Variation of Human Neural Stem Cells Generating Organizer States In Vitro before Committing to Cortical Excitatory or Inhibitory Neuronal Fates.

Better understanding of the progression of neural stem cells (NSCs) in the developing cerebral cortex is important for modeling neurogenesis and defining the pathogenesis of neuropsychiatric disorders. Here, we use RNA sequencing, cell imaging, and lineage tracing of mouse and human in vitro NSCs and monkey brain sections to model the generation of cortical neuronal fates. We show that conserved signaling mechanisms regulate the acute transition from proliferative NSCs to committed glutamatergic excitatory neurons. As human telencephalic NSCs develop from pluripotency in vitro, they transition through organizer states that spatially pattern the cortex before generating glutamatergic precursor fates. NSCs derived from multiple human pluripotent lines vary in these early patterning states, leading differentially to dorsal or ventral telencephalic fates. This work furthers systematic analyses of the earliest patterning events that generate the major neuronal trajectories of the human telencephalon.

Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs.

Human induced pluripotent stem cells (hiPSCs) are a powerful model of neural differentiation and maturation. We present a hiPSC transcriptomics resource on corticogenesis from 5 iPSC donor and 13 subclonal lines across 9 time points over 5 broad conditions: self-renewal, early neuronal differentiation, neural precursor cells (NPCs), assembled rosettes, and differentiated neuronal cells. We identify widespread changes in the expression of both individual features and global patterns of transcription. We next demonstrate that co-culturing human NPCs with rodent astrocytes results in mutually synergistic maturation, and that cell type-specific expression data can be extracted using only sequencing read alignments without cell sorting. We lastly adapt a previously generated RNA deconvolution approach to single-cell expression data to estimate the relative neuronal maturity of iPSC-derived neuronal cultures and human brain tissue. Using many public datasets, we demonstrate neuronal cultures are maturationally heterogeneous but contain subsets of neurons more mature than previously observed.

A human-specific AS3MT isoform and BORCS7 are molecular risk factors in the 10q24.32 schizophrenia-associated locus.

Genome-wide association studies (GWASs) have reported many single nucleotide polymorphisms (SNPs) associated with psychiatric disorders, but knowledge is lacking regarding molecular mechanisms. Here we show that risk alleles spanning multiple genes across the 10q24.32 schizophrenia-related locus are associated in the human brain selectively with an increase in the expression of both BLOC-1 related complex subunit 7 (BORCS7) and a previously uncharacterized, human-specific arsenite methyltransferase (AS3MT) isoform (AS3MT(d2d3)), which lacks arsenite methyltransferase activity and is more abundant in individuals with schizophrenia than in controls. Conditional-expression analysis suggests that BORCS7 and AS3MT(d2d3) signals are largely independent. GWAS risk SNPs across this region are linked with a variable number tandem repeat (VNTR) polymorphism in the first exon of AS3MT that is associated with the expression of AS3MT(d2d3) in samples from both Caucasians and African Americans. The VNTR genotype predicts promoter activity in luciferase assays, as well as DNA methylation within the AS3MT gene. Both AS3MT(d2d3) and BORCS7 are expressed in adult human neurons and astrocytes, and they are upregulated during human stem cell differentiation toward neuronal fates. Our results provide a molecular explanation for the prominent 10q24.32 locus association, including a novel and evolutionarily recent protein that is involved in early brain development and confers risk for psychiatric illness.

Strong Components of Epigenetic Memory in Cultured Human Fibroblasts Related to Site of Origin and Donor Age.

Differentiating pluripotent cells from fibroblast progenitors is a potentially transformative tool in personalized medicine. We previously identified relatively greater success culturing dura-derived fibroblasts than scalp-derived fibroblasts from postmortem tissue. We hypothesized that these differences in culture success were related to epigenetic differences between the cultured fibroblasts by sampling location, and therefore generated genome-wide DNA methylation and transcriptome data on 11 intrinsically matched pairs of dural and scalp fibroblasts from donors across the lifespan (infant to 85 years). While these cultured fibroblasts were several generations removed from the primary tissue and morphologically indistinguishable, we found widespread epigenetic differences by sampling location at the single CpG (N = 101,989), region (N = 697), "block" (N = 243), and global spatial scales suggesting a strong epigenetic memory of original fibroblast location. Furthermore, many of these epigenetic differences manifested in the transcriptome, particularly at the region-level. We further identified 7,265 CpGs and 11 regions showing significant epigenetic memory related to the age of the donor, as well as an overall increased epigenetic variability, preferentially in scalp-derived fibroblasts-83% of loci were more variable in scalp, hypothesized to result from cumulative exposure to environmental stimuli in the primary tissue. By integrating publicly available DNA methylation datasets on individual cell populations in blood and brain, we identified significantly increased inter-individual variability in our scalp- and other skin-derived fibroblasts on a similar scale as epigenetic differences between different lineages of blood cells. Lastly, these epigenetic differences did not appear to be driven by somatic mutation--while we identified 64 probable de-novo variants across the 11 subjects, there was no association between mutation burden and age of the donor (p = 0.71). These results depict a strong component of epigenetic memory in cell culture from primary tissue, even after several generations of daughter cells, related to cell state and donor age.

Practical impacts of genomic data "cleaning" on biological discovery using surrogate variable analysis.

BACKGROUND: Genomic data production is at its highest level and continues to increase, making available novel primary data and existing public data to researchers for exploration. Here we explore the consequences of "batch" correction for biological discovery in two publicly available expression datasets. We consider this to include the estimation of and adjustment for wide-spread systematic heterogeneity in genomic measurements that is unrelated to the effects under study, whether it be technical or biological in nature. METHODS: We present three illustrative data analyses using surrogate variable analysis (SVA) and describe how to perform artifact discovery in light of natural heterogeneity within biological groups, secondary biological questions of interest, and non-linear treatment effects in a dataset profiling differentiating pluripotent cells (GSE32923) and another from human brain tissue (GSE30272). RESULTS: Careful specification of biological effects of interest is very important to factor-based approaches like SVA. We demonstrate greatly sharpened global and gene-specific differential expression across treatment groups in stem cell systems. Similarly, we demonstrate how to preserve major non-linear effects of age across the lifespan in the brain dataset. However, the gains in precisely defining known effects of interest come at the cost of much other information in the "cleaned" data, including sex, common copy number effects and sample or cell line-specific molecular behavior. CONCLUSIONS: Our analyses indicate that data "cleaning" can be an important component of high-throughput genomic data analysis when interrogating explicitly defined effects in the context of data affected by robust technical artifacts. However, caution should be exercised to avoid removing biological signal of interest. It is also important to note that open data exploration is not possible after such supervised "cleaning", because effects beyond those stipulated by the researcher may have been removed. With the goal of making these statistical algorithms more powerful and transparent to researchers in the biological sciences, we provide exploratory plots and accompanying R code for identifying and guiding "cleaning" process (https://github.com/andrewejaffe/StemCellSVA). The impact of these methods is significant enough that we have made newly processed data available for the brain data set at http://braincloud.jhmi.edu/plots/ and GSE30272.

The growth factor environment defines distinct pluripotent ground states in novel blastocyst-derived stem cells.

Pluripotent stem cell lines can be derived from blastocyst embryos, which yield embryonic stem cell lines (ES cells), as well as the postimplantation epiblast, which gives rise to epiblast stem cell lines (EpiSCs). Remarkably, ES cells and EpiSCs display profound differences in the combination of growth factors that maintain their pluripotent state. Molecular and functional differences between these two stem cell types demonstrate that the tissue of origin and/or the growth factor milieu may be important determinants of the stem cell identity. We explored how developmental stage of the tissue of origin and culture growth factor conditions affect the stem cell pluripotent state. Our findings indicate that novel stem cell lines, with unique functional and molecular properties, can be generated from murine blastocyst embryos. We demonstrate that the culture growth factor environment and cell-cell interaction play a critical role in defining several unique and stable stem cell ground states.