Evidence map›Paper›PMID 26438392›Full record

ArticleBMC genomics2015

Adult porcine genome-wide DNA methylation patterns support pigs as a biomedical model.

Kyle M Schachtschneider, Ole Madsen, Chankyu Park, Laurie A Rund, Martien A M Groenen, Lawrence B Schook

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

51 citing papers in PubMed, 92 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Generation of RAG2 Knockout Immune-Deficient Miniature Pigs.Animals : an open access journal from MDPI · 2024
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  8. The effects of COHeliyon · 2024
    Article
  9. Proteasome localization and activity in pig brain andFrontiers in cellular neuroscience · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Porcine models of acute kidney injury.American journal of physiology. Renal physiology · 2021
    Article
  18. In vivo measurement of pH and COScientific reports · 2021
    Article
  19. Article
  20. 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

6 authors at 3 institutions in 3 countries.

Kyle M SchachtschneiderDepartment of Animal Sciences, University of Illinois, Urbana, IL, USA. kschach2@illinois.edu.
Ole MadsenAnimal Breeding and Genomics Center, Wageningen University, Wageningen, The Netherlands. ole.madsen@wur.nl.
Chankyu ParkDepartment of Animal Biotechnology, Konkuk University, Gwangjin-gu, Seoul, South Korea. chankyu@konkuk.ac.kr.
Laurie A RundDepartment of Animal Sciences, University of Illinois, Urbana, IL, USA. larund@illinois.edu.
Martien A M GroenenAnimal Breeding and Genomics Center, Wageningen University, Wageningen, The Netherlands. martien.groenen@wur.nl.
Lawrence B SchookDepartment of Animal Sciences, University of Illinois, Urbana, IL, USA. schook@illinois.edu.
University of Illinois Urbana-Champaign · USWageningen University & Research · NLKonkuk University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPigs (Sus scrofa) provide relevant biomedical models to dissect complex diseases due to their anatomical, genetic, and physiological similarities with humans. Aberrant DNA methylation has been linked to many of these diseases and is associated with gene expression; however, the functional similarities and differences between porcine and human DNA methylation patterns are largely unknown.

methodsDNA and RNA was isolated from eight tissue samples (fat, heart, kidney, liver, lung, lymph node, muscle, and spleen) from the adult female Duroc utilized for the pig genome sequencing project. Reduced representation bisulfite sequencing (RRBS) and RNA-seq were performed on an Illumina HiSeq2000. RRBS reads were aligned using BSseeker2, and only sites with a minimum depth of 10 reads were used for methylation analysis. RNA-seq reads were aligned using Tophat, and expression analysis was performed using Cufflinks. In addition, SNP calling was performed using GATK for targeted control and whole genome sequencing reads for CpG site validation and allelic expression analysis, respectively.

resultsAnalysis on the influence of DNA variation in methylation calling revealed a reduced effectiveness of WGS datasets in covering CpG rich regions, as well as the usefulness of a targeted control library for SNP detection. Analysis of over 500,000 CpG sites demonstrated genome wide methylation patterns similar to those observed in humans, including reduced methylation within CpG islands and at transcription start sites (TSS), X chromosome inactivation, and anticorrelation of TSS CpG methylation with gene expression. In addition, a positive correlation between TSS CpG density and expression, and a negative correlation between TSS TpG density and expression were demonstrated. Low but non-random non-CpG methylation (<1%) was also detected in all non-neuronal somatic tissues, with differences in tissue clustering observed based on CpG and non-CpG methylation patterns. Finally, allele specific expression analysis revealed enrichment of genes involved in metabolic and regulatory processes. DISCUSSION: These results provide transcriptional and DNA methylation datasets for the biomedical community that are directly relatable to current genomic resources. In addition, the correlation between TSS CpG density and expression suggests increased mutation rates at CpG sites play a significant role in adaptive evolution by reducing CpG density at TSS over time, resulting in higher methylation levels in these regions and more permanent changes to lower gene expression. This is proposed to occur predominantly through deamination of 5-methylcytosine to thymidine, resulting in the replacement of CpG with TpG sites in these regions, as indicated by the increased TSS TpG density observed in non-expressed genes, resulting in a negative correlation between expression and TSS TpG density.

conclusionsThis study provides baseline methylation and gene transcription profiles for a healthy adult pig, reports similar patterns to those observed in humans, and supports future porcine studies related to human disease and development. Additionally, the observed reduced CpG and increased TpG density at TSS of lowly expressed genes suggests DNA methylation plays a significant role in adaptive evolution through more permanent changes to lower gene expression.

Indexed as

DNA MethylationEpigenesis, GeneticGenome-Wide Association StudyGenomicsModels, BiologicalAdaptation, BiologicalAllelesAnimalsCpG IslandsEvolution, MolecularFemaleGene Expression RegulationGene LibraryHigh-Throughput Nucleotide SequencingOrgan SpecificityReproducibility of Results

Identifiers

PMID26438392
PMCPMC4594891
OpenAlexW1873376748

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.