Multi-Trait Phenotypic and SSR-Based Genetic Diversity Assessment of Individual Plants for Parental Selection in Turf-Type Tall Fescue

Climate change has increased the need for turfgrass germplasm with improved adaptation, persistence, and resource-use efficiency. Tall fescue (Schedonorus arundinaceus) is an important cool-season turfgrass species valued for its tolerance to environmental stresses. This study aimed to assess phenotypic and molecular diversity among individual tall fescue plants derived from 24 United States Department of Agriculture (USDA) Gene Bank accessions and to identify promising turf-type parental material by integrating phenotypic and molecular information. A total of 223 genotypes were evaluated for 17 morphological and agronomic traits, and 120 genotypes were selected using a multi-trait weighted selection index for SSR-based molecular characterization. Principal component (PC) analysis showed that PC1 and PC2 accounted for 50.8% and 12.0% of the total phenotypic variation, respectively. Fourteen polymorphic SSR markers generated 69 polymorphic bands, with an overall mean polymorphism information content (PIC) value of 0.343. Unweighted Pair Group Method with Arithmetic Mean (UPGMA) analysis resolved two major molecular groups with four nested subclusters. Mantel analysis showed a weak but significant positive association between phenotypic and SSR-based molecular distances (r = 0.137, p < 0.001), indicating limited correspondence between the two data types. By jointly considering morphological performance and molecular diversity, 60 genotypes were identified as promising parental candidates for future tall fescue breeding programs.

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Journal
Plants
Published
2026-10-14
DOI
https://doi.org/10.3390/plants15203146
Primary Topic
Turfgrass Adaptation and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-Trait Phenotypic and SSR-Based Genetic Diversity Assessment of Individual Plants for Parental Selection in Turf-Type Tall Fescue

Fikret Yönter, Sevin Teoman Duran, Sinem Zere Taşkın, Meryem İpek et al.
Plants
Turfgrass Adaptation and Management
article

Multi-Trait Phenotypic and SSR-Based Genetic Diversity Assessment of Individual Plants for Parental Selection in Turf-Type Tall Fescue

Fikret Yönter, Sevin Teoman Duran, Sinem Zere Taşkın, Meryem İpek, Uğur Bilgili
article en

Abstract

Climate change has increased the need for turfgrass germplasm with improved adaptation, persistence, and resource-use efficiency. Tall fescue (Schedonorus arundinaceus) is an important cool-season turfgrass species valued for its tolerance to environmental stresses. This study aimed to assess phenotypic and molecular diversity among individual tall fescue plants derived from 24 United States Department of Agriculture (USDA) Gene Bank accessions and to identify promising turf-type parental material by integrating phenotypic and molecular information. A total of 223 genotypes were evaluated for 17 morphological and agronomic traits, and 120 genotypes were selected using a multi-trait weighted selection index for SSR-based molecular characterization. Principal component (PC) analysis showed that PC1 and PC2 accounted for 50.8% and 12.0% of the total phenotypic variation, respectively. Fourteen polymorphic SSR markers generated 69 polymorphic bands, with an overall mean polymorphism information content (PIC) value of 0.343. Unweighted Pair Group Method with Arithmetic Mean (UPGMA) analysis resolved two major molecular groups with four nested subclusters. Mantel analysis showed a weak but significant positive association between phenotypic and SSR-based molecular distances (r = 0.137, p < 0.001), indicating limited correspondence between the two data types. By jointly considering morphological performance and molecular diversity, 60 genotypes were identified as promising parental candidates for future tall fescue breeding programs.

PlantsVol. 15(20)
Bursa Uludağ Üni̇versi̇tesi̇ (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Zero hunger
Openalex Percentile: Top 24%
Turfgrass Adaptation and Management
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