Exploring the groundbreaking theories that revealed randomness as a major force in molecular evolution
For much of the 20th century, the narrative of evolution was dominated by natural selection—the powerful force that preserves advantageous traits and eliminates detrimental ones. When James Watson and Francis Crick unraveled the structure of DNA in 1953, they opened a new window into evolution's inner workings. For the first time, scientists could compare the genetic sequences of different species and track evolutionary change at the most fundamental level.
This clock ticked to a rhythm that didn't quite match the expected tempo of natural selection, presenting evolutionary biologists with a compelling puzzle. The solution would emerge from a radical new perspective—one that recognized the power of randomness in shaping the blueprint of life itself.
The 1953 discovery of DNA structure enabled direct comparison of genetic sequences across species.
Scientists observed a constant rate of genetic mutation that challenged traditional evolutionary models.
In 1968, Japanese biologist Motoo Kimura proposed a startlingly simple yet profound explanation for the molecular clock: the neutral theory of molecular evolution. Working independently, American biologists Jack Lester King and Thomas Hughes Jukes arrived at a similar conclusion, publishing their findings in 1969 3 5 . Kimura's mathematical approach suggested that the vast majority of evolutionary changes at the molecular level are neither beneficial nor harmful, but instead selectively neutral 3 .
Japanese population geneticist who proposed the neutral theory of molecular evolution in 1968.
| Aspect | Selectionist View | Neutralist View |
|---|---|---|
| Primary force in molecular evolution | Natural selection | Genetic drift |
| Nature of most mutations | Deleterious or advantageous | Mostly neutral or slightly deleterious |
| Proportion of polymorphic sites | Maintained by balancing selection | Transient phase of molecular evolution |
| Molecular clock mechanism | Constrained by selection pressure | Constant neutral mutation rate |
| Prediction for genetic diversity | Correlated with environmental variation | Proportional to population size |
Kimura found support for his theory in patterns of protein evolution. For instance, he noted that the parts of hemoglobin molecules on the surface where structure matters less evolve nearly ten times faster than the interior pockets where iron-containing heme groups reside—exactly what the neutral theory predicted, as mutations in functionally constrained regions are more likely to be harmful 3 .
While Kimura's theory gained traction, questions remained. Some observations, particularly regarding the relationship between generation time and evolutionary rates, didn't align perfectly with strict neutrality 1 . In 1973, Tomoko Ohta, a colleague of Kimura, introduced an important refinement: the nearly neutral theory of molecular evolution 1 6 .
Japanese evolutionary biologist who developed the nearly neutral theory of molecular evolution.
Ohta recognized that many mutations aren't strictly neutral but are instead slightly deleterious—harmful enough that natural selection would remove them from large populations, but not harmful enough to escape the influence of random genetic drift in smaller populations 1 6 . This seemingly subtle distinction had profound implications:
In large populations, even slightly harmful mutations are efficiently purged by natural selection. But in small populations, random genetic drift can overpower weak selection, allowing slightly deleterious mutations to occasionally become fixed 1 4 .
The effectiveness of selection depends on the product of the selection coefficient (s) and the effective population size (Nₑ). When |s| is less than 1/Nₑ, drift dominates; when |s| is greater than 1/Nₑ, selection prevails 1 .
Ohta's theory helped explain why protein evolution rates appeared independent of generation time—the effect of population size on slightly deleterious mutations created an offsetting effect to generation time 1 .
| Theory | Primary Advocate | View of Mutations | Key Evolutionary Force | Population Size Dependence |
|---|---|---|---|---|
| Selection Theory | Traditional Darwinians | Mostly subject to selection | Natural selection | Weak |
| Neutral Theory | Motoo Kimura | Strictly neutral or deleterious | Genetic drift | Substitution rate independent of population size |
| Nearly Neutral Theory | Tomoko Ohta | Slightly deleterious or advantageous | Interaction of selection and drift | Strong dependence; smaller populations evolve faster |
Ohta further developed her theory in the early 1990s, replacing the original "shift model" with a more realistic "fixed model" that included both beneficial and deleterious mutations without requiring artificial adjustments to population fitness 1 . This nearly neutral theory has become particularly important for understanding patterns observed in modern genomic data, where strict neutrality is frequently violated 6 .
While the neutral and nearly neutral theories emerged from mathematical population genetics, they prompted numerous empirical tests. One particularly illuminating approach came from comparative studies of protein evolution across species with different population sizes—a research strategy that continues to yield insights today.
Researchers compared the rates of molecular evolution in proteins across multiple species with varying effective population sizes. The experimental approach typically involved these steps:
Studies revealed a clear pattern: proteins in species with smaller effective population sizes consistently showed higher rates of molecular evolution 1 4 . This finding provided strong support for Ohta's nearly neutral theory, which predicted exactly this relationship.
The explanation lies in how population size affects the fate of slightly deleterious mutations. In large populations, natural selection efficiently removes these marginally harmful mutations before they can become fixed. But in small populations, random genetic drift can overwhelm weak selection, allowing slightly deleterious mutations to occasionally drift to fixation 1 6 .
| Organism Group | Effective Population Size | Protein Evolutionary Rate | Generation Time Effect |
|---|---|---|---|
| Rodents | Large | High | Short generation time |
| Primates | Small | Lower | Long generation time |
| Bacteria | Very Large | Very Low | Very short generation time |
| Marine Invertebrates | Very Large | Very Low | Variable generation times |
Modern molecular evolutionary research relies on sophisticated laboratory techniques and computational tools. Below are essential components of the methodological toolkit that enable scientists to test neutral and nearly neutral theories:
| Tool/Reagent | Function | Role in Neutral Theory Testing |
|---|---|---|
| DNA Sequencers | Determine the order of nucleotides in DNA fragments | Generate raw sequence data for within- and between-species comparisons |
| PCR Reagents | Amplify specific DNA segments for analysis | Enable study of particular genes across multiple individuals and species |
| Restriction Enzymes | Cut DNA at specific recognition sites | Facilitate earlier methods of DNA polymorphism detection (RFLP analysis) |
| Computational Algorithms | Analyze sequence data and perform statistical tests | Implement neutrality tests (e.g., McDonald-Kreitman test) and estimate parameters |
| Evolutionary Models | Mathematical frameworks for sequence evolution | Provide null hypotheses against which neutral theory predictions are tested |
Advanced sequencing methods provide the raw data needed to test evolutionary hypotheses.
Bioinformatics tools enable statistical testing of neutral theory predictions.
Evolutionary models provide the mathematical framework for testing neutrality.
The neutral and nearly neutral theories of molecular evolution represent a profound shift in how we understand life's history at the molecular level. From Kimura's initial insight that random drift might dominate molecular evolution to Ohta's recognition that many mutations occupy a nuanced middle ground between neutrality and selection, these theories have provided powerful explanatory frameworks that continue to guide evolutionary research.
Today, the neutral theory serves as the essential null hypothesis in molecular evolution . Even when deviations from neutrality are detected—as frequently happens—the identification process itself relies on the neutral expectation as a baseline.
The nearly neutral theory has proven particularly valuable for interpreting patterns revealed by modern genomics, where the interaction between selection and drift appears to shape genetic variation across diverse organisms.
As we continue to unravel the complexities of genomes across the tree of life, the insights of Kimura, Ohta, and their colleagues provide an enduring foundation for understanding both the regularities and exceptions in molecular evolution.