Zhenwu Zheng

South China Agricultural University

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Jinyan Huang

Zhejiang University

Yijun Wang

Yangzhou University

Xiaoya Liang

South China Agricultural University

Yuan‐Ming Zhang

Huazhong Agricultural University

Shaokui Wang

South China Agricultural University

Zupei Liu

South China Agricultural University

Suhong Bu

South China Agricultural University

Haitao Zhu

South China Agricultural University

Guifu Liu

South China Agricultural University

C. Wang

Key Laboratory of Guangdong Province

Cooperative Institutions

South China Agricultural University

Key Laboratory of Guangdong Province

State Key Laboratory For Conservation and Utilization of Subtropical Agro-Bioresources

Nanjing Agricultural University

Chinese Academy of Sciences

Zhejiang University

Guangxi University

Tongji University

Harbin Institute of Technology

Chengdu University of Traditional Chinese Medicine

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qGL3.4 controls kernel size and plant architecture in rice.

PubMed (2023)

Zhenwu Zheng Hongyuan Zhao Xiaoya Liang Yijun Wang C. Wang

Kernel size and plant architecture play important roles in kernel yield in rice. Cloning and functional study of genes related to kernel size and plant architecture are of great significance for breeding high-yield rice. Using the single-segment substitution lines which developed with Oryza barthii as a donor parent and an elite indica cultivar Huajingxian74 (HJX74) as a recipient parent, we identified a novel QTL (quantitative trait locus), named qGL3.4, which controls kernel size and plant architecture. Compared with HJX74, the kernel length, kernel width, 1000-kernel weight, panicle length, kernels per plant, primary branches, yield per plant, and plant height of near isogenic line-qGL3.4 (NIL-qGL3.4) are increased, whereas the panicles per plant and secondary branches per panicle of NIL-qGL3.4 are comparable to those of HJX74. qGL3.4 was narrowed to a 239.18 kb interval on chromosome 3. Cell analysis showed that NIL-qGL3.4 controlled kernel size by regulating cell growth. qGL3.4 controls kernel size at least in part through regulating the transcription levels of EXPANSINS, GS3, GL3.1, PGL1, GL7, OsSPL13 and GS5. These results indicate that qGL3.4 might be beneficial for improving kernel yield and plant architecture in rice breeding.籽粒大小与株型对水稻产量具有重要影响，因此其相关基因克隆与功能研究对培育高产水稻具有重大的意义。本研究从以短舌野生稻为供体、华粳籼74 (HJX74)为受体的染色体单片段代换系(SSSLs)中鉴定到一个新的调控籽粒大小与株型的QTL位点qGL3.4。与对照HJX74相比，近等基因系NIL-qGL3.4的粒长、粒宽、千粒重、穗长、穗粒数、一次枝梗数、单株产量与株高显著增加，而NIL-qGL3.4的分蘖数和二级枝梗数与HJX74对应值无显著差异。通过图位克隆，将qGL3.4定位在第3号染色体239.18 kb区间内。细胞学分析表明，NIL-qGL3.4通过调节颖壳细胞的生长进而调控籽粒的大小。分子机理研究表明，qGL3.4可能通过调控籽粒大小相关基因EXPANSINs、GS3、GL3.1、PGL1、GL7、OsSPL13和GS5的表达进而调控籽粒大小。本研究可能为高产与理想株型的水稻培育提供新的靶标位点。.

Panicle

Kernel (algebra)

10.16288/j.yczz.23-064

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GS6.1 controls kernel size and plant architecture in rice

Planta (2023)

Hongyuan Zhao Yu Fu Yuan‐Ming Zhang Yingqin Luo Weifeng Yang

Panicle

Kernel (algebra)

Rice plant

10.1007/s00425-023-04201-4

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Citations (1)

qGLF5 from Oryza rufipogon Griff. improves kernel shape, plant architecture, and yield in rice

Theoretical and Applied Genetics (2023)

Yijun Wang Xiaoya Liang Gaoyang Gong Yuan‐Ming Zhang Hongyuan Zhao

Oryza rufipogon

Panicle

10.1007/s00122-023-04478-9

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Citations (2)

GS6.1 controls kernel size and plant architecture in rice

Research Square (Research Square) (2023)

Hongyuan Zhao Yu Fu Yuan‐Ming Zhang Yingqin Luo Weifeng Yang

Abstract Kernel size and plant architecture are critical agronomic traits that greatly influence kernel yield in rice. We identified a novel quantitative trait locus (QTL), named GS6.1 , which regulates kernel size and plant architecture in rice. Near isogenic line- GS6.1 (NIL- GS6.1 ) produces long and narrow kernels by regulating cell length and width in the hull, thus increasing the 1000-kernel weight. Compared with the control, the plant height, panicles per plant, panicle length, kernels per plant, and secondary branches per panicle of NIL- GS6.1 are increased. In addition, GS6.1 regulates the kernel filling rate. GS6.1 controls kernel size at least in part through regulating the transcription levels of EXPA13 , EXPA19 , EXPB14 , GS2 , GS3 , GL3 , GL6 , OML4 , GL7 , and GL10 . These results indicate that GS6.1 might be beneficial for improving kernel yield and plant architecture in rice breeding by molecular design.

Panicle

Kernel (algebra)

10.21203/rs.3.rs-2616757/v1

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