Microsatellite (SSR) Markers Application in the Characterization of Genetic Diversity in Capsicum annuum Germplasm

This study focused on the genetic diversity of Capsicum annuum (commonly known as chili or bell pepper) using 40 Simple Sequence Repeat (SSR) markers across 133 genotypes. Out of 40 SSR markers, 29 were polymorphic, indicating considerable genetic variation within the genotypes. The polymorphic information content (PIC) values ranged from 0.098 to 0.992, with an average of 0.708, reflecting a broad spectrum of genetic information. Notably, 22 markers had PIC values greater than 0.5, demonstrating strong discriminatory power. Among SSRs, the marker AVRDC-17 exhibited the highest PIC value at 0.992, followed by AVRDC 174 (0.990), Agi96 (0.967), and HPMS 1-5 (0.961). The expected heterozygosity (He) of the genotypes varied from 0.038 to 0.766, with an average of 0.428. The marker HPMS 1-214 showed the highest expected heritability value of 0.766, a high level of genetic variability in certain genotypes. Cluster analysis grouped the genotypes into seven distinct genetic clusters, reinforcing the presence of considerable genetic differentiation among the genotypes. Genetic similarity coefficients ranged from 0.11 to 0.91, reflecting the diverse genetic relationships within the population. The highest similarity was observed between genotypes 36569 and 36627, with a coefficient of 0.91, indicating a close genetic relationship. These findings confirm the usefulness of SSR markers in assessing genetic diversity, offering valuable information for breeding programs aimed at developing improved Capsicum annuum cultivars with enhanced yield and adaptability.

Publication Details

Journal
International Journal of Agriculture and Biology
Published
2025-08-14
DOI
https://doi.org/10.17957/ijab/15.2398
Citations
1
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
2.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Microsatellite (SSR) Markers Application in the Characterization of Genetic Diversity in Capsicum annuum Germplasm

1 citations
International Journal of Agriculture and Biology
Geochemistry and Geologic Mapping
2.48
article

Microsatellite (SSR) Markers Application in the Characterization of Genetic Diversity in Capsicum annuum Germplasm

article en
1 citations

Abstract

This study focused on the genetic diversity of Capsicum annuum (commonly known as chili or bell pepper) using 40 Simple Sequence Repeat (SSR) markers across 133 genotypes. Out of 40 SSR markers, 29 were polymorphic, indicating considerable genetic variation within the genotypes. The polymorphic information content (PIC) values ranged from 0.098 to 0.992, with an average of 0.708, reflecting a broad spectrum of genetic information. Notably, 22 markers had PIC values greater than 0.5, demonstrating strong discriminatory power. Among SSRs, the marker AVRDC-17 exhibited the highest PIC value at 0.992, followed by AVRDC 174 (0.990), Agi96 (0.967), and HPMS 1-5 (0.961). The expected heterozygosity (He) of the genotypes varied from 0.038 to 0.766, with an average of 0.428. The marker HPMS 1-214 showed the highest expected heritability value of 0.766, a high level of genetic variability in certain genotypes. Cluster analysis grouped the genotypes into seven distinct genetic clusters, reinforcing the presence of considerable genetic differentiation among the genotypes. Genetic similarity coefficients ranged from 0.11 to 0.91, reflecting the diverse genetic relationships within the population. The highest similarity was observed between genotypes 36569 and 36627, with a coefficient of 0.91, indicating a close genetic relationship. These findings confirm the usefulness of SSR markers in assessing genetic diversity, offering valuable information for breeding programs aimed at developing improved Capsicum annuum cultivars with enhanced yield and adaptability.

International Journal of Agriculture and BiologyVol. 34(05)
Reduced inequalities
Openalex Percentile: Top 7%
Geochemistry and Geologic Mapping
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.