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Ecological genetics

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"Ecological Genetics" redirects here. For the book by E. B. Ford, see Ecological Genetics (book).
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Ecological genetics is the study of genetics in natural populations. It combines ecology, evolution, and genetics to understand the processes behind adaptation.[1] It is virtually synonymous with the field of molecular ecology.

This contrasts with classical genetics, which works mostly on crosses between laboratory strains, and DNA sequence analysis, which studies genes at the molecular level.

Research in this field is on traits of ecological significance—traits that affect an organism's fitness, or its ability to survive and reproduce.[1] Examples of such traits include flowering time, drought tolerance, polymorphism, mimicry, and avoidance of attacks by predators.[2]

Research usually involves a mixture of field and laboratory studies.[3] Samples of natural populations may be taken back to the laboratory for their genetic variation to be analyzed. Changes in the populations at different times and places will be noted, and the pattern of mortality in these populations will be studied. Research is often done on organisms that have short generation times, such as insects and microbial communities.[4][5]

History

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Although work on natural populations had been done previously, it is acknowledged that the field was founded by the English biologist E.B. Ford (1901–1988) in the early 20th century.[6] Ford started research on the genetics of natural populations in 1924 and worked extensively to develop his formal definition of genetic polymorphism.[7][8] Ford's magnum opus was Ecological Genetics, which ran to four editions and was widely influential.[6]

Other notable ecological geneticists include R. A. Fisher and Theodosius Dobzhansky. Fisher helped form what is known as the modern synthesis of ecology, by mathematically merging the ideas of Darwin and Mendel.[9] Dobzhansky worked on chromosome polymorphism in fruit flies. He and his colleagues carried out studies on natural populations of Drosophila species in western USA and Mexico over many years.[10][11][12]

Philip Sheppard, Cyril Clarke, Bernard Kettlewell and A.J. Cain were all strongly influenced by Ford; their careers date from the post World War II era. Collectively, their work on lepidoptera and on human blood groups established the field and threw light on selection in natural populations, where its role had been once doubted.[13]

Research

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Inheritance and Natural Selection

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Ecological genetics is closely tied to the concept of natural selection.[14] Many classical ecology works have employed aspects of ecological genetics, investigating how inheritance and the environment affect individuals.

Ecological genetics further explores how inherited genetic variation influences an organism’s ability to survive and reproduce in specific environments. Natural selection favours traits that enhance fitness, while other evolutionary forces, including mutations, gene flow, and genetic drift can play crucial roles in shaping the genetic makeup of populations. These interactions can drive local adaptation and evolutionary change. Earlier discussions questioned whether random mutation alone could account for the complexity observed in genetic sequences. [15] While this remains a point of theoretical interest, molecular tools in modern ecological genetics have enabled researchers to identify genetic variants under selection in natural populations. [15]

Industrial Melanism in Peppered Moths

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Industrial melanism in the peppered moth Biston betularia is a well-known example of the process of natural selection.[16][17] The typical wing colour phenotype of B. betularia is black and white flecks, but variant 'melanic' phenotypes with increased amounts of black also occur.[16] In the nineteenth century, the frequency of these melanic variants increased rapidly. Many biologists proposed explanations for this phenomenon. It was demonstrated in the early 1910s, and again in many later studies, that the melanic variants were a result of dominant alleles at a single locus in the B. betularia genome.[16] The proposed explanations, then, centered around various environmental factors that could contribute to natural selection. In particular, it was proposed that bird predation was selecting for the melanic moth forms, which were more cryptic in industrialized areas.[17] H. B. D. Kettlewell investigated this hypothesis extensively in the early 1950s.

Uncertainty surrounding whether birds preyed on moths at all posed an initial challenge, leading Kettlewell to perform a series of experiments with captive birds.[16][17] These experiments, while initially unsuccessful, found that when a variety of insects are provided, the birds did preferentially prey on the most conspicuous moths: those with coloration unmatched to their surroundings. Kettlewell then performed field experiments using mark-recapture techniques to investigate the selective predation of moths in their natural habitat. These experiments found that in woods near industrialized areas, melanic moth forms were recaptured at much higher rates than the traditional lighter-coloured forms, while in non-industrialized woods, the reverse held true.[17]

More recent research has further emphasized the role of genetics in the case of industrialized melanism in B. betularia. While research had already emphasized the role of alleles in determining wing-color phenotype, it was still unknown whether the melanic alleles had a single origin or had arisen multiple times independently. The use of molecular marking and chromosomal mapping in conjunction with population surveys demonstrated in the early 2010s that the melanic B. betularia variants have one single ancestral origin.[18] Additionally, the melanic variants appear to have arisen by mutation from a typical wing-colour phenotype.

Polygenic Selection

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Research on ecologically important traits has traditionally focused on single alleles.[19] However, in many cases, phenotypes are controlled by multiple alleles. Complex traits, such as traits involved in morphology, behaviour, life history or disease are often controlled by multiple alleles and are therefore polygenic traits. Through the use of genome-wide association studies (GWAS), researchers are able to scan genomes and identify loci associated with complex traits. Observing changes in allele frequency across a population can provide insight into polygenic adaptation.[20]

A major line of evidence for polygenic traits can be drawn from artificial selection. Many experiments involving artificial selection have shown that traits often respond rapidly and steadily, suggesting they are influenced by many genes with small effects. For example, between 1957 and 2001, the weight of eight-week-old chickens increased by 4 times. This sustained improvement over time wouldn’t make sense if only a few alleles of large effect were responsible for this phenotype, as the alleles would rapidly reach fixation, causing phenotypic change to plateau.[20]

The prevalence of traits with a polygenic basis poses some issues when researching traits and adaptation in natural populations. With complex traits, it may be hard to separate the effects of genes, environmental factors, and random genetic drift.[14]

Technology

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Ecological genetics combines various technologies to study the genetics underlying adaptive behaviours in populations.[21]

Animal Tracking Technologies

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Animal instrumentation provides different types of biological information, involving migration patterns, habitat selection, energy spent and temporal patterns, which are used to study population dynamics.[21] These tools include:

  • Heart-rate monitors: Assesses stress levels.
  • Accelerometers: Measures acceleration of an object for activities such as diving or foraging.
  • Acoustic recorders: Captures communication between organisms.
  • Video recorders: Observes foraging behaviour, habitat interface and social interaction.
  • Temperature loggers: Devices that measure body temperature patterns.
  • Automated image-based tracking: Tracks behavioural patterns, social interactions and predator-prey interactions.[21]

DNA Sequencing

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Once data is collected using the animal tracking technologies, DNA sequencing technologies are used to analyze the genetic composition of the studied populations.[21] DNA sequencing provides insight into the relationship between behaviour, migration patterns, and gene flow. Gene flow plays a role in evolutionary processes.[22] In order for DNA sequencing to occur, DNA samples, including blood, tissue or saliva, are collected from animals.[21] This DNA is then sequenced using next-generation sequencing (NGS) techniques, which allows for simultaneous sequencing of high quantities of DNA fragments in parallel.[23]

  • RNA sequencing: This is a NGS technique commonly used in ecological genetics. It’s used to identify all of the expressed genes in a given cell or tissue. The RNA is first reverse transcribed into cDNA and adaptors are added. These fragments are then run through next-generation sequencing technology. During next-generation sequencing, thousands of DNA fragments are sequenced simultaneously, generating thousands of reads in a single run. The reads are either aligned with a reference genome or assembled de novo. This information is used to identify differences in gene expression between tissues, species and populations.[23]
  • Chromatin-immuno-precipitation sequencing (ChIP-seq): Another NGS technology used in ecological genetics. ChIP-seq identifies differences in transcription factor binding. This is used to examine how transcription factors influence gene expression in different environments and across populations. The process of ChIP-seq involves crosslinking DNA to transcription factor proteins, then fragmenting the DNA to produce small pieces of DNA. The DNA-transcription factor complex is then isolated through immunoprecipitation, which involves the binding of an antibody to the protein. The isolated DNA can then be sequenced.[23]

SNP Genotyping

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Single nucleotide polymorphism (SNP) genotyping is a technique used to look at the nucleotides at specific loci, used as a marker for genetic variation in a population.[24] SNP genotyping allows researchers to observe changes in genotype frequencies throughout different habitats.[25]

One example of the application of SNP genotyping is the ecological genetic study by Park et al. on the Rocky Mountain Apollo butterfly (Parnassius smintheus). The researchers performed a removal experiment on certain patches to see the effect of population reduction on the neighbouring patches. 4,830 butterflies were removed from two specific patches, P and Q over the course of eight years. They genotyped a sample of the population from patch P and Q over the years, as well as samples from neighbouring patches to assess the impact of the population reduction on genetic composition. They used 152 SNP loci to study the genetic variation in the populations. When analyzing the SNPs, the researchers noticed there was no significant change in mean allelic richness or expected heterozygosity between populations despite constant removal. The percentage of loci out of Hardy-Weinberg equilibrium and percentage of SNP pairs in linkage disequilibrium increased with each year, suggesting demographic changes may have influenced the population.[25]

Other ecological genetics studies have used SNP genotyping to understand the relationship between genetic diversity in a population and environmental pressures.[26]

Environmental DNA

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Environmental DNA (eDNA) is genetic material that is collected from the environment, rather than directly from an organism. [27]

In ecological genetics, eDNA provides a non-invasive way to assess variation in population structures, detect species presence, and monitor gene flow or diversity in natural habitats. [27] This makes eDNA a valuable tool in modern ecological genetics, becoming especially useful when direct sampling is impractical or invasive.

Tissue based analysis and eDNA methods both consistently produce similar allele frequencies and genetic variation patterns within and between populations. [27] This reinforces the reliability of eDNA as an alternative to the traditional way of sampling techniques.

The ability to assess ecological and evolutionary processes across multiple levels of biological organization, where individuals to entire ecosystems can be studied, offers a powerful approach to understanding biodiversity and genetic dynamics. [28] As a result, eDNA is useful in detection of species but can further be utilized in exploring how evolutionary processes enable genetic patterns in shaping natural systems.

Generative AI and Ecological Genetics

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Generative artificial intelligence (AI) refers to models that are capable of generating new content, such as text, images, data, based on patterns learned from existing information. [29] These models are being investigated as potential complementary tools in ecological genetics, where they may support research related to evolutionary processes and environmental interactions. [30] By learning from large data sets, generative AI can be applied to predict or classify outcomes, which may include modeling scenarios such as genetic divergence, speciation, or genetic flow under various ecological condition. In some contexts, agent-based and generative models have been used to simulate patterns such as adaptive radiation, contributing to hypothetical ecological populations. [30] Generative models also have been used to explore relationships between complex traits and environmental factors, potentially linking phenotypic traits to ecological function and evolutionary patterns. [31] In addition, they may assist in addressing missing data issues resulting from limited sampling, species, rarity, or constraints in data collection methods. [30]

Limitations

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Work of this kind needs long-term funding, as well as grounding in both ecology and genetics. These are both difficult requirements. Research projects can last longer than a researcher's career; for instance, research in mimicry started 150 years ago and is still going strongly.[32][2]

See also

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References

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  1. ^ a b Conner, Jeffrey K.; Hartl, Daniel L. (2004). A primer of ecological genetics. Sunderland, Mass: Sinauer Associates. ISBN 978-0-87893-202-3.
  2. ^ a b Ruxton G.D. Sherratt T.N. and Speed M.P. 2004. Avoiding attack: the evolutionary ecology of crypsis, warning signals & mimicry. Oxford University Press.
  3. ^ Ford E.B. 1981. Taking genetics into the countryside. Weidenfeld & Nicolson, London.
  4. ^ Fellowes, Mark, ed. (2005). Insect evolutionary ecology: proceedings of the Royal Entomological Society's 22nd Symposium. Proceedings of the Royal Entomological Society's ... symposium. Wallingford: CABI Publ. ISBN 978-0-85199-812-1.
  5. ^ Kassen, Rees; Rainey, Paul B. (October 2004). "The Ecology and Genetics of Microbial Diversity". Annual Review of Microbiology. 58 (1): 207–231. doi:10.1146/annurev.micro.58.030603.123654. ISSN 0066-4227. PMID 15487936.
  6. ^ a b Ford E.B. 1975. Ecological genetics, 4th ed. Chapman and Hall, London.
  7. ^ Ford E.B. 1940. Polymorphism and taxonomy. In Huxley J. The new systematics. Oxford University Press.
  8. ^ Ford E.B. 1965. Genetic polymorphism. All Souls Studies, Faber & Faber, London.
  9. ^ Berry, Andrew; Browne, Janet (2022-07-26). "Mendel and Darwin". Proceedings of the National Academy of Sciences of the United States of America. 119 (30): e2122144119. Bibcode:2022PNAS..11922144B. doi:10.1073/pnas.2122144119. ISSN 0027-8424. PMC 9335214. PMID 35858395.
  10. ^ Dobzhansky, Theodosius. Genetics and the origin of species. Columbia, N.Y. 1st ed 1937; second ed 1941; 3rd ed 1951.
  11. ^ Dobzhansky, Theodosius 1970. Genetics of the evolutionary process. Columbia, New York.
  12. ^ Dobzhansky, Theodosius 1981. Dobzhansky's genetics of natural populations I-XLIII. R.C. Lewontin, J.A. Moore, W.B. Provine & B. Wallace, eds. Columbia University Press, New York 1981. (reprints the 43 papers in this series, all but two of which were authored or co-authored by Dobzhansky)
  13. ^ Cook, Laurence M. (2024-06-10). "Arthur Cain and ecological genetics in the Oxford Zoology Department". Archives of Natural History. 51: 73–85. doi:10.3366/anh.2024.0897.
  14. ^ a b Beebee, Trevor J. C.; Rowe, Graham (2008). An introduction to molecular ecology (2nd ed.). Oxford; New York: Oxford University Press. ISBN 978-0-19-929205-9.
  15. ^ a b Salisbury, Frank B. (1969-10-25). "Natural Selection and the Complexity of the Gene". Nature. 224 (5217): 342–343. Bibcode:1969Natur.224..342S. doi:10.1038/224342a0. ISSN 0028-0836.
  16. ^ a b c d Cook, L M; Saccheri, I J (2013). "The peppered moth and industrial melanism: evolution of a natural selection case study". Heredity. 110 (3): 207–212. Bibcode:2013Hered.110..207C. doi:10.1038/hdy.2012.92. ISSN 0018-067X. PMC 3668657. PMID 23211788.
  17. ^ a b c d Rudge, David W. (2005). "The Beauty of Kettlewell's Classic Experimental Demonstration of Natural Selection". BioScience. 55 (4): 369. doi:10.1641/0006-3568(2005)055[0369:TBOKCE]2.0.CO;2. ISSN 0006-3568.
  18. ^ van't Hof, Arjen E.; Edmonds, Nicola; Dalíková, Martina; Marec, František; Saccheri, Ilik J. (2011). "Industrial Melanism in British Peppered Moths Has a Singular and Recent Mutational Origin". Science. 332 (6032): 958–960. Bibcode:2011Sci...332..958V. doi:10.1126/science.1203043. ISSN 0036-8075. JSTOR 29784314. PMID 21493823.
  19. ^ Fuhrmann, Nico; Prakash, Celine; Kaiser, Tobias S (2023-02-28). Weigel, Detlef (ed.). "Polygenic adaptation from standing genetic variation allows rapid ecotype formation". eLife. 12: e82824. doi:10.7554/eLife.82824. ISSN 2050-084X. PMC 9977305. PMID 36852484.
  20. ^ a b Sella, Guy; Barton, Nicholas H. (2019-08-31). "Thinking About the Evolution of Complex Traits in the Era of Genome-Wide Association Studies". Annual Review of Genomics and Human Genetics. 20 (1): 461–493. doi:10.1146/annurev-genom-083115-022316. ISSN 1527-8204. PMID 31283361.
  21. ^ a b c d e Shafer, Aaron B. A.; Northrup, Joseph M.; Wikelski, Martin; Wittemyer, George; Wolf, Jochen B. W. (2016-01-08). "Forecasting Ecological Genomics: High-Tech Animal Instrumentation Meets High-Throughput Sequencing". PLOS Biology. 14 (1): e1002350. doi:10.1371/journal.pbio.1002350. ISSN 1545-7885. PMC 4712824. PMID 26745372.
  22. ^ Müller, Mara F.; Banks, Sam C.; Crewe, Tara L.; Campbell, Hamish A. (2023). "The rise of animal biotelemetry and genetics research data integration". Ecology and Evolution. 13 (3): e9885. Bibcode:2023EcoEv..13E9885M. doi:10.1002/ece3.9885. ISSN 2045-7758. PMC 10019913. PMID 36937069.
  23. ^ a b c Kratochwil, Claudius F.; Meyer, Axel (2015). "Closing the genotype–phenotype gap: Emerging technologies for evolutionary genetics in ecological model vertebrate systems". BioEssays. 37 (2): 213–226. doi:10.1002/bies.201400142. ISSN 1521-1878. PMID 25380076.
  24. ^ Nascimento-Schulze, Jennifer C.; Bean, Tim P.; Peñaloza, Carolina; Paris, Josephine R.; Whiting, James R.; Simon, Alexis; Fraser, Bonnie A.; Houston, Ross D.; Bierne, Nicolas; Ellis, Robert P. (2023). "SNP discovery and genetic structure in blue mussel species using low coverage sequencing and a medium density 60 K SNP-array". Evolutionary Applications. 16 (5): 1044–1060. Bibcode:2023EvApp..16.1044N. doi:10.1111/eva.13552. ISSN 1752-4571. PMC 10197230. PMID 37216031.
  25. ^ a b Park, Keon Young; Lucas, Mel; Chaulk, Andrew; Matter, Stephen F.; Roland, Jens; Keyghobadi, Nusha (2024-07-31). "Immigration allows population persistence and maintains genetic diversity despite an attempted experimental extinction". Royal Society Open Science. 11 (7): 240557. Bibcode:2024RSOS...1140557P. doi:10.1098/rsos.240557. PMC 11288673. PMID 39086829.
  26. ^ Akohoue, Félicien; Achigan-Dako, Enoch Gbenato; Sneller, Clay; Deynze, Allen Van; Sibiya, Julia (2020-06-30). "Genetic diversity, SNP-trait associations and genomic selection accuracy in a west African collection of Kersting's groundnut [Macrotyloma geocarpum(Harms) Maréchal & Baudet]". PLOS ONE. 15 (6): e0234769. Bibcode:2020PLoSO..1534769A. doi:10.1371/journal.pone.0234769. ISSN 1932-6203. PMC 7326195. PMID 32603370.
  27. ^ a b c Andres, Kara J.; Lodge, David M.; Andrés, Jose (2023-09-12). "Environmental DNA reveals the genetic diversity and population structure of an invasive species in the Laurentian Great Lakes". Proceedings of the National Academy of Sciences. 120 (37). Bibcode:2023PNAS..12007345A. doi:10.1073/pnas.2307345120. ISSN 0027-8424. PMC 10500163. PMID 37669387.
  28. ^ Blackman, Rosetta; Couton, Marjorie; Keck, François; Kirschner, Dominik; Carraro, Luca; Cereghetti, Eva; Perrelet, Kilian; Bossart, Raphael; Brantschen, Jeanine; Zhang, Yan; Altermatt, Florian (2024-04-16). "Environmental DNA : The next chapter". Molecular Ecology. 33 (11): e17355. Bibcode:2024MolEc..33E7355B. doi:10.1111/mec.17355. ISSN 0962-1083. PMID 38624076.
  29. ^ Bommasani, Rishi; Hudson, Drew A.; Adeli, Ehsan; Altman, Russ; Arora, Simran; von Arx, Sydney; Bernstein, Michael S.; Bohg, Jeannette; Bosselut, Antoine (2021), On the Opportunities and Risks of Foundation Models, arXiv:2108.07258, retrieved 2025-04-04
  30. ^ a b c Rafiq, Kasim; Beery, Sara; Palmer, Meredith S.; Harchaoui, Zaid; Abrahms, Briana (2025-01-29). "Generative AI as a tool to accelerate the field of ecology". Nature Ecology & Evolution. 9 (3): 378–385. Bibcode:2025NatEE...9..378R. doi:10.1038/s41559-024-02623-1. ISSN 2397-334X. PMID 39880986.
  31. ^ Dinnage, Russell; Kleineberg, Marian (2025-03-17). D'Andrea, Rafael (ed.). "Generative AI extracts ecological meaning from the complex three dimensional shapes of bird bills". PLOS Computational Biology. 21 (3): e1012887. doi:10.1371/journal.pcbi.1012887. ISSN 1553-7358. PMC 11940575. PMID 40096239.
  32. ^ Mallet J. and Joron M. 1999. Evolution in diversity in warning color and mimicry: polymorphisms, shifting balance and speciation. Annual Review of Ecological Systematics 1999. 30 201–233

Further reading

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  • Cain A.J. and W.B. Provine 1992. Genes and ecology in history. In: R.J. Berry, T.J. Crawford and G.M. Hewitt (eds). Genes in ecology. Blackwell Scientific: Oxford. Provides a good historical background.
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