Differential DNA methylation analysis reveals key genes in Chinese Qingyu and Landrace pigs

Genome ◽  
2021 ◽  
Author(s):  
Kai Wang ◽  
Pingxian Wu ◽  
Shujie Wang ◽  
Xiang Ji ◽  
Dong Chen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Muscle Development ◽  
Methylation Analysis ◽  
Reduced Representation ◽  
Phenotypic Differences ◽  
Reduced Representation Bisulfite Sequencing ◽  
A Genome ◽  
The Difference ◽  
Dna Methylation Analysis ◽  
Landrace Pig

The Chinese Qingyu pig is a typical domestic fatty pig breed and an invaluable indigenous genetic resource in China. Compared with Landrace pig, Qingyu pig has unique meat characteristics, including muscle development, intramuscular fat, and other meat quality traits. At present, few studies have explored the epigenetic difference due to DNA methylation between Qingyu pig and Landrace pig. In this study, 30 Qingyu pigs and 31 Landrace pig were subjected to reduced representation bisulfite sequencing (RRBS). A genome wide differential DNA methylation analysis was conducted. Six genomic regions, including regions on sus scrofa chromosome (SSC) 1: 266.09-274.23Mb, SSC5:0.88-10.68Mb, SSC8:41.23-48.51Mb, SSC12:45.43-54.38Mb, SSC13:202.15-207.95Mb, and SSC14:126.43-139.85Mb, were regarded as key regions that may be associated with phenotypic differences between Qingyu pig and Landrace pig. Furthermore, according to the further analysis, 5 differential methylated genes (ADCY1, FUBP3, GRIN2B, KIT, and PIK3R6) were deemed as key candidate genes that might be associated with meat characteristics. Our findings provide new insights into the difference of DNA methylation between Qingyu pig and Landrace pig. The results enrich the epigenetic research of Chinese Qingyu pigs.

scholarly journals Genome-wide DNA methylation analysis in Chinese Chenghua and Yorkshire pigs

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kai Wang ◽  
Pingxian Wu ◽  
Shujie Wang ◽  
Xiang Ji ◽  
Dong Chen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Meat Quality ◽  
Muscle Development ◽  
Production Performance ◽  
High Rate ◽  
Methylation Analysis ◽  
Phenotypic Differences ◽  
Genome Wide ◽  
Differentially Methylated Genes ◽  
Dna Methylation Analysis

Abstract Background The Chinese Chenghua pig (CHP) is a typical Chinese domestic fatty pig breed with superior meat quality characteristics, while the Yorkshire pig (YP) has the characteristics of fast growth and a high rate of lean meat. Long term natural selection and artificial selection resulted in great phenotypic differences between the two breeds, including growth, development, production performance, meat quality, and coat color. However, genome-wide DNA methylation differences between CHP and YP remain unclear. Results DNA methylation data were generated for muscle tissues of CHP and YP using reduced representation bisulfite sequencing (RRBS). In this study, a total of 2,416,211 CpG sites were identified. Besides, the genome-wide DNA methylation analysis revealed 722 differentially methylated regions (DMRs) and 466 differentially methylated genes (DMGs) in pairwise CHP vs. YP comparison. Six key genomic regions (Sus scrofa chromosome (SSC)1:253.47–274.23 Mb, SSC6:148.71–169.49 Mb, SSC7:0.25–9.86 Mb, SSC12:43.06–61.49 Mb, SSC14:126.43–140.95 Mb, and SSC18:49.17–54.54 Mb) containing multiple DMRs were identified, and differences of methylation patterns in these regions may be related to phenotypic differences between CHP and YP. Based on the functional analysis of DMGs, 8 DMGs (ADCY1, AGBL4, EXOC2, FUBP3, PAPPA2, PIK3R1, MGMT and MYH8) were considered as important candidate genes associated with muscle development and meat quality traits in pigs. Conclusions This study explored the difference in meat quality between CHP and YP from the epigenetic point of view, which has important reference significance for the local pork industry and pork food processing.

5 Gene expression analysis and DNA methylation patterns of porcine somatic cell nuclear transfer blastocysts with high and low incidence of apoptosis

2019 ◽  
Vol 31 (1) ◽  
pp. 128
Author(s):  
L. Moley ◽  
R. Jones ◽  
R. Kaundal ◽  
A. Thomas ◽  
A. Benninghoff ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Enrichment Analysis ◽  
Epigenetic Reprogramming ◽  
Reduced Representation ◽  
False Discovery ◽  
Reduced Representation Bisulfite Sequencing ◽  
Methylation Patterns ◽  
Dna Methylation Analysis ◽  
Go Terms

Somatic cell NT (SCNT) efficiency remains poor, preventing the technology from being regularly used in the agricultural industry. It is believed that faulty epigenetic reprogramming of SCNT embryos leads to the low overall success. A clear apoptotic signature is associated with inappropriate gene expression and epigenomic aberrancies in many experimental cell culture systems, and we hypothesised that an apoptosis biomarker could be used to effectively separate properly reprogrammed porcine SCNT embryos from those that are destined to fail due to incomplete reprogramming. Therefore, our objective was to evaluate global gene expression and DNA methylation patterns in high- and low-apoptosis individual embryos in an effort to characterise the extent of genomic reprogramming that had taken place. Porcine SCNT blastocysts on Day 6 of development were stained with a nontoxic, noninvasive caspase activity reporter, and the top and bottom 20% of detected caspase activity were classified as high and low apoptosis, respectively (3 replicate cloning sessions; n=13 embryos per group). Genomic DNA and total RNA were isolated from each individual blastocyst. The RNA sequencing libraries were prepared using the Ovation SoLo RNA-Seq system (NuGen, San Carlos, CA, USA). Reduced representation bisulfite sequencing libraries were prepared for DNA methylation analysis using a modification of the single-cell reduced representation bisulfite sequencing global DNA methylation analysis approach detailed by Guo et al. (2015 Nat. Protoc. 10, 645-59). The RNA sequencing analysis using EdgeR (https://bioconductor.org/packages/release/bioc/html/edgeR.html) revealed 175 total differentially expressed genes (fold change ≥1.5; false discovery rate ≤0.05) between the high- and low-apoptosis SCNT embryos. This list of differentially expressed genes was used to perform enrichment analysis to identify overrepresented Gene Ontology (GO) terms or Kyoto Encyclopedia of Genes and Genomes pathways (DAVID Ease version 6.8 (https://david.ncifcrf.gov/) against the Sus scrofa background genome). However, no significantly enriched GO terms or pathways were identified (false discovery rate P>0.05). Analysis of global DNA methylation patterns between high- and low-apoptosis SCNT embryos using MethylKit (Akalin et al. 2012Genome Biol. 13, R87) revealed 335 differentially methylated 100-bp regions with at least 25% difference in methylation (adjusted P ≤ 0.01). Gene transcription start sites associated with these regions were used for enrichment analysis; again, no significant enrichment of GO terms or Kyoto Encyclopedia of Genes and Genomes pathways was identified. Principal component analysis of CpG methylation showed the low-apoptosis embryos clustering more tightly than the high-apoptosis embryos, which were highly scattered. Ongoing comparisons of high- and low-apoptosis cloned embryos with naturally fertilized embryos produced invivo may provide more information about which embryos were properly reprogrammed. Although we are still pursuing a link between reprogramming and gene expression in high- and low-apoptosis embryos, we conclude that these data support a model of stochastic epigenetic reprogramming following SCNT and reinforce the necessity of identifying embryos most likely to be successful due to proper epigenetic reprogramming in order to increase SCNT efficiency.

scholarly journals Epigenetic outlier profiles in depression: A genome-wide DNA methylation analysis of monozygotic twins

PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0207754 ◽  
Author(s):  
Aldo Córdova-Palomera ◽  
Helena Palma-Gudiel ◽  
Jaume Forés-Martos ◽  
Rafael Tabarés-Seisdedos ◽  
Lourdes Fañanás
Keyword(s):  
Dna Methylation ◽  
Monozygotic Twins ◽  
Methylation Analysis ◽  
Genome Wide ◽  
A Genome ◽  
Dna Methylation Analysis

scholarly journals Identification of DNA differential methylation markers in breast tumors with different response to neoadjuvant chemotherapy

2020 ◽  
pp. 20-21
Author(s):  
В.О. Сигин ◽  
Е.О. Игнатова ◽  
Н.В. Литвяков ◽  
А.И. Калинкин ◽  
В.В. Стрельников ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Neoadjuvant Chemotherapy ◽  
Residual Tumor ◽  
Breast Tumors ◽  
Methylation Analysis ◽  
Genome Wide ◽  
A Genome ◽  
Leading Position ◽  
Different Response ◽  
Dna Methylation Analysis

Рак молочной железы (РМЖ) занимает лидирующие позиции среди новообразований у женщин по показателям заболеваемости и смертности. Несмотря на то, что неоадъювантная химиотерапия (НАХТ) позволяет добиться высоких результатов лечения, остается значительная часть пациенток с резидуальной опухолью и значимо худшим прогнозом. Мы провели широкогеномный анализ метилирования ДНК и выявили 33 гена, метилирование промоторных областей которых различается в опухолях молочной железы с различным ответом на НАХТ. Полученные результаты создают основу формирования систем маркеров метилирования ДНК для диагностики потенциальной чувствительности опухолей молочной железы к НАХТ. Breast cancer (BC) occupies a leading position among neoplasms in women in terms of morbidity and mortality. Despite the advantages of neoadjuvant chemotherapy (NACT) which allows achieving high treatment results, a significant part of patients with residual tumor and significantly worse prognosis remains. We have carried out a genome-wide DNA methylation analysis and identified 33 genes methylation of which distinguishes breast tumors with different responses to NACT. Our findings provide the basis for development of test systems for diagnostics of potential sensitivity of breast tumors to NACT via DNA methylation analysis.

scholarly journals Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 2055 ◽  
Author(s):  
Yunshun Chen ◽  
Bhupinder Pal ◽  
Jane E. Visvader ◽  
Gordon K. Smyth
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Differential Methylation ◽  
Complete Analysis ◽  
Methylation Analysis ◽  
Model Framework ◽  
Experimental Conditions ◽  
Reduced Representation ◽  
Reduced Representation Bisulfite Sequencing

Studies in epigenetics have shown that DNA methylation is a key factor in regulating gene expression. Aberrant DNA methylation is often associated with DNA instability, which could lead to development of diseases such as cancer. DNA methylation typically occurs in CpG context. When located in a gene promoter, DNA methylation often acts to repress transcription and gene expression. The most commonly used technology of studying DNA methylation is bisulfite sequencing (BS-seq), which can be used to measure genomewide methylation levels on the single-nucleotide scale. Notably, BS-seq can also be combined with enrichment strategies, such as reduced representation bisulfite sequencing (RRBS), to target CpG-rich regions in order to save per-sample costs. A typical DNA methylation analysis involves identifying differentially methylated regions (DMRs) between different experimental conditions. Many statistical methods have been developed for finding DMRs in BS-seq data. In this workflow, we propose a novel approach of detecting DMRs using edgeR. By providing a complete analysis of RRBS profiles of epithelial populations in the mouse mammary gland, we will demonstrate that differential methylation analyses can be fit into the existing pipelines specifically designed for RNA-seq differential expression studies. In addition, the edgeR generalized linear model framework offers great flexibilities for complex experimental design, while still accounting for the biological variability. The analysis approach illustrated in this article can be applied to any BS-seq data that includes some replication, but it is especially appropriate for RRBS data with small numbers of biological replicates.

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