Methylome and transcriptome profiles in three yak tissues revealed that DNA methylation and the transcription factor ZGPAT co-regulate milk production

Abstract Background Domestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat. They have evolved numerous physiological adaptations to high-altitude environment, including strong blood oxygen transportation capabilities and high metabolism. The roles of DNA methylation and gene expression in milk production and high-altitudes adaptation need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lung, and biceps brachii muscle tissues from yaks of different ages. We identified 432,350 differentially methylated regions (DMRs) across the age groups within each tissue. The post-mature breast tissue had considerably more differentially methylated regions (155,957) than that from the three younger age groups. Hypomethylated genes with high expression levels might regulate milk production by influencing protein processing in the endoplasmic reticulum. According to weighted gene correlation network analysis, the “hub” gene ZGPAT was highly expressed in the post-mature breast tissue, indicating that it potentially regulates the transcription of 280 genes that influence protein synthesis, processing, and secretion. The tissue network analysis indicated that high expression of HIF1A regulates energy metabolism in the lung. Conclusions This study provides a basis for understanding the epigenetic mechanisms underlying milk production in yaks, and the results offer insight to breeding programs aimed at improving milk production.

Download Full-text

Methylome and transcriptome profiles in three yak tissues revealed that DNA methylation and the transcription factor ZGPAT co-regulate milk production

10.21203/rs.3.rs-20775/v4 ◽

2020 ◽

Author(s):

Jinwei Xin ◽

Zhixin Chai ◽

Chengfu Zhang ◽

Qiang Zhang ◽

Yong Zhu ◽

...

Keyword(s):

Dna Methylation ◽

Network Analysis ◽

Milk Production ◽

Breast Tissue ◽

Biceps Brachii ◽

Age Groups ◽

High Expression ◽

Differentially Methylated Regions ◽

Muscle Tissues ◽

Gene Correlation

Abstract BackgroundDomestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat. They have evolved numerous physiological adaptations to high-altitude environment, including strong blood oxygen transportation capabilities and high metabolism. The roles of DNA methylation and gene expression in milk production and high-altitudes adaptation need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lung, and biceps brachii muscle tissues from yaks of different ages. We identified 432,350 differentially methylated regions (DMRs) across the age groups within each tissue. The post-mature breast tissue had considerably more differentially methylated regions (155,957) than that from the three younger age groups. Hypomethylated genes with high expression levels might regulate milk production by influencing protein processing in the endoplasmic reticulum. According to weighted gene correlation network analysis, the “hub” gene ZGPAT was highly expressed in the post-mature breast tissue, indicating that it potentially regulates the transcription of 280 genes that influence protein synthesis, processing, and secretion. The tissue network analysis indicated that high expression of HIF1A regulates energy metabolism in the lung. ConclusionsThis study provides a basis for understanding the epigenetic mechanisms underlying milk production in yaks, and the results offer insight to breeding programs aimed at improving milk production.

Download Full-text

Methylome and transcriptome profiles in three yak tissues revealed that DNA methylation and transcription factor ZGPAT co-regulate milk production

10.21203/rs.3.rs-20775/v3 ◽

2020 ◽

Author(s):

Jinwei Xin ◽

Zhixin Chai ◽

Chengfu Zhang ◽

Qiang Zhang ◽

Yong Zhu ◽

...

Keyword(s):

Dna Methylation ◽

Network Analysis ◽

Milk Production ◽

Breast Tissue ◽

Biceps Brachii ◽

Age Groups ◽

High Expression ◽

Differentially Methylated Regions ◽

Genome Wide ◽

Gene Correlation

Abstract Background Domestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat. They have evolved numerous physiological adaptabilities to high-altitude environment, such as the strong capacity of blood oxygen transportation and high metabolism. The role of DNA methylation and network of gene expression underlying milk production and adaptation to high altitudes of yak need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lung, and biceps brachii muscle from yaks of different ages. We identified differentially methylated regions (DMRs) across age groups within the each tissue. The breast tissue had considerably more differentially methylated regions than that from the three younger age groups. Hypomethylated genes with high expression level might regulate milk production by influencing protein processing in the endoplasmic reticulum. Weighted gene correlation network analysis revealed that the “hub” gene ZGPAT was highly expressed in the post-mature breast tissue. It potentially regulated the transcription of 280 genes, which play roles in regulating protein synthesis, processing, and secretion. Besides, Tissue network analysis indicates that high expression of HIF1A regulates energy metabolism in the lung. Conclusions The results of this comprehensive study provide a solid basis for understanding the epigenetic mechanisms underlying milk production in yaks, which could be helpful to breeding programs aimed at improving milk production.

Download Full-text

Methylome and transcriptome profiles in three yak tissues revealed that DNA methylation and transcription factor ZGPAT co-regulate milk production

10.21203/rs.3.rs-20775/v2 ◽

2020 ◽

Author(s):

Jinwei Xin ◽

Zhixin Chai ◽

Chengfu Zhang ◽

Qiang Zhang ◽

Yong Zhu ◽

...

Keyword(s):

Dna Methylation ◽

Network Analysis ◽

Milk Production ◽

Breast Tissue ◽

Age Groups ◽

High Expression ◽

Differentially Methylated Regions ◽

Genome Wide ◽

Younger Age ◽

Gene Correlation

Abstract Background Domestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat, and have evolved numerous physiological adaptabilities to high-altitude landscape, such as strong capacity of blood oxygen transportation and high metabolism. The role of DNA methylation and network of gene expression underlying milk production and adaptation to high altitudes of yak need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lungs, and gluteal muscle from yaks of different ages. We identified differentially methylated regions (DMRs) across age groups within the each tissue, and breast tissue had considerably more differentially methylated regions than that from the three younger age groups. Hypomethylated genes with high expression level might regulate milk production by influencing protein processing in the endoplasmic reticulum. Weighted gene correlation network analysis revealed that the “hub” gene ZGPAT was highly expressed in post-mature breast tissue and that it potentially regulated the transcription of 280 genes, which play roles in regulating protein synthesis, processing, and secretion. Besides, Tissue network analysis indicates that high expression of HIF1A regulates energy metabolism in the lung. Conclusions The results of this comprehensive study provide a solid basis for understanding the epigenetic mechanisms underlying milk production in yaks, which could be helpful to breeding programs aimed at improving milk production.

Download Full-text

Methylome and transcriptome analyses of yaks of different ages revealed that DNA methylation and transcription factor ZGPAT co-regulate milk production

10.21203/rs.3.rs-20775/v1 ◽

2020 ◽

Author(s):

Jinwei Xin ◽

Zhixin Chai ◽

Chengfu Zhang ◽

Qiang Zhang ◽

Yong Zhu ◽

...

Keyword(s):

Network Analysis ◽

Milk Production ◽

Breast Tissue ◽

Molecular Mechanisms ◽

Age Groups ◽

High Expression ◽

Genome Wide ◽

Different Ages ◽

Gene Correlation ◽

Transcriptome Analyses

Abstract Background Domestic yaks play an indispensable role in sustaining the livelihood of Tibetans and other ethnic groups on the Qinghai-Tibetan Plateau (QTP), by providing milk and meat, and have evolved numerous physiological adaptabilities to high-altitude landscape, such as strong capacity of blood oxygen transportation and high metabolism. The molecular mechanisms underlying milk production and adaptation to high altitudes of yak need further exploration. Results We performed genome-wide DNA methylome and transcriptome analyses of breast, lungs, and gluteal muscle from yaks of different ages. We identified differentially methylated regions (DMRs) across age groups within the each tissue, and breast tissue had considerably more differential methylation than that from the three younger age groups. Hypomethylated genes with high expression level might regulate milk production by influencing protein processing in the endoplasmic reticulum. Weighted gene correlation network analysis revealed that the “hub” gene ZGPAT was highly expressed in adult breast tissue and that it potentially regulated the transcription of 280 genes, which play roles in regulating protein synthesis, processing, and secretion. Besides, Tissue network analysis indicates that high expression of HIF1A regulates energy metabolism in the lung. Conclusions The results of this comprehensive study provide a solid basis for understanding the epigenetic mechanisms underlying milk production in yaks, which could be helpful to breeding programs aimed at improving milk production.

Download Full-text

Accelerated aging in normal breast tissue of women with breast cancer

Breast Cancer Research ◽

10.1186/s13058-021-01434-7 ◽

2021 ◽

Vol 23 (1) ◽

Author(s):

Shoghag Panjarian ◽

Jozef Madzo ◽

Kelsey Keith ◽

Carolyn M. Slater ◽

Carmen Sapienza ◽

...

Keyword(s):

Breast Cancer ◽

Dna Methylation ◽

Anomaly Detection ◽

Breast Tissue ◽

Preventive Intervention ◽

Normal Breast Tissue ◽

Accelerated Aging ◽

Normal Breast ◽

Age Related ◽

Unsupervised Anomaly Detection

Abstract Background DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean. Methods We generated whole-genome DNA methylation profiles (GSE160233) on purified epithelial cells and used publicly available Infinium HumanMethylation 450K array datasets (TCGA, GSE88883, GSE69914, GSE101961, and GSE74214) for discovery and validation. Results We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39/427) were outliers for DNA methylation from 6 DNA methylation datasets. We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) than in normal samples (15/228, 5.2%). Additionally, we found significant differences between the predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, we found that the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer. Conclusions A subset of patients with breast cancer has severely altered epigenomes which are characterized by accelerated aging in their normal-appearing tissue. In the future, these DNA methylation sites should be studied further such as in cell-free DNA to determine their potential use as biomarkers for early detection of malignant transformation and preventive intervention in breast cancer.

Download Full-text

Abstract 2087: Breast tissue-specific DNA methylation levels predicted by genetic variants in association with breast cancer

10.1158/1538-7445.am2021-2087 ◽

2021 ◽

Author(s):

Chunyan He ◽

James Castle ◽

Nan Lin ◽

Jinpeng Liu ◽

Chi Wang ◽

...

Keyword(s):

Breast Cancer ◽

Dna Methylation ◽

Genetic Variants ◽

Breast Tissue ◽

Tissue Specific

Download Full-text

Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2020.631775 ◽

2021 ◽

Vol 7 ◽

Author(s):

Tao Yan ◽

Shijie Zhu ◽

Miao Zhu ◽

Chunsheng Wang ◽

Changfa Guo

Keyword(s):

Atrial Fibrillation ◽

Network Analysis ◽

Molecular Mechanism ◽

Immune Cells ◽

Bioinformatics Analysis ◽

Functional Enrichment ◽

Correlation Network ◽

Hub Genes ◽

Qrt Pcr ◽

Gene Correlation

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF.Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR).Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis.Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.

Download Full-text

Key Markers Involved in the Anticolon Cancer Response of CD8+ T Cells through the Regulation of Cholesterol Metabolism

Journal of Oncology ◽

10.1155/2021/9398661 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Liang Dong ◽

Xi Yang ◽

Yangyanqiu Wang ◽

Yin Jin ◽

Qing Zhou ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Network Analysis ◽

Gene Family ◽

Cd8 T Cells ◽

Cholesterol Metabolism ◽

Differential Expression Analysis ◽

High Expression ◽

Ppi Network ◽

Low Expression

Background. T cell-mediated antitumor immune response is the basis of colorectal cancer (CRC) immunotherapy. Cholesterol plays an important role in T cell signal transduction and function. Apolipoprotein E (APOE) plays a major role in cholesterol metabolism. Objective. To screen and analyze key markers involved in the anticolon cancer response of CD8+ T cells through the regulation of cholesterol metabolism. Methods. Based on the median cutoff of the expression value of APOE according to the data downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database, patients were grouped into low and high expression groups. Differences in clinical factors were assessed, and survival analysis was performed. Differentially expressed genes (DEGs) in the high and low expression groups were screened, followed by the analysis of differences in tumor-infiltrating immune cells and weighted gene coexpression network analysis results. The closely related genes to APOE were identified, followed by enrichment analysis, protein–protein interaction (PPI) network analysis, and differential expression analysis. Immunohistochemical staining (IHC) was used to detect the expression of CD8 in CRC tissues. Results. There were significant differences in prognosis and pathologic_N between the APOE low and high expression groups. A total of 2,349 DEGs between the high and low expression groups were selected. A total of 967 genes were obtained from the blue and brown modules. The probability of distribution of CD8+ T cells differed significantly between the two groups, and 320 closely related DEGs of APOE were screened. Genes including the HLA gene family, B2M, IRF4, and STAT5A had a higher degree in the PPI network. GEO datasets verified the prognosis and the related DEGs of APOE. IHC staining verified the relationship between the distribution of CD8+ T cells and APOE expression. Conclusion. Genes including the HLA gene family, B2M, IRF4, and STAT5A might be the key genes involved in the anticolon cancer response of CD8+ T cells through the regulation of cholesterol metabolism.

Download Full-text