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Leaf Transcriptome and Weight Gene Co-expression Network Analysis Uncovers Genes Associated with Photosynthetic Efficiency in Camellia oleifera

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Abstract

Camellia oleifera Abel. (C. oleifera) as an important economic tree species in China has drawn growing attention because of its highly commercial, medic, cosmetic, and ornamental value. To deepen our understanding about the photosynthetic characters during the whole developmental stage as well as the molecular basis of photosynthesis, a comparative analysis of the leaf transcriptome of two C. oleifera cultivars, ‘Guoyou No.13’ (GY13) and ‘Xianglin No.82’ (XL82), with different photosynthetic characteristics from May to September has been conducted. In this study, a group of genes related to photosynthesis, hormone regulation, circadian clock and transcription factor, involved in the photosynthetic advantage. Photosynthetic parameters from May to September of these two cultivars provided evidence supporting photosynthetic advantage of GY13 compared to XL82. In addition, expression levels of 12 differentially expressed genes (DEGs) were validated using real-time PCR (RT-PCR). To screen gene clusters and hub genes that might directly regulated the photosynthetic differences between cultivars, a Weight Gene Co-expression Network Analysis (WGCNA) was conducted. Three co-expression network (module) and top ten connected genes (hub genes) were identified that might play crucial role in the regulatory network of photosynthesis. The results not only showed multiple functional genes that might involve in the differences of photosynthetic characteristics between cultivars, but also provide some evidences for the heat tolerance might be an important character which helps GY13 kept higher photosynthetic parameters than XL82 during the developmental stage. In summary, our transcriptomic approach together with RT-PCR tests allowed us to expand our understanding of the characters of C. oleifera cultivars with different photosynthetic efficiency during the developmental stage and to further exploring new candidate genes involve in high photosynthetic efficiency in molecular-assisted breeding program of C. oleifera.

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Acknowledgements

All authors thank Novogene for efficiently complete transcriptome sequencing project. Meanwhile, we wish to thank the Science and Technology Major Program and Natural Science Foundation of Hunan Province to offer the research funding.

Funding

This research was funded by Science and Technology Major Program of Hunan Province, China (Grant No. 2018NK1030), and the Natural Science Foundation of Hunan Province, China (Grant No.2019JJ50303).

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Authors and Affiliations

  1. Research Institute of Oil Tea Camellia, Hunan Academy of Forestry, Shaoshan South Road, No. 658, Changsha, 410004, China

    Zhilong He, Caixia Liu, Xiangnan Wang, Rui Wang & Yongzhong Chen

  2. National Engineering Research Center for Oil Tea Camellia, Changsha, 410004, China

    Zhilong He, Caixia Liu, Xiangnan Wang, Rui Wang & Yongzhong Chen

  3. College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, Hunan, China

    Zhilong He & Yun Tian

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  1. Zhilong He
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  2. Caixia Liu
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  4. Rui Wang
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  5. Yun Tian
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  6. Yongzhong Chen
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Contributions

Software, CL.; validation, ZH and CL; investigation, RW and XW; data curation, ZH; writing—original draft preparation, ZH; writing—review and editing, ZH; supervision, YT; project administration, YC; funding acquisition, YC. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Yun Tian or Yongzhong Chen.

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He, Z., Liu, C., Wang, X. et al. Leaf Transcriptome and Weight Gene Co-expression Network Analysis Uncovers Genes Associated with Photosynthetic Efficiency in Camellia oleifera. Biochem Genet 59, 398–421 (2021). https://doi.org/10.1007/s10528-020-09995-6

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