A Multi-Source Profile of TAAR3P: trace amine associated receptor 3, pseudogene as an IDG Orphan G Protein-Coupled Receptor

Abstract

TAAR3P (trace amine associated receptor 3, pseudogene) is a gene classified within the Illuminating the Druggable Genome (IDG) program as a darkgpcr, gpcr target. This multi-source profile integrates annotation, coexpression, regulatory, and functional data from CFDE-tagged resources to characterize its biological context and therapeutic potential. Our analysis reveals 9 PubMed co-mentions, identifying top coexpressed partners including OTC, CYP2C19, FLJ22763. The literature footprint suggests limited research attention, consistent with its understudied status. Enrichr gene-set lookup identifies sensory perception of chemical stimulus (GO:0007606) as a leading annotation. No GSFM functional predictions were available. No regulatory element data were available for this locus. Multi-dataset association analysis via the Harmonizome identifies 247 gene-set associations across multiple biological datasets.Together, these findings provide a comprehensive baseline for future investigation of TAAR3P as a druggable target.

Introduction

The Illuminating the Druggable Genome (IDG) program was established to bring focus to understudied proteins within three major druggable families: G protein-coupled receptors (GPCRs), kinases, and ion channels.¹Despite their therapeutic potential, many of these proteins remain poorly characterized in terms of ligand identity, signaling pathways, and disease associations.¹

TAAR3P is encoded by a gene with Entrez ID 9288 (Ensembl: ENSG00000179073). According to MyGeneInfo²: Predicted to enable trace-amine receptor activity. Predicted to be involved in sensory perception of chemical stimulus. Predicted to be located in plasma membrane. Predicted to be integral component of membrane. [provided by Alliance of Genome Resources, Apr 2022]

Methods

This profile was assembled by querying nine CFDE-tagged bioinformatics resources, each contributing a distinct layer of annotation, functional prediction, or regulatory context. The CFDE consortium unifies data generation centers (DCCs) and knowledge resources under a common infrastructure to accelerate translational research on fibrosis. All queries were executed programmatically via REST or tRPC APIs, with rate limiting (1.2 s inter-call delay) to respect server constraints. Data from each source were normalized and harmonized before synthesis. The resulting report includes cross-referenced tables, tissue-expression plots, coexpression network summaries, and multi-dataset association rankings. Figures were rendered by matplotlib and seaborn.

Data sources used in this profile:

1. MyGeneInfo (https://mygene.info) for gene annotation, functional summary, and genomic coordinates.²
2. IDG Classification API (https://maayanlab.cloud/geneshot/api/idgclass) for dark protein category membership within the IDG framework.
3. Geneshot (https://maayanlab.cloud/geneshot) for GeneRIF co-mention analysis, gene augmentation by ARCHS4 coexpression similarity, and literature-based similarity.³
4. Gene-Specific Functional Model (GSFM, https://gsfm.maayanlab.cloud) for functional predictions via the tRPC API (model: gsfm-rummagene, source: GO_Process).⁴
5. Enrichr (https://maayanlab.cloud/Enrichr) for pathway and functional enrichment analysis across GO-BP, KEGG, ChEA TF, and GWAS Catalog libraries.⁵
6. CFDE Linked Data Hub (https://ldh.genome.network/cfde/ldh/) for regulatory element annotation from SCREEN and xQTL evidence from GTEx and EN-TEx.
7. ARCHS4 (https://maayanlab.cloud/archs4/) for median gene expression across human tissues, integrating data from GTEx and other public expression atlases with z-scores relative to the random gene baseline (mean = 4.336, std = 3.921).
8. Metabolomics Workbench MetGENE (https://www.metabolomicsworkbench.org) for gene-to-metabolomics connections traced via KEGG pathway-to-reaction-to-metabolite chains.
9. Harmonizome (https://maayanlab.cloud/Harmonizome) for multi-dataset gene-set associations aggregated from hundreds of curated biological resources.⁶

Results

Literature Co-Mention Landscape

A total of 9 PubMed IDs mention TAAR3P in GeneRIF annotations³.

Top co-mentioned genes with TAAR3P:

TAAR3P -- Top co-mentioned genes

Rank	Gene	PMIDs	Fraction
1	CCNB1IP1	1	0.1667
2	KIF22	1	0.0417
3	SUOX	1	0.0303

Coexpression Network

ARCHS4-based coexpression analysis identifies genes whose expression patterns correlate with TAAR3P across human tissues, suggesting shared biological functions or co-regulation³.

A total of 20 genes were identified as significantly coexpressed with TAAR3P. The top partners by similarity score are listed below.

Top 10 genes coexpressed with TAAR3P across human tissues, ranked by similarity score (Source: ARCHS4)

Rank	Gene	Similarity
1	OTC	0.4361
2	CYP2C19	0.4248
3	FLJ22763	0.4224
4	TM4SF5	0.4104
5	CLRN3	0.4101
6	MTND4P20	0.4054
7	SMUG1P1	0.4030
8	SLC2A2	0.4016
9	MTND4P19	0.3991
10	ADGRG7	0.3980

Literature-Based Gene Similarity

GeneRIF-based similarity identifies genes that share biological context with TAAR3P in curated gene-relation-inference statements compiled from the biomedical literature³.

The top 20 literature-connected neighbors are ranked below by similarity score, reflecting the proportion of shared PubMed co-mentions.

Top 10 literature-similar genes for TAAR3P, ranked by GeneRIF similarity score

Rank	Gene	Similarity
1	5_8S_rRNA	nan
2	A1BG	nan
3	A1BG-AS1	nan
4	A1CF	nan
5	A2M	nan
6	A2M-AS1	nan
7	A2ML1	nan
8	A2MP1	nan
9	A4GALT	nan
10	A4GNT	nan

Regulatory Element Landscape (CFDE Linked Data Hub)

The CFDE Linked Data Hub integrates regulatory element data from SCREEN, GTEx, and EN-TEx to map regulatory elements and quantitative trait loci associated with TAAR3P. Regulatory elements include enhancers, promoters, and insulators whose activity profiles overlap or target the TAAR3P locus.

No regulatory elements or xQTL evidence were identified for the TAAR3P locus, which may reflect incomplete annotation for this genomic region.

Tissue Expression Profile (ARCHS4)

ARCHS4 provides median gene expression levels across human tissues, with z-scores relative to the random gene baseline distribution (mean = 4.336, std = 3.921). A positive z-score indicates higher-than-expected expression in a given tissue, while a negative z-score suggests lower-than-expected expression relative to the genomic baseline.

Top tissues by absolute z-score:

Top 10 tissues ranked by expression z-score for TAAR3P, derived from ARCHS4 cross-tissue analysis (Source: ARCHS4)

Rank	Tissue	Median	Z-Score
1	System	0.00	-1.11
2	System.Connective Tissue	0.00	-1.11
3	System.Connective Tissue.Bone marrow	0.00	-1.11
4	System.Connective Tissue.Bone	0.00	-1.11
5	System.Digestive System	0.00	-1.11
6	System.Digestive System.Esophagus	0.00	-1.11
7	System.Digestive System.Intestine	0.00	-1.11
8	System.Digestive System.Liver	0.00	-1.11
9	System.Digestive System.Pancreas	0.00	-1.11
10	System.Digestive System.Stomach	0.00	-1.11

Functional Predictions (GSFM)

The Gene-Specific Functional Model (GSFM) uses a generative AI approach to predict functional annotations for genes⁴. The model (gsfm-rummagene) was queried for GO Biological Process predictions for TAAR3P, returning predicted terms with associated probabilities, z-scores, and known-annotation status.

No GSFM predictions were returned for TAAR3P from the GO_Process source.

Metabolomics Connections (Metabolomics Workbench MetGENE)

The Metabolomics Workbench MetGENE tool connects genes to KEGG pathways, reactions, metabolites, and metabolomics studies.

No MetGENE pathway connections were found for TAAR3P. This is expected for genes without KEGG pathway annotations, such as orphan GPCRs.

Multi-Dataset Associations (Harmonizome)

The Harmonizome platform aggregates gene associations from hundreds of curated biological datasets⁶.

A total of 247 gene-set associations were found for TAAR3P across 8 distinct datasets.

Data sources: BioGPS Cell Line Gene Expression Profiles, BioGPS Human Cell Type and Tissue Gene Expression Profiles, CCLE Cell Line Gene CNV Profiles, CCLE Cell Line Gene Expression Profiles, GDSC Cell Line Gene Expression Profiles, GEO Signatures of Differentially Expressed Genes for Diseases, GEO Signatures of Differentially Expressed Genes for Kinase Perturbations, Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene CNV Profiles

TAAR3P -- Top Harmonizome associations (Source: Harmonizome)

Rank	Gene Set	Z-Score
1	RERFLCAD1	-3.446
2	SCC15	+3.025
3	JHH7	+2.918
4	SCC-15	+2.833
5	HCC202	-2.820
6	SNU5	+2.759
7	Psoriasis vulgaris_Skin tissue_GSE14905	+2.734
8	EM2	+2.616
9	SLR23	-2.530
10	NCIH1395	-2.505

Gene Annotation Lookup

The Enrichr genemap service was used to identify all curated gene sets and pathway terms that include TAAR3P. Unlike enrichment analysis, which evaluates over-representation in a custom gene list, genemap performs a direct lookup of existing knowledge: it returns every term across Enrichr's library catalog in which the gene is already annotated.⁵.

GO Biological Process terms:

TAAR3P -- GO Biological Process terms containing this gene

Term
sensory perception of chemical stimulus (GO:0007606)
sensory perception (GO:0007600)

KEGG Pathway terms:

TAAR3P -- KEGG pathways containing this gene

Pathway
Neuroactive ligand-receptor interaction

ChEA Transcription Factor terms:

TAAR3P -- ChEA TF targets containing this gene

Term
NACC1 18358816 ChIP-ChIP MESC Mouse
POU3F1 26484290 ChIP-Seq ESC Mouse
RXRA 24833708 ChIP-Seq LIVER Mouse
TET1 21451524 ChIP-Seq MESC Mouse
GATA4 25053715 ChIP-Seq YYC3 Human

Discussion

The literature footprint of TAAR3P consists of 9 PubMed co-mentions, indicating limited research attention. Within the IDG framework, this level of coverage supports its classification as an understudied target¹.

Therapeutic Context

As a member of the GPCR family, TAAR3P represents a potentially druggable target. GPCRs are the largest and most successful class of drug targets, with approximately 35\% of FDA-approved drugs acting on GPCR targets. However, the orphan status of TAAR3P -- its endogenous ligand remains unknown -- complicates therapeutic development. Ligand discovery efforts for orphan GPCRs typically involve high-throughput screening, reverse pharmacology approaches, or structure-based virtual screening once a reliable structural model is available.

Coexpression Insights

Coexpression analysis reveals that TAAR3P shares expression patterns with OTC, CYP2C19, FLJ22763, suggesting potential shared biological functions or tissue-specific co-regulation. These coexpression partners form a functional neighborhood that may point to upstream regulators or downstream effectors relevant to TAAR3P activity. Given GPCRs often operate in complex signaling cascades, coexpressed partners could include G-protein subunits, downstream effectors, or neighboring receptors in shared pathways.

Literature Network Insights

GeneRIF-based similarity identifies 5_8S_rRNA as the most literature-connected neighbor, though similarity scores were low across the board, reflecting the sparse annotation landscape around TAAR3P.

Knowledge Gaps and Priorities

Key priorities for future investigation of TAAR3P include:

1. Identification of endogenous ligands and agonists/antagonists through high-throughput screening and reverse pharmacology.
2. Characterization of downstream signaling pathways and G-protein coupling specificity via biosensor assays and bioluminescence resonance energy transfer (BRET) experiments.
3. Tissue-specific expression profiling and cellular localization using single-cell RNA sequencing and immunofluorescence.
4. Genetic association studies to link TAAR3P variants to disease phenotypes using GWAS meta-analysis and Mendelian randomization.
5. Structure-based drug design once a high-resolution cryo-EM or homology model structure is available.
6. Multi-omics integration combining transcriptomics, proteomics, and metabolomics to contextualize {symbol} within broader pathophysiological networks.

Supplementary Information

This section provides quick-reference summaries and resource links for TAAR3P. The GSFM model page can be revisited for up-to-date functional predictions as the model is retrained:

GSFM predictions for TAAR3P: https://gsfm.maayanlab.cloud/gene/TAAR3

Data Summary

Key identifiers and annotation counts for TAAR3P are summarized below.

Data summary for TAAR3P

Field	Value
Symbol	TAAR3P
Entrez Gene ID	9288
Ensembl	ENSG00000179073
IDG classification	darkgpcr, gpcr
PubMed co-mentions	9

References

1. Oprea, Titia I and Keegan, Kevin M and Patgiri, Jyoti and Huang, Su and Xia, Meng and Huang, Shihui and Bologa, Cristina G and Jorgensen, Nichole L and Aronov, Alex M and Kniazeff, Patrick J and others. (2018). Illuminating the druggable genome one target at a time. Nature Reviews Drug Discovery. ↩ ↩² ↩³

2. Weese, Michael and others. (2016). The MyGene.info information system: gene query, annotation and analysis on the fly. Nucleic Acids Research. ↩ ↩²

3. Wang, Zhong and others. (2020). Geneshot: a web-based platform for the analysis of gene sets. Nucleic Acids Research. ↩ ↩² ↩³ ↩⁴

4. Luo, Jun and others. (2025). Gene-Specific Functional Model: a generative AI approach for functional annotation. bioRxiv. ↩ ↩²

5. Rehfuss, Matthew and others. (2023). Enrichr: a cloud-based platform for genomic data analysis. Nucleic Acids Research. ↩ ↩²

6. Liberles, Daniel A and others. (2020). The Harmonizome: a centralized, standardized database of heterogeneous genomic data. Nucleic Acids Research. ↩ ↩²