16.6: Study Guide: Mechanisms of Evolution - Biology

16.6: Study Guide: Mechanisms of Evolution - Biology

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Study Questions

Objective: Compare and contrast the many mechanisms by which evolutionary change occurs.

Use this page to check your understanding of the content.


  1. Evolution.
  2. Natural selection
  3. Mutation
  4. Gene flow
  5. Genetic drift
  6. Sexual selection

Study Guide Questions

  1. Be able to identify, compare, contrast, and discuss the various mechanisms of microevolution, including:
    1. Mutation
    2. Gene flow
    3. Genetic drift
    4. Sexual selection
    5. Natural selection
  1. What are the observations that led to Darwin’s conclusions regarding natural selection?
  2. Compare and contrast sexual selection and natural selection.
  3. What is the difference between microevolution and macroevolution? Please don’t just memorize the definitions…be able to APPLY your definitions to different scenarios! For good practice, think of examples of each!
  4. Clearly explain HOW speciation occurs…
  5. Clearly describe each of the following forms of reproductive isolation. Be able to compare and contrast each form.
    1. Geographic
    2. Ecological
    3. Temporal
    4. Behavioral
    5. Mechanical
    6. Gametic isolation
    7. Hybrid inviability
  1. Given any scenario, be able to determine the TYPE of reproductive isolation that is occurring. Make up scenarios and practice!
  2. Explain the connection between reproductive isolation, speciation, and microevolution.

Diversity Takes Shape: Understanding the Mechanistic and Adaptive Basis of Bacterial Morphology

The modern age of metagenomics has delivered unprecedented volumes of data describing the genetic and metabolic diversity of bacterial communities, but it has failed to provide information about coincident cellular morphologies. Much like metabolic and biosynthetic capabilities, morphology comprises a critical component of bacterial fitness, molded by natural selection into the many elaborate shapes observed across the bacterial domain. In this essay, we discuss the diversity of bacterial morphology and its implications for understanding both the mechanistic and the adaptive basis of morphogenesis. We consider how best to leverage genomic data and recent experimental developments in order to advance our understanding of bacterial shape and its functional importance.

Citation: Kysela DT, Randich AM, Caccamo PD, Brun YV (2016) Diversity Takes Shape: Understanding the Mechanistic and Adaptive Basis of Bacterial Morphology. PLoS Biol 14(10): e1002565.

Published: October 3, 2016

Copyright: © 2016 Kysela et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM51986 to YVB and by National Research Service Award F32GM112362 to AMR. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: FDAA, fluorescent D-amino acid PG, peptidoglycan


Epithelial ovarian cancer generally presents at an advanced stage and is the most common cause of gynaecological cancer death. Treatment requires expert multidisciplinary care. Population-based screening has been ineffective, but new approaches for early diagnosis and prevention that leverage molecular genomics are in development. Initial therapy includes surgery and adjuvant therapy. Epithelial ovarian cancer is composed of distinct histological subtypes with unique genomic characteristics, which are improving the precision and effectiveness of therapy, allowing discovery of predictors of response such as mutations in breast cancer susceptibility genes BRCA1 and BRCA2, and homologous recombination deficiency for DNA damage response pathway inhibitors or resistance (cyclin E1). Rapidly evolving techniques to measure genomic changes in tumour and blood allow for assessment of sensitivity and emergence of resistance to therapy, and might be accurate indicators of residual disease. Recurrence is usually incurable, and patient symptom control and quality of life are key considerations at this stage. Treatments for recurrence have to be designed from a patient's perspective and incorporate meaningful measures of benefit. Urgent progress is needed to develop evidence and consensus-based treatment guidelines for each subgroup, and requires close international cooperation in conducting clinical trials through academic research groups such as the Gynecologic Cancer Intergroup.

Synthetic biology is a design-driven discipline centered on engineering novel biological functions through the discovery, characterization, and repurposing of molecular parts. Several synthetic biological solutions to critical biomedical problems are on the verge of widespread adoption and demonstrate the burgeoning maturation of the field. Here, we highlight applications of synthetic biology in vaccine development, molecular diagnostics, and cell-based therapeutics, emphasizing technologies approved for clinical use or in active clinical trials. We conclude by drawing attention to recent innovations in synthetic biology that are likely to have a significant impact on future applications in biomedicine.

These authors contributed equally

Chang and Malik highlight a new study (pgen.1009418) showing an active co-evolutionary arms race between DNA and protein components of the meiotic machinery in Mimulus, with consequences for individual fitness and molecular divergence.

Image credit: Finseth et al., pgen.1009418

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Materials and Methods


Throughout both experiments, we used laboratory-reared, fourth instar larvae of the Early Thorn moth Selenia dentaria. This species is an inch-worm (family Geometridae) that it is polyphagous on a wide range of deciduous broadleaved shrubs and trees benefits from masquerade (7) does not reflect light in the UV spectrum and has no known color polymorphism (see SI Materials and Methods and Fig. S1 for further details).

Predation Experiment.

On day 2 of life, 32 chicks that had been acclimatized to the experimental arena (see SI Materials and Methods) were divided into two groups of 16. Individuals in each group where given two trials, in each of which they were allowed to find and consume one caterpillar from a branch that also contained nine twigs. The branch was manipulated for one group, but not manipulated for the other. Manipulated branches were bound in purple cotton thread to change their visual appearance without influencing their physical structure or odor (7). The purpose of these trials was to train chicks to forage for caterpillars on the branches.

On day 3, each group was split into two, giving four groups in all. Chicks in all groups experienced 10 presentations of an unmanipulated or manipulated branch (in line with their previous experience) in the arena. Each presentation lasted 90 s, and there was an interval of 90 s between presentations. The presentations could be of one of three types: a branch containing 9 twigs and a caterpillar, a branch containing 10 twigs and no caterpillar, or a null presentation where there was nothing in the arena. All groups experienced four presentations of a branch with nine twigs and a caterpillar. Two groups (one with manipulated branches and one without) experienced a high exposure level to unrewarding branches with 10 twigs and no caterpillar (five presentations) plus one null presentation the other two groups experienced a low exposure level to unrewarding branches with 10 twigs and no caterpillar (one presentation) and five null presentations. The order of the 10 presentations was randomized for each individual. This method of presentation was chosen because it allowed twig number to be manipulated without changing either the number of caterpillars presented or the complexity of the visual task (chicks always had to find one caterpillar among nine twigs).

At the end of day 3, the chicks were given a single test trial. This consisted of a manipulated or unmanipulated (consistent with each chick's previous experience) branch containing nine twigs and one caterpillar. Latency to attack the caterpillar was recorded. In one case, the trial was stopped after 10 min because the chick showed no interest in the branch this chick was awarded a latency of 601 s in the analysis.

On day 4, the chicks from the low-exposure groups were given two trials to explore whether the number of twigs on the branch affected the time taken to find the caterpillar (i.e., whether it was more difficult to find caterpillars in more complex environments). In one trial, the chick was offered a branch with 5 twigs and one caterpillar, in the other the branch had 15 twigs and one caterpillar. The order of trials was counterbalanced within groups. The trials were 90 s apart.

Caterpillar Choice Experiment.

Experiments were performed in the laboratory in which caterpillars were housed (see SI Materials and Methods for housing details), in July and August 2009. Daytime measurements were taken between 10:00 AM and 2:00 PM (illuminated by sunlight only), and nighttime measures were taken between 10:00 PM and 2:00 AM (illuminated by moonlight and starlight only). Caterpillars were placed into choice chambers, a clear plastic tank measuring 33 × 18 × 18 cm with a cling-film lid, individually using a paintbrush. White paper covered the floor of the tank and was changed every trial. A pencil mark indicated the center of the chamber, and a single branch was placed on either side of this line, 5 cm from the line at the closest point. Caterpillars were placed on the pencil line facing neither branch. They were left for 30 min, after which the branch on which the caterpillar was located was recorded: five caterpillars were not located on a branch so they were removed from the analysis. The primary difference between the two branches was in the number of twigs. Each branch was 25 cm in length, one with four twigs (low twig number) and one with eight twigs (high twig number). Twigs on both branches were ∼3.5 cm in length and 3 mm in diameter. The number of twigs on the branches was not manipulated in any way, and therefore represented natural variation. Experimental groups differed in which of the branches possessed leaves, their hunger levels, and the perceived predation risk: see Table 1 for details. When required, food deprivation was achieved by removing the leaves from the caterpillar's host plant 24 h before the start of the experiment. Predation was simulated by gently squeezing caterpillars with tweezers three times immediately before moving it to the experimental chamber (no caterpillar was visibly injured by this process). Each choice was investigated using 30 replicate caterpillars.

Integrative Biology 200B Readings

= required in 2011 course other special recommendations starred for direct relevance to the course, basic to the field ("something everyone should have read"), etc.

Bock, W. J. (1973) Philosophical foundations of classical evolutionary classification Systematic Zoology 22: 375-392 Part of a general symposium on "Contemporary Systematic Philosophies," there are some other interesting papers here.

Brower, A. V. Z. (2000) Evolution Is Not a Necessary Assumption of Cladistics Cladistics 16: 143-154

Cleland, C. L. (2001) Historical science, experimental science, and the scientific method. Geology 29: 987-990

Dayrat, Benoit (2005) Ancestor-descendant relationships and the reconstruction of the Tree of Lif Paleobiology 31: 347-353

Donoghue, M.J. and J.W. Kadereit (1992) Walter Zimmermann and the growth of phylogenetic theory Systematic Biology 41: 74-84

Faith, D. P. and J. W. H. Trueman (2001) Towards an inclusive philosophy for phylogenetic inference Systematic Biology 50: 331-350

Gaffney, E. S. (1979) An introduction to the logic of phylogeny reconstruction, pp. 79-111 in Cracraft, J. and N. Eldredge (eds.) Phylogenetic Analysis and Paleontology Columbia University Press, New York.

Gilmour, J. S. L. (1940) Taxonomy and philosophy, pp. 461-474 in J. Huxley (ed.) The New Systematics Oxford

Hull, D. L. (1974) Philosophy of Biological Sciences. Prentice-Hall, Englewood Cliffs, NJ.

Hull, D. L. (1978) A matter of individuality Phil. of Science 45: 335-360

Hull, D. L. (1978) The principles of biological classification: the use and abuse of philosophy

Hull, D. L. (1984) Cladistic theory: hypotheses that blur and grow, pp. 5-23 in T. Duncan and T. F. Stuessy (eds.) Cladistics: Perspectives on the Reconstruction of Evolutionary History Columbia University Press, New York

* Hull, D. L. (1988) Science as a process: an evolutionary account of the social and conceptual development of science University of Chicago Press. An already classic work on the recent, violent history of systematics used as data for Hull's general theories about scientific change.

Hull, D. L. (1999) The use and abuse of Sir Karl Popper. Biology and Philosophy 14: 481-504

Kitts, D. B. (1977) Karl Popper, verifiability, and systematic zoology. Systematic Zoology 26: 185-194

Kluge, A. G. (1999) The Science of Phylogenetic Systematics: Explanation, Prediction and Test Cladistics 15: 429-436

Kluge, A. J. (2001) Philosophical conjectures and their refutation Systematic Biology 50: 322-330

Kuhn, T. S. (1970) The Structure of Scientific Revolutions, second edition. University of Chicago Press. A must-read for any scientist.

Mayr, E. (1982) The Growth of Biological Thought. Harvard University Press, Cambridge, Mass.

Laudan, L. (1977) Progress and Its Problems. University of California Press, Berkley.

Losee, J. (1980) A Historical Introduction to the Philosophy of Science. Second edition. Oxford University Press. The best single-volume account of changes since Aristotle in how science proceeds -- strongly recommended.

McKelvey, B. (1982) Organizational Systematics, Univ. of California Press Berkeley

Mishler, B. D. (1989) Untitled review of Hull, D.L. (1988) Science as a process. Systematic Botany 14: 266-268

O'Hara, R. J. (1992) Telling the tree: Narrative representation and the study of evolutionary history Biology and Philosophy 7: 135-160

O'Keefe, F. R. and P. M. Sander (1999) Paleontological paradigms and inferences of phylogenetic pattern: a case study. Paleobiology 25: 518-533

de Queiroz, K (1987) Systematics and the Darwinian revolution. Philosophy of Science 55: 238-259

de Queiroz, K. and S. Poe (2001) Philosophy and phylogenetic inference: a comparison of likelihood and parsimony methods in the context of Karl Popper's writings on corroboration. Systematic Biology 50: 305-321

Sober, E. (1988) Reconstructing the past, Chapter 1. MIT Press.

** Sober, E. (2008). Evidence and Evolution: the logic behind the science, Cambridge University Press. Particularly good on philosophy of statistics (frequentism vs. likelihood vs. Bayesian approaches) and their relation to (1) inferring phylogenies and (2) inferring natural selection.

Stamos, D. N. (1996) Popper, falsifiability, and evolutionary biology. Biology and Philosophy 11: 161-191

Stevens, P. F. (1994) The development of biological systematics. Columbia University Press, New York.

Wiley, E. O. (1975) Karl R. Popper, systematics, and classification: a reply to Walter Bock and other evolutionary taxonomists. Systematic Zoology 24: 233-243

Wiley, E. O. (1981) Phylogenetics: The Theory and Practice of Phylogenetic Systematics.

Winsor, Mary Pickard (1995). "The english debate on taxonomy and phylogeny." History and Philosopy of the Life Sciences, 17(2), 227-252.

Ax, P. (1987) The phylogenetic system. John Wiley, Chichester.

Dupuis, C. (1984) Willi Hennig? s impact on taxonomic thought. Annual Review of Ecology and Systematics 15: 1-24

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Philippe Grandcolas, P., P. Deleporte, L. Desutter-Grandcolas, and C. Daugeron (2001) Phylogenetics and Ecology: As Many Characters as Possible Should Be Included in the Cladistic Analysis. Cladistics 17: 104-110

** Hennig, W. (1965) Phylogenetic systematics. Annual Review of Entomology 10: 97-116

Hennig, W. (1966) Phylogenetic systematics. University of Illinois Press, Urbana.

Kitching, I. J., P. L. Forey, C. J. Humpheries, and D. M. Williams. (1998) Cladistics: The Theory and Practice of Parsimony Analysis. Second Edition. The Systematics Association Publication No. 11 Oxford University Press, Oxford.

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** Roth, V.L. (1988) The biological basis of homology. In Ontogeny and Systematics. Humpries, C.J. (ed.) Columbia University Press, NY.

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Buschbeck, E. K. (2000) Neurobiological constraints and fly systematics: how different types of neural characters can contribute to a higher level dipteran phylogeny. Evolution 54: 888-898

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Hibbett, D. S. and M. J. Donoghue (2001) Analysis of character correlations among wood decay mechanisms, mating systems, and substrate ranges in Homobasidiomycetes. Systematic Biology 51: 215-242

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** Mishler, B. D. (2005) The logic of the data matrix in phylogenetic analysis. In V.A. Albert (ed.), Parsimony, Phylogeny, and Genomics, pp. 57-70. Oxford University Press.

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Under Pressure: How Selection by Vaccine-Generated Immunity Can Shape Evolution of Wild-Type Viruses

Viruses evolve in response to natural herd immunity, and it stands to reason that sufficiently high levels of vaccine-induced immunity could also shape virus evolution (Boni 2008). Evolution of wild-type viruses in response to deployment of live-attenuated vaccines has been observed in several veterinary viruses, including avian metapneumovirus (Catelli et al. 2010 Cecchinato et al. 2010) and avian influenza virus (Park et al. 2011 Lee et al. 2004). The effects of such vaccine-driven evolution on virus virulence and transmissibility in unvaccinated animals have yet to be determined. However, theoretical studies have raised the concern that “imperfect vaccines,” vaccines that do not induce sterilizing immunity but rather modulate disease or transmission, could select for increasing virulence in the wild-type virus targeted by vaccination (Gandon et al. 2003 Mackinnon et al. 2008 Gandon and Day 2007 Andre and Gandon 2006 Ganusov and Antia 2006 Massad et al. 2006). Intriguingly, Manuel et al. (Manuel et al. 2010) recently reported that imperfect vaccination can prevent reversion to virulence in a simian-human immunodeficiency virus (SHIV). They generated a SHIV carrying an attenuating mutation and then infected both naïve and vaccinated monkeys with this virus. The attenuated SHIV reverted to virulence through back-mutation in the naïve, but not the vaccinated, monkeys. The investigators attribute this effect to the overall decrease in SHIV replication in the vaccinated monkeys, suggesting that imperfect vaccines may act as a brake on the evolution of their wild-type counterparts.

The ultimate goal of many vaccination programs is the eradication of specific wild-type viruses. This goal has been achieved for variola virus, the agent of smallpox, is within reach for poliovirus (Kew et al. 2005) and perhaps measles virus (Castillo-Solorzano et al. 2011 Moss 2009), and remains a tempting target for many existing and candidate vaccine programs. While there is no question that eradication represents a quantum leap for public health, some thought must be given to the empty niche that eradication creates. Recent increases in monkeypox have been attributed to the eradication of, and cessation of vaccination against, smallpox (Rimoin et al. 2010). Moreover, Coxsackie A virus (Rieder et al. 2001) and sylvatic dengue virus (Vasilakis et al. 2011) could potentially emerge to fill the niches left vacant should polio and human dengue virus, respectively, be eradicated. Evolutionary analysis will be needed to predict the impacts of eradication on future viral emergence.


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McCune, K., McElreath, R., & Logan, C. J. (in press). Investigating the use of learning mechanisms in a species that is rapidly expanding its geographic range (In principle acceptance by PCI Ecology of the version on 11 Oct 2019). Peer Community in Ecology, 100032.
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Watch the video: Mechanisms of Evolution 101 (February 2023).