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Updated: Jun 18, 2025

Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits
Published on: January 3, 2025
Deciphering the genetic basis of agronomic, yield, and nutritional traits in rice (Oryza sativa L.) using a saturated
Mark Ian C Calayugan1,2, Tapas Kumer Hore1,2,3, Alvin D Palanog1,2,4
1Rice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines.
Abstract:
Developing high-yielding rice varieties that possess favorable agronomic characteristics and enhanced grain Zn content is crucial in ensuring food security and addressing nutritional needs. This research employed ICIM, IM, and multi-parent population QTL mapping methods to identify important genetic regions associated with traits such as DF, PH, NT, NP, PL, YLD, TGW, GL, GW, Zn, and Fe. Two populations of recombinant inbred lines consisting of 373 lines were phenotyped for agronomic, yield and grain micronutrient traits for three seasons at IRRI, and genotyped by sequencing. Most of the traits demonstrated moderate to high broad-sense heritability. There was a positive relationship between Zn and Fe contents. The principal components and correlation results revealed a significant negative association between YLD and Zn/Fe. ICIM identified 81 QTLs, while IM detected 36 QTLs across populations. The multi-parent population analysis detected 27 QTLs with six of them consistently detected across seasons. We shortlisted eight candidate genes associated with yield QTLs, 19 genes with QTLs for agronomic traits, and 26 genes with Zn and Fe QTLs. Notable candidate genes included CL4 and d35 for YLD, dh1 for DF, OsIRX10, HDT702, sd1 for PH, OsD27 for NP, whereas WFP and OsIPI1 were associated with PL, OsRSR1 and OsMTP1 were associated to TGW. The OsNAS1, OsRZFP34, OsHMP5, OsMTP7, OsC3H33, and OsHMA1 were associated with Fe and Zn QTLs. We identified promising RILs with acceptable yield potential and high grain Zn content from each population. The major effect QTLs, genes and high Zn RILs identified in our study are useful for efficient Zn biofortification of rice.
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