Genetic mapping of a QTL controlling leaf width and grain number in rice

Tian, Yonghang; Hong-yu, Zhang; Xu, Peizhou; Chen, Xiaoqiong; Liao, Yongxiang; Han, Bei‐Zhong; Chen, Xiangbin; Fu, Xiang‐Dong; Wu, Xiaoyun

doi:10.1007/s10681-014-1263-5

Cited by 28 publications

(18 citation statements)

References 42 publications

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“…The flag leaf is the most important source organ for synthesis and output of assimilates during the reproductive stage, and is responsible for regulating final plant growth and yield formation in cereal crops [ 4 , 5 ]. The morphological attributes of flag leaves, such as FLL, FLW, FLA and BAFL, are therefore critical factors in determining a desirable plant type [ 43 ], and also sense environmental signals for adaptation [ 4 , 5 ]. In this study, ANOVA clearly showed that phenotypic means of tested traits in a RIL population were more affected by both water regime and environment factors.…”

Section: Discussionmentioning

confidence: 99%

“…Grain yield in cereal crops is due to complex physiological and biochemical processes but is essentially associated with the carbohydrate accumulation process of grain filling, which in turn is attributed to leaf functionalities [ 4 ]. By contrast to other leaves in the duration of reproductive phase, flag leaves are the main organ for photosynthesis, providing the major assimilate source required for plant growth and panicle development and also sensing environmental signals for adaptation [ 4 , 5 ]. For example, under favorable conditions and depending on wheat genotype, the wheat flag leaf contributes 45–58 % of photosynthetic performance [ 6 ] and 41-43 % of assimilates used in grain filling after flowering [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…This understanding will provide knowledge on how genes/QTLs underlying phenotypic variation are modulated. Much effort has already been exerted to uncover the genetic mechanism for such traits in cereal crops [ 5 , 23 – 25 ]. Early studies showed that FLM-related traits were under additive control combined with partial dominance and epistasis [ 14 , 26 ], or even predominantly controlled by complex epistatic interactions, dominance, and additive × dominance variation [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

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Genetic dissection of flag leaf morphology in wheat (Triticum aestivum L.) under diverse water regimes

et al. 2016

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Background: Morphological traits related to flag leaves are determinant traits influencing plant architecture and yield potential in wheat (Triticum aestivum L.). However, little is known regarding their genetic controls under drought stress. One hundred and twenty F 8 -derived recombinant inbred lines from a cross between two common wheat cultivars Longjian 19 and Q9086 were developed to identify quantitative trait loci (QTLs) and to dissect the genetic bases underlying flag leaf width, length, area, length to width ratio and basal angle under drought stress and well-watered conditions consistent over four environments. Results: A total of 55 additive and 51 pairs of epistatic QTLs were identified on all 21 chromosomes except 6D, among which additive loci were highly concentrated in a few of same or adjacent marker intervals in individual chromosomes. Two specific marker intervals of Xwmc694-Xwmc156 on chromosome 1B and Xbarc1072-Xwmc272 on chromosome 2B were co-located by additive QTLs for four tested traits. Twenty additive loci were repeatedly detected in more than two environments, suggestive of stable A-QTLs. A majority of QTLs involved significant additive and epistatic effects, as well as QTL × environment interactions (QEIs). Of these, 72.7 % of additive QEIs and 80 % of epistatic QEIs were related to drought stress with significant genetic effects decreasing phenotypic values. By contrast, additive and QEIs effects contributed more phenotypic variation than epistatic effects. Conclusions: Flag leaf morphology in wheat was predominantly controlled by additive and QEIs effects, where more QEIs effects occurred in drought stress and depressed phenotypic performances. Several QTL clusters indicated tight linkage or pleiotropy in the inheritance of these traits. Twenty stable QTLs for flag leaf morphology are potentially useful for the genetic improvement of drought tolerance in wheat through QTL pyramiding.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genetic dissection of flag leaf morphology in wheat (Triticum aestivum L.) under diverse water regimes

et al. 2016

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“…Delayed leaf senescence is another drought adaptive trait in wheat to sustain yield through maintaining photosynthetic capacity and the supply of assimilates to the grain for a longer period of time (Chen et al., ). To avoid excessive transpirational loss in rice under drought conditions, LA, LL, LW and LS traits were decreased (Biswal and Kohli, ; Tian et al., ; Wang, ). In this regard, obtaining optimal leaf architecture could be an important target for breeding drought‐tolerant cereal crops, especially in terminal drought stress.…”

Section: Introductionmentioning

confidence: 99%

QTL mapping for six ear leaf architecture traits under water‐stressed and well‐watered conditions in maize (Zea mays L.)

et al. 2018

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Morphological traits for ear leaf are determinant traits influencing plant architecture and drought tolerance in maize. However, the genetic controls of ear leaf architecture traits remain poorly understood under drought stress. Here, we identified 100 quantitative trait loci (QTLs) for leaf angle, leaf orientation value, leaf length, leaf width, leaf size and leaf shape value of ear leaf across four populations under drought‐stressed and unstressed conditions, which explained 0.71%–20.62% of phenotypic variation in single watering condition. Forty‐five of the 100 QTLs were identified under water‐stressed conditions, and 29 stable QTLs (sQTLs) were identified under water‐stressed conditions, which could be useful for the genetic improvement of maize drought tolerance via QTL pyramiding. We further integrated 27 independent QTL studies in a meta‐analysis to identify 21 meta‐QTLs (mQTLs). Then, 24 candidate genes controlling leaf architecture traits coincided with 20 corresponding mQTLs. Thus, new/valuable information on quantitative traits has shed some light on the molecular mechanisms responsible for leaf architecture traits affected by watering conditions. Furthermore, alleles for leaf architecture traits provide useful targets for marker‐assisted selection to generate high‐yielding maize varieties.

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“…In cereal crops, the top three leaves on the stem, especially flag leaf are the primary source of carbohydrates production (Sicher, 1993). The flag leaf could produce a large proportion of the carbohydrates stored in grains, and it is responsible for regulating final plant growth and yield formation in cereal crops (Biswal and Kohli, 2013;Tian et al, 2015;Yang et al, 2016). Therefore, flag leaf characteristics have been considered to be important determinants of grain yield in cereals crops including wheat (Chen et al, 1995;Hirota et al, 1990;Simon, 1999).…”

Section: Introductionmentioning

confidence: 99%

Phenotypic Selection and Bulked Segregant Analysis for Flag Leaf Angle under Heat Stress in Bread Wheat (Triticum aestivum L.)

2016

AJAS

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Divergent phenotypic selection was performed for flag leaf angle (FLAN) under heat stress in five F 2 populations of bread wheat (Triticum aestivum L.). Direct responses for FLAN and correlated responses for grain yield per plant (GYP) and thousand kernel weight (TKW) were measured. FLAN was positively and significantly correlated with GYP and TKW under heat stress. Positive and highly significant (P<0.01) responses to selection for FLAN were obtained in both directions for the five populations, which were higher in magnitude in the low direction (averaged 31.41) than those obtained in the high direction (averaged 22.0%). Selection for high FLAN produced concurrent positive and significant (P<0.05) responses in GYP in only two populations, with an average of 5.17%, which was lower in magnitude than averaged correlated responses (8.24%) obtained in GYP for lower FLAN in four populations. Significant (P<0.05) correlated responses to selection in TKW for higher FLAN were obtained in four populations (averaged 4.03%) and were smaller in magnitude than those obtained for lower FLAN (averaged 9.56%). Additive gene effects were found to be mainly controlling FLAN. Moderate realized heritability estimates obtained for FLAN (averaged 0.53) were similar to heritability obtained by parent-offspring regression (averaged 0.50). Bulked segregant analysis (BSA) using twelve simple sequence repeats (SSR) markers for FLAN identified three SSR markers, namely Xgwm294-2A; Xbarc113-6A and Xwmc398-6B were able to distinguish high from low bulks in at least two populations. Three bands specific for high and two specific for low FLAN were generated, that could be used in the future as markers associated with FLAN under heat stress in wheat. The information presented here could help in understanding the genetic system controlling FLAN and its relationship with grain yield under heat stress.

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Genetic mapping of a QTL controlling leaf width and grain number in rice

Cited by 28 publications

References 42 publications

Genetic dissection of flag leaf morphology in wheat (Triticum aestivum L.) under diverse water regimes

Genetic dissection of flag leaf morphology in wheat (Triticum aestivum L.) under diverse water regimes

QTL mapping for six ear leaf architecture traits under water‐stressed and well‐watered conditions in maize (Zea mays L.)

Phenotypic Selection and Bulked Segregant Analysis for Flag Leaf Angle under Heat Stress in Bread Wheat (Triticum aestivum L.)

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