水稻不同遺傳力的數(shù)量性狀在中國和贊比亞4個環(huán)境下的遺傳分析
發(fā)布時間：2020-10-08 15:56
盡管水稻在不同國家糧食作物中的重要性不同,但是它對全球糧食安全來說十分重要,這也使得提高水稻產(chǎn)量成為養(yǎng)活日益增長的全球人口的重要解決方案之一。水稻的產(chǎn)量和品質(zhì)在稻米產(chǎn)業(yè)的可持續(xù)發(fā)展中起著同等重要的作用。在育種改良中,水稻產(chǎn)量和品質(zhì)相關(guān)的數(shù)量性狀是人們關(guān)注的重點,然而目前,對于遺傳力較低的性狀,如出米率等的還了解不夠。為此,我們進(jìn)行了一項實驗,研究中使用的群體來自于秈稻明恢63和粳稻02428的亞種間雜交組合,主要目的是通過研究這些材料來加深對出米率等數(shù)量性狀在不同環(huán)境下的相關(guān)遺傳因素的理解。我們利用了3個群體對碾磨品質(zhì)這一重要農(nóng)藝性狀的遺傳背景效應(yīng)進(jìn)行了探討,其中包括226份MH63_ILs、229份以02428為背景的導(dǎo)入系(02428_ILs)和261份重組自交系(RILs)。我們將供試群體分別種植在中國的北京(Env 1)和海南(Env 2)、贊比亞的Mongu Namushakende農(nóng)業(yè)研究所(Env 3)和Mount Makulu研究站(Env 4)四種環(huán)境。在此基礎(chǔ)上,我們在多種性狀之間進(jìn)行對數(shù)量性狀位點的連鎖分析。另外,我們也研究了出米率與高遺傳力性狀之間的相互關(guān)系,包括以品種50%抽穗為調(diào)查抽穗期的標(biāo)準(zhǔn)對其抽穗期和粒型性狀的調(diào)查。QTL分析了粒型(粒長(GL)、粒寬(GW)、長寬比(LWR)、籽粒體積(GV))、碾磨質(zhì)量(糙米率(BRR)、精米率(MRR)、整精米率(HRR))和包括抽穗期(DTH)、株高(PH)、糧食產(chǎn)量(GY)、千粒重(TGW)和籽粒灌漿速率(GFR)在內(nèi)的農(nóng)藝性狀。我們在四個環(huán)境下一共檢測到102個QTL,其中在3個碾磨品質(zhì)中共定位到9個QTL,在4個粒型性狀中定位到32個QTL,剩余其他5個被檢測農(nóng)藝性狀中共定位到61個QTL。有22個QTL至少在兩個環(huán)境中檢測到,分別包括11個與粒型相關(guān)的QTL和11個與5個農(nóng)藝性狀相關(guān)的QTL。一共有27個粒型和農(nóng)藝性狀QTL不止一種環(huán)境中被檢測到,其中包括qGL3c、qGL9a、qGL11a、qGW3a、qGW5a、qLWR3a、qLWR5a、qGV1a、qGV3a、qGV5a、qGV5b、qPH1e、qPH3c,qPH5c、qPH6a、qPH12a、qTGW3d、qTGW5a、qTGW5c、qTGW11a、qTGW11b、qGFR11a。此外,qDTH2a、qDTH5a、qPH12a、qTGW3d、qGY3a、qGY6a和qGFR3c不止在一個群體中被檢測到。有3個QTL(qGY3a、qGY6a和qTGW3d)在多個環(huán)境和多個群體中檢測到。我們的分析進(jìn)一步揭示了17個與谷物品質(zhì)性狀相關(guān)的主效QTL的影響包括在8號染色體上的與水稻整精米率相關(guān)的QTL,qHR8a。遺傳背景效應(yīng)研究顯示,在檢測到的QTL中,大約有58.7%和28.6%的QTL分別在MH63_ILs和RILs中被檢測到,有12.7%的QTL在MH63_ILs和RILs中被共同檢測到。本研究中定位到17個控制粒型及其他農(nóng)藝性狀QTL所在區(qū)間與已克隆的基因或精細(xì)定位的QTL sd.1,sdg,GS3,GS5,Chalk5,GS7,qGL7,GIF1,qHD5,qSS7,SUS1,TGW6 and tgw11等一致。此外,有5個QTL可以分解為25個QTL簇,且至少控制一種碾磨品質(zhì)。其中有兩個QTL簇顯示兩種碾磨品質(zhì)和抽穗期之間存在某種聯(lián)系。1號染色體上位于M443和M450標(biāo)記之間的QTL簇包含了qDTH1c和qMR1a,這兩個QTL只相差2cM。3號染色體上包含qHR3a和qDTH3a的簇位于M989和M1028之間,說明在低遺傳力的條件下,對抽穗期的選擇是對加工品質(zhì)的進(jìn)行選擇的主要目標(biāo)。而且,結(jié)果還揭示了在不同環(huán)境下抽穗期對加控制工品質(zhì)相關(guān)QTL表達(dá)變異的影響。值得提出的是,控制相關(guān)QTL的等位基因有73.5%來自于秈稻親本明恢63。表型差異分析顯示,與輪回親本相比,導(dǎo)入系存在顯著的超親變異。其中,39.4%的導(dǎo)入系的整精米率對輪回親本明恢63表現(xiàn)出正向超親遺傳。廣義遺傳率從低到高分別為碾磨品質(zhì)(17 18%),農(nóng)藝性狀(24 60%)和粒型(69 83%)。通常遺傳率由群體類型決定,環(huán)境因素同時也影響群體類型對遺傳率的效應(yīng)。本研究還表明,在特定的環(huán)境下,基于粒長、粒寬、千粒重和抽穗期與整精米率顯著正相關(guān),它們可以為整精米率提供有效的間接選擇指標(biāo)。本研究有助于拓寬我們對數(shù)量性狀的認(rèn)識,并為分子育種提供有用的信息。
【學(xué)位單位】：中國農(nóng)業(yè)科學(xué)院
【學(xué)位級別】：博士
【學(xué)位年份】：2018
【中圖分類】：S511
【文章目錄】：
摘要
ABSTRACT
CHAPTER 1 INTRODUCTION
1.1 Background
1.2 The genus Oryza sativa L
1.3 Economic and nutritional importance
1.4 Rice production and milling quality
1.5 Rice milling quality
1.6 Rice grain appearance
1.7 Factors that affect milling quality of rice
1.8 Past achievements in rice breeding
1.9 Molecular breeding progress
1.10 Genetic mapping
1.10.1 Linkage analysis
1.10.2 Quantitative trait loci mapping for rice milling quality
1.10.3 Quantitative trait loci mapping for rice grain shape
1.11 Application of biotechnology in rice quality improvement
1.11.1 Marker assisted breeding for rice quality improvement
1.11.2 Genetic engineering
1.11.2.1 Genetic transformation
1.11.2.2 Genome editing
1.12 Future trends of rice quality improvement
1.13 Past research limitations
1.14 Aim of the study
1.15 Scope and outline of the thesis
CHAPTER 2 GENETIC VARIABILITY, HERITABILITY AND CORRELATION STUDIES OF MILLING QUALITY, GRAIN DIMENSION AND AGRONOMIC TRAITS IN INTROGRESSION LINES DERIVED FROM AN INTERSPECIFIC (INDICA X JAPONICA) CROSS OF RICE.
2.1 Introduction
2.2 Materials and methods
2.2.1 Materials
2.2.2 Methods
2.2.3 Trait measurements
2.2.4 Data analysis
2.3 Results
2.3.1 Phenotypic variability assessment
2.3.2 Phenotypic variance components
2.3.3 Trait mean performance of introgression lines and parents
2.3.4 Heritability
2.3.5 Pearson’s correlation analysis
2.3.6 Path analysis for head rice recovery
2.3.7 Path analysis for grain yield
2.4 Discussion
2.4.1 High genetic variability among genotypes
2.4.2 Genotype x Environment Interactions
2.4.3 Inferences from trait mean performance of introgression lines and parents
2.4.4 Inferences from variation of heritability among traits
2.4.5 Inferences from trait correlations
2.4.6 Effect of various traits on head rice recovery
2.4.7 Effect of various traits on grain yield
2.5 Conclusion
CHAPTER 3 MAPPING QUANTITATIVE TRAIT LOCI FOR MILLING QUALITY AND GRAIN DIMENSION TRAITS OF A SET OF INTROGRESSION LINES DERIVED FROM AN INTERSPECIFIC CROSS (indica x japonica) OF RICE
3.1 Introduction
3.2 Materials and methods
3.2.1 Materials
3.2.2 Methods
3.2.3 Genotyping
3.2.4 QTL analysis
3.3 Results
3.3.1 QTL detection for milling quality traits
3.3.2 QTL detection for grain dimension traits
3.3.3 Stably expressed QTL for quality related traits
3.3.4 QTL clusters for quality related traits
3.4 Discussion
3.4.1 Contributions of QTL main effects of milling quality traits
3.4.2 Contributions of QTL main effects of grain dimension traits
3.4.3 Stably expressed QTL for quality related traits
3.4.4 Genetic interactions among quality traits
3.5 Conclusion
CHAPTER 4 GENETIC BACKGROUND EFFECTS ON QUANTITATIVE TRAIT LOCI MAPPING OF AGRONOMIC TRAITS USING MULTIPLE POPULATIONS IN FOUR ENVIRONMENTS
4.1 Introduction
4.2 Materials and methods
4.2.1 Materials
4.2.2 Experimental sites
4.2.3 Methods
4.2.4 Data analysis
4.2.5 QTL analysis
4.3 Results
4.3.1 Trait variability assessment
4.3.2 Trait mean performance and heritability
4.3.3 Pearson’s correlation and path analysis
4.3.4 QTL mapping of agronomic traits across populations
4.3.5 QTL clusters
4.4 Discussion
4.4.1 High genetic variability among genotypes across populations
4.4.2 Heritability inferences from various populations
4.4.3 Inferences from trait correlations
4.4.4 Contributions of QTL main effect of agronomic traits
4.4.5 Genetic interactions between DTH and milling quality traits
4.4.6 Genetic interactions between milling quality and other traits
4.4.7 Genetic association between traitsprobably caused by QTL clusters
4.4.8 Overall novel QTL of the study
4.5 Conclusion
CHAPTER 5
5.1 SUMMARY AND CONCLUSIONS
REFERENCES
APPENDICES
ACKNOWLEDGEMENT
RESUME
本文編號：2832438
【學(xué)位單位】：中國農(nóng)業(yè)科學(xué)院
【學(xué)位級別】：博士
【學(xué)位年份】：2018
【中圖分類】：S511
【文章目錄】：
摘要
ABSTRACT
CHAPTER 1 INTRODUCTION
1.1 Background
1.2 The genus Oryza sativa L
1.3 Economic and nutritional importance
1.4 Rice production and milling quality
1.5 Rice milling quality
1.6 Rice grain appearance
1.7 Factors that affect milling quality of rice
1.8 Past achievements in rice breeding
1.9 Molecular breeding progress
1.10 Genetic mapping
1.10.1 Linkage analysis
1.10.2 Quantitative trait loci mapping for rice milling quality
1.10.3 Quantitative trait loci mapping for rice grain shape
1.11 Application of biotechnology in rice quality improvement
1.11.1 Marker assisted breeding for rice quality improvement
1.11.2 Genetic engineering
1.11.2.1 Genetic transformation
1.11.2.2 Genome editing
1.12 Future trends of rice quality improvement
1.13 Past research limitations
1.14 Aim of the study
1.15 Scope and outline of the thesis
CHAPTER 2 GENETIC VARIABILITY, HERITABILITY AND CORRELATION STUDIES OF MILLING QUALITY, GRAIN DIMENSION AND AGRONOMIC TRAITS IN INTROGRESSION LINES DERIVED FROM AN INTERSPECIFIC (INDICA X JAPONICA) CROSS OF RICE.
2.1 Introduction
2.2 Materials and methods
2.2.1 Materials
2.2.2 Methods
2.2.3 Trait measurements
2.2.4 Data analysis
2.3 Results
2.3.1 Phenotypic variability assessment
2.3.2 Phenotypic variance components
2.3.3 Trait mean performance of introgression lines and parents
2.3.4 Heritability
2.3.5 Pearson’s correlation analysis
2.3.6 Path analysis for head rice recovery
2.3.7 Path analysis for grain yield
2.4 Discussion
2.4.1 High genetic variability among genotypes
2.4.2 Genotype x Environment Interactions
2.4.3 Inferences from trait mean performance of introgression lines and parents
2.4.4 Inferences from variation of heritability among traits
2.4.5 Inferences from trait correlations
2.4.6 Effect of various traits on head rice recovery
2.4.7 Effect of various traits on grain yield
2.5 Conclusion
CHAPTER 3 MAPPING QUANTITATIVE TRAIT LOCI FOR MILLING QUALITY AND GRAIN DIMENSION TRAITS OF A SET OF INTROGRESSION LINES DERIVED FROM AN INTERSPECIFIC CROSS (indica x japonica) OF RICE
3.1 Introduction
3.2 Materials and methods
3.2.1 Materials
3.2.2 Methods
3.2.3 Genotyping
3.2.4 QTL analysis
3.3 Results
3.3.1 QTL detection for milling quality traits
3.3.2 QTL detection for grain dimension traits
3.3.3 Stably expressed QTL for quality related traits
3.3.4 QTL clusters for quality related traits
3.4 Discussion
3.4.1 Contributions of QTL main effects of milling quality traits
3.4.2 Contributions of QTL main effects of grain dimension traits
3.4.3 Stably expressed QTL for quality related traits
3.4.4 Genetic interactions among quality traits
3.5 Conclusion
CHAPTER 4 GENETIC BACKGROUND EFFECTS ON QUANTITATIVE TRAIT LOCI MAPPING OF AGRONOMIC TRAITS USING MULTIPLE POPULATIONS IN FOUR ENVIRONMENTS
4.1 Introduction
4.2 Materials and methods
4.2.1 Materials
4.2.2 Experimental sites
4.2.3 Methods
4.2.4 Data analysis
4.2.5 QTL analysis
4.3 Results
4.3.1 Trait variability assessment
4.3.2 Trait mean performance and heritability
4.3.3 Pearson’s correlation and path analysis
4.3.4 QTL mapping of agronomic traits across populations
4.3.5 QTL clusters
4.4 Discussion
4.4.1 High genetic variability among genotypes across populations
4.4.2 Heritability inferences from various populations
4.4.3 Inferences from trait correlations
4.4.4 Contributions of QTL main effect of agronomic traits
4.4.5 Genetic interactions between DTH and milling quality traits
4.4.6 Genetic interactions between milling quality and other traits
4.4.7 Genetic association between traitsprobably caused by QTL clusters
4.4.8 Overall novel QTL of the study
4.5 Conclusion
CHAPTER 5
5.1 SUMMARY AND CONCLUSIONS
REFERENCES
APPENDICES
ACKNOWLEDGEMENT
RESUME
本文編號：2832438
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