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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 董致韡(Chih-Wei Tung) | |
dc.contributor.author | Chia-Hui Chou | en |
dc.contributor.author | 周家卉 | zh_TW |
dc.date.accessioned | 2021-06-08T02:39:12Z | - |
dc.date.copyright | 2020-11-13 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-10-27 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/20043 | - |
dc.description.abstract | 臺灣本土栽種小麥品種主要為已育成超過三十年的台中選2號,在近年氣候變遷及市場需求改變下,亟需新品種以因應現今頻繁發生的極端天氣現象以及多元的加工用途。然而臺灣目前對小麥的育種投入及遺傳研究較為缺乏,因此本研究針對臺中區農業改良場所引種之小麥種原進行遺傳分析及外表型評估,並進一步探勘與重要農藝性狀緊密連鎖的分子標誌。 此種原族群包含39個四倍體杜蘭小麥(Triticum turgidum ssp. durum),60個六倍體斯佩耳特小麥(T. aestivum ssp. spelta),以及765個六倍體麵包小麥(T. aestivum ssp. aestivum)。首先我們利用小麥90K單核苷酸多型性之微陣列晶片進行基因型分型,經過次要等位基因頻率與缺值率的篩選後,將基因型資料用於探勘族群結構與評估親緣關係。主成分分析的結果偵測到三個明顯分群,可分別對應杜蘭小麥、斯佩耳特小麥,以及麵包小麥,另有一些個體則是散布於不同分群之間,我們進一步探勘麵包小麥的族群結構並發現其族群結構與品系的起源有關;而祖源分析與親緣關係樹的結果亦與主成分分析的結果相互呼應。 另外我們也從種原當中分別挑選211及132個麵包小麥品系,於兩次實驗中調查其抽穗期、株高、穗長,以及穗上發芽耐受性等重要農藝性狀,並結合基因型資料進行全基因體關聯性分析,在不同染色體片段上偵測到許多與性狀顯著相關的分子標誌。其中,部分分子標誌則是位於前人研究所偵測到的數量性狀基因座或是已知基因附近,例如利用抽穗期性狀在染色體5A上所偵測到的訊號與Vrn-A1基因位於鄰近區域。 本研究探勘與性狀顯著相關的分子標誌將可應用於未來分子標誌輔助選種,以進一步提升小麥的品質與產量。 | zh_TW |
dc.description.abstract | The most widely grown wheat variety in Taiwan is “Taichung Sel. 2”, which was released over three decades ago. Climate change and shifting market demand have led to the urgent need for new varieties that are tolerant of extreme weather events and suitable for versatile end uses. However, the breeding resources and genetic studies in wheat are limited in Taiwan. Therefore, the objective of the study was to characterize the population structure of an introduced wheat germplasm and identify SNP markers associated with agronomic traits. An introduced wheat diversity panel from the Taichung District Agricultural Research and Extension Station, including 39 durum wheat (Triticum turgidum ssp. durum), 60 spelt wheat (T. aestivum ssp. spelta), and 765 bread wheat accessions (T. aestivum ssp. aestivum), was genotyped using 90K single nucleotide polymorphism (SNP) array. After filtering for minor allele frequency and missing rate, the genotypic data were used to characterize the population structure. The results from principal component analysis revealed three distinct clusters which corresponded to durum wheat, spelt wheat, and bread wheat, while some individuals were admixed among groups, in concordance with the results of ancestry analysis and the phylogenetic trees. We further found that the population structure of bread wheat group was related to the origin of accessions. Two subsets containing 211 and 132 varieties were evaluated for traits such as plant height, days to heading, spike length and resistance to preharvest sprouting. Phenotypic data together with genotypic data were used for genome-wide association studies (GWAS) to identify markers significantly associated with quantitative trait loci (QTL) underlying these traits. Significant markers were detected across the wheat genome. We also found SNPs adjacent to known QTL and cloned genes controlling the traits we investigated. For example, a cluster of SNPs on chromosome 5A was located near the Vrn-A1 gene for days to heading. Our study provides valuable information that could be used in marker-assisted selection for improving wheat yield and quality. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T02:39:12Z (GMT). No. of bitstreams: 1 U0001-2710202011131600.pdf: 19599490 bytes, checksum: b66ced2ce8d038329081e59b9f469482 (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 誌謝 I 摘要 II Abstract III Table of Content V Index of Figures VII Index of Tables X Introduction 1 Materials and Methods 5 Plant material and SNP array hybridization 5 Assign physical position of iSelect 90K SNP markers 5 Genotyping of wheat accessions using Illumina iSelect 90K SNP arrays 6 Principal component analysis (PCA) and phylogenetic tree 7 Model-based clustering analysis and genetic diversity index 7 Genotyping-by-sequencing (GBS) and SNP calling 8 Linkage disequilibrium (LD) analysis 8 Phenotypic evaluation 9 Genome-wide association studies 10 Kompetitive Allele-Specific PCR (KASP) assay 11 Results 12 Physical position of Illumina iSelect wheat 90K markers 12 SNP clustering and SNP genotyping of a wheat diversity panel 14 Genotyping-by-sequencing (GBS) 16 Population structure of wheat species 17 Linkage disequilibrium of wheat species 20 GWAS to identify loci associated with agronomic traits 21 1. Phenotypic variation 21 2. Marker-trait association identified in E1 experiment 22 3. Marker-trait association identified in E2 experiment 24 KASP assay 25 Discussion 28 Resolving physical positions of 90K markers in updated IWGSC RefSeq v2.0 28 SNP clustering, genotype calling, and validation of 90K markers 28 Population structure of the diversity panel and bread wheat accessions 30 Linkage disequilibrium in wheat species 31 Phenotypic variation of a diverse wheat panel 32 Marker-trait associations for agronomic traits 34 Reference 36 Figures 51 Tables 81 | |
dc.language.iso | en | |
dc.title | 探勘小麥引種種原之族群結構及全基因體關聯性分析 | zh_TW |
dc.title | Characterization of the Population Structure and Genome-Wide Association Study of Introduced Wheat Germplasm | en |
dc.type | Thesis | |
dc.date.schoolyear | 109-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 陳凱儀(Kai-Yi Chen),黃永芬(Yung-Fen Huang),林耀正(Yao-Cheng Lin) | |
dc.subject.keyword | 小麥,小麥 90K 晶片,族群結構,全基因體關聯性分析,株高,穗長,抽穗期, | zh_TW |
dc.subject.keyword | Wheat,Wheat 90K SNP array,Population structure,Genome-wide association study (GWAS),Plant height,Spike length,Days to heading, | en |
dc.relation.page | 93 | |
dc.identifier.doi | 10.6342/NTU202004309 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2020-10-28 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 農藝學研究所 | zh_TW |
顯示於系所單位: | 農藝學系 |
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