Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Alok kumar Singh
ORCID logo ,
Devendra Kumar
ORCID logo ,
Donato Gemmati
ORCID logo ,
Ranjith Kumar Ellur
ORCID logo ,
Ashutosh Singh
ORCID logo ,
Veronica Tisato
ORCID logo ,
D.K. Dwivedi
,
Sanjay Kumar Singh
,
Kishor Kumar Sadasivuni
,
Nawaz Ahmad Khan
,
Ajay Vikram Singh
* ORCID logo
Version 1 : Received: 19 March 2024 / Approved: 19 March 2024 / Online: 20 March 2024 (04:45:59 CET)

How to cite: Singh, A.K.; Kumar, D.; Gemmati, D.; Ellur, R.K.; Singh, A.; Tisato, V.; Dwivedi, D.; Singh, S.K.; Sadasivuni, K.K.; Khan, N.A.; Singh, A.V. Investigating Genetic Diversity and Population Structure in Rice Breeding from Association Mapping of 116 Accessions Using 64 Polymorphic SSR Markers. Preprints 2024, 2024031134. https://doi.org/10.20944/preprints202403.1134.v1 Singh, A.K.; Kumar, D.; Gemmati, D.; Ellur, R.K.; Singh, A.; Tisato, V.; Dwivedi, D.; Singh, S.K.; Sadasivuni, K.K.; Khan, N.A.; Singh, A.V. Investigating Genetic Diversity and Population Structure in Rice Breeding from Association Mapping of 116 Accessions Using 64 Polymorphic SSR Markers. Preprints 2024, 2024031134. https://doi.org/10.20944/preprints202403.1134.v1

Abstract

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. 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% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.

Keywords

Rice; Population structure; Genetic diversity; PIC; Association mapping; Variability

Subject

Biology and Life Sciences, Agricultural Science and Agronomy

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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