Study explores promise and pitfalls of evolutionary genomics

The Alexandrian mathematician and astronomer Claudius Ptolemy in the second century had a great ambition. Hoping to understand the motion of the stars and the paths of the planets, he published an ingenious treatise on the subject, known as the Almagest. Ptolemy created a complex mathematical model of the universe that seemed to sum up the motions of the celestial bodies he had observed.

Unfortunately, there was a fatal flaw at the core of his cosmic plan. Following the prejudices of his day, Ptolemy postulated that the Earth was the center of the universe. The Ptolemaic universe, made up of complex “epipers” to calculate the motions of planets and stars, has long been in the history books, although its conclusions have been scientific dogma for more than 1,200 years.

However, the field of evolutionary biology is subject to flawed theoretical approaches, sometimes producing dazzling models that fail to convey the true workings of nature that make up the dizzying array of living forms on Earth.

A new study looks at mathematical models designed to draw conclusions about how evolution works at the community level. The study concluded that such models must be built with great care, avoid unjustified initial assumptions, balance the quality of current knowledge and remain open to alternative interpretations.

Failure to apply rigorous procedures in constructing null models can lead to theories that appear to match some aspects of the available data derived from DNA sequencing, but fail to properly elucidate basic evolutionary processes, which are often extremely complex and multifaceted.

Such theoretical frameworks can provide convincing but ultimately false pictures of how evolution actually affected populations over time, whether they were groups of bacteria, groups of fish, or human societies and their various migrations during prehistoric times.

In the new study, Jeffrey Jensen, a researcher at Arizona State University’s Biodesign Center for the Mechanisms of Evolution and a professor in the School of Life Sciences at the Center for Evolution and Medicine, leads a group of world leaders in the field in advising for future research. Together they describe a set of criteria that can be used to ensure the accuracy of models that produce statistical inferences in population genomics – a scientific discipline concerned with large-scale comparisons of DNA sequences within and between populations and species.

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“One of our key messages is the importance of looking at the contributions of evolutionary processes that are sure to be at work (such as purification of selection and genetic drift), before simply relying on hypothetical or rare as primary drivers of observed diversity in a population (such as positive selection),” Jensen noted.

The results of the search appear in the current issue of the magazine Plus Biology.

field matures

Population genomics emerged when early efforts in this field attempted to reconcile Charles Darwin’s idea of ​​evolution through natural selection with early insights into the mechanisms of heredity, discovered by the Augustinian monk Gregor Mendel.

The synthesis peaked in the 1920s and early 1930s, in large part due to the mathematical work of Fisher, Haldane, and Wright, who pioneered the exploration of how natural selection, along with other evolutionary forces, could alter the genetic makeup of Mendelian populations over time.

Today, studies in population genomics include the widespread application of different genomic techniques to explore the genetic makeup of biological populations, and how various factors, including natural selection and genetic drift, cause changes in genetic makeup over time.

To do this, population geneticists develop mathematical models that quantify the contributions of these evolutionary processes to the formation of gene frequencies, use this theory to design statistical inference approaches to estimate the productive forces of observed patterns of genetic diversity in real populations and test their conclusions against accumulated data. .

flavor of life

The study of genomic variation focuses on the differences in DNA sequence between individuals and populations. Some of these variants are critical for biological function, including mutations responsible for genetic diseases, while others have no detectable biological effect.

This variation in the human genome can take many forms. The common source of variation is known as single nucleotide polymorphisms, or SNPs, where a single letter of DNA is changed in the genome. But genome-wide variation is also possible, including the simultaneous change of hundreds or even thousands of base pairs. Again, some of these alterations may play a role in disease risk and survival, while many other changes have no effect.

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Natural selection can occur when different discrete variables in a population have a fitness difference with respect to each other. By devising and studying mathematical models that govern the change in frequency of the corresponding genes and applying these models to experimental data, population geneticists seek to understand the contributing evolutionary processes in an accurate and quantitative manner. Thus, population genetics is often considered the theoretical cornerstone of modern Darwinian evolution.

Adrift across the genome

Although the importance of natural selection to the evolutionary process is undeniable, the role of positive selection in increasing the frequency of beneficial variants – a potential driver of adaptation – is certainly relatively rare compared to even other forms of natural selection. For example, purification of selection – the removal of harmful variants from a population – is a form of selection that behaves consistently and is more widespread.

In addition, there are many non-selective evolutionary processes of great importance. For example, genetic drift describes many of the random fluctuations that are inherent in evolution. In large populations, natural selection can operate more effectively by purging harmful variation and the potential to repair beneficial variation, while genetic drift becomes increasingly prevalent as populations become smaller.

The distinction can be seen in interesting form when comparing prokaryotic organisms such as bacteria with organisms made up of eukaryotic cells, including humans. In the first case, large population sizes tend to be more efficient selection. In contrast, the weaker selection pressure operating in eukaryotes is more permissive of genetic modifications, provided they are not too harmful.

According to the neutral theory of molecular evolution – a now guiding principle for the theory of evolution proposed by population geneticist Motoo Kimura more than 50 years ago – most evolutionary changes at the molecular level in true populations are not governed by natural selection, but by genetics. derivative. The study emphasizes that this critical point is often overlooked by evolutionary biologists. As co-author Michael Lynch, director of the Center for the Biodesign of Evolutionary Mechanisms at Arizona State University notes, “Natural selection is just one of many evolutionary mechanisms, and failure to recognize it is perhaps the most important obstacle to the successful integration of evolutionary theory with molecular and cellular biology. and developmental.

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The new consensus study further highlights that failure to consider alternative evolutionary mechanisms that are certain to act, including genetic drift, and to incorporate them into population genomics models, is likely to motivate misleading researchers. The authors argue that an overreliance on purely adaptive models to explain genetic variation has led to a range of explanations of questionable value.

The study provides a detailed flowchart that could help guide the development of more accurate models used to draw evolutionary inferences, based on genetic data. Biological parameters that differ between species include not only evolutionary variables such as clan size, mutation rates, recombination rates, population structure and history, but also how the genome itself is organized and life history traits, including mating behaviour. All of these factors play a vital role in determining the observed molecular variability and evolution.

“While these many considerations may seem daunting to some researchers, it is important to note that many excellent research groups at ASU and around the world are actively working to improve our understanding of these basic evolutionary parameters, providing ongoing enhancement to inference, for example, mutations and Recombination rates,” Susan Pfeiffer, associate professor at the Center for Evolution and Medicine and the Biodesign Center for the Mechanisms of Evolution, added, “recombination rates.”

While theoretical models of population genomics have proliferated alongside relatively sparse genomic data, an avalanche of data made possible by rapid and inexpensive DNA sequencing of organisms across the tree of life has radically changed the field. Careful and discreet use of this goldmine of genomic data will aid in the development of more rigorous models to unravel many of the remaining mysteries of evolution.

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