S-Space College of Agriculture and Life Sciences (농업생명과학대학) Dept. of Plant Science (식물생산과학부) Journal Papers (저널논문_식물생산과학부)
Quantitative Trait Locus Mapping and Candidate Gene Analysis for Functional Stay-Green Trait in Rice
- Lim, Jung-Hyun; Paek, Nam-Chon
- Issue Date
- Korean Society of Breeding Science
- Plant breeding and biotechnology, vol.3 no.2, pp. 95-107
- Candidate gene; Functional stay-green; Heading date; Quantitative trait locus; Rice; Whole genome re-sequencing
- This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Functional stay-green (FSG) delays leaf yellowing, maintaining photosynthetic competence, whereas nonfunctional stay-green (NFSG) retains only leaf greenness without sustaining photosynthetic activity. Retention of chlorophylls and photosynthetic capacity is important for increasing crop yield. We determined the main-effect quantitative trait loci (QTLs) for FSG traits in the japonica rice SNU-SG1 and isolated candidate genes. To identify QTLs influencing FSG, we analyzed eight traits: (1) 1 day after heading-degree of chlorophyll content of flag leaf, (2) 1 day after heading-degree of chlorophyll content of second leaf, (3) 1 day after heading-degree of chlorophyll content of flag and second leaves, (4) 50 day after heading-degree of chlorophyll content of flag leaf, (5) 50 day after heading-degree of chlorophyll content of second leaf, (6) 50 day after heading-degree of chlorophyll content of flag and second leaves, (7) relative decline degree of chlorophyll content of flag and second leaves, and (8) flowering time. We carried out QTL analysis with F7 RIL from a cross of japonica rice ‘SNU-SG1’ and indica rice ‘Milyang23 (M23)’. Using 131 molecular markers, we identified 18 QTLs for the eight traits with a threshold LOD value > 2.8. Sequence analysis identified 16 candidate genes for 10 main-effect QTLs. Of these, we have chosen seven strong candidate genes for the 10 main-effect QTLs. These genetic resources will be useful for breeding high-yielding rice cultivars.