<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY center_name="GEO" alias="GSE169348" accession="SRP311670">
    <IDENTIFIERS>
      <PRIMARY_ID>SRP311670</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject" label="primary">PRJNA716305</EXTERNAL_ID>
      <EXTERNAL_ID namespace="GEO">GSE169348</EXTERNAL_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>Next Generation Sequencing Facilitates Quantitative Analysis of IL4/IL13 treated wild-type BMDMs</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Transcriptome Analysis"/>
      <STUDY_ABSTRACT>Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived IL4/IL13 treated BMDMs transcriptome profiling (RNA-seq) to quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods. Methods: BMDMs mRNA profiles of 8 weeks old wild-type (WT) mice were generated, stimulated with IL4/IL13, IL4/IL13+ TNF or TNF, deep sequenced, in triplicate, using Illumina NovaSeq 6000 platform. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9). Conclusions: Our study represents the first detailed analysis of IL4/IL13 or IL4/IL13+TNF stimulated BMDMs, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Overall design: mRNA profiles of wild-type BMDMs stimulated with IL4/IL13, IL4/IL13 + TNF or TNF for 6 or 24 hours</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>GSE169348</CENTER_PROJECT_NAME>
    </DESCRIPTOR>
    <STUDY_LINKS>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>34162546</ID>
        </XREF_LINK>
      </STUDY_LINK>
    </STUDY_LINKS>
  </STUDY>
</STUDY_SET>
