Evidence map›Paper›PMID 40340757›Full record

ArticleGenome biology2025

Development of a whole-exome sequencing kit to facilitate porcine biomedical research.

Vishwaarth Vijayakumar, Tanvi Joshi, Lobna Elkhadragy, Lawrence B Schook, Ron C Gaba, Mohammed El-Kebir, Kyle M Schachtschneider

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In one paragraph

Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Review
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.

Vishwaarth VijayakumarCarle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA. vvijay8@illinois.edu.
Tanvi JoshiDepartment of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
Lobna ElkhadragyDepartment of Radiology, University of Illinois at Chicago, Chicago, IL, USA.
Lawrence B SchookDepartment of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
Ron C GabaDepartment of Radiology, University of Illinois at Chicago, Chicago, IL, USA.
Mohammed El-KebirDepartment of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA.
Kyle M SchachtschneiderDepartment of Radiology, University of Illinois at Chicago, Chicago, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is important for porcine models to replicate gene mutations present in human diseases to improve the translatability of animal studies. In this study, the high efficacy of a whole exome sequencing kit was demonstrated for the improved pig reference genome (Sus scrofa 11.1) to profile biomedically relevant swine breeds and enable high-depth sequencing required for intratumor heterogeneity profiling.

resultsWe identify a total of 751,624 single nucleotide variants (SNVs) and 113,597 insertions and deletions (INDELs) across 93 samples from 12 porcine breeds. The identified mutations and affected pathways are correlated to muscle-to-fat ratios between different porcine breeds and further inform their utility as models of obesity and cardiovascular disease. Finally, 7935 SNVs and 358 INDELs are present in an Oncopig hepatocellular carcinoma (HCC) cell line and samples from a single Oncopig HCC tumor, with pathways related to hepatic fibrosis, WNT/B-catenin, ATM signaling, and p53 signaling enriched.

conclusionsThese results demonstrate the kit's high efficacy and utility for identifying mutations in the context of obesity, cardiovascular disease, and cancer across a range of pig models used in biomedical research.

Indexed as

Biomedical ResearchExome SequencingSus scrofaAnimalsCarcinoma, HepatocellularHumansINDEL MutationLiver NeoplasmsMutationObesityPolymorphism, Single NucleotideSwineExome sequencingLiver cancerPorcine animal modelsSingle nucleotide variants

Identifiers

PMID40340757
PMCPMC12060350

What Socratic holds

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LicenceCC BY
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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.