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DOTTORATO&DI&RICERCA&IN& Estimation)Of)Adaptive ! ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! !!!!!!!!!!!!!!!!!!!!!!!!!! ! ! DOTTORATO&DI&RICERCA&IN& &&&&&&&&Scienze&e&Technologie&Vegetali,&Microbiche&e&Genetiche& & & & & & &&&&&&&CICLO XXVII COORDINATORE Prof. Aniello Scala Estimation)of)adaptive)genetic)variation)in)Norway)) spruce)(Picea)abies)(L.))Karst))to)climate)changeEstimation of adaptive genetic variation in ) ) Norway spruce across European Alps ) ~ project update ~ )))))))PhD)candidate:)Irina)Calic& & PhD candidate: Irina Calic & & & Co-authors: Pedro J. Martinez-Garcia, Markus Neteler, Lorenzo Bonosi, Filippo Bussotti & & & & &&&&December,&2014& PI: David B. Neale & Declaration I hereby declare that this submission is my own work and that, to the best of my knowledge and belief, it contains no material previously published or written by another person nor material which to a substantial extent has been accepted for the award of any other degree or diploma of the university or other institute of higher learning, except where due acknowledgment has been made in the text. December 31th, 2014 Nome Cognome del dottorando A copy of the thesis will be available at: www.dispaa.unifi.it Dichiarazione Con la presente affermo che questa tesi è frutto del mio lavoro e che, per quanto io ne sia a conoscenza, non contiene materiale precedentemente pubblicato o scritto da un'altra persona né materiale che è stato utilizzato per l’ottenimento di qualunque altro titolo o diploma dell'Università o altro istituto di apprendimento, a eccezione del caso in cui ciò venga riconosciuto nel testo. 31 dicembre 2014 Nome Cognome del dottorando Una copia della tesi sarà disponibile presso: www.dispaa.unifi.it Contents Riassunto -------------------------------------------------------------------------------------------------------------------------- i Summary -------------------------------------------------------------------------------------------------------------------------- ii Lavori correlati alla Tesi - Papers related to the Thesis ------------------------------------------------------------- iii List of Figures ------------------------------------------------------------------------------------------------------------------- iv List of Tables --------------------------------------------------------------------------------------------------------------------- v Acknowledgment -------------------------------------------------------------------------------------------------------------- vi 1. INTRODUCTION ------------------------------------------------------------------------------------------------------------- 1 1.1. About Conifers ------------------------------------------------------------------------------------------------------------ 1 1.2 Pinaceae (The Pinus family) --------------------------------------------------------------------------------------------- 2 1.3 Norway spruce natural distribution ----------------------------------------------------------------------------------- 2 1.4 Ecology of Norway spruce ----------------------------------------------------------------------------------------------- 3 1.5 Climate change and its impact on Conifers ------------------------------------------------------------------------- 4 1.6 Phenomena of adaptation ---------------------------------------------------------------------------------------------- 7 1.7 Adaptive genetic variation in Conifers with emphasis on Norway spruce (common garden trials) --------------------------------------------------------------------------------------------------- 9 1.8 Genotype versus environment in Conifers with emphasis on Norway spruce --------------------------- 10 1.9 Gene groups associated to environment among Conifers ---------------------------------------------------- 12 2. RESEARCH OBJECTIVES -------------------------------------------------------------------------------------------------- 15 3. MATERIAL AND METHODS --------------------------------------------------------------------------------------------- 16 3.1 Sample collection -------------------------------------------------------------------------------------------------------- 16 3.2 Illumina 384 GoldenGate chip design ------------------------------------------------------------------------------ 17 3.3 Germination of seeds --------------------------------------------------------------------------------------------------- 20 3.4 DNA isolation from needles and megagametophytes ---------------------------------------------------------- 21 3.5 Environmental dataset ------------------------------------------------------------------------------------------------- 22 3. 5.1 Aridity index (AI) calculation ------------------------------------------------------------------------------ 24 3. 5.2 Principal component analyses ---------------------------------------------------------------------------- 25 3.6 Genotyping data Analyses --------------------------------------------------------------------------------------------- 27 3.7 Basic diversity statistics of genotype data ------------------------------------------------------------------------ 28 3.8 Population structure analyses ---------------------------------------------------------------------------------------- 30 3.9 Outlier detection methods -------------------------------------------------------------------------------------------- 31 3.9.1 BayeScan outlier detection method ------------------------------------------------------------------- 31 3.9.2 Bayesian linear mixed model (BayEnv) ---------------------------------------------------------------- 32 3.9.3 Spatial analyses detection (Samβada) ----------------------------------------------------------------- 33 4. RESULTS --------------------------------------------------------------------------------------------------------------------- 36 4.1 Climatic data estimation within mapping population ---------------------------------------------------------- 36 4.2 Analyses of 384 Illumina GoldenGate genotyping data -------------------------------------------------------- 43 4.3 Basic diversity statistics on genotype data ------------------------------------------------------------------------ 46 4.4 Population structure estimation ------------------------------------------------------------------------------------- 48 4.5 BayeScan outlier detection method -------------------------------------------------------------------------------- 52 4.6 Environmental association analyses: Bayesian linear mixed model detection (BayEnv) -------------- 54 4.7 Spatial analyses detection (Samβada) ------------------------------------------------------------------------------ 61 5. DISCUSSION ---------------------------------------------------------------------------------------------------------------- 62 5.1 The thesis summary ----------------------------------------------------------------------------------------------------- 62 5.2 Limitations of the current study ------------------------------------------------------------------------------------- 64 5.3 Future perspective of the study ------------------------------------------------------------------------------------- 68 REFERENCES ------------------------------------------------------------------------------------------------------------------- 69 SUPPLEMENTS ---------------------------------------------------------------------------------------------------------------- 78 Supplement 1: List of mother trees sampled across the European Alps with geo-reference data provided ------------------------------------------------------------------------------------------ 77 Supplement 2: List of SNPs submitted to 384 Illumina GoldenGate genotyping assay --------------------- 86 Supplement 3. Assignment of 392 individuals based on the geo-reference data ---------------------------- 98 Supplement 4. List of SNPs failed during 384 Illumina GoldenGate genotyping assay --------------------- 100 Supplement 5. Basic diversity statistics indices on genotyping matrix on polymorphic SNPs ------------------------------------------------------------------------------------------------------- 103 Supplement 6. (A) Barplot when K=6 for original order for 394 individuals assuming existence of panmixia ------------------------------------------------------------------------------------------------------ 110 Supplement 7. Fst coefficient estimated as the posterior mean using model averaging (BayeScan) ------------------------------------------------------------------------------------------------------ 112 Supplement 8: Samβada results for univariate models ------------------------------------------------------------ 118 Parole chiave: abete rosso, adattamento, genotipizzazione 384 SNPs, analisi degli outiliers Riassunto Scopo: L'obiettivo principale di questo studio è stato quello di investigare sul potenziale genetico adattativo in abete rosso (Picea abies (L.) Karst) nell’arco alpino. Metodi e Risultati: In questo studio, è stato adottato un approccio genomico sul polimorfismo del nucleotide singolo 384 (SNP), secondo il test di genotipizzazione Illumina GoldenGate, per investigare la variabilità genetica e la capacità adattativa in una popolazione di 392 individui di abete rosso campionati nell’arco alpino e georeferenziati. I dati ambientali sono stati ottenuti tramite i dataset WORLDCLIM e IGP MODIS LST satellitare. Per l’analisi statistica multivariata (componenti principali –PCA) è stata applicata su tutte le serie di dati ambientali per ridurre la dimensionalità del campione ed estrarre la più alta
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