Nonstochastic reprogramming from a privileged somatic cell state.

Reprogramming somatic cells to induced pluripotency by Yamanaka factors is usually slow and inefficient and is thought to be a stochastic process. We identified a privileged somatic cell state, from which acquisition of pluripotency could occur in a nonstochastic manner. Subsets of murine hematopoietic progenitors are privileged whose progeny cells predominantly adopt the pluripotent fate with activation of endogenous Oct4 locus after four to five divisions in reprogramming conditions. Privileged cells display an ultrafast cell cycle of ∼8 hr. In fibroblasts, a subpopulation cycling at a similar ultrafast speed is observed after 6 days of factor expression and is increased by p53 knockdown. This ultrafast cycling population accounts for >99% of the bulk reprogramming activity in wild-type or p53 knockdown fibroblasts. Our data demonstrate that the stochastic nature of reprogramming can be overcome in a privileged somatic cell state and suggest that cell-cycle acceleration toward a critical threshold is an important bottleneck for reprogramming. PAPERCLIP:

Dysregulation of BRD4 Function Underlies the Functional Abnormalities of MeCP2 Mutant Neurons.

Rett syndrome (RTT), mainly caused by mutations in methyl-CpG binding protein 2 (MeCP2), is one of the most prevalent intellectual disorders without effective therapies. Here, we used 2D and 3D human brain cultures to investigate MeCP2 function. We found that MeCP2 mutations cause severe abnormalities in human interneurons (INs). Surprisingly, treatment with a BET inhibitor, JQ1, rescued the molecular and functional phenotypes of MeCP2 mutant INs. We uncovered that abnormal increases in chromatin binding of BRD4 and enhancer-promoter interactions underlie the abnormal transcription in MeCP2 mutant INs, which were recovered to normal levels by JQ1. We revealed cell-type-specific transcriptome impairment in MeCP2 mutant region-specific human brain organoids that were rescued by JQ1. Finally, JQ1 ameliorated RTT-like phenotypes in mice. These data demonstrate that BRD4 dysregulation is a critical driver for RTT etiology and suggest that targeting BRD4 could be a potential therapeutic opportunity for RTT.

Shortcut barcoding and early pooling for scalable multiplex single-cell reduced-representation CpG methylation sequencing at single nucleotide resolution.

DNA methylation is essential for a wide variety of biological processes, yet the development of a highly efficient and robust technology remains a challenge for routine single-cell analysis. We developed a multiplex scalable single-cell reduced representation bisulfite sequencing (msRRBS) technology. It allows cell-specific barcoded DNA fragments of individual cells to be pooled before bisulfite conversion, free of enzymatic modification or physical capture of the DNA ends, and achieves read mapping rates of 62.5 ± 3.9%, covering 60.0 ± 1.4% of CpG islands and 71.6 ± 1.6% of promoters in K562 cells. Its reproducibility is shown in duplicates of bulk cells with close to perfect correlation (R = 0.97-0.99). At a low 1 Mb of clean reads, msRRBS provides highly consistent coverage of CpG islands and promoters, outperforming the conventional methods with orders of magnitude reduction in cost. Here, we use this method to characterize the distinct methylation patterns and cellular heterogeneity of six cell lines, plus leukemia and hepatocellular carcinoma models. Taking 4 h of hands-on time, msRRBS offers a unique, highly efficient approach for dissecting methylation heterogeneity in a variety of multicellular systems.

Sample-multiplexing approaches for single-cell sequencing.

Single-cell sequencing is widely used in biological and medical studies. However, its application with multiple samples is hindered by inefficient sample processing, high experimental costs, ambiguous identification of true single cells, and technical batch effects. Here, we introduce sample-multiplexing approaches for single-cell sequencing in transcriptomics, epigenomics, genomics, and multiomics. In single-cell transcriptomics, sample multiplexing uses variants of native or artificial features as sample markers, enabling sample pooling and decoding. Such features include: (1) natural genetic variation, (2) nucleotide-barcode anchoring on cellular or nuclear membranes, (3) nucleotide-barcode internalization to the cytoplasm or nucleus, (4) vector-based barcode expression in cells, and (5) nucleotide-barcode incorporation during library construction. Other single-cell omics methods are based on similar concepts, particularly single-cell combinatorial indexing. These methods overcome current challenges, while enabling super-loading of single cells. Finally, selection guidelines are presented that can accelerate technological application.

Integrating Single-Cell Transcriptome and Network Analysis to Characterize the Therapeutic Response of Chronic Myeloid Leukemia.

Chronic myeloid leukemia (CML) is a myeloproliferative disease characterized by a unique BCR-ABL fusion gene. Tyrosine kinase inhibitors (TKIs) were developed to target the BCR-ABL oncoprotein, inhibiting its abnormal kinase activity. TKI treatments have significantly improved CML patient outcomes. However, the patients can develop drug resistance and relapse after therapy discontinues largely due to intratumor heterogeneity. It is critical to understand the differences in therapeutic responses among subpopulations of cells. Single-cell RNA sequencing measures the transcriptome of individual cells, allowing us to differentiate and analyze individual cell populations. Here, we integrated a single-cell RNA sequencing profile of CML stem cells and network analysis to decipher the mechanisms of distinct TKI responses. Compared to normal hematopoietic stem cells, a set of genes that were concordantly differentially expressed in various types of stem cells of CML patients was revealed. Further transcription regulatory network analysis found that most of these genes were directly controlled by one or more transcript factors and the genes have more regulators in the cells of the patients who responded to the treatment. The molecular markers including a known drug-resistance gene and novel gene signatures for treatment response were also identified. Moreover, we combined protein-protein interaction network construction with a cancer drug database and uncovered the drugs that target the marker genes directly or indirectly via the protein interactions. The gene signatures and their interacted proteins identified by this work can be used for treatment response prediction and lead to new strategies for drug resistance monitoring and prevention. Our single-cell-based findings offered novel insights into the mechanisms underlying the therapeutic response of CML.

One thousand somatic SNVs per skin fibroblast cell set baseline of mosaic mutational load with patterns that suggest proliferative origin.

Few studies have been conducted to understand post-zygotic accumulation of mutations in cells of the healthy human body. We reprogrammed 32 skin fibroblast cells from families of donors into human induced pluripotent stem cell (hiPSC) lines. The clonal nature of hiPSC lines allows a high-resolution analysis of the genomes of the founder fibroblast cells without being confounded by the artifacts of single-cell whole-genome amplification. We estimate that on average a fibroblast cell in children has 1035 mostly benign mosaic SNVs. On average, 235 SNVs could be directly confirmed in the original fibroblast population by ultradeep sequencing, down to an allele frequency (AF) of 0.1%. More sensitive droplet digital PCR experiments confirmed more SNVs as mosaic with AF as low as 0.01%, suggesting that 1035 mosaic SNVs per fibroblast cell is the true average. Similar analyses in adults revealed no significant increase in the number of SNVs per cell, suggesting that a major fraction of mosaic SNVs in fibroblasts arises during development. Mosaic SNVs were distributed uniformly across the genome and were enriched in a mutational signature previously observed in cancers and in de novo variants and which, we hypothesize, is a hallmark of normal cell proliferation. Finally, AF distribution of mosaic SNVs had distinct narrow peaks, which could be a characteristic of clonal cell selection, clonal expansion, or both. These findings reveal a large degree of somatic mosaicism in healthy human tissues, link de novo and cancer mutations to somatic mosaicism, and couple somatic mosaicism with cell proliferation.

Ritornello: high fidelity control-free chromatin immunoprecipitation peak calling.

With the advent of next generation high-throughput DNA sequencing technologies, omics experiments have become the mainstay for studying diverse biological effects on a genome wide scale. Chromatin immunoprecipitation (ChIP-seq) is the omics technique that enables genome wide localization of transcription factor (TF) binding or epigenetic modification events. Since the inception of ChIP-seq in 2007, many methods have been developed to infer ChIP-target binding loci from the resultant reads after mapping them to a reference genome. However, interpreting these data has proven challenging, and as such these algorithms have several shortcomings, including susceptibility to false positives due to artifactual peaks, poor localization of binding sites and the requirement for a total DNA input control which increases the cost of performing these experiments. We present Ritornello, a new approach for finding TF-binding sites in ChIP-seq, with roots in digital signal processing that addresses all of these problems. We show that Ritornello generally performs equally or better than the peak callers tested and recommended by the ENCODE consortium, but in contrast, Ritornello does not require a matched total DNA input control to avoid false positives, effectively decreasing the sequencing cost to perform ChIP-seq. Ritornello is freely available at https://github.com/KlugerLab/Ritornello.

Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells.

Conventional DNA bisulfite sequencing has been extended to single cell level, but the coverage consistency is insufficient for parallel comparison. Here we report a novel method for genome-wide CpG island (CGI) methylation sequencing for single cells (scCGI-seq), combining methylation-sensitive restriction enzyme digestion and multiple displacement amplification for selective detection of methylated CGIs. We applied this method to analyzing single cells from two types of hematopoietic cells, K562 and GM12878 and small populations of fibroblasts and induced pluripotent stem cells. The method detected 21 798 CGIs (76% of all CGIs) per cell, and the number of CGIs consistently detected from all 16 profiled single cells was 20 864 (72.7%), with 12 961 promoters covered. This coverage represents a substantial improvement over results obtained using single cell reduced representation bisulfite sequencing, with a 66-fold increase in the fraction of consistently profiled CGIs across individual cells. Single cells of the same type were more similar to each other than to other types, but also displayed epigenetic heterogeneity. The method was further validated by comparing the CpG methylation pattern, methylation profile of CGIs/promoters and repeat regions and 41 classes of known regulatory markers to the ENCODE data. Although not every minor methylation differences between cells are detectable, scCGI-seq provides a solid tool for unsupervised stratification of a heterogeneous cell population.

Single cell transcriptomics reveals unanticipated features of early hematopoietic precursors.

Molecular changes underlying stem cell differentiation are of fundamental interest. scRNA-seq on murine hematopoietic stem cells (HSC) and their progeny MPP1 separated the cells into 3 main clusters with distinct features: active, quiescent, and an un-characterized cluster. Induction of anemia resulted in mobilization of the quiescent to the active cluster and of the early to later stage of cell cycle, with marked increase in expression of certain transcription factors (TFs) while maintaining expression of interferon response genes. Cells with surface markers of long term HSC increased the expression of a group of TFs expressed highly in normal cycling MPP1 cells. However, at least Id1 and Hes1 were significantly activated in both HSC and MPP1 cells in anemic mice. Lineage-specific genes were differently expressed between cells, and correlated with the cell cycle stages with a specific augmentation of erythroid related genes in the G2/M phase. Most lineage specific TFs were stochastically expressed in the early precursor cells, but a few, such as Klf1, were detected only at very low levels in few precursor cells. The activation of these factors may correlate with stages of differentiation. This study reveals effects of cell cycle progression on the expression of lineage specific genes in precursor cells, and suggests that hematopoietic stress changes the balance of renewal and differentiation in these homeostatic cells.

Dynamic changes in replication timing and gene expression during lineage specification of human pluripotent stem cells.

Duplication of the genome in mammalian cells occurs in a defined temporal order referred to as its replication-timing (RT) program. RT changes dynamically during development, regulated in units of 400-800 kb referred to as replication domains (RDs). Changes in RT are generally coordinated with transcriptional competence and changes in subnuclear position. We generated genome-wide RT profiles for 26 distinct human cell types, including embryonic stem cell (hESC)-derived, primary cells and established cell lines representing intermediate stages of endoderm, mesoderm, ectoderm, and neural crest (NC) development. We identified clusters of RDs that replicate at unique times in each stage (RT signatures) and confirmed global consolidation of the genome into larger synchronously replicating segments during differentiation. Surprisingly, transcriptome data revealed that the well-accepted correlation between early replication and transcriptional activity was restricted to RT-constitutive genes, whereas two-thirds of the genes that switched RT during differentiation were strongly expressed when late replicating in one or more cell types. Closer inspection revealed that transcription of this class of genes was frequently restricted to the lineage in which the RT switch occurred, but was induced prior to a late-to-early RT switch and/or down-regulated after an early-to-late RT switch. Analysis of transcriptional regulatory networks showed that this class of genes contains strong regulators of genes that were only expressed when early replicating. These results provide intriguing new insight into the complex relationship between transcription and RT regulation during human development.

Somatic copy number mosaicism in human skin revealed by induced pluripotent stem cells.

Reprogramming somatic cells into induced pluripotent stem cells (iPSCs) has been suspected of causing de novo copy number variation. To explore this issue, here we perform a whole-genome and transcriptome analysis of 20 human iPSC lines derived from the primary skin fibroblasts of seven individuals using next-generation sequencing. We find that, on average, an iPSC line manifests two copy number variants (CNVs) not apparent in the fibroblasts from which the iPSC was derived. Using PCR and digital droplet PCR, we show that at least 50% of those CNVs are present as low-frequency somatic genomic variants in parental fibroblasts (that is, the fibroblasts from which each corresponding human iPSC line is derived), and are manifested in iPSC lines owing to their clonal origin. Hence, reprogramming does not necessarily lead to de novo CNVs in iPSCs, because most of the line-manifested CNVs reflect somatic mosaicism in the human skin. Moreover, our findings demonstrate that clonal expansion, and iPSC lines in particular, can be used as a discovery tool to reliably detect low-frequency CNVs in the tissue of origin. Overall, we estimate that approximately 30% of the fibroblast cells have somatic CNVs in their genomes, suggesting widespread somatic mosaicism in the human body. Our study paves the way to understanding the fundamental question of the extent to which cells of the human body normally acquire structural alterations in their DNA post-zygotically.

Extended lifespan and reduced adiposity in mice lacking the FAT10 gene.

The HLA-F adjacent transcript 10 (FAT10) is a member of the ubiquitin-like gene family that alters protein function/stability through covalent ligation. Although FAT10 is induced by inflammatory mediators and implicated in immunity, the physiological functions of FAT10 are poorly defined. We report the discovery that FAT10 regulates lifespan through pleiotropic actions on metabolism and inflammation. Median and overall lifespan are increased 20% in FAT10ko mice, coincident with elevated metabolic rate, preferential use of fat as fuel, and dramatically reduced adiposity. This phenotype is associated with metabolic reprogramming of skeletal muscle (i.e., increased AMP kinase activity, ß-oxidation and -uncoupling, and decreased triglyceride content). Moreover, knockout mice have reduced circulating glucose and insulin levels and enhanced insulin sensitivity in metabolic tissues, consistent with elevated IL-10 in skeletal muscle and serum. These observations suggest novel roles of FAT10 in immune metabolic regulation that impact aging and chronic disease.

A high throughput embryonic stem cell screen identifies Oct-2 as a bifunctional regulator of neuronal differentiation.

Neuronal differentiation is a complex process that involves a plethora of regulatory steps. To identify transcription factors that influence neuronal differentiation we developed a high throughput screen using embryonic stem (ES) cells. Seven-hundred human transcription factor clones were stably introduced into mouse ES (mES) cells and screened for their ability to induce neuronal differentiation of mES cells. Twenty-four factors that are capable of inducing neuronal differentiation were identified, including four known effectors of neuronal differentiation, 11 factors with limited evidence of involvement in regulating neuronal differentiation, and nine novel factors. One transcription factor, Oct-2, was studied in detail and found to be a bifunctional regulator: It can either repress or induce neuronal differentiation, depending on the particular isoform. Ectopic expression experiments demonstrate that isoform Oct-2.4 represses neuronal differentiation, whereas Oct-2.2 activates neuron formation. Consistent with a role in neuronal differentiation, Oct-2.2 expression is induced during differentiation, and cells depleted of Oct-2 and its homolog Oct-1 have a reduced capacity to differentiate into neurons. Our results reveal a number of transcription factors potentially important for mammalian neuronal differentiation, and indicate that Oct-2 may serve as a binary switch to repress differentiation in precursor cells and induce neuronal differentiation later during neuronal development.

Transcriptional regulation in pluripotent stem cells by methyl CpG-binding protein 2 (MeCP2).

Rett syndrome (RTT) is one of the most prevalent female mental disorders. De novo mutations in methyl CpG-binding protein 2 (MeCP2) are a major cause of RTT. MeCP2 regulates gene expression as a transcription regulator as well as through long-range chromatin interaction. Because MeCP2 is present on the X chromosome, RTT is manifested in an X-linked dominant manner. Investigation using murine MeCP2 null models and post-mortem human brain tissues has contributed to understanding the molecular and physiological function of MeCP2. In addition, RTT models using human induced pluripotent stem cells derived from RTT patients (RTT-iPSCs) provide novel resources to elucidate the regulatory mechanism of MeCP2. Previously, we obtained clones of female RTT-iPSCs that express either wild-type or mutant MECP2 due to the inactivation of one X chromosome. Reactivation of the X chromosome also allowed us to have RTT-iPSCs that express both wild-type and mutant MECP2. Using these unique pluripotent stem cells, we investigated the regulation of gene expression by MeCP2 in pluripotent stem cells by transcriptome analysis. We found that MeCP2 regulates genes encoding mitochondrial membrane proteins. In addition, loss of function in MeCP2 results in de-repression of genes on the inactive X chromosome. Furthermore, we showed that each mutation in MECP2 affects a partly different set of genes. These studies suggest that fundamental cellular physiology is affected by mutations in MECP2 from early development, and that a therapeutic approach targeting to unique forms of mutant MeCP2 is needed.

Robust measurement of telomere length in single cells.

Measurement of telomere length currently requires a large population of cells, which masks telomere length heterogeneity in single cells, or requires FISH in metaphase arrested cells, posing technical challenges. A practical method for measuring telomere length in single cells has been lacking. We established a simple and robust approach for single-cell telomere length measurement (SCT-pqPCR). We first optimized a multiplex preamplification specific for telomeres and reference genes from individual cells, such that the amplicon provides a consistent ratio (T/R) of telomeres (T) to the reference genes (R) by quantitative PCR (qPCR). The average T/R ratio of multiple single cells corresponded closely to that of a given cell population measured by regular qPCR, and correlated with those of telomere restriction fragments (TRF) and quantitative FISH measurements. Furthermore, SCT-pqPCR detected the telomere length for quiescent cells that are inaccessible by quantitative FISH. The reliability of SCT-pqPCR also was confirmed using sister cells from two cell embryos. Telomere length heterogeneity was identified by SCT-pqPCR among cells of various human and mouse cell types. We found that the T/R values of human fibroblasts at later passages and from old donors were lower and more heterogeneous than those of early passages and from young donors, that cancer cell lines show heterogeneous telomere lengths, that human oocytes and polar bodies have nearly identical telomere lengths, and that the telomere lengths progressively increase from the zygote, two-cell to four-cell embryo. This method will facilitate understanding of telomere heterogeneity and its role in tumorigenesis, aging, and associated diseases.

Two methods for full-length RNA sequencing for low quantities of cells and single cells.

The ability to determine the gene expression pattern in low quantities of cells or single cells is important for resolving a variety of problems in many biological disciplines. A robust description of the expression signature of a single cell requires determination of the full-length sequence of the expressed mRNAs in the cell, yet existing methods have either 3' biased or variable transcript representation. Here, we report our protocols for the amplification and high-throughput sequencing of very small amounts of RNA for sequencing using procedures of either semirandom primed PCR or phi29 DNA polymerase-based DNA amplification, for the cDNA generated with oligo-dT and/or random oligonucleotide primers. Unlike existing methods, these protocols produce relatively uniformly distributed sequences covering the full length of almost all transcripts independent of their sizes, from 1,000 to 10 cells, and even with single cells. Both protocols produced satisfactory detection/coverage of the abundant mRNAs from a single K562 erythroleukemic cell or a single dorsal root ganglion neuron. The phi29-based method produces long products with less noise, uses an isothermal reaction, and is simple to practice. The semirandom primed PCR procedure is more sensitive and reproducible at low transcript levels or with low quantities of cells. These methods provide tools for mRNA sequencing or RNA sequencing when only low quantities of cells, a single cell, or even degraded RNA are available for profiling.

Functional genomic screen of human stem cell differentiation reveals pathways involved in neurodevelopment and neurodegeneration.

Human embryonic stem cells (hESCs) can be induced and differentiated to form a relatively homogeneous population of neuronal precursors in vitro. We have used this system to screen for genes necessary for neural lineage development by using a pooled human short hairpin RNA (shRNA) library screen and massively parallel sequencing. We confirmed known genes and identified several unpredicted genes with interrelated functions that were specifically required for the formation or survival of neuronal progenitor cells without interfering with the self-renewal capacity of undifferentiated hESCs. Among these are several genes that have been implicated in various neurodevelopmental disorders (i.e., brain malformations, mental retardation, and autism). Unexpectedly, a set of genes mutated in late-onset neurodegenerative disorders and with roles in the formation of RNA granules were also found to interfere with neuronal progenitor cell formation, suggesting their functional relevance in early neurogenesis. This study advances the feasibility and utility of using pooled shRNA libraries in combination with next-generation sequencing for a high-throughput, unbiased functional genomic screen. Our approach can also be used with patient-specific human-induced pluripotent stem cell-derived neural models to obtain unparalleled insights into developmental and degenerative processes in neurological or neuropsychiatric disorders with monogenic or complex inheritance.

A highly integrated and complex PPARGC1A transcription factor binding network in HepG2 cells.

PPARGC1A is a transcriptional coactivator that binds to and coactivates a variety of transcription factors (TFs) to regulate the expression of target genes. PPARGC1A plays a pivotal role in regulating energy metabolism and has been implicated in several human diseases, most notably type II diabetes. Previous studies have focused on the interplay between PPARGC1A and individual TFs, but little is known about how PPARGC1A combines with all of its partners across the genome to regulate transcriptional dynamics. In this study, we describe a core PPARGC1A transcriptional regulatory network operating in HepG2 cells treated with forskolin. We first mapped the genome-wide binding sites of PPARGC1A using chromatin-IP followed by high-throughput sequencing (ChIP-seq) and uncovered overrepresented DNA sequence motifs corresponding to known and novel PPARGC1A network partners. We then profiled six of these site-specific TF partners using ChIP-seq and examined their network connectivity and combinatorial binding patterns with PPARGC1A. Our analysis revealed extensive overlap of targets including a novel link between PPARGC1A and HSF1, a TF regulating the conserved heat shock response pathway that is misregulated in diabetes. Importantly, we found that different combinations of TFs bound to distinct functional sets of genes, thereby helping to reveal the combinatorial regulatory code for metabolic and other cellular processes. In addition, the different TFs often bound near the promoters and coding regions of each other's genes suggesting an intricate network of interdependent regulation. Overall, our study provides an important framework for understanding the systems-level control of metabolic gene expression in humans.

Extensive genetic variation in somatic human tissues.

Genetic variation between individuals has been extensively investigated, but differences between tissues within individuals are far less understood. It is commonly assumed that all healthy cells that arise from the same zygote possess the same genomic content, with a few known exceptions in the immune system and germ line. However, a growing body of evidence shows that genomic variation exists between differentiated tissues. We investigated the scope of somatic genomic variation between tissues within humans. Analysis of copy number variation by high-resolution array-comparative genomic hybridization in diverse tissues from six unrelated subjects reveals a significant number of intraindividual genomic changes between tissues. Many (79%) of these events affect genes. Our results have important consequences for understanding normal genetic and phenotypic variation within individuals, and they have significant implications for both the etiology of genetic diseases such as cancer and for immortalized cell lines that might be used in research and therapeutics.

A core erythroid transcriptional network is repressed by a master regulator of myelo-lymphoid differentiation.

Two mechanisms that play important roles in cell fate decisions are control of a "core transcriptional network" and repression of alternative transcriptional programs by antagonizing transcription factors. Whether these two mechanisms operate together is not known. Here we report that GATA-1, SCL, and Klf1 form an erythroid core transcriptional network by co-occupying >300 genes. Importantly, we find that PU.1, a negative regulator of terminal erythroid differentiation, is a highly integrated component of this network. GATA-1, SCL, and Klf1 act to promote, whereas PU.1 represses expression of many of the core network genes. PU.1 also represses the genes encoding GATA-1, SCL, Klf1, and important GATA-1 cofactors. Conversely, in addition to repressing PU.1 expression, GATA-1 also binds to and represses >100 PU.1 myelo-lymphoid gene targets in erythroid progenitors. Mathematical modeling further supports that this dual mechanism of repressing both the opposing upstream activator and its downstream targets provides a synergistic, robust mechanism for lineage specification. Taken together, these results amalgamate two key developmental principles, namely, regulation of a core transcriptional network and repression of an alternative transcriptional program, thereby enhancing our understanding of the mechanisms that establish cellular identity.