The Evolution of Phenotypic Plasticity Antonine Nicoglou
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How Morphological Development Can Guide Evolution Sam Kriegman1,*, Nick Cheney1, and Josh Bongard1
How morphological development can guide evolution Sam Kriegman1,*, Nick Cheney1, and Josh Bongard1 1University of Vermont, Department of Computer Science, Burlington, VT, USA *[email protected] ABSTRACT Organisms result from adaptive processes interacting across different time scales. One such interaction is that between development and evolution. Models have shown that development sweeps over several traits in a single agent, sometimes exposing promising static traits. Subsequent evolution can then canalize these rare traits. Thus, development can, under the right conditions, increase evolvability. Here, we report on a previously unknown phenomenon when embodied agents are allowed to develop and evolve: Evolution discovers body plans robust to control changes, these body plans become genetically assimilated, yet controllers for these agents are not assimilated. This allows evolution to continue climbing fitness gradients by tinkering with the developmental programs for controllers within these permissive body plans. This exposes a previously unknown detail about the Baldwin effect: instead of all useful traits becoming genetically assimilated, only traits that render the agent robust to changes in other traits become assimilated. We refer to this as differential canalization. This finding also has implications for the evolutionary design of artificial and embodied agents such as robots: robots robust to internal changes in their controllers may also be robust to external changes in their environment, such as transferal from simulation to reality or deployment in novel environments. Introduction The shape of life changes on many different time scales. From generation to generation, populations gradually increase in complexity and relative competency. At the individual level, organisms grow from a single-celled egg and exhibit extreme postnatal change as they interact with the outside world during their lifetimes. -
Transformations of Lamarckism Vienna Series in Theoretical Biology Gerd B
Transformations of Lamarckism Vienna Series in Theoretical Biology Gerd B. M ü ller, G ü nter P. Wagner, and Werner Callebaut, editors The Evolution of Cognition , edited by Cecilia Heyes and Ludwig Huber, 2000 Origination of Organismal Form: Beyond the Gene in Development and Evolutionary Biology , edited by Gerd B. M ü ller and Stuart A. Newman, 2003 Environment, Development, and Evolution: Toward a Synthesis , edited by Brian K. Hall, Roy D. Pearson, and Gerd B. M ü ller, 2004 Evolution of Communication Systems: A Comparative Approach , edited by D. Kimbrough Oller and Ulrike Griebel, 2004 Modularity: Understanding the Development and Evolution of Natural Complex Systems , edited by Werner Callebaut and Diego Rasskin-Gutman, 2005 Compositional Evolution: The Impact of Sex, Symbiosis, and Modularity on the Gradualist Framework of Evolution , by Richard A. Watson, 2006 Biological Emergences: Evolution by Natural Experiment , by Robert G. B. Reid, 2007 Modeling Biology: Structure, Behaviors, Evolution , edited by Manfred D. Laubichler and Gerd B. M ü ller, 2007 Evolution of Communicative Flexibility: Complexity, Creativity, and Adaptability in Human and Animal Communication , edited by Kimbrough D. Oller and Ulrike Griebel, 2008 Functions in Biological and Artifi cial Worlds: Comparative Philosophical Perspectives , edited by Ulrich Krohs and Peter Kroes, 2009 Cognitive Biology: Evolutionary and Developmental Perspectives on Mind, Brain, and Behavior , edited by Luca Tommasi, Mary A. Peterson, and Lynn Nadel, 2009 Innovation in Cultural Systems: Contributions from Evolutionary Anthropology , edited by Michael J. O ’ Brien and Stephen J. Shennan, 2010 The Major Transitions in Evolution Revisited , edited by Brett Calcott and Kim Sterelny, 2011 Transformations of Lamarckism: From Subtle Fluids to Molecular Biology , edited by Snait B. -
Communiqué SOCIÉTÉ CANADIENNE D’HISTOIRE ET DE PHILOSOPHIE DES SCIENCES
Communiqué SOCIÉTÉ CANADIENNE D’HISTOIRE ET DE PHILOSOPHIE DES SCIENCES CANADIAN SOCIETY FOR THE HISTORY AND PHILOSOPHY OF SCIENCE No 80 Autumn/Automne 2011 The Organism Issue The saga of Simmons draba: how one plant Cancer cells: All dressed up and nowhere to go specimen crossed the Atlantic and back again by Tricia Close-Koenig in search of a name Cancer cells are organisms that divide and grow uncon- by Paul C. Sokoloff and Lynn J. Gillespie trollably, forming malignant tumours and infiltrate the Simmons draba (or as a botanist might write: Draba body. Like other cells, they are invisible to the naked eye simmonsii Elven & Al-Shebaz) is a diminutive member and are translucent through the microscope. They were of the Mustard family – the Brassicaceae –native to the identified in the mid nineteenth century. However, until Canadian Arctic. Distinguished by yellow cross-shaped the early twentieth century, diagnosis and treatment of flowers and a small, slender stature, it has proliferated cancer was largely under the jurisdiction of surgeons, the steadfastly on the tundra since it speciated (split from principal therapeutic being the extirpation of growths its closest relative), botanists have only recognized it as and tumours. Other practitioners and medical institu- a distinct species since 2008. tions were interested neither in cancer, which was incur- able, nor in cancer cells. Albeit, cancer was identified as The type specimen of Simmons draba (that single sam- continued on page 18 ple which best represents a species) was collected by its namesake, Herman Georg Simmons, during the second expedition of the “Fram” - a Norwegian research ves- sel. -
Gene Expression and Phenotypic Traits Yuan-Chuan Chen
Chapter Introductory Chapter: Gene Expression and Phenotypic Traits Yuan-Chuan Chen 1. Gene expression Gene expression is a process by which the genetic information is used in the syn- thesis of functional products including proteins and functional RNAs (e.g., tRNA, small nuclear RNA, microRNA, small/short interfering RNA, etc.). The process of gene expression is applied by all organisms including eukaryotes, prokaryotes, and viruses to produce the macromolecular machinery for life. Through controlling the cell structure and function, the gene plays an important role in cellular dif- ferentiation, morphogenesis, adaptability, and diversity. Because the control of the timing, location, and levels of gene expression can have a significant effect on gene functions in a single cell or a multicellular organism, gene regulation may also drive evolutionary change. Several steps in the gene expression process can be regulated, such as transcription, posttranscriptional modification (e.g., RNA splicing, 3′ poly A adding, 5′-capping), translation, and posttranslational modification (e.g., protein splicing, folding, and processing). 1.1 Transcription The genomic DNA is composed of two antiparallel strands with 5′ and 3′ ends which are reverse and complementary for each. Regarding to a gene, the two DNA strands are classified as the “coding strand (sense strand),” which includes the DNA version of the RNA transcript sequence, and the “template strand (antisense strand, noncoding strand)” which serves as a blueprint for synthesizing an RNA strand. During transcription, the DNA template strand is read by an RNA polymerase to produce a complementary and antiparallel RNA primary transcript. Transcription is the first step of gene expression which involves copying a DNA sequence to make an RNA molecule including messenger RNA (mRNA), ribosome RNA (rRNA), and transfer RNA (tRNA) by the principle of complementary base pairing. -
Mapping of the Waxy Bloom Gene in 'Black Jewel'
agronomy Article Mapping of the Waxy Bloom Gene in ‘Black Jewel’ in a Parental Linkage Map of ‘Black Jewel’ × ‘Glen Ample’ (Rubus) Interspecific Population Dora Pinczinger 1, Marcel von Reth 1, Jens Keilwagen 2 , Thomas Berner 2, Andreas Peil 1, Henryk Flachowsky 1 and Ofere Francis Emeriewen 1,* 1 Julius Kühn-Institut (JKI)—Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Fruit Crops, Pillnitzer Platz 3a, 01326 Dresden, Germany; [email protected] (D.P.); [email protected] (M.v.R.); [email protected] (A.P.); henryk.fl[email protected] (H.F.) 2 Julius Kühn-Institut (JKI)—Federal Research Centre for Cultivated Plants, Institute for Biosafety in Plant Biotechnology, Erwin-Baur-Str. 27, 06484 Quedlinburg, Germany; [email protected] (J.K.); [email protected] (T.B.) * Correspondence: [email protected] Received: 16 September 2020; Accepted: 12 October 2020; Published: 16 October 2020 Abstract: Black and red raspberries (Rubus occidentalis L. and Rubus idaeus L.) are the prominent members of the genus Rubus (Rosaceae family). Breeding programs coupled with the low costs of high-throughput sequencing have led to a reservoir of data that have improved our understanding of various characteristics of Rubus and facilitated the mapping of different traits. Gene B controls the waxy bloom, a clearly visible epicuticular wax on canes. The potential effects of this trait on resistance/susceptibility to cane diseases in conjunction with other morphological factors are not fully studied. Previous studies suggested that gene H, which controls cane pubescence, is closely associated with gene B. -
Heritability, Selection, and the Response to Selection in the Presence of Phenotypic Measurement Error: Effects, Cures, and the Role of Repeated Measurements
bioRxiv preprint doi: https://doi.org/10.1101/247189; this version posted January 12, 2018. 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. Heritability, selection, and the response to selection in the presence of phenotypic measurement error: effects, cures, and the role of repeated measurements Erica Ponzi1;2, Lukas F. Keller1;3, Timoth´ee Bonnet1;4, Stefanie Muff1;2;? Running title: Phenotypic measurement error { effects and cures 1 Institute of Evolutionary Biology and Environmental Studies, University of Zurich,¨ Winterthurerstrasse 190, 8057 Zurich,¨ Switzerland 2 Department of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich,¨ Hirschengraben 84, 8001 Zurich,¨ Switzerland 3 Zoological Museum, University of Zurich,¨ Karl-Schmid-Strasse 4, 8006 Zurich,¨ Switzerland 4 Division of Ecology and Evolution, Research School of Biology,The Australian Na- tional University, Acton, Canberra, ACT 2601,Australia ? Corresponding author. E-mail: stefanie.muff@uzh.ch 1 bioRxiv preprint doi: https://doi.org/10.1101/247189; this version posted January 12, 2018. 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. Quantitative genetic analyses require extensive measurements of phe- notypic traits, which may be especially challenging to obtain in wild populations. On top of operational measurement challenges, some traits undergo transient fluctuations that might be irrelevant for selection pro- cesses. -
Extinction Dynamics of Age-Structured Populations in A
Proc. Nadl. Acad. Sci. USA Vol. 85, pp. 7418-7421, October 1988 Population Biology Extinction dynamics of age-structured populations in a fluctuating environment (demography/ecology/life history/stochastic model/diffusion process) RUSSELL LANDE AND STEVEN HECHT ORZACK Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637 Communicated by David M. Raup, June 3, 1988 (received for review February 2, 1988) ABSTRACT We model density-independent growth of an a recursion formula for the numbers of individuals in each age- (or stage-) structured population, assuming that mortality age class or developmental stage at time t + 1 in terms of and reproductive rates fluctuate as stationary time series. An- those at the previous time t, alytical formulas are derived for the distribution of time to extinction and the cumulative probability of extinction before n(t + 1) = A(t)n(t), [1] a certain time, which are determined by the initial age distri- bution, and by the infinitesimal mean and variance, # and a2, where n(t) is a column vector with entries representing the of a diffusion approximation for the logarithm of total popula- numbers of (female) individuals of each type at time t and tion size. These parameters can be estimated from the average A(t) is a square projection matrix with nonnegative entries life history and the pattern of environmental fluctuations in Aij(t) that determine the number of individuals of type i pro- the vital rates. We also show that the distribution of time to duced at time t + 1 per individual of type j at time t. -
Maintenance of Quantitative Genetic Variance Under Partial Self-Fertilization, with Implications for Evolution of Selfing
GENETICS | INVESTIGATION Maintenance of Quantitative Genetic Variance Under Partial Self-Fertilization, with Implications for Evolution of Selfing Russell Lande*,1 and Emmanuelle Porcher† *Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, Berkshire SL5 7PY, United Kingdom, and †Centre d’Ecologie et des Sciences de la Conservation (UMR7204), Sorbonne Universités, MNHN, Centre National de la Recherche Scientifique, UPMC, 75005 Paris, France ABSTRACT We analyze two models of the maintenance of quantitative genetic variance in a mixed-mating system of self-fertilization and outcrossing. In both models purely additive genetic variance is maintainedbymutationandrecombinationunder stabilizing selection on the phenotype of one or more quantitative characters. The Gaussian allele model (GAM) involves a finite number of unlinked loci in an infinitely large population, with a normal distribution of allelic effects at each locus within lineages selfed for t consecutive generations since their last outcross. The infinitesimal model for partial selfing (IMS) involves an infinite number of loci in a large but finite population, with a normal distribution of breeding values in lineages of selfing age t. In both models a stable equilibrium genetic variance exists, the outcrossed equilibrium, nearly equal to that under random mating, for all selfing rates, r, up to critical value,^r;the purging threshold, which approximately equals the mean fitness under random mating relative to that under complete selfing. In the GAM a second stable equilibrium, the purged equilibrium, exists for any positive selfing rate, with genetic variance less than or equal to that under pure selfing; as r increases above ^r the outcrossed equilibrium collapses sharply to the purged equilibrium genetic variance. -
A Complete Bibliography of Publications in the Journal of Theoretical Biology: 1990–1999
A Complete Bibliography of Publications in the Journal of Theoretical Biology: 1990{1999 Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA Tel: +1 801 581 5254 FAX: +1 801 581 4148 E-mail: [email protected], [email protected], [email protected] (Internet) WWW URL: http://www.math.utah.edu/~beebe/ 01 June 2019 Version 1.00 Title word cross-reference 2 [SOR91]. 3 [LBND98, Mar92b, SL91a, Van91]. 4 [Lac90]. 6 [RP99]. > [Hir93]. + [BS92, Cla95, Joh93, NK90]. 2+ [AH90, Cha90, CJMBM92, HP97a, ◦ KD94, Kum91, LF95, LC97, LH91, LR94c, SW91]. [Fli99]. 0 [O'N91]. 1 [O'N91]. 2 [CLY99]. 3 [KD94, LR94c, WBC99]. cmax [WBC99]. i [LR94c]. ml + [WBC99]. α [LBDDG90, MGL 95, Nak95, SST91, TSC90]. b1 [Yar96]. β [Iid90, Rad91, TSC90]. · [SST91, Spe90]. ∆ [Fri98]. [Boe90]. g [MNB97]. Km [RP96]. L = C [Hes90]. µ [RSB92]. N [Dug90, Bla97]. p [DGSK99, Khr98]. Φ [N¨ol98, N¨ol99]. ΦF (0) [PN98]. ! [MR98, O'N91]. -1 [LBND98]. -Adic [DGSK99, Khr98]. -amylase-catalyzed [Nak95]. -ATPase [BS92]. -azaadenine [SOR91]. -chymotrypsin [LBDDG90]. -D [Mar92b, SL91a, Van91]. -dependent [MNB97, CJMBM92]. -globin [Boe90, Iid90]. -helix [TSC90]. -induced [KD94]. -morphogen [Lac90]. -person [Dug90]. -phosphogluconolactone [RP99]. -player [Bla97]. -sarcin [MGL+95]. -sarcin-membrane [MGL+95]. -structure [TSC90]. 1 2 -structures [Rad91]. -thalassemia [Iid90]. -values [N¨ol98, N¨ol99]. [Boe90]. /K [BS92]. 1 [Fin92b, Ham93, Mel93a, TCZ95, TL98, WDP98]. 1-dimenthylurea [LBND98]. 100 [CF94b]. 100-A˚ [CF94b]. 16S [AIK99]. 185 [BBM+13a, BBM+13b]. 19th [Ano99c]. 2 [MK93, SST91]. 2- [RSB92]. 2nd [Ano99a]. 353-379 [Ano92-29]. -
Modular Organization of Cis-Regulatory Control Information of Neurotransmitter Pathway Genes in Caenorhabditis Elegans
HIGHLIGHTED ARTICLE | INVESTIGATION Modular Organization of Cis-regulatory Control Information of Neurotransmitter Pathway Genes in Caenorhabditis elegans Esther Serrano-Saiz,*,†,1 Burcu Gulez,* Laura Pereira,*,‡ Marie Gendrel,*,§ Sze Yen Kerk,* Berta Vidal,* Weidong Feng,** Chen Wang,* Paschalis Kratsios,** James B. Rand,†† and Oliver Hobert*,1 *Department of Biological Sciences, Columbia University, Howard Hughes Medical Institute, New York, New York 10027, †Centro de Biologia Molecular Severo Ochoa/Consejo Superior de Investigaciones Científicas (CSIC), Madrid 28049, Spain, ‡New York Genome Center, New York 10013 §Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, Université Paris Sciences et Lettres Research University, Paris 75005, France, **Department of Neurobiology, University of Chicago, Illinois 60637, and ††Oklahoma Medical Research Foundation, Oklahoma 73104 ORCID IDs: 0000-0003-0077-878X (E.S.-S.); 0000-0002-0991-0479 (M.G.); 0000-0002-3363-139X (C.W.); 0000-0002-1363-9271 (P.K.); 0000-0002-7634-2854 (O.H.) ABSTRACT We explore here the cis-regulatory logic that dictates gene expression in specific cell types in the nervous system. We focus on a set of eight genes involved in the synthesis, transport, and breakdown of three neurotransmitter systems: acetylcholine (unc-17/ VAChT, cha-1/ChAT, cho-1/ChT, and ace-2/AChE), glutamate (eat-4/VGluT), and g-aminobutyric acid (unc-25/GAD, unc-46/LAMP, and unc-47/VGAT). These genes are specifically expressed in defined subsets of cells in the nervous system. Through transgenic reporter gene assays, we find that the cellular specificity of expression of all of these genes is controlled in a modular manner through distinct cis-regulatory elements, corroborating the previously inferred piecemeal nature of specification of neurotransmitter identity. -
Mining Bacterial Species Records for Phenotypic Trait Information
RESEARCH ARTICLE Ecological and Evolutionary Science crossm Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information Albert Barberán,a Hildamarie Caceres Velazquez,b Stuart Jones,b Noah Fiererc,d Department of Soil, Water, and Environmental Science, University of Arizona, Tucson, Arizona, USAa; Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USAb; Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, USAc; Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USAd ABSTRACT Cultivation in the laboratory is essential for understanding the pheno- typic characteristics and environmental preferences of bacteria. However, basic phe- Received 23 May 2017 Accepted 17 July notypic information is not readily accessible. Here, we compiled phenotypic and en- 2017 Published 2 August 2017 Ͼ Citation Barberán A, Caceres Velazquez H, vironmental tolerance information for 5,000 bacterial strains described in the Jones S, Fierer N. 2017. Hiding in plain sight: International Journal of Systematic and Evolutionary Microbiology (IJSEM) with all in- mining bacterial species records for formation made publicly available in an updatable database. Although the data span phenotypic trait information. mSphere 2: e00237-17. https://doi.org/10.1128/mSphere 23 different bacterial phyla, most entries described aerobic, mesophilic, neutrophilic .00237-17. strains from Proteobacteria (mainly Alpha- and Gammaproteobacteria), Actinobacteria, Editor Steven J. Hallam, University of British Firmicutes, and Bacteroidetes isolated from soils, marine habitats, and plants. Most of Columbia the routinely measured traits tended to show a significant phylogenetic signal, al- Copyright © 2017 Barberán et al. This is an though this signal was weak for environmental preferences. -
Phenotypic Plasticity and Plant Adaptation
Acta Bot. Neerl. 44(4), December 1995, p. 363-383 * Phenotypic plasticity and plant adaptation S.E. Sultan Department of Biology, Wesleyan University, Middletown, CT 06459-0170, USA SUMMARY This paper focuses on phenotypic plasticity as a major mode of adaptation in plants. A methodological critique examines difficulties in studying plasticity, including the conceptually critical distinction between functionally adaptive and inevitable aspects of response. It is that argued plasticity studies depend critically upon the genotypic the and factor sample, choice of environmental factors states, and the definitionof phenotypic traits. Examples are drawn from recent studies to showing adaptive response by genotypes physical aspects of the environment, as well as to biotic factors such as neighbour density and the presence of bacterial symbionts. Alterations of offspring traits by parental plants of Polygonum persicaria are discussed as a cross-generational aspect of plastic response to environment. Finally, individual plasticity and local ecotypes are alternative bases of examined as species ecological breadth, and these alternatives methodological problems in distinguishing are discussed. Key-words: adaptation, maternal effects, norm of reaction, phenotypic plasticity, Polygonum, species distribution. INTRODUCTION Natural environments inevitably vary, both spatially and temporally. According to the classic neo-Darwinian model, organisms accommodate that variation by means of natural selection, which through evolutionary time matches specific genotypes and environments. By assuming a simple Mendelian relationship of genotype to phenotype, this powerful model provides a genetic mechanism for adaptive phenotypic changes in In this I wish to focus second mode of populations. paper on a major adaptation, one which is becoming particularly well understood in plants: the capacity of a single genotype to produce different, functionally appropriate phenotypes in different This environments, or adaptive phenotypic plasticity.