Transcript suppression of TaGW2 increased grain width and weight in bread wheat

Hong, Yantao; Chen, Longfei; Du, Liangcheng; Su, Zhenqi; Wang, Jinfen; Ye, Xingguo; Lin, Qingsong; Zhang, Zengyan

doi:10.1007/s10142-014-0380-5

Cited by 75 publications

(66 citation statements)

References 29 publications

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“…Among these 30 genes, 26 are located in the candidate region mapped by at least one method (SLM, JLM, and GWAS) in the RIL populations and five were found to be significantly associated with kernel traits by candidate gene association mapping in a large association panel. Given the conserved functions of many of the known genes for kernel development in maize, rice, and wheat (Su et al, 2011;Hong et al, 2014;Qin et al, 2014;Jaiswal et al, 2015;Wang et al, 2015Wang et al, , 2016Ma et al, 2016;Simmonds et al, 2016), these genes represent additional candidates for kernel development across various species.…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, Liu et al (2015) showed that GS5 contributes to kernel size variation in maize as well as in rice. Notably, the wheat orthologs of rice GW2 and GS5 also were associated significantly with wheat kernel size and weight (Su et al, 2011;Hong et al, 2014;Qin et al, 2014;Jaiswal et al, 2015;Wang et al, 2015Wang et al, , 2016Ma et al, 2016;Simmonds et al, 2016). In addition to GS3, GW2, and GS5, many other genes controlling rice kernel size/weight have been cloned, such as genes involved in G-protein signaling (DEP1 and D1) and genes from phytohormone pathways (DST and Gn1a for cytokinin; D11, SRS5, D61, qGL3, and SMG1 for brassinosteroid; and TGW6 for auxin).…”

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The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice

et al. 2017

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Maize (Zea mays) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice (Oryza sativa) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1, a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis (Arabidopsis thaliana) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis.Maize (Zea mays) is one of the most important crops and is cultivated worldwide as a source of staple food, animal feed, and industrial materials. According to the Food and Agriculture Organization, the production of maize was 1,016.7 million tons in 2013, which was far more than rice (Oryza sativa) and wheat (Triticum aestivum; 745.7 and 713.1 million tons, respectively). Yield improvement is a central goal of maize breeding. Kernel size and weight are two significant components of maize yield, and many attempts have been made to elucidate the genetic basis of kernel size and weight.Many studies have mapped quantitative trait loci (QTLs) for natural variations in kernel size and weight. (2015) mapped 28 QTLs in a test cross population. Most of these studies used two diverse inbred lines to develop the segregating population and used a limited number of genetic markers to construct the linkage map, which greatly limited the resolution and power to detect rare and/or small-effect QTLs. Large-scale QTL mapping studies including more diverse genetic backgrounds and dense genetic markers would provide more insight into the number and effect of QTLs controlling the natural variations of kernel size and weight in maize.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice

et al. 2017

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“…Huang et al (2012) performed a genome-wide association study (GWAS) of flowering time and grain yield traits in a panel of 950 worldwide rice varieties and did not detect an association of OsGW2 and yield. TaGW2s in wheat are functional RING-type E3 ligases (Bednarek et al, 2012), and gene expression analysis and RNAi demonstrated that variation in them was negatively correlated with grain weight, a function that was similar to OsGW2 in rice (Su et al, 2011; Yang et al, 2012; Hong et al, 2014; Qin et al, 2014). Strong selection of certain TaGW2-6A and TaGW2-6B haplotypes occurred in global wheat breeding (Su et al, 2011; Qin et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

“…This caused premature termination and led to increased grain width and weight. However, RNAi results showed that the patterns of TaGW2 regulation on grain development might be more complex (Bednarek et al, 2012; Hong et al, 2014). Simmonds et al (2016) screened an EMS TILLING population of a tetraploid wheat cultivar “Kronos” and found that a GW2-A1 mutant allele significantly increased thousand grain weight, grain width and grain length in both durum and bread wheats.…”

Section: Introductionmentioning

confidence: 99%

TaGW2, a Good Reflection of Wheat Polyploidization and Evolution

Lin¹,

Zhao

Tian

et al. 2017

Front. Plant Sci.

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Hexaploid wheat consists of three subgenomes, namely, A, B, and D. These well-characterized ancestral genomes also exist at the diploid and tetraploid levels, thereby rendering wheat as a good model species for studying polyploidization. Here, we performed intra- and inter-species comparative analyses of wheat and its relatives to dissect polymorphism and differentiation of the TaGW2 genes. Our results showed that genetic diversity of TaGW2 decreased with progression from the diploids to tetraploids and hexaploids. The strongest selection occurred in the promoter regions of TaGW2-6A and TaGW2-6B. Phylogenetic trees clearly indicated that Triticum urartu and Ae. speltoides were the donors of the A and B genomes in tetraploid and hexaploid wheats. Haplotypes detected among hexaploid genotypes traced back to the tetraploid level. Fst and π values revealed that the strongest selection on TaGW2 occurred at the tetraploid level rather than in hexaploid wheat. This infers that grain size enlargement, especially increased kernel width, mainly occurred in tetraploid genotypes. In addition, relative expression levels of TaGW2s significantly declined from the diploid level to tetraploids and hexaploids, further indicating that these genes negatively regulate kernel size. Our results also revealed that the polyploidization events possibly caused much stronger differentiation than domestication and breeding.

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“…Considering that Sorghum has a strong adaptability to the environment, these analyses imply that Sorghum genes related to drought tolerance, salt tolerance, cytochrome, dehydrin, high temperature tolerance, disease and insect resistance can functionally enhance rice yield. This reveals that some evolutionarily homologous genes may show different functions when alien genes were expressed in different plant species (Gururani et al 2015;Hong et al 2014), and provide a novel approach to explore gene resources for plant improvement.…”

Section: Discussionmentioning

confidence: 97%

High throughput transformation of a Sorghum cDNA library for rice improvement

Qin

Qiu

Wen

et al. 2016

Plant Cell Tiss Organ Cult

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The improvement of rice productivity is an important subject due to great population pressure. As plant functional genomics rapidly develops, increasing numbers of genes from different organisms are documented for rice improvement. Sorghum, a relative of rice, has many novel phenotypic characteristics such as strong stature, large panicle, drought tolerance, and a tolerance for low soil fertility, making this species an excellent gene resource for rice improvement. A Sorghum cDNA library was transformed into rice generating an overexpression population with 1153 fertile transgenic lines. Over 900 of these lines displayed phenotypic changes including: plant height, leaf shape and size, effective panicles, and other vegetative characteristics. Importantly, there were 19 lines with higher grain yield than the wild type, which demonstrates that the high-throughput transformation of overexpressing transgenes from Sorghum into rice is a highly efficient method for rice improvement.

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Transcript suppression of TaGW2 increased grain width and weight in bread wheat

Cited by 75 publications

References 29 publications

The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice

The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice

TaGW2, a Good Reflection of Wheat Polyploidization and Evolution

High throughput transformation of a Sorghum cDNA library for rice improvement

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