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Integration of genomic and transcriptomic data of inbred mouse models for polygenic obesity and leanness revealed “obese” and “lean” candidate alleles in polyadenylation signals
ID
Šimon, Martin
(
Author
),
ID
Mikec, Špela
(
Author
),
ID
Morton, Nicholas M.
(
Author
),
ID
Atanur, Santosh S.
(
Author
),
ID
Horvat, Simon
(
Author
),
ID
Kunej, Tanja
(
Author
)
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https://www.sciencedirect.com/science/article/pii/S2452014424000268
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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.
Language:
English
Keywords:
alternative polyadenylation
,
obesity
,
polyadenylation signal
,
single nucleotide polymorphism
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
BF - Biotechnical Faculty
Publication status:
Published
Publication version:
Version of Record
Year:
2024
Number of pages:
15 str.
Numbering:
Vol. 35, art. 101903
PID:
20.500.12556/RUL-155311
UDC:
575
ISSN on article:
2452-0144
DOI:
10.1016/j.genrep.2024.101903
COBISS.SI-ID:
188127747
Publication date in RUL:
28.03.2024
Views:
437
Downloads:
90
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Record is a part of a journal
Title:
Gene reports
Publisher:
Elsevier
ISSN:
2452-0144
COBISS.SI-ID:
526509593
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
genetika
,
genomika
,
transkriptomika
,
debelost
,
mišji modeli
,
kandidatni aleli
Projects
Funder:
ARIS - Slovenian Research and Innovation Agency
Funding programme:
Young researchers
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
P4-0220
Name:
Primerjalna genomika in genomska biodiverziteta
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
J4-2548
Name:
Vpliv RNA variant na fenotipsko raznolikost pri živalskih modelih
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