Integration of genomic and transcriptomic data of inbred mouse models for polygenic obesity and leanness revealed "obese" and "lean" candidate alleles in polyadenylation signals

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Šimon, M, Mikec, Š, Morton, NM ORCID: https://orcid.org/0000-0001-8218-8462, Atanur, SS, Horvat, S and Kunej, T, 2024. Integration of genomic and transcriptomic data of inbred mouse models for polygenic obesity and leanness revealed "obese" and "lean" candidate alleles in polyadenylation signals. Gene Reports, 35: 101903. ISSN 2452-0144

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Official URL: https://doi.org/10.1016/j.genrep.2024.101903

Abstract

Most mammalian genes have multiple polyadenylation (PA) sites, and alternative polyadenylation (APA) has been linked to diseases such as obesity. Studies have shown that changes in the polyadenylation signal (PAS) can influence the efficiency of cleavage and affect disease susceptibility and phenotype. In our recent study we used inbred mouse models of polygenic obesity and leanness and identified single-nucleotide polymorphisms in PAS (PAS-SNPs) within several obesity candidate genes, including five with differential expression. Nevertheless, to date, there has been no systematic, whole-genome-level approach aiming to prioritise PAS-SNPs potentially affecting APA. Therefore, in this study, we build upon our previous work by integrating existing genomics data with transcriptomics. DEGs were identified in nine tissues by Affymetrix GeneChip. PA and PAS sites were from the PolyASite 2.0 portal. Prioritisation of candidate PAS-SNPs was performed based on whether they were located in DEG, the type of PAS changes they caused, locations of PA sites relative to PAS, and location(s) and expression(s) of Affymetrix probes within a given gene in various tissues. For the candidates, potential consequences due to the alteration in APA events were investigated using bioinformatics databases and tools. The analysis found 127 PAS-SNPs in 101 DEGs across different tissues and identified 12 high-priority and 7 moderate-priority PAS-SNP candidates in 10 and 7 DEGs, respectively. Candidate PAS-SNPs were in 3′ UTR of 12 protein-coding genes (Lean line: Edil3, Eif2s1, Fbxl3, Hlf, Hsf2bp, Knop1, Lair1, Nmrk1; Fat line: Ehd1, Rpl14, Spon1, Txndc9), introns of four protein-coding genes (Lean line: Abi3bp, Prr16; Fat line: Agmo, Itga7) and intron of one lncRNA (Lean line: 1700086O06Rik). The integration of whole-genome sequencing and transcriptome analyses in this study has identified potential genome-wide candidate SNPs that could affect APA by altering/disrupting PAS motifs and be related to obesity in mice. The data provides a foundation for further research into these PAS-SNPs, their genes, and their contribution to the obesity/leanness phenotype, and contributes a part in explaining missing heritability commonly observed in complex traits.

Item Type:	Journal article
Publication Title:	Gene Reports
Creators:	Šimon, M., Mikec, Š., Morton, N.M., Atanur, S.S., Horvat, S. and Kunej, T.
Publisher:	Elsevier
Date:	June 2024
Volume:	35
ISSN:	2452-0144
Identifiers:	Number Type 10.1016/j.genrep.2024.101903 DOI S2452014424000268 Publisher Item Identifier 2465842 Other
Rights:	© 2024 the authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	09 Jul 2025 09:26
Last Modified:	09 Jul 2025 09:57
URI:	https://irep.ntu.ac.uk/id/eprint/53914