Evidence map›Paper›PMID 38483771›Full record

ArticleGenes & genomics2024

Whole genome sequencing of mouse lines divergently selected for fatness (FLI) and leanness (FHI) revealed several genetic variants as candidates for novel obesity genes.

Martin Šimon, Špela Mikec, Santosh S Atanur, Janez Konc, Nicholas M Morton, Simon Horvat, Tanja Kunej

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genes & genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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

7 authors at 4 institutions in 2 countries.

Martin ŠimonChair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia. martin.simon@bf.uni-lj.si.ORCID 0000-0002-3708-6798
Špela MikecChair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia.
Santosh S AtanurFaculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK.
Janez KoncLaboratory for Molecular Modeling, National Institute of Chemistry, Ljubljana, 1000, Slovenia.
Nicholas M MortonThe Queen's Medical Research Institute, Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Simon HorvatChair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia.
Tanja KunejChair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia. tanja.kunej@bf.uni-lj.si.
University of Ljubljana · SIImperial College London · GBNational Institute of Chemistry · SIThe Queen's Medical Research Institute · GB

Funding

Javna Agencija za Raziskovalno Dejavnost RS J4-2548Javna Agencija za Raziskovalno Dejavnost RS P4-0220Javna Agencija za Raziskovalno Dejavnost RS Young researchers
6 · The paper itself

Abstract

backgroundAnalysing genomes of animal model organisms is widely used for understanding the genetic basis of complex traits and diseases, such as obesity, for which only a few mouse models exist, however, without their lean counterparts.

objectiveTo analyse genetic differences in the unique mouse models of polygenic obesity (Fat line) and leanness (Lean line) originating from the same base population and established by divergent selection over more than 60 generations.

methodsGenetic variability was analysed using WGS. Variants were identified with GATK and annotated with Ensembl VEP. g.Profiler, WebGestalt, and KEGG were used for GO and pathway enrichment analysis. miRNA seed regions were obtained with miRPathDB 2.0, LncRRIsearch was used to predict targets of identified lncRNAs, and genes influencing adipose tissue amount were searched using the IMPC database.

resultsWGS analysis revealed 6.3 million SNPs, 1.3 million were new. Thousands of potentially impactful SNPs were identified, including within 24 genes related to adipose tissue amount. SNP density was highest in pseudogenes and regulatory RNAs. The Lean line carries SNP rs248726381 in the seed region of mmu-miR-3086-3p, which may affect fatty acid metabolism. KEGG analysis showed deleterious missense variants in immune response and diabetes genes, with food perception pathways being most enriched. Gene prioritisation considering SNP GERP scores, variant consequences, and allele comparison with other mouse lines identified seven novel obesity candidate genes: 4930441H08Rik, Aff3, Fam237b, Gm36633, Pced1a, Tecrl, and Zfp536.

conclusionWGS revealed many genetic differences between the lines that accumulated over the selection period, including variants with potential negative impacts on gene function. Given the increasing availability of mouse strains and genetic polymorphism catalogues, the study is a valuable resource for researchers to study obesity.

Indexed as

ObesityThinnessAdipose TissueAnimalsGenomeMiceWhole Genome SequencingMouse modelsObesitySingle-nucleotide polymorphismWhole-genome sequencing

Identifiers

PMID38483771
PMCPMC11024027
OpenAlexW4392817458

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.