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Published on: August 2, 2018
iHypoxia: An Integrative Database of Protein Expression Dynamics in Response to Hypoxia in Animals
Ze-Xian Liu1, Panqin Wang2, Qingfeng Zhang1
1State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Sun Yat-sen University, Guangzhou 510060, China.
Abstract:
Mammals have evolved mechanisms to sense hypoxia and induce hypoxic responses. Recently, high-throughput techniques have greatly promoted global studies of protein expression changes during hypoxia and the identification of candidate genes associated with hypoxia-adaptive evolution, which have contributed to the understanding of the complex regulatory networks of hypoxia. In this study, we developed an integrated resource for the expression dynamics of proteins in response to hypoxia (iHypoxia), and this database contains 2589 expression events of 1944 proteins identified by low-throughput experiments (LTEs) and 422,553 quantitative expression events of 33,559 proteins identified by high-throughput experiments from five mammals that exhibit a response to hypoxia. Various experimental details, such as the hypoxic experimental conditions, expression patterns, and sample types, were carefully collected and integrated. Furthermore, 8788 candidate genes from diverse species inhabiting low-oxygen environments were also integrated. In addition, we conducted an orthologous search and computationally identified 394,141 proteins that may respond to hypoxia among 48 animals. An enrichment analysis of human proteins identified from LTEs shows that these proteins are enriched in certain drug targets and cancer genes. Annotation of known posttranslational modification (PTM) sites in the proteins identified by LTEs reveals that these proteins undergo extensive PTMs, particularly phosphorylation, ubiquitination, and acetylation. iHypoxia provides a convenient and user-friendly method for users to obtain hypoxia-related information of interest. We anticipate that iHypoxia, which is freely accessible at https://ihypoxia.omicsbio.info, will advance the understanding of hypoxia and serve as a valuable data resource.
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