Divergent evolution is an interesting phenomenon in biological evolution. It occurs when closely related populations show striking differences. Population genetics, which studies the genetic structure and evolution of populations, is a useful tool for understanding divergent evolution.
This article discusses the relationship between divergent evolution and population genetics. It explains the theoretical basis of divergent evolution, including factors like ecological opportunities, selective pressures, genetic drift, and population genetics parameters. It also describes classic and modern genomic methods used in population genetics to study divergent evolution, showing how these methods are applied in research through case studies. Finally, it looks at current challenges and new technologies in this field to offer a complete view and deeper understanding for further research.
Theoretical Foundations of Divergent Evolution
Divergent evolution, a mysterious and captivating biological phenomenon, harbors intricate and sophisticated underlying mechanisms. To gain a profound understanding of its occurrence and progression, it's essential to dissect it from several pivotal angles. Below, we'll delve into the core factors such as ecological opportunities, selective pressures, and genetic drift, along with relevant parameters in population genetics.
Theoretical foundations of divergent evolution
Ecological Opportunities: Adapting to Vacant Niches
Ecological opportunities play a pivotal role in the process of divergent evolution, providing the initial impetus for the differentiation of biological populations. When new ecological niches emerge or existing ones become vacant, closely related populations have the chance to gradually diverge by adapting to these unique ecological conditions.
In the study of biological divergent evolution, Darwin's finches and Hawaiian honeycreepers serve as two classic examples of adaptive radiation. Darwin's finches evolved into 14 distinct species on the Galápagos Islands, with diverse beak morphologies enabling them to exploit different food resources, such as seeds, insects, and cactus pulp. Similarly, Hawaiian honeycreepers diversified into multiple species across the Hawaiian Islands, exhibiting extreme beak diversity that allows them to feed on nectar or capture insects. These cases underscore the critical role of ecological opportunities and geographic isolation in species differentiation and adaptive radiation, showcasing the capacity of organisms to undergo divergent evolution in vacant niches.
Selective Pressures: Divergent Natural Selection
Natural selection is a key driver of divergent evolution. Different environments create selective pressures that push populations in different evolutionary directions. For instance, the presence of phosphate can affect the production of Streptomyces gilvosporeus and natamycin. In a study, Streptomyces gilvosporeus was grown in a medium with phosphate. Over time, some individuals developed resistance to phosphate due to genetic mutations. These resistant individuals were more likely to survive and reproduce, passing on their resistance genes. This led to an increase in resistance genes in the population. In areas with little or no phosphate, the population evolved differently. This is an example of divergent natural selection.
Divergent natural selection of Streptomyces gilvosporeus in environments with phosphate(Wang et al., 2025)
Genetic Drift: Founder Effect in Isolated Populations
Genetic drift stands as another crucial factor influencing divergent evolution, particularly pronounced in small, isolated populations. The founder effect exemplifies a typical manifestation of genetic drift. Take, for instance, island lizards. When a small group of lizards accidentally migrates to and establishes itself on a new island, the gene pool of this new population originates solely from the few individuals that initially made the journey. Due to the limited sample size, the gene frequencies in the new population may differ significantly from those of the original population. These discrepancies arise not from natural selection but from random fluctuations in gene frequencies. Over time, these variations in gene frequencies accumulate, leading to genetic and phenotypic divergence between the island lizard population and the original mainland population, thereby driving divergent evolution.
Population Genetics Parameters
Population genetics parameters offer quantitative tools for a deeper understanding of divergent evolution. Changes in allele frequencies constitute a core focus of population genetics research. Selection and drift emerge as the two primary factors influencing these changes. Natural selection acts to increase the frequency of advantageous alleles and decrease that of deleterious ones, based on the genes' contributions to an organism's environmental adaptability. Conversely, genetic drift leads to random fluctuations in allele frequencies, a phenomenon that may be more pronounced in small populations.
Methods for Studying Divergence in Population Genetics
After gaining a deep understanding of the underlying mechanisms of divergent evolution, mastering scientific and effective research methods becomes crucial for uncovering its full picture. The field of population genetics has developed a combination of classical and modern approaches. Below, we will introduce these methods and their applications in the study of divergent evolution.
Methods for studying divergence in population genetics
F-Statistics
F-statistics, a set of statistical measures proposed by Wright, are used to quantify population substructure, with FST being one of the most commonly employed indicators. FST assesses the degree of genetic differentiation between populations by comparing genetic variation within and between populations. Its calculation is based on differences in allele frequencies, providing a straightforward reflection of the similarities or differences in genetic composition among different populations.
Genome-Wide Association Studies (GWAS)
GWAS represents a method for detecting associations between genetic variations and phenotypic traits at the whole-genome level. In the study of divergent evolution, GWAS can be utilized to identify genetic loci subjected to divergent selection. By comparing genetic variations across the entire genome in different populations and correlating these with phenotypic differences, researchers can pinpoint gene regions associated with divergent evolution.
Genotyping-by-Sequencing (GBS)
GBS is a genotyping method based on high-throughput sequencing technology, offering the advantages of low cost and high throughput, particularly suitable for studies involving non-model organisms. GBS involves cutting genomic DNA with restriction enzymes, followed by sequencing the resulting fragments to obtain a large number of SNP markers. These SNP markers can be used to analyze the genetic structure of populations, assess genetic diversity, and investigate divergent evolution. Compared to traditional genotyping methods, GBS does not require prior knowledge of genome sequence information, significantly reducing research costs and complexity, and providing a novel approach for studying divergent evolution in non-model organisms.
Approximate Bayesian Computation (ABC)
ABC is a model-based statistical inference method particularly suited for handling complex models and large datasets. In the study of divergent evolution, ABC can be employed to estimate divergence times. This method involves simulating a vast number of evolutionary processes to generate simulated datasets resembling actual observed data. By comparing the similarity between simulated and actual datasets, the values of model parameters, including divergence times, can be inferred. ABC overcomes the limitations of traditional methods in dealing with complex evolutionary models, offering an effective means for accurately estimating divergence times.
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Case Study: Divergence and Population Genetics
After delving into the theories and methodologies of divergent evolution and population genetics, examining real-world case studies offers a more intuitive understanding of how these concepts apply in deciphering biological evolutionary phenomena.
Dong et al. researched the evolutionary ecology of microorganisms in deep-sea cold seep sediments, analyzing 39 dominant species across six global cold seep sites. These species, distributed from the sediment surface to depths of up to 4.3 meters, primarily engage in methane oxidation and sulfate reduction, categorized into Methane-Oxidizing Bacteria (MOB), ANME, and SRB.
The study revealed varying degrees of intraspecific sequence divergence and evolutionary trajectories among these microorganisms, characterized by low homologous recombination rates and strong purifying selection. Functional genes, such as pmoA, mcrA, and dsrA, were predominantly under purifying selection in most species, although positive selection pressures were also observed. Additionally, intraspecific diversity of the species varied with sediment depth and was subjected to distinct selective pressures across different redox zones. These findings underscore the interplay between ecological processes and the evolution of key bacteria and archaea in the extreme environment of deep-sea cold seeps, shedding light on how microbial communities adapt to environmental changes within the seafloor biosphere.
Evolution of microbial communities in deep-sea cold seep sediments(Dong et al., 2023)
Mara and colleagues conducted a metagenomic and metatranscriptomic analysis of deep sediments from the Guaymas Basin in Mexico to investigate the distribution and adaptive evolution of archaea and bacteria along thermal and geochemical gradients. Their research revealed that the composition of microbial communities is closely tied to temperature and geochemical parameters.
In sediments with lower temperatures, microbial diversity was observed to be higher, whereas in deeper sediments exceeding 45°C, diversity significantly decreased. Specific archaeal lineages, such as Bathyarchaea and Hadarchaeota, exhibited increased relative abundance in high-temperature environments, indicating adaptive evolution to heat, with their genomes containing genes associated with high-temperature adaptation. Furthermore, some microbial lineages demonstrated diverse metabolic capabilities, such as utilizing multiple organic substrates and potentially fixing carbon through the Wood-Ljungdahl pathway. This study sheds light on the mechanisms of adaptive evolution among microorganisms in the deep biosphere.
Distribution and divergent evolution of archaea and bacteria along thermal and geochemical gradients (Mara et al., 2023)
Sriaporn and colleagues investigated the community distribution and prevalence of bacteria and archaea in hot springs with varying physicochemical conditions within the Taupo Volcanic Zone of New Zealand. Analyzing 16S rRNA gene ASVs from 76 underwater sediment samples, the researchers found that the relative abundance of archaea and bacteria exhibited an inverse correlation with temperature and pH.
While most ASVs were detected within narrow temperature and pH ranges, a few ASVs, including Thermoplasmatales, Desulfurella, Mesoaciditoga, and Acidithiobacillus, were prevalent across a broad spectrum of temperatures and pH levels. These widespread microorganisms demonstrated divergent evolution through genome-specific metabolic traits, such as sulfur, nitrogen, and hydrogen metabolism capabilities, enabling them to adapt to diverse hot spring environments. The study unveils the distribution patterns and mechanisms of divergent evolution among microorganisms in extreme environments.
Divergent evolution of bacteria and archaea in hot springs under varying conditions (Sriaporn et al., 2023)
Challenges and Frontiers
Despite significant advancements in population genetics for studying divergent evolution, several methodological hurdles persist. One common issue is low-depth sequencing in Genotyping-by-Sequencing (GBS) data. Due to shallow sequencing depths, GBS data may contain a substantial number of imputation errors, which compromise the accuracy and reliability of SNP markers, thereby interfering with subsequent genetic analyses. To address this, researchers need to develop more effective imputation algorithms and quality control methods to enhance the quality of GBS data.
With the continuous evolution of scientific and technological advancements, emerging technologies offer new opportunities for divergent evolution research. Long-read GBS technology enables the resolution of structural variations within divergent populations. Structural variations, including insertions, deletions, inversions, and translocations, play crucial roles in the evolutionary processes of organisms. Traditional GBS technologies, constrained by shorter read lengths, struggle to accurately detect these structural variations. In contrast, long-read GBS technology provides longer sequencing reads, facilitating more effective identification and analysis of structural variations, thus offering new perspectives for a deeper understanding of the genetic mechanisms underlying divergent evolution.
Conclusion
Divergent evolution, as a significant phenomenon in the field of biological evolution, is governed by complex and diverse mechanisms involving the interplay of ecological opportunities, selective pressures, genetic drift, and other factors. Population genetics, as a pivotal discipline in studying the genetic structure and evolution of populations, provides a rich theoretical foundation and powerful analytical tools for comprehending divergent evolution. From classical F-statistics and coalescent theory to modern approaches like genome-wide association studies, sequencing-based genotyping, and approximate Bayesian computation, population genetics methodologies are continually evolving and refining, offering increasing possibilities for unraveling the mysteries of divergent evolution.
In summary, divergent evolution is not merely an evolutionary pattern but a dynamic process shaped by the interplay of ecology, genetics, and chance. Future research necessitates the integration of multiple methodologies and technological approaches to delve deeper into the mechanisms and patterns of divergent evolution, thereby providing a more comprehensive and profound understanding of the formation and evolution of biological diversity.
References:
- Wang L, Xiao W, Zhang H, Zhang J, Chen X. "Improved Natamycin Production in Streptomyces gilvosporeus Through Mutagenesis and Enhanced Nitrogen Metabolism." Microorganisms. 2025 13(2):390 https://doi.org/10.3390/microorganisms13020390
- Dong X, Peng Y, Wang M, Woods L, Wu W, Wang Y, Xiao X, Li J, Jia K, Greening C, Shao Z, Hubert CRJ. "Evolutionary ecology of microbial populations inhabiting deep-sea sediments associated with cold seeps." Nat Commun. 2023 14(1):1127 https://doi.org/10.1038/s41467-023-36877-3
- Mara P, Geller-McGrath D, Edgcomb V, Beaudoin D, Morono Y, Teske A. "Metagenomic profiles of archaea and bacteria within thermal and geochemical gradients of the Guaymas Basin deep subsurface." Nat Commun. 2023 14(1):7768 https://doi.org/10.1038/s41467-023-43296-x
- Sriaporn C, Campbell KA, Van Kranendonk MJ, Handley KM. "Bacterial and archaeal community distributions and cosmopolitanism across physicochemically diverse hot springs." ISME Commun. 2023 3(1):80 https://doi.org/10.1038/s43705-023-00291-z
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