Assessing molecular diversity of tropical maize inbred lines using Single Nucleotide Polymorphic (SNP) markers

Citation

Sharanu, S. G., Patil, A., Kuchanur, P. H., Nair, S., Kisan, B., Yeri, S. B., Vinayan, M. T., & Zaidi, P. H. (2025). Assessing molecular diversity of tropical maize inbred lines using single nucleotide polymorphic (SNP) markers. Journal of Experimental Agriculture International, 47(10), 490–500. https://doi.org/10.9734/jeai/2025/v47i103831

Abstract/Description

Advances in genotyping technologies have changed how breeders study and manage maize genetics. Identification of single nucleotide polymorphisms (SNPs) helped researchers understand the molecular diversity among tropical maize (Zea mays L.) inbred lines, The present study was conducted to assess the molecular diversity and population structure of 107 tropical maize inbred lines collected from working germplasm programs using SNP markers. A total of 97 genome-wide SNP markers were employed for genotyping through the KASP assay. The polymorphism information content (PIC) values ranged from 0.018 to 0.375 with an overall mean of 0.285, indicating that the majority of markers were moderately informative. Hierarchical clustering grouped the inbred lines into three major clusters, reflecting clear genetic differentiation among the tropical maize inbred lines. Principal component analysis (PCA) further validated these findings by identifying highly divergent lines Viz., AHG-122, CIMMYT-22, BHG-20 and AHG-110-1. The congruence between UPGMA clustering and PCA confirmed the robustness of the diversity analysis. These findings provide valuable insights into the genetic relationships among tropical maize inbreds and highlight the utility of SNP markers in guiding the selection of parental lines for hybrid development.

Permanent link to cite or share this item

External link to download this item

CGIAR Action Areas

CGIAR Initiatives

Share

Review Status

Peer Review

Language

en

Access Rights

Open Access Open Access

Usage Rights

CC-BY-4.0

Attention