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<p>In the present investigation, phenotypic and molecular profiling was performed for 30 elite QPM germplasm lines using agro-morphological, quality traits and 61 SSR markers. The highest morphological variation was found in the number of kernel rows per cob. Eight clusters were identified based on phenotypic data using D<sup>2</sup> statistic. The first four principal components explained 82.81% of the total variation. Molecular analysis identified 119 polymorphic alleles averaging 3.5 per primer. PIC values ranged from 0.250 (umc2334) to 0.730 (phi034) with a mean of 0.521. Genotypes were categorized into two major clusters using the UPGMA algorithm, while neighbor-joining analysis delineated three main clusters. Structure analysis divided the genotypes into two sub-populations. Fifteen genotypes (DQL-609–1-3, DQL-774–171, DQL-614–6, BJ QPM-18, BJ QPM-20, BJ QPM-21, BJ QPM-1, BJ QPM-7, BJ QPM-2, BJ QPM-3, BJ QPM-4, BJ QPM-8, BJ QPM-14, BJ QPM-22 and BJ QPM-24) were found common across both morphological and molecular analyses. Mantel’s test showed a strong correlation (<i>r</i> = 0.711) between morphological and molecular datasets. Five genotypes viz., BJ QPM-13, BJ QPM-15, BJ QPM-19, DQL-609–1-3, and DQL-614–6 were most divergent based on molecular analysis and also had good quality traits viz., crude protein (%), lysine (g/16 g N) and tryptophan (g/16 g N). These genetically diverse genotypes can be exploited to expand the genetic variability for developing high-yielding single cross QPM hybrids.</p>

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Morpho-molecular Genetic Diversity and Population Structure Analysis in Elite Quality Protein Maize (Zea mays L.) Germplasm Adapted to North-Western Himalayas Using Simple Sequence Repeat Markers

  • 期刊论文

  • 发表日期：

    2025年3月17日

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  • Shailaja Godara,
  • Uttam Chandel,
  • Tanvi Rawal,
  • Rajan Katoch

摘要

In the present investigation, phenotypic and molecular profiling was performed for 30 elite QPM germplasm lines using agro-morphological, quality traits and 61 SSR markers. The highest morphological variation was found in the number of kernel rows per cob. Eight clusters were identified based on phenotypic data using D2 statistic. The first four principal components explained 82.81% of the total variation. Molecular analysis identified 119 polymorphic alleles averaging 3.5 per primer. PIC values ranged from 0.250 (umc2334) to 0.730 (phi034) with a mean of 0.521. Genotypes were categorized into two major clusters using the UPGMA algorithm, while neighbor-joining analysis delineated three main clusters. Structure analysis divided the genotypes into two sub-populations. Fifteen genotypes (DQL-609–1-3, DQL-774–171, DQL-614–6, BJ QPM-18, BJ QPM-20, BJ QPM-21, BJ QPM-1, BJ QPM-7, BJ QPM-2, BJ QPM-3, BJ QPM-4, BJ QPM-8, BJ QPM-14, BJ QPM-22 and BJ QPM-24) were found common across both morphological and molecular analyses. Mantel’s test showed a strong correlation (r = 0.711) between morphological and molecular datasets. Five genotypes viz., BJ QPM-13, BJ QPM-15, BJ QPM-19, DQL-609–1-3, and DQL-614–6 were most divergent based on molecular analysis and also had good quality traits viz., crude protein (%), lysine (g/16 g N) and tryptophan (g/16 g N). These genetically diverse genotypes can be exploited to expand the genetic variability for developing high-yielding single cross QPM hybrids.