might aggravate the common reader is Ol’ Reliable, the paywall – blocking access to an article unless some volume of money is transferred to the publisher, usually through a subscription basis. You might argue that this is a necessary evil, or that rewarding well-written pieces and informative journalism through monetary means might lead to the free market starving poor media (extremely optimistically). Or you might argue that the paywall is morally corrupt and greedy, and just another way to extort money out of hapless readers.

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Yes, that is a literal paywall. And no, I don’t do subtlety.

Accessibility in science

I’m loathe to tell that you that even science, the powerhouse of objectivity with peer-review to increase accountability, is stifled by the weight of corporate greed. You may notice this from some big name journals, like Nature and Science – articles cost money to access, either at the individual level (e.g. per individual article, or as a subscription for a single person for a year) or for an entire institution (such as universities). To state that these paywalls are exorbitantly priced would be a tremendous understatement – for reference, an institution subscription to the single journal Nature (one of 2,512 journals listed under the conglomerate of Springer Nature) costs nearly $8,000 per year. A download of a single paper often costs around $30 for a curious reader.

Some myths about the publishing process

You might be under the impression, as above, that this money goes towards developing good science and providing a support network for sharing and distributing scientific research. I wish you were right. In his book ‘The Effective Scientist’, Professor Corey Bradshaw describes the academic publishing process as “knowledge slavery”, and no matter how long I spend thinking about this blog post would I ever come up with a more macabre yet apt description. And while I highly recommend his book for a number of reasons, his summary and interpretation of how publishing in science actually works (both the strengths and pitfalls) is highly informative and representative.

There are a number of different aspects about publishing in science that make it so toxic to researchers. For example, the entirety of the funds acquired from the publishing process goes to the publishing institution – none of it goes to the scientists that performed and wrote the work, none to the scientists who reviewed and critiqued the paper prior to publication, and none to the institutions who provided the resources to develop the science. In fact, the perception is that if you publish science in a journal, especially high-ranking ones, it should be an honour just to have your paper in that journal. You got into Nature – what more do you want?

Publishing cycle.jpg
The alleged cycle of science. You do Good Science; said Good Science gets published in an equally Good Journal; the associated pay increase (not from the paper itself, of course, but by increasing success rates of grant applications and collaborations) helps to fund the next round of Good Science and the cost of publishing in a Good Journal. Unfortunately, and critically, the first step into the cycle (the yellow arrow) is remarkably difficult and acts as a barrier to many researchers (many of whom do Very Good Science).

Open Access journals

Thankfully, some journals exist which publish science without the paywall: we refer to these as ‘Open Access’ (OA) journals. Although the increased accessibility is undoubtedly a benefit for the spread of scientific knowledge, the reduced revenue often means that a successful submission comes with an associated cost. This cost is usually presented as an ‘article processing charge’: for a paper in a semi-decent journal, this can be upwards of thousands of dollars for a single paper. Submitting to an OA journal can be a bit of a delicate balance: the increased exposure, transparency and freedom to disseminate research is a definite positive for scientists, but the exorbitant costs that can be associated with OA journals can preclude less productive or financially robust labs from publishing in them (regardless of the quality of science produced).

Open access logo.png
The logo for Open Access journals, originally designed by PLoS.

Manuscripts and ArXives

There is somewhat of a counter culture to the rigorous tyranny of scientific journals: some sites exist where scientists can freely upload their manuscripts and articles without a paywall or submission cost. Naturally, the publishing industry reviles this and many of these are not strictly legal (since you effectively hand over almost all publishing rights to the journal at submission). The most notable of these is Sci-Hub, which uses various techniques (including shifting through different domain names in different countries) to bypass paywalls.

Other more user-generated options exist, such as the different subcategories of ArXiv, where users can upload their own manuscripts free of charge and without a paywall and predominantly prior to the peer-review process. By being publically uploaded, ArXiv sites allow scientists to broaden the peer-review process beyond a few journal-selected reviewers. There is still some screening process when submitting to ArXiv to filter out non-scientific articles, but the overall method is much more transparent and scientist-friendly than a typical publishing corporation. For articles that have already been published, other sites such as Researchgate often act as conduits for sharing research (either those obscured by paywalls, despite copyright issues, or those freely accessible by open access).

You might also have heard through the grapevine that “scientists are allowed to send you PDFs of their research if you email them.” This is a bit of a dubious copyright loophole: often, this is not strictly within the acceptable domain of publishing rights as the journal that has published this research maintains all copyrights to the work (clever). Out of protest, many scientists may send their research to interested parties, often with the caveat of not sharing it anywhere else or in manuscript form (as opposed to the finalised published article). Regardless, scientists are more than eager to share their research however they can.

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A summary of some of the benefits and detriments of each journal type. For articles published in pre-print sites there is still the intention of (at some date) publishing the article under one of the other two official journal models (and thereof are not mutually exclusive).

Civil rights and access to science

There are a number of both empirical and philosophical reasons why free access to science is critically important for all people. At least one of these (among many others) is based on your civil rights. Scientific research is incredibly expensive, and is often funded through a number of grants from various sources, among the most significant of which includes government-funded programs such as the Australian Research Council (ARC).

Where does this money come from? Well, indirectly, you (if you pay your taxes, anyway). While this connection can be at times frustrating for scientists – particularly if there is difficulty in communicating the importance of your research due to a lack of or not-readily-transparent commercial, technological or medical impact of the work – the logic applies to access to scientific data and results, too. As someone who has contributed monetarily to the formation and presentation of scientific work, it is your capitalist right to have access to the results of that work. Although privatisation ultimately overpowers this in the publishing world, there is (in my opinion) a strong moral philosophy behind demanding access to the results of the research you have helped to fund.

Walled off from research

Anyone who has attempted to publish in the scientific literature is undoubtedly keenly aware of the overt corruption and inadequacy of the system. Private businesses hold a monopoly on the dissemination of scientific research, and although science tries to overcome this process, it is a pervasive structure. However, some changes are in process which are seeking to re-invent the way we handle the publishing of scientific research and with strong support from the general public there is opportunity to minimise the damage that private publication businesses proliferate.