DOCSLIB.ORG

Landscape Genetics

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Landscape Genetics Landscape genetics Instructor: K. McGarigal Assigned Reading: Manel et al (2003) Objective: Provide an overview of the consequences of landscape pattern to the spatial genetic structure of populations. Highlight the role of landscape structure in gene flow and approaches for examining the relationship between spatial genetic structure and the structure of landscapes. Topics covered: 1. What is landscape genetics? 2. What is gene flow? 3. Why is gene flow important? 4. How much gene flow is enough? 5. Gene flow in heterogeneous landscapes 6. Landscape genetics: statistical approaches and examples Comments: Slides adapted from presentation by Dr. Michael Schwartz, USDA Forest Service Rocky Mountain Research Station, Missoula, Montana. 15.1 1. What is Landscape Genetics Landscape genetics is an approach for understanding of how geographical and environmental features structure genetic variation at both the population and individual levels. Importantly, landscape genetics: a. does not require that discrete populations be identified in advance; b. emphasizes the processes and patterns of gene flow and local adaptation; and c. the analysis involves detection of genetic discontinuities and the correlation of these discontinuities with landscape features. Landscape genetics is an emerging discipline that combines the fields of population genetics and landscape ecology. 15.2 2. What is Gene Flow? Gene flow is the incorporation of genes into the gene pool of one population from other populations. In this regard, it is important to distinguish between the processes of dispersal and migration as defined from a genetics perspective. • Dispersal – the permanent movement away from the site where an organism was born (i.e., its natal site). Note dispersal refers to the movement of an individual away from its natal site; it is not necessarily true that the individuals genes will be incorporated into the new population, since this requires successful reproduction. • Migration – refers to the movement of genes from one population to another accomplished by individuals that move and breed in a population other than their birth site. Migration, as defined here, equals gene flow. Note, migration is defined somewhat differently by biologists, where it generally refers to the periodic (typically seasonal) movement of individuals between geographic locations. 15.3 3. Why is Gene Flow Important? Gene flow is important for many reasons, including the following: • Prevent inbreeding of populations – gene flow reduces the potential for inbreeding, the reduction in fitness due to the random loss of heterozygosity (genetic diversity) associated with small populations, by introducing new genes into a population.. • Prevent depression of population fitness – gene flow functions to increase the heterozygosity of individuals and populations and thereby increase population fitness. • Prevent the suite of demographic problems that arise as a consequence of inbreeding or alone (e.g., allee) – gene flow helps to prevent inbreeding depression, as noted above, and can reduce the potential for the Allee effect in small populations – the rapid loss of fitness (e.g., fecundity) in very small populations. • Decrease extinction risk – by functioning to reduce inbreeding depression and the reduction in fitness due to the loss of heterozygosity, gene flow can serve to decrease the risk of population extinction. 15.4 Example: Greater prairie chicken (Westemeier et al. 1998) In 1933, the greater prairie chicken in Illinois numbered 25,000; in 1962 it was down to 2,000; and in 1993 it was down to just 50 individuals. Moreover, in 1960 there was a 90% hatching success rate, but in 1990 that rate had fallen to 74%. The decrease in fecundity (i.e., fitness) was hypothesized to be due to the loss of genetic diversity associated, which declined 30% between 1960-1990. To reverse the situation, managers introduced birds from Minnesota and Kansas to infuse new genes into the population, and hatching rate success increased to 94%. The population has since recovered from near extinction. 15.5 Example: Scandanavian adder (Maddsen et al. 2001) An Scandanavian adder population crashed between 1983-1993. The population had very low genetic diversity and a large number of stillborn offspring were observed, an indication of low fitness due to inbreeding depression. To counter the population crash, managers introduced 20 males from a larger population for 3 years between 1996-1999. The immediate result was an increase in male recruitment and a decrease in the number of stillborns. Note, the males were returned to their native population after performing their duty. 15.6 As this table illustrates (from Manel et al 2003), there are numerous empirical examples of studies showing genetic rescue effects of induced gene flow to small populations. 15.7 4. How Much Gene Flow is Enough? So, if gene flow is important, at the very least to reduce the potential for inbreeding depression in small populations, how much is enough? While this is not an easy question to answer, the general rule of thumb that has been put forth is that one migrant per generation is necessary to prevent the adversities of inbreeding depression, while also allowing for divergence in allele frequencies among subpopulations. Mills and Allendorf (1996) authors argue that one migrant per generation is an appropriate minimum, but that the “rule” should be broadened to include a maximum of 10 migrants per generation. Vucetich and Waite (2000) question whether that rule of thumb is sufficient for fluctuation populations, and demonstrate that most populations fluctuate enough to require >10 migrants per generation and many may even require >20 per generation. 15.8 Example: Brassica campestris (Newman and Tallmon 2001) In this inbreeding experiment involving the mustard Brassica campestris, five of six fitness related components were negatively effected by inbreeding. The researchers experimentally introduced migrant treatments of 0, 1, and 2.5. The results were dramatic. The 1 migrant treatment and 2.5 migrant treatment produced higher fitness components than the 0 migrant treatment, and there was no difference between 1 and 2.5 migrant treatments, suggesting that in this case the 1 migrant per generation rule may be enough to prevent inbreeding depression. 15.9 Example: Peromyscus maniculatus (Schwartz and Mills 2005) In this study involving Peromyscus maniculatus, the researchers compared survival rates in a relatively isolated control population against two different treatments: a migrant treatment in which individuals from another distant source population were introduced to the local population, and an inbreeding treatment in which a population was experimentally inbreed. The migrant treatment resulted in a dramatic increase in survival. Surprisingly, the inbreeding treatment also resulted in an increase in survival, which the authors attribute to a number of factors. 15.10 5. Gene Flow in Heterogeneous Landscapes The question we are most interested in is whether landscape patterns, in particular those created by human land uses, influence gene flow and to what extent. Consider the following series of slides and try to answer the question, is gene flow occurring? 15.11 15.12 15.13 In order to answer the question, is gene flow occurring, we need to sidetrack and do a quick genetics primer for those that either haven’t had genetics or had it too long ago. Collection of genetic samples The first thing we need to do is collect genetic samples. There are many ways to do this. Optimal samples (i.e., containing the most DNA) include tissue and blood, but the collection of these samples requires invasive sampling. Sub-optimal samples include hair, scat, urine, skins/museum specimens, feathers and guano, and these can generally be obtained using non-invasive methods. 15.14 Types of DNA 1. Mitochondrial DNA (mtDNA) – is contained (obviously) in the mitochondria of cells and there are thousands of copies per cell (at least 20 times more DNA than in cell nucleus). Mitochondrial DNA is maternally inherited, so it is passed down directly from mother to offspring, and is highly conserved; i.e., it is very stable and does not change much over generations. Thus, the DNA in your mitochondria and very much the same as those that were carried by your great, great, great, great, etc. grandmother. 2. Nuclear DNA – is contained (obviously) in the nucleus of cells and there are two copies per cell. Nuclear DNA is inherited from both parents, one copy from each parent. There are highly variable regions called microsatellites that are very useful for distinguishing individuals and for differentiating very recent population divergences. 15.15 Species ID using mtDNA mtDNA is especially useful for distinguishing among species, which is often the first thing that must be done after collecting non-invasive samples in order to be sure of the species. There are two common approaches for this purpose: 1. Restriction digests (RFLP) – in which known genes are extracted using restriction enzymes and the size of the alleles are used to distinguish among species. 2. DNA sequence analysis – in which the exact nucleotide sequence for a section of DNA is determined and differences in the sequence are used to distinguish among species. 15.16 Restriction Digests Step 1. The first step is to separate the DNA from other cellular material. Note, at this stage all of the DNA, both nuclear and mitochondrial, is mixed together. Step 2. The next step is to add a primer pair (2 short pieces of DNA, approximately 20 base pairs in length), which latch on to either side of an area of interest (typically a 100-800 bp length of DNA). Step 3. The next step is to make many copies of the genetic fragment using Polymerase chain reaction (PCR). Step 4. Finally, the last step is to separate the fragments by size using gel electrophoresus. Essentially, this entails putting the genetic material on a gel and passing an electrical current across it. The DNA fragments migrate across the gel according to their size; large fragments only move a short distance, while small fragments move farther across the gel.
Load more

Recommended publications
  • Spatial Population Genetics: It's About Time
    Spatial Population Genetics: It's About Time Gideon S. Bradburd1a and Peter L. Ralph2 May 13, 2019 1Ecology, Evolutionary Biology, and Behavior Group, Department of Inte- grative Biology, Michigan State University, East Lansing, MI, USA, 48824 2Institute of Ecology and Evolution, Departments of Mathematics and Bi- ology, University of Oregon, Eugene, OR 97403 [email protected] Abstract Many questions that we have about the history and dynamics of organisms have a geographical component: How many are there, and where do they live? How do they move and interbreed across the land- scape? How were they moving a thousand years ago, and where were the ancestors of a particular individual alive today? Answers to these questions can have profound consequences for our understanding of his- tory, ecology, and the evolutionary process. In this review, we discuss how geographic aspects of the distribution, movement, and reproduc- tion of organisms are reflected in their pedigree across space and time. Because the structure of the pedigree is what determines patterns of relatedness in modern genetic variation, our aim is to thus provide in- tuition for how these processes leave an imprint in genetic data. We also highlight some current methods and gaps in the statistical toolbox arXiv:1904.09847v2 [q-bio.PE] 10 May 2019 of spatial population genetics. 1 Contents 1 Introduction 3 2 The spatial pedigree 4 2.1 Peeking at the spatial pedigree . 6 2.2 Simulating spatial pedigrees . 6 2.3 Estimating \effective" parameters from the spatial pedigree . 7 3 Things we want to know 8 3.1 Where are they? .
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • Effective Population Size Is Strongly Correlated with Breeding Pond Size in the Endangered California Tiger Salamander, Ambystoma Californiense
    Conserv Genet (2011) 12:911–920 DOI 10.1007/s10592-011-0194-0 RESEARCH ARTICLE Effective population size is strongly correlated with breeding pond size in the endangered California tiger salamander, Ambystoma californiense Ian J. Wang • Jarrett R. Johnson • Benjamin B. Johnson • H. Bradley Shaffer Received: 19 October 2010 / Accepted: 31 January 2011 / Published online: 18 February 2011 Ó The Author(s) 2011. This article is published with open access at Springerlink.com Abstract Maintaining genetic diversity and population breeding habitat for A. californiense. We found no cor- viability in endangered and threatened species is a primary relation between pond area and heterozygosity or allelic concern of conservation biology. Genetic diversity diversity, but we identified a strong positive relationship depends on population connectivity and effective popula- between breeding pond area and Ne, particularly for vernal tion size (Ne), both of which are often compromised in pools. Our results provide some of the first empirical endangered taxa. While the importance of population evidence that variation in breeding habitat can be associ- connectivity and gene flow has been well studied, inves- ated with differences in Ne and suggest that a more tigating effective population sizes in natural systems has complete understanding of the environmental features that received far less attention. However, Ne plays a prominent influence Ne is an important component of conservation role in the maintenance of genetic diversity, the preven- genetics and management. tion of inbreeding depression, and in determining the probability of population persistence. In this study, we Keywords Effective population size Á Landscape examined the relationship between breeding pond char- genetics Á Dispersal Á Bottleneck Á Population structure Á acteristics and Ne in the endangered California tiger sal- Microsatellite amander, Ambystoma californiense.
    [Show full text]
  • 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.
    [Show full text]
  • A Longitudinal Genetic Survey Identifies Temporal Shifts in the Population
    Heredity (2016) 117, 259–267 & 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved 0018-067X/16 www.nature.com/hdy ORIGINAL ARTICLE A longitudinal genetic survey identifies temporal shifts in the population structure of Dutch house sparrows L Cousseau1, M Husemann2, R Foppen3,4, C Vangestel1,5 and L Lens1 Dutch house sparrow (Passer domesticus) densities dropped by nearly 50% since the early 1980s, and similar collapses in population sizes have been reported across Europe. Whether, and to what extent, such relatively recent demographic changes are accompanied by concomitant shifts in the genetic population structure of this species needs further investigation. Therefore, we here explore temporal shifts in genetic diversity, genetic structure and effective sizes of seven Dutch house sparrow populations. To allow the most powerful statistical inference, historical populations were resampled at identical locations and each individual bird was genotyped using nine polymorphic microsatellites. Although the demographic history was not reflected by a reduction in genetic diversity, levels of genetic differentiation increased over time, and the original, panmictic population (inferred from the museum samples) diverged into two distinct genetic clusters. Reductions in census size were supported by a substantial reduction in effective population size, although to a smaller extent. As most studies of contemporary house sparrow populations have been unable to identify genetic signatures of recent population declines, results of this study underpin the importance of longitudinal genetic surveys to unravel cryptic genetic patterns. Heredity (2016) 117, 259–267; doi:10.1038/hdy.2016.38; published online 8 June 2016 INTRODUCTION demographic population growth and increased genetic variation as Rapid land use changes, most severely the loss or fragmentation of a result of gene flow (Hanski and Gilpin, 1991; Clobert et al.,2001).
    [Show full text]
  • Impact of Landscape on Host–Parasite Genetic Diversity and Distribution Using the Puumala Orthohantavirus–Bank Vole System
    microorganisms Article Impact of Landscape on Host–Parasite Genetic Diversity and Distribution Using the Puumala orthohantavirus–Bank Vole System Maria Razzauti 1,* , Guillaume Castel 1 and Jean-François Cosson 2 1 CBGP, INRAE, CIRAD, IRD, Montpellier SupAgro, Université Montpellier, 34000 Montpellier, France; [email protected] 2 UMR BIPAR, Animal Health Laboratory, ANSES, INRAE, Ecole Nationale Vétérinaire d’Alfort, Université Paris-Est, 94700 Maisons-Alfort, France; [email protected] * Correspondence: [email protected] Abstract: In nature, host specificity has a strong impact on the parasite’s distribution, prevalence, and genetic diversity. The host’s population dynamics is expected to shape the distribution of host-specific parasites. In turn, the parasite’s genetic structure is predicted to mirror that of the host. Here, we study the tandem Puumala orthohantavirus (PUUV)–bank vole system. The genetic diversity of 310 bank voles and 33 PUUV isolates from 10 characterized localities of Northeast France was assessed. Our findings show that the genetic diversity of both PUUV and voles, was positively correlated with forest coverage and contiguity of habitats. While the genetic diversity of voles was weakly structured in space, that of PUUV was found to be strongly structured, suggesting that the dispersion of voles was not sufficient to ensure a broad PUUV dissemination. Genetic diversity of PUUV was mainly shaped by purifying selection. Genetic drift and extinction events were better Citation: Razzauti, M.; Castel, G.; reflected than local adaptation of PUUV. These contrasting patterns of microevolution have important Cosson, J.-F. Impact of Landscape on consequences for the understanding of PUUV distribution and epidemiology.
    [Show full text]
  • Current Status, Future Opportunities, and Remaining Challenges in Landscape Genetics
    Chapter 14 CURRENT STATUS, FUTURE OPPORTUNITIES, AND REMAINING CHALLENGES IN LANDSCAPE GENETICS 1 2 3 4 Niko Balkenhol, Samuel A. Cushman, Lisette P. Waits, and Andrew Storfer 1 Department of Wildlife Sciences, University of Göttingen, Germany 2 Forest and Woodlands Ecosystems Program, Rocky Mountain Research Station, United States Forest Service, USA 3 Fish and Wildlife Sciences, University of Idaho, USA 4 School of Biological Sciences, Washington State University, USA 14.1 INTRODUCTION essentially replaced the isolation-by-distance paradigm with spatially explicit tests of effects of landscape varia- Just over a decade ago, advances in geographic informa- bles on genetic population structure. More generally, tion systems and genetic methodology helped usher in landscape genetics has advanced the field of evolution- the field of landscape genetics, an amalgamation of ary ecology by providing a direct focus on relationships landscape ecology, population genetics, and spatial sta- between landscape patterns and population processes, tistics aimed at testing how landscape heterogeneity such as gene flow, selection, and genetic drift. shapes patterns of spatial genetic variation. It is clear Since the inception of landscape genetics, there have that the tools developed in landscape genetics have been many calls for: (1) better communication among shaped a new paradigm for conducting empirical popu- spatial statisticians, landscape ecologists, and population lation genetics studies; although population genetics geneticists (Storfer et al. 2007; Balkenhol et al. 2009a); theory itself remains largely unchanged, the majority (2) more rigorous hypothesis testing (Storfer et al. 2007, of empirical studies of spatial genetic structure now 2010; Cushman & Landguth 2010; Segelbacher et al. include spatially explicit tests of landscape influences 2010; Manel & Holderegger 2013); (3) increased con- on gene flow.
    [Show full text]
  • Cancer Genomics Terminology
    Cancer Genomics Terminology Acquired Susceptibility Mutation: A mutation in a gene that occurs after birth from a carcinogenic insult. Allele: One of the variant forms of a gene. Different alleles may produce variation in inherited characteristics. Allele Heterogeneity: A phenotype that can be produced by different genetic mechanisms. Amino Acid: The building blocks of protein, for which DNA carries the genetic code. Analytical Sensitivity: The proportion of positive test results correctly reported by the laboratory among samples with a mutation(s) that the laboratory’s test is designed to detect. Analytic Specificity: The proportion of negative test results correctly reported among samples when no detectable mutation is present. Analytic Validity: A test’s ability to accurately and reliably measure the genotype of interest. Apoptosis: Programmed cell death. Ashkenazi: Individuals of Eastern European Jewish ancestry/decent (For example-Germany and Poland). Non-assortative mating occurred in this population. Association: When significant differences in allele frequencies are found between a disease and control population, the disease and allele are said to be in association. Assortative Mating: In population genetics, selective mating in a population between individuals that are genetically related or have similar characteristics. Autosome: Any chromosome other than a sex chromosome. Humans have 22 pairs numbered 1-22. Base Excision Repair Gene: The gene responsible for the removal of a damaged base and replacing it with the correct nucleotide. Base Pair: Two bases, which form a “rung on the DNA ladder”. Bases are the “letters” (Adenine, Thymine, Cytosine, Guanine) that spell out the genetic code. Normally adenine pairs with thymine and cytosine pairs with guanine.
    [Show full text]
  • Linkage & Genetic Mapping in Eukaryotes
    LinLinkkaaggee && GGeenneetticic MMaappppiningg inin EEuukkaarryyootteess CChh.. 66 1 LLIINNKKAAGGEE AANNDD CCRROOSSSSIINNGG OOVVEERR ! IInn eeuukkaarryyoottiicc ssppeecciieess,, eeaacchh lliinneeaarr cchhrroommoossoommee ccoonnttaaiinnss aa lloonngg ppiieeccee ooff DDNNAA – A typical chromosome contains many hundred or even a few thousand different genes ! TThhee tteerrmm lliinnkkaaggee hhaass ttwwoo rreellaatteedd mmeeaanniinnggss – 1. Two or more genes can be located on the same chromosome – 2. Genes that are close together tend to be transmitted as a unit Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display 2 LinkageLinkage GroupsGroups ! Chromosomes are called linkage groups – They contain a group of genes that are linked together ! The number of linkage groups is the number of types of chromosomes of the species – For example, in humans " 22 autosomal linkage groups " An X chromosome linkage group " A Y chromosome linkage group ! Genes that are far apart on the same chromosome can independently assort from each other – This is due to crossing-over or recombination Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display 3 LLiinnkkaaggee aanndd RRecombinationecombination Genes nearby on the same chromosome tend to stay together during the formation of gametes; this is linkage. The breakage of the chromosome, the separation of the genes, and the exchange of genes between chromatids is known as recombination. (we call it crossing over) 4 IndependentIndependent assortment:assortment:
    [Show full text]
  • Genetic Distance
    NBER WORKING PAPER SERIES THE DIFFUSION OF DEVELOPMENT Enrico Spolaore Romain Wacziarg Working Paper 12153 http://www.nber.org/papers/w12153 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 March 2006 Spolaore: Department of Economics, Tufts University, 315 Braker Hall, 8 Upper Campus Rd., Medford, MA 02155-6722, [email protected]. Wacziarg: Graduate School of Business, Stanford University, Stanford CA 94305-5015, USA, [email protected]. We thank Alberto Alesina, Robert Barro, Francesco Caselli, Steven Durlauf, Jim Fearon, Oded Galor, Yannis Ioannides, Pete Klenow, Andros Kourtellos, Ed Kutsoati, Peter Lorentzen, Paolo Mauro, Sharun Mukand, Gérard Roland, Antonio Spilimbergo, Chih Ming Tan, David Weil, Bruce Weinberg, Ivo Welch, and seminar participants at Boston College, Fundação Getulio Vargas, Harvard University, the IMF, INSEAD, London Business School, Northwestern University, Stanford University, Tufts University, UC Berkeley, UC San Diego, the University of British Columbia, the University of Connecticut and the University of Wisconsin-Madison for comments. We also thank Robert Barro and Jim Fearon for providing some data. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. ©2006 by Enrico Spolaore and Romain Wacziarg. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. The Diffusion of Development Enrico Spolaore and Romain Wacziarg NBER Working Paper No. 12153 March 2006 JEL No. O11, O57 ABSTRACT This paper studies the barriers to the diffusion of development across countries over the very long-run.
    [Show full text]
  • Using Landscape Genetics to Assess Population Connectivity in a Habitat Generalist
    University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2010 Using Landscape Genetics To Assess Population Connectivity In A Habitat Generalist Tyler Duncan Hether University of Central Florida Part of the Biology Commons, and the Natural Resources and Conservation Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Hether, Tyler Duncan, "Using Landscape Genetics To Assess Population Connectivity In A Habitat Generalist" (2010). Electronic Theses and Dissertations, 2004-2019. 1567. https://stars.library.ucf.edu/etd/1567 USING LANDSCAPE GENETICS TO ASSESS POPULATION CONNECTIVITY IN A HABITAT GENERALIST by TYLER DUNCAN HETHER B.S. University of Central Florida, 2006 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Biological Sciences in the College of Sciences at the University of Central Florida Orlando, Florida Summer Term 2010 Major Professor: Eric A. Hoffman © 2010 Tyler Hether ii ABSTRACT Understanding the nature of genetic variation in natural populations is an underlying theme of population genetics. In recent years population genetics has benefited from the incorporation of landscape and environmental data into pre-existing models of isolation by distance (IBD) to elucidate features influencing spatial genetic variation. Many of these landscape genetics studies have focused on populations separated by discrete barriers (e.g., mountain ridges) or species with specific habitat requirements (i.e., habitat specialists).
    [Show full text]