DOCSLIB.ORG

Using Genomics to Understand Population Demographics in the Context of Amphibian Conservation

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Using Genomics to Understand Population Demographics in the Context of Amphibian Conservation University of Kentucky UKnowledge Theses and Dissertations--Biology Biology 2017 USING GENOMICS TO UNDERSTAND POPULATION DEMOGRAPHICS IN THE CONTEXT OF AMPHIBIAN CONSERVATION Schyler O. Nunziata University of Kentucky, [email protected] Digital Object Identifier: https://doi.org/10.13023/ETD.2017.390 Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Nunziata, Schyler O., "USING GENOMICS TO UNDERSTAND POPULATION DEMOGRAPHICS IN THE CONTEXT OF AMPHIBIAN CONSERVATION" (2017). Theses and Dissertations--Biology. 49. https://uknowledge.uky.edu/biology_etds/49 This Doctoral Dissertation is brought to you for free and open access by the Biology at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Biology by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT: I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained needed written permission statement(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine) which will be submitted to UKnowledge as Additional File. I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and royalty-free license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known. I agree that the document mentioned above may be made available immediately for worldwide access unless an embargo applies. I retain all other ownership rights to the copyright of my work. I also retain the right to use in future works (such as articles or books) all or part of my work. I understand that I am free to register the copyright to my work. REVIEW, APPROVAL AND ACCEPTANCE The document mentioned above has been reviewed and accepted by the student’s advisor, on behalf of the advisory committee, and by the Director of Graduate Studies (DGS), on behalf of the program; we verify that this is the final, approved version of the student’s thesis including all changes required by the advisory committee. The undersigned agree to abide by the statements above. Schyler O. Nunziata, Student Dr. David W. Weisrock, Major Professor Dr. David F. Westneat, Director of Graduate Studies USING GENOMICS TO UNDERSTAND POPULATION DEMOGRAPHICS IN THE CONTEXT OF AMPHIBIAN CONSERVATION ________________________________________ DISSERTATION ________________________________________ A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the College of Arts and Sciences at the University of Kentucky By Schyler Olivia Nunziata Lexington, Kentucky Director: Dr. David Weisrock, Professor of Biology Lexington, Kentucky 2017 Copyright © Schyler Olivia Nunziata 2017 ABSTRACT OF DISSERTATION USING GENOMICS TO UNDERSTAND POPULATION DEMOGRAPHICS IN THE CONTEXT OF AMPHIBIAN CONSERVATION Understanding the demography of species over recent history (e.g., < 100 years) is critical in studies of ecology and evolution, but records of population history are rarely available. Large single nucleotide polymorphism datasets generated with restriction-site associated DNA sequencing (RADseq), in combination with demographic inference methods, are improving our ability to gain insights into the population history of both model and non-model species. However, to assess the performance of genetic methods it is important to compare their estimates of population history to known demography, in both simulation and empirical settings. Here, I used a simulation approach to examine the potential for RADseq datasets to accurately estimate effective population size (Ne) in Wright-Fisher populations over the course of stable and declining population trends, and distinguish stable from steadily declining populations over a contemporary time scale (20 generations). Overall, my results reveal that demographic inference using genome-wide data can be successfully applied to estimate Ne, and the detection of population-size declines. Next, I assess these methods in an empirical study from a wetland with 37 years of amphibian mark-recapture data to study the utility of genetically-based demographic inference on salamander species with documented population declines (Ambystoma talpoideum) and expansions (A. opacum). For both species, demographic model inference supported population size changes that corroborated mark-recapture data. To further validate these findings, I used individual-based population models of the pond-breeding salamander, Ambystoma opacum, with life-history parameters estimated from a long-term dataset, over a 50 year projection. My results demonstrate that genetically estimated Ne is positively correlated with census size in isolated and subdivided A. opacum populations. Finally, I investigated metapopulation patterns of genomic diversity in A. opacum and A. talpoideum and how migration may impact Ne estimation. I found strong patterns of subpopulation structuring, signatures of migration between subpopulations, and differences in Ne at the subpopulation level in both species. Overall, my findings suggest the ability of genomic data to reconstruct recent demographic changes, which can have important applications to conservation biology, and ultimately can help us elucidate the effects of environmental disturbances in the demography of endangered or declining species. KEYWORDS: demographic inference, temporal samples, genetic monitoring, coalescent, Ambystoma Schyler Olivia Nunziata June 2, 2017 USING GENOMICS TO UNDERSTAND POPULATION DEMOGRAPHICS IN THE CONTEXT OF AMPHIBIAN CONSERVATION By Schyler Olivia Nunziata David W. Weisrock, Ph.D. Director of Dissertation David F. Westneat, Ph.D. Director of Graduate Studies June 2, 2017 ACKNOWLEDGEMENTS I thank all of my committee members, Drs. Catherine Linnen, Philip Crowley, Stacey Lance, and Steven Price for advice. I would especially like to thank my advisor, Dr. David Weisrock, for guidance throughout my graduate career. I thank David Scott for his expert advice on all things Ambystoma. I would like to thank the numerous people who have assisted with data collection, entry, and management of the Rainbow Bay study. I thank the University of Kentucky Center for Computational Sciences and the Lipscomb High Performance Computing Cluster for access to computing resources, and Vikram Gazula for help with script optimization. For help with lab and bioinformatic research, I want to thank Paul Hime, Scott Hotaling, and Robin Bagley. I thank all members of the combined Weisrock and Linnen Superlab. I would like to thank all of the organizations that provided funding, including: University of Kentucky (UKY) Department of Biology Mini-Ribble Grant, UKY College of Arts and Sciences Summer Research Fellowship, Kentucky NSF EPSCoR, SSAR Grants in Herpetology, Kentucky Academy of Sciences Marcia Athey Fund, and the National Science Foundation. iii TABLE OF CONTENTS Acknowledgement ......................................................................................................................... iii List of Tables ................................................................................................................................ vii List of Figures ................................................................................................................................ ix Chapter One: General Introduction Introduction ............................................................................................................................... 10 Estimation of effective size ....................................................................................................... 12 LD-based estimations of recent demographic history ............................................................... 12 Coalescent-based estimations of recent demographic history................................................... 14 Major differences between LD and coalescent Ne.................................................................... 16 Demographic inference in complex and dynamic systems ....................................................... 17 Case Studies with a focus on amphibians--Chapters 2 through 5 ............................................. 18 Chapter Two: Estimation of contemporary effective population size and population declines using RAD sequence data Abstract ..................................................................................................................................... 22 Introduction ............................................................................................................................... 23 Methods ..................................................................................................................................... 26 Data simulation ...................................................................................................................... 26 In silico RADseq mutations and data filtering ...................................................................... 27 Ne estimation and demographic inference ............................................................................. 29 Accuracy assessments ...........................................................................................................
Load more

Recommended publications
  • Knowledge Status and Sampling Strategies to Maximize Cost-Benefit
    www.nature.com/scientificreports OPEN Knowledge status and sampling strategies to maximize cost- beneft ratio of studies in landscape genomics of wild plants Alesandro Souza Santos* & Fernanda Amato Gaiotto To avoid local extinction due to the changes in their natural ecosystems, introduced by anthropogenic activities, species undergo local adaptation. Landscape genomics approach, through genome– environment association studies, has helped evaluate the local adaptation in natural populations. Landscape genomics, is still a developing discipline, requiring refnement of guidelines in sampling design, especially for studies conducted in the backdrop of stark socioeconomic realities of the rainforest ecologies, which are global biodiversity hotspots. In this study we aimed to devise strategies to improve the cost-beneft ratio of landscape genomics studies by surveying sampling designs and genome sequencing strategies used in existing studies. We conducted meta-analyses to evaluate the importance of sampling designs, in terms of (i) number of populations sampled, (ii) number of individuals sampled per population, (iii) total number of individuals sampled, and (iv) number of SNPs used in diferent studies, in discerning the molecular mechanisms underlying local adaptation of wild plant species. Using the linear mixed efects model, we demonstrated that the total number of individuals sampled and the number of SNPs used, signifcantly infuenced the detection of loci underlying the local adaptation. Thus, based on our fndings, in order to optimize the cost-beneft ratio of landscape genomics studies, we suggest focusing on increasing the total number of individuals sampled and using a targeted (e.g. sequencing capture) Pool-Seq approach and/or a random (e.g. RAD- Seq) Pool-Seq approach to detect SNPs and identify SNPs under selection for a given environmental cline.
    [Show full text]
  • The Climatic and Genetic Heritage of Italian Goat Breeds with Genomic
    www.nature.com/scientificreports OPEN The climatic and genetic heritage of Italian goat breeds with genomic SNP data Matteo Cortellari 1,16, Mario Barbato2,16, Andrea Talenti1,3*, Arianna Bionda1, Antonello Carta4, Roberta Ciampolini5, Elena Ciani6, Alessandra Crisà7, Stefano Frattini1, Emiliano Lasagna8, Donata Marletta9, Salvatore Mastrangelo10, Alessio Negro1, Ettore Randi11, Francesca M. Sarti8, Stefano Sartore12, Dominga Soglia12, Luigi Liotta13, Alessandra Stella14, Paolo Ajmone‑Marsan2, Fabio Pilla15, Licia Colli2 & Paola Crepaldi1 Local adaptation of animals to the environment can abruptly become a burden when faced with rapid climatic changes such as those foreseen for the Italian peninsula over the next 70 years. Our study investigates the genetic structure of the Italian goat populations and links it with the environment and how genetics might evolve over the next 50 years. We used one of the largest national datasets including > 1000 goats from 33 populations across the Italian peninsula collected by the Italian Goat Consortium and genotyped with over 50 k markers. Our results showed that Italian goats can be discriminated in three groups refective of the Italian geography and its geo‑political situation preceding the country unifcation around two centuries ago. We leveraged the remarkable genetic and geographical diversity of the Italian goat populations and performed landscape genomics analysis to disentangle the relationship between genotype and environment, fnding 64 SNPs intercepting genomic regions linked to growth, circadian rhythm, fertility, and infammatory response. Lastly, we calculated the hypothetical future genotypic frequencies of the most relevant SNPs identifed through landscape genomics to evaluate their long‑term efect on the genetic structure of the Italian goat populations.
    [Show full text]
  • Title: the Genomic Consequences of Hybridization Authors
    Title: The genomic consequences of hybridization Authors: Benjamin M Moran1,2*+, Cheyenne Payne1,2*+, Quinn Langdon1, Daniel L Powell1,2, Yaniv Brandvain3, Molly Schumer1,2,4+ Affiliations: 1Department of Biology, Stanford University, Stanford, CA, USA 2Centro de Investigaciones Científicas de las Huastecas “Aguazarca”, A.C., Calnali, Hidalgo, Mexico 3Department of Ecology, Evolution & Behavior and Plant and Microbial Biology, University of Minnesota, St. Paul, MN, USA 4Hanna H. Gray Fellow, Howard Hughes Medical Institute, Stanford, CA, USA *Contributed equally to this work +Correspondence: [email protected], [email protected], [email protected] Abstract In the past decade, advances in genome sequencing have allowed researchers to uncover the history of hybridization in diverse groups of species, including our own. Although the field has made impressive progress in documenting the extent of natural hybridization, both historical and recent, there are still many unanswered questions about its genetic and evolutionary consequences. Recent work has suggested that the outcomes of hybridization in the genome may be in part predictable, but many open questions about the nature of selection on hybrids and the biological variables that shape such selection have hampered progress in this area. We discuss what is known about the mechanisms that drive changes in ancestry in the genome after hybridization, highlight major unresolved questions, and discuss their implications for the predictability of genome evolution after hybridization. Introduction Recent evidence has shown that hybridization between species is common. Hybridization is widespread across the tree of life, spanning both ancient and recent timescales and a broad range of divergence levels between taxa [1–10]. This appreciation of the prevalence of hybridization has renewed interest among researchers in understanding its consequences.
    [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]
  • Recent Advances in Conservation and Population Genomics Data Analysis
    Received: 20 February 2018 | Revised: 8 May 2018 | Accepted: 21 May 2018 DOI: 10.1111/eva.12659 MEETING REPORT Recent advances in conservation and population genomics data analysis Sarah Hendricks1 | Eric C. Anderson2,3 | Tiago Antao4 | Louis Bernatchez5 | Brenna R. Forester6 | Brittany Garner7,8 | Brian K. Hand7 | Paul A. Hohenlohe1 | Martin Kardos7 | Ben Koop9 | Arun Sethuraman10 | Robin S. Waples11 | Gordon Luikart7,8 1Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, Idaho 2Fisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Santa Cruz, California 3University of California, Santa Cruz, California 4Division of Biological Sciences, University of Montana, Missoula, Montana 5Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada 6Department of Biology, Colorado State University, Fort Collins, Colorado 7Flathead Lake Biological Station, Montana Conservation Genomics Laboratory, Division of Biological Science, University of Montana, Missoula, Montana 8Wildlife Program, Fish and Wildlife Genomics Group, College of Forestry and Conservation, University of Montana, Missoula, Montana 9Department of Biology, Centre for Biomedical Research, University of Victoria, Victoria, British Columbia, Canada 10Department of Biological Sciences, California State University San Marcos, San Marcos, California 11NOAA Fisheries, Northwest Fisheries Science Center,
    [Show full text]
  • Recent Advances in Conservation and Population Genomics Data Analysis
    Received: 20 February 2018 | Revised: 8 May 2018 | Accepted: 21 May 2018 DOI: 10.1111/eva.12659 MEETING REPORT Recent advances in conservation and population genomics data analysis Sarah Hendricks1 | Eric C. Anderson2,3 | Tiago Antao4 | Louis Bernatchez5 | Brenna R. Forester6 | Brittany Garner7,8 | Brian K. Hand7 | Paul A. Hohenlohe1 | Martin Kardos7 | Ben Koop9 | Arun Sethuraman10 | Robin S. Waples11 | Gordon Luikart7,8 1Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, Idaho 2Fisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Santa Cruz, California 3University of California, Santa Cruz, California 4Division of Biological Sciences, University of Montana, Missoula, Montana 5Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada 6Department of Biology, Colorado State University, Fort Collins, Colorado 7Flathead Lake Biological Station, Montana Conservation Genomics Laboratory, Division of Biological Science, University of Montana, Missoula, Montana 8Wildlife Program, Fish and Wildlife Genomics Group, College of Forestry and Conservation, University of Montana, Missoula, Montana 9Department of Biology, Centre for Biomedical Research, University of Victoria, Victoria, British Columbia, Canada 10Department of Biological Sciences, California State University San Marcos, San Marcos, California 11NOAA Fisheries, Northwest Fisheries Science Center,
    [Show full text]
  • Ten Years of Landscape Genetics
    TREE-1709; No. of Pages 8 Review Ten years of landscape genetics 1,2 3,4 Ste´ phanie Manel and Rolf Holderegger 1 Laboratoire LPED ‘‘Population Environnement, De´ veloppement’’ - UMR151 - Aix Marseille University - IRD Marseille, France 2 UMR Botanique et BioinforMatique de l’Architecture des Plantes, CIRAD, TA A51/PS2 34398 Montpellier Cedex 5, France 3 WSL Swiss Federal Research Institute, Zu¨ rcherstrasse 111, CH-8903 Birmensdorf, Switzerland 4 Institute of Integrative Biology, ETH Zu¨ rich, Universita¨ tsstrasse 16, CH-8092 Zu¨ rich, Switzerland Landscape genetics is now ten years old. It has stimu- discipline with a particular focus on potential applications lated research into the effect of landscapes on evolution- in terms of adaptation to global change and the conserva- ary processes. This review describes the main topics that tion of natural resources. have contributed most significantly to the progress of landscape genetics, such as conceptual and methodo- Glossary logical developments in spatial and temporal patterns of Adaptation: the process by which a population or a species globally or locally gene flow, seascape genetics, and landscape genomics. adapts to its environment. Adaptation refers to both the current state of being We then suggest perspectives for the future, investigat- adapted and the dynamic evolutionary process that leads to adaptation. Adaptive genetic variation: variation at loci that are under selection. ing what the field will contribute to the assessment of Covariance structure: incorporating a matrix of pairwise covariances of data into global change and conservation in general and to the a model allows researchers to statistically account for the autocorrelation of data.
    [Show full text]
  • Sampling Strategy Optimization to Increase Statistical Power In
    bioRxiv preprint doi: https://doi.org/10.1101/603829; this version posted August 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 1 Sampling strategy optimization to increase statistical power in 2 landscape genomics: a simulation-based approach 3 4 Running title: Sampling strategy in landscape genomics 5 6 7 Oliver Selmoni1, Elia Vajana1, Annie Guillaume1, Estelle Rochat1, Stéphane Joost1 8 9 1Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), 10 Ecole PolytechniQue Fédérale de Lausanne (EPFL), Lausanne, Switzerland 11 12 1 bioRxiv preprint doi: https://doi.org/10.1101/603829; this version posted August 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 13 14 Abstract (250 words max) 15 An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. 16 The implementation of this approach reQuires the sampling phase to consider the compleXity of environmental settings and the 17 burden of logistic constraints. These important aspects are often underestimated in the literature dedicated to sampling 18 strategies. 19 In this study, we computed simulated genomic datasets to run against actual environmental data in order to trial landscape 20 genomics eXperiments under distinct sampling strategies.
    [Show full text]
  • The Population Genomic Signature of Environmental Selection in the Widespread Insect-Pollinated Tree Species Frangula Alnus at Different Geographical Scales
    Heredity (2015) 115, 415–425 & 2015 Macmillan Publishers Limited All rights reserved 0018-067X/15 www.nature.com/hdy ORIGINAL ARTICLE The population genomic signature of environmental selection in the widespread insect-pollinated tree species Frangula alnus at different geographical scales H De Kort1, K Vandepitte1, J Mergeay2, KV Mijnsbrugge2,3 and O Honnay1 The evaluation of the molecular signatures of selection in species lacking an available closely related reference genome remains challenging, yet it may provide valuable fundamental insights into the capacity of populations to respond to environmental cues. We screened 25 native populations of the tree species Frangula alnus subsp. alnus (Rhamnaceae), covering three different geographical scales, for 183 annotated single-nucleotide polymorphisms (SNPs). Standard population genomic outlier screens were combined with individual-based and multivariate landscape genomic approaches to examine the strength of selection relative to neutral processes in shaping genomic variation, and to identify the main environmental agents driving selection. Our results demonstrate a more distinct signature of selection with increasing geographical distance, as indicated by the proportion of SNPs (i) showing exceptional patterns of genetic diversity and differentiation (outliers) and (ii) associated with climate. Both temperature and precipitation have an important role as selective agents in shaping adaptive genomic differentiation in F. alnus subsp. alnus, although their relative importance differed among spatial scales. At the ‘intermediate’ and ‘regional’ scales, where limited genetic clustering and high population diversity were observed, some indications of natural selection may suggest a major role for gene flow in safeguarding adaptability. High genetic diversity at loci under selection in particular, indicated considerable adaptive potential, which may nevertheless be compromised by the combined effects of climate change and habitat fragmentation.
    [Show full text]
  • Landscape Genomics of a Widely Distributed Snake, Dolichophis Caspius (Gmelin, 1789) Across Eastern Europe and Western Asia
    G C A T T A C G G C A T genes Article Landscape Genomics of a Widely Distributed Snake, Dolichophis caspius (Gmelin, 1789) across Eastern Europe and Western Asia Sarita Mahtani-Williams 1,2,3, William Fulton 1,2 , Amelie Desvars-Larrive 1,4,5 , Sara Lado 1, Jean Pierre Elbers 1,Bálint Halpern 6,Dávid Herczeg 7 , Gergely Babocsay 6,8, Boris Lauš 9, Zoltán Tamás Nagy 10 , Daniel Jablonski 11 , Oleg Kukushkin 12,13, 2 14,15, , 1, , Pablo Orozco-terWengel , Judit Vörös * y and Pamela Anna Burger * y 1 Research Institute of Wildlife Ecology, Vetmeduni Vienna, Savoyenstrasse 1, A-1160 Vienna, Austria; [email protected] (S.M.-W.); [email protected] (W.F.); [email protected] (A.D.-L.); [email protected] (S.L.); [email protected] (J.P.E.) 2 Cardiff School of Biosciences, Cardiff University, The Sir Martin Evans Building, Museum Ave, Cardiff CF103AX, UK; orozco-terwengelpa@cardiff.ac.uk 3 Fundación Charles Darwin, Avenida Charles Darwin s/n, Casilla 200144, Puerto Ayora EC-200350, Ecuador 4 Institute of Food Safety, Food Technology and Veterinary Public Health, Vetmeduni Vienna, Veterinaerplatz 1, A-1210 Vienna, Austria 5 Complexity Science Hub Vienna, Josefstädter Straße 39, A-1080 Vienna, Austria 6 MME Birdlife Hungary, Költ˝outca 21., H-1121 Budapest, Hungary; [email protected] (B.H.); [email protected] (G.B.) 7 Lendület Evolutionary Ecology Research Group, Centre for Agricultural Research, Plant Protection Institute, Herman Ottó út 15., H-1022 Budapest, Hungary; [email protected] 8 Mátra Museum of the Hungarian Natural History Museum, Kossuth Lajos utca 40., H-3200 Gyöngyös, Hungary 9 Association HYLA, Lipocac I., No.
    [Show full text]
  • A Practical Guide to Environmental Association Analysis in Landscape Genomics
    Molecular Ecology (2015) 24, 4348–4370 doi: 10.1111/mec.13322 INVITED REVIEWS AND SYNTHESES A practical guide to environmental association analysis in landscape genomics CHRISTIAN RELLSTAB,* FELIX GUGERLI,* ANDREW J. ECKERT,† ANGELA M. HANCOCK‡ and ROLF HOLDEREGGER*§ *WSL Swiss Federal Research Institute, Zurcherstrasse€ 111, 8903 Birmensdorf, Switzerland, †Department of Biology, Virginia Commonwealth University, Richmond, VA 23284, USA, ‡Faculty of Molecular Biology, Max F. Perutz Laboratories and University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria, §ETH Zurich,€ Institute of Integrative Biology, Universit€atstrasse 16, 8092 Zürich, Switzerland Abstract Landscape genomics is an emerging research field that aims to identify the environ- mental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describ- ing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for con- ducting environmental association analysis including categorical tests, logistic regres- sions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorpo- rating neutral genetic structure in the analysis.
    [Show full text]
  • Quercus Conservation Genetics and Genomics: Past, Present, and Future
    Review Quercus Conservation Genetics and Genomics: Past, Present, and Future Janet R. Backs * and Mary V. Ashley Department of Biological Sciences, University of Illinois at Chicago, Chicago, IL 60607, USA; [email protected] * Correspondence: [email protected] Abstract: Quercus species (oaks) have been an integral part of the landscape in the northern hemi- sphere for millions of years. Their ability to adapt and spread across different environments and their contributions to many ecosystem services is well documented. Human activity has placed many oak species in peril by eliminating or adversely modifying habitats through exploitative land usage and by practices that have exacerbated climate change. The goal of this review is to compile a list of oak species of conservation concern, evaluate the genetic data that is available for these species, and to highlight the gaps that exist. We compiled a list of 124 Oaks of Concern based on the Red List of Oaks 2020 and the Conservation Gap Analysis for Native U.S. Oaks and their evaluations of each species. Of these, 57% have been the subject of some genetic analysis, but for most threatened species (72%), the only genetic analysis was done as part of a phylogenetic study. While nearly half (49%) of published genetic studies involved population genetic analysis, only 16 species of concern (13%) have been the subject of these studies. This is a critical gap considering that analysis of intraspecific genetic variability and genetic structure are essential for designing conservation management strategies. We review the published population genetic studies to highlight their application to conservation. Finally, we discuss future directions in Quercus conservation genetics and genomics.
    [Show full text]