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Mining of Elite Alleles for Outcrossing Related Traits in Rice (Oryza Sativa L.)through Association Analysis

作　者: CALEB MANAMIK BRERIA
导　师: 洪德林
学　校: 南京农业大学
专　业: 作物遗传育种
关键词: out-crossing traits elite alleles association analysis polymorphism linkage disequilibrium
分类号: S511
类　型: 硕士论文
年　份: 2013年
下　载: 2次
引　用: 0次
阅　读: 论文下载

内容摘要

China’s production of indica hybrid rice accounts for more than16million hectares per year, which makes up52%of the total cultivated rice area. Japonica rice cultivation only covers8.28million hectares per annum making up another27%of the total rice acreage. Japonica hybrid rice acreage is3%of the total japonica rice acreage as compared to indica hybrid rice. Main reasons for the slow development of hybrid japonica rice were due to its properties of weaker competitive advantages and lower seed production. Improvement of hybrid japonica rice lines is very critical in China as there are reasonable comparative advantage between indica rice production and japonica rice production. Although research on the utilization of heterosis in rice has made tremendous gains during the last30years, it is, from a strategic point of view, still in its infancy because the outcrossing characteristic potential has not been fully tapped yet. Improving japonica seed production is very vital in China. In order for higher seed productions in japonica rice, characteristics of out-crossing related traits in rice must be well studied and understood. A variety with good stigma traits and good architectural traits would have an advantage of giving high and stable F1seed production yield. Therefore, genetic and breeding studies at this level provide a platform for increase hybrid japonica seeds production.For the experiment on the evaluation procedure, a total of462different rice varieties from Taihu Lake and other areas were used as testing materials. Investigative study was done on the following traits:flag leaf angle, filament length, stigma length, anther length and percentage exerted stigma. For the genotyping,263SSR molecular markers covering the12chromosomes of rice were used to screen the462rice varieties. TASSEL software General Linear Model (GLM) was used to identify association between markers and traits. The results obtained are as follows: (1) Percentage Exerted Stigma recorded the highest co-efficient of variation with90.49%in2011. This was followed by flag leaf angle with a co-efficient variation of49.09%in2011and48.09%in2012.(2) In analysis of genetic diversity,263SSR molecular markers detected a total of730alleles. The number of alleles varied from2to25with an overall mean of9.35alleles per locus indicating polymorphism within the population. The average genetic diversity is0.0832and the genetic diversity ranged from0.009to0.2015. Polymorphic Information Content (PIC) values ranged from0.0269to0.9329with an average value of0.699.(3) Analysis of population structure revealed that5sub-population existed in the total population of462varieties.(4) SSR molecular markers detected730alleles.(5) Flag leaf angle has3SSR loci associated with the trait in both2011and2012. They are RM212, RM5951, and RM405. RM212was associated with alleles RM212-120in both2011and2012. Their a; was0.941and0.948respectively. The carrier varieties were found to be’mudanjiang27’and’ligengqing’. The largest allele effect ai was0.94identifying’ligengqing’. RM5951was associated with alleles RM5951-75and RM5951-80in2011and2012but associated with allele RM5951-100only in2012. The ai for RM5951-71was3.608(2011) and RM5951-71was3.611(2012). RM5951-100a; was0.1. The allele with the largest effect is RM5951-80and the variety identified was ’longdao6’. RM405was associated with alleles RM405-95, RM405-110, RM405-115and RM405-150. The allele with the largest ai effect was RM405-110identifying the carrier variety’mudanjiang27’.In all, allele RM5951-80has the largest ai effect of4.067reasonably above all other alleles in flag leaf angle, thus identifying ’longdao6’as the elite carrier variety.Stigma length has3SSR loci associated with the trait in both2011and2012. They are RM129, RM140and RM212. RM129is associated with RM129-90. The largest allele effect ai value of allele RM129-90is0.062identifying ’zhonghua3’as the carrier variety. RM140is associated with alleles RM140-265, RM140-270and RM140-285. Allele RM140-285has the largest allele effect identifying ’yue82(17.11-2)’ as the carrier variety. RM212is associated with alleles RM212-80and RM212-135. RM212-80has the largest as effect identifying ’zhonghua3’ as the carrier variety. In all, RM140-285has the largest ai of all other alleles in SL thus identifying ’yue82(17.11-2)’ as the carrier variety.Anther length has3SSR loci associated with the trait in both2011and2012. They are RM129, RM545and RM212. RM129was associated with allele RM129-190and RM129-105. Allele Rm129-190has the larger as value identifying carrier variety’kuobanzhong’. RM545was associated with alleles RM545-175, RM545-180and RM545-185. RM545-185has the larger ai effect identifying variety ’zijianwujing’. RM212was associated with alleles RM212-80and RM212-135. RM212-135has the higher ai of0.068identifying carrier variety yue36(17.10-1). In all, allele RM545-185has the largest ai effect of all other alleles in anther length thus identifying ’zijianwujing’ as the carrier variety.In filament length, there were no identical SSR loci markers associated with the trait both in2011and including2012. However,8SSR loci markers were associated independently in two years. The alleles found to be associated include RM269-170, RM269-175, RM269-180, RM280-100, RM280-175, RM129-190, RM7163-225, RM437-275, RM545-175, RM545-185, RM433-185, and RM304-135. The elite of all alleles with the largest ai was RM545-185which identified the carrier variety ’zijianwujing’.Percentage exerted stigma have5SSR loci associated with the trait. The alleles in association were RM159-150, RM159-230, RM159-240, RM159-250, RM159-255, RM159-260, RM225-115, RM225-225, RM225-235, RM281-115, RM281-130, RM259-155RM281-285, RM259-135, RM259-145and RM281-220. Allele RM281-115has the largest a; effect identifying ’Chiguhong’ as the carrier variety

全文目录

ABSTRACT  6-9
List of Abbreviaitons  9-10
Chapter 1: Literature Review  10-22
  1.1 Hybrid Rice in China  10-11
  1.2 Rice Flowering Habits,Out-Crossing Traits and Genetic Research Progress  11-12
  1.3 Rice Flower Layer Structure,Flag Leaf Traits and Its Genetic Research Progress  12-16
  1.4 Concepts and Principles of Association,Analysis  16-18
  1.5 Basic Methods of Association Analysis  18-20
  1.6 Objectives of the Study  20-22
Chapter 2: Materials and Methods  22-36
  2.1 Test Materials  22-26
  2.2 Test Methods  26
  2.3 DNA Extraction and PCR Amplification  26-31
  2.4 Data Analysis  31-32
  2.5 Measure of Linkage Disequilibrium  32
  2.6 Population Structure  32-33
  2.7 Identifying Molecular Markers Associated with Traits  33
  2.8 Identifying Elite Alleles Associated with Traits  33-36
Chapter 3: Results and Analysis  36-54
  3.1 Descriptive Statistics and Heritability of Out-Crossing Traits within the Population  36-37
  3.2 Frequency Distribution of Traits across the 2 Years  37-41
  3.3 Phenotypic Correlations among Traits  41-42
  3.4 SSR Loci Analysis of Genetic Diversity  42-45
  3.5 Sub Population within the Accessions  45-47
  3.6 Elite Allele Mining  47-54
    3.6.1 SSR Loci Associated with Out-crossing Traits  47
    3.6.2 Outcrossing Traits Associated with Elite Alleles and Its Carrier Varieties  47-54
Chapter 4: Discussion and Conclusion  54-56
List of References  56-64
Publications  64-66
Appendix A: Traits Data for 2011 and 2012  66-76
Acknowledgement  76

Mining of Elite Alleles for Outcrossing Related Traits in Rice (Oryza Sativa L.)through Association Analysis

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