GenTree, an integrated resource for analyzing the evolution and function of primate-specific coding genes

Shao, Yi; Chen, Chunyan; Shen, Hao; He, Bin; Yu, Dongke; Jiang, Shuai; Zhao, Shilei; Gao, Zhiqiang; Zhu, Zhenglin; Chen, Xi; Fu, Yan; Chen, Hua; Gao, Ge; Long, Manyuan; Zhang, Yong E.

doi:10.1101/gr.238733.118

Cited by 79 publications

(147 citation statements)

References 106 publications

(181 reference statements)

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“…Age of human genes and orthology The classification of human genes according to their evolutionary age (i.e., to when they first originated) was retrived from the Gen-Tree database (http://gentree.ioz.ac.cn/) (Shao et al, 2019). The age assignments are based on the human genome assembly hg19 and on Ensembl version 73 annotations.…”

Section: Methods Detailsmentioning

confidence: 99%

“…Cell Reports 33, 108308, October 27, 2020 5 Article ll OPEN ACCESS primates split from the glires lineage (i.e., rodents and rabbits), which indicates gene loss events in the non-human lineages or genome annotation problems (Shao et al, 2019). Overall, these analyses suggest that most human disease genes could in principle be studied in one of the four mammalian models.…”

Section: Most Disease Genes Have Orthologs In Mammalian Modelsmentioning

confidence: 99%

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Developmental Gene Expression Differences between Humans and Mammalian Models

et al. 2020

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Section: Methods Detailsmentioning

confidence: 99%

Section: Most Disease Genes Have Orthologs In Mammalian Modelsmentioning

confidence: 99%

Developmental Gene Expression Differences between Humans and Mammalian Models

et al. 2020

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“…The expression profile of PRKCG across multiple brain developmental stages reveals that its expression is extremely lower in the prenatal stages, but dramatically increases in the infancy stages and is stabilized in the latter stages according to GenTree (Additional file 4: Fig. S3) [73]. Previous studies have documented that unlike other PKC family members that are expressed in many tissues aside from brain, PRKCG is brain-specifically expressed [74] and that mutations in PRKCG are associated with spinocerebellar ataxia [75,76].…”

Section: Resultsmentioning

confidence: 98%

Computational identification and characterization of glioma candidate biomarkers through multi-omics integrative profiling

Liu

Wang

et al. 2020

Biol Direct

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Background: Glioma is one of the most common malignant brain tumors and exhibits low resection rate and high recurrence risk. Although a large number of glioma studies powered by high-throughput sequencing technologies have led to massive multi-omics datasets, there lacks of comprehensive integration of glioma datasets for uncovering candidate biomarker genes. Results: In this study, we collected a large-scale assemble of multi-omics multi-cohort datasets from worldwide public resources, involving a total of 16,939 samples across 19 independent studies. Through comprehensive molecular profiling across different datasets, we revealed that PRKCG (Protein Kinase C Gamma), a brain-specific gene detectable in cerebrospinal fluid, is closely associated with glioma. Specifically, it presents lower expression and higher methylation in glioma samples compared with normal samples. PRKCG expression/methylation change from high to low is indicative of glioma progression from low-grade to high-grade and high RNA expression is suggestive of good survival. Importantly, PRKCG in combination with MGMT is effective to predict survival outcomes in a more precise manner. Conclusions: PRKCG bears the great potential for glioma diagnosis, prognosis and therapy, and PRKCG-like genes may represent a set of important genes associated with different molecular mechanisms in glioma tumorigenesis. Our study indicates the importance of computational integrative multi-omics data analysis and represents a datadriven scheme toward precision tumor subtyping and accurate personalized healthcare.

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“…The expression profile of PRKCG across multiple brain developmental stages reveals that its expression is extremely lower in the prenatal stages, but dramatically increases in the infancy stages and is stabilized in the latter stages according to GenTree (Additional file 4: Fig. S3) [61]. Previous studies have documented that unlike other PKC family members that are expressed in many tissues aside from brain, PRKCG is brain-specifically expressed [62] and that mutations in PRKCG are associated with spinocerebellar ataxia [63,64].…”

Section: Resultsmentioning

confidence: 98%

Computational identification and characterization of glioma candidate biomarkers through multi-omics integrative profiling

Liu

Wang

Wang³

et al. 2020

Preprint

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Background: Glioma is one of the most common malignant brain tumors and exhibits low resection rate and high recurrence risk. Although a large number of glioma studies powered by high-throughput sequencing technologies have led to massive multi-omics datasets, there lacks of comprehensive integration of glioma datasets for uncovering candidate biomarker genes.Results: In this study, we collected a large-scale assemble of multi-omics multi-cohort datasets from worldwide public resources, involving a total of 16,939 samples across 19 independent studies. Through comprehensive molecular profiling across different datasets, we revealed that PRKCG (Protein Kinase C Gamma), a brain-specific gene detectable in cerebrospinal fluid, is closely associated with glioma. Specifically, it presents lower expression and higher methylation in glioma samples compared with normal samples. PRKCG expression/methylation change from high to low is indicative of glioma progression from low-grade to high-grade and high RNA expression is suggestive of good survival. Importantly, PRKCG in combination with MGMT is effective to predict survival outcomes in a more precise manner.Conclusions: PRKCG bears the great potential for glioma diagnosis, prognosis and therapy, and PRKCG-like genes may represent a set of important genes associated with different molecular mechanisms in glioma tumorigenesis. Our study indicates the importance of computational integrative multi-omics data analysis and represents a data-driven scheme toward precision tumor subtyping and accurate personalized healthcare.

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GenTree, an integrated resource for analyzing the evolution and function of primate-specific coding genes

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Cited by 79 publications

References 106 publications

Developmental Gene Expression Differences between Humans and Mammalian Models

Developmental Gene Expression Differences between Humans and Mammalian Models

Computational identification and characterization of glioma candidate biomarkers through multi-omics integrative profiling

Computational identification and characterization of glioma candidate biomarkers through multi-omics integrative profiling

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