Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

Zeng, Yanwei; Ji, Zhijuan; Zhang, Wen; Liang, Yan; Yang, Chuanxi

doi:10.1371/journal.pone.0150832

Cited by 11 publications

(10 citation statements)

References 44 publications

(60 reference statements)

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“…Detailed information on the two F 2 , the F 3 , and two of the RIL (F 7 and F 8 ) mapping populations is given in Zeng et al [ 43 ]. Briefly, the first F 2 mapping population (n = 190 individuals) was planted in May 2011 and the second F 2 mapping population (n = 182 individuals) was sown in May 2012, both in Hangzhou, China; the F 3 mapping population (n = 160 lines, each including 18 individuals that were arranged in three rows with six plants each), deriving from the former F 2 populations, was planted in November 2012 in Hainan, China.…”

Section: Methodsmentioning

confidence: 99%

“…The strategy for identifying grain-weight-related QTLs followed the method described in Zeng et al [ 43 ]. Briefly, we first detected the QTLs responsible for grain weight using the three primary mapping populations (F 2 and F 3 populations), and then confirmed mapping results using four permanent mapping populations (F 7 to F 10 ).…”

Section: Methodsmentioning

confidence: 99%

“…Detailed information on these 179 markers is given in Wen et al [ 42 ]. The six grain-weight-related QTLs detected in these two populations (see Results section) were further examined in the F 2 populations planted in 2012 in Hangzhou, using 44 markers that covered the regions of these six QTLs, as described in Zeng et al [ 43 ].…”

Section: Methodsmentioning

confidence: 99%

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Combination of twelve alleles at six quantitative trait loci determines grain weight in rice

Zeng

Shi²,

et al. 2017

PLoS ONE

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Grain weight, which is controlled by quantitative trait loci (QTLs), is one of the most important determinants of rice yield. Although many QTLs for grain weight have been identified, little is known about how different alleles in different QTLs coordinate to determine grain weight. In the present study, six grain-weight-QTLs were detected in seven mapping populations (two F2, one F3, and four recombinant inbred lines) developed by crossing ‘Lemont’, a United States japonica variety, with ‘Yangdao 4’, a Chinese indica variety. In each of the six loci, one allele from one parent increased grain weight and one allele from another parent decreased it. Thus, the 12 alleles at the six QTLs were subjected to regression analysis to examine whether they acted additively across loci leading to a linear relationship between the predicted breeding value of QTL and phenotype. Results suggested that a combination of the 12 alleles determined grain weight. In addition, plants carrying more grain-weight-increasing alleles had heavier grains than those carrying more grain-weight-decreasing alleles. This trend was consistent in the seven mapping populations. Thus, these six QTLs might be used in marker-assisted selection of grain weight, by stacking different grain-weight-increasing or -decreasing alleles.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Combination of twelve alleles at six quantitative trait loci determines grain weight in rice

Zeng

Shi²,

et al. 2017

PLoS ONE

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“…Multiple interval mapping (MIM) was run in Windows QTL Cartographer 2.5 software (Wang et al 2012). The MIM model used for QTL analysis followed Zeng et al (2016). Detection of two or more QTLs in the same marker interval was defined as a QTL cluster.…”

Section: Multiple Interval Mapping and Statistical Analysismentioning

confidence: 99%

Control of plant height by 24 alleles at 12 quantitative trait loci in rice

Zeng

Chen

et al. 2019

Crop Breed. Appl. Biotechnol.

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Plant height (PH) is controlled by quantitative trait loci (QTLs) in rice. In the present study, a recombinant inbred line population developed by crossing two rice cultivars, Lemont and Yangdao4, was grown in eight environments for QTL analysis. Multiple interval mapping detected 53 PH-QTLs, 39 of which clustered at 12 chromosome regions/putative loci. An examination of the 12 putative loci identified 24 alleles that are simultaneously involved in controlling PH. Linear regression analyses suggested that these 24 alleles function additively across the 12 loci to control PH, and plants carrying more PH-increasing alleles at the 12 loci were taller than those carrying more PH-decreasing alleles. Multiple comparison tests indicated that the effect of a single allele at the 12 loci was small and that multiple alleles must be pyramided to attain a statistically significant effect. The closest markers to the 12 loci can be used directly in marker-assisted breeding to manipulate PH.

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“…In recent years, molecular markers have greatly aided breeding programs by allowing breeders to select for their trait of choice at the early stages of the rice plant. Several QTLs and functional markers have been reported for rice grain length (Fan et al, 2006, Wang et al, 2011, Zeng et al, 2016, grain width (Song et al, 2007, chalk (Zhao et al, 2015) and textural traits (Chen et al, 2008a, Chen et al, 2008b, Cuevas and Fitzgerald, 2012 and aroma (Bradbury et al, 2005a). With amylose being the predominant starch polymer in rice (Fitzgerald et al, 2009a), several genetic and molecular studies have been done to define the role of amylose in rice quality (Lugay and Juliano, 1965, Ward et al, 2006, Koroteeva et al, 2007.…”

Section: Introductionmentioning

confidence: 99%

Understanding the genetics and chemistry of important quality traits in rice (Oryza sativa L.)

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Rice grain quality is a determinant of rice breeding success. Although several studies have independently looked at the different traits of quality to infer the phenotype of the grain, few studies have identified the various metabolites that are produced in high quality rice. In recent years, genetic markers have proven to be effective in increasing the efficiency of breeding line selection and therefore shortening the breeding cycle. In complex traits such as rice grain quality, the availability of more specific phenotypes will increase the value of these genetic markers. Many traits of quality in rice are associated with starch; however, lipids interact with starch and have been shown to influence many of the traits of eating quality and aroma. To identify these new phenotypes and understand their genetic basis, using relevant tools that can discriminate between the phenotypes of varieties at the metabolite and genetic levels is necessary. To identify these new phenotypes, in Chapter 3, a set of 40 Cambodian rice varieties were screened for physical and texture-associated traits including apparent amylose content (AAC), gelatinisation temperature (GT), gel consistency (GelCon) and pasting properties and then a subset from this set was screened for volatile compounds using a two-dimensional gas chromatography-time-of-flightmass spectrometer (GC×GC-TOF-MS) and fatty acids (FA) using gas chromatography-mass spectrometry (GC-MS). The FA analysis showed that unsaturated FA (UFA) oleic (C18:1n-9) and linoleic acid (C18:2n-6) were the most abundant in milled rice grains, followed by palmitic acid (C16:0). These results infer about the lipid origin of odour-active volatile compounds, which were found to be characterising the group of known fragrant, low amylose and soft-textured rice varieties, including the Jasmine-style indica variety Phka Rumduol (PRD). To identify the genetic determinants of these important traits of quality, in Chapters 4 and 5, quantitative trait loci (QTL) mapping was carried out for the texture and aroma traits in PRD using a population of about 300 F6 recombinant-inbred lines (RIL) derived from an intraspecific cross between PRD and Thmar Krem (TMK), both of which were identified as the most discriminating varieties in Chapter 3. This RIL population was genotyped for single nucleotide polymorphisms (SNPs). QTL analysis revealed large-effect QTLs for AAC, GT and all of the pasting properties. Candidate genes for these QTLs relate back to the starch biosynthesis pathways. Major QTLs were colocalised to the Waxy (Wx) gene and starch synthase IIa (SSIIa) on chromosome 6. Minor QTLs on chromosomes 3 and 8 were identified for AAC, SB, PV and HPC, and at chromosomes 4 and 7 for GT and pasting temperature (PTemp). This chapter has shown that the rice texture is regulated by multiple genes and that although correlations do exist among the routinely measured textural traits, these correlations may not necessarily translate into the already existing molecular markers. Publications included in this thesis...

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Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

Cited by 11 publications

References 44 publications

Combination of twelve alleles at six quantitative trait loci determines grain weight in rice

Combination of twelve alleles at six quantitative trait loci determines grain weight in rice

Control of plant height by 24 alleles at 12 quantitative trait loci in rice

Understanding the genetics and chemistry of important quality traits in rice (Oryza sativa L.)

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