2010
DOI: 10.1007/s10681-010-0327-4
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Quantitative trait loci for seed dormancy in rice

Abstract: Seed dormancy (SD) is controlled by its own complicated genetic factors and environmental factors. SD is an important trait affecting grain yield and quality in cereal crops. A population comprising 240 recombinant inbred lines (RIL) was used for detecting quantitative trait locus (QTL) for SD in rice. To minimize the effect of environment, data for lines for which the optimum temperature during the late ripening stage is either below 20°C or above 30°C were excluded from the analysis, which left 185 lines. In… Show more

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Cited by 24 publications
(20 citation statements)
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“…We constructed a density plot of SNPs showing allelic differentiation between PHS resistant and susceptible accessions, finding different densities in different chromosomal regions. Some regions containing high numbers of these SNPs overlap with previously reported QTLs associated with PHS and seed dormancy; Region-1 and Region-2 of Chromosome-1, Region-3 of Chromosome-3, Region-6 of Chromosome-7, and Region-7 of Chromosome-12 overlap with previously reported QTLs and fine-mapped genes ( Miura et al, 2002 ; Dong et al, 2003 ; Takeuchi et al, 2003 ; Gu et al, 2004 , 2006 , 2010 ; Sugimoto et al, 2010 ; Jiang et al, 2011 ; Li et al, 2011 ; Lu et al, 2011 ; Marzougui et al, 2012 ). The most genome-wide germination associated loci reported by GWAS in rice germplasm ( Magwa et al, 2016 ) were included in the regions revealing high number of differential SNPs between PHS resistant and susceptible accessions.…”
Section: Discussionsupporting
confidence: 70%
See 2 more Smart Citations
“…We constructed a density plot of SNPs showing allelic differentiation between PHS resistant and susceptible accessions, finding different densities in different chromosomal regions. Some regions containing high numbers of these SNPs overlap with previously reported QTLs associated with PHS and seed dormancy; Region-1 and Region-2 of Chromosome-1, Region-3 of Chromosome-3, Region-6 of Chromosome-7, and Region-7 of Chromosome-12 overlap with previously reported QTLs and fine-mapped genes ( Miura et al, 2002 ; Dong et al, 2003 ; Takeuchi et al, 2003 ; Gu et al, 2004 , 2006 , 2010 ; Sugimoto et al, 2010 ; Jiang et al, 2011 ; Li et al, 2011 ; Lu et al, 2011 ; Marzougui et al, 2012 ). The most genome-wide germination associated loci reported by GWAS in rice germplasm ( Magwa et al, 2016 ) were included in the regions revealing high number of differential SNPs between PHS resistant and susceptible accessions.…”
Section: Discussionsupporting
confidence: 70%
“…Seven new PHS- and GI-associated loci (V2, S4, V5, S13, S21, S16, and S19) in the japonica group are not included among previously reported QTLs, whereas the Dynamin family protein gene (OS03G0260000), containing the S3 and S9 variations associated with GI, overlaps with reported QTLs including Sdr1 ( Takeuchi et al, 2003 ), qDT-SGC3.1 ( Jiang et al, 2011 ) and qSD-3 ( Guo et al, 2004 ). Among the three loci that are significantly associated with PHS in the indica group, S1, located on the short arm of chromosome-1, overlaps with reported QTLs including Sdr6 ( Marzougui et al, 2012 ), qSD-1 ( Miura et al, 2002 ), qSD1 ( Gu et al, 2004 , 2006 ), qDEG1 ( Li et al, 2011 ). We investigated the spatio-temporal expression patterns of genes harboring significant PHS- and GI-associated SNPs by surveying a publically available expression database (RiceXPro).…”
Section: Resultsmentioning
confidence: 82%
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“…However, only four seed dormancy QTLs were detected in a double haploid (DH) population [41]. Four [42] and nine [15] seed dormancy QTLs were identified by two different RIL populations, respectively. Second, it is easier to develop a secondary F 2 population derived from a cross between a CSSL line containing the target QTL and the recurrent parent for fine mapping [38,43].…”
Section: Seed Dormancy Qtl Analysismentioning
confidence: 99%
“…Thus, it is obvious that CSSLs have more power in QTL mapping as compared to other primary populations. Besides the performance of agronomic traits, Minghui 63 showed very different responses to low nitrogen, seed dormancy and bacteria blight resistance from Zhenshan 97 (Chen et al, 2002;Lian et al, 2005;Li et al, 2011). Thus, the set of CSSLs can be used for comprehensively evaluating these kinds of traits and mapping new QTLs.…”
mentioning
confidence: 99%