Rates and Patterns of Molecular Evolution Neutral Theory Predictions

Total Page:16

File Type:pdf, Size:1020Kb

Load more

NEUTRAL THEORY TOPIC 3: Rates and patterns of molecular evolution Neutral theory predictions A particularly valuable use of neutral theory is as a rigid null hypothesis. The neutral theory makes a wide variety of predictions, and one or more of these predictions may be tested in any given molecular dataset. Depending on which predictions (if any) are rejected, we gain considerable insight in the underlying process of evolution for the involved molecular data. The following four predictions are so widely applicable to the field of molecular evolution, that they are often viewed as principles of molecular evolution. 1. The level of within species genetic variation is determined by population size and mutation rate, and is correlated with the level of sequence divergence between species. 2. The rate of gene evolution (substitution) is inversely related to the level of functional constraint (purifying selection) acting on the gene. 3. The pattern of base composition (and codon usage in protein coding genes) at neutral sites reflects mutational equilibrium. 4. There is a constant rate of sequence evolution; i.e., a molecular clock. Each of these predictions is examined in detail in the following four sections of these notes. 1. Variation within and among species Neutral theory provides the bridge between microevolution, in populations, and macroevolution. The connection between the two is actually quite simple, which is one of the reasons why neutral theory has been so successful as a scientific theory. Neutral theory makes two clear predictions about genetic variation within and between species: 1. Equilibrium polymorphism (usually measured as heterozygosity) is controlled by only two parameters; population size (Ne) and mutation rate (µ). 2. Neutral population polymorphism is correlated with divergence between species. 1.1 Equilibrium polymorphism: We covered the first prediction in some detail in the last set of notes. Not surprisingly, there was early interest (1970’s) in comparing natural levels of heterozygosity inferred by protein gel-electrophoresis with those predicted under neutral theory. The results were surprising, in that natural levels of population polymorphism were lower than expected. This finding lead to two important developments in the field: (i) that the parameters Ne and µ are hard to estimate; and (ii) that there were some problems with the original theory that were corrected in what is now called NEARLY NEUTRAL THEORY (we will return to this topic later). Note that protein gel electrophoresis can underestimate polymorphism, and that more recent studies have revealed a general association between heterozygosity and mutation rate. This approach has low power as a means of testing for the expectations of neutral evolution, so most modern work in this area has focused on prediction 2. 1.2 Polymorphism and divergence are correlated: If genes are evolving neutrally, measures of polymorphism within a species should be proportional to the level of divergence between species. This is where the impact of the genetic code on the effect of a mutation becomes very important. Remember that all changes in protein coding sequences can be divided into two classes: (i) synonymous (S) and (ii) non-synonymous (NS). These types of mutation will be impacted differently by the effect of selection on the protein product of the gene. Under neutral theory, selection is not involved, so the ratio of S to NS polymorphism within a species is expected to be equal to the ratio of S and NS substitutions measured between species. If positive selection were acting on at least some mutations, their residence time in the population would we lower than neutral mutations. Hence the ratios would not be the same, and NS mutants would represent a smaller proportion of the within species polymorphism. Comparison of the ratio of synonymous and nonsynonymous polymorphism within species to divergence between species. Neutral theory suggests that the fraction of variation that is nonsynonymous within species should be the same as between species. Species 1 Species 2 Species 3 12:4 6:2 10:3 Polymorphism within a species 17:6 14:5 19:6 Substitutions between species Synonymous (S) Non-synonymous (NS) S:NS Polymorphic 28 9 3.1 Fixed 50 17 2.9 Data are hypothetical. Ratios are tested by using a G-test on the counts of S and NS. These hypothetical data are not significant. If positive selection were acting, residence times for NS would be lower within species and polymorphic S:NS > fixed S:NS. Tests for heterogeneity in the pattern of polymorphism to divergence are called NEUTRALITY TESTS. Tests need not be based on S and NS; amino acids can be divided into physiochemically radical (r) and conservative (c) and the c:r ratio can be tested for heterogeneity. Neutrality tests are powerful and useful. However there is an important caveat with the interpretation of a significant result. Rejection of strict neutrality does not distinguish between violation of the assumption of selective equivalence of alleles, and violation of another one of the involved assumptions of the model. For example, if the effect of selection changes over time due to changes in effective population size, as in nearly neutral theory, a significant result will be obtained from this test. We will return to this topic later. 2. The rate of gene evolution is inversely related to functional constraint Under neutral theory the substitution rate is determined by the mutation rate and the probability of fixation. It is well known that rates vary among genes (e.g., histones verses MHC) and within genes (e.g., introns verse exons). Such rate variation is consistent with neutral theory, even when mutation rates are the same. Remember that neutral theory only asserts that polymorphism is selectively equivalent; it does not require that the frequency of such polymorphism cannot change among sites, gene, or species. 2.1 Variation within genes: We begin with rate variation within genes because it is unlikely that mutation rates vary, and the interpretation of variation in substitution rates is easier. Consider a protein coding gene. It stands to reason that due to the genetic code mutations at some sites will have little effect on the encoded protein (e.g., 3rd codon positions) whereas mutations at other sites (e.g., 1st and 2nd codon positions) are very likely to affect the encoded protein. Consequently, the frequency of selectively equivalent alleles occurring at 3rd codon positions is expected to be much higher than 1st and 2nd codon positions. Hence, 3rd positions are expected to evolve more quickly than 1st and 2nd codon positions. The evolution of functional genes fits this pattern in the vast majority of known cases. For a real example see plot below. Mean number of substitution per site at the three codon positions of the epsilon-globin gene of primates. Two measures are presented: (i) the average over all pair wise comparisons between genes; and (ii) the sum of the branch lengths of the epsilon globin gene tree. Cebus Mean number of substitutions/site Saimiri Aotus 0.15 0.8 Callithrix Lagothrix 0.6 Brachyteles 0.1 Alouatta 0.4 Ateles 0.05 over tree Pan 0.2 pairwise subst/site Homo subst/sitea sum as Pongo 0 0 Macaca 123 Hylobates Tarsius Codon position Galago Otolemur mean pairwise subst rate Cheirogaleus Subst rate as a sum of branch lengths 0.01 Eulemur Under both measures of substitution rate, 3rd codon st nd Gene tree for primate epsilon globins positions evolve faster than 1 and 2 positions. Note: mean number of substitutions per site were computed in all cases by using the Jukes and Cantor (1969) correction. The previous logical argument, as well as the above plots of real data, demonstrates a well known principle of molecular evolution: The greater the functional constraint, the slower the rate of molecular evolution. Under neutral theory we can formulate this principle as a model (Kimura 1968). First we divide all mutations into three categories: (i) adaptive, (ii) deleterious, and (iii) neutral. The first category is assumed to occur very rarely, so their frequency is expected to be effectively zero. Hence the frequency of deleterious mutations is fD and the frequency of neutral mutations f0 = 1 - fD. Let µT equal the total mutation rate per site per unit time. Then the neutral mutation rate per site is: µ0 = µT f0 Hence, the rate of substitution per site per unit time is: k = µT f0 The rate of evolution depends on the “size (f ) of the selective sieve” 0 New mutations New mutations Fixation in a “slow gene” Fixation in a “fast gene” Kimura’s f0 is the fraction of mutations that passes through the “sieve”. So within genes we will assume that µT is the same for all sites. Clearly the value of f0 is largest for the 3rd codon positions of protein coding genes. However we know that not all mutations at 3rd codon positions are synonymous. Thus we might expect that f0 for synonymous positions is even rd larger than f0 for 3 codon positions, and this turns out to be generally true. rd positions: 0.40 Mean at 3 and rodents is higher for synonymousMean at synonymous sites sites: 0.61 45 40 mous sites 35 y 30 ynon S 25 ymous. 20 non 15 y 10 ostions number of proteins of number p 5 substitutions / site / 2x80 million years 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 More rd codon positions because some Rodent 3rd codon gene The average substitution rate between primates as compared with third codon positions. The results are based on a sample of 82 nuclear This result is consistent with neutral theory given that genes.
Recommended publications
  • IN EVOLUTION JACK LESTER KING UNIVERSITY of CALIFORNIA, SANTA BARBARA This Paper Is Dedicated to Retiring University of California Professors Curt Stern and Everett R

    IN EVOLUTION JACK LESTER KING UNIVERSITY of CALIFORNIA, SANTA BARBARA This Paper Is Dedicated to Retiring University of California Professors Curt Stern and Everett R

    THE ROLE OF MUTATION IN EVOLUTION JACK LESTER KING UNIVERSITY OF CALIFORNIA, SANTA BARBARA This paper is dedicated to retiring University of California Professors Curt Stern and Everett R. Dempster. 1. Introduction Eleven decades of thought and work by Darwinian and neo-Darwinian scientists have produced a sophisticated and detailed structure of evolutionary ,theory and observations. In recent years, new techniques in molecular biology have led to new observations that appear to challenge some of the basic theorems of classical evolutionary theory, precipitating the current crisis in evolutionary thought. Building on morphological and paleontological observations, genetic experimentation, logical arguments, and upon mathematical models requiring simplifying assumptions, neo-Darwinian theorists have been able to make some remarkable predictions, some of which, unfortunately, have proven to be inaccurate. Well-known examples are the prediction that most genes in natural populations must be monomorphic [34], and the calculation that a species could evolve at a maximum rate of the order of one allele substitution per 300 genera- tions [13]. It is now known that a large proportion of gene loci are polymorphic in most species [28], and that evolutionary genetic substitutions occur in the human line, for instance, at a rate of about 50 nucleotide changes per generation [20], [24], [25], [26]. The puzzling observation [21], [40], [46], that homologous proteins in different species evolve at nearly constant rates is very difficult to account for with classical evolutionary theory, and at the very least gives a solid indication that there are qualitative differences between the ways molecules evolve and the ways morphological structures evolve.
  • Experiments on the Role of Deleterious Mutations As Stepping Stones In

    Experiments on the Role of Deleterious Mutations As Stepping Stones In

    Experiments on the role of deleterious mutations as PNAS PLUS stepping stones in adaptive evolution Arthur W. Covert IIIa,b,c,d, Richard E. Lenskia,c,e,1, Claus O. Wilkec,d, and Charles Ofriaa,b,c,1 aProgram in Ecology, Evolutionary Biology and Behavior, Departments of bComputer Science and Engineering and eMicrobiology and Molecular Genetics, and cBEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824; and dCenter for Computational Biology, Institute for Cellular and Molecular Biology, and Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712 Contributed by Richard E. Lenski, July 16, 2013 (sent for review April 22, 2013) Many evolutionary studies assume that deleterious mutations spread unless they are tightly linked (5, 6). In an asexual pop- necessarily impede adaptive evolution. However, a later mutation ulation, however, the fortuitous combination, once formed, will that is conditionally beneficial may interact with a deleterious be stably inherited, thereby providing a simple way to traverse a predecessor before it is eliminated, thereby providing access to fitness valley (5–10). adaptations that might otherwise be inaccessible. It is unknown Previous research on a variety of systems, both biological and whether such sign-epistatic recoveries are inconsequential events computational, has documented many examples of epistatic inter- or an important factor in evolution, owing to the difficulty of actions between mutations (3, 6, 11, 14–24), including a few cases monitoring the effects and fates of all mutations during experi- of mutational pairs that are individually deleterious but jointly ments with biological organisms.
  • The Neutral Theory of Molecular Evolution

    The Neutral Theory of Molecular Evolution

    Copyright 2000 by the Genetics Society of America Perspectives Anecdotal, Historical and Critical Commentaries on Genetics Edited by James F. Crow and William F. Dove Thomas H. Jukes (1906±1999) James F. Crow Genetics Department, University of Wisconsin, Madison, Wisconsin 53706 OM Jukes accepted our invitation to write a Perspec- duced an immediate outcry from traditional students Ttives on the early history of molecular evolution, of evolution, undoubtedly abetted by the title. In the and in August 1999 he sent a rough beginning con- ensuing polemics, Kimura played the major role. King taining some now-forgotten early history. He planned an died prematurely in 1983 and Jukes wrote mainly about extensive revision and continuation, but on November 1 other things, although he did participate in one joint his death intervened. We have decided to publish his paper (Jukes and Kimura 1984). One of his interests early draft, realizing that it was but a start toward the was the evolution of the genetic code (Jukes 1983). I article that he had planned. particularly liked his showing how, in an orderly sequen- Tom, along with Jack L. King and Motoo Kimura, tial way, mutation pressure in the codon and anti-codon formulated the neutral theory of molecular evolution. could produce the unexpected codes in bacteria and Earlier, the idea had been foreshadowed by Sueoka mitochondria (Jukes 1985). He also developed a widely (1962) and Freese (1962). They had each suggested used correction for multiple undetected changes in evo- mutation pressure of near-neutral changes to account lutionary base substitutions (Jukes and Cantor 1969).
  • Population Genetics of Neutral Mutations in Exponentially

    Population Genetics of Neutral Mutations in Exponentially

    The Annals of Applied Probability 2013, Vol. 23, No. 1, 230–250 DOI: 10.1214/11-AAP824 c Institute of Mathematical Statistics, 2013 POPULATION GENETICS OF NEUTRAL MUTATIONS IN EXPONENTIALLY GROWING CANCER CELL POPULATIONS By Rick Durrett1 Duke University In order to analyze data from cancer genome sequencing projects, we need to be able to distinguish causative, or “driver,” mutations from “passenger” mutations that have no selective effect. Toward this end, we prove results concerning the frequency of neutural mutations in exponentially growing multitype branching processes that have been widely used in cancer modeling. Our results yield a simple new population genetics result for the site frequency spectrum of a sample from an exponentially growing population. 1. Introduction. It is widely accepted that cancers result from an accu- mulation of mutations that increase the fitness of tumor cells compared to the cells that surround them. A number of studies [Sj¨oblom et al. (2006), Wood et al. (2007), Parsons et al. (2008), The Cancer Genome Atlas (2008) and Jones et al. (2008, 2010)] have sequenced the genomes of tumors in or- der to find the causative or “driver” mutations. However, due to the large number of genes being sequenced, one also finds a large number of “passen- ger” mutations that are genetically neutral and hence have no role in the disease. To explain the issues involved in distinguishing the two types of mutations, it is useful to take a look at a data set. Wood et al. (2007) did a “discovery” screen in which 18,191 genes were sequenced in 11 colorectal cancers, and then a “validation” screen in which the top candidates were sequenced in 96 additional tumors.
  • Effectively Neutral Mutations

    Effectively Neutral Mutations

    Proc. Natl. Acad. Sci. USA Vol. 76, No. 7, pp. 3440-3444, July 1979 Genetics Model of effectively neutral mutations in which selective constraint is incorporated (molecular evolution/protein polymorphism/population genetics/neutral mutation theory) MOTOO KIMURA National Institute of Genetics, Mishima 411, Japan Contributed by Motoo Kimura, April 25, 1979 ABSTRACT Based on the idea that selective neutrality is however, Ohta's model has a drawback in that it cannot ac- the limit when the selective disadvantage becomes indefinitely commodate enough mutations that behave effectively as neutral small, a model of neutral (and nearly neutral) mutations is pro- when the population size gets large. This difficulty can be posed that assumes that the selection coefficient (s') against the overcome by assuming that the selection coefficients follow a mutant at various sites within a cistron (gene) follows a r dis- r distribution. tribution; Ass') = aPe-as's.-l/P(,B), in which a = fi/i and s' is the mean selection coefficient against the mutants (?'> 0; 1 _ ft > 0). The mutation rate for alleles whose selection coef- MODEL OF EFFECTIVELY NEUTRAL ficients s' lie in the range between 0 and 1/(2Ne), in which Ne MUTATIONS is the effective population size, is termed the effectively neutral mutation rate (denoted by ye). Using the model of "infinite Let us assume that the frequency distribution of the selective sites" in population genetics, formulas are derived giving the disadvantage (denoted by s') of mutants among different sites average heterozygosity (he) and evolutionary rate per generation follows the r distribution (kg) in terms of mutant substitutions.
  • Genomic Insights Into Positive Selection

    Genomic Insights Into Positive Selection

    Review TRENDS in Genetics Vol.22 No.8 August 2006 Genomic insights into positive selection Shameek Biswas and Joshua M. Akey Department of Genome Sciences, University of Washington, 1705 NE Pacific, Seattle, WA 98195, USA The traditional way of identifying targets of adaptive more utilitarian benefits, each target of positive selection evolution has been to study a few loci that one has a story to tell about the historical forces and events hypothesizes a priori to have been under selection. that have shaped the history of a population. This approach is complicated because of the confound- Several genome-wide analyses for positive selection ing effects that population demographic history and have been performed in a variety of species. In this review, selection have on patterns of DNA sequence variation. In we summarize some of the recent studies, primarily principle, multilocus analyses can facilitate robust focusing on humans, critically evaluate what genome- inferences of selection at individual loci. The deluge of wide scans for selection are and are not likely to find and large-scale catalogs of genetic variation has stimulated suggest future avenues of research. A brief overview of many genome-wide scans for positive selection in statistical methods used to detect deviations from several species. Here, we review some of the salient neutrality is summarized in Box 1. For more detailed observations of these studies, identify important chal- discussions, see Refs [6,7]. lenges ahead, consider the limitations of genome-wide scans for selection and discuss the potential significance Thinking genomically of a comprehensive understanding of genomic patterns Positive selection perturbs patterns of genetic variation of selection for disease-related research.
  • Evolution on Neutral Networks Accelerates the Ticking Rate of the Molecular Clock Arxiv:1307.0968V2 [Q-Bio.PE] 24 Sep 2014

    Evolution on Neutral Networks Accelerates the Ticking Rate of the Molecular Clock Arxiv:1307.0968V2 [Q-Bio.PE] 24 Sep 2014

    Evolution on neutral networks accelerates the ticking rate of the molecular clock Susanna Manrubia1 and Jos´eA. Cuesta2;3 Grupo Interdisciplinar de Sistemas Complejos (GISC), Madrid 1 Dept. de Biolog´ıade Sistemas, Centro Nacional de Biotecnolog´ıa(CSIC) c/ Darwin 3, 28045 Madrid, Spain. 2 Dept. de Matem´aticas,Universidad Carlos III de Madrid 28911 Legan´es,Madrid, Spain. 3 Instituto de Biocomputaci´ony F´ısicade Sistemas Complejos (BIFI) Universidad de Zaragoza, 50009 Zaragoza, Spain. June 17, 2021 Abstract Large sets of genotypes give rise to the same phenotype because phenotypic expression is highly redundant. Accordingly, a population can accept mutations without altering its phenotype, as long as the genotype mutates into another one on the same set. By linking every pair of genotypes that are mutually accessible through mutation, geno- types organize themselves into neutral networks (NN). These networks are known to be heterogeneous and assortative, and these properties affect the evolutionary dynamics of the population. By studying the dynamics of populations on NN with arbitrary topology we analyze the arXiv:1307.0968v2 [q-bio.PE] 24 Sep 2014 effect of assortativity, of NN (phenotype) fitness, and of network size. We find that the probability that the population leaves the network is smaller the longer the time spent on it. This progressive \phenotypic entrapment" entails a systematic increase in the overdispersion of the process with time and an acceleration in the fixation rate of neutral mutations. We also quantify the variation of these effects with the size of the phenotype and with its fitness relative to that of neighbouring alternatives.
  • A Study on a Nearly Neutral Mutation Model in Finite Populations

    A Study on a Nearly Neutral Mutation Model in Finite Populations

    Copyright 0 1991 by the Genetics Society of America A Study on a Nearly Neutral Mutation Model in Finite Populations Hidenori Tachida National Institute of Genetics, Mishima, Shizuoka-ken 41 1,Japan Manuscript received August 16, 1990 Accepted for publication January 19, 199 1 ABSTRACT As a nearly neutral mutation model, the house-of-cards model is studied in finite populations using computer simulations. The distribution of the mutant effect is assumed to be normal. The behavior is mainly determined by the product of the population size, N, and the standard deviation, u, of the distribution of the mutant effect. If 4Nu is large compared to one, a few advantageous mutants are quickly fixed in early generations. Then most mutation becomes deleterious and very slow increase of the average selection coefficient follows. It takesvery long for the population to reach the equilibrium state. Substitutions of alleles occur very infrequently in the later stage. If 4Na is the order of one or less, the behavior is qualitatively similar to that of the strict neutral case. Gradual increase of the average selection coefficient occurs and in generations of several times the inverse of the mutation rate the population almost reaches the equilibrium state. Both advantageous and neutral (including slightly deleterious) mutations are fixed. Except in the early stage, an increase of the standard deviation of the distribution of the mutant effect decreases the average heterozygosity. The substitution rate is reduced as 4Nu is increased. Three tests of neutrality, one using the relationship between the average and the variance of heterozygosity, another using the relationship between the average heterozygosity and the average number of substitutions and Watterson’s homozygosity test are applied to the consequences of the present model.
  • Neutral Evolution of Model Proteins: Diffusion in Sequence Space and Overdispersion

    Neutral Evolution of Model Proteins: Diffusion in Sequence Space and Overdispersion

    Neutral evolution of model proteins: diffusion in sequence space and overdispersion. Ugo Bastolla(a)∗, H. Eduardo Roman(b) and Michele Vendruscolo(c) (a)HLRZ, Forschungszentrum J¨ulich, D-52425 J¨ulich, Germany (b)Dipartimento di Fisica and INFN, Universit`adi Milano, I-20133 Milano Italy (c)Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel We simulate the evolution of model protein sequences subject to mutations. A mutation is considered neutral if it conserves 1) the structure of the ground state, 2) its thermodynamic stabil- ity and 3) its kinetic accessibility. All other mutations are considered lethal and are rejected. We adopt a lattice model, amenable to a reliable solution of the protein folding problem. We prove the existence of extended neutral networks in sequence space – sequences can evolve until their similarity with the starting point is almost the same as for random sequences. Furthermore, we find that the rate of neutral mutations has a broad distribution in sequence space. Due to this fact, the substitution process is overdispersed (the ratio between variance and mean is larger than one). This result is in contrast with the simplest model of neutral evolution, which assumes a Poisson process for substitutions, and in qualitative agreement with biological data. I. INTRODUCTION A recent study on the Protein Data Bank (PDB) showed that the distribution of pairwise sequence identity between structurally homologous proteins presents a large Gaussian peak at 8.5% sequence identity, only slightly larger than what expected in the purely random case1 (Rost, 1998). This is an interesting result which means that the structural similarity does not imply sequence similarity.
  • “Neutralism” Elsevier Handbook in Philosophy of Biology Stephens and Matthen, Editors Anya Plutynski Fall 2004 in 1968, Moto

    “Neutralism” Elsevier Handbook in Philosophy of Biology Stephens and Matthen, Editors Anya Plutynski Fall 2004 in 1968, Moto

    “Neutralism” Elsevier Handbook in Philosophy of Biology Stephens and Matthen, Editors Anya Plutynski Fall 2004 In 1968, Motoo Kimura submitted a note to Nature entitled “Evolutionary Rate at the Molecular Level,” in which he proposed what has since become known as the neutral theory of molecular evolution. This is the view that the majority of evolutionary changes at the molecular level are caused by random drift of selectively neutral or nearly neutral alleles. Kimura was not proposing that random drift explains all evolutionary change. He does not challenge the view that natural selection explains adaptive evolution, or, that the vertebrate eye or the tetrapod limb are products of natural selection. Rather, his objection is to “panselectionism’s intrusion into the realm of molecular evolutionary studies”. According to Kimura, most changes at the molecular level from one generation to the next do not affect the fitness of organisms possessing them. King and Jukes (1969) published an article defending the same view in Science, with the radical title, “Non- Darwinian Evolution,” at which point, “the fat was in the fire” (Crow, 1985b). The neutral theory was one of the most controversial theories in biology in the late twentieth century. On the one hand, the reaction of many biologists was extremely skeptical; how could evolution be “non-Darwinian”? Many biologists claimed that a “non-Darwinian” theory of evolution was simply a contradiction in terms. On the other hand, some molecular biologists accepted without question that many changes at the molecular level from one generation to the next were neutral. Indeed, when King and Jukes’ paper was first submitted, it was rejected on the grounds that one reviewer claimed it was obviously false, and the other claimed that it was obviously true (Jukes, 1991).
  • Molecular Evolution? Molecular Evolution • Evolution at the Molecular Level

    Molecular Evolution? Molecular Evolution • Evolution at the Molecular Level

    BIOL2007 What is molecular evolution? Molecular Evolution • Evolution at the molecular level Kanchon Dasmahapatra [email protected] Modes of molecular evolution Modes of molecular evolution Gene duplication INDELS: insertions and deletions Slippage in tandem repeats 1 Modes of molecular evolution Substitutions GCG ACG GGG GAG • Single base pair changes, substitutions or point mutations GCG ACA GGG GA G • Insertions or deletions, also known as indels 64 triplet codons coding for 20 amino acids • Gene duplications - formation of multigene GT T CG T TGG Tryptophan families and pseudogenes Histidine GT C CG C Proline Cysteine • Slippage – microsatellite length changes GT A TGC GT G • Chromosomal mutations Twofold degenerate Fourfold degenerate NON- SYNONYMOUS SYNONYMOUS SUBSTITUTION SUBSTITUTION (silent substitution) Classical vs. Balance schools Who is right? • Classical school • Data in the form of allozymes showed that lots of – polymorphisms are rare polymorphisms are present. – because selection gets rid of less fit alleles • But .... causes the problem of genetic load • Balance school 30,000 to 50,000 genes in humans – polymorphisms are common If only 1000 are homozygous – because of balancing selection If selective coefficient = 0.01 Fitness per locus = 0.99 Summed over 1000 loci, fitness = (0.99) 1000 = 0.00004 2 The neutral theory Neutralists vs. selectionists • Proposed by Kimura (1968) and King & Jukes Neutralists Selectionists (1969) • Majority of mutations that spread through a Deleterious population have no effect on fitness Neutral Advantageous • Therefore, genetic drift NOT natural selection drives molecular evolution • Mutations fixed by • Mutations fixed by genetic drift selection Kimura’s calculations Predictions from neutral theory µ = mutation rate per gene per generation • Molecular clock N = population size (effective) • rate of substitution ∝ 1 No.
  • Neutral Mutation and Selective Constraint Play Major Role in Dictating the Codon Bias in Breast Cancer Risk Genes

    Neutral Mutation and Selective Constraint Play Major Role in Dictating the Codon Bias in Breast Cancer Risk Genes

    International Journal of Computational Biology ISSN: 2229-6700 & E-ISSN:2229-6719, Volume 5, Issue 1, 2014, pp.-061-067. Available online at http://www.bioinfopublication.org/jouarchive.php?opt=&jouid=BPJ0000220 NEUTRAL MUTATION AND SELECTIVE CONSTRAINT PLAY MAJOR ROLE IN DICTATING THE CODON BIAS IN BREAST CANCER RISK GENES MAZUMDER T.H. AND CHAKRABORTY S.* Department of Biotechnology, Assam University, Silchar- 788 011, Assam, India. *Corresponding Author: Email- [email protected] Received: September 24, 2014; Accepted: October 30, 2014 Abstract- Breast cancer is ranked the first cancer in women worldwide and the second leading cause of death after cervical cancer particular- ly in developing countries. Specific genes are associated with breast cancer risk in human genome. Understanding the codon usage bias (CUB) with compositional dynamics of coding sequence is of great importance in gaining clues to predict the level of gene expression and genome characterization. In this study, we have analyzed the complete nucleotide coding sequences of fifteen breast cancer risk genes with the help of various genetic indices. Our analysis revealed that both neutral mutation and selective constraint play major roles in the codon usage patterns of breast cancer risk genes. Our results further show that gene expression level is linked with alterations in the nucleotide skewness. Breast cancer gene products showed the dominance of three amino acids namely serine, leucine and glutamate in their composi- tion but the least usage of two amino acids namely tryptophan and methionine. Moreover, the level of breast cancer gene expression meas- ured by RCBS revealed a significant negative correlation with highly used amino acids.