Evolution and Human Adaptation
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Natural Selection and Adaptation, Part I
Natural Selection and Adaptation, Part I 36-149 The Tree of Life Christopher R. Genovese Department of Statistics 132H Baker Hall x8-7836 http://www.stat.cmu.edu/~genovese/ . Plan • Review of Natural Selection • Detecting Natural Selection (discussion) • Examples of Observed Natural Selection ............................... Next Time: • Adaptive Traits • Methods for Reasoning about and studying adaptations • Explaining Complex Adaptations (discussion) 36-149 The Tree of Life Class #10 -1- Overview The theories of common descent and natural selection play different roles within the theory of evolution. Common Descent explains the unity of life. Natural Selection explains the diversity of life. An adaptation (or adaptive trait) is a feature of an organism that enhances reproductive success, relative to other possible variants, in a given environment. Adaptations become prevalent and are maintained in a population through natural selection. Indeed, natural selection is the only mechanism of evolutionary change that can satisfactorily explain adaptations. 36-149 The Tree of Life Class #10 -2- Darwin's Argument Darwin put forward two main arguments in support of natural selection: An analogical argument: Artificial selection A logical argument: The struggle for existence (As we will see later, we now have more than just argument in support of the theory.) 36-149 The Tree of Life Class #10 -3- The Analogical Argument: Artificial Selection 36-149 The Tree of Life Class #10 -4- The Analogical Argument: Artificial Selection 36-149 The Tree of Life Class #10 -5- The Analogical Argument: Artificial Selection Teosinte to Corn 36-149 The Tree of Life Class #10 -6- The Analogical Argument: Artificial Selection • Darwin was intimately familiar with the efforts of breeders in his day to produce novel varieties. -
1. Adaptation and the Evolution of Physiological Characters
Bennett, A. F. 1997. Adaptation and the evolution of physiological characters, pp. 3-16. In: Handbook of Physiology, Sect. 13: Comparative Physiology. W. H. Dantzler, ed. Oxford Univ. Press, New York. 1. Adaptation and the evolution of physiological characters Department of Ecology and Evolutionary Biology, University of California, ALBERT F. BENNETT 1 Irvine, California among the biological sciences (for example, behavioral CHAPTER CONTENTS science [I241). The Many meanings of "Adaptationn In general, comparative physiologists have been Criticisms of Adaptive Interpretations much more successful in, and have devoted much more Alternatives to Adaptive Explanations energy to, pursuing the former rather than the latter Historical inheritance goal (37). Most of this Handbook is devoted to an Developmentai pattern and constraint Physical and biomechanical correlation examination of mechanism-how various physiologi- Phenotypic size correlation cal systems function in various animals. Such compara- Genetic correlations tive studies are usually interpreted within a specific Chance fixation evolutionary context, that of adaptation. That is, or- Studying the Evolution of Physiological Characters ganisms are asserted to be designed in the ways they Macroevolutionary studies Microevolutionary studies are and to function in the ways they do because of Incorporating an Evolutionary Perspective into Physiological Studies natural selection which results in evolutionary change. The principal textbooks in the field (for example, refs. 33, 52, 102, 115) make explicit reference in their titles to the importance of adaptation to comparative COMPARATIVE PHYSIOLOGISTS HAVE TWO GOALS. The physiology, as did the last comparative section of this first is to explain mechanism, the study of how organ- Handbook (32). Adaptive evolutionary explanations isms are built functionally, "how animals work" (113). -
Biology of Human Variation Fall 2014
Anthropology 2110 Biology of Human Variation Fall 2014 Professor: Dr. Tamara Varney Location: AT1010 Lecture time: Tues 7-10 Phone: 807-343-8204 Office: Braun Building 2001D Email: [email protected] Office Hours: Thurs 9-11am am until Oct 15 then by appointment**(if its more convenient feel free to set an appointment time) OR you can phone, email or drop in anytime to see if I am free – just be prepared to come at another time if I am busy with something I cannot interrupt I cannot guarantee that I will respond in a timely fashion if messages are left on my voice mail rather than email and students should NOT expect less than 24 hour turnaround time to email messages. Please DO NOT assume that your message, voice or email, has been received unless you receive an acknowledgement. Course Description: This course focuses on human microevolution. Topics include evolutionary theory, the genetic background of human variation, the distribution of human variation, human adaptability, and the role of disease and other influences on human evolution. Required Textbook: (available at the University Bookstore) Mielke JH, Konigsberg LW and Relethford JH. 2011. Human Biological Variation. 2nd Edition. Oxford University Press. ISBN 13: 978-0-19-538740-7 Also see the course Desire2Learn (D2L) site (look in MyCourseLinks on the LU website) for additional resources. Evaluation: Your final grade will be based on: Term Test 1 25% Oct 27 Term Test 2 30% Nov 18 Final Exam 45% Final examination period – Dec 9-19 **Note exam contingency date is Dec 20. Please note that Fri, November 6, 2015 is the last date for withdrawal without academic penalty from this course. -
Evolutionary and Historical Biogeography of Animal Diversity Learning Objectives
Evolutionary and historical biogeography of animal diversity Learning objectives • The students can explain the common ancestor of animal kingdom. • The students can explain the historical biogeography of animal. • The students can explain the invasion of animal from aquatic to terrestrial habitat. • The students can explain the basic mechanism of speciation, allopatric and non-allopatric. The Common Ancestor of Animal Kingdom Characteristics of Animals • Animals or “metazoans” are typically heterotrophic, multicellular organisms with diploid, eukaryotic cells. • Trichoplax adhaerens is defined as an animal by the presence of different somatic (i.e., non-reproductive) cell types and by impermeable cell–cell connections. Trichoplax adhaerens Blackstone, 2009 Two Hypotheses for the Branching Order of Groups at the Root of the Metazoan Tree 1 2 The choanoflagellates serve as an outgroup in the Bilaterians are the sister group to the placozoan + analysis, and sponges are the sister group to the sponge + ctenophore + cnidarian clade, while placozoans placozoan + cnidarian + ctenophore + bilaterian are the sister group to the sponge + ctenophore + clade. cnidarian clade. Blackstone, 2009 Ancestry and evolution of animal–bacterial interactions • Choanoflagellates as the last common ancestor of animal kingdom. • Urmetazoan is the group of animal with multicellular and produce differentiated cell types (ex. Egg & sperm) R.A. Alegado & N. King, 2014 Conserved morphology and ultrastructure of Choanoflagellates and Sponge choanocytes The collar complex is conserved in choanoflagellates (A. S. rosetta) and sponge collar cells (B. Sycon coactum) flagellum (fL), microvilli (mv), a nucleus (nu), and a food vacuole (fv) Brunet & King, 2017 The Historical Biogeography of Animal Zoogeographic regions Old New Cox, 2001 Plate tectonic regulation of global marine animal diversity A. -
Reducing Risks Through Adaptation Actions | Fourth National Climate
Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II 28 Reducing Risks Through Adaptation Actions Federal Coordinating Lead Authors Review Editor Jeffrey Arnold Mary Ann Lazarus U.S. Army Corps of Engineers Cameron MacAllister Group Roger Pulwarty National Oceanic and Atmospheric Administration Chapter Lead Robert Lempert RAND Corporation Chapter Authors Kate Gordon Paulson Institute Katherine Greig Wharton Risk Management and Decision Processes Center at University of Pennsylvania (formerly New York City Mayor’s Office of Recovery and Resiliency) Cat Hawkins Hoffman National Park Service Dale Sands Village of Deer Park, Illinois Caitlin Werrell The Center for Climate and Security Technical Contributors are listed at the end of the chapter. Recommended Citation for Chapter Lempert, R., J. Arnold, R. Pulwarty, K. Gordon, K. Greig, C. Hawkins Hoffman, D. Sands, and C. Werrell, 2018: Reducing Risks Through Adaptation Actions. In Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K. Maycock, and B.C. Stewart (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, pp. 1309–1345. doi: 10.7930/NCA4.2018.CH28 On the Web: https://nca2018.globalchange.gov/chapter/adaptation Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II 28 Reducing Risks Through Adaptation Actions Key Message 1 Seawall surrounding Kivalina, Alaska Adaptation Implementation Is Increasing Adaptation planning and implementation activities are occurring across the United States in the public, private, and nonprofit sectors. Since the Third National Climate Assessment, implementation has increased but is not yet commonplace. -
Sequence Variations in the Public Human Genome Data Reflect a Bottlenecked Population History
Sequence variations in the public human genome data reflect a bottlenecked population history Gabor Marth*†, Greg Schuler*, Raymond Yeh‡, Ruth Davenport§, Richa Agarwala*, Deanna Church*, Sarah Wheelan*¶, Jonathan Baker*, Ming Ward*, Michael Kholodov*, Lon Phan*, Eva Czabarka*, Janos Murvai*, David Cutlerʈ, Stephen Wooding**, Alan Rogers**, Aravinda Chakravartiʈ, Henry C. Harpending**, Pui-Yan Kwok†,††, and Stephen T. Sherry*† *National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894; ‡Department of Genetics, Washington University School of Medicine, St. Louis, MO 63130; §Division of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63130; ¶Department of Molecular Biology and Genetics and ʈMcKusick–Nathans Institute of Genetic Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD 21205; **Department of Anthropology, University of Utah, Salt Lake City, UT 84112; and ††Cardiovascular Research Institute and Department of Dermatology, University of California, San Francisco, CA 94143 Contributed by Henry C. Harpending, November 5, 2002 Single-nucleotide polymorphisms (SNPs) constitute the great ma- (density) distribution of genomic sequence variations. To this jority of variations in the human genome, and as heritable variable end, we built a set of reagents (pairwise sequence alignments landmarks they are useful markers for disease mapping and re- and their corresponding sets of variation) by analyzing the solving population structure. Redundant coverage in overlaps of overlapping regions of large-insert clones sequenced as part of large-insert genomic clones, sequenced as part of the Human the human genome project. These data provided marker Genome Project, comprises a quarter of the genome, and it is density observations grouped by overlap fragment length. -
Methods to Detect Selection in Populations with Applications to the Human
P1: FQP/VEN July 6, 2000 12:24 Annual Reviews AR104-19 Annu. Rev. Genomics Hum. Genet. 2000. 01:539–59 Copyright c 2000 by Annual Reviews. All rights reserved METHODS TO DETECT SELECTION IN POPULATIONS WITH APPLICATIONS TO THE HUMAN Martin Kreitman Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637; e-mail: [email protected] Key Words natural selection, genetic drift, polymorphism, molecular evolution ■ Abstract The development of statistical tests of natural selection at the DNA level in population samples has been ongoing for the past 13 years. The current state of the field is reviewed, and the available tests of selection are described. All tests use predictions from the theory of neutrally evolving sites as a null hypothesis. Departures from equilibrium-neutral expectations can indicate the presence of natural selection acting either at one or more of the sites under investigation or at a sufficiently tightly linked site. Complications can arise in the interpretation of departures from neutrality if populations are not at equilibrium for mutation and genetic drift or if populations are subdivided, both of which are likely scenarios for humans. Attempts to understand the nonequilibrium configuration of silent polymorphism in human mitochondrial DNA illustrate the difficulty of distinguishing between selection and alternative demographic hypotheses. The range of plausible alternatives to selection will become better defined, however, as additional population genetic data sets become available, allowing better null models to be constructed. INTRODUCTION Kimura’s immensely influential formulation of the neutral theory of molecular evolution, which came in 1968, was based primarily on an argument about the magnitude of the genetic load that would be imposed by positive selection if it were the only driving force in protein evolution (56). -
General Adaptation Guidance: a Guide to Adapting Evidence-Based Sexual Health Curricula
General Adaptation Guidance: A Guide to Adapting Evidence-Based Sexual Health Curricula Adaptation Kit Tools and Resources for Making Informed Adaptations s Evidence-Based ProgramAn ed A An Evidence-BasedAn Program Evidence Based Program Adaptation Kit Tools and Resources for Making InformedAdaptation Adaptations Kit Tools and Resources for Making Informed Adaptations - Nicole Lezin Lori Rolleri For more information, contact: Julie Taylor More information about adaptation guidelines is available at ReCAPP, www.etr.org/recapp Regina Firpo-Triplett, MPH, CHES ETR [email protected], www.etr.org/recapp Taleria R. Fuller, PhD CDC Division of Reproductive Health [email protected], www.cdc.gov/teenpregnancy/ Spring 2012 Funding was made possible by Contract #GS10F0171T from the Centers for Disease Control and Prevention (CDC). About this Guide and the Adaptation Project Using an evidence-based intervention or EBI (a program that has been shown through rigorous evaluation to be effective at changing risk-taking behavior) assures that intervention efforts are devoted to what has been proven to work. Most practitioners make adaptations to EBIs to meet the unique characteristics of their local populations or projects. However, while this is a common practice, making changes to an EBI without a clear understanding of its core components can compromise the program’s effectiveness. ETR Associates, with funding from and in collaboration with the CDC Division of Reproductive Health (DRH), has developed guidelines on how to make appropriate adaptations to sexual health EBIs without sacrificing their core components. This guide provides general green (safe), yellow (proceed with caution) and red (unsafe) light adaptation guidance for practitioners considering making adaptations to sexual health EBIs. -
Human DNA Sequences: More Variation and Less Race
AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 139:23–34 (2009) Human DNA Sequences: More Variation and Less Race Jeffrey C. Long,1* Jie Li,1 and Meghan E. Healy2 1Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109-5618 2Department of Anthropology, University of New Mexico, Albuquerque, NM 87131 KEY WORDS race; DNA sequence; short tandem repeat; diversity; hierachical models ABSTRACT Interest in genetic diversity within and sity is one of nested subsets, such that the diversity in between human populations as a way to answer questions non-Sub-Saharan African populations is essentially a sub- about race has intensified in light of recent advances in set of the diversity found in Sub-Saharan African popula- genome technology. The purpose of this article is to apply tions. The actual pattern of DNA diversity creates some a method of generalized hierarchical modeling to two unsettling problems for using race as meaningful genetic DNA data sets. The first data set consists of a small sam- categories. For example, the pattern of DNA diversity ple of individuals (n 5 32 total, from eight populations) implies that some populations belong to more than one who have been fully resequenced for 63 loci that encode a race (e.g., Europeans), whereas other populations do not total of 38,534 base pairs. The second data set consists of belong to any race at all (e.g., Sub-Saharan Africans). As a large sample of individuals (n 5 928 total, from 46 popu- Frank Livingstone noted long ago, the Linnean classifica- lations) who have been genotyped at 580 loci that encode tion system cannot accommodate this pattern because short tandem repeats. -
The New Adaptation Marketplace: Climate Change and Opportunities for Green Economic Growth
The new adaptation marketplace: Climate change and opportunities for green economic growth Climate change is a growing humanitarian crisis that we cannot ignore. Developing innovative ways to adapt to its impacts is a necessity. Policies that address the impact of global warming on the world’s most vulnerable communities can drive the market toward new innovation and stimulate the US economy. It is critical that we make investments in what are known By investing in adaptation strategies, such as flood defenses as “climate change preparedness” or “adaptation” measures. and efficient irrigation systems, not only can we lessen the These strategies can help reduce the risk of harm to vulner- impact of future natural disasters, but we can drive economic able communities by building resilience to the impacts of growth by strengthening infrastructure and spurring the climate change. For example, one adaptation approach en- development of new technologies. Strong public policies that ables people in coastal areas to construct or strengthen homes provide funding for adaptation have multiple benefits, both that can withstand stronger storms and increased flooding. in the US and abroad. These include the following: Even with aggressive efforts to reduce emissions, the • Encouraging companies to develop new, innovative consequences of climate change will be severe; increased technologies and to hire new workers, creating jobs and temperatures, rising sea levels, and more intense droughts, stimulating the economy; floods, and storms threaten the existence of many communi- • Enabling long-term economic growth built around green ties—especially in developing countries. Adaptation efforts technologies that are resilient to climate change; reflect the unavoidable fact that the situation is already bad • Helping vulnerable communities in the US and around the enough. -
Adaptation, Natural Selection and Evolution Learning Intentions • Give the Meaning of the Term Mutation
Adaptation, natural selection and evolution Learning Intentions • Give the meaning of the term mutation. • State that mutations may be neutral, confer an advantage or a disadvantage. • State that mutations are spontaneous and are the only source of new alleles. • Give two environmental factors which can increase the rate of mutation. • Give the meaning of the term adaptation. • Give examples of adaptations which allow a species to survive. • State that adaptation may be structural, physiological or behavioural. • Describe examples of behaviours which allow a species to survive. • State that variation within a population makes it possible for a population to evolve over time in response to changing conditions. • Describe natural selection/survival of the fittest. • Describe the process of speciation. Mutation • A mutation is a random change to the genetic material of an organism • Mutations are rare, random and spontaneous • Mutations can alter the phenotype or functioning of the organism. • Mutations which occur in sex cells are inherited by offspring, they are the only source of new alleles, and can alter the phenotype or functioning of the organism. Types of Mutation • Mutations can be neutral, an advantage or a disadvantage • Neutral – these have no effect on the organism • Confer an advantage – for example the peppered moth mutation which made moths dark in colour – this allowed them to be camouflaged in industrial areas with soot covering trees • Confer a disadvantage – for example a gene mutation in chromosome 7 in humans leads to cystic fibrosis Moths…how many can you see? Mutagenic Agents • The rate of mutations can be artificially increased by environmental factors such as: – Radiation such as X-rays, UV light, gamma rays – Chemicals like colchicine, mustard gas and benzene. -
Systematic Uncertainties and Domain Adaptation
Systematic Uncertainties and Domain Adaptation Michael Kagan SLAC Hammers and Nails July, 2017 2 The Goal ATLAS-CONF-2017-043 The Higgs Boson! 3 The Goal ATLAS-CONF-2017-043 The Higgs Boson! • Want to reject the “No Higgs” hypothesis ( + ) • Hopefully measure the size of the 4 The Goal ATLAS-CONF-2017-043 The Higgs Boson! • Need accurate predictions for and 5 The Goal ATLAS-CONF-2017-043 The Higgs Boson! • And we need to know how wrong these predictions could be… 6 Sources of Systematic Uncertainty ATLAS-CONF-2017-041 • Experimental – How well we understand the detector and our ability to identify / measure properties of particles given that they are present • Theoretical – How well we understand the underlying theoretical model of the physical processes • Modeling uncertainties – How well can I constrain backgrounds in alternate data measurements / control regions Error Propagation 7 • Random variables x={x1, x2, … , xn} distributed according to p(x) – Assume we only know E[x] = µ and Var[xi, xj] = Vij • For some function f(x), first order approximation N @f f(x) f(µ)+ (xi µi) ⇡ @xi x=µ − i=1 X • Then E[f(x)] f(µ) ⇡ N 2 2 @f @f σf = E[(f(x) f(µ)) ] Vij − ⇡ @x @x x=µ i, j=1 i j X h i Error Propagation 8 • Often, we only have samples of x • But we know how x varies under some uncertainty – x → x ± Δx – Where Δx is a 1 standard deviation change in x • Then often approximate the error on f(x) with – ±Δf(x) = f(x ± Δx ) – f(x) • So we vary x and see how f(x) changes – Often histogram the distributions, showing ±Δf(x) as a band on the histogram