Multiple and independent origins of short seeded alleles of &lt;i&gt;GS3&lt;/i&gt; in rice

Takano-Kai, Noriko; Jiang, Hui; Powell, Adrian F.; McCouch, Susan R.; Takamure, Itsuro; Furuya, Naruto; Doi, Kouki; Yoshimura, Atsushi

doi:10.1270/jsbbs.63.77

Cited by 42 publications

(48 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These germplasms differed in GL according to their GS3 allelic variation. The remaining 104 germplasms contained a novel allele (termed the B-allele) (Additional file 6 ), which had a 45-bp insertion in the first intron and did not exhibit the C165A mutation (Takano-Kai et al 2013 ). Germplasms carrying the B-allele of GS3 gene had an intermediate GL compared to the germplasms carrying the A- and C-alleles (Table 1 ).…”

Section: Discussionmentioning

confidence: 99%

Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters

Lee

Park

Kim

et al. 2015

Rice

View full text Add to dashboard Cite

BackgroundGrain size is one of the key factors determining yield and quality in rice. A large number of genes are involved in the regulation of grain size parameters such as grain length and grain width. Different alleles of these genes have different impacts on the grain size traits under their control. However, the combined influence of multiple alleles of different genes on grain size remains to be investigated. Six key genes known to influence grain size were investigated in this study: GS3, GS5, GS6, GW2, qSW5/GW5, and GW8/OsSPL16. Allele and grain measurement data were used to develop a regression equation model that can be used for molecular breeding of rice with desired grain characteristics.ResultsA total of 215 diverse rice germplasms, which originated from or were developed in 28 rice-consuming countries, were used in this study. Genotyping analysis demonstrated that a relatively small number of allele combinations were preserved in the diverse population and that these allele combinations were significantly associated with differences in grain size. Furthermore, in several cases, variation at a single gene was sufficient to influence grain size, even when the alleles of other genes remained constant. The data were used to develop a regression equation model for prediction of rice grain size, and this was tested using data from a further 34 germplasms. The model was significantly correlated with three of the four grain size-related traits examined in this study.ConclusionRice grain size is strongly influenced by specific combinations of alleles from six different genes. A regression equation model developed from allele and grain measurement data can be used in rice breeding programs for the development of new rice varieties with desired grain size and shape.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-015-0066-1) contains supplementary material, which is available to authorized users.

show abstract

Section: Discussionmentioning

confidence: 99%

Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters

Lee

Park

Kim

et al. 2015

Rice

View full text Add to dashboard Cite

show abstract

“…As one of the three wheat yield elements, thousand-kernel weight (TKW) is considered to have an important influence on wheat yield and could be determined by the kernel size. To date, some important yield-related genes (GS3, GS5, GW2, GW3, GW5, GW6, GW8, GIF1, and Ghd7) associated with kernel size were gradually discovered and cloned in rice (Li et al, 2004a , b , 2011 ; Fan et al, 2006 ; Xie et al, 2006 ; Song et al, 2007 ; Wang et al, 2008 , 2012b ; Weng et al, 2008 ; Xue et al, 2008 ; Guo et al, 2009 ; Takano-Kai et al, 2009 , 2013 ). For example, the GS5 gene, encoding a putative serine carboxypeptidase, was cloned in rice as a positive regulator of grain size by regulating grain width, filling, and weight (Li et al, 2011 ).…”

Section: Introductionmentioning

confidence: 99%

A Single-Nucleotide Polymorphism of TaGS5 Gene Revealed its Association with Kernel Weight in Chinese Bread Wheat

et al. 2015

View full text Add to dashboard Cite

TaGS5 genes were cloned from bread wheat and were physically mapped on 3AS and 3DS. Sequencing results revealed that a SNP was found in the sixth exon of TaGS5-A1 gene. The SNP resulted in amino acid change from alanine to serine at the 303 bp position of TaGS5-A1. These two alleles were designated as TaGS5-A1a (alanine at the 303 bp position) and TaGS5-A1b genes (serine at the 303-bp position). Analysis of association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with TaGS5-A1b possessed wider kernel width and higher thousand-kernel weight, as well as significantly lower plant height, spike length, and internode length below spike than those of cultivars with TaGS5-A1a over 3 years. These trait differences between TaGS5-A1a and TaGS5-A1b genotypes were larger in landraces than in modern cultivars. This finding suggested that TaGS5 gene played an important role in modulating yield-related traits in the landraces, which possibly resulted from numerous superior genes gathering in modern cultivars after strong artificial selection. The preferred TaGS5-A1b haplotype underwent very strong positive selection in Chinese modern wheat breeding, but not in Chinese landraces. Expression analysis of the TaGS5-A1 gene indicated that TaGS5-A1b allele possessed significantly higher expression level than TaGS5-A1b allele in differently developmental seeds. This study could provide relatively superior genotype in view of agronomic traits in wheat breeding programs. Likewise, this study could offer important information for the dissection of molecular and genetic basis of yield-related traits.

show abstract

“…GRAIN SIZE3 ( GS3 ) was the first QTL characterized to regulate grain size (Fan et al ), Grain number 1a ( Gn1a ) was the first QTL identified to control the grain number (Ashikari et al ). Loss of function of the OSR domain at the N terminus of GS3 results in long grain and enhances grain yield phenotypes (Takano‐Kai et al ; Mao et al ; Takano‐Kai et al ). Reduction or loss of function of Gn1a increases the number of reproductive organs, resulting in enhanced grain production (Ashikari et al ; Wang et al ).…”

mentioning

confidence: 99%

QTL editing confers opposing yield performance in different rice varieties

Shen

Chün

et al. 2016

JIPB

126

View full text Add to dashboard Cite

Grain yield is one of the most important and complex trait for genetic improvement in crops; it is known to be controlled by a number of genes known as quantitative trait loci (QTLs). In the past decade, many yield-contributing QTLs have been identified in crops. However, it remains unclear whether those QTLs confer the same yield performance in different genetic backgrounds. Here, we performed CRISPR/Cas9-mediated QTL editing in five widely-cultivated rice varieties and revealed that the same QTL can have diverse, even opposing, effects on grain yield in different genetic backgrounds.

show abstract

Multiple and independent origins of short seeded alleles of <i>GS3</i> in rice

Cited by 42 publications

References 22 publications

Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters

Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters

A Single-Nucleotide Polymorphism of TaGS5 Gene Revealed its Association with Kernel Weight in Chinese Bread Wheat

QTL editing confers opposing yield performance in different rice varieties

Contact Info

Product

Resources

About