Jiajie She

Dr. Jiajie She

OCES, The Hong Kong University of Science and Technology, Hong Kong, China
orcid
Postdoctoral researcher

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 October 2019 in Frontiers in Plant Science
Verified
Journal Article
Open access
PDF file
LDLingling Da
Lingling Da
YLYue Liu
Yue Liu
JYJiaotong Yang
Jiaotong Yang
TTTian Tian
Tian Tian
JSJiajie She
Jiajie She
ZSZhen Su
Zhen Su
As an economically important crop, apple is one of the most cultivated fruit trees in temperate regions worldwide. Recently, a large number of high-quality transcriptomic and epigenomic datasets for apple were made available to the public, which could be helpful in inferring gene regulatory relationships and thus predicting gene function at the genome level. Through integration of the available apple genomic, transcriptomic, and epigenomic datasets, we constructed co-expression networks, identified functional modules, and predicted chromatin states. A total of 112 RNA-seq datasets were integrated to construct a global network and a conditional network (tissue-preferential network). Furthermore, a total of 1,076 functional modules with closely related gene sets were identified to assess the modularity of biological networks and further subjected to functional enrichment analysis. The results showed that the function of many modules was related to development, secondary metabolism, hormone response, and transcriptional regulation. Transcriptional regulation is closely related to epigenetic marks on chromatin. A total of 20 epigenomic datasets, which included ChIP-seq, DNase-seq, and DNA methylation analysis datasets, were integrated and used to classify chromatin states. Based on the ChromHMM algorithm, the genome was divided into 620,122 fragments, which were classified into 24 states according to the combination of epigenetic marks and enriched-feature regions. Finally, through the collaborative analysis of different omics datasets, the online database AppleMDO (http://bioinformatics.cau.edu.cn/AppleMDO/) was established for cross-referencing and the exploration of possible novel functions of apple genes. In addition, gene annotation information and functional support toolkits were also provided. Our database might be convenient for researchers to develop insights into the function of genes related to important agronomic traits and might serve as a reference for other fruit trees.

22 March 2019 in Frontiers in Genetics
Verified
Journal Article
Open access
PDF file
JSJiajie She
Jiajie She
HYHengyu Yan
Hengyu Yan
JYJiaotong Yang
Jiaotong Yang
WXWenying Xu
Wenying Xu
ZSZhen Su
Zhen Su
Catharanthus roseus is a medicinal plant, which can produce monoterpene indole alkaloid (MIA) metabolites with biological activity and is rich in vinblastine and vincristine. With release of the scaffolded genome sequence of C. roseus, it is necessary to annotate gene functions on the whole-genome level. Recently, 53 RNA-seq datasets are available in public with different tissues (flower, root, leaf, seedling, and shoot) and different treatments (MeJA, PnWB infection and yeast elicitor). We used in-house data process pipeline with the combination of PCC and MR algorithms to construct a co-expression network exploring multi-dimensional gene expression (global, tissue preferential, and treat response) through multi-layered approaches. In the meanwhile, we added miRNA-target pairs, predicted PPI pairs into the network and provided several tools such as gene set enrichment analysis, functional module enrichment analysis, and motif analysis for functional prediction of the co-expression genes. Finally, we have constructed an online croFGD database (http://bioinformatics.cau.edu.cn/croFGD/). We hope croFGD can help the communities to study the C. roseus functional genomics and make novel discoveries about key genes involved in some important biological processes.

26 July 2024 in Molecular Plant
Verified
Journal Article
Closed access
Dingliang ZhangDingliang Zhang
Dingliang Zhang
XYXinxin Yang
Xinxin Yang
ZWZhiyan Wen
Zhiyan Wen
ZLZhen Li
Zhen Li
XZXinyu Zhang
Xinyu Zhang
YZYongliang Zhang
Yongliang Zhang

1 June 2022 in Genomics, Proteomics & Bioinformatics
Verified
Journal Article
Open access
ZLZhongqiu Li
Zhongqiu Li
YHYiheng Hu
Yiheng Hu
XMXuelian Ma
Xuelian Ma
LDLingling Da
Lingling Da
JSJiajie She
Jiajie She
ZSZhen Su
Zhen Su
Genetic and epigenetic changes after polyploidization events could result in variable gene expression and modified regulatory networks. Here, using large-scale transcriptome data, we constructed co-expression networks for diploid, tetraploid, and hexaploid wheat species, and built a platform for comparing co-expression networks of allohexaploid wheat and its progenitors, named WheatCENet. WheatCENet is a platform for searching and comparing specific functional co-expression networks, as well as identifying the related functions of the genes clustered therein. Functional annotations like pathways, gene families, protein–protein interactions, microRNAs (miRNAs), and several lines of epigenome data are integrated into this platform, and Gene Ontology (GO) annotation, gene set enrichment analysis (GSEA), motif identification, and other useful tools are also included. Using WheatCENet, we found that the network of WHEAT ABERRANT PANICLE ORGANIZATION 1 (WAPO1) has more co-expressed genes related to spike development in hexaploid wheat than its progenitors. We also found a novel motif of CCWWWWWWGG (CArG) specifically in the promoter region of WAPO-A1, suggesting that neofunctionalization of the WAPO-A1 gene affects spikelet development in hexaploid wheat. WheatCENet is useful for investigating co-expression networks and conducting other analyses, and thus facilitates comparative and functional genomic studies in wheat. WheatCENet is freely available at http://bioinformatics.cpolar.cn/WheatCENet and http://bioinformatics.cau.edu.cn/WheatCENet.

22 May 2023 in The Plant Cell
Verified
Journal Article
Open access
PDF file
QZQianshen Zhang
Qianshen Zhang
ZWZhiyan Wen
Zhiyan Wen
XZXin Zhang
Xin Zhang
JSJiajie She
Jiajie She
XWXiaoling Wang
Xiaoling Wang
YZYongliang Zhang
Yongliang Zhang
Endomembrane remodeling to form a viral replication complex (VRC) is crucial for a virus to establish infection in a host. Although the composition and function of VRCs have been intensively studied, host factors involved in the assembly of VRCs for plant RNA viruses have not been fully explored. TurboID-based proximity labeling (PL) has emerged as a robust tool for probing molecular interactions in planta. However, few studies have employed the TurboID-based PL technique for investigating plant virus replication. Here, we used Beet black scorch virus (BBSV), an endoplasmic reticulum (ER)-replicating virus, as a model, and systematically investigated the composition of BBSV VRCs in Nicotiana benthamiana by fusing the TurboID enzyme to viral replication protein p23. Among the 185 identified p23-proximal proteins, the reticulon family of proteins showed high reproducibility in the mass spectrometry datasets. We focused on RETICULON-LIKE PROTEIN B2 (RTNLB2) and demonstrated its pro-viral functions in BBSV replication. We showed that RTNLB2 binds to p23, induces ER membrane curvature, and constricts ER tubules to facilitate the assembly of BBSV VRCs. Our comprehensive proximal interactome analysis of BBSV VRCs provides a resource for understanding plant viral replication and offers additional insights into the formation of membrane scaffolds for viral RNA synthesis.

25 April 2023 in Chemical Engineering Journal
Verified
Journal Article
Closed access
XLXuemin Liu
Xuemin Liu
HWHuihui Wang
Huihui Wang
JSJiajie She
Jiajie She
QZQiang Zhang
Qiang Zhang
QHQingyu Hu
Qingyu Hu
LWLiping Wang
Liping Wang