Investigating Genetic Diversity and Population Structure in Rice Breeding from Association Mapping of 116 Accessions Using 64 Polymorphic SSR Markers

被引:1
|
作者
Singh, Alok Kumar [1 ]
Kumar, Devendra [2 ]
Gemmati, Donato [3 ,4 ]
Ellur, Ranjith Kumar [5 ]
Singh, Ashutosh [6 ]
Tisato, Veronica [3 ,4 ]
Dwivedi, Devendra Kumar [1 ]
Singh, Sanjay Kumar [5 ]
Kumar, Kishor [7 ]
Khan, Nawaz Ahmad [1 ]
Singh, Ajay Vikram [8 ]
机构
[1] Acharya Narendra Deva Univ Agr & Technol, Dept Plant Mol Biol & Genet Engn, Ayodhya 224229, India
[2] Uttar Pradesh Pandit Deen Dayal Upadhyaya Pashu Ch, Coll Biotechnol, Dept Plant Biotechnol, Mathura 281001, UP, India
[3] Univ Ferrara, Dept Translat Med, I-44121 Ferrara, Italy
[4] Univ Ferrara, Ctr Haemostasis & Thrombosis, I-44121 Ferrara, Italy
[5] ICAR Indian Agr Res Inst, Div Genet, New Delhi 110012, India
[6] Rani Laxmi Bai Cent Agr Univ, Dept Biotechnol & Crop Improvement, Jhansi 284003, India
[7] Qatar Univ, Ctr Adv Mat CAM, Dept Mech & Ind Engn, POB 2713, Doha, Qatar
[8] German Fed Inst Risk Assesment BfR, D-10589 Berlin, Germany
来源
CROPS | 2024年 / 4卷 / 02期
关键词
rice; population structure; genetic diversity; PIC; association mapping; variability; ORYZA-SATIVA; SUBMERGENCE TOLERANCE; WILD; DIFFERENTIATION; CONSERVATION; COLLECTION; PATTERNS; AFLP; SNP; L;
D O I
10.3390/crops4020014
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Genetic variability in rice breeding programs plays a very crucial role. It provides an outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For a greater understanding of population structure, the genetic relationship among different rice lines is indispensable prior to the setting of a correlation among dynamic alleles and traits. In the present investigation, the genetic diversity and population structure of 116 rice accessions were studied to understand genetic relatedness and diversity among them using 64 polymorphic SSR markers. A genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model- and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% was likely due to differences within groups. This study suggested that population structure and genetic relatedness should be considered to establish marker-trait associations for association mapping when working with the core collection of germplasm lines.
引用
收藏
页码:180 / 194
页数:15
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