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. 2018 Oct 9:9:380.
doi: 10.3389/fgene.2018.00380. eCollection 2018.

Defining Essentiality Score of Protein-Coding Genes and Long Noncoding RNAs

Pan Zeng  1 , Ji Chen  1 , Yuhong Meng  1 , Yuan Zhou  1 , Jichun Yang  1 , Qinghua Cui  1
Affiliations

Defining Essentiality Score of Protein-Coding Genes and Long Noncoding RNAs

Pan Zeng et al. Front Genet. .

Abstract

Measuring the essentiality of genes is critically important in biology and medicine. Here we proposed a computational method, GIC (Gene Importance Calculator), which can efficiently predict the essentiality of both protein-coding genes and long noncoding RNAs (lncRNAs) based on only sequence information. For identifying the essentiality of protein-coding genes, GIC outperformed well-established computational scores. In an independent mouse lncRNA dataset, GIC also achieved an exciting performance (AUC = 0.918). In contrast, the traditional computational methods are not applicable to lncRNAs. Moreover, we explored several potential applications of GIC score. Firstly, we revealed a correlation between gene GIC score and research hotspots of genes. Moreover, GIC score can be used to evaluate whether a gene in mouse is representative for its homolog in human by dissecting its cross-species difference. This is critical for basic medicine because many basic medical studies are performed in animal models. Finally, we showed that GIC score can be used to identify candidate genes from a transcriptomics study. GIC is freely available at http://www.cuilab.cn/gic/.

Keywords: essentiality; lncRNAs; machine learning; prediction; protein-coding genes.

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Figures

FIGURE 1
FIGURE 1
Correlation of GIC score with known measurements of essentiality in human genes. (A) Genes with higher GIC scores tend to have more homologs across species. (B) Genes with higher GIC scores tend to have slower evolutionary rate as measured by dN/dS ratio. (C) Proteins encoded by genes with higher GIC scores tend to have higher degrees in protein interaction network. (D) The percentage of human essential genes increases with GIC score.
FIGURE 2
FIGURE 2
Correlation of GIC score with known measurements of essentiality in mouse genes. (A) Genes with higher GIC scores tend to have more homologs across species. (B) Genes with higher GIC scores tend to have slower evolutionary rate as measured by dN/dS ratio. (C) Proteins encoded by genes with higher GIC scores tend to have higher degrees in protein interaction network. (D) The percentage of human essential genes increases with GIC score.
FIGURE 3
FIGURE 3
Validation of GIC score. (A) ROC curves illustrating the results from human essential gene prediction analysis. (B) ROC curves illustrating the results of essentiality prediction in an independent mouse lncRNA dataset.
FIGURE 4
FIGURE 4
Correlation of GIC score and number of publications of genes.
FIGURE 5
FIGURE 5
Correlation of GIC score of homologous genes between human and mouse.
FIGURE 6
FIGURE 6
siRNA-mediated silencing of target mRNAs on the cell viability of primary rat VSMCs. (A) The efficacy of siRNA treatment on the repression of target mRNA levels. The target mRNA levels were analyzed by real time PCR assays at 48 h post siRNA transfection. N = 5, ∗P < 0.05 vs. control cells transfected with scrambled siRNAs. (B–E) Silencing of target mRNAs on the cell viability. At 48 h post siRNA transfection, cell viability was determined using MTT assay as described in experimental procedure. In every experiment, 3–4 parallel observations were set for each siRNA mixture. In panels B–E, GIC-predicted essential genes but with less significant expression change were presented as fill bars, whereas GIC-predicted non-essential genes but with significant expression change were presented as blank bars. N = 4, ∗P < 0.05 versus control cells transfected with scrambled siRNAs or between indicated two groups. (F). Cell cycle analysis of primary rat VSMCs. Silencing of Serperb2 and Ryr2 on cell cycle determined by flow cytometry. N = 4, ∗P < 0.05, ∗∗P < 0.01 vs. control cells treated with scrambled siRNAs or between two indicated groups.
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References

    1. Bartha I., di Iulio J., Venter J. C., Telenti A. (2018). Human gene essentiality. Nat. Rev. Genet. 19 51–62. 10.1038/nrg.2017.75 - DOI - PubMed
    1. Bello S. M., Smith C. L., Eppig J. T. (2015). Allele, phenotype and disease data at mouse genome informatics: improving access and analysis. Mamm. Genome 26 285–294. 10.1007/s00335-015-9582-y - DOI - PMC - PubMed
    1. Blomen V. A., Májek P., Jae L. T., Bigenzahn J. W., Nieuwenhuis J., Staring J., et al. (2015). Gene essentiality and synthetic lethality in haploid human cells. Science 350 1092–1096. 10.1126/science.aac7557 - DOI - PubMed
    1. Bult C. J., Eppig J. T., Blake J. A., Kadin J. A., Richardson J. E., Mouse G. (2016). Genome database, mouse genome database 2016. Nucleic Acids Res. 44 D840–D847. 10.1093/nar/gkv1211 - DOI - PMC - PubMed
    1. Chen G., Wang Z., Wang D., Qiu C., Liu M., Chen X., et al. (2013). LncRNADisease: a database for long-non-coding RNA-associated diseases. Nucleic Acids Res. 41 D983–D986. 10.1093/nar/gks1099 - DOI - PMC - PubMed

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