Feb 19, 2026

Public workspaceBulk RNA-seq

DOI
https://dx.doi.org/10.17504/protocols.io.261ge1jbov47/v1
  • Lexi Bounds1,
  • Alejandro Barrera1,
  • Maria A. ter Weele1,
  • Siyan Liu1,
  • Euphy Wu2,
  • Shengyu Li1,
  • Revathy Venukuttan1,
  • Ruhi Rai1,
  • Wancen Mu2,
  • Nahid Iglesias1,
  • Paola Giusti-Rodriguez3,
  • Timothy Reddy1,
  • Yun Li2,
  • Raluca Gordan1,
  • Andrew Allen1,
  • Michael Love2,
  • Patrick Sullivan2,
  • Greg Crawford1,
  • Charles Gersbach1
  • 1Duke University;
  • 2University of North Carolina;
  • 3University of Florida
  • Gersbach Lab
Andrea R Daniel
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DOI: https://dx.doi.org/10.17504/protocols.io.261ge1jbov47/v1
Protocol Citation: Lexi Bounds, Alejandro Barrera, Maria A. ter Weele, Siyan Liu, Euphy Wu, Shengyu Li, Revathy Venukuttan, Ruhi Rai, Wancen Mu, Nahid Iglesias, Paola Giusti-Rodriguez, Timothy Reddy, Yun Li, Raluca Gordan, Andrew Allen, Michael Love, Patrick Sullivan, Greg Crawford, Charles Gersbach 2026. Bulk RNA-seq. protocols.io https://dx.doi.org/10.17504/protocols.io.261ge1jbov47/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: February 17, 2026
Last Modified: February 19, 2026
Protocol Integer ID: 243530
Keywords: RNA-seq, WTC11, neural progenitor cells, methods for bulk rna, bulk rna, neural progenitor cell, using wtc11 cell, wtc11 cell, seq, seq this protocol, npc
Funders Acknowledgements:
NIH
Grant ID: HG012053
Disclaimer
This protocol was adapted from the work of Lexi Bounds in the Gersbach lab at Duke University.
Abstract
This protocol describes methods for bulk RNA-seq using WTC11 cells and Neural Progenitor Cells (NPCs).
Materials
High Sensitivity RNA ScreenTape Analysis (Agilent #5067)
Troubleshooting
Bulk RNA-seq
Total RNA is purified from WTC11 iPSCs and NPCs using the Qiagen RNeasy kit according to the manufacturer’s protocol.
RNA quality is verified to have RIN score > 8 for all samples using High Sensitivity RNA ScreenTape Analysis (Agilent #5067).
RNA-sequencing libraries are prepared by Genewiz and sequenced on an Illumina HiSeq with 2x150bp configuration.
Perform RNA-sequencing in duplicate for each cell type.
Bulk RNA-seq analysis
The pipeline for processing and analysis of the bulk RNA-seq data can be found here: https://github.com/Duke-GCB/GGR-cwl/blob/master/v1.0/RNA-seq_pipeline/pipeline-pe-unstranded-with-sjdb.cwl.
Quality control of FASTQ files is performed using FASTQC (Ref. 1). Adapter reads were then trimmed using Trimmomatic (Ref.2) and mapped using the STAR aligner (Ref. 3). 
Quantification is performed using RSEM (Ref. 4).
For comparisons of basal gene expression levels, a mean transcripts per million (TPM) value is calculated using two biological replicates.
Protocol references
1. Babraham Bioinformatics - FastQC A Quality Control tool for High Throughput Sequence Data. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.

2.   Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinforma. Oxf. Engl. 30, 2114–2120 (2014).

3.   Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinforma. Oxf. Engl. 29, 15–21 (2013).

4.   Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).