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

Overview of attention for article published in BMC Genomics, October 2015
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Title
Adult porcine genome-wide DNA methylation patterns support pigs as a biomedical model
Published in
BMC Genomics, October 2015
DOI 10.1186/s12864-015-1938-x
Pubmed ID
Authors

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

Abstract

Pigs (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. DNA 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. Analysis 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.  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. This 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 1%
Unknown 95 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 24%
Researcher 18 19%
Student > Master 10 10%
Student > Bachelor 7 7%
Professor 5 5%
Other 12 13%
Unknown 21 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 32%
Biochemistry, Genetics and Molecular Biology 23 24%
Veterinary Science and Veterinary Medicine 6 6%
Medicine and Dentistry 4 4%
Immunology and Microbiology 3 3%
Other 4 4%
Unknown 25 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 October 2015.
All research outputs
#16,862,340
of 24,792,414 outputs
Outputs from BMC Genomics
#7,035
of 11,067 outputs
Outputs of similar age
#168,792
of 283,321 outputs
Outputs of similar age from BMC Genomics
#265
of 361 outputs
Altmetric has tracked 24,792,414 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,067 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 283,321 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 361 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.