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Population Genetics Of Taxus Cuspidata Sieb.et Zucc Based On RADseq

Posted on:2020-05-29Degree:MasterType:Thesis
Country:ChinaCandidate:Y YanFull Text:PDF
GTID:2393330575497474Subject:Forestry
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Taxus cuspidata Sieb.et Zucc.is widely distributed in north-east China,Russia,North Korea and Japan.However,due to severe habitat fragmentation the population size of T.cuspidata is extremely small and considered as endangered species.At present,the research on T.cuspidata is mainly concentrated on the chemical composition,physiology,ecology and breeding of the species,while the research on the genetic mechanism of its endangerment is limited.In the thesis,the population genetics and landscape genomics analyses of T.cuspidata were carried out by Restriction site-associated DNA sequencing(RADseq),also known as Reduced-representation genome sequencing(RRGS).Firstly,high quality T.cuspidata DNA extracted from 179 individuals of 26 populations was digested with restriction enzymes TaqaI and MseI and sequenced by Illumina HiSeqTM.After quality control and filter of raw data we obtained 31,343 single nucleotide polymorphism(SNP)loci.Secondly,outliers were detected by two methods based on FST(BAYESCAN)and allele frequence associated with environmental gradient(LFMM).Loci influenced by directional selection detected by BAYESCAN were used as outlier SNP datasets for population genetic analyses.The genetics diversity of the species is high while no obvious genetic structure among all populations and natural populations.Gradient Forests(GF)was used to analyze the response pattern of genetic variation with environmental gradients of T.cuspidata.The results showed that geographical factors and the mean temperature of coldest quarter(bio11)is the most explained factors for the genetic variation.This thesis revealed the endangerment mechanism of T.cuspidata and in situ conservation strategy were recommended.
Keywords/Search Tags:Taxus cuspidata, single nucleotide polymorphism, population genetics, Restriction site-associated DNA sequencing, landscape genomics
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