QTL mapping and validation of bread wheat flag leaf morphology across multiple environments in different genetic backgrounds

Tu, Yang; Liu, Huan; Liu, Jiajun; Tang, Huaping; Mu, Yang; Deng, Mei; Jiang, Qiantao; Liu, Yaxi; Chen, Guoyue; Wang, Jirui; Qi, Pengfei; Pu, Zhien; Chen, Guangdeng; Peng, Yuanying; Xu, Qiang; Kang, Houyang; Lan, Xiujin; Wei, Yuming; Zheng, Youliang; Ma, Jian

doi:10.1007/s00122-020-03695-w

Cited by 31 publications

(31 citation statements)

References 64 publications

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“…The line 20828 (G214-5/3/Chuanyu19//Lang 9247/50788) shows longer kernels than SY95-71 ( Figure 1 ) and has other excellent agronomic traits including multiple spikelets ( Ma et al, 2019a ) and high resistance to stripe rust ( Ma et al, 2019b ). SY95-71 (Eronga 83/Fan 6//Fan 6) is a stable line with well-developed root system ( Zheng et al, 2019 ), more tillers ( Liu et al, 2020 ), and better plant type ( Tu et al, 2021 ). These excellent agronomic traits have enabled 20828 and SY95-71 to be widely used as a breeding parent in the past few years.…”

Section: Methodsmentioning

confidence: 99%

“…These excellent agronomic traits have enabled 20828 and SY95-71 to be widely used as a breeding parent in the past few years. Another two populations used for validating the identified QTL were developed with SY95-71 as a common parent, and they were derived from crosses S849-8/SY95-71 (SSY, 214 F 5 lines) ( Liu et al, 2020 ) and MTL4-5-3/SY95-71 (MTL4SY, F 3 200 lines) ( Tu et al, 2021 ). Seeds of 20828 (ZM030677) and SY95-71 (ZM030678) were submitted to the Chinese Crop Germplasm Resources Information System hosted by National Germplasm Bank, China (NGBC).…”

Section: Methodsmentioning

confidence: 99%

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Genetic Mapping and Validation of Loci for Kernel-Related Traits in Wheat (Triticum aestivum L.)

Liu

Xie

et al. 2021

Front. Plant Sci.

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Kernel size (KS) and kernel weight play a key role in wheat yield. Phenotypic data from six environments and a Wheat55K single-nucleotide polymorphism array–based constructed genetic linkage map from a recombinant inbred line population derived from the cross between the wheat line 20828 and the line SY95-71 were used to identify quantitative trait locus (QTL) for kernel length (KL), kernel width (KW), kernel thickness (KT), thousand-kernel weight (TKW), kernel length–width ratio (LWR), KS, and factor form density (FFD). The results showed that 65 QTLs associated with kernel traits were detected, of which the major QTLs QKL.sicau-2SY-1B, QKW.sicau-2SY-6D, QKT.sicau-2SY-2D, and QTKW.sicau-2SY-2D, QLWR.sicau-2SY-6D, QKS.sicau-2SY-1B/2D/6D, and QFFD.sicau-2SY-2D controlling KL, KW, KT, TKW, LWR, KS, and FFD, and identified in multiple environments, respectively. They were located on chromosomes 1BL, 2DL, and 6DS and formed three QTL clusters. Comparison of genetic and physical interval suggested that only QKL.sicau-2SY-1B located on chromosome 1BL was likely a novel QTL. A Kompetitive Allele Specific Polymerase chain reaction (KASP) marker, KASP-AX-109379070, closely linked to this novel QTL was developed and used to successfully confirm its effect in two different genetic populations and three variety panels consisting of 272 Chinese wheat landraces, 300 Chinese wheat cultivars most from the Yellow and Huai River Valley wheat region, and 165 Sichuan wheat cultivars. The relationships between kernel traits and other agronomic traits were detected and discussed. A few predicted genes involved in regulation of kernel growth and development were identified in the intervals of these identified major QTL. Taken together, these stable and major QTLs provide valuable information for understanding the genetic composition of kernel yield and provide the basis for molecular marker–assisted breeding.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Genetic Mapping and Validation of Loci for Kernel-Related Traits in Wheat (Triticum aestivum L.)

Liu

Xie

et al. 2021

Front. Plant Sci.

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“…The major SNS loci in the AM RIL population can thus be identified. This is not uncommon in the past studies of QTL identification based on RIL populations (Liu et al, 2020a; Shang et al, 2020; Tu et al, 2021).…”

Section: Discussionmentioning

confidence: 86%

“…Compared with the above genotyping technologies, the wheat 55K SNP array has been widely used for genotyping and QTL identification in hexaploid common wheat because it is economical and has practical characteristics (Liu et al, 2018; Ren et al, 2018; Ma et al, 2019a; Liu et al, 2020a; Liu et al, 2020b; Ma et al, 2020; Tu et al, 2021). To the author’s knowledge, this is the first study to use the wheat 55K SNP array to construct the genetic linkage map of a tetraploid wheat RIL population.…”

Section: Discussionmentioning

confidence: 99%

“…For example, SNS and SL (Cui et al, 2012), SNS and KNS (Zhang et al, 2009), SNS and SD (Zhang et al, 2009; Cui et al, 2012; Luo et al, 2016), SL and SD (Zhang et al, 2009; Luo et al, 2016), and SL and KNS (Zhang et al, 2009) have been mapped in the same genomic region. The co-located interval is likely involved in multiple traits with higher correlations, and a major QTL with pleiotropic effects or a QTL cluster in the same genomic region affecting various traits exist (Cui et al, 2012; Tu et al, 2021). Fine mapping or cloning of these QTL in the future can reveal their genetic mechanisms in depth.…”

Section: Discussionmentioning

confidence: 99%

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The 55K SNP-Based Exploration of QTL for Spikelet Number Per Spike in a Tetraploid Wheat (Triticum turgidumL.) Population: Chinese Landrace ‘Ailanmai’ × Wild Emmer

Zhu

Wei

et al. 2020

Preprint

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Spikelet number per spike (SNS) is a key factor in determining kernel number per spike which has a great effect on wheat grain yield. Modern wheat breeding narrows genetic diversity among cultivars leading to a detrimental effect on future wheat improvement. It is thus of great significance to explore new genetic resources for SNS to increase wheat yield. Here, a tetraploid landrace Ailanmai mult wild emmer wheat recombinant inbred line (RIL) population was used to construct a high-density genetic map using the wheat 55K single nucleotide polymorphism (SNP) array. Our results showed that the genetic and physical locations of 94.83% (6204) of the mapped markers were consistent. Subsequently, fourteen quantitative trait loci (QTL) for SNS explaining 4.23-27.26% of the phenotypic variation were identified. QSns.sau-AM-2B.3 and QSns.sau-AM-3B.2 were considered as major and novel QTL and their combination had the largest effect and increased SNS by 17.47%. In the physical intervals of QSns.sau-AM-2B.3 and QSns.sau-AM-3B.2, some development-related genes were predicted to participate in the spikelet growth and affect SNS. Additionally, significant correlations between SNS and other agronomic traits like significant and positive correlation between SNS and thousand kernel weight were detected and analyzed. Our findings demonstrated the feasibility of wheat 55K SNP array in genetic mapping of tetraploid wheat and provided an example of exploring outstanding genetic resources from wheat related species for further utilization in common wheat improvement.

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Identifying genomic regions associated with key agro‐morphological traits in soft red winter wheat using genome‐wide association study

Subedi,

Bagwell,

Ghimire

et al. 2024

Crop Science

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Agro‐morphological traits play a significant role in the adaptation of wheat to diverse agroecosystems. Genetic understanding of these traits is crucial to develop cultivars adapted to specific environments and maximize their productivity. This is a comprehensive genome‐wide association study (GWAS) of 230 diverse lines of soft red winter wheat for identifying quantitative trait loci (QTLs) related to eight key agro‐morphological traits. The diversity panel was evaluated in two locations for three consecutive years (2020–2023). A total of 150 significant marker–trait associations were detected, including 65 for three flag leaf traits, 35 for peduncle length, 33 for plant height, 16 for heading date, and one for plant vigor using 27,466 single nucleotide polymorphism (SNP) markers. Eleven high‐confidence major‐effect QTLs explaining greater than 10% phenotypic variance were detected, of which seven were stable, and one showed an association with plant height and peduncle length. QTLs possibly allelic for important dwarfing (Rht23) and vernalization (Vrn‐B1) genes were identified. Six QTLs, QFlw.uga‐1A, QPdl.uga‐1A, QFlw.uga‐2B.2, QPdl.uga‐5A, QPdl.uga‐7A, and QPht.uga‐7B, are presumed to be novel, and nearby candidate gene(s) were identified for all except QPdl.uga‐1A. The pyramiding of favorable alleles from major‐effect QTLs was found to have significant improvement in peduncle length (shortened by 5 cm), flag leaf width (increased by 0.18 cm), and plant height (shortened by 11 cm). This study has improved our genetic understanding of important agro‐morphological traits. These results, upon further validation, can be used in breeding for desirable plant architecture to improve wheat yield potential.

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QTL mapping and validation of bread wheat flag leaf morphology across multiple environments in different genetic backgrounds

Cited by 31 publications

References 64 publications

Genetic Mapping and Validation of Loci for Kernel-Related Traits in Wheat (Triticum aestivum L.)

Genetic Mapping and Validation of Loci for Kernel-Related Traits in Wheat (Triticum aestivum L.)

The 55K SNP-Based Exploration of QTL for Spikelet Number Per Spike in a Tetraploid Wheat (Triticum turgidumL.) Population: Chinese Landrace ‘Ailanmai’ × Wild Emmer

Identifying genomic regions associated with key agro‐morphological traits in soft red winter wheat using genome‐wide association study

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