Genetic and molecular dissection of quantitative traits in rice

Yano, Masahiro; Sasaki, Takuji

doi:10.1007/978-94-011-5794-0_14

Cited by 110 publications

(101 citation statements)

References 53 publications

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“…For the second step, the LOD peaks (> 2.0), of which the nearest RFLP marker showed P < 0.01, were accepted as QTLs. This threshold has also been commonly used in recent singlepoint QTL analyses (Yano and Sasaki 1997). Moreover, we only focused on the genomic regions that repeatedly showed QTLs for a trait across crop seasons to confirm our analysis.…”

Section: Qtl Mappingmentioning

confidence: 79%

“…For the first step, all the visible LOD peaks > 2.0 were located, including that near the highest peak. This threshold is suitable for detecting relatively minor-effect genes in avoiding a false positive effect (Yano and Sasaki 1997). For the second step, the LOD peaks (> 2.0), of which the nearest RFLP marker showed P < 0.01, were accepted as QTLs.…”

Section: Qtl Mappingmentioning

confidence: 99%

“…The recent development of molecular markers has enabled to identify gene loci affecting quantitative traits, such as days to heading, culm length (CL) and panicle number (PnN), on a linkage map in rice (Yano and Sasaki 1997). The response of such an agronomically important quantitative trait locus (QTL) to the growth environments has been demonstrated by Yan et al (1999), Yamamoto et al (2000) and Kobayashi et al (2003) who conducted QTL analyses across different locations.…”

Section: Introductionmentioning

confidence: 99%

“…M23 has a long, wide and erect flag leaf, compared with AK. Since these two varieties have been used in actual breeding programs (Yokoo et al 1994), QTL mapping using the M23/AK cross would possibly disclose a typical genetic nature (background) underlying the different types of flag leaf development (Yano and Sasaki 1997). In this study, recombinant inbred lines (RILs) derived from the M23/AK cross were grown during the cropping season in Joetsu, Japan (temperate zone), and during the dry and wet seasons in Los Baños, Philippines (tropical zone), to map QTLs for FLL, FLW and FLA.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Trait Loci Affecting Flag Leaf Development in Rice (Oryza sativa L.)

et al. 2003

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One hundred and ninety-one recombinant inbred lines (RILs) (F 7 ) derived from a cross between Milyang 23 (M23) and Akihikari (AK) were grown in 1997 in Joetsu, Japan (temperate zone), and during the 2000-01 dry and wet seasons (four consecutive seasons) in Los Baños, Philippines (tropical zone) to detect quantitative trait loci (QTLs) for flag leaf length, width and angle (FLL, FLW and FLA) of rice (Oryza sativa L.). The detected QTLs suggested that flag leaf development was influenced by nine genomic regions categorized into three groups. In Group I, three regions (chromosomes 1, 4 and 6) increased both FLL and FLW. The QTL profiles showed that the effects of these three regions were powerful and stable across locations. Especially, the effect of the region on chromosome 4 (the nearest RFLP marker, XNpb235) accounted for 9-17 % and 20-26 % of the FLL and FLW variances, respectively. In Group II, four regions (chromosomes 2, 3, 10 and 11) affected FLL, whereas in Group III, two regions (chromosomes 8 and 12) affected FLW. The detection pattern of QTLs showed that three regions in Groups II and III (chromosomes 3, 10 and 12) were expressed by the growth conditions of Los Baños. No region with a clear effect on FLA was identified, although this trait was segregated largely in the RILs. By characterizing the nine regions in detail, this paper elaborates on the genetic factors and mechanisms controlling flag leaf development.

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Section: Qtl Mappingmentioning

confidence: 79%

Section: Qtl Mappingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantitative Trait Loci Affecting Flag Leaf Development in Rice (Oryza sativa L.)

et al. 2003

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“…Naturally occurring allelic diversity in plants has been suggested to be an important genetic component for phenotypic variation (Doebley and Lukens, 1998;Buckler and Thornsberry, 2002). In contrast with induced mutations that eliminate or cause a large reduction of a functional gene product, naturally occurring allelic variation modulates gene products and may be an underlying mechanism for quantitative trait variation (Tanksley, 1993;Yano and Sasaki, 1997;Mackay, 2001). A large amount of nucleotide sequence data has been generated as facilitated by recent advances in DNA sequencing technology.…”

Section: Introductionmentioning

confidence: 99%

Allelic Variation of Gene Expression in Maize Hybrids[W]

et al. 2004

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Allelic expression variation of nonimprinted autosomal genes has recently been uncovered in mouse hybrids and humans. The allelic expression variation is attributed to differences in noncoding DNA sequences and does not involve epigenetic regulation or gene imprinting. This expression variation is suggested to play important roles in determining phenotypic diversity. Virtually nothing is known about such allele-specific expression variation in a hybrid plant where two alleles are compared in the same genetic context. We examined parental transcript accumulation in maize (Zea mays) hybrids using allele-specific RT-PCR analysis. Among 15 genes analyzed, 11 showed differences at the RNA level, ranging from unequal expression of the two alleles (biallelic) to expression of a single allele (monoallelic). Maternal or paternal transmission had little effect on the allele-specific transcript ratio of nearly all genes analyzed, suggesting that parent-of-origin effect was minimal. We analyzed the allelic difference in genetically contrasting hybrids and hybrids under high planting density and drought stress. Whereas a genetically improved modern hybrid expressed both alleles, a less improved old hybrid frequently showed mono-allelic expression. Furthermore, the two alleles in the hybrid responded differentially to abiotic stresses. The results of allele-specific regulation in different tissues in responding to environment and stress suggest an unequivalent function of the parental alleles in the hybrid, which may have an impact on heterosis.

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Population Based Linkage Disequilibrium Mapping of QTL: An Application to Simulated Data in an Isolated Population

Zhao

Xiong

2001

Genetic Epidemiology

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Despite successes in mapping and cloning genes involved in rare Mendelian diseases, genetic dissection of quantitative traits into single Mendelian factors still remains a challenging task. As the dense map of single nucleotide polymorphism (SNP) markers becomes available in the near future, linkage disequilibrium (LD) mapping will become one of major tools for mapping and identifying quantitative trait loci (QTL). In this report, we present a population-based linkage disequilibrium mapping of QTL. This method unifies the analysis of mapping QTL in humans and in model organisms and can be used for randomly sampled individuals. The proposed method is applied to search for polymorphism sites within the candidate genes 2 and 6, which influence quantitative traits Q1 and Q2 or Q5, in a simulated data set in an isolated population.

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Genetic and molecular dissection of quantitative traits in rice

Cited by 110 publications

References 53 publications

Quantitative Trait Loci Affecting Flag Leaf Development in Rice (Oryza sativa L.)

Quantitative Trait Loci Affecting Flag Leaf Development in Rice (Oryza sativa L.)

Allelic Variation of Gene Expression in Maize Hybrids[W]

Population Based Linkage Disequilibrium Mapping of QTL: An Application to Simulated Data in an Isolated Population

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