DOCSLIB.ORG

Causation in the Nature-Nurture Debate: the Case of Genotype-Environment Interaction

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Causation in the Nature-Nurture Debate: the Case of Genotype-Environment Interaction Causation in the Nature-Nurture Debate: The Case of Genotype-Environment Interaction by James Gregory Tabery Bachelor of Science, Fairfield University, 2000 Submitted to the Graduate Faculty of Arts and Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2007 UNIVERSITY OF PITTSBURGH COLLEGE OF ARTS AND SCIENCES This dissertation was presented by James Gregory Tabery It was defended on July 17, 2007 and approved by Robert C. Olby, Research Professor, Dept. of History and Philosophy of Science Michael Pogue-Geile, Associate Professor, Psychology Department Kenneth F. Schaffner, University Professor, Dept. of History and Philosophy of Science Dissertation Director: Sandra D. Mitchell, Professor, Dept. of History and Philosophy of Science Dissertation Director: Paul E. Griffiths, Professor, Philosophy, University of Queensland ii Copyright © by James Gregory Tabery 2007 iii Causation in the Nature-Nurture Debate: The Case of Genotype-Environment Interaction James Gregory Tabery University of Pittsburgh, 2007 I attempt to resolve an aspect of the nature-nurture debate. Consider a typical nature-nurture question: Why do some individuals develop a complex trait such as depression, while others do not? This question incorporates an etiological query about the causal mechanisms responsible for the individual development of depression; it also incorporates an etiological query about the causes of variation responsible for individual differences in the occurrence of depression. Scientists in the developmental research tradition of biology investigate the former; scientists in the biometric research tradition of biology investigate the latter. So what is the relationship? The developmental and biometric research traditions, I argue, are united in their joint effort to elucidate what I call difference mechanisms. Difference mechanisms are regular causal mechanisms made up of difference-making variables that take different values in the natural world. On this model, individual differences are the effect of difference-makers in development that take different values in the natural world. I apply this model to the case of genotype-environment interaction (or G×E), showing that there have actually been two separate concepts of G×E: a biometric concept (or G×EB) and a developmental concept (or G×ED). These concepts also may be integrated via the difference mechanisms model: G×E results from the interdependence of difference-makers in development that take different values in the natural world. iv TABLE OF CONTENTS ACKNOWLEDGMENTS………………………………………………………………………...x PREFACE………………………………………………………………………………………..xii 1. Introduction……………………………………………………………………………………..1 1.1. Genotype-Environment Interaction…………………………………………………..2 1.2. Genotype-Environment Interaction in the Nature-Nurture Debate…………………..7 1.3. G×EB vs. G×ED……………………………………………………………………….9 1.4. Difference Mechanisms and the Interdependence of Difference-Makers in Development that Take Different Values in the Natural World…………………….11 2. R. A. Fisher, Lancelot Hogben, and the Origin(s) of Genotype-Environment Interaction……14 2.1. Introduction………………………………………………………………………….14 2.2. R. A. Fisher and the “Nonlinear Interaction of Heredity and Environment”……….16 2.2.1. The Environment Expunged………………………………………………17 2.2.2. Rothamsted and the Environment Reconsidered—the Origin of G×EB…..21 2.3. Lancelot Hogben and the “Interdependence of Nature and Nurture”……………….28 2.3.1. Cleaning the Augean Stables……………………………………………...35 2.3.2. The William Withering Memorial Lectures………………………………39 2.3.3. From Development to Interaction—the Origin of G×ED………………….47 2.4. Fisher vs. Hogben: On the Importance of Genotype-Environment Interaction……..54 2.5. The Legacies of Fisher and Hogben: G×EB vs. G×ED………………………………61 2.6. Conclusion…………………………………………………………………………..64 3. Genotype-Environment Interaction in the IQ Controversy…………………………………...66 3.1. Introduction………………………………………………………………………….66 3.2. Genotype-Environment Interaction in the IQ Controversy…………………………71 3.2.1. The Argument from Genotype-Environment Interaction…………………76 3.2.2. The Argument from Genotype-Environment Interaction Dismissed……...93 3.3. Science Studies on Genotype-Environment Interaction in the IQ Controversy…….96 3.4. G×EB vs. G×ED…………………………………………………………………….101 3.5. Conclusion…………………………………………………………………………110 4. Difference Mechanisms……………………………………………………………………...112 4.1. Introduction………………………………………………………………………...112 4.2. The Case of Genotype-Environment Interaction…………………………………..119 4.2.1. The Call for an Isolationist Pluralism……………………………………121 4.2.2. The Call for an Integrative Pluralism…………………………………….127 4.3. Difference Mechanisms……………………………………………………………130 4.3.1. Causes as Difference-Makers……………………………………………131 4.3.2. Difference-Makers in Development that Take Different Values in the Natural World……………………………………………………………133 4.3.3. The Interdependence of Difference-Makers in Development that Take Different Values in the Natural World…………………………………..143 4.4. Conclusion…………………………………………………………………………147 5. Rats! So What Is G×E? ……………………………………………………………………...149 5.1. Introduction………………………………………………………………………...149 5.2. G×EB vs. G×ED…………………………………………………………………….151 v 5.2.1. G×EB……………………………………………………………………..151 5.2.2. G×ED……………………………………………………………………..155 5.3. G×EB and G×ED……………………………………………………………………158 5.3.1. What Is an Analysis of Variance?………………………………………..158 5.3.1.1. Mill’s Methods…………………………………………………159 5.3.1.2. Fisher’s Methods……………………………………………….161 5.3.2. What Is the Measure Measuring?………………………………………..168 5.4. Conclusion…………………………………………………………………………173 6. Conclusion…………………………………………………………………………………...175 6.1. Causes of Controversy……………………………………………………………..175 6.2. Making a Difference with Difference Mechanisms………………………………..177 BIBLIOGRAPHY………………………………………………………………………………179 vi LIST OF TABLES Table 1: The components of the biometric and developmental research traditions………………2 Table 2: The components of the biometric research tradition…………………………………...28 Table 3: The components of the developmental research tradition……………………………...54 Table 4: The components of the biometric and developmental research traditions……………..59 Table 5: The components of the biometric research tradition………………………………….105 Table 6: The components of the developmental research tradition…………………………….108 Table 7: The components of the biometric and developmental research traditions……………109 Table 8: The components of the biometric and developmental research traditions……………117 Table 9: The components of the biometric research tradition………………………………….153 Table 10: The components of the developmental research tradition…………………………...156 Table 11: Subgroup means for hypothetical rat population…………………………………….164 Table 12: Subgroup means for actual rat population. Data from Cooper and Zubek (1958)…..167 vii LIST OF FIGURES Figure 1: Norms of reaction for genotypes conferring low and high MAOA activity in response to varying levels of childhood maltreatment………………………………………............4 Figure 2: R. A. Fisher……………………………………………………………………………17 Figure 3: Fisher’s experimental design for differential response of potato varieties to manurial treatments………………………………………………………………………………...24 Figure 4: Fisher’s analysis of variation due to manuring, variety, deviations from summation formula, and variation between parallel plots……………………………………………25 Figure 5: Lancelot Thomas Hogben……………………………………………………………..29 Figure 6: Two frogs, 19 days after pituitary operation by Hogben. (A) partial removal of only anterior lobe. (B) complete removal……………………………………………………...32 Figure 7: Hogben’s norms of reaction for low-bar and ultra-bar Drosophila strains derived from Krafka (1920)…………………………………………………………………………….45 Figure 8: Krafka’s norms of reaction for unselected bar stock (top), low-bar stock (middle), and ultra-bar stock (bottom) eye-facets in response to temperature………………………….52 Figure 9: Lewontin’s hypothetical reaction norm graphs for phenotypic traits caused by canalization……………………………………………….................................................79 Figure 10: Lewontin’s hypothetical reaction norm graphs for phenotypic traits caused by an additive genotype-environment relation………………………………………………….80 Figure 11: Lewontin and Feldman’s hypothetical reaction norm graph…………………………81 Figure 12: Lewontin’s actual reaction norms for viability of fourth chromosome homozygotes of Drosophila pseudoobscura……………………………………………………………….84 Figure 13: Photograph of Richard Lewontin from 1973 Boston Phoenix article “The Brains Do Battle in I.Q. Controversy”……………………………………………………………….87 Figure 14: Layzer’s hypothetical reaction norm graph for three genotypes (x1, x2, and x3) exposed to a variable environment (y)…………………………………………………...91 Figure 15: Molecular, cellular, brain-system, and organismal mechanisms involved in the production of spatial memory in rats……………………………………………………114 Figure 16: Sample Hebb-Williams maze test configurations…………………………………..115 Figure 17: Reaction norm graphs for s/s, s/l, and l/l groups measured for probability of a major depression episode (y-axis) across an array of environments (x-axis). (A) Hypothetically parallel reaction norms. (B) Non-parallel reaction norms from empirical data (Caspi et al. 2003)…………………………………………………………………………………….121 Figure 18: Mechanisms involved in the production of depression. (A) Protein synthesis at the molecular level. (B) Synapse transmission at the cellular level (modified from Hariri and Holmes 2006, Figure 1). (C) Amygdala-cingulate feedback at the brain-system
Load more

Recommended publications
  • Interpreting Noncoding Genetic Variation in Complex Traits and Human Disease
    REVIEW Interpreting noncoding genetic variation in complex traits and human disease Lucas D Ward1,2 & Manolis Kellis1,2 Association studies provide genome-wide information about the genetic basis of complex disease, but medical research has focused primarily on protein-coding variants, owing to the difficulty of interpreting noncoding mutations. This picture has changed with advances in the systematic annotation of functional noncoding elements. Evolutionary conservation, functional genomics, chromatin state, sequence motifs and molecular quantitative trait loci all provide complementary information about the function of noncoding sequences. These functional maps can help with prioritizing variants on risk haplotypes, filtering mutations encountered in the clinic and performing systems-level analyses to reveal processes underlying disease associations. Advances in predictive modeling can enable data-set integration to reveal pathways shared across loci and alleles, and richer regulatory models can guide the search for epistatic interactions. Lastly, new massively parallel reporter experiments can systematically validate regulatory predictions. Ultimately, advances in regulatory and systems genomics can help unleash the value of whole-genome sequencing for personalized genomic risk assessment, diagnosis and treatment. Understanding the genetic basis of disease can transform medicine ture of the human genome, and its systematic mapping by the HapMap by elucidating relevant biochemical pathways for drug targets and by Project9, allowed single-nucleotide polymorphisms (SNPs) to be used enabling personalized risk assessments1,2. With the evolution of technol- as markers for common haplotypes, which could be genotyped using ogies over the past century, geneticists are no longer limited to studying chip technology. The stage was set for a flood of unbiased, genome-wide Mendelian disorders and can tackle complex phenotypes.
    [Show full text]
  • 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.
    [Show full text]
  • The Spice of Life the Variety of Life: a Survey and a Celebration of All the Creatures Snakes in the Grass That Have Ever Lived by Colin Tudge
    book reviews think that’s a false dichotomy.” She quotes, ating input from new methodologies, this is as this there is much to take issue with. In my but seems far less at home with, Sarah Hrdy’s heroism. Since the author took 10 years over own areas of special interest I found almost flat statement: “I did not come into science the job, he must have been daunted by how more to question and argue with than to and primatology because of a love for non- much the ground changed beneath his feet as agree with; and Tudge inevitably can only human primates. I was first attracted to prob- he progressed. When the world around you afford space for a thin overview of the real lems and to things I wanted to understand … is bursting with new kinds of information issues that excite us today. Indeed, for animal There is really no one way of doing science … that are just beginning to shed fresh light on phylogeny, the book only sparsely applies we need people to stress theory as much as a key question, it is a brave man who decides the information that is now emerging observation.” One of Jahme’s subjects, read- to write about the answer! So why has Colin from ‘evolutionary developmental biology’ ing the section about herself, murmured: Tudge done it? (which is revealing underlying similarities “Oh dear. This is half right and all wrong.” To Tudge’s answer is twofold: to help put tax- between diverse species in the structure of me that sums up the book, including some onomy back at the centre of biology (and the genes that control pattern formation and amazing scientific slip-ups.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • Genetics in Harry Potter's World: Lesson 2
    Genetics in Harry Potter’s World Lesson 2 • Beyond Mendelian Inheritance • Genetics of Magical Ability 1 Rules of Inheritance • Some traits follow the simple rules of Mendelian inheritance of dominant and recessive genes. • Complex traits follow different patterns of inheritance that may involve multiples genes and other factors. For example, – Incomplete or blended dominance – Codominance – Multiple alleles – Regulatory genes Any guesses on what these terms may mean? 2 Incomplete Dominance • Incomplete dominance results in a phenotype that is a blend of a heterozygous allele pair. Ex., Red flower + Blue flower => Purple flower • If the dragons in Harry Potter have fire-power alleles F (strong fire) and F’ (no fire) that follow incomplete dominance, what are the phenotypes for the following dragon-fire genotypes? – FF – FF’ – F’F’ 3 Incomplete Dominance • Incomplete dominance results in a phenotype that is a blend of the two traits in an allele pair. Ex., Red flower + Blue flower => Purple flower • If the Dragons in Harry Potter have fire-power alleles F (strong fire) and F’ (no fire) that follow incomplete dominance, what are the phenotypes for the following dragon-fire genotypes: Genotypes Phenotypes FF strong fire FF’ moderate fire (blended trait) F’F’ no fire 4 Codominance • Codominance results in a phenotype that shows both traits of an allele pair. Ex., Red flower + White flower => Red & White spotted flower • If merpeople have tail color alleles B (blue) and G (green) that follow the codominance inheritance rule, what are possible genotypes and phenotypes? Genotypes Phenotypes 5 Codominance • Codominance results in a phenotype that shows both traits of an allele pair.
    [Show full text]
  • The Genetics of Complex Traits Programme Course 7.5 Credits Genetiska Mekanismer Bakom Komplexa Egenskaper 8MEA14 Valid From: 2019 Autumn Semester
    DNR LIU-2019-00662 1(5) The genetics of complex traits Programme course 7.5 credits Genetiska mekanismer bakom komplexa egenskaper 8MEA14 Valid from: 2019 Autumn semester Determined by The Board for First and Second Cycle Programmes at the Faculty of Medicine and Health Sciences Date determined 2019-03-07 LINKÖPING UNIVERSITY FACULTY OF MEDICINE AND HEALTH SCIENCES LINKÖPING UNIVERSITY THE GENETICS OF COMPLEX TRAITS FACULTY OF MEDICINE AND HEALTH SCIENCES 2(5) Main field of study Medical Biology Course level Second cycle Advancement level A1X Course offered for Master's Programme in Experimental and Medical Biosciences Entry requirements Degree of Bachelor of Science, 180 ECTS in a major subject area such as medicine, biology, technology/natural sciences, odontology or veterinary medicine. 90 ECTS of courses included in the Bachelor degree should be in subjects such as biochemistry, cell biology, molecular biology, genetics, gene technology, microbiology, immunology, physiology, histology, anatomy or pathology. Documented skills in English corresponding to level 6/B. Intended learning outcomes The student will learn and understand the basis of quantitative genetic techniques, in particular how they pertain to the identification of genes underlying complex traits and diseases. Knowledge and understanding On completion of the course, the student shall be able to: Describe and understand statistical quantitative genetic techniques and how they apply to complex traits. Explain the statistical basis of quantitative traits. Explain and distinguish between linkage and linkage disequilibrium and their uses. Analyse the genetic architecture of different behavioral and disease-related traits. Analyse and understand the theory and steps required to identify the genetic components of a quantitative trait.
    [Show full text]
  • THE DIALECTICAL BIOLOGIST 11 III II I, 11 1 1 Ni1 the DIALECTICAL BIOLOGIST
    THE DIALECTICAL BIOLOGIST 11 III II I, 11 1 1 ni1 THE DIALECTICAL BIOLOGIST Richard Levins and Richard Lewontin AAKAR THE DIALECTICAL BIOLOGIST Richard Levins and Richard Lewontin Harvard University Press, 1985 Aakar Books for South Asia, 2009 Reprinted by arrangement with Harvard University Press, USA for sale only in the Indian Subcontinent (India, Pakistan, Bangladesh, Nepal, Maldives, Bhutan & Sri Lanka) All rights reserved. No part of this book may be reproduced or transmitted, in any form or by any means, without prior permission of the publisher First Published in India, 2009 ISBN 978-81-89833-77-0 (Pb) Published by AAKAR BOOKS 28 E Pocket IV, Mayur Vihar Phase I, Delhi-110 091 Phone : 011-2279 5505 Telefax : 011-2279 5641 [email protected]; www.aakarbooks.com Printed at S.N. Printers, Delhi-110 032 To Frederick Engels, who got it wrong a lot of the time but who got it right where it counted ,, " I 1 1■ 1-0 ■44 pH III lye II I! Preface THIS Bow( has come into existence for both theoretical andpractical reasons. Despite the extraordinary successes of mechanistic reduction- ist molecular biology, there has been a growing discontent in the last twenty years with simple Cartesian reductionism as the universal way to truth. In psychology and anthropology, and especially in ecology, evolution, neurobiology, and developmental biology, where the Carte- sian program has failed to give satisfaction, we hear more and more calls for an alternative epistemological stance. Holistic, structuralist, hierarchical, and systems theories are all offered as alternative modes of explaining the world, as ways out of the cul-de-sacs into which re- ductionism has led us.
    [Show full text]
  • From Fox Keller, Back to Leibniz and on to Darwin
    Leibnizian Analysis in Metaphysics, Mathematics, Physics, Geology and Biology: From Fox Keller, back to Leibniz and on to Darwin Emily R. Grosholz I. Introduction The world of classical physics proposed a view of nature where systems behaved like machines: they were reducible to their parts, governed by universal laws (which were moreover time-reversal invariant), and thus representable by an axiomatized discourse where predictable events could be deduced, given the correct boundary conditions. Thus, the philosophers of science of the early and mid-twentieth century happily offered the Deductive-Nomological Model of Explanation (and Prediction). It fit Newton’s Principia, Book I, Proposition XI pretty well. However, it doesn’t really account for Book III, the development of the theory and practice of differential equations, the n-body problem, electro-magnetic phenomena, thermodynamics, atoms, galaxies or the expanding universe, limitations that even Thomas Kuhn, author of the revolutionary book The Structure of Scientific Revolutions, (University of Chicago Press, 1962) played down. But the philosophers did notice that the Deductive-Nomological Model of Explanation wasn’t a very good fit for biology, as after Darwin it struggled to account for natural history with its attendant one-way temporality, the emergence of novelty, and the intentionality and nested downwards complexity of living things, that seemed so stubbornly un-machine-like. The discovery of DNA and the rise of a new kind of machine, the computer, briefly encouraged philosophers (and scientists) to think that biology might finally look like a real science, populated by tiny robots that lend themselves to axioms and predictions; but, alas.
    [Show full text]
  • Reaction Norms for the Study of Genotype- Environment Interaction for Growth and Indicator Traits of Sexual Precocity in Nellore Cattle
    Reaction norms for the study of genotype- environment interaction for growth and indicator traits of sexual precocity in Nellore cattle M.V.A. Lemos, H.L.J. Chiaia, M.P. Berton, F.L.B. Feitosa, C. Aboujaoude, G.C. Venturini, H.N. Oliveira, L.G. Albuquerque and F. Baldi Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, SP, Brasil Corresponding author: F. Baldi E-mail: [email protected] Genet. Mol. Res. 14 (2): 7151-7162 (2015) Received August 8, 2014 Accepted February 5, 2015 Published June 29. 2015 DOI http://dx.doi.org/10.4238/2015.June.29.9 ABSTRACT. The objective of this study was to quantify the magnitude of genotype-environment interaction (GxE) effects on age at first calving (AFC), scrotal circumference (SC), and yearling weight (YW) in Nellore cattle using reaction norms. For the study, 89,152 weight records of female and male Nellore animals obtained at yearling age were used. Genetic parameters were estimated with a single-trait random- regression model using Legendre polynomials as base functions. The heritability estimates were of low to medium magnitude for AFC (0.05 to 0.47) and of medium to high magnitude for SC (0.32 to 0.51) and YW (0.13 to 0.72), and increased as the environmental gradient became more favorable. The genetic correlation estimates ranged from 0.25 to 1.0 for AFC, from 0.71 to 1.0 for SC, and from 0.42 to 1.0 for YW. High Spearman correlation coefficients were obtained for the three traits, ranging from 0.97 to 0.99.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]