QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai × Yu8679

Wang, R. X.; Lin, Hai; Zhang, X. Y.; You, Guang-Xia; Yan, Chang-Sheng; Xiao, Shuai

doi:10.1007/s00122-008-0901-5

Cited by 196 publications

(138 citation statements)

References 42 publications

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“…A cluster for PH and TKW on 4D (Fig. 3) was reported in other studies (McCartney et al 2005;Huang et al 2006;Wang et al 2009). There were one QTL for NDVI and four QTL for CC at this locus, harboring QTL for plant height.…”

Section: Qtl Clustering and Pleiotropysupporting

confidence: 81%

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

Shi

Azam

et al. 2017

Euphytica

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Wheat (Triticum aestivum L.) yield is directly proportional to physio-morphological traits. A high-density genetic map consisting of 2575 markers was used for mapping QTL controlling stay-green and agronomic traits in wheat grown under four diverse water regimes. A total of 108 additive QTL were identified in target traits. Among them, 28 QTL for chlorophyll content (CC) were detected on 11 chromosomes, 43 for normalized difference vegetation index (NDVI) on all chromosomes except 5B, 5D, and 7D, five for spikes per plant (NSP) on different chromosomes, nine for plant height (PH) on four chromosomes, and 23 for thousand-kernel weight (TKW) on 11 chromosomes. Considering all traits, the phenotypic variation explained (PVE) ranged from 3.61 to 41.62%. A major QTL, QNDVI.cgb-5A.7, for NDVI with a maximum PVE of 20.21%, was located on chromosome 5A. A stable and major PH QTL was observed on chromosome 4D with a PVE close to 40%. Most distances between QTL and corresponding flanking markers were less than 1 cM, and approximately one-third of the QTL coincided with markers. Each of 16 QTL clusters on 10 chromosomes controlled more than one trait and therefore could be regarded as pleiotropic regions in response to different water regimes. Forty-one epistatic QTL were identified for all traits having PVE of 6.00 to 25.07%. Validated QTL closely linked to flanking markers will be beneficial for marker-assisted selection in improving drought-tolerance in wheat.

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Section: Qtl Clustering and Pleiotropysupporting

confidence: 81%

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

Shi

Azam

et al. 2017

Euphytica

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“…The specific marker for grain number was barc101 (2BL), which has not been previously associated with this trait, indicating the presence of a new QTL. The presence of QTLs near marker gwm11 for a large number of agronomic and adaptive traits has been proven by Wang et al (2009), whereas, in the present study, the only association of this marker was found with sterile spikelets per spike. Only a limited number of QTL studies for sterile spikelet number per spike have been documented (Ma et al, 2007).…”

Section: Ssr Markerscontrasting

confidence: 50%

Genetic associations in the detection of QTLs for wheat spike-related traits

Brbaklić¹,

Trkulja²,

Kondić‐Špika³

et al. 2015

Pesq. agropec. bras.

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-The objective of this work was to assess the genetic diversity and population structure of wheat genotypes, to detect significant and stable genetic associations, as well as to evaluate the efficiency of statistical models to identify chromosome regions responsible for the expression of spike-related traits. Eight important spike characteristics were measured during five growing seasons in Serbia. A set of 30 microsatellite markers positioned near important agronomic loci was used to evaluate genetic diversity, resulting in a total of 349 alleles. The marker-trait associations were analyzed using the general linear and mixed linear models. The results obtained for number of allelic variants per locus (11.5), average polymorphic information content value (0.68), and average gene diversity (0.722) showed that the exceptional level of polymorphism in the genotypes is the main requirement for association studies. The population structure estimated by model-based clustering distributed the genotypes into six subpopulations according to log probability of data. Significant and stable associations were detected on chromosomes 1B, 2A, 2B, 2D, and 6D, which explained from 4.7 to 40.7% of total phenotypic variations. The general linear model identified a significantly larger number of marker-trait associations (192) than the mixed linear model (76). The mixed linear model identified nine markers associated to six traits.Index terms: Triticum aestivum, genetic resources, microsatellites, population structure, spike-related traits. Associação genética na detecção de QTLs relacionados a características da espiga de trigoResumo -O objetivo deste trabalho foi avaliar a diversidade genética e a estrutura de população de genótipos de trigo, para detectar associações genéticas significativas e estáveis, bem como avaliar a eficácia de modelos estatísticos para identificar as regiões cromossômicas responsáveis pela expressão de características da espiga. Foram determinadas oito importantes características durante cinco safras agrícolas na Sérvia. Uma série de 30 marcadores microssatélites, localizados próximos a locos agronomicamente importantes, foi utilizada para avaliação da diversidade genética, o que resultou num total de 349 alelos. As associações marcador-características foram analisadas com uso dos modelos linear generalizado e linear misto. Os resultados obtidos para número de variantes alélicas por loco (11,5), valor médio de conteúdo de informação polimórfica (0,68) e diversidade genética média (0,722) mostraram que o nível excepcional de polimorfismo nos genótipos é o principal requerimento para estudos de associação. A estrutura da população estimada pelo agrupamento com base no modelo distribuiu os genótipos em seis subpopulações, de acordo com o log da probabilidade dos dados. Associações significativas e estáveis foram detectadas nos cromossomos 1B, 2A, 2B, 2D e 6D, que explicaram de 4,7 a 40,7% do total das variações fenotípicas. O modelo linear generalizado revelou número significativamente maior de asso...

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“…Data of grain dry weight was then fitted over the accumulated thermal time after anthesis using the logistic growth curve (Wang et al, 2009;Zahedi and Jenner, 2003).…”

Section: Individual Grain Dry Matter and Water Accumulationmentioning

confidence: 99%

Early anthesis and delayed but fast leaf senescence contribute to individual grain dry matter and water accumulation in wheat

Xie

Mayes

Sparkes

2016

Field Crops Research

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Abbreviations: chl, chlorophyll; Chl accum , accumulated chlorophyll content; Chl loss , duration of rapid chlorophyll loss; Chl per , duration of chlorophyll persistence; Chl tot , total duration of chlorophyll persistence and loss; o Cd, degree day; GA, green area; GA accum , accumulated green area; GA loss , duration of rapid green area loss; GA per , duration of green area persistence;GA tot , total duration of green area persistence and loss; GF, grain filling; GFR, grain filling rate; H 2 , broad sense heritability; LOD, logarithm of the odds; Max chl, maximum chlorophyll content; Max CLR, maximum chlorophyll loss rate; Max GALR, maximum green area loss rate; MWC, maximum water content of grain; QTL, quantitative trait locus; RIL, recombinant inbred line; TGW, thousand grain weight; t max , the time at maximum grain filling rate; t mwc , the time at maximum water content; WAR, grain water absorption rate; WLR, grain water loss rate. 2 AbstractThe physiological process of how anthesis time and leaf senescence patterns affect individual grain weight of wheat has only been partially elucidated. In this study, a recombinant inbred line mapping population of bread wheat (Triticum aestivum L. 'Forno') and its relative spelt (Triticum spelta L. 'Oberkulmer'), contrasting for phasic development and leaf senescence kinetics, was used to understand the physiological and genetic relationships among anthesis time, leaf senescence, grain filling processes, and individual grain weight. Phenotypic measurements were taken in the field over two growing seasons. The results showed that earlier anthesis and delayed leaf senescence were associated with larger grains. Furthermore, early anthesis and delayed but fast leaf senescence promoted grain filling rate (but shortened its duration), grain water absorption rate and maximum grain water content, while individual grain dry matter and water accumulation displayed strong relationships with individual grain weight. A total of 118 significant quantitative trait loci (QTL) were identified in this mapping population, including six QTL for anthesis dates, 24 for flag leaf senescence, 69 for grain filling traits, and 19 for individual grain weight. Frequent QTL coincidences between these traits were observed on chromosomes 2A, 3B, 4A, 4DL, 5A, 5B, 5DL and 7B. Analysis of allelic effects confirmed the above physiological relationships. Therefore, anthesis time and leaf senescence affect individual grain weight at least partly through their effects on individual grain dry matter and water accumulation, resulting from pleiotropy or tight gene linkages. Slightly early anthesis, and delayed but fast leaf senescence, can be used to maximize individual grain weight and yield potential in wheat.

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QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai × Yu8679

Cited by 196 publications

References 42 publications

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

Genetic associations in the detection of QTLs for wheat spike-related traits

Early anthesis and delayed but fast leaf senescence contribute to individual grain dry matter and water accumulation in wheat

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