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Genetic structure and diversity of upland rice germplasm using diversity array technology (DArT)-based single nucleotide polymorphism (SNP) markers

Published online by Cambridge University Press:  04 November 2020

Kehinde A. Adeboye Open the ORCID record for Kehinde A. Adeboye [Opens in a new window] ,
Olayinka E. Oyedeji ,
Ahmad M. Alqudah ,
Andreas Börner ,
Olusegun Oduwaye ,
Olutumininu Adebambo  and
Isaac O. Daniel
Kehinde A. Adeboye*
Affiliation:
Center of Excellence in Agricultural Development and Sustainable Environment (CEADESE), Federal University of Agriculture, Abeokuta, Nigeria Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland/OT Gatersleben, Germany
Olayinka E. Oyedeji
Affiliation:
Center of Excellence in Agricultural Development and Sustainable Environment (CEADESE), Federal University of Agriculture, Abeokuta, Nigeria Department of Agricultural, Food and Nutritional Sciences, Agriculture/Forestry Centre, University of Alberta, Edmonton, Canada
Ahmad M. Alqudah
Affiliation:
Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland/OT Gatersleben, Germany
Andreas Börner
Affiliation:
Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland/OT Gatersleben, Germany
Olusegun Oduwaye
Affiliation:
Department of Plant Breeding and Seed Technology, Federal University of Agriculture, Abeokuta, Nigeria
Olutumininu Adebambo
Affiliation:
Department of Animal Breeding and Genetics, Federal University of Agriculture, Abeokuta, Nigeria
Isaac O. Daniel
Affiliation:
Department of Plant Breeding and Seed Technology, Federal University of Agriculture, Abeokuta, Nigeria
*
*Corresponding author. E-mail: kaadeboye@yahoo.com
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Abstract

Investigating genetic structure and diversity is crucial for rice improvement strategies, including mapping quantitative trait loci with the potential for improved productivity and adaptation to the upland ecology. The present study elucidated the population structure and genetic diversity of 176 rice germplasm adapted to the upland ecology using 7063 genome-wide single nucleotide polymorphism (SNP) markers from the Diversity Array Technology (DArT)-based sequencing platform (DArTseq). The SNPs were reasonably distributed across the rice genome, ranging from 432 SNPs on chromosome 9 to 989 SNPs on chromosome 1. The minimum minor allele frequency was 0.05, while the average polymorphism information content and heterozygosity were 0.25 and 0.03, respectively. The model-based (Bayesian) population structure analysis identified two major groups for the studied rice germplasm. Analysis of molecular variance revealed that all (100%) of the genetic variance was attributable to differences within the population, and none was attributable to the population structure. The estimates of genetic differentiation (PhiPT = 0.001; P = 0.197) further showed a negligible difference among the population structures. The results indicated a high genetic exchange or gene flow (number of migrants, Nm = 622.65) and a substantial level of diversity (number of private alleles, Pa = 1.52 number of different alleles, Na = 2.67; Shannon's information index, I = 0.084; and percentage of polymorphic loci, %PPL = 55.9%) within the population, representing a valuable resource for rice improvement. The findings in this study provide a critical analysis of the genetic diversity of upland rice germplasm that would be useful for rice yield improvement. We suggested further breeding and genetic analyses.

Keywords

genetic differentiationgene flowupland ecology
Type
Research Article
Information
Plant Genetic Resources , Volume 18 , Issue 5 , October 2020 , pp. 343 - 350
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of NIAB

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