Genetic Structure of Populations and Differentiation in Forest Trees1
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Autism, Genetics, and Inbreeding: an Evolutionary View
Vol. 8(5), pp. 67-71, May 2016 DOI: 10.5897/JPHE2015.0764 Article Number: 5670C9357949 Journal of Public Health and ISSN 2141-2316 Copyright © 2016 Epidemiology Author(s) retain the copyright of this article http://www.academicjournals.org/JPHE Review Autism, genetics, and inbreeding: An evolutionary view Alex S. Prayson National Council on Rehabilitation Education Received 18 July, 2015; Accepted 22 January, 2016 Recently there have been increased reports of autism, yet the disease is not contagious. Since it is not catching, there must be other forces at work that somehow create or pass on the autistic symptoms. DNA reports show that deviations in the genetic code due to ancient inbreeding can follow a human line for generations. Studies show that inbreeding was widespread until a few hundred years ago and is continued today, but to a lesser degree. After millions of inbreeds, the world population has become so numerous that it is globally sharing ancestors which is producing genetic abnormalities. In other words, autism may be the result of the widespread inbreeding of ancient generations. We are all touched by autism to one degree or another through common ancestors. The DNA of modern Homo sapiens of European and/or Asian descent will show 1 to 4% Neanderthal from 40,000 years ago. With that in mind, todays outbreaks may be due to descendants of ancient inbreeding times surfacing at the same time. Key words: Autism, genetics, inbreeding, DNA, ancient generations, consanguineous marriage, incest INTRODUCTION The world might be smaller than you think chances of inheriting a bad DNA fit which results in a birth defect. -
Cousin Marriage & Inbreeding Depression
Evidence of Inbreeding Depression: Saudi Arabia Saudi Intermarriages Have Genetic Costs [Important note from Raymond Hames (your instructor). Cousin marriage in the United States is not as risky compared to cousin marriage in Saudi Arabia and elsewhere where there is a long history of repeated inter-marriage between close kin. Ordinary cousins without a history previous intermarriage are related to one another by 0.0125. However, in societies with a long history of intermarriage, relatedness is much higher. For US marriages a study published in The Journal of Genetic Counseling in 2002 said that the risk of serious genetic defects like spina bifida and cystic fibrosis in the children of first cousins indeed exists but that it is rather small, 1.7 to 2.8 percentage points higher than for children of unrelated parents, who face a 3 to 4 percent risk — or about the equivalent of that in children of women giving birth in their early 40s. The study also said the risk of mortality for children of first cousins was 4.4 percentage points higher.] By Howard Schneider Washington Post Foreign Service Sunday, January 16, 2000; Page A01 RIYADH, Saudi Arabia-In the centuries that this country's tribes have scratched a life from the Arabian Peninsula, the rule of thumb for choosing a marriage partner has been simple: Keep it in the family, a cousin if possible, or at least a tribal kin who could help conserve resources and contribute to the clan's support and defense. But just as that method of matchmaking served a purpose over the generations, providing insurance against a social or financial mismatch, so has it exacted a cost--the spread of genetic disease. -
Gene Linkage and Genetic Mapping 4TH PAGES © Jones & Bartlett Learning, LLC
© Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION Gene Linkage and © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC 4NOTGenetic FOR SALE OR DISTRIBUTIONMapping NOT FOR SALE OR DISTRIBUTION CHAPTER ORGANIZATION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR4.1 SALELinked OR alleles DISTRIBUTION tend to stay 4.4NOT Polymorphic FOR SALE DNA ORsequences DISTRIBUTION are together in meiosis. 112 used in human genetic mapping. 128 The degree of linkage is measured by the Single-nucleotide polymorphisms (SNPs) frequency of recombination. 113 are abundant in the human genome. 129 The frequency of recombination is the same SNPs in restriction sites yield restriction for coupling and repulsion heterozygotes. 114 fragment length polymorphisms (RFLPs). 130 © Jones & Bartlett Learning,The frequency LLC of recombination differs © Jones & BartlettSimple-sequence Learning, repeats LLC (SSRs) often NOT FOR SALE OR DISTRIBUTIONfrom one gene pair to the next. NOT114 FOR SALEdiffer OR in copyDISTRIBUTION number. 131 Recombination does not occur in Gene dosage can differ owing to copy- Drosophila males. 115 number variation (CNV). 133 4.2 Recombination results from Copy-number variation has helped human populations adapt to a high-starch diet. 134 crossing-over between linked© Jones alleles. & Bartlett Learning,116 LLC 4.5 Tetrads contain© Jonesall & Bartlett Learning, LLC four products of meiosis. -
Population Structure
Population Structure Population Structure Nonrandom Mating HWE assumes that mating is random in the population Most natural populations deviate in some way from random mating There are various ways in which a species might deviate from random mating We will focus on the two most common departures from random mating: inbreeding population subdivision or substructure Population Structure Nonrandom Mating: Inbreeding Inbreeding occurs when individuals are more likely to mate with relatives than with randomly chosen individuals in the population Increases the probability that offspring are homozygous, and as a result the number of homozygous individuals at genetic markers in a population is increased Increase in homozygosity can lead to lower fitness in some species Increase in homozygosity can have a detrimental effect: For some species the decrease in fitness is dramatic with complete infertility or inviability after only a few generations of brother-sister mating Population Structure Nonrandom Mating: Population Subdivision For subdivided populations, individuals will appear to be inbred due to more homozygotes than expected under the assumption of random mating. Wahlund Effect: Reduction in observed heterozygosity (increased homozygosity) because of pooling discrete subpopulations with different allele frequencies that do not interbreed as a single randomly mating unit. Population Structure Wright's F Statistics Sewall Wright invented a set of measures called F statistics for departures from HWE for subdivided populations. F stands for fixation index, where fixation being increased homozygosity FIS is also known as the inbreeding coefficient. The correlation of uniting gametes relative to gametes drawn at random from within a subpopulation (Individual within the Subpopulation) FST is a measure of population substructure and is most useful for examining the overall genetic divergence among subpopulations Is defined as the correlation of gametes within subpopulations relative to gametes drawn at random from the entire population (Subpopulation within the Total population). -
Allele Frequency–Based and Polymorphism-Versus
View metadata, citation and similar papers at core.ac.uk brought to you by CORE Allele Frequency–Based and Polymorphism-Versus- provided by PubMed Central Divergence Indices of Balancing Selection in a New Filtered Set of Polymorphic Genes in Plasmodium falciparum Lynette Isabella Ochola,1 Kevin K. A. Tetteh,2 Lindsay B. Stewart,2 Victor Riitho,1 Kevin Marsh,1 and David J. Conway*,2 1Kenya Medical Research Institute, Centre for Geographic Medicine Research Coast, Kilifi, Kenya 2Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom *Corresponding author: E-mail: [email protected], [email protected]. Associate editor: John H. McDonald Research article Abstract Signatures of balancing selection operating on specific gene loci in endemic pathogens can identify candidate targets of naturally acquired immunity. In malaria parasites, several leading vaccine candidates convincingly show such signatures when subjected to several tests of neutrality, but the discovery of new targets affected by selection to a similar extent has been slow. A small minority of all genes are under such selection, as indicated by a recent study of 26 Plasmodium falciparum merozoite- stage genes that were not previously prioritized as vaccine candidates, of which only one (locus PF10_0348) showed a strong signature. Therefore, to focus discovery efforts on genes that are polymorphic, we scanned all available shotgun genome sequence data from laboratory lines of P. falciparum and chose six loci with more than five single nucleotide polymorphisms per kilobase (including PF10_0348) for in-depth frequency–based analyses in a Kenyan population (allele sample sizes .50 for each locus) and comparison of Hudson–Kreitman–Aguade (HKA) ratios of population diversity (p) to interspecific divergence (K) from the chimpanzee parasite Plasmodium reichenowi. -
Genetic Diversity in Partially Selfing Populations with the Stepping-Stone Structure
Heredity 77 (1996) 469—475 Received 20 October 1995 Genetic diversity in partially selfing populations with the stepping-stone structure HIDENORI TACHIDA*t & HIROSHI YOSHIMARU tDepartment of Biology, Faculty of Science, Kyushu University 33, Fukuoka 812, Japan and tPopulation Genetics Laboratory, Forestry and Forest Products Research Institute, Tsukuba, Ibaraki 305, Japan Amethod to compute identity coefficients of two genes in the stepping-stone model with partial selfing is developed. The identity coefficients in partially selfing populations are computed from those in populations without selfing as functions of s (selfing rate), m (migra- tion rate), N (subpopulation size), n (number of subpopulations) and u (mutation rate). For small m, 1/N and u, it is shown that approximate formulae for the identity coefficients of two genes from different individuals are the same as those in random mating populations if we replace N in the latter with N(1 —s12).Thus,the effects of selfing on genetic variability are summarized as reducing variation within subpopulations and increasing differentiation among subpopulations by reducing the subpopulation size. The extent of biparental inbreeding as measured by the genotypic correlation between truly outcrossed mates was computed in the one-dimensional stepping-stone model. The correlation was shown to be independent of the selfing rate and starts to fall off as the migration rate increases when mN is larger than 0.1. Keywords:biparentalinbreeding, fixation index, genetic variability, geographical differentia- tion, selfing, stepping-stone model. Introduction Model analysis Manyplant species are partially self-fertilizing Genesare defined to be identical by descent if they (Brown, 1990; Murawski & Hamrick, 1991, 1992; have a common ancestor gene and there is no muta- Kitamura et a!., 1994). -
Development of Novel SNP Assays for Genetic Analysis of Rare Minnow (Gobiocypris Rarus) in a Successive Generation Closed Colony
diversity Article Development of Novel SNP Assays for Genetic Analysis of Rare Minnow (Gobiocypris rarus) in a Successive Generation Closed Colony Lei Cai 1,2,3, Miaomiao Hou 1,2, Chunsen Xu 1,2, Zhijun Xia 1,2 and Jianwei Wang 1,4,* 1 The Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430070, China; [email protected] (L.C.); [email protected] (M.H.); [email protected] (C.X.); [email protected] (Z.X.) 2 University of Chinese Academy of Sciences, Beijing 100049, China 3 Guangdong Provincial Key Laboratory of Laboratory Animals, Guangdong Laboratory Animals Monitoring Institute, Guangzhou 510663, China 4 National Aquatic Biological Resource Center, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430070, China * Correspondence: [email protected] Received: 10 November 2020; Accepted: 11 December 2020; Published: 18 December 2020 Abstract: The complex genetic architecture of closed colonies during successive passages poses a significant challenge in the understanding of the genetic background. Research on the dynamic changes in genetic structure for the establishment of a new closed colony is limited. In this study, we developed 51 single nucleotide polymorphism (SNP) markers for the rare minnow (Gobiocypris rarus) and conducted genetic diversity and structure analyses in five successive generations of a closed colony using 20 SNPs. The range of mean Ho and He in five generations was 0.4547–0.4983 and 0.4445–0.4644, respectively. No significant differences were observed in the Ne, Ho, and He (p > 0.05) between the five closed colony generations, indicating well-maintained heterozygosity. -
Microevolution and the Genetics of Populations Microevolution Refers to Varieties Within a Given Type
Chapter 8: Evolution Lesson 8.3: Microevolution and the Genetics of Populations Microevolution refers to varieties within a given type. Change happens within a group, but the descendant is clearly of the same type as the ancestor. This might better be called variation, or adaptation, but the changes are "horizontal" in effect, not "vertical." Such changes might be accomplished by "natural selection," in which a trait within the present variety is selected as the best for a given set of conditions, or accomplished by "artificial selection," such as when dog breeders produce a new breed of dog. Lesson Objectives ● Distinguish what is microevolution and how it affects changes in populations. ● Define gene pool, and explain how to calculate allele frequencies. ● State the Hardy-Weinberg theorem ● Identify the five forces of evolution. Vocabulary ● adaptive radiation ● gene pool ● migration ● allele frequency ● genetic drift ● mutation ● artificial selection ● Hardy-Weinberg theorem ● natural selection ● directional selection ● macroevolution ● population genetics ● disruptive selection ● microevolution ● stabilizing selection ● gene flow Introduction Darwin knew that heritable variations are needed for evolution to occur. However, he knew nothing about Mendel’s laws of genetics. Mendel’s laws were rediscovered in the early 1900s. Only then could scientists fully understand the process of evolution. Microevolution is how individual traits within a population change over time. In order for a population to change, some things must be assumed to be true. In other words, there must be some sort of process happening that causes microevolution. The five ways alleles within a population change over time are natural selection, migration (gene flow), mating, mutations, or genetic drift. -
Genetic and Epigenetic Regulation of Phenotypic Variation in Invasive Plants – Linking Research Trends Towards a Unified Fr
A peer-reviewed open-access journal NeoBiota 49: 77–103Genetic (2019) and epigenetic regulation of phenotypic variation in invasive plants... 77 doi: 10.3897/neobiota.49.33723 REVIEW ARTICLE NeoBiota http://neobiota.pensoft.net Advancing research on alien species and biological invasions Genetic and epigenetic regulation of phenotypic variation in invasive plants – linking research trends towards a unified framework Achyut Kumar Banerjee1, Wuxia Guo1, Yelin Huang1 1 State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University 135 Xingangxi Road, Guangzhou, Guangdong, 510275, China Corresponding author: Yelin Huang ([email protected]) Academic editor: Harald Auge | Received 7 February 2019 | Accepted 26 July 2019 | Published 19 August 2019 Citation: Banerjee AK, Guo W, Huang Y (2019) Genetic and epigenetic regulation of phenotypic variation in invasive plants – linking research trends towards a unified framework. NeoBiota 49: 77–103. https://doi.org/10.3897/ neobiota.49.33723 Abstract Phenotypic variation in the introduced range of an invasive species can be modified by genetic variation, environmental conditions and their interaction, as well as stochastic events like genetic drift. Recent stud- ies found that epigenetic modifications may also contribute to phenotypic variation being independent of genetic changes. Despite gaining profound ecological insights from empirical studies, understanding the relative contributions of these molecular mechanisms behind phenotypic variation has received little attention for invasive plant species in particular. This review therefore aimed at summarizing and synthesizing information on the genetic and epige- netic basis of phenotypic variation of alien invasive plants in the introduced range and their evolutionary consequences. -
Inbreeding Effects in Wild Populations
230 Review TRENDS in Ecology & Evolution Vol.17 No.5 May 2002 43 Putz, F.E. (1984) How trees avoid and shed lianas. estimate of total aboveground biomass for an neotropical forest of French Guiana: spatial and Biotropica 16, 19–23 eastern Amazonian forest. J. Trop. Ecol. temporal variability. J. Trop. Ecol. 17, 79–96 44 Appanah, S. and Putz, F.E. (1984) Climber 16, 327–335 52 Pinard, M.A. and Putz, F.E. (1996) Retaining abundance in virgin dipterocarp forest and the 48 Fichtner, K. and Schulze, E.D. (1990) Xylem water forest biomass by reducing logging damage. effect of pre-felling climber cutting on logging flow in tropical vines as measured by a steady Biotropica 28, 278–295 damage. Malay. For. 47, 335–342 state heating method. Oecologia 82, 350–361 53 Chai, F.Y.C. (1997) Above-ground biomass 45 Laurance, W.F. et al. (1997) Biomass collapse in 49 Restom, T.G. and Nepstad, D.C. (2001) estimation of a secondary forest in Sarawak. Amazonian forest fragments. Science Contribution of vines to the evapotranspiration of J. Trop. For. Sci. 9, 359–368 278, 1117–1118 a secondary forest in eastern Amazonia. Plant 54 Putz, F.E. (1983) Liana biomass and leaf area of a 46 Meinzer, F.C. et al. (1999) Partitioning of soil Soil 236, 155–163 ‘terra firme’ forest in the Rio Negro basin, water among canopy trees in a seasonally dry 50 Putz, F.E. and Windsor, D.M. (1987) Liana Venezuela. Biotropica 15, 185–189 tropical forest. Oecologia 121, 293–301 phenology on Barro Colorado Island, Panama. -
Intro Forensic Stats
Popstats Unplugged 14th International Symposium on Human Identification John V. Planz, Ph.D. UNT Health Science Center at Fort Worth Forensic Statistics From the ground up… Why so much attention to statistics? Exclusions don’t require numbers Matches do require statistics Problem of verbal expression of numbers Transfer evidence Laboratory result 1. Non-match - exclusion 2. Inconclusive- no decision 3. Match - estimate frequency Statistical Analysis Focus on the question being asked… About “Q” sample “K” matches “Q” Who else could match “Q" partial profile, mixtures Match – estimate frequency of: Match to forensic evidence NOT suspect DNA profile Who is in suspect population? So, what are we really after? Quantitative statement that expresses the rarity of the DNA profile Estimate genotype frequency 1. Frequency at each locus Hardy-Weinberg Equilibrium 2. Frequency across all loci Linkage Equilibrium Terminology Genetic marker variant = allele DNA profile = genotype Database = table that provides frequency of alleles in a population Population = some assemblage of individuals based on some criteria for inclusion Where Do We Get These Numbers? 1 in 1,000,000 1 in 110,000,000 POPULATION DATA and Statistics DNA databases are needed for placing statistical weight on DNA profiles vWA data (N=129) 14 15 16 17 18 19 20 freq 14 9 75 15 3 0 6 16 19 1 1 46 17 23 1 14 9 72 18 6 0 3 10 4 31 19 6 1 7 3 2 2 23 20 0 0 0 3 2 0 0 5 258 Because data are not available for every genotype possible, We use allele frequencies instead of genotype frequencies to estimate rarity. -
Inference and Analysis of Population Structure Using Genetic Data and Network Theory
| INVESTIGATION Inference and Analysis of Population Structure Using Genetic Data and Network Theory Gili Greenbaum,*,†,1 Alan R. Templeton,‡,§ and Shirli Bar-David† *Department of Solar Energy and Environmental Physics and †Mitrani Department of Desert Ecology, Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, 84990 Midreshet Ben-Gurion, Israel, ‡Department of Biology, Washington University, St. Louis, Missouri 63130, and §Department of Evolutionary and Environmental Ecology, University of Haifa, 31905 Haifa, Israel ABSTRACT Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance- based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition’s modularity, a network theory measure indicating the quality of community partitions.