Journal of Innovative Agriculture, Volume 12, Issue 1 : 18-27 . Doi : 10.37446/jinagri/rsa/12.1.2025.18-27

Research Article

OPEN ACCESS | Published on : 31-Mar-2025

Genome-wide association study for composite performance index in rice (Oryza sativa L.)

• Raveendran Muthurajan
• Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore - 641003, India.

Williams Mohanavel
• Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore - 641003, India.

Ameena Premnath
• Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore - 641003, India.

Bharathi Ayyenar
• Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore - 641003, India.

Veera Ranjani Rajagopalan
• Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore - 641003, India.

Sudha Manickam
• Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore - 641003, India.

Abstract

Background: A critical step to maximize the usefulness of genome-wide association studies (GWAS) in plant breeding is the identification and validation of candidate genes underlying genetic associations. Once strong candidates are identified, further validation helps confirm whether the gene truly influences the trait. This process strengthens confidence in marker-trait relationships and enables the development of more precise molecular markers or genomic prediction models for crop improvement.

Methods: Genome-wide association study (GWAS) was conducted on a panel of 100 genetically diverse rice genotypes to dissect the genetic architecture of the Composite Performance Index (CPI), a multivariate principal component score integrating all major agronomic traits. 

Results: Full annotation of all six significant SNPs revealed perfect convergence on four biologically coherent functional modules. Four reproducible quantitative loci (CPI-1, CPI-4, CPI-8 and CPI-11) were identified, explaining the major gradients in field performance. These loci encompass biologically coherent modules linked to energy metabolism, growth regulation, cell-wall integrity and dehydration response. Favourable alleles were located on chromosomes 8 and 11 contributing +1.12 and +1.38 CPI units, respectively. Unfavourable alleles on chromosomes 1 and 4 were associated with stress response and growth-defense trade-offs. The combined fixation of favourable haplotypes from CPI-8 and CPI-11 while purging unfavourable alleles from CPI-1 and CPI-4 predicted a +2.5 CPI gain representing the top 1% ideotype.

Conclusion: The two tightly linked SNPs on chromosome 8 (separated by only 1,069 bp) tag the identical haplotype and are therefore merged into a single locus (CPI-8). No additional loci reached genome-wide significance, confirming that CPI is controlled by a compact, high-impact genetic architecture amenable to rapid marker-assisted pyramiding. The compact genetic basis uncovered in this study provides a practical foundation for marker-assisted selection and genomic designing of high-performing rice varieties.

Keywords

rice, GWAS, COMPOSITE Performance Index (CPI), SNPs, genomic designing

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