The Pleiotropic Structure of the Genotype–Phenotype Map: the Evolvability of Complex Organisms
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A Comprehensive Study of Metabolite Genetics Reveals Strong Pleiotropy and Heterogeneity Across Time and Context
ARTICLE https://doi.org/10.1038/s41467-019-12703-7 OPEN A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context Apolline Gallois1,12, Joel Mefford2,12, Arthur Ko 3, Amaury Vaysse 1, Hanna Julienne1, Mika Ala-Korpela4,5,6,7,8,9, Markku Laakso 10, Noah Zaitlen2,12*, Päivi Pajukanta 3,12*& Hugues Aschard 1,11,12* 1234567890():,; Genetic studies of metabolites have identified thousands of variants, many of which are associated with downstream metabolic and obesogenic disorders. However, these studies have relied on univariate analyses, reducing power and limiting context-specific under- standing. Here we aim to provide an integrated perspective of the genetic basis of meta- bolites by leveraging the Finnish Metabolic Syndrome In Men (METSIM) cohort, a unique genetic resource which contains metabolic measurements, mostly lipids, across distinct time points as well as information on statin usage. We increase effective sample size by an average of two-fold by applying the Covariates for Multi-phenotype Studies (CMS) approach, identifying 588 significant SNP-metabolite associations, including 228 new associations. Our analysis pinpoints a small number of master metabolic regulator genes, balancing the relative proportion of dozens of metabolite levels. We further identify associations to changes in metabolic levels across time as well as genetic interactions with statin at both the master metabolic regulator and genome-wide level. 1 Department of Computational Biology - USR 3756 CNRS, Institut Pasteur, Paris, France. 2 Department of Medicine, University of California, San Francisco, CA, USA. 3 Department of Human Genetics, University of California, Los Angeles, CA, USA. -
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. -
Evolution by Natural Selection, Formulated Independently by Charles Darwin and Alfred Russel Wallace
UNIT 4 EVOLUTIONARY PATT EVOLUTIONARY E RNS AND PROC E SS E Evolution by Natural S 22 Selection Natural selection In this chapter you will learn that explains how Evolution is one of the most populations become important ideas in modern biology well suited to their environments over time. The shape and by reviewing by asking by applying coloration of leafy sea The rise of What is the evidence for evolution? Evolution in action: dragons (a fish closely evolutionary thought two case studies related to seahorses) 22.1 22.4 are heritable traits that with regard to help them to hide from predators. The pattern of evolution: The process of species have changed evolution by natural and are related 22.2 selection 22.3 keeping in mind Common myths about natural selection and adaptation 22.5 his chapter is about one of the great ideas in science: the theory of evolution by natural selection, formulated independently by Charles Darwin and Alfred Russel Wallace. The theory explains how T populations—individuals of the same species that live in the same area at the same time—have come to be adapted to environments ranging from arctic tundra to tropical wet forest. It revealed one of the five key attributes of life: Populations of organisms evolve. In other words, the heritable characteris- This chapter is part of the tics of populations change over time (Chapter 1). Big Picture. See how on Evolution by natural selection is one of the best supported and most important theories in the history pages 516–517. of scientific research. -
Evolving Neural Networks That Are Both Modular and Regular: Hyperneat Plus the Connection Cost Technique Joost Huizinga, Jean-Baptiste Mouret, Jeff Clune
Evolving Neural Networks That Are Both Modular and Regular: HyperNeat Plus the Connection Cost Technique Joost Huizinga, Jean-Baptiste Mouret, Jeff Clune To cite this version: Joost Huizinga, Jean-Baptiste Mouret, Jeff Clune. Evolving Neural Networks That Are Both Modular and Regular: HyperNeat Plus the Connection Cost Technique. GECCO ’14: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation, ACM, 2014, Vancouver, Canada. pp.697-704. hal-01300699 HAL Id: hal-01300699 https://hal.archives-ouvertes.fr/hal-01300699 Submitted on 11 Apr 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. To appear in: Proceedings of the Genetic and Evolutionary Computation Conference. 2014 Evolving Neural Networks That Are Both Modular and Regular: HyperNeat Plus the Connection Cost Technique Joost Huizinga Jean-Baptiste Mouret Jeff Clune Evolving AI Lab ISIR, Université Pierre et Evolving AI Lab Department of Computer Marie Curie-Paris 6 Department of Computer Science CNRS UMR 7222 Science University of Wyoming Paris, France University of Wyoming [email protected] [email protected] [email protected] ABSTRACT 1. INTRODUCTION One of humanity’s grand scientific challenges is to create ar- An open and ambitious question in the field of evolution- tificially intelligent robots that rival natural animals in intel- ary robotics is how to produce robots that possess the intel- ligence and agility. -
High Heritability of Telomere Length, but Low Evolvability, and No Significant
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423128; this version posted December 16, 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. 1 High heritability of telomere length, but low evolvability, and no significant 2 heritability of telomere shortening in wild jackdaws 3 4 Christina Bauch1*, Jelle J. Boonekamp1,2, Peter Korsten3, Ellis Mulder1, Simon Verhulst1 5 6 Affiliations: 7 1 Groningen Institute for Evolutionary Life Sciences, University of Groningen, Nijenborgh 7, 8 9747AG Groningen, The Netherlands 9 2 present address: Institute of Biodiversity Animal Health & Comparative Medicine, College 10 of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United 11 Kingdom 12 3 Department of Animal Behaviour, Bielefeld University, Morgenbreede 45, 33615 Bielefeld, 13 Germany 14 15 16 * Correspondence to: 17 [email protected] 18 19 Running head: High heritability of telomere length bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423128; this version posted December 16, 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. 20 Abstract 21 Telomere length (TL) and shortening rate predict survival in many organisms. Evolutionary 22 dynamics of TL in response to survival selection depend on the presence of genetic variation 23 that selection can act upon. However, the amount of standing genetic variation is poorly known 24 for both TL and TL shortening rate, and has not been studied for both traits in combination in 25 a wild vertebrate. -
12 Evolvability of Real Functions
i i i i Evolvability of Real Functions PAUL VALIANT , Brown University We formulate a notion of evolvability for functions with domain and range that are real-valued vectors, a compelling way of expressing many natural biological processes. We show that linear and fixed-degree polynomial functions are evolvable in the following dually-robust sense: There is a single evolution algorithm that, for all convex loss functions, converges for all distributions. It is possible that such dually-robust results can be achieved by simpler and more-natural evolution algorithms. Towards this end, we introduce a simple and natural algorithm that we call wide-scale random noise and prove a corresponding result for the L2 metric. We conjecture that the algorithm works for a more general class of metrics. 12 Categories and Subject Descriptors: F.1.1 [Computation by Abstract Devices]: Models of Computa- tion—Self-modifying machines; G.1.6 [Numerical Analysis]: Optimization—Convex programming; I.2.6 [Artificial Intelligence]: Learning—Concept learning;J.3[Computer Applications]: Life and Medical Sciences—Biology and genetics General Terms: Algorithms, Theory Additional Key Words and Phrases: Evolvability, optimization ACM Reference Format: Valiant, P. 2014. Evolvability of real functions. ACM Trans. Comput. Theory 6, 3, Article 12 (July 2014), 19 pages. DOI:http://dx.doi.org/10.1145/2633598 1. INTRODUCTION Since Darwin first assembled the empirical facts that pointed to evolution as the source of the hugely diverse and yet finely honed mechanisms of life, there has been the mys- tery of how the biochemical mechanisms of evolution (indeed, how any mechanism) can apparently consistently succeed at finding innovative solutions to the unexpected problems of life. -
Investigations Into Roles for Endocytosis in LIN-12/Notch
Investigations into roles for endocytosis in LIN-12/Notch signaling and its regulation Jessica Chan Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2020 © 2020 Jessica Chan All Rights Reserved Abstract The LIN-12/Notch signaling pathway is highly conserved in all animals, and is crucial for proper development. It is a key pathway in specifying cell fate in many cellular contexts, and dysregulation of the pathway can have deleterious consequences. Therefore, understanding how LIN-12/Notch signaling is regulated in different contexts has been a main area of interest in the field. Previous studies in different model organisms have identified many modes of regulation of the signaling pathway, one of which is endocytosis of the ligand and receptor. Here, I further investigated the role of endocytosis in LIN-12/Notch signaling in multiple developmental contexts in Caenorhabditis elegans. Work in Drosophila and vertebrates had previously established that ligand-mediated activation of Notch requires ubiquitination of the intracellular domain of the transmembrane ligand and the activity of the endocytic adaptor Epsin in the signaling cell. The consensus in the field is that Epsin-mediated endocytosis of mono-ubiquitinated ligand generates a pulling force that exposes a cleavage site in Notch for an ADAM protease, a critical step in signal transduction. In contrast, in this thesis, I examined two different transmembrane ligands in several different cell contexts and found that activation of LIN-12/Notch and the paralogous GLP-1/Notch in C. -
Nicotinic Receptor Alpha7 Expression During Tooth Morphogenesis Reveals Functional Pleiotropy
Nicotinic Receptor Alpha7 Expression during Tooth Morphogenesis Reveals Functional Pleiotropy Scott W. Rogers1,2*, Lorise C. Gahring1,3 1 Geriatric Research, Education and Clinical Center, Veteran’s Administration, Salt Lake City, Utah, United States of America, 2 Department of Neurobiology and Anatomy, University of Utah School of Medicine, Salt Lake City, Utah, United States of America, 3 Division of Geriatrics, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America Abstract The expression of nicotinic acetylcholine receptor (nAChR) subtype, alpha7, was investigated in the developing teeth of mice that were modified through homologous recombination to express a bi-cistronic IRES-driven tau-enhanced green fluorescent protein (GFP); alpha7GFP) or IRES-Cre (alpha7Cre). The expression of alpha7GFP was detected first in cells of the condensing mesenchyme at embryonic (E) day E13.5 where it intensifies through E14.5. This expression ends abruptly at E15.5, but was again observed in ameloblasts of incisors at E16.5 or molar ameloblasts by E17.5–E18.5. This expression remains detectable until molar enamel deposition is completed or throughout life as in the constantly erupting mouse incisors. The expression of alpha7GFP also identifies all stages of innervation of the tooth organ. Ablation of the alpha7-cell lineage using a conditional alpha7Cre6ROSA26-LoxP(diphtheria toxin A) strategy substantially reduced the mesenchyme and this corresponded with excessive epithelium overgrowth consistent with an instructive role by these cells during ectoderm patterning. However, alpha7knock-out (KO) mice exhibited normal tooth size and shape indicating that under normal conditions alpha7 expression is dispensable to this process. -
The University of Chicago Epistasis, Contingency, And
THE UNIVERSITY OF CHICAGO EPISTASIS, CONTINGENCY, AND EVOLVABILITY IN THE SEQUENCE SPACE OF ANCIENT PROTEINS A DISSERTATION SUBMITTED TO THE FACULTY OF THE DIVISION OF THE BIOLOGICAL SCIENCES AND THE PRITZKER SCHOOL OF MEDICINE IN CANDIDACY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY GRADUATE PROGRAM IN BIOCHEMISTRY AND MOLECULAR BIOPHYSICS BY TYLER NELSON STARR CHICAGO, ILLINOIS AUGUST 2018 Table of Contents List of Figures .................................................................................................................... iv List of Tables ..................................................................................................................... vi Acknowledgements ........................................................................................................... vii Abstract .............................................................................................................................. ix Chapter 1 Introduction ......................................................................................................1 1.1 Sequence space and protein evolution .............................................................1 1.2 Deep mutational scanning ................................................................................2 1.3 Epistasis ...........................................................................................................3 1.4 Chance and determinism ..................................................................................4 1.5 Evolvability ......................................................................................................6 -
An Introduction to Quantitative Genetics I Heather a Lawson Advanced Genetics Spring2018 Outline
An Introduction to Quantitative Genetics I Heather A Lawson Advanced Genetics Spring2018 Outline • What is Quantitative Genetics? • Genotypic Values and Genetic Effects • Heritability • Linkage Disequilibrium and Genome-Wide Association Quantitative Genetics • The theory of the statistical relationship between genotypic variation and phenotypic variation. 1. What is the cause of phenotypic variation in natural populations? 2. What is the genetic architecture and molecular basis of phenotypic variation in natural populations? • Genotype • The genetic constitution of an organism or cell; also refers to the specific set of alleles inherited at a locus • Phenotype • Any measureable characteristic of an individual, such as height, arm length, test score, hair color, disease status, migration of proteins or DNA in a gel, etc. Nature Versus Nurture • Is a phenotype the result of genes or the environment? • False dichotomy • If NATURE: my genes made me do it! • If NURTURE: my mother made me do it! • The features of an organisms are due to an interaction of the individual’s genotype and environment Genetic Architecture: “sum” of the genetic effects upon a phenotype, including additive,dominance and parent-of-origin effects of several genes, pleiotropy and epistasis Different genetic architectures Different effects on the phenotype Types of Traits • Monogenic traits (rare) • Discrete binary characters • Modified by genetic and environmental background • Polygenic traits (common) • Discrete (e.g. bristle number on flies) or continuous (human height) -
Synthetic Morphogenesis
Downloaded from http://cshperspectives.cshlp.org/ on September 24, 2021 - Published by Cold Spring Harbor Laboratory Press Synthetic Morphogenesis Brian P. Teague, Patrick Guye, and Ron Weiss Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 Correspondence: [email protected] Throughout biology, function is intimately linked with form. Across scales ranging from subcellular to multiorganismal, the identity and organization of a biological structure’s subunits dictate its properties. The field of molecular morphogenesis has traditionally been concerned with describing these links, decoding the molecular mechanisms that give rise to the shape and structure of cells, tissues, organs, and organisms. Recent advances in synthetic biology promise unprecedented control over these molecular mechanisms; this opens the path to not just probing morphogenesis but directing it. This review explores several frontiers in the nascent field of synthetic morphogenesis, including programmable tissues and organs, synthetic biomaterials and programmable matter, and engineering complex morphogenic systems de novo. We will discuss each frontier’s objectives, current approaches, constraints and challenges, and future potential. hat is the underlying basis of biological 2014). As the mechanistic underpinnings of Wstructure? Speculations were based on these processes are elucidated, opportunities macroscopic observation until the 17th century, arise to use this knowledge to direct mor- when Antonie van Leeuwenhoek and Robert phogenesis toward novel, useful ends. We call Hooke discovered that organisms were com- this emerging field of endeavor “synthetic mor- posed of microscopic cells (Harris 1999), and phogenesis.” Inspired by and based on natural that the size and shape of the cells affected the morphogenic systems, synthetic morphogenesis properties of the structures they formed. -
Reconciling Explanations for the Evolution of Evolvability
Reconciling Explanations for the Evolution of Evolvability Bryan Wilder and Kenneth O. Stanley To Appear In: Adaptive Behavior journal. London: SAGE, 2015. Abstract Evolution's ability to find innovative phenotypes is an important ingredient in the emergence of complexity in nature. A key factor in this capability is evolvability, or the propensity towards phenotypic variation. Numerous explanations for the origins of evolvability have been proposed, often differing in the role that they attribute to adaptive processes. To provide a new perspective on these explanations, experiments in this paper simulate evolution in gene regulatory networks, revealing that the type of evolvability in question significantly impacts the dynamics that follow. In particular, while adaptive processes result in evolvable individuals, processes that are either neutral or that explicitly encourage divergence result in evolvable populations. Furthermore, evolvability at the population level proves the most critical factor in the production of evolutionary innovations, suggesting that nonadaptive mechanisms are the most promising avenue for investigating and understanding evolvability. These results reconcile a large body of work across biology and inform attempts to reproduce evolvability in artificial settings. Keywords: Evolvability, evolutionary computation, gene regulatory networks Introduction Something about the structure of biological systems allows evolution to find new innovations. An important question is whether such evolvability (defined roughly as the propensity to introduce novel 1 phenotypic variation) is itself a product of selection. In essence, is evolvability evolvable (Pigliucci, 2008)? Much prior work has attempted to encourage evolvability in artificial systems in the hope of reproducing the open-ended dynamics of biological evolution (Reisinger & Miikkulainen, 2006; Grefenstette, 1999; Bedau et al., 2000; Channon, 2006; Spector, Klein, & Feinstein, 2007; Standish, 2003).