QTLs for rice flag leaf traits in doubled haploid populations in different environments

Cai, Jing; Zhang, M.; Guo, Longbiao; Li, X.M.; Bao, Jinsong; Ma, Liangyong

doi:10.4238/2015.june.18.21

Cited by 16 publications

(11 citation statements)

References 21 publications

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“…These data indicate that the semi dwarf genes are probably the major QTLs responsible for the pleiotropic phenotypes. In comparison with previous reports (Hittalmani et al, 2002;Hori et al, 2012;Cai et al, 2015), QTLs for PH and yield-related traits were usually detected on these chromosomal regions. Another two QTL clusters on chromosomes 2 and 3 were collocated for several yield and yield-related traits including TGW and GW traits, and their alleles were all from 'TD70' and had enhancing effects.…”

Section: Discussioncontrasting

confidence: 85%

“…Recently, studies of QTL mapping for panicle-and yield-related traits have been performed in rice (Liu et al, 2012;Bian et al, 2013;Cai et al, 2015), allowing several important agronomic genes such as qSH1, PLOG1, and qSW5 to be cloned and functionally analyzed (Konishi et al, 2006;Weng et al, 2008;Wang and Li, 2011), which are of great significance for rice breeding and genomics. PE is a typically and quantitatively inherited trait in mapping populations derived from different rice varieties with natural allelic variation (Yamamoto et al, 2001;Qiao et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of QTLs for panicle exsertion and its relationship with yield and yield-related traits in rice (Oryza sativa L.)

Zhao¹,

Chen²,

QingYong³

et al. 2016

Genet. Mol. Res.

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ABSTRACT. Panicle exsertion (PE) is an important morphological trait that is closely associated with spikelet fertility and grain yield. To understand the genetic basis of PE and its relationships with yield and yield-related traits, a recombinant inbred population consisting of 240 lines derived from a cross between an Indica cultivar 'Kasalath' and a Japonica germplasm 'TD70', was studied over two years. PE was significantly correlated with plant height, heading date (HD), panicle length (PL), and panicle characteristics such as primary branch number, spikelet number per panicle, and spikelet density, but showed poor correlation with yield components. Based on linkage mapping of 141 SSR markers, a total of 38 quantitative trait loci (QTLs) were located for 12 investigated traits, with the contribution varying from 6.51 to 8.61%. Among these, four QTL clusters were identified on chromosomes 1, 2, 3, and 6, suggesting the existence of pleiotropic alleles. In some intervals, two loci for PE were collocated with several traits, which is consistent with the correlations observed with phenotypic variations. The PE QTLs with 'Kasalath' alleles and without pleiotropic effects would be valuable for the improvement of PE in 'TD70' and in other rice varieties.

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Section: Discussioncontrasting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Analysis of QTLs for panicle exsertion and its relationship with yield and yield-related traits in rice (Oryza sativa L.)

Zhao¹,

Chen²,

QingYong³

et al. 2016

Genet. Mol. Res.

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“…Canopy height in turfgrasses is a function of both stem and leaf extension, a fact that was evident from several significant correlations between HT, stolon (particularly ILEN), and leaf traits (particularly LLEN), further supported by a number of coincident QTL among traits (more so with ILEN and LLEN). Significant positive correlation between plant height and leaf length was also reported in rice (Cui et al 2002; Yan et al 1999), switchgrass (Sripathi et al 2013), and perennial ryegrass (Yamada et al 2004), and co-localized QTL were also evident in some studies (Cai et al 2015; Yan et al 1999), suggesting that the genetic basis of plant height and leaf length are partially overlapping. In the current study, four markers were significantly linked with both traits - two of which were also detected by CIM.…”

Section: Discussionmentioning

confidence: 74%

“…However, QTL colocalization between leaf traits is often lacking or limited, as observed in the current study. QTL correspondence was completely lacking in perennial ryegrass (Yamada et al 2004), centipedegrass (Wang et al 2014), sorghum (Lu et al 2011), and Brachiaria (Thaikua et al 2016), while few colocalized QTL were reported in rice (Cai et al 2015; Liu et al 2015; Wang et al 2012; Yan et al 1999; Zhang et al 2015a) and wheat (Wu et al 2016). In a maize nested association mapping (NAM) population, leaf length and width displayed weak correlations and largely discrete putative causative variants underlying the traits (Tian et al 2011).…”

Section: Discussionmentioning

confidence: 99%

Molecular Dissection of Quantitative Variation in Bermudagrass Hybrids (Cynodon dactylonxtransvaalensis): Morphological Traits

Khanal

Dunne

Schwartz

et al. 2019

G3 Genes|Genomes|Genetics

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Bermudagrass ( Cynodon (L.)) is the most important warm-season grass grown for forage or turf. It shows extensive variation in morphological characteristics and growth attributes, but the genetic basis of this variation is little understood. Detection and tagging of quantitative trait loci (QTL) affecting above-ground morphology with diagnostic DNA markers would provide a foundation for genetic and molecular breeding applications in bermudagrass. Here, we report early findings regarding genetic architecture of foliage (canopy height, HT), stolon (stolon internode length, ILEN and length of the longest stolon LLS), and leaf traits (leaf blade length, LLEN and leaf blade width, LW) in 110 F 1 individuals derived from a cross between Cynodon dactylon (T89) and C. transvaalensis (T574). Separate and joint environment analyses were performed on trait data collected across two to five environments (locations, and/or years, or time), finding significant differences ( P < 0.001) among the hybrid progeny for all traits. Analysis of marker-trait associations detected 74 QTL and 135 epistatic interactions. Composite interval mapping (CIM) and mixed-model CIM (MCIM) identified 32 main effect QTL (M-QTL) and 13 interacting QTL (int-QTL). Colocalization of QTL for plant morphology partially explained significant correlations among traits. M-QTL qILEN-3-2 (for ILEN; R 2 = 11–19%), qLLS-7-1 (for LLS; R 2 = 13–27%), qLEN-1-1 (for LLEN; R 2 = 10–11%), and qLW-3-2 (for LW; R 2 = 10–12%) were ‘stable’ across multiple environments, representing candidates for fine mapping and applied breeding applications. QTL correspondence between bermudagrass and divergent grass lineages suggests opportunities to accelerate progress by predictive breeding of bermudagrass.

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“…With the technology development of molecular biology and molecular markers, the molecular genetic maps for many kinds of plants, such as rice (Cai et al, 2015), maize (Zheng and Liu, 2013), pumpkin (Ge et al, 2015), and pepper (Moulin et al, 2015), have been constructed. In addition, finished quantitative trait locus (QTL) mapping for a variety of traits, greatly explained the genetic mechanisms of these traits.…”

Section: Introductionmentioning

confidence: 99%

Molecular genetic map construction and QTL analysis of fruit maturation period in grapevine

Zhao

Guo

Ma³

et al. 2016

Genet. Mol. Res.

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ABSTRACT. In this study, we aimed at finding the genetic regularity of grape maturation period. Early-maturing grapevine, "87-1", was used as the female parent and late-maturing, "9-22", as the male parent, to create an F1 hybrid population. A total of 149 individual plants and their parents were selected as the mapping population. Sequencerelated amplified polymorphism and simple-sequence repeat analyses were performed. We performed a linkage analysis and constructed a molecular genetic map. In the obtained map, the female and male parents each covered 19 linkage groups containing 188 and 175 maker loci, respectively. The total map distances for the female and male parents were 1074.5 and 1100.2 cM, respectively, whereas the average genetic distances between each two loci were 5.7 and 7.8 cM, respectively. The interval-mapping method was used in a quantitative trait locus (QTL) analysis for fruit maturation period. A total of 12 QTLs associated with fruit maturation period were detected. These included four QTLs in the male parent genetic map that were located in linkage groups M5, M11, M14-1, and M16, with a 62.6-75.7% rate of contribution of each QTL. Another three QTLs were found in the female parent genetic map, located in linkage groups F6, F14-1, and F18, with a 72.7-77.7% rate of contribution of each QTL. Five more QTLs were detected in the consensus map, located in linkage groups LG11, LG14-1, LG16, LG17, and LG18, with 8.9-75.7% phenotypic variance explained by each QTL.

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QTLs for rice flag leaf traits in doubled haploid populations in different environments

Cited by 16 publications

References 21 publications

Analysis of QTLs for panicle exsertion and its relationship with yield and yield-related traits in rice (Oryza sativa L.)

Analysis of QTLs for panicle exsertion and its relationship with yield and yield-related traits in rice (Oryza sativa L.)

Molecular Dissection of Quantitative Variation in Bermudagrass Hybrids (Cynodon dactylonxtransvaalensis): Morphological Traits

Molecular genetic map construction and QTL analysis of fruit maturation period in grapevine

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