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Assessment of Molecular Diversity and Population Structure of Pakistani Mulberry Accessions Using Retrotransposon-Based DNA Markers
2024
Journal:  
Agriculture
Author:  
Abstract:

: Both morphological and molecular markers have been extensively used to evaluate genetic diversity; however, molecular markers are considered more reliable and can lead to improved reproductive efficiency. This study utilized inter-primer binding site (iPBS) markers to examine the genetic diversity and population structure of thirty mulberry accessions from the districts of Sahiwal and Faisalabad, Pakistan. These mulberry accessions belonged to three species: Morus nigra (n = 13), Morus alba (n = 12), and Morus rubra (n = 5). The use of nine iPBS primers in this study provided a comprehensive understanding of genetic diversity among the selected mulberry accessions. Nine iPBS primers were used in the study and generated 431 bands with allelic frequencies ranging from 21 to 75 and band sizes from 200 to 1500 base pairs. The primer 2230 showed the highest polymorphic information content (PIC) value of 0.47 and the highest Shannon’s information index (I = 0.53). The Morus nigra accessions had the highest levels of expected heterozygosity (He = 0.30), unbiased expected heterozygosity (µHe = 0.33), and Shannon’s information index (I = 0.45). The molecular variance analysis (AMOVA) revealed a high degree of genetic variation, as estimated by the pairwise PhiPT value of 0.21, which was significant at the p < 0.001 *** level. The neighbor joining tree, principal coordinate analysis, and structure analysis grouped the 30 mulberry accessions into four main clusters. The distinct grouping of accessions SWLS14, SWLS6, FSDS30, and SWLS7 validated their notable genetic distinctiveness. Overall, these findings contribute valuable insights into the genetic landscape of mulberry accessions, which are essential for conservation and breeding strategies.

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2024
Journal:  
Agriculture
Author:  
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Agriculture

Journal Type :   Uluslararası

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Article : 9.835
Cite : 6.420
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Agriculture