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. 2021 May 22;3(2):lqab045. doi: 10.1093/nargab/lqab045

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© The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.

This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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Figure 6. — Cellular effects of METTL9 knockout. (A) Workflow for proteomics characterization of METTL9 KO cells. Proteins were extracted from HAP-1 wild type (WT) and METTL9 knockout (KO) cells and processed for label free quantitative mass spectrometry. (B) Principal component analysis. Separation of experimental conditions (WT and KO) and replicates (n = 5) in the first principal component is shown. (C) Clustering analysis. Hierarchical cluster of z-scored LFQ intensities for proteins having a significant difference in abundance (Student's t-test, P-adj < 0.05; Benjamini-Hochberg FDR) between the WT and KO condition. (D) Gene ontology analysis. The top five ontologies within biological process and cellular component are shown both for up- and down regulated proteins in METTL9 KO cells, relative to a WT control.