Information Theory, Developmental Psychology, and the Baldwin Effect
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Gene Regulatory Networks
Gene Regulatory Networks 02-710 Computaonal Genomics Seyoung Kim Transcrip6on Factor Binding Transcrip6on Control • Gene transcrip.on is influenced by – Transcrip.on factor binding affinity for the regulatory regions of target genes – Transcrip.on factor concentraon – Nucleosome posi.oning and chroman states – Enhancer ac.vity Gene Transcrip6onal Regulatory Network • The expression of a gene is controlled by cis and trans regulatory elements – Cis regulatory elements: DNA sequences in the regulatory region of the gene (e.g., TF binding sites) – Trans regulatory elements: RNAs and proteins that interact with the cis regulatory elements Gene Transcrip6onal Regulatory Network • Consider the following regulatory relaonships: Target gene1 Target TF gene2 Target gene3 Cis/Trans Regulatory Elements Binding site: cis Target TF regulatory element TF binding affinity gene1 can influence the TF target gene Target gene2 expression Target TF gene3 TF: trans regulatory element TF concentra6on TF can influence the target gene TF expression Gene Transcrip6onal Regulatory Network • Cis and trans regulatory elements form a complex transcrip.onal regulatory network – Each trans regulatory element (proteins/RNAs) can regulate mul.ple target genes – Cis regulatory modules (CRMs) • Mul.ple different regulators need to be recruited to ini.ate the transcrip.on of a gene • The DNA binding sites of those regulators are clustered in the regulatory region of a gene and form a CRM How Can We Learn Transcriponal Networks? • Leverage allele specific expressions – In diploid organisms, the transcript levels from the two copies of the genes may be different – RNA-seq can capture allele- specific transcript levels How Can We Learn Transcriponal Networks? • Leverage allele specific gene expressions – Teasing out cis/trans regulatory divergence between two species (WiZkopp et al. -
What Can We Learn from Fitness Landscapes?
What can we learn from fitness landscapes? The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Hartl, Daniel L. 2014. “What Can We Learn from Fitness Landscapes?” Current Opinion in Microbiology 21 (October): 51–57. doi:10.1016/j.mib.2014.08.001. Published Version 10.1016/j.mib.2014.08.001 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:22898356 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#OAP Elsevier Editorial System(tm) for Current Opinion in Microbiology Manuscript Draft Manuscript Number: Title: What Can We Learn From Fitness Landscapes? Article Type: 22 Growth&Develop: prokaryotes (2014 Corresponding Author: Dr. Daniel Hartl, Corresponding Author's Institution: First Author: Daniel Hartl Order of Authors: Daniel Hartl Manuscript Click here to view linked References What Can We Learn From Fitness Landscapes? Daniel L. Hartl Department of Organismic and Evolutionary Biology Harvard University Cambridge, Massachusetts 02138 USA Contact information: Email: [email protected], TEL: 617-396-3917 In evolutionary biology, the fitness landscape of set of mutants is the mapping of genotypes onto phenotypes when the phenotype is fitness or some proxy for fitness such as growth rate or drug resistance. When the set of mutants is not too large, it is possible to create every possible combination of mutants and map these to fitness. -
1. Basis of Fitness Landscape
Optimisation Origin and definition of fitness landscape Position and goal 1. Basis of fitness landscape Fitness landscape analysis for understanding and designing local search heuristics Sebastien´ Verel LISIC - Universit´edu Littoral C^oted'Opale, Calais, France http://www-lisic.univ-littoral.fr/~verel/ The 51st CREST Open Workshop Tutorial on Landscape Analysis University College London 27th, February, 2017 Optimisation Origin and definition of fitness landscape Position and goal Outline of this part Basis of fitness landscape : introductory example (Done) brief history and background of fitness landscape fundamental definitions Optimisation Origin and definition of fitness landscape Position and goal Mono-objective Optimization Search space : set of candidate solutions X Objective fonction : quality criterion (or non-quality) f : X ! IR X discrete : combinatorial optimization X ⊂ IRn : numerical optimization Solve an optimization problem (maximization) ? X = argmaxX f or find an approximation of X ?. Optimisation Origin and definition of fitness landscape Position and goal Context : black-box optimization x −! −! f (x) No information on the objective definition function f Objective fonction : can be irregular, non continuous, non differentiable, etc. given by a computation or a simulation Optimisation Origin and definition of fitness landscape Position and goal Real-world black-box optimization : first example PhD of Mathieu Muniglia, Saclay Nuclear Research Centre (CEA), Paris x −! −! f (x) (73;:::; 8) −! −! ∆z P Multi-physic simulator Optimisation Origin and definition of fitness landscape Position and goal Search algorithms Principle Enumeration of the search space A lot of ways to enumerate the search space Using exact method : A?, Branch&Bound, etc. Using random sampling : Monte Carlo technics, approx. -
Culture and the Baldwin Effect
Culture and the Baldwin Effect Diego Federici1 Norwegian University of Science and Technology Department of computer and information science N-7491 Trondheim, Norway [email protected], http://www.idi.ntnu.no/~federici Abstract. It is believed that the second phase of the Baldwin effect is basically governed by the cost of learning. In this paper we argue that when learning takes place the fitness landscape undergoes a modification that might block the Baldwin effect even if the cost of learning is high. The argument is that learning strategies will bias the evolutionary pro- cess towards individuals that genetically acquire better compared to in- dividuals that genetically behave better. Once this process starts the probability of experiencing the Baldwin effect decreases dramatically, whatever the learning cost. A simulation with evolving learning indi- viduals capable of communication is set to show this effect. The set of acquired behaviors (culture) competes with the instinctive one (genes) giving rise to a co-evolutionary effect. 1 Introduction 1.1 The Baldwin effect In the context of the debate between Darwinism and Lamarckism, James Mark Baldwin (1896) proposed that phenotypic plasticity might be regarded as \a new factor in evolution" [1]. Phenotypic plasticity allowing adaptation, would smooth the fitness landscape increasing the efficiency of the evolutionary process [2, 3]. However, phenotypic plasticity has inherent costs associated with the training phase in terms of energy, time and eventual mistakes. For these reasons, in a second phase, evolution may find a way to achieve the same successful behaviors without plasticity. Thus the Baldwin effect has two phases. -
Spectrum of Mutations and Genotype ± Phenotype Analysis in Currarino Syndrome
European Journal of Human Genetics (2001) 9, 599 ± 605 ã 2001 Nature Publishing Group All rights reserved 1018-4813/01 $15.00 www.nature.com/ejhg ARTICLE Spectrum of mutations and genotype ± phenotype analysis in Currarino syndrome Joachim KoÈchling1, Mohsen Karbasiyan2 and Andre Reis*,2,3 1Department of Pediatric Oncology/Hematology, ChariteÂ, Humboldt University, Berlin, Germany; 2Institute of Human Genetics, ChariteÂ, Humboldt University, Berlin, Germany; 3Institute of Human Genetics, Friedrich- Alexander University Erlangen-NuÈrnberg, Erlangen, Germany The triad of a presacral tumour, sacral agenesis and anorectal malformation constitutes the Currarino syndrome which is caused by dorsal-ventral patterning defects during embryonic development. The syndrome occurs in the majority of patients as an autosomal dominant trait associated with mutations in the homeobox gene HLXB9 which encodes the nuclear protein HB9. However, genotype ± phenotype analyses have been performed only in a few families and there are no reports about the specific impact of HLXB9 mutations on HB9 function. We performed a mutational analysis in 72 individuals from nine families with Currarino syndrome. We identified a total of five HLXB9 mutations, four novel and one known mutation, in four out of four families and one out of five sporadic cases. Highly variable phenotypes and a low penetrance with half of all carriers being clinically asymptomatic were found in three families, whereas affected members of one family showed almost identical phenotypes. However, an obvious genotype ± phenotype correlation was not found. While HLXB9 mutations were diagnosed in 23 patients, no mutation or microdeletion was detected in four sporadic patients with Currarino syndrome. The distribution pattern of here and previously reported HLXB9 mutations indicates mutational predilection sites within exon 1 and the homeobox. -
Predictability of a Large Intragenic Fitness Landscape
On the (un)predictability of a large intragenic fitness landscape Claudia Banka,b,c,1, Sebastian Matuszewskib,c,1, Ryan T. Hietpasd,e, and Jeffrey D. Jensenb,c,2,3 aInstituto Gulbenkian de Ciencia,ˆ 2780-156 Oeiras, Portugal; bSchool of Life Sciences, Ecole Polytechnique Fed´ erale´ de Lausanne, 1015 Lausanne, Switzerland; cSwiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; dEli Lilly and Company, Indianapolis, IN 46225; and eDepartment of Biochemistry & Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605 Edited by Andrew G. Clark, Cornell University, Ithaca, NY, and approved October 11, 2016 (received for review August 2, 2016) The study of fitness landscapes, which aims at mapping geno- of previously observed beneficial mutations or on the dissection types to fitness, is receiving ever-increasing attention. Novel exper- of an observed adaptive walk (i.e., a combination of muta- imental approaches combined with next-generation sequencing tions that have been observed to be beneficial in concert). (NGS) methods enable accurate and extensive studies of the fitness Secondly, theoretical research has proposed different land- effects of mutations, allowing us to test theoretical predictions scape architectures [such as the House-of-Cards (HoC), the and improve our understanding of the shape of the true under- Kauffman NK (NK), and the Rough Mount Fuji (RMF) model], lying fitness landscape and its implications for the predictability studied their respective properties, and developed a number and repeatability of evolution. Here, we present a uniquely large of statistics that characterize the landscape and quantify the multiallelic fitness landscape comprising 640 engineered mutants expected degree of epistasis (i.e., interaction effects between that represent all possible combinations of 13 amino acid-changing mutations) (10–14). -
Solutions for Practice Problems for Molecular Biology, Session 5
Solutions to Practice Problems for Molecular Biology, Session 5: Gene Regulation and the Lac Operon Question 1 a) How does lactose (allolactose) promote transcription of LacZ? 1) Lactose binds to the polymerase and increases efficiency. 2) Lactose binds to a repressor protein, and alters its conformation to prevent it from binding to the DNA and interfering with the binding of RNA polymerase. 3) Lactose binds to an activator protein, which can then help the RNA polymerase bind to the promoter and begin transcription. 4) Lactose prevents premature termination of transcription by directly binding to and bending the DNA. Solution: 2) Lactose binds to a repressor protein, and alters its conformation to prevent it from binding to the DNA and interfering with the binding of RNA polymerase. b) What molecule is used to signal low glucose levels to the Lac operon regulatory system? 1) Cyclic AMP 2) Calcium 3) Lactose 4) Pyruvate Solution: 1) Cyclic AMP. Question 2 You design a summer class where you recreate experiments studying the lac operon in E. coli (see schematic below). In your experiments, the activity of the enzyme b-galactosidase (β -gal) is measured by including X-gal and IPTG in the growth media. X-gal is a lactose analog that turns blue when metabolisize by b-gal, but it does not induce the lac operon. IPTG is an inducer of the lac operon but is not metabolized by b-gal. I O lacZ Plac Binding site for CAP Pi Gene encoding β-gal Promoter for activator protein Repressor (I) a) Which of the following would you expect to bind to β-galactosidase? Circle all that apply. -
Evolutionary Developmental Biology 573
EVOC20 29/08/2003 11:15 AM Page 572 Evolutionary 20 Developmental Biology volutionary developmental biology, now often known Eas “evo-devo,” is the study of the relation between evolution and development. The relation between evolution and development has been the subject of research for many years, and the chapter begins by looking at some classic ideas. However, the subject has been transformed in recent years as the genes that control development have begun to be identified. This chapter looks at how changes in these developmental genes, such as changes in their spatial or temporal expression in the embryo, are associated with changes in adult morphology. The origin of a set of genes controlling development may have opened up new and more flexible ways in which evolution could occur: life may have become more “evolvable.” EVOC20 29/08/2003 11:15 AM Page 573 CHAPTER 20 / Evolutionary Developmental Biology 573 20.1 Changes in development, and the genes controlling development, underlie morphological evolution Morphological structures, such as heads, legs, and tails, are produced in each individual organism by development. The organism begins life as a single cell. The organism grows by cell division, and the various cell types (bone cells, skin cells, and so on) are produced by differentiation within dividing cell lines. When one species evolves into Morphological evolution is driven another, with a changed morphological form, the developmental process must have by developmental evolution changed too. If the descendant species has longer legs, it is because the developmental process that produces legs has been accelerated, or extended over time. -
Evolution—The Extended Synthesis
EVOLUTION—THE EXTENDED SYNTHESIS edited by Massimo Pigliucci and Gerd B. Müller The MIT Press Cambridge, Massachusetts London, England © 2010 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. MIT Press books may be purchased at special quantity discounts for business or sales promotional use. For information, please email [email protected] or write to Special Sales Department, The MIT Press, 55 Hayward Street, Cambridge, MA 02142. This book was set in Times Roman by Toppan Best-set Premedia Limited. Printed and bound in the United States of America. Library of Congress Cataloging-in-Publication Data Evolution—the extended synthesis / edited by Massimo Pigliucci and Gerd B. Müller. p. cm. Includes bibliographical references and index. ISBN 978-0-262-51367-8 (pbk. : alk. paper) 1. Evolution (Biology) 2. Evolutionary genetics. 3. Developmental biology. I. Pigliucci, Massimo, 1964– II. Müller, Gerd B. QH366.2.E8627 2010 576.8—dc22 2009024587 10 9 8 7 6 5 4 3 2 1 Index Abir-Am, Pnina, 445 Average effects, 87 Abstract gene model, 102 Avital, E., 165 Accommodation, 298, 324, 366. See also Phenotypic and genetic Badyaev, A. V., 365 accommodation Baldwin effect, 219, 257–258, 366, 367, Activator-inhibitor systems, 290 371 Adams, Paul, 220 Baldwin, James Marc, 219, 366, 367, 371 Adaptation, 163–164, 425–427 Bat wings, 268 Adaptation and Natural Selection Beaks, fi nch, 271 (Williams), 84, 88 Behavioral inheritance, 187 Adaptive cell behaviors, 268 Benkemoun, L., 153–154 Adaptive landscapes/adaptive Biodiversity, areas for future research on topographies. -
Myths and Legends of the Baldwin Effect
Myths and Legends of the Baldwin Effect Peter Turney Institute for Information Technology National Research Council Canada Ottawa, Ontario, Canada, K1A 0R6 [email protected] Abstract ary computation when there is an evolving population of learning individuals (Ackley and Littman, 1991; Belew, This position paper argues that the Baldwin effect 1989; Belew et al., 1991; French and Messinger, 1994; is widely misunderstood by the evolutionary Hart, 1994; Hart and Belew, 1996; Hightower et al., 1996; computation community. The misunderstandings Whitley and Gruau, 1993; Whitley et al., 1994). This syn- appear to fall into two general categories. Firstly, ergetic effect is usually called the Baldwin effect. This has it is commonly believed that the Baldwin effect is produced the misleading impression that there is nothing concerned with the synergy that results when more to the Baldwin effect than synergy. A myth or legend there is an evolving population of learning indi- has arisen that the Baldwin effect is simply a special viduals. This is only half of the story. The full instance of synergy. One of the goals of this paper is to story is more complicated and more interesting. dispel this myth. The Baldwin effect is concerned with the costs Roughly speaking (we will be more precise later), the and benefits of lifetime learning by individuals in Baldwin effect has two aspects. First, lifetime learning in an evolving population. Several researchers have individuals can, in some situations, accelerate evolution. focussed exclusively on the benefits, but there is Second, learning is expensive. Therefore, in relatively sta- much to be gained from attention to the costs. -
Principles of Differentiation and Morphogenesis
Swarthmore College Works Biology Faculty Works Biology 2016 Principles Of Differentiation And Morphogenesis Scott F. Gilbert Swarthmore College, [email protected] R. Rice Follow this and additional works at: https://works.swarthmore.edu/fac-biology Part of the Biology Commons Let us know how access to these works benefits ouy Recommended Citation Scott F. Gilbert and R. Rice. (2016). 3rd. "Principles Of Differentiation And Morphogenesis". Epstein's Inborn Errors Of Development: The Molecular Basis Of Clinical Disorders On Morphogenesis. 9-21. https://works.swarthmore.edu/fac-biology/436 This work is brought to you for free by Swarthmore College Libraries' Works. It has been accepted for inclusion in Biology Faculty Works by an authorized administrator of Works. For more information, please contact [email protected]. 2 Principles of Differentiation and Morphogenesis SCOTT F. GILBERT AND RITVA RICE evelopmental biology is the science connecting genetics with transcription factors, such as TFHA and TFIIH, help stabilize the poly anatomy, making sense out of both. The body builds itself from merase once it is there (Kostrewa et al. 2009). Dthe instructions of the inherited DNA and the cytoplasmic system that Where and when a gene is expressed depends on another regula interprets the DNA into genes and creates intracellular and cellular tory unit of the gene, the enhancer. An enhancer is a DNA sequence networks to generate the observable phenotype. Even ecological fac that can activate or repress the utilization of a promoter, controlling tors such as diet and stress may modify the DNA such that different the efficiency and rate of transcription from that particular promoter. -
Lamarck's Ladder
Lamarck’s Ladder Overview Darwinism is a theory of biological evolution developed by the English naturalist Charles Darwin (1809–1882) and others. It states that all species of organisms arise and develop through the natural selection of small, inherited variations that increase the individual's ability to compete, survive, and reproduce. The environment plays a critical role in the natural selection process of Darwinian evolution through the phenotypic variation produced over time by small genetic changes to the DNA sequence, such as beneficial random mutations. However, the vast majority of environmental factors cannot directly alter DNA sequence. Jean-Baptiste Pierre Antoine de Monet, chevalier de Lamarck (1744 – 1829), often known simply as Lamarck, was a French naturalist. Before Darwin, Lamarck was one of the first scientists to support the Theory of Evolution. His theory was that species evolved based on the behavior of their parents. His hypothesis stated that an organism can pass on phenotypes acquired because of environmental pressures within their lifetime and pass them to its offspring. One of his most famous examples is his explanation of a giraffe’s long neck. He proposed that the continuous stretching of the neck by the giraffe to reach higher and higher leaves caused the muscles in the neck to strengthen and gradually lengthen over a period of time, which gave rise to longer necks in giraffes. Lamarck’s hypothesis was rejected and later became associated with flawed science concepts. However, scientists today debate whether advances in the field of transgenerational epigenetics indicate that Lamarck was correct, at least to some extent.