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Description
BT20 cells were exposed to a non-targeting siRNA (Uni) or siRNA targeting NEK4. RNA was harvested, and RNASeq followed by GSEA was completed. We note that depleting NEK4 alone caused enhancement in cell cycle genes that was consistent with the increase in cell proliferation observed in the BT20 cells following knockdown.
Document Type
Dataset
Publication Date
9-8-2025
Publisher
Dryad Data Repository
Keywords
Biological Sciences, NEK4, p21, proliferation, RNAseq, Triple Negative Breast Cancer
Disciplines
Biochemistry | Biology | Chemistry
Department / Organizational Unit
Department of Chemistry & Biochemistry
Copyright Statement
Public Domain / CC0, no rights reserved
Funder
National Institute of General Medical Sciences
Grant / Award Number
P20GM103451
Recommended Citation
Ashley, Amanda, "Data from: NEK4 Suppresses Cell Proliferation in BT20 Triple-Negative Breast Cancer Cells by Diminishing Expression of Cell Cycle Genes, While Its Depletion Mitigates Proliferation in Other Cell Lines" (2025). Chemistry & Biochemistry: Datasets. 2.
https://digitalcommons.nmsu.edu/chem-biochem-data/2
Comments
Methods:
RNA from BT20 cells, transfected with NT or NEK4 siRNA, was isolated and quantified as above. RNA was sequenced using Illumina HiSeq 2000 at the National Center for Genome Resources (NCGR) in Santa Fe, NM. The samples were sequenced using paired-end reads with a read length of 150 base pairs and a read depth of 20 million reads per sample. Quality control of sample reads was performed using the FastQC tool. Raw reads from sequencing were processed to remove adapter and primer sequences. Processed sequences were aligned to the Human reference genome using HISAT2. Read counts were generated using the featureCounts software. Differential gene expression was assessed using the DeSEQ2 tool. Significantly differentially expressed Q24 genes, i.e., genes with an FDR < 0.05 and fold change of > 0 for upregulated genes and < 0 for downregulated genes, were included for pathway enrichment analysis using Broad Institute’s Gene Set Enrichment Analysis (GSEA) software (http://www.broadinstitute.org/gsea/). Genes were pre-ranked based on the Wald statistic, which is represented by log2 fold change/ standard error of log2 fold change. Change in gene expression was considered significant when the Padj value was < 0.05. Log2 fold change of > 0 was noted as upregulation, while < 0 was noted as downregulation. Genes were interrogated against the Reactome database provided in the GSEA tool. Leading edge analysis was carried out on significantly enriched pathways (FDR < 0.05) to reveal a subset of genes contributing the most toward the enrichment score for each of the enriched pathways. The STRING database was used to prioritize genes with known interactors that promote cell cycle.