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Ji, Zhe

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Ji, Zhe

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2015 - 20174

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Author's Publications: search.filters.isAuthorOfPublication.c5a88de6-0453-4107-a1ba-be4ac40fc4cb

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Now showing 1 - 4 of 4
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    LINC00520 is induced by Src, STAT3, and PI3K and plays a functional role in breast cancer
    (Impact Journals LLC, 2016) Henry, Whitney S.; Hendrickson, David G.; Beca, Francisco; Glass, Benjamin; Lindahl-Allen, Marianne; He, Lizhi; Ji, Zhe; Struhl, Kevin; Beck, Andrew; Rinn, John; Toker, Alex
    Long non-coding RNAs (lncRNAs) have been implicated in normal cellular homeostasis as well as pathophysiological conditions, including cancer. Here we performed global gene expression profiling of mammary epithelial cells transformed by oncogenic v-Src, and identified a large subset of uncharacterized lncRNAs potentially involved in breast cancer development. Specifically, our analysis revealed a novel lncRNA, LINC00520 that is upregulated upon ectopic expression of oncogenic v-Src, in a manner that is dependent on the transcription factor STAT3. Similarly, LINC00520 is also increased in mammary epithelial cells transformed by oncogenic PI3K and its expression is decreased upon knockdown of mutant PIK3CA. Additional expression profiling highlight that LINC00520 is elevated in a subset of human breast carcinomas, with preferential enrichment in the basal-like molecular subtype. ShRNA-mediated depletion of LINC00520 results in decreased cell migration and loss of invasive structures in 3D. RNA sequencing analysis uncovers several genes that are differentially expressed upon ectopic expression of LINC00520, a significant subset of which are also induced in v-Src-transformed MCF10A cells. Together, these findings characterize LINC00520 as a lncRNA that is regulated by oncogenic Src, PIK3CA and STAT3, and which may contribute to the molecular etiology of breast cancer.
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    Transcriptome-scale RNase-footprinting of RNA-protein complexes
    (2015) Ji, Zhe; Song, Ruisheng; Huang, Hailiang; Regev, Aviv; Struhl, Kevin
    Ribosome profiling is widely used to study translation in vivo, but not all sequence reads correspond to ribosome-protected RNA. Here, we develop Rfoot, a computational pipeline that analyzes ribosomal profiling data and identifies native, non-ribosomal RNA-protein complexes in the same sample.. We use Rfoot to precisely map RNase-protected regions within small nucleolar RNAs, spliceosomal RNAs, microRNAs, tRNAs, long noncoding (lnc) RNAs, and 3’ˊ untranslated regions of mRNAs in human cells. We show that RNAs of the same class can show differential complex association. Although only a subset of lncRNAs show RNase footprints, many of these have multiple footprints, and the protected regions are evolutionarily conserved, suggestive of biological functions.
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    Many lncRNAs, 5’UTRs, and pseudogenes are translated and some are likely to express functional proteins
    (eLife Sciences Publications, Ltd, 2015) Ji, Zhe; Song, Ruisheng; Regev, Aviv; Struhl, Kevin
    Using a new bioinformatic method to analyze ribosome profiling data, we show that 40% of lncRNAs and pseudogene RNAs expressed in human cells are translated. In addition, ~35% of mRNA coding genes are translated upstream of the primary protein-coding region (uORFs) and 4% are translated downstream (dORFs). Translated lncRNAs preferentially localize in the cytoplasm, whereas untranslated lncRNAs preferentially localize in the nucleus. The translation efficiency of cytoplasmic lncRNAs is nearly comparable to that of mRNAs, suggesting that cytoplasmic lncRNAs are engaged by the ribosome and translated. While most peptides generated from lncRNAs may be highly unstable byproducts without function, ~9% of the peptides are conserved in ORFs in mouse transcripts, as are 74% of pseudogene peptides, 24% of uORF peptides and 32% of dORF peptides. Analyses of synonymous and nonsynonymous substitution rates of these conserved peptides show that some are under stabilizing selection, suggesting potential functional importance. DOI: http://dx.doi.org/10.7554/eLife.08890.001
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    Genome-wide identification and differential analysis of translational initiation
    (Nature Publishing Group UK, 2017) Zhang, Peng; He, Dandan; Xu, Yi; Hou, Jiakai; Pan, Bih-Fang; Wang, Yunfei; Liu, Tao; Davis, Christel M.; Ehli, Erik A.; Tan, Lin; Zhou, Feng; Hu, Jian; Yu, Yonghao; Chen, Xi; Nguyen, Tuan M.; Rosen, Jeffrey M.; Hawke, David H.; Ji, Zhe; Chen, Yiwen
    Translation is principally regulated at the initiation stage. The development of the translation initiation (TI) sequencing (TI-seq) technique has enabled the global mapping of TIs and revealed unanticipated complex translational landscapes in metazoans. Despite the wide adoption of TI-seq, there is no computational tool currently available for analyzing TI-seq data. To fill this gap, we develop a comprehensive toolkit named Ribo-TISH, which allows for detecting and quantitatively comparing TIs across conditions from TI-seq data. Ribo-TISH can also predict novel open reading frames (ORFs) from regular ribosome profiling (rRibo-seq) data and outperform several established methods in both computational efficiency and prediction accuracy. Applied to published TI-seq/rRibo-seq data sets, Ribo-TISH uncovers a novel signature of elevated mitochondrial translation during amino-acid deprivation and predicts novel ORFs in 5′UTRs, long noncoding RNAs, and introns. These successful applications demonstrate the power of Ribo-TISH in extracting biological insights from TI-seq/rRibo-seq data.