Xiao Dong

Genetic evidence for common pathways in human age-related diseases

Aging is the single largest risk factor for chronic disease. Studies in model organisms have identified conserved pathways that modulate aging rate and the onset and progression of multiple age‐related diseases, suggesting that common pathways of aging may influence age‐related diseases in humans as well. To determine whether there is genetic evidence supporting the notion of common pathways underlying age‐related diseases, we analyzed the genes and pathways found to be associated with five major categories of age‐related disease using a total of 410 genomewide association studies (GWAS). While only a small number of genes are shared among all five disease categories, those found in at least three of the five major age‐related disease categories are highly enriched for apoliprotein metabolism genes. We found that a more substantial number of gene ontology (GO) terms are shared among the 5 age‐related disease categories and shared GO terms include canonical aging pathways identified in model organisms, such as nutrient‐sensing signaling, translation, proteostasis, stress responses, and genome maintenance. Taking advantage of the vast amount of genetic data from the GWAS, our findings provide the first direct evidence that conserved pathways of aging simultaneously influence multiple age‐related diseases in humans as has been demonstrated in model organisms.

Analysis of individual cells identifies cell-to-cell variability following induction of cellular senescence

Senescent cells play important roles in both physiological and pathological processes, including cancer and aging. In all cases, however, senescent cells comprise only a small fraction of tissues. Senescent phenotypes have been studied largely in relatively homogeneous populations of cultured cells. In vivo, senescent cells are generally identified by a small number of markers, but whether and how these markers vary among individual cells is unknown. We therefore utilized a combination of single‐cell isolation and a nanofluidic PCR platform to determine the contributions of individual cells to the overall gene expression profile of senescent human fibroblast populations. Individual senescent cells were surprisingly heterogeneous in their gene expression signatures. This cell‐to‐cell variability resulted in a loss of correlation among the expression of several senescence‐associated genes. Many genes encoding senescence‐associated secretory phenotype (SASP) factors, a major contributor to the effects of senescent cells in vivo, showed marked variability with a subset of highly induced genes accounting for the increases observed at the population level. Inflammatory genes in clustered genomic loci showed a greater correlation with senescence compared to nonclustered loci, suggesting that these genes are coregulated by genomic location. Together, these data offer new insights into how genes are regulated in senescent cells and suggest that single markers are inadequate to identify senescent cells in vivo.

Genome-wide, Single-Cell DNA Methylomics Reveals Increased Non-CpG Methylation during Human Oocyte Maturation

Summary The establishment of DNA methylation patterns in oocytes is a highly dynamic process marking gene-regulatory events during fertilization, embryonic development, and adulthood. However, after epigenetic reprogramming in primordial germ cells, how and when DNA methylation is re-established in developing human oocytes remains to be characterized. Here, using single-cell whole-genome bisulfite sequencing, we describe DNA methylation patterns in three different maturation stages of human oocytes. We found that while broad-scale patterns of CpG methylation have been largely established by the immature germinal vesicle stage, localized changes continue into later development. Non-CpG methylation, on the other hand, undergoes a large-scale, generalized remodeling through the final stage of maturation, with the net overall result being the accumulation of methylation as oocytes mature. The role of the genome-wide, non-CpG methylation remodeling in the final stage of oocyte maturation deserves further investigation.

Genome instability: a conserved mechanism of ageing?

DNA is the carrier of genetic information and the primary template from which all cellular information is ultimately derived. Changes in the DNA information content through mutation generate diversity for evolution through natural selection but are also a source of deleterious effects. It has since long been hypothesized that mutation accumulation in somatic cells of multicellular organisms could causally contribute to age-related cellular degeneration and death. Assays to detect different types of mutations, from base substitutions to large chromosomal aberrations, have been developed and show unequivocally that mutations accumulate in different tissues and cell types of ageing humans and animals. More recently, next-generation sequencing-based methods have been developed to accurately determine the complete landscape of base substitution mutations in single cells. The first results show that the somatic mutation rate is much higher than the germline mutation rate and that base substitution loads in somatic cells are high enough to potentially affect cellular function.

Development of a method to implement whole-genome bisulfite sequencing of cfDNA from cancer patients and a mouse tumor model

The goal of this study was to develop a method for whole genome cell-free DNA (cfDNA) methylation analysis in humans and mice with the ultimate goal to facilitate the identification of tumor derived DNA methylation changes in the blood. Plasma or serum from patients with pancreatic neuroendocrine tumors or lung cancer, and plasma from a murine model of pancreatic adenocarcinoma was used to develop a protocol for cfDNA isolation, library preparation and whole-genome bisulfite sequencing of ultra low quantities of cfDNA, including tumor-specific DNA. The protocol developed produced high quality libraries consistently generating a conversion rate >98% that will be applicable for the analysis of human and mouse plasma or serum to detect tumor-derived changes in DNA methylation.

A high-fidelity method for genomic sequencing of single somatic cells reveals a very high mutational burden.

Postzygotic mutations in somatic cells lead to genome mosaicism and can be the cause of cancer, possibly other human diseases and aging. Somatic mutations are difficult to detect in bulk tissue samples. Here, we review the available assays for measuring somatic mutations, with a focus on recent single-cell, whole genome sequencing methods. Impact statement Somatic mutations cause cancer, possibly other diseases and aging. Yet, very little is known about the frequency of such mutations in vivo, their distribution across the genome, and their possible functional consequences other than cancer. Even in cancer, we do not know the heterogeneity of mutations within a tumor and if seemingly normal cells in its surroundings already have elevated mutation frequencies. Here, we review a new, whole genome amplification system that allows accurate quantification and characterization of single-cell mutational landscapes in human cells and tissues in relation to disease.

Intratissue DNA Methylation Heterogeneity in Aging

Abstract DNA methylation is a critical epigenetic marker involved in development, differentiation, and cell fate diversity. Here we discuss the possible role of adaptive and stochastic changes in DNA methylation in aging. We describe recent progress in studying stochastic changes in DNA methylation, most notably alterations at the level of the single cell. We show that fidelity of individual CpG sites is several orders of magnitude lower than the fidelity of DNA sequence integrity. At this high level of instability, age-related methylation changes could well be a cause of the gradual loss of specific cell fate or differentiation status and, therefore contribute to loss of function and increased disease risk at old age. However, the current lack of a complete understanding of the relationship between DNA methylation patterns and gene expression essentially constrains definite conclusions about the impact of DNA methylation changes on the aging process.

Global, integrated analysis of methylomes and transcriptomes from laser capture microdissected bronchial and alveolar cells in human lung

ABSTRACT Gene regulatory analysis of highly diverse human tissues in vivo is essentially constrained by the challenge of performing genome-wide, integrated epigenetic and transcriptomic analysis in small selected groups of specific cell types. Here we performed genome-wide bisulfite sequencing and RNA-seq from the same small groups of bronchial and alveolar cells isolated by laser capture microdissection from flash-frozen lung tissue of 12 donors and their peripheral blood T cells. Methylation and transcriptome patterns differed between alveolar and bronchial cells, while each of these epithelia showed more differences from mesodermally-derived T cells. Differentially methylated regions (DMRs) between alveolar and bronchial cells tended to locate at regulatory regions affecting promoters of 4,350 genes. A large number of pathways enriched for these DMRs including GTPase signal transduction, cell death, and skeletal muscle. Similar patterns of transcriptome differences were observed: 4,108 differentially expressed genes (DEGs) enriched in GTPase signal transduction, inflammation, cilium assembly, and others. Prioritizing using DMR-DEG regulatory network, we highlighted genes, e.g., ETS1, PPARG, and RXRG, at prominent alveolar vs. bronchial cell discriminant nodes. Our results show that multi-omic analysis of small, highly specific cells is feasible and yields unique physiologic loci distinguishing human lung cell types in situ.

Corrigendum: Accurate identification of single-nucleotide variants in whole-genome-amplified single cells

This corrects the article DOI: 10.1038/nmeth.4227