Genetic Diversity Assessment in Rice Germplasm

Genetic diversity assessment in rice germplasm provides a foundation for enhanced crop resilience, yield potential and nutritional quality. Germplasm collections, comprising landraces, wild relatives and improved varieties, are analysed through a combination of morphological characterisation and molecular marker systems to reveal allelic variation, population structure and patterns of genetic differentiation. Simple sequence repeats (SSR) and single nucleotide polymorphisms (SNP) remain the principal tools for estimating gene diversity, polymorphism information content and heterozygosity across loci. Multivariate statistics such as principal component analysis, cluster analysis and analysis of molecular variance are deployed to define genetic relationships and infer population subdivisions. Insights gained from such studies enable breeders to select complementary parental lines for hybrid development, to identify unique alleles for introgression and to conserve valuable germplasm under changing climatic conditions. Recent advances in high-throughput sequencing and genotyping platforms have increased marker density and improved resolution of fine-scale genetic structure, strengthening the ability to dissect complex traits such as stress tolerance, nutritional profiling and yield stability.

Research from Nature Portfolio

Integrated morpho-molecular and nutritional profiling of aromatic Joha rice cultivars from Assam employed thirty-seven morphological descriptors alongside sixty-six polymorphic SSR markers to delineate genetic clusters corresponding to aroma, grain yield and nutritional indices. Principal component analysis explained over 85 % of variation, highlighting key contributors such as filled grains per panicle and stem thickness. Unique SSR alleles facilitated cultivar fingerprinting and identified accessions rich in iron and zinc for potential breeding. A complementary study on North Eastern Indian rice germplasm evaluated drought-tolerance and root architecture traits in 114 genotypes using sixty-five SSR markers. Multivariate analysis and AMOVA revealed three distinct subpopulations with significant differentiation. Genotypic data correlated with phenotypic measures of root volume and drought score, underlining the value of diverse germplasm in developing climate-resilient varieties.

Genetic Diversity Assessment in Rice Germplasm publication trend

The graph below shows the total number of articles in genetic diversity assessment in rice germplasm across all publications each year (not limited to Nature Index journals).

Technical terms

Germplasm: A collection of genetic resources for an organism, including seeds, tissues or whole plants, preserved for breeding and conservation.

SSR marker: A DNA marker based on variation in the number of repeated short sequence motifs, used to assess polymorphism at specific loci.

SNP: A single nucleotide polymorphism, representing a single base-pair variation in the genome, used for high-resolution genotyping.

Polymorphic Information Content (PIC): A measure of a marker’s informativeness based on the number and frequency of alleles detected.

Principal Component Analysis (PCA): A statistical technique that reduces multidimensional data into principal axes to reveal patterns of variation.

Analysis of Molecular Variance (AMOVA): A method that partitions genetic variation within and among predefined populations to quantify differentiation.

References

1. Morpho-molecular and nutritional profiling for yield improvement and value addition of indigenous aromatic Joha rice of Assam. Scientific Reports (2024).
2. Variability Assessment for Root and Drought Tolerance Traits and Genetic Diversity Analysis of Rice Germplasm using SSR Markers. Scientific Reports (2019).
3. Assessing the Genetic Diversity of Parents for Developing Hybrids Through Morphological and Molecular Markers in Rice (Oryza sativa L.). Rice (2024).
4. Genetic Diversity and Relationship of Shanlan Upland Rice Were Revealed Based on 214 Upland Rice SSR Markers. Plants (2023).
5. SSR and SNP Marker-Based Investigation of Indian Rice Landraces in Relation to Their Genetic Diversity, Population Structure, and Geographical Isolation. Agriculture (2023).