Heterogeneity within pluripotent stem cell (PSC) populations is indicative of dynamic changes that occur when cells drift between different states. Although the role of metastability in PSCs is unclear, it appears to reflect heterogeneity in cell signaling. Using the Fucci cell-cycle indicator system, we show that elevated expression of developmental regulators in G1 is a major determinant of heterogeneity in human embryonic stem cells. Although signaling pathways remain active throughout the cell cycle, their contribution to heterogeneous gene expression is restricted to G1. Surprisingly, we identify dramatic changes in the levels of global 5-hydroxymethylcytosine, an unanticipated source of epigenetic heterogeneity that is tightly linked to cell-cycle progression and the expression of developmental regulators. When we evaluated gene ex pression in differentiating cells, we found that cell-cycle regulation of developmental regulators was maintained during lineage specification. Cell-cycle regulation of developmentally regulated transcription factors is therefore an inherent feature of the mechanisms underpinning differentiation.
by
Xuyu Qian;
Ha Nam Nguyen;
Mingxi M. Song;
Christopher Hadiono;
Sarah C. Ogden;
Christy Hammack;
Bing Yao;
Gregory Hamersky;
Fadi Jacob;
Chun Zhong;
Ki-Joon Yoon;
William Jeang;
Li Lin;
Yujing Li;
Jai Thakor;
Daniel Berg;
Ce Zhang;
Eunchai Kang;
Michael Chickering;
David Nauen;
Cheng-Ying Ho;
Zhexing Wen;
Kimberly M Christian;
Pei-Yong Shi;
Brady J. Maher;
Hao Wu;
Peng Jin;
Hao Tang;
Hongjun Song;
Guo-li Ming
Cerebral organoids, three-dimensional cultures that model organogenesis, provide a new platform to investigate human brain development. High cost, variability, and tissue heterogeneity limit their broad applications. Here, we developed a miniaturized spinning bioreactor (SpinΩ) to generate forebrain-specific organoids from human iPSCs. These organoids recapitulate key features of human cortical development, including progenitor zone organization, neurogenesis, gene expression, and, notably, a distinct human-specific outer radial glia cell layer. We also developed protocols for midbrain and hypothalamic organoids. Finally, we employed the forebrain organoid platform to model Zika virus (ZIKV) exposure. Quantitative analyses revealed preferential, productive infection of neural progenitors with either African or Asian ZIKV strains. ZIKV infection leads to increased cell death and reduced proliferation, resulting in decreased neuronal cell-layer volume resembling microcephaly. Together, our brain-region-specific organoids and SpinΩ provide an accessible and versatile platform for modeling human brain development and disease and for compound testing, including potential ZIKV antiviral drugs.
DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Recent developments in whole genome bisulfite sequencing (WGBS) technology have enabled genome-wide measurements of DNA methylation at single base pair resolution. Many experiments have been conducted to compare DNA methylation profiles under different biological contexts, with the goal of identifying differentially methylated regions (DMRs). Due to the high cost of WGBS experiments, many studies are still conducted without biological replicates. Methods and tools available for analyzing such data are very limited.We develop a statistical method, DSS-single, for detecting DMRs from WGBS data without replicates. We characterize the count data using a rigorous model that accounts for the spatial correlation of methylation levels, sequence depth and biological variation. We demonstrate that using information from neighboring CG sites, biological variation can be estimated accurately even without replicates. DMR detection is then carried out via a Wald test procedure. Simulations demonstrate that DSS-single has greater sensitivity and accuracy than existing methods, and an analysis of H1 versus IMR90 cell lines suggests that it also yields the most biologically meaningful results. DSS-single is implemented in the Bioconductor package DSS.
Lin28, a well-known RNA-binding protein, regulates diverse cellular properties. All physiological functions of Lin28A characterized so far have been attributed to its repression of let-7 miRNA biogenesis or modulation of mRNA translational efficiency. Here we show that Lin28A directly binds to a consensus DNA sequence in vitro and in mouse embryonic stem cells in vivo. ChIP-seq and RNA-seq reveal enrichment of Lin28A binding around transcription start sites and a positive correlation between its genomic occupancy and expression of many associated genes. Mechanistically, Lin28A recruits 5-methylcytosine-dioxygenase Tet1 to genomic binding sites to orchestrate 5-methylcytosine and 5-hydroxymethylcytosine dynamics. Either Lin28A or Tet1 knockdown leads to dysregulated DNA methylation and expression of common target genes. These results reveal a surprising role for Lin28A in transcriptional regulation via epigenetic DNA modifications and have implications for understanding mechanisms underlying versatile functions of Lin28A in mammalian systems. RNA-binding protein Lin28A shapes the post-transcriptional gene expression by influencing RNA metabolism. Zeng et al. define a DNA binding characteristic of Lin28A, providing evidence for its ability to directly regulate transcription. Lin28A preferentially recognizes transcription initiation loci and recruits DNA demethylase Tet1 to modulate target cytosine modification dynamics and, ultimately, transcription.
The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve â € findability' of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant.
5-hydroxymethylcytosine (5hmC) is enriched in brain and has been recognized as an important DNA modification. However, the roles of 5hmC and its writers, ten-eleven translocation (Tet) proteins, in stress-induced response have yet to be elucidated. Here, we show that chronic restraint stress (CRS) induced depression-like behavior in mice and resulted in a 5hmC reduction in prefrontal cortex (PFC). We found that loss of Tet1 (Tet1 KO) led to resistance to CRS, whereas loss of Tet2 (Tet2 KO) increased the susceptibility of mice to CRS. Genome-wide 5hmC profiling identified the phenotype-associated stress-induced dynamically hydroxymethylated loci (PA-SI-DhMLs), which are strongly enriched with hypoxia-induced factor (HIF) binding motifs. We demonstrated the physical interaction between TET1 and HIF1α induced by CRS and revealed that the increased HIF1α binding under CRS is associated with SI-DhMLs. These results suggest that TET1 could regulate stress-induced response by interacting with HIF1α. The roles of 5-hydroxymethylcytosine (5hmC) and its writers, Tet proteins, in stress-induced response remain unclear. Cheng et al. show that Tet1 knockout mice exhibit resistance, whereas Tet2 knockout mice have increased susceptibility to stress. Biochemical and genome-wide analyses suggest that Tet1 could regulate stress-induced response by interacting with Hif1α.