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.

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

Gemmati D.;Tisato V.;
2024

Abstract

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.
2024
Singh, A. K.; Kumar, D.; Gemmati, D.; Ellur, R. K.; Singh, A.; Tisato, V.; Dwivedi, D. K.; Singh, S. K.; Kumar, K.; Khan, N. A.; Singh, A. V.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2574093
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