Experimental Evolution with Yeast Clifford Zeyl
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E D I T O R I a L
E D I T O R I A L A MECHANISM FOR RAPID CHANGE? In a highly recommended book1 Del Ratzsch notes that creationists and evolutionists often criticize each other for positions that are more imagined than real. One of the most common misconceptions is the alleged creationist belief in fixity of species.2 One may read dogmatic statements that creation theory cannot be true because Noah’s ark could not hold all the species of beetles, etc. Such arguments seem misguided to many creationists. I doubt any creationist believes that the ark needed to hold 250,000 or more species of beetles. One reason this criticism seems misguided is that creation theory includes the expectation of change in species. Whether every species of beetle depended on the ark for survival is an interesting question that will not be pursued here. The Bible includes several statements that indicate that change in species is to be expected. Genesis 3 records the story of the sin of Adam and Eve, followed by the curses pronounced on nature. As a result of those curses, the serpent was to crawl on its belly, and thorns and thistles would be produced. If these conditions already existed, they could not be attributed to the curses resulting from sin. Thus, these species would change. Another suggestion that plants would change is found in Genesis 2:5, which states that certain types of plants had not yet appeared.3 The text seems to be referring to the spiny xerophytic plants now common in Israel, but the changes that produced this type of plant had not yet occurred at the time Adam was created. -
Spike Protein Mutational Landscape in India: Could Muller’S Ratchet Be a Future Game
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.18.255570; this version posted August 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Spike protein mutational landscape in India: Could Muller’s ratchet be a future game- changer for COVID-19? Rachana Banerjeea, Kausik Basaka, Anamika Ghoshb, Vyshakh Rajachandranc, Kamakshi Surekaa, Debabani Gangulya,1, Sujay Chattopadhyaya,1 aCentre for Health Science and Technology, JIS Institute of Advanced Studies and Research Kolkata, JIS University, 700091, West Bengal, India. bDepartment of Chemistry, Indian Institute of Engineering Science and Technology, Shibpur, 711103, West Bengal, India. cSchool of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam, 690525, Kerala, India. 1To whom correspondence may be addressed. Email: [email protected] or [email protected] Classification Major: Biological Sciences, Minor: Evolution Keywords: SARS-CoV-2, Muller's ratchet, mutational meltdown, molecular docking, viral evolutionary dynamics 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.18.255570; this version posted August 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract The dire need of effective preventive measures and treatment approaches against SARS-CoV-2 virus, causing COVID-19 pandemic, calls for an in-depth understanding of its evolutionary dynamics with attention to specific geographic locations, since lockdown and social distancing to prevent the virus spread could lead to distinct localized dynamics of virus evolution within and between countries owing to different environmental and host-specific selection pressures. -
Genetic and Demographic Dynamics of Small Populations of Silene Latifolia
Heredity (2003) 90, 181–186 & 2003 Nature Publishing Group All rights reserved 0018-067X/03 $25.00 www.nature.com/hdy Genetic and demographic dynamics of small populations of Silene latifolia CM Richards, SN Emery and DE McCauley Department of Biological Sciences, Vanderbilt University, PO Box 1812, Station B, Nashville, TN 37235, USA Small local populations of Silene alba, a short-lived herbac- populations doubled in size between samples, while others eous plant, were sampled in 1994 and again in 1999. shrank by more than 75%. Similarly, expected heterozygosity Sampling included estimates of population size and genetic and allele number increased by more than two-fold in diversity, as measured at six polymorphic allozyme loci. individual populations and decreased by more than three- When averaged across populations, there was very little fold in others. When population-specific change in number change between samples (about three generations) in and change in measures of genetic diversity were considered population size, measures of within-population genetic together, significant positive correlations were found be- diversity such as number of alleles or expected hetero- tween the demographic and genetic variables. It is specu- zygosity, or in the apportionment of genetic diversity within lated that some populations were released from the and among populations as measured by Fst. However, demographic consequences of inbreeding depression by individual populations changed considerably, both in terms gene flow. of numbers of individuals and genetic composition. Some Heredity (2003) 90, 181–186. doi:10.1038/sj.hdy.6800214 Keywords: genetic diversity; demography; inbreeding depression; gene flow Introduction 1986; Lynch et al, 1995), the interaction of genetics and demography could also influence population persistence How genetics and demography interact to influence in common species, because it is generally accepted that population viability has been a long-standing question in even many abundant species are not uniformly distrib- conservation biology. -
Genetic Threats to Population Persistence
Ann. Zool. Fennici 40: 155–168 ISSN 0003-455X Helsinki 30 April 2003 © Finnish Zoological and Botanical Publishing Board 2003 Genetic threats to population persistence Oscar E. Gaggiotti Metapopulation Research Group, Department of Ecology and Systematics, P.O. Box 65, FIN-00014 University of Helsinki, Finland (e-mail: oscar.gaggiotti@helsinki.fi ) Received 27 Nov. 2002, revised version received 20 Jan. 2003, accepted 20 Jan. 2003 Gaggiotti, O. E. 2003: Genetic threats to population persistence. — Ann. Zool. Fennici 40: 155–168. Human activities are having a devastating effect on the survival of natural popula- tions. The reduction in population size and changes in the connectivity of populations due to human disturbances enhance the effect of demographic and genetic factors that can lead to population extinction. This article provides an overview of our current understanding of the role of genetic factors in the extinction of populations. The three primary genetic factors are loss of genetic variability, inbreeding depression, and accu- mulation of mildly deleterious mutations. The effects of these factors are discussed in the context of three different scenarios: isolated populations, local populations with immigration, and metapopulations. Introduction demographic and genetic factors (Lande 1988). However, the last decade has witnessed much Although the extinction of populations is a natu- progress in this area and there is a general agree- ral phenomenon, human induced habitat loss, ment that, although the most immediate causes pollution and overexploitation have increased of extinction are human predation, introduction extinction rates well above background levels of exotic species and habitat loss, genetic factors and have lead to the mass extinction that we are can still play an important role. -
Michael Behe Makes the Argument That
Opening the Black Box Throughout “Darwin’s Black Box”, Michael Behe makes the argument that Darwinian evolution can’t be used as a universal explanation for all of life, because it can’t account for irreducibly complex organisms. However, Behe also neglects to acknowledge any existing research that suggests otherwise. A study conducted at Michigan State University by scientist Richard Lenski has shown that there could be a scientific explanation for these seemingly irreducibly complex organism, and that Behe shouldn’t be so quick to point to a supernatural solution, or to call it quits so soon when his mousetrap breaks. While Behe may think he has all the answers, contrary research has shown there are other answers worth consideration. Behe begins his argument by introducing the idea of organisms that are irreducibly complex, otherwise defined as a “single system composed of several well-matched, interacting parts that contribute to the basic function of the system, wherein the removal of any one of the parts causes the system to effectively cease functioning” (Darwin’s Black Box, 39). In order to demonstrate this principle, Behe raises the example of a mousetrap. He argues that if you remove one part of a mousetrap, it will cease to function, and because of this, all of the parts must have evolved simultaneously in order for a mousetrap to exist, therefor rendering it irreducibly complex. However, is any of this really true? Besides the holes in Behe’s mousetrap argument, there also lies the fact that mousetraps are not living creatures and therefore are incapable of evolution. -
Fixation of New Mutations in Small Populations
Whitlock MC & Bürger R (2004). Fixation of New Mutations in Small Populations. In: Evolutionary Conservation Biology, eds. Ferrière R, Dieckmann U & Couvet D, pp. 155–170. Cambridge University Press. c International Institute for Applied Systems Analysis 9 Fixation of New Mutations in Small Populations Michael C. Whitlock and Reinhard Bürger 9.1 Introduction Evolution proceeds as the result of a balance between a few basic processes: mu- tation, selection, migration, genetic drift, and recombination. Mutation is the ulti- mate source of all the genetic variation on which selection may act; it is therefore essential to evolution. Mutations carry a large cost, though; almost all are delete- rious, reducing the fitness of the organisms in which they occur (see Chapter 7). Mutation is therefore both a source of good and ill for a population (Lande 1995). The overall effect of mutation on a population is strongly dependent on the pop- ulation size. A large population has many new mutations in each generation, and therefore the probability is high that it will obtain new favorable mutations. This large population also has effective selection against the bad mutations that occur; deleterious mutations in a large population are kept at a low frequency within a balance between the forces of selection and those of mutation. A population with relatively fewer individuals, however, will have lower fitness on average, not only because fewer beneficial mutations arise, but also because deleterious mutations are more likely to reach high frequencies through random genetic drift. This shift in the balance between fixation of beneficial and deleterious mutations can result in a decline in the fitness of individuals in a small population and, ultimately, may lead to the extinction of that population. -
Chapter 6.Qxp
Testing Darwin Digital organisms that breed thousands of times faster than common bacteria are beginning to shed light on some of the biggest unanswered questions of evolution BY CARL ZIMMER F YOU WANT TO FIND ALIEN LIFE-FORMS, does this. Metabolism? Maybe not quite yet, but Ihold off on booking that trip to the moons of getting pretty close.” Saturn. You may only need to catch a plane to East Lansing, Michigan. One thing the digital organisms do particularly well is evolve. “Avida is not a simulation of evolu- The aliens of East Lansing are not made of car- tion; it is an instance of it,” Pennock says. “All the bon and water. They have no DNA. Billions of them core parts of the Darwinian process are there. These are quietly colonizing a cluster of 200 computers in things replicate, they mutate, they are competing the basement of the Plant and Soil Sciences building with one another. The very process of natural selec- at Michigan State University. To peer into their tion is happening there. If that’s central to the defi- world, however, you have to walk a few blocks west nition of life, then these things count.” on Wilson Road to the engineering department and visit the Digital Evolution Laboratory. Here you’ll It may seem strange to talk about a chunk of find a crew of computer scientists, biologists, and computer code in the same way you talk about a even a philosopher or two gazing at computer mon- cherry tree or a dolphin. But the more biologists itors, watching the evolution of bizarre new life- think about life, the more compelling the equation forms. -
Life's Conservation Law: Why Darwinian
William A. Dembski and Robert J. Marks II, "Life's Conservation Law: Why Darwinian Evolution Cannot Create Biological Information" in Bruce Gordon and William Dembski, editors, The Nature of Nature (Wilmington, Del.: ISI Books, 2011) pp.360-399 E F E IS an irn:volcaIJ!e selection and exclusion. as when you marry one woman you up all the so when you take one course of action you up all the other courses."4 Intelligence creates information. Bur is the causal power of Darwin's main claim to fame is that he is supposed to have a that could create informa- tion without the need intelligence. Interestingly, he to this mechanism as "natural selection." Sel.e~tion, as understood before had been an activity confined to intelligent agents. Darwll1 s great coup was to the power to nature-hence "natural selection." as conceived Darwin and his acts without is non-teleo- and therefore unintelligent. As genetlClst Coyne puts it in opposing intdlige:nt "If we're to defend we must defend it as a science: a in which the of life results from the action natural selection and on random mutations."5 But do and Darwinists insist that to count as must be non-teleological?6 did that rule come from? The of with the sciences is itselfa well-established science-it's called engineering. conceived, to the engi- ne.:::nng SCIences. 1. THE CREATION OF INFORMATION But to return to the at does nature really possess the power to select and th,>rph" create To answer this we to turn to relation between po~,sit)ilil:ies to create inlonnal:1011. -
The Landscape of Innovation in Bacteria, Battleships, and Beyond Downloaded by Guest on October 1, 2021 Thus, Fig
SPECIAL FEATURE: PERSPECTIVE The landscape of innovation in bacteria, battleships, and beyond SPECIAL FEATURE: PERSPECTIVE Terence C. Burnhama,b,1 and Michael Travisanoc,d,1,2 Edited by Simon A. Levin, Princeton University, Princeton, NJ, and approved November 18, 2020 (received for review August 12, 2020) We draw lessons from microbial experimental evolution and naval warfare to improve the understanding of innovation in financial markets. Major financial innovations often arise without explicit societal planning because novel approaches can be favored by markets, in a manner strikingly parallel to natural selection. We utilize the concept of an adaptive landscape to characterize environments that increase the speed and magnitude of innovation. We apply this adaptive landscape framework to innovation in portfolio management. We create a general taxonomy for understanding and nurturing innovation. adaptation | experimental evolution | finance | innovation What environmental characteristics favor innovation? relationship between design and performance. Con- We begin with an examination of innovation evident in sequently, both battleship and bacterial innovation naval warfare, primarily the design and function of can be represented in a similar adaptive landscape. battleships. Improvements in battleships suggest that We draw general lessons regarding approaches to fierce competition fosters innovation. innovation, aided by the adaptive landscape repre- While the battleship heuristic appears straightfor- sentation. The goal is to understand innovation in ward, the study of any historical set of innovations has finance and other domains. From this perspective, we the challenge of disentangling causation from corre- analyze one area of finance: the management of lation. Without a time machine, we cannot be sure of investment portfolios. -
Experiments in Digital Evolution Christoph Adami∗ Claus O
Experiments in Digital Evolution Christoph Adami∗ Claus O. Wilke (Editors’ Introduction to the Digital Life Laboratory 136-93 Special Issue) California Institute of Technology Pasadena, CA 91125 {adami,wilke}@caltech.edu Whether or not the field of artificial life has succeeded in doing what its name sug- gests, namely synthesizing life from non-living components, is a matter of contention. Clearly, this journal covers a broad range of topics related to the synthesis and sim- ulation of living systems, but only a few articles go so far as to unabashedly study wholly artificial forms of life. The field of digital evolution is an exception: Artificial life forms, in the form of self-replicating computer code inhabiting specially prepared areas of a standard computer, have been used to learn about fundamental aspects of the evolutionary process since Tom Ray introduced us to them [23]. In this issue, we present experiments using digital organisms of the Avida variety (that is, implemented with the Avida software described in this issue [20]), but there are a number of other implementations of digital evolution that have been used for experimental evolution (see, e.g., [31, 32, 22, 5]). Whether or not these digitals are truly alive is ultimately of no concern to us as researchers: We use them because we are interested in complicated and vexing questions of evolutionary biology, and digitals offer us the possibility to attack them. Digital evolution is currently undergoing a boom phase, and public perception of this discipline is steadily increasing [21]. This boom can be traced back in part to a maturation of the Avida software used in the majority of digital evolution experiments, in part to a perceived need for rigor in evolution experiments [7], and in part to the adoption of digitals as experimental organisms alongside bacteria and viruses by a growing number of microbiologists (see, e.g., [16]). -
Lecture on Positive and Negative Selection
POSITIVE AND NEGATIVE SELECTION (AND RELATED PROBLEMS) CLAUDIA BANK Evolutionary Dynamics @ IGC: ➤ How do populations adapt to challenging environments? E.g., how does drug resistance evolve? ➤ Which processes drive speciation & diversification? ➤ What is the role of interactions in evolution? Mutation Genetic drift Migration Selection What we do ➤ Study evolutionary processes using simple models ➤ Evaluate these models using empirical and simulated data ➤ Use modeling to inform experimental design a priori Evolutionary Dynamics @ IGC: ➤ How do populations adapt to challenging environments? E.g., how does drug resistance evolve? ➤ Which processes drive speciation & diversification? ➤ What is the role of interactions in evolution? Mutation Genetic drift Migration Selection What we do ➤ Study evolutionary processes using simple models ➤ Evaluate these models using empirical and simulated data ➤ Use modeling to inform experimental design a priori It may be said that natural selection is daily and hourly scutinising, throughout the world, every variation, even the slightest; rejecting that which is bad, preserving and adding up all that is good; silently and insensibly working , whenever and “ wherever opportunity offers, at the improvement of each organic being in relation to its organic and inorganic conditions of life. We see nothing of these slow changes in progress, until the hand of time has marked the long lapse of ages. - Darwin, 1859 It may be said that natural selection is daily and hourly scutinising, throughout the world, every variation, even the slightest; rejecting that which is bad, preserving and adding up all that is good; silently and insensibly working , whenever and “ wherever opportunity offers, at the improvement of each organic being in relation to its organic and inorganic conditions of life. -
Genome Size and the Extinction of Small Populations
bioRxiv preprint doi: https://doi.org/10.1101/173690; this version posted August 8, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Genome size and the extinction of small populations Thomas LaBar1;2;3, Christoph Adami1;2;3;4 1 Department of Microbiology & Molecular Genetics 2 BEACON Center for the Study of Evolution in Action 3 Program in Ecology, Evolutionary Biology, and Behavior 4 Department of Physics and Astronomy Michigan State University, East Lansing, MI 48824 Abstract Species extinction is ubiquitous throughout the history of life. Understanding the factors that cause some species to go extinct while others survive will help us manage Earth's present-day biodiversity. Most studies of extinction focus on inferring causal factors from past extinction events, but these studies are constrained by our inability to observe extinction events as they occur. Here, we use digital experimental evolution to avoid these constraints and study \extinction in action". Previous digital evolution experiments have shown that strong genetic drift in small populations led to larger genomes, greater phenotypic complexity, and high extinction rates. Here we show that this elevated extinction rate is a consequence of genome expansions and a con- current increase in the genomic mutation rate. High genomic mutation rates increase the lethal mutation rate, leading to an increase the likelihood of a mutational melt- down. Genome expansions contribute to this lethal mutational load because genome expansions increase the likelihood of lethal mutations.