Global Protein Interactome Mapping in Rice Using Barcode‐Indexed PCR Coupled with HiFi Long‐Read Sequencing

Establishing the protein-protein interaction network sheds light on functional genomics studies by providing insights from known counterparts. However, the rice interactome has barely been studied due to the lack of massive, reliable, and cost-effective methodologies. Here, the development of a barcode-indexed PCR coupled with HiFi long-read sequencing pipeline (BIP-seq) is reported for high throughput Protein Protein Interaction (PPI)identification. BIP-seq is essentially built on the integration of library versus library Y2H mating strategy to facilitate the efficient acquisition of random PPI colonies, semi-mechanized dual barcode-indexed yeast colony PCR for the large-scale indexed amplification of bait and prey cDNAs, and massive pac-bio sequencing of PCR amplicon pools. It is demonstrated that BIP-seq could map over 15 000 high-confidence (≈62.5% could be verified by Bimolecular fluorescence Complementation (BiFC)) rice PPIs within 2 months, outperforming the other reported methods. In addition, the obtained 23 032 rice PPIs, including 22,665 newly identified PPIs, greatly expanded the current rice PPI dataset, provided a comprehensive overview of the rice PPIs networks, and could be a valuable asset in facilitating functional genomics research in rice.

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Publication Details

Journal
Advanced Science
Published
2025-01-22
DOI
https://doi.org/10.1002/advs.202416243
Citations
2
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
1.61

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article

Global Protein Interactome Mapping in Rice Using Barcode‐Indexed PCR Coupled with HiFi Long‐Read Sequencing

Wenya Yuan, Fengyong Zhang, Dawei Xue, Wanning Liu et al.
2 citations
Advanced Science
Bioinformatics and Genomic Networks
1.61
article

Global Protein Interactome Mapping in Rice Using Barcode‐Indexed PCR Coupled with HiFi Long‐Read Sequencing

Wenya Yuan, Fengyong Zhang, Dawei Xue, Wanning Liu, Jinjin Luo, Jian Zhang, Huayu Xu, Sanqiang Zhang, Xixi Liu, Xiaohong Tong, Jiezheng Ying, Jie Huang, Jianwei Zhang, Yifeng Wang, Yi-Ting Chen, Zhiyong Li, Mengyuan Li, Lijuan Chen, Zhichao Liu, Yang Yuan, Yu Cheng, Shiyi Wang, Guanghao Li, Xinyong Liu, Dandan Xia, Yuxuan Hou, Yanan Li, Abdullaev Mirtemir Baxodir ugli, Mukhammadjon Arabboevich Ergashev
article en
2 citations

Abstract

Establishing the protein-protein interaction network sheds light on functional genomics studies by providing insights from known counterparts. However, the rice interactome has barely been studied due to the lack of massive, reliable, and cost-effective methodologies. Here, the development of a barcode-indexed PCR coupled with HiFi long-read sequencing pipeline (BIP-seq) is reported for high throughput Protein Protein Interaction (PPI)identification. BIP-seq is essentially built on the integration of library versus library Y2H mating strategy to facilitate the efficient acquisition of random PPI colonies, semi-mechanized dual barcode-indexed yeast colony PCR for the large-scale indexed amplification of bait and prey cDNAs, and massive pac-bio sequencing of PCR amplicon pools. It is demonstrated that BIP-seq could map over 15 000 high-confidence (≈62.5% could be verified by Bimolecular fluorescence Complementation (BiFC)) rice PPIs within 2 months, outperforming the other reported methods. In addition, the obtained 23 032 rice PPIs, including 22,665 newly identified PPIs, greatly expanded the current rice PPI dataset, provided a comprehensive overview of the rice PPIs networks, and could be a valuable asset in facilitating functional genomics research in rice.

Advanced ScienceVol. 12(11)
Hangzhou Normal University (CN), Huazhong Agricultural University (CN), China National Rice Research Institute (CN), Hubei University of Technology (CN), Hubei University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Zhejiang University, Chinese Academy of Agricultural Sciences, National Key Research and Development Program of China, Agricultural Science and Technology Innovation Program
Openalex Percentile: Top 20%
Bioinformatics and Genomic Networks
1.61
DOIOpen Access PDFOpenAlex
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