Authors
Om Prakash Raigar, Gaurav Augustine, Neha Kumari, Vikas Kumar Verma, Gursewak Singh, Shah Mohammad Usman, V Shasi Kiran Reddy, Karthikeyan Thiyagarajan, Prabhjot Singh, Renu Khhana, Neeraj Rani, Asif Bashir Shikari, Pradeep Kumar Bhati, Rupinder Kaur, Nitika Sandhu
Published in
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik. Volume 139. Issue 8. Jul 11, 2026. Epub Jul 11, 2026.
Abstract
Iron (Fe) and zinc (Zn) deficiencies frequently limit nutrient acquisition and grain micronutrient accumulation in rice grown under direct-seeded rice (DSR) systems due to reduced micronutrient availability in aerobic soils. Understanding the genetic architecture controlling micronutrient uptake and its association with root system architecture (RSA) is critical for developing nutrient-efficient rice varieties. In this study, a diverse panel of 290 rice genotypes was evaluated for RSA, agronomic traits, and grain Fe and Zn concentration under DSR conditions across three years. Genome-wide association analysis using 18,639 high-quality SNP markers identified 118 significant marker-trait associations distributed across the rice genome. Several loci exhibited pleiotropic effects, linking RSA traits with grain micronutrient accumulation and yield-related traits. Notably, multiple genomic regions co-localized with previously reported QTLs and key genes involved in metal homeostasis, including OsIRO2, OsNAS, OsYSL, OsZIP, OsHMA2, and OsVIT1, suggesting conserved regulatory mechanisms controlling Fe and Zn uptake. Expression profiling under Fe and Zn deficiency further revealed differential regulation of transcription factors and metal transporters between nutrient-efficient and inefficient genotypes, indicating genotype-specific adaptive responses to micronutrient stress. These findings provide insights into the genetic basis of micronutrient uptake and identify promising donors, genomic regions and candidate genes for marker-assisted breeding of nutrient-efficient rice varieties adapted to DSR cultivation systems.
PMID:
42436329
Bibliographic data and abstract were imported from PubMed on 12 Jul 2026.
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