Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions.

Summary Organoid techniques provide unique platforms to model brain development and neurological disorders. While several methods for recapitulating corticogenesis have been described, a system modeling human medial ganglionic eminence (MGE) development, a critical ventral brain domain producing cortical interneurons and related lineages, has been lacking until recently. Here, we describe the generation of MGE and cortex-specific organoids from human pluripotent stem cells that recapitulate the development of MGE and cortex domains respectively. Population and single-cell RNA-seq profiling combined with bulk ATAC-seq analyses revealed transcriptional and chromatin accessibility dynamics and lineage relationships during MGE and cortical organoid development. Furthermore, MGE and cortical organoids generated physiologically functional neurons and neuronal networks. Finally, fusing region-specific organoids followed by live-imaging enabled analysis of human interneuron migration and integration. Together, our study provides a platform for generating domain-specific brain organoids, for modeling human interneuron migration, and offers deeper insight into molecular dynamics during human brain development.

Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

No abstract

The rarity and inaccessibility of the earliest primordial germ cells (PGCs) in the mouse embryo thwarts efforts to investigate molecular mechanisms of germ cell specification. Stella marks the minute founder population of the germ lineage1,2. Here we differentiate mouse embryonic stem cells (ESCs) carrying a Stella transgenic reporter into putative PGCs in vitro. The Stella+ cells possess a transcriptional profile similar to embryo-derived PGCs, and like their counterparts in vivo, lose imprints in a time-dependent manner. Using inhibitory RNAs to screen candidate genes for effects on the development of Stella+ cells in vitro, we discovered that Lin28, a negative regulator of let-7 microRNA processing3-6, is essential for proper PGC development. We further show that Blimp1, a let-7 target and a master regulator of PGC specification7-9, can rescue the effect of Lin28-deficiency during PGC development, thereby establishing a mechanism of action for Lin28 during PGC specification. Over-expression of Lin28 promotes formation of Stella+ cells in vitro and PGCs in chimeric embryos, and is associated with human germ cell tumours. The differentiation of putative PGCs from ESCs in vitro recapitulates the early stages of gamete development in vivo, and provides an accessible system for discovering novel genes involved in germ cell development and malignancy.

Current DNA methylation assays are limited in the flexibility and efficiency of characterizing a large number of genomic targets. We report a method to specifically capture an arbitrary subset of genomic targets for single-molecule bisulfite sequencing for digital quantification of DNA methylation at single-nucleotide resolution. A set of ~30,000 padlock probes was designed to assess methylation of 66,000 CpG sites within 2,020 CpG islands on human chromosome 12, chromosome 20, and 34 selected regions. To investigate epigenetic differences associated with dedifferentiation, we compared methylation in three human fibroblast lines and eight human pluripotent stem cell lines. Chromosome-wide methylation patterns were similar among all lines studied, but cytosine Correspondence should be addressed to K.Z. (E-mail: kzhang@bioeng.ucsd.edu) or Y.G. (E-mail: ygao@vcu.edu). Accession numbers. All sequence reads and methylation data have been deposited at GEO, with accession number GSE15007.Note: Supplementary information is available on the Nature Biotechnology website. AUTHOR CONTRIBUTIONS NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript methylation was slightly more prevalent in the pluripotent cells than in the fibroblasts. Induced pluripotent stem (iPS) cells appeared to display more methylation than embryonic stem cells. We found 288 regions methylated differently in fibroblasts and pluripotent cells. This targeted approach should be particularly useful for analyzing DNA methylation in large genomes.DNA methylation is a primary epigenetic mechanism for transcriptional regulation during normal development and goes awry in many diseases, including cancers. Genome-scale patterns of DNA methylation have been characterized by microarray hybridization or bisulfite sequencing 1 . Microarray methods have enabled methylation to be quantified at 1,536 discrete CpG sites in the human genome with the GoldenGate assay 2,3 . They have also been coupled with methylated DNA immunoprecipitation or methyl-specific restriction enzyme digestion to quantify relative levels of DNA methylation, although the read-outs of such approaches are only averages of the levels of methylation of multiple adjacent CpG sites [4][5][6] .More recently, next-generation sequencing has enabled absolute quantification of DNA methylation with single-nucleotide resolution on a larger scale than previously possible. These efforts include bisulfite sequencing of PCR amplicons from human tissues and cancer cell lines 7-9 , single-molecule sequencing of reduced representation libraries from mouse embryonic stem cells 10,11 and whole-genome bisulfite sequencing of Arabidopsis thaliana 12,13 . Although whole-genome bisulfite sequencing of a mammalian genome should be technically feasible, the large genome sizes pose a considerable challenge 14 .Selection or enrichment of genomic targets prior to sequencing would substantially reduce sequencing cost. PCR-based target selection is highly specific, but cannot be multiplexed easily for...

Stem cells are defined as self-renewing cell populations that can differentiate into multiple distinct cell types. However, hundreds of different human cell lines from embryonic, fetal, and adult sources have been called stem cells, even though they range from pluripotent cells, typified by embryonic stem cells, which are capable of virtually unlimited proliferation and differentiation, to adult stem cell lines, which can generate a far more limited repertory of differentiated cell types. The rapid increase in reports of new sources of stem cells and their anticipated value to regenerative medicine 1, 2 have highlighted the need for a general, reproducible method for classification of these To sort the cell types we used an unsupervised machine learning approach to cluster transcriptional profiles of the cell preparations into stable distinct groups. Sparse nonnegative matrix factorization (sNMF) was adjusted for this task by implementing a bootstrapping algorithm to find the most stable groupings (see also Supplementary Discussion 1). 4, 5 The stability of the clustering 9 indicated that the dataset most likely contained about twelve different types of samples ( . The HANSE cell group consisted of transcriptional profiles that were derived from neurosurgical specimens following published protocols for multipotent neural progenitor derivation and propagation. 10, 11 These cells expressed markers that are commonly used to identify neural stem cells 12 (see Supplementary Figure 4), but the clustering clearly separated them from the other samples that had been derived from postmortem brains of prematurely born infants (see Figure 2). 10,11 We used a combination of analysis tools to explore the basis of the unsupervised classification of the samples in the core dataset. Gene Set Analysis 3 (GSA) is a means to identify the underlying themes in transcriptional data in terms of their biological relevance.GSA uses lists of genes 5 that are related in some way; the common criterion is that the relationships among the genes in the lists are supported by empirical evidence. 20 GSA highlighted numerous significant differences among the computationally defined categories.(See Supplementary Figure 2, Supplementary Table 11 and Supplementary Online Materials).While GSA is valuable for discovering specific differences among sample groups, it is limited to curated gene lists and cannot be used to discover new regulatory networks. The MATISSE algorithm 6 (http://acgt.cs.tau.ac.il/matisse) takes predefined protein-protein interactions (e.g. from yeast-two-hybrid screens) and seeks connected subnetworks that manifest high similarity in sample subsets. The modified version used in this analysis is capable of extracting subnetworks that are co-expressed in many samples but also significantly up-or down-regulated in a specific sample cluster. Since the PSC preparations were consistently clustered together we used MATISSE to look for distinctive molecular networks that might be associated with the unique PSC qualities of pluri...

The International Stem Cell Initiative analyzed 125 human embryonic stem (ES) cell lines and 11 induced pluripotent stem (iPS) cell lines, from 38 laboratories worldwide, for genetic changes occurring during culture. Most lines were analyzed at an early and late passage. Single-nucleotide polymorphism (SNP) analysis revealed that they included representatives of most major ethnic groups. Most lines remained karyotypically normal, but there was a progressive tendency to acquire changes on prolonged culture, commonly affecting chromosomes 1, 12, 17 and 20. DNA methylation patterns changed haphazardly with no link to time in culture. Structural variants, determined from the SNP arrays, also appeared sporadically. No common variants related to culture were observed on chromosomes 1, 12 and 17, but a minimal amplicon in chromosome 20q11.21, including three genes, ID1, BCL2L1 and HM13, expressed in human ES cells, occurred in >20% of the lines. Of these genes, BCL2L1 is a strong candidate for driving culture adaptation of ES cells.