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Studies On Genetic Diversity Of Rice Germplasm Introduced From Xinjiang And Elsewhere Region

Posted on:2019-05-26Degree:MasterType:Thesis
Country:ChinaCandidate:L Q BuFull Text:PDF
GTID:2393330551456562Subject:Crop Genetics and Breeding
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Rice is one of the most principal food crops in the world.It is of great significance for rice breeding to find and utilize good genes and apply them to parental choice.Genetic diversity of rice germplasm introduced from Xinjiang and elsewhere was analyzed and evaluated by using 32 agronomic traits combined with 60 sample sequences repeats(SSR)markers.The purpose of this study was to illustrate the differentiated degree between different source resources.The results were as follows:1.Among the 16 quantitative traits,the maximum variation coefficient was the secondary branch number(32.22%),and the smallest was grain width(6.82%).The average genetic diversity indices of the quality traits in Xinjiang rice gerrnplasm was 0.51,and the quantitative traits was 1.95.The average genetic diversity indices of the quality traits in elsewhere was 0.40,and the quantitative traits was 2.02.It is indicated that the quality characters of rice genlplasm resources in Xinjiang are more abundant,while the quantitative characters of rice resources in other regions are more different.By the principal component analysis,these sixteen single indexes could be converted to five principal components.They could present 84.66%(Xinjiang)and 84.60%(elsewhere)information of the raw data.2.Using the UPGMA method,358 rice resources gerrmplasm were clustered into 5 groups.The first group contained 201 gerrnplasm including 65 Xinjiang gerrmplasm,.which characters of more grain.The second group consists of five germplasm with high plant height and large ears,but with low yield.In the third group,there were 32 kinds of materials,all of which were less grain density and less grain number.The fourth group contained 118 germplasm,of which were 36 gerrmplasm from Xinjiang.The total grain number of each spike and the number of real grains per panicle in this group were less than the average of all materials but higher than the third group.The fifth group contained only two varieties,which is more differentiated than other resources and has great genetic differences.3.60 pairs of SSR primers were used to analyze the genetic diversity of 358 japonica rice resources.263 alleles were detected,and the range of variation was from 2 to 9,with an average of 4.38 per marker,among which RM1306 was the most.The average number of alleles detected on chromosome 10 was 5.60.The average number of effective alleles was 2.08,and the range of variation was 1.02 to 4.67 and the 1.02 was belong to RM 1182,4.67 was belong to RM23823.Shannon index ranged from 0.40 to 1.69,and the Shannon index with an a'verage of 0.81 RM333 was the highest,with 1.65 RM23823 and RM1306 higher than 1.5.The results showed that RM23823 RM333 and RM1306 could reflect the differences among the rtested varieties and were suitable for genetic diversity research.4.Tlie population genetic structure was analyed based on SSR molecular detection.The results showed that a total of 336 materials could be classified into three groups.The first group containing 74 materials,accounting for 20.67%,among which 14 are Xinxiang materials,accounting for 13.21%of Xinxiang materials.The second group consisting of 90 materials,accounting for 25.14%,among which 30 are Xinxiang materials,and accounting for 28.57%of Xinxiang materials.The third group containing 165 materials,accounting for 46.09%,among which 55 are Xinxiang materials,accounting for 52.38%of Xinxiang materials.There are 22 undefined categories,accounting for 6.15%,of which 6 are Xinjiang germplasm,accounting for 5.71%of Xinjiang germplasim.5.It can be seen that there were certain genetic differences between rice germplasm germplasm and other regions in Xinjiang,and the beneficial genes of different regional germpJasnm can be excavated in the breeding work to increase the genetic diversity.
Keywords/Search Tags:Rice, Genetic diversity, Principal component analysis, Cluster analysis, Genetic structure
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