Evidence map›Paper›PMID 40264021›Full record

ArticleBMC genomics2025

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

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

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xiugong GaoDivision of Toxicology, Office of Chemistry and Toxicology (OCT), Office of Laboratory Operations and Applied Science (OLOAS), Human Foods Program (HFP), U.S. Food and Drug Administration (FDA), Laurel, MD, 20708, USA. xiugong.gao@fda.hhs.gov.
Miranda R YourickDivision of Toxicology, Office of Chemistry and Toxicology (OCT), Office of Laboratory Operations and Applied Science (OLOAS), Human Foods Program (HFP), U.S. Food and Drug Administration (FDA), Laurel, MD, 20708, USA.
Kayla CampasinoDivision of Toxicology, Office of Chemistry and Toxicology (OCT), Office of Laboratory Operations and Applied Science (OLOAS), Human Foods Program (HFP), U.S. Food and Drug Administration (FDA), Laurel, MD, 20708, USA.
Yang ZhaoDivision of Toxicology, Office of Chemistry and Toxicology (OCT), Office of Laboratory Operations and Applied Science (OLOAS), Human Foods Program (HFP), U.S. Food and Drug Administration (FDA), Laurel, MD, 20708, USA.
Estatira SepehrDivision of Toxicology, Office of Chemistry and Toxicology (OCT), Office of Laboratory Operations and Applied Science (OLOAS), Human Foods Program (HFP), U.S. Food and Drug Administration (FDA), Laurel, MD, 20708, USA.
Cory VaughtDivision of Toxicology, Office of Chemistry and Toxicology (OCT), Office of Laboratory Operations and Applied Science (OLOAS), Human Foods Program (HFP), U.S. Food and Drug Administration (FDA), Laurel, MD, 20708, USA.
Robert L SprandoDivision of Toxicology, Office of Chemistry and Toxicology (OCT), Office of Laboratory Operations and Applied Science (OLOAS), Human Foods Program (HFP), U.S. Food and Drug Administration (FDA), Laurel, MD, 20708, USA.
Jeffrey J YourickDivision of Toxicology, Office of Chemistry and Toxicology (OCT), Office of Laboratory Operations and Applied Science (OLOAS), Human Foods Program (HFP), U.S. Food and Drug Administration (FDA), Laurel, MD, 20708, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTranscriptomic 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.

resultsWe 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.

conclusionsConsidering 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.

Indexed as

CannabinoidsGene Expression ProfilingOligonucleotide Array Sequence AnalysisRNA-SeqTranscriptomeHumansSequence Analysis, RNACannabinoidsBMC modelingCannabichromeneCannabinoidCannabinolConcentration responseIn vitroMicroarrayRNA-seqToxicogenomics

Identifiers

PMID40264021
PMCPMC12016467

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.