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Unveiling genetic basis of seedling emergence from deep soil depth under dry direct- seeded conditions in rice (Oryza sativa L.)
Unveiling genetic basis of seedling emergence from deep soil depth under dry direct- seeded conditions in rice (Oryza sativa L.)
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Unveiling genetic basis of seedling emergence from deep soil depth under dry direct- seeded conditions in rice (Oryza sativa L.)
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Unveiling genetic basis of seedling emergence from deep soil depth under dry direct- seeded conditions in rice (Oryza sativa L.)
Unveiling genetic basis of seedling emergence from deep soil depth under dry direct- seeded conditions in rice (Oryza sativa L.)

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Unveiling genetic basis of seedling emergence from deep soil depth under dry direct- seeded conditions in rice (Oryza sativa L.)
Unveiling genetic basis of seedling emergence from deep soil depth under dry direct- seeded conditions in rice (Oryza sativa L.)
Journal Article

Unveiling genetic basis of seedling emergence from deep soil depth under dry direct- seeded conditions in rice (Oryza sativa L.)

2025
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Overview
Water scarcity and labor shortage pose significant challenges in rice farming. Direct-seeded rice (DSR) is an efficient method that conserves water, reduces labor costs, and allows for full mechanization of cultivation. However, variable planting depth in undulated field leading to deep/shallow sowing of rice seeds during mechanical sowing presents a major hurdle, as existing varieties lack tolerance to deep sowing. To address this, a mapping population comprising 150 F 4 lines, derived from MTU 1010 and AUS295, was developed and phenotyped for emergence from deep soil depth-related traits, including days of emergence (DE), percent germination (PG), mesocotyl length (ML), and coleoptile length (CL). The correlation revealed that DE has a significant negative correlation with PG, ML, and CL, whereas PG, ML, and CL are all positively correlated with each other. The mapping population was genotyped with mid-density SNP assay (1k-RiCA), and a linkage map was established with 414 polymorphic SNP markers. A total of 16 QTLs were identified for four traits, with phenotypic variance explained (PVE) ranging from 6.63% to 19.6% in the WS22. These included 5 QTLs for DE, 3 QTLs for PG, 4 QTLs for ML, and 4 QTLs for CL. Out of 16 QTLs identified, 12 were major effect QTLs ( qDE 1.2 , qDE 1.3 , qDE 1.4 , qDE 2.1 , qDE 12 , qPG 2.1 , qPG 2.2 , qML 2.1 , qML 2.2 , qCL 1 , qCL 2.2 , qCL 2.3 ) and 4 were minor effect QTLs ( qPG 1 , qML 1.2 , qCL 2.1 ). During DS23 season, QTL analysis for DE and PG traits identified seven and three QTLs, respectively. Out of the ten QTLs identified in DS23 season, eight were stable across the season. This study reported 11 novel QTLs, while 7 had been previously reported. The study pinpointed three QTL hotspot regions: one on chromosome 1 ( qPG 1 , qCL 1 ) and two on chromosome 2 ( qPG 2.1 , qML 2.2 , qCL 2.1 ) and ( qPG 2.2 , qCL 2.2 ). Candidate gene analysis in the identified QTL regions found two genes associated with hormonal pathways: OsSLR1 for gibberellin signaling and OsSAUR11 for abscisic acid signaling. Additionally, one gene ( OsMT3a ) associated with early seedling vigor and another ( OsABA8ox1 ) regulates germination through coleoptile growth. The identified QTLs, genes, and breeding lines from this study provide valuable resources for developing rice varieties with enhanced tolerance to deep soil emergence, making them well-suited for mechanized DSR systems.