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Background <p>Transcriptomic benchmark concentration (BMC) modeling provides quantitative toxicogenomic information that is increasingly being used in regulatory risk assessment of data poor chemicals. Over the past decade, RNA sequencing (RNA-seq) is gradually replacing microarray as the major platform for transcriptomic applications due to its higher precision, wider dynamic range, and capability of detecting novel transcripts. However, it is unclear whether RNA-seq offers substantial advantages over microarray for concentration response transcriptomic studies.</p> Results <p>We provide an updated comparison between microarray and RNA-seq using two cannabinoids, cannabichromene (CBC) and cannabinol (CBN), as case studies. The two platforms revealed similar overall gene expression patterns with regard to concentration for both CBC and CBN. However, in spite of the many varieties of non-coding RNA transcripts and larger numbers of differentially expressed genes (DEGs) with wider dynamic ranges identified by RNA-seq, the two platforms displayed equivalent performance in identifying functions and pathways impacted by compound exposure through gene set enrichment analysis (GSEA). Furthermore, transcriptomic point of departure (tPoD) values derived by the two platforms through BMC modeling were on the same levels for both CBC and CBN.</p> Conclusions <p>Considering the relatively low cost, smaller data size, and better availability of software and public databases for data analysis and interpretation, microarray is still a viable method of choice for traditional transcriptomic applications such as mechanistic pathway identification and concentration response modeling.</p>

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An updated comparison of microarray and RNA-seq for concentration response transcriptomic study: case studies with two cannabinoids, cannabichromene and cannabinol

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月23日

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  • Xiugong Gao,
  • Miranda R. Yourick,
  • Kayla Campasino,
  • Yang Zhao,
  • Estatira Sepehr,
  • Cory Vaught,
  • Robert L. Sprando,
  • Jeffrey J. Yourick

摘要

Background

Transcriptomic benchmark concentration (BMC) modeling provides quantitative toxicogenomic information that is increasingly being used in regulatory risk assessment of data poor chemicals. Over the past decade, RNA sequencing (RNA-seq) is gradually replacing microarray as the major platform for transcriptomic applications due to its higher precision, wider dynamic range, and capability of detecting novel transcripts. However, it is unclear whether RNA-seq offers substantial advantages over microarray for concentration response transcriptomic studies.

Results

We provide an updated comparison between microarray and RNA-seq using two cannabinoids, cannabichromene (CBC) and cannabinol (CBN), as case studies. The two platforms revealed similar overall gene expression patterns with regard to concentration for both CBC and CBN. However, in spite of the many varieties of non-coding RNA transcripts and larger numbers of differentially expressed genes (DEGs) with wider dynamic ranges identified by RNA-seq, the two platforms displayed equivalent performance in identifying functions and pathways impacted by compound exposure through gene set enrichment analysis (GSEA). Furthermore, transcriptomic point of departure (tPoD) values derived by the two platforms through BMC modeling were on the same levels for both CBC and CBN.

Conclusions

Considering the relatively low cost, smaller data size, and better availability of software and public databases for data analysis and interpretation, microarray is still a viable method of choice for traditional transcriptomic applications such as mechanistic pathway identification and concentration response modeling.